(Dfmo) & Etoposide Loaded Nanocarriers for the Tr

DEVELOPMENT AND EVALUATION OF POLYMERIC HYBRID α- DIFLUOROMETHYLORNITHINE (DFMO) & ETOPOSIDE LOADED NANOCARRIERS FOR THE TREATMENT OF NEUROBLASTOMA

A DISSERTATION SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI’I AT HILO IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

DOCTOR OF PHILOSOPHY IN PHARMACEUTICAL SCIENCES AUGUST 2016

By MICAH DAVID KEALAKA’I GLASGOW

Dissertation Committee: Mahavir B. Chougule, Primary Adviser Kenneth R. Morris, Co-Adviser Dana-Lynn Koomoa-Lange Mazen Hamad Cheryl Ramos Ghee Tan

Keywords: Neuroblastoma, DFMO, Etoposide, Combination chemotherapy, Drug delivery, Multifunctional nanocarriers

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DEDICATION I’d like to dedicate my dissertation to my family, who have always supported me through all my endeavors. My mother and father, Lillian & James Glasgow, my sisters, Renae & Melissa, my brothers, Shawn & Ikaika and my nephews, Nakana & Kaulana Glasgow. They have always been my foundation in life and the reason I continue to excel in any task I undertake. My degree wouldn’t have been possible without their undying sacrifice and love throughout the years.

I’d also like to dedicate my work to my Aunty Connie Law and Aunty Alvernia Inamine who lost their battle with cancer but continue to watch over me from above. I will always remember their words of encouragement and generous hearts forever [xoxo].

Love you all!

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ACKNOWLEDGEMENTS I’d like to thank the numerous people I had the great opportunity to work with during my Ph.D. tenure. A special thanks to my colleagues and lab members; Mrs. Marites Calibuso-Salazar, Mr. Nishant Gandhi, Dr. Susanne Youngren-Ortiz, Dr. Rongbing Yang, and Dr. Laura Espana Serrano for their knowledge and input throughout my dissertation.

An enourmous amount of gratitude goes to my co-adviser, Dr. Kenneth Morris, for encouraging me to apply to the Ph.D. in Pharmaceutical Sciences program at the Daniel K. Inouye College of Pharmacy (DKICP), UHH. Dr. Morris unknowingly is also my role-model and I feel very fortunate to have had the opportunity to work alongside him at DKICP. Many thanks also to Dr. Dana-Lynn Koomoa-Lange for sacrificing her time and energy to mentor me throughout my project. Also, her heavy involvement with the community allowed me to share the knowledge I’ve obtained to the next generation of scientists. Herself, along with Dr. Morris, have also financially supported me throughout my Ph.D. tenure and I am forever grateful for their generosity and kindness.

A special thanks to my primary adviser, Dr. Mahavir Chougule, whom I’m sure wanted to strangle me at times but kept on believing I could get my project done. He allowed me to work on a project I had no knowledge of and therefore it allowed me to grow as a researcher. We may have gotten into several, actually many, disagreements but in the end I am truly grateful for his time and dedication to seeing my project through, thank you very much. Thank you to my remaining committee members; Dr. Mazen Hamad, whose equipment I always managed to break, and Dr. Cheryl Ramos whose radiant smile will brighten anyone’s day. To all of my committee members, please enjoy the honor of reading my 300+ page dissertation, you’re very welcome.

I’d like to thank the numerous scholarship and grant agencies for providing financial support during my Ph.D. tenure. I’d first like to acknowledge the National Science Foundation – Engineering Resource Center on Structured Organic Particulate Solids (NSF-ERC-SOP) for stipend support and support of minorities in the higher education field. Thank you to these numerous scholarship agencies for their support in obtaining my doctorate in the pharmaceutical sciences degree; Kamehameha Schools Na Ho’okama a Pauahi Scholarship, Hawai’i Community Foundation, Dr. Hans and Clara Zimmerman Fund, Ke Ola Mau Scholarship, Rosemary & Nellie Ebrie Fund, Shelley M Williams RPh Scholarship Fund, Walter Francis and Mary Dillingham Frear Scholarship, ALEX travel award, University of Hawaii at Hilo Alumni Scholarship, Na Ho’okahua Award (Department of Education), George & Lucille Cushnie Scholarship Fund, Liko A’e Native Hawaiian Leadership Scholarship, University of Hawai’i at Hilo 2014 Community

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Spirit Award, Kukui Malama Scholarship Award. I would also like to thank the University of Hawai’i at Hilo - Daniel K. Inouye College of Pharmacy for providing a tuition waiver and a year of stipend support.

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ABSTRACT Neuroblastoma (NB) is the most common extra-cranial solid cancer in childhood and infancy with patients having an average age of 17 months. Most are diagnosed with advanced stage NB when tumor progression is aggressive, making treatment of NB even more difficult. Up to 45% of patients are in the high-risk category with MYCN gene amplification being observed.

The FDA-approved drug difluoromethylornithine (DFMO) exhibits anticancer activity against MYCN- amplified NB cells. DFMO is a suicide inhibitor of ornithine decarboxylase (ODC), a rate-limiting enzyme in the biosynthesis of polyamines. ODC gene expression is directly activated by MYCN suggesting that MYCN amplification is connected to high ODC expression. ODC expression produces high polyamine levels that contribute to the malignant phenotype and maintenance of NB tumorgenesis. This MYCN-ODC connection suggests that ODC may be a suitable new target for the treatment of NB with the administration DFMO.

Etoposide, a topoisomerase inhibitor is often used in front-line therapy in the treatment of NB. The use of DFMO/Etoposide in vivo is currently limited due to the short half-lives (fast elimination/clearance) of both drugs which may explain why antitumor in vivo were not synergistic as observed in vitro. iRGD peptide-conjugated PEGylated polymeric hybrid nanocarriers loaded with synergistically acting DFMO and Etoposide drugs (iRGD-PEG-HNC-D-E) were characterized at 81±7nm in size, +12±2.5mV in zeta potential with a mean polydispersity index 0f 0.354±0.03. The developed nanocarriers had a 10 and 6-fold decrease in initial drug concentrations, DFMO and Etoposide respectively, with similar efficacy as compared to free drugs alone against various NB cell-lines over a 72h period. The current formulation shows stability suspended in phosphate buffer saline (PBS) 7.4 over 6 days. iRGD-PEG-HNC-D-E formulations can be modified (polymer: polymer ratio) to alter drug release profiles with the developed formula having a 90% release of both drugs after 72h in PBS 5.4 and 7.4 containing glutathione.

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TABLE OF CONTENTS DEDICATION ACKNOWLEDGEMENTS ABSTRACT LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS AND SYMBOLS FLOW DIAGRAM OF PROPOSED THESIS WORK 1. INTRODUCTION 1.1 Cancer and Nanotechnologies 1.2 Brief overview of Neuroblastoma 1.3 Cancer Therapy 1.4 Mechanisms of drug resistance 1.5 Combination chemotherapies 1.6 Small molecule drugs of interest: α-Difluoromethylornithine (DFMO) and Etoposide 1.7 Synergistic effects of DFMO and Etoposide in vitro and in vivo 1.8 Combination chemotherapy nanocarriers against multi-drug resistant (MDR) cancer 1.9 Overview of iRGD Peptide as a potential Tumor Target for Neuroblastoma treatment 2. HYPOTHESIS, OBJECTIVES, AND RATIONALE 3. LITERATURE REVIEW 3.1 CURRENT NANOCARRIERS AS MULTIFUNCTIONAL DRUG DELIVERY SYSTEMS 3.2 Liposomes 3.3 Polymeric micelles 3.4 Poly-(lactic-co-glycolic acid)-based nanocarriers 3.5 Mesoporous silica based nanocarriers (MSNPs) 3.6 Polymer-drug nano-conjugates 3.7 Dendrimers based nanocarriers 3.8 Miscellaneous multifunctional nanocarriers 4. CURRENT PROGNOSIS AND THERAPEUTIC TREATMENTS FOR NEUROBLASTOMA 4.1 INTRODUCTION 4.2 DIAGNOSTIC STUDIES AND TESTS 4.3 PROGNOSTIC FACTORS 4.3.1 Histology 4.3.2 MYCN Oncogene

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4.3.3 Tumor Cell Ploidy 4.3.4 Chromosome Abnormalities 4.3.5 Neurotrophins and Neurotrophin Receptors 4.4 RISK GROUP STRATIFICATION SYSTEM 4.5 RISK-BASED TREATMENT 4.5.1 Low-Risk Disease 4.5.2 Intermediate-Risk Disease 4.5.3 High-Risk Disease 4.6 Treatment of Spinal Cord Compression 4.7 Treatment of Opsoclonus/Myoclonus Syndrome 4.8 NEW THERAPEUTIC AGENTS 4.8.1 Cytotoxic Agents 4.8.2 Retinoids 4.8.3 Immunotherapy 4.8.4 Radioiodinated mIBG 4.8.5 Antiangiogenic Therapy 4.8.6 Late Effects of Therapy 4.9 Summary 5. CURRENT NANOCARRIER DELIVERY SYSTEMS FOR NEUROBLASTOMA 6. TARGETED MULTIFUNCTIONAL NANOCARRIERS IN COMBINATION CHEMOTHERAPEUTICS 6.1 Antibodies and antibody fragment based targeted nanocarriers 6.2 Peptide-based targeted nanocarriers 6.3 Small molecule based targeted nanocarriers 6.4 Aptamer-based targeted nanocarriers 6.5 Miscellaneous targeted approaches 7. iRGD PEPTIDE FOR CANCER THERAPY 7.1 Antagonists (Non-Antibody) of αvβ3 7.2 RGD-Targeted Delivery of Therapy 7.2.1 Chemotherapy 7.2.2 Peptides and Proteins 7.2.3 Nucleic Acids 7.2.4 Radionuclides 7.2.5 Theranostics

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7.2.6 iRGD Cyclic Penetrating Peptide 7.3 Summary of RGD Peptide as a Potential Ligand to Target Tumors 8. THERNOSTICS MULTIFUNCTIONAL NANOCARRIERS FOR CHEMOTHERAPY AND IMAGING 9. THERNOSTICS SUMMARY 10. QUANTIFICATION OF α-DIFLUOROMETHYLORNITHINE (DFMO) AND ETOPOSIDE USING HIGH PERFORMANCE LIQUID CHROMATOGRAPHY (HPLC) AND PLATE-READER 10.1.1 Derivatization of DFMO using TNBSA (2, 4, 6-trinitrobenzene sulfonic acid) assay for UV- detection 10.1.2 Quantification of DFMO derivative using Biotek plate-reader 10.1.3 Quantification of DFMO derivative using HPLC 10.1.4 Detection and Quantification of Etoposide using HPLC 10.1.5 Simultaneous Detection and Quantification of DFMO derivative and Etoposide using HPLC 11. IN VITRO CYTOTOXICITY STUDIES OF DFMO AND ETOPOSIDE ALONE 11.1.1 Introduction to MTT and MTS cell proliferation assays 11.1.2 MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide Cell Proliferation Assay

11.1.3 MTS (3-(4, 5-dimethylthiazoly-2yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H- tetrazolium) Cell Proliferation Assay 11.2 In vitro Dose-response durves of DFMO and Etoposide drugs alone 11.3 In vitro DFMO and Etoposide drug combination studies 11.4 Determination of Synergistic, Additive or Antagonistic Effect on Neuroblastoma cell-lines 12. CHARACTERIZATION, PREPRATION, AND EVALUATION OF HNC FORMULATIONS 12.1 CHARACTERIZATION METHODS OF HNC FORMULATIONS 12.1.1 Dynamic Light Scattering and Zeta Potential Measurements 12.1.2 Polydispersity Index (PdI) of nanocarrier formulations 12.1.3 Determination of Entrapment Efficiency (%EE) and Loading Efficiency (%LE) 12.1.4 Purification via dialysis, density gradient centrifugation or vivaspin method 12.2 PREPARATION METHODS OF HNC FORMULATIONS 12.2.1 Preparation Methods for HNC formulation 12.2.2 Selection of Excipients 12.2.3 Determination of Variables Affecting HNC formulations (i.e particle size, zeta potential, PdI) 12.2.4 Taguchi Orthogonal Array Design of Experiments (DoE) 12.2.5 Development of bovine serum albumin (BSA) nanocarriers and chitosan (CS) nanocarriers using Taguchi Orthogonal Array Design of Experiments (DoE)

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12.2.6 Phases of HNC formulation (explanation of flow diagram) 12.2.7 Development of Hybrid nanocarriers loaded with DFMO and Etoposide (HNC-D-E) using Taguchi Orthogonal Array Design of Experiments (DoE) 12.2.8 Optimization of HNC-D-E using Taguchi orthogonal array and predicted full factorial DoE 12.2.8.1 Quantification of amine groups present on run order #10 of chitosan coated bovine serum albumin loaded with DFMO and Etoposide (HNC-D-E) using TNBSA colorimetric assay 12.2.9 Quantification of free Polyethylene glycol (PEG) 12.2.10 Preparation of iRGD peptide conjugated PEGylated HNC-D-E (iRGD-PEG-HNC-D-E) 12.2.11 Determination of Surface Bound Peptides per HNC using BCA protein assay 12.2.12 Optimization of iRGD peptides on HNC surface for in vitro internalization 12.3 EVALUATION METHODS OF PEG-HNC-D-E FORMULATIONS 12.3.1 Stability of HNC in biological media and phosphate buffers 12.3.2 In vitro Release Profiles of PEG-HNC-D-E formulations in various phosphate buffers 12.3.3 In vitro Cytotoxicity Studies of various HNC formulations against SK-N-Be(2)c and IMR-32 Neuroblastoma Cell-lines 12.3.4 Cell-Associated Fluorescence (flow cytometry) for Cell Binding Assay studies using iRGD- PEG-HNC-FITC nanocarriers 13. SUMMARY, CLOSING REMARKS, AND FUTURE DIRECTIONS 13.1 Summary 13.2 Closing Remarks 13.3 Future Directions 14. REFERENCES 15. APPENDIX A: PUBLICATIONS 16. Supplemental Data

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LIST OF TABLES Table 4.1 Prognostic factors in neuroblastoma

Table 4.2 Children’s Oncology Group: neuroblastoma risk-group schema Table 7. Non-exhaustive Examples of Recent Preclinical Studies of RGD-Targeted Nanocarriers Delivering Chemotherapeutics. Reprinted with permission from ref. 1. Danhier F, Vroman B, Lecouturier N, et al. Targeting of tumor endothelium by RGD-grafted PLGA-nanoparticles loaded with paclitaxel. J Control Release. 2009;140: 166-173

Table 10. Linearity study of DFMO derivative (TNP-DFMO-TNP) quantified using Biotek plate reader at 345nm. Linearity was found in a range of 10 to 60ug/mL. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP- DFMO-TNP derivative analyzed after 2h.

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Table 10.7 Dionex Ultimate 3000 HPLC Isocratic method for Etoposide elucidation (10-minute total run- time) at 283nm having a retention time of 6.5 minutes.

Table 10.8 Standard curve parameters for Etoposide drug in a range of 13 to 104ug/mL using absorbance area (mAU*min) at 283nm. Linearity was found in a range of 13 to 104ug/mL using absorbance area (mAU*min) and absorbance height (mAU). Linearity range were performed in triplicates. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were shown for both absorbance readings.

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Table 11. Experimental set-up for DFMO and Etoposide drugs alone treating SK-N-Be(2)c cell-lines. Cells seeded at 5 x 103 per well and incubated for 24h prior to drug treatments. Cells incubated with respective drugs alone for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%.

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Table 11.12 Combination Index level and the suggested effect level.

Table 12.1 Combination of desolvating agents (acetone & methanol) and its effects on particle size (nm) and polydispersity index (PdI) using 10% BSA solution (1mL) at 650 RPM (small paddle stirrer), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as

15 | Page mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%.

Table 12.2 Combination of desolvating agents (ethanol & methanol) and its effects on particle size (nm) and polydispersity index (PdI) using 10% BSA solution (1mL) at 650 RPM (small paddle stirrer), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%

Table 12.6 Minitab 16 Taguchi orthogonal array design of experiment 33 (3 level, 3 factor) set-up for the development of bovine serum albumin (BSA) nanocarriers. 3 factors: stir rate (RPM), volume of desolvating agent (methanol) used and stir time (minutes). Each factor has 3 levels; 200, 400, and 600 RPM stir rate factor, 6, 8, and 10mL for desolvating agent factor and 15, 30, and 45-minute stir time factor. These factors were deemed most influential on particle size (PS) and polydispersity index (PdI) based on literature review 2. Desolvating agent (methanol) flow rate set at 1mL/min (continuously, not drop-wise, into solution). 10% w/v BSA used (10mL).

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Table 12.8 Predicted experimental outcomes using Minitab 16 Taguchi orthogonal array design of experiment 33 (3 level, 3 factor) results for the development of bovine serum albumin (BSA) nanocarriers. 3 factors: stir rate (RPM), volume of desolvating agent (methanol) used and stir time (minutes). Each factor has 3 levels; 200, 400, and 600RPM stir rate factor, 6, 8, and 10mL for desolvating agent factor and 15, 30, and 45-minute stir time factor. These factors were deemed most influential on drug loading and entrapment efficiency based on literature review 2. These data are generated in Minitab 16 and are not actual results. The highlighted (yellow) indicates experimental goals (smallest particle size (PS) and smallest polydispersity index (PdI)) generated. These predicted results will be validated with an experimental run.

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Table 12.12 Ionotrophic gelation method between chitosan and tripolyphosphate linker. Data shpws a molar ratio of 1:5.7065 (CS:TPP) yields the smallest particle size, These data will be utilized during hybrid nanocarrier formulations.

Table 12.17 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (BSA-D-E). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. Total volume of starting %BSA solution was 10mL. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments.

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Table 12.18 Results of HPLC analysis of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA-D-E). HPLC analysis conducted to determine entrapment efficiency of BSA-D-E. BSA-D-E were purified using vivaspin method and supernatant analyzed for free drug. Free drug calculated using standard curves (absorbance area) to determine final entrapment efficiency.

Table 12.22 Experimental set-up of taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set- up for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA-D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been added to each run.

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Table 12.23 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D- E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA- D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been added to each run.

Table 12.25 Linearity study of chitosan coated BSA-D-E nanocarriers for the quantification of total amine groups present on HNC surface using TNBSA colorimetric assay in Biotek plate reader at 345nm. Linearity was found in a range of 100 to 500ug/mL with a linear regression value (R2) of 0.995. Varying concentrations of Chitosan (200uL each) treated with 800uL borate buffer 8.5, 250uL TNBSA stock solution (0.025% w/v) and allowed to react for 2h at 37°C. Samples were read in a 96-well plate within 10 minutes of reaction time. Run order #10 were purified via vivaspin method. HNC were re-suspended in DI-H2O and treated with same conditions as chitosan concentrations.

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Table 12.28 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of PEGylated chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (PEG-HNC-D-E). 2 factors: total volume of carboxy-PEG (COOH-PEG, mL, 1mM), and total volume of AMAS-PEG-COOH (mL, 1mg/mL). Each factor has 3 levels; 0.5, 3, and 5mL for total volume of COOH- PEG factor, 0.5, 2.5, 5mL total volume of AMAS-PEG-COOH (mL) factor. Total volume of starting HNC- D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run.

Table 12.29 Results of taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: total volume of carboxy-PEG (COOH-PEG, mL, 1mg/mL), and total volume of AMAS-PEG-COOH (mL, 1mg/mL). Each factor has 3 levels; 0.5, 3, and 5mL for total volume of COOH-PEG factor, 0.5, 2.5, 5mL total volume of AMAS-PEG-COOH (mL) factor. Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run.

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D-E using Barium-Iodine assay (@535nm). Barium-Iodine assay will not distinguish between COOH-PEG and COOH-PEG-AMAS molecules, therefore, total PEG is calculated. Absorbance area were collected from diluted solutions. A dilution factor of 1000 is calculated into Total unreacted PEG data. iRGD peptide will be quantified at 562nm using BCA protein assay.

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Table 12.35b Flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported.

Table 12.35c Normalized flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell- lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N- Be(2)c cells alone.

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Table 12.39 Stability data of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC- D-E) various media: DI-H2O, PBS 7.4, 0.9% NaCl, and 10% w/v FBS. 100uL of final PEG-HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD reported. Coefficient of Variance (CV) calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%.

Table 12.39a In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. Release studies were performed in various media solutions to stimulate cellular microenvironment. Nanocarriers formulations (150uL) were placed in media under sink conditions (15mL media, 37°C, 100 RPM stir) with samples collected at pre-determined time points. Samples were analyzed via HPLC and the absorbance area (mAU*min) were used to calculate total drug released. Percentage total drug calculated from HPLC absorbance area at various time points were plotted and analyzed against free-drug media containing no nanocarriers. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

Table 12.40 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 containing

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10mM glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

Table 12.41 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. b) PBS 5.4 without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

Table 12.42 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. c) PBS 7.4 with 10mM GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

Table 12.43 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. d) PBS 7.4 without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

Table 12.44 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. e) PBS 7.4 with 20uM GSH (blood levels) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

Table 12.45 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. f) PBS 7.4 with 60ug of free drug (each) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample.

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Table 12.50 Flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported.

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Table 12.51 Normalized flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N-Be(2)c cells alone.

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LIST OF FIGURES Figure 1. Neuroblastoma cell culture studies. a) Cell viability of NB cell lines: Be2C (390nM Etoposide, 20mM DFMO), LA1-55n (98 nM Etoposide, 2.5 mM DFMO), SMS-KCNR (98 nM Etoposide 10 mM DFMO). b) Western blot analysis of NB cell line SK-N-SH using p27, caspase 3, PARP, and GAPDH antibodies. DFMO (D), 5 mM; Etoposide (E), 50 µg/mL. Data in (A) in collaboration with Dr. G. Sholler, Helen DeVos Children’s Hospital, Grand Rapids, MI, USA.

Figure 2. Neuroblastoma xenograft studies. Nude mice were injected with 1 x 107 SMS-KCNR neuroblastoma cells subcutaneously and treated with 1) vehicle, 2) 40mg/kg Etoposide on Day 1 and 30 intraperitoneally, 3) 2% DFMO in drinking water, or 4) the combination of Etoposide and DFMO. Images (right panel) show control animals (top, yellow arrows) and DFMO/Etoposide-treated animals (bottom, green arrows). Data in collaboration with Dr. G. Sholler, Helen DeVos Children’s Hospital, Grand Rapids, MI, USA.

Figure 2a. Illustration of proposed final nanocarrier formulation (iRGD-PEG-HNC-D-E). DFMO and Etoposide drugs (center of yellow sphere) are entrapped within bovine serum albumin (BSA) nanocarrier (yellow sphere) with a chitosan (CS) coating (green shell). Nanocarrier is PEGylated (pink) followed by iRGD ppeptide (y-shaped molecule) conjugation to PEGylated molecule. Final nanocarrier formulation will be iRGD peptide conjugated, PEGylated hybrid chitosan coated bovine serum albumin nanocarrier loaded with DFMO and Etoposide (iRGD-PEG-HNC-D-E).

Figure 3. Schematic illustration of nanoscale drug carriers used for combinatorial drug delivery: (a) liposome, (b) polymeric micelle, (c) polymer–drug conjugate, (d) dendrimer, (e) oil nanoemulsion, (f) mesoporous silica nanocarrier, and (g) iron oxide nanocarrier. Reprinted with permission from ref. 3, C. M. Hu, and L. Zhang, Nanocarrier-based combination therapy toward overcoming drug resistance in cancer. Biochemical pharmacology. 83, 1104-11 (2012). CopyrightatElsevier.

Figure 3.1 Schematic representation of SPIO/PTX-loaded PLGA-based nanocarriers. Reprinted with permission from ref. 4, N. Schleich, P. Sibret, P. Danhier, B. Ucakar, S. Laurent, R. N. Muller, C. Jerome, B. Gallez, V. Preat, and F. Danhier, Dual anticancer drug/superparamagnetic iron oxide-loaded PLGA- based nanocarriers for cancer therapy and magnetic resonance imaging. Int. J. Pharm. 447, 94-101 (2013). CopyrightatElsevier.

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Figure 3.2 Schematic graph of TPGS functions as a pore former and promotes anti-tumor activity of DTX- loaded Nps. Reprinted with permission from ref. 5, H. Zhu, H. Chen, X. Zeng, Z. Wang, X. Zhang, Y. Wu, Y. Gao, J. Zhang, K. Liu, R. Liu, L. Cai, L. Mei, and S.-S. Feng, Co-delivery of chemotherapeutic drugs with vitamin E TPGS by porous PLGA nanocarriers for enhanced chemotherapy against multi-drug resistance. Biomaterials. 35, 2391-400 (2014). CopyrightatElsevier.

Figure 3.3 Illustration of biodegradable amphiphilic copolymer NPs loaded with both DOX and TAX using improved double emulsion method. Emulsification procedure used to generate double emulsions. Step (I), generating water-in-oil for encapsulations of DOX; Step (II), generating water-in-oil-in-water for encapsulations of TAX. Green represents the oil phase containing amphiphilic copolymer and red the aqueous phase containing DOX. Reprinted with permission from ref. 6, H. Wang, Y. Zhao, Y. Wu, Y.-l. Hu, K. Nan, G. Nie, and H. Chen, Enhanced anti-tumor efficacy by co-delivery of doxorubicin and paclitaxel with amphiphilic methoxy PEG-PLGA copolymer nanocarriers. Biomaterials. 32, 8281-90 (2011). CopyrightatElsevier.

Figure 3.4 A) Examples of bonds utilized in the synthesis of biodegradable polymer-drug conjugates. Biodegradation typically occurs via hydrolysis (via reduction for disulfides). B) Overall strategy for the synthesis of multiblock polyHPMA copolymers. HPMA copolymer blocks are linked together via lysosomally degradable Gly-Phe-Leu-Gly (GFLG) linkages introduced via a combination of RAFT polymerization and click chemistry. Reprinted with permission from ref. 7, J. Yang, K. Luo, H. Pan, P. Kopeckova, and J. Kopecek, Synthesis of Biodegradable Multiblock Copolymers by Click Coupling of RAFT-Generated HeterotelechelicPolyHPMA Conjugates. Reactive & functional polymers. 71, 294-302 (2011). CopyrightatElsevier.

Figure 3.5 A) Dendrimers are hyperbranched, star-link polymers. Drugs can be either conjugated to the dendrimer surface or encapsulated within “void” spaces between adjacent branches. B) Dendrimers grow linearly in size and exponentially in surface area with each successive “generation.” They can be utilized as multifunctional nanocarriers, bearing drugs, imaging agents, and/or targeting moieties. C) Synthesis of poly(amido amine) (PAMAM) dendrimers occurs from a ethylenediamine core with alternating reactions with methyl acrylate and ethylenediamine to produce each generation. Reprinted with permission from ref. 8, N. Larson, and H. Ghandehari, Polymeric conjugates for drug delivery. Chem. Mater. 24, 840-853 (2012). CopyrightatAmerican Chemical Society.

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Figure 4. 131 I-mIBG scan of a patient with stage 4 NB showing an adrenal primary tumor and bone lesions in the femur and spine. Reprinted with permission from ref. 9. Brodeur GM, Pritchard J, Berthold F, et al. Revisions of the international criteria for neuroblastoma diagnosis, staging, and response to treatment. J Clin Oncol. 1993;11: 1466-1477.

Figure 4.1 Kaplan-Meier Survival (S) and event-free survival (EFS) curves and life tables for patients with INSS stage 1 NB. Reprinted with permission from ref. 10. Alvarado CS, London WB, Look AT, et al. Natural history and biology of stage A neuroblastoma: a Pediatric Oncology Group Study. J Pediatr Hematol Oncol. 2000;22: 197-205.

Figure 4.2 Kaplan-Meier EFS curves from the time of first randomization into the CCG 3891 study for high-risk NB patients treated with myeloablative therapy plus autologous stem cell rescue versus continuous chemotherapy. Reprinted with permission 11. Matthay KK, Villablanca JG, Seeger RC, et al. Treatment of high-risk neuroblastoma with intensive chemotherapy, radiotherapy, autologous bone marrow transplantation, and 13-cis-retinoic acid. Children's Cancer Group. N Engl J Med. 1999;341: 1165-1173.

Figure 4.3 Kaplan-Meier EFS curves from the time of second randomization into the CCG 3891 study for high-risk NB patients treated with 13-cis-retinoic acid following consolidation therapy versus no further therapy. Reprinted with permission 11. Matthay KK, Villablanca JG, Seeger RC, et al. Treatment of high- risk neuroblastoma with intensive chemotherapy, radiotherapy, autologous bone marrow transplantation, and 13-cis-retinoic acid. Children's Cancer Group. N Engl J Med. 1999;341: 1165-1173.

Figure 6. A) Schematic diagram showing EGFRvIII-IONPs. (B-F) Survival studies of nude mice implanted with the U87ΔEGFRvIII glioma model. B) T2-weighted MRI showing a tumor region with a bright signal 7 days after tumor implantation (arrow). C) A tumor is shown (arrow) after injection of a gadolinium contrast agent (Gd-DTPA). D) The MRI signal decreased (arrow) after CED of EGFRvIIIAb-IONPs. E) EGFRvIIIAb-IONP dispersion and T2 signal decrease (arrow) 4 days after CED. F) Survival curve of the nude mice bearing U87ΔEGFRvIII cells after a treatment regimen of MRI-guided CED: the untreated control, IONPs, EGFRvIIIAb, or EGFRvIIIAb-IONPs. Reprinted with permission from ref. 194, C. G. Hadjipanayis, R. Machaidze, M. Kaluzova, L. Wang, A. J. Schuette, H. Chen, X. Wu, and H. Mao, EGFRvIII antibody-conjugated iron oxide nanocarriers for magnetic resonance imaging-guided convection-enhanced delivery and targeted therapy of glioblastoma. Cancer Res. 70, 6303-12 (2010). CopyrightatCancer Research.

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Figure 6.1 A) Schematic diagram showing the synthesis of MN-EPPT-siBIRC5. B) Representative pre- contrast images and 24 h post-contrast T2-weighted images (top), and color-coded T2 maps (bottom) of the tumor-bearing mice i.v. injected with MN-EPPT-siBIRC5 (10 mg/kg Fe). C) Relative tumor volume measurements of MN-EPPT-siBIRC5- and MN-EPPT-siSCR-injected animals over the course of treatment. Reprinted with permission from ref. 212, M. Kumar, M. Yigit, G. Dai, A. Moore, and Z. Medarova, Image-guided breast tumor therapy using a small interfering RNA nanodrug. Cancer Res. 70, 7553-61 (2010). CopyrightatCancer Research.

Figure 6.2 Schematic illustration of the silica nanoporous particle-supported lipid bilayer, depicting the disparate types of therapeutic and diagnostic agents that can be loaded within the nanoporous silica core, as well as the ligands that can be displayed on the surface of the nanocarrier. Reprinted with permission from ref. 279, C. E. Ashley, E. C. Carnes, G. K. Phillips, D. Padilla, P. N. Durfee, P. A. Brown, T. N. Hanna, J. Liu, B. Phillips, M. B. Carter, N. J. Carroll, X. Jiang, D. R. Dunphy, C. L. Willman, D. N. Petsev, D. G. Evans, A. N. Parikh, B. Chackerian, W. Wharton, D. S. Peabody, and C. J. Brinker, The targeted delivery of multicomponent cargos to cancer cells by nanoporous particle-supported lipid bilayers. Nature materials. 10, 389-97 (2011). CopyrightatNature Publishing Group.

Figure 6.3 A) Schematic representation of nanocarrier communication to achieve amplified tumor targeting. Tumor-targeted signaling nanocarriers (blue) broadcast the tumor location to the receiving nanocarriers (red) present in circulation. B) Shown are the harnessing of the biological cascade to transmit and amplify nanocarrier communication and the molecular signaling pathway between the signaling and receiving components. C) Thermographic images of the photothermal NRs with heating. Seventy-two hours after NR or saline injection, mice were co-injected with FXIII-NWs and untargeted control-NWs, and their right flanks were broadly irradiated (top). Twenty-four hours post-irradiation, whole-animal fluorescence imaging revealed the distribution of the receiving nanocarriers (bottom). D) Amplified tumor therapy with communicating nanocarriers. Tumor volumes following a single treatment with the communicating nanocarrier systems and controls. Reprinted with permission from ref. 280, G. von Maltzahn, J. H. Park, K. Y. Lin, N. Singh, C. Schwoppe, R. Mesters, W. E. Berdel, E. Ruoslahti, M. J. Sailor, and S. N. Bhatia, Nanocarriers that communicate in vivo to amplify tumour targeting. Nature materials. 10, 545-52 (2011). CopyrightatNature Publishing Group.

31 | Page bioconjugates comprised of PLGA-b-PEG nanocarriers surface functionalized with the A10 PSMA aptamer for co-delivery of Dtxl and DOX. Both drugs can be released from the bioconjugates over time. Reprinted with permission from ref. 281, J. Zhou, M. L. Bobbin, J. C. Burnett, and J. J. Rossi, Current progress of RNA aptamer-based therapeutics. Frontiers in genetics. 3, 234 (2012). CopyrightatCancer Research.

Figure 6.5 Schematic illustration of multifunctional core–shell hybrid nanogels. The Ag–Au bimetallic NP (10 ± 3 nm) core is NIR resonant and highly fluorescent. The thermo-responsive nonlinear PEG-based gel shell cannot only manipulate the fluorescence intensity of Ag–Au NP core, but also trigger the release of drug molecules encapsulated in the gel shell under the local temperature increase of targeted pathological zones or the heat generated upon NIR irradiation. HA, a known targeting ligand, can be readily semi- interpenetrated into the surface networks of gel shell at a light penetration depth. Reprinted with permission from ref. 254, W. Wu, J. Shen, P. Banerjee, and S. Zhou, Core-shell hybrid nanogels for integration of optical temperature-sensing, targeted tumor cell imaging, and combined chemo-photothermal treatment. Biomaterials. 31, 7555-66 (2010). CopyrightatElsevier.

Figure 7. Chemical structures. (A) The original RGD sequence. (B) Cyclic RGD peptide antagonist (c(RGDf[N-Me]V) or cilengitide. (C) Cyclicpeptide c(RGDfK). (D) ACDCRGDCFCG (RGD4C). (E) Example of RGD peptidomimetic-containing the RGD sequence (S-247).28(F)Example of RGD peptidomimetic. Reprinted with permission from ref. 12. Rerat V, Dive G, Cordi AA, et al. alphavbeta3 Integrin-targeting Arg-Gly-Asp (RGD) peptidomimetics containing oligoethylene glycol (OEG) spacers. J Med Chem. 2009;52: 7029-7043.

Figure 7.1 Tissue penetrating iRGD. Penetration mechanism of iRGD. The iRGD peptide binds to αv integrin expressed by tumor blood vessel endothelial cells and tumor cells. After the binding, the peptide is cleaved by proteases to expose the cryptic CendR element. This CendR element binds to neuropilin-1 and penetrates into cells and tissue. The peptide can also penetrate into tumors while carrying a cargo attached to the N-terminus of the iRGD peptide. Reprinted with permission from ref. 13. Sugahara KN, Teesalu T, Karmali PP, et al. Tissue-penetrating delivery of compounds and nanoparticles into tumors. Cancer Cell. 2009;16: 510-520.

32 | Page labeled with Cy5.5, a near-infrared fluorescent (NIRF) dye, and modified with hydrophobic 5β-cholanic acid. C) A TEM image of Cy5.5-labeled CNPs (1 mg/ml) in distilled water. D) Bright field and NIRF images of the Cy5.5-labeled CNPs in PBS. The NIRF image was obtained using a Cy5.5 filter set (ex = 674 nm, em = 695 nm). E) Time-dependant size distribution of Cy5.5-labeled CNPs in PBS at 37 °C was confirmed using dynamic light scattering. F) Filtration of water-soluble glycol chitosan (GC), CNPs, and polystyrene (PS) beads through filters of different pore sizes (0.8 μm, 0.45 μm, and 0.2 μm). The amount of each particle passed through the filters was quantified through NIRF intensity of the filtrate. (G) In vitro stability of the Cy5.5-labeled CNPs was determined using an SDS-PAGE test. Cy5.5-labeled GC polymers and CNPs were incubated in 10% serum for 6 h at 37 °C and their migratory positions were monitored using a Cy5.5 filter set. Reprinted with permission from ref. 14, K. Kim, J. H. Kim, H. Park, Y. S. Kim, K. Park, H. Nam, S. Lee, J. H. Park, R. W. Park, I. S. Kim, K. Choi, S. Y. Kim, K. Park, and I. C. Kwon, Tumor-homing multifunctional nanocarriers for cancer theragnosis: Simultaneous diagnosis, drug delivery, and therapeutic monitoring. J. Cntrl. Release. 146, 219-27 (2010). CopyrightatElsevier.

Figure 9.1 A) In vivo biodistribution of Cy5.5-labeled CNPs in SCC7 tumor-bearing mice. After tumor diameters reached 7–8 mm, 3.3 μmol of Cy5.5-labeled CNPs (5 mg/kg) were i.v. injected into the tumor- bearing C3H/HeN nude mice. (NIRF signal scale: 45–2680). B) Time-dependent tumor contrast after administration of Cy5.5-labeled CNPs into tumor-bearing mice (n = 3). C) NIRF images of the dissected major organs harvested from Cy5.5-labeled CNP-treated mice. The first row represents the bright field images of individual organs. A strong NIRF signal was observed in tumor tissues at all experimental times. D) Ex vivo imaging of SCC7 xenograft tumor showed higher NIRF signal than other organs at all time points. A quantification of in vivo targeting characteristics of Cy5.5-labeled CNPs was recorded as total photons per centimeter squared per steradian (p/s/cm2/sr) per milligram of each organ at all time points (n = 3 mice per group). All data represent mean ± s.e. Reprinted with permission from ref. 14, K. Kim, J. H. Kim, H. Park, Y. S. Kim, K. Park, H. Nam, S. Lee, J. H. Park, R. W. Park, I. S. Kim, K. Choi, S. Y. Kim, K. Park, and I. C. Kwon, Tumor-homing multifunctional nanocarriers for cancer theragnosis: Simultaneous diagnosis, drug delivery, and therapeutic monitoring. J. Cntrl. Release. 146, 219-27 (2010). CopyrightatElsevier.

Figure 9.2 Schematic illustrations of the concept of the study. pH-responsive DOX (DOX)-loaded nanocarriers (NPs), made of N-palmitoyl chitosan bearing a Cy5 moiety (Cy5–NPCS), were prepared as an anticancer delivery device. Using the technique of Förster resonance energy transfer (FRET), the drug release behavior of DOX-loaded Cy5–NPCS NPs can be monitored/imaged intracellularly. Reprinted with permission from ref. 15, K. J. Chen, Y. L. Chiu, Y. M. Chen, Y. C. Ho, and H. W. Sung, Intracellularly

33 | Page monitoring/imaging the release of doxorubicin from pH-responsive nanocarriers using Forster resonance energy transfer. Biomaterials. 32, 2586-92 (2011). CopyrightatElsevier.

Figure 9.3 Dual-emission fluorescence images of HT1080 cells; cells were incubated with DOX-loaded Cy5–NPCS nanocarriers (NPs) for distinct durations and fluorescence images were then taken by CLSM in optical windows between 560–600 nm (DOX imaging channel) and 660–700 nm (Cy5 imaging channel) when irradiating NP suspensions at 488 nm. Reprinted with permission from ref. 15, K. J. Chen, Y. L. Chiu, Y. M. Chen, Y. C. Ho, and H. W. Sung, Intracellularly monitoring/imaging the release of doxorubicin from pH-responsive nanocarriers using Forster resonance energy transfer. Biomaterials. 32, 2586-92 (2011). CopyrightatElsevier.

Figure 9.4 In vivo real-time microdistribution of DACHPt/m with different diameters in tumours. a, b) Microdistribution of fluorescently labelled 30 nm (green) and 70 nm (red) micelles 1 h after injection into C26 (a) and BxPC3 (b) tumours. Their colocalization is shown in yellow. Right panels in a and b show fluorescence intensity profile from the blood vessel (0–10mm; grey area) to the tumour tissue (10–100 mm) in the selected region (indicated by a white rectangle) expressed as a percentage of the maximum fluorescence intensity attained in the vascular region (%Vmax). c, d) Z-stack volume reconstruction of C26 (c) and BxPC3 (d) tumours 1 h after co-injection of the fluorescent micelles. e) Magnification of the perivascular region (indicated by a white trapezium) of the z-stack volume image of BxPC3 tumours. f, g) Distribution of 30 and 70 nm micelles 24 h after injection into C26 tumours (f) and BxPC3 tumours (g). White arrows in g indicate 70 nm micelles localizing at perivascular regions. Right panels show fluorescence intensity profile from the blood vessel (0–10 mm; grey area) to the tumour tissue (10–100 mm) in the selected region (indicated by white rectangle). Reprinted with permission from ref. 16, H. Cabral, Y. Matsumoto, K. Mizuno, Q. Chen, M. Murakami, M. Kimura, Y. Terada, M. R. Kano, K. Miyazono, M. Uesaka, N. Nishiyama, and K. Kataoka, Accumulation of sub-100 nm polymeric micelles in poorly permeable tumours depends on size. Nature nanotechnology. 6, 815-23 (2011). CopyrightatNature Publishing Group.

Figure 10. Reaction of 2, 4, 6-trinitrobenzenesulfonic acid with a primary amine containing molecule to produce trinitrophenyl derivative. Trinitrophenyl molecule is UV-active at 345nm. TNBS protein-sulfite complex is formed by a simple one stage hydrolysis reaction in a base solution.

Figure 10.1 One-step hydrolysis reaction of 2, 4, 6-trinitrobenzenesulfonic acid (TNBSA) with primary amine containing α-difluoromethylornithine (DFMO) drug molecule yields Trinitrophenyl-DFMO-

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Trinitrophenyl (TNP-DFMO-TNP) derivative. TNP-DFMO-TNP molecule is UV-active at 345nm. 0.025% w/v TNBSA stock solution in DI-H2O used as reactant. DFMO suspended in borate buffer 10.2 allows for protonation of both primary amine groups. TNBS protein-sulfite complex is formed by a simple one stage hydrolysis reaction.

Figure 10.2 Linearity graph of linearity study of DFMO derivative (TNP-DFMO-TNP) quantified using a Biotek plate reader at 345nm. Linearity was found in a range of 10 to 60ug/mL at 345nm with a linear regression value (R2) of 0.997. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP-DFMO-TNP derivative analyzed after 2h.

Figure 10.3 A representative chromatogram of DFMO derivative (TNP-DFMO-TNP, retention time of 30.35 minutes) and TNBSA reagent (retention time of 2 minutes) versus the Absorbance area (mAU*min) at 345nm. Chromatogram represents concentration range of 10 to 50ug/mL of TNP-DFMO-TNP adduct. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP-DFMO-TNP derivative analyzed after 2h.

Figure 10.4 Linearity graph of standard curve parameters of DFMO derivative (TNP-DFMO-TNP) quantified using Dionex Ultimate 3000 HPLC at 345nm. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP- DFMO-TNP derivative analyzed after 2h. Linearity was found in a range of 10 to 50ug/mL using absorbance area (mAU*min). Linearity range were performed in triplicates.

Figure 10.5 Chromatogram of Etoposide drug, retention time of 6.5 minutes) versus the absorbance area (mAU*min) at 283nm. Chromatogram represents concentration of 104ug/mL of Etoposide drug.

Figure 10.6 A representative chromatogram of Etoposide drug, retention time of 6.5 minutes versus absorbance area (mAU*min) at 283nm. Chromatogram represents concentration range of 13, 26, 52 and 104ug/mL of Etoposide drug at 2 hours after solution preparation. Chromatogram shows the drug solution was stable within the experimental conditions of the developed method.

Figure 10.7 a) Linearity graph of linearity study of Etoposide quantified using a Dionex Ultimate 3000 HPLC at 283nm with concentrations 13, 26, 52, and 104ug/mL versus absorbance area (mAU*min) and b)

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Absorbance height (mAU). Linearity was found in a range of 13 to 104ug/mL. Linear regression value (R2) of 0.999 were shown for both absorbance readings.

Figure 10.8 Chromatogram of HPLC procedures to quantify DFMO derivative (#2, TNP-DFMO-TNP) and Etoposide (#3). DFMO derivative (TNP-DFMO-TNP) at 345nm (10 to 60ug/mL) with a retention time of 27.9 minutes. TNBS (#1) at 345nm has a retention time of 2 minutes. Etoposide at 283nm (10 to 60ug/mL) w/retention time of 31 minutes. Total run-time was 60 minutes for this HPLC procedure.

Figure 10.9 Etoposide (#2) at 283nm with a retention time of 13.9 minutes (10ug/mL). TNBS (#1) at 283nm has a retention time of 6.9 minutes. Chromatogram shows no interaction between TNBS and Etoposide (as compared against know concentrations of Etoposide, previous chromatogram in Etoposide drug only HPLC section). 10ug/mL Etoposide shows same absorbance area as compared to free etoposide (no TNBSA reagent present).

Figure 10.10 Linearity graph of standard curve parameters of DFMO derivative (TNP-DFMO-TNP) and Etoposide quantified using Dionex Ultimate 3000 HPLC at 345nm and 283nm, respectively. Linearity was found in a range of 10 to 60ug/mL using absorbance area (mAU*min) and absorbance height (mAU, plot above). Linearity range were performed in triplicates for each drug. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were shown for both absorbance readings.

Figure 11. Structures of MTT and colored formazan product.17 The MTT molecule is metabolicly reduced to formazan product (yielding a color change) using NADH molecule found within the cell. This is a metabolic reaction and will not proceed forward in non-viable cells.

Figure 11.1 Direct correlation of formazan absorbance with B9 hybridoma cell number and time-dependent increase in absorbance. Note: there is little absorbance change between 2 and 4 hours. Adapted from CellTiter 96® Non-Radioactive Cell Proliferation Assay Technical Bulletin #112.17

Figure 11.2 Intermediate electron acceptor pheazine ethyl sylfate (PES) transfers electron from NADH in the cytoplasm to reduce MTS in the culture medium into an aqueous soluble formazan.17

Figure 11.3 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with varying concentrations of free DFMO (yellow) and Etoposide (pink) separately at 2 hour

36 | Page reading. Cells seeded at 5 x 103 per well. Experiment was done in triplicates with raw data shown above (a, b and c represent independent experiments).

Figure 11.4 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of Be(2)c NB cell-line treated with varying concentrations a free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 5 x 103 per well. Log [DFMO] versus % effect of DFMO (Left graph) and Log [Etoposide] versus % effect of Etoposide (Right graph). IC50 values were determined at 0.4054mM and 227.4nM for DFMO and Etoposide, respectively, for Be(2)c NB cell-lines. Experiment was done in triplicates (n=3).

Figure 11.5 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-SH NB cell-line treated with varying concentrations of free DFMO (yellow) and Etoposide (pink) separately at 2 hour reading. Cells seeded at 1 x 104 per well. Experiment was done in triplicates with raw data shown above (a, b and c represent independent experiments).

Figure 11.6 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-SH NB cell-line treated with varying concentrations a free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 1 x 104 per well. Log [DFMO] versus % effect of DFMO (Left graph) and Log [Etoposide] versus % effect of Etoposide (Right graph). IC50 values were determined at 5.523mM and 76.5nM for DFMO and Etoposide, respectively, for SK-N-SH NB cell-lines. Experiment was done in triplicates (n=3).

Figure 11.7 MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell-line treated with varying concentrations of free DFMO (yellow) and Etoposide (pink) separately at 2 hour reading. Cells seeded at 5 x 103 per well. Experiment were done in triplicates with raw data shown above (a, b and c represent independent experiments).

Figure 11.8 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell-line treated with varying concentrations a free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 5 x 103 per well. Log [DFMO] versus % effect of DFMO (Left graph) and Log [Etoposide] versus % effect of Etoposide (Right graph). IC50 values were determined at 1.468mM and 3.02nM for DFMO and Etoposide, respectively, for IMR-32 NB cell-lines. Experiment was done in triplicates (n=3).

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Figure 11.9 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with varying concentrations of free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 5 x 103 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h. Experiment was done in duplicates with raw data shown above. Data set; a, c, and e represent one complete experiment at 0.1 (pink), 0.2 (blue), and 0.3 (green) IC50 equivalents of DFMO, respectively. Data set; b, d, and f represents duplicate experiment.

Figure 11.10 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with varying concentrations of DFMO and Etoposide combinations at 2 hour reading (post-treatment with MTS reagent). Cells seeded at 5 x 103 per well. Cells incubated with respective drug combinations for 96h. Log [Etoposide] versus % effect plotted with three varying concentrations of IC50 equivalent ratios of DFMO. New IC50 values were determined for each cell-line at their respective drug-to-drug concentrations. Each DFMO IC50 equivalent ration yielded a new IC50 value when combined with Etoposide. New Etoposide IC50 values are; 26.68nM (combined with 0.3 ratio of IC50 DFMO equivalent), 30.30nM (at 0.2 ratio DFMO), and 40.87nM (at 0.1 ratio DFMO). Experiment done in duplicates (n=2). Experiment done in duplicates (n=2).

Figure 11.11 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-SH NB cell-line treated with varying concentrations of free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 2 x 104 per well. Cells incubated with respective drug combinations for 96h. Experiment was done in duplicates with raw data shown above. Data set; a, c, and e represent one complete experiment at 0.1 (pink), 0.2 (blue), and 0.3 (green) IC50 equivalents of DFMO, respectively. Data set; b, d, and f represents duplicate experiment.

Figure 11.12 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with varying concentrations of DFMO and Etoposide combinations at 2 hour reading (post-treatment with MTS reagent). Cells seeded at 5 x 103 per well. Cells incubated with respective drug combinations for 96h. Log [Etoposide] versus % effect plotted with three varying concentrations of IC50 equivalent ratios of DFMO. New IC50 values were determined for each cell-line at their respective drug-to-drug concentrations. Each DFMO IC50 equivalent ratio yielded a new IC50 value when combined with Etoposide. New Etoposide IC50 values are; 0.90nM (combined with 0.3 ratio of IC50 DFMO equivalent), 6.15nM (at 0.2 ratio DFMO), and 29.03nM (at 0.1 ratio DFMO). Experiment done in duplicates (n=2).

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Figure 11.13 MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell-line treated with varying concentrations of free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 5 x 103 per well. Cells incubated with respective drug combinations for 96h. Experiment was done in duplicates with raw data shown above. Data set; a, c, and e represent one complete experiment at 0.1 (pink), 0.2 (blue), and 0.3 (green) IC50 equivalents of DFMO, respectively. Data set; b, d, and f represents duplicate experiment.

Figure 11.14 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell-line treated with varying concentrations of DFMO and Etoposide combinations at 2 hour reading (post-treatment with MTS reagent). Cells seeded at 5 x 103 per well. Cells incubated with respective drug combinations for 96h. Log [Etoposide] versus % effect plotted with three varying concentrations of IC50 equivalent ratios of DFMO. New IC50 values were determined for each cell-line at their respective drug-to-drug concentrations. Each DFMO IC50 equivalent ration yielded a new IC50 value when combined with Etoposide. New Etoposide IC50 values are; 0.116nM (combined with 0.3 ratio of IC50 DFMO equivalent), 0.439nM (at 0.2 ratio DFMO), and 6.312nM (at 0.1 ratio DFMO). Experiment done in duplicates (n=2). Experiment done in duplicates (n=2).

Figure 11.15 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of a) Be(2)c, b) SK-N-SH, and c) IMR-32 NB cell-line treated with varying concentrations of DFMO and Etoposide combinations at 2 hour reading. Cells seeded at 5 x 103, 1 x 104, and 5 x 103 per well for Be(2)c, SK-N-SH, and IMR-32, respectively. Cells incubated with respective drug combinations for 96h. Log [Etoposide] versus % effect plotted with three varying concentrations of IC50 equivalent ratios of DFMO. New IC50 values were determined for each cell-line at their respective drug-to-drug concentrations. Each DFMO IC50 equivalent ration yielded a new IC50 value when combined with Etoposide. Experiment was done in duplicates (n=2).

Figure 11.16 Combination studies of DFMO and Etoposide using SK-N-Be(2)c (a), SK-N-SH (b) and IMR- 32 (c) NB cell-lines. Combination index at 50% effect level used to determine evaluation effect level. Data calculated using equations 1 and 2. Data done in triplicates for each cell-line. Line of additivity at combination index of 1. Data below the line of additivity shows synergism, and above shows antagonism. Data falling on or close to the line of additivity shows additive effects of the drugs.

39 | Page interferes constructively to form a bright patch. The dark areas are where the phase additions are mutually destructive and cancel each other out.

Figure 12.1 The signal intensity at (t) with itself then we would have perfect correlation, as the signals are identical. Perfect correlation is reported as 1 and no correlation is reported as 0.

Figure 12.2 The correlation function for large and small particles. As can be seen, the rate of decay for the correlation function is related to particle size as the rate of decay is much faster for small particles than it is for large.

Figure 12.3 A typical size distribution graph. The X axis shows a distribution of size classes, while the Y axis shows the relative intensity of the scattered light. This is therefore known as an intensity distribution.

Figure 12.4 The first graph below shows the result as a number distribution. As expected, the two peaks are of the same size (1:1) as there is equal number of particles. The second graph shown the result of the volume distribution. The area of the peak for the 50nm particles is 1000 times larger the peak for the 5nm (1:1000 ratio). This is because the volume of a 50nm particle is 1000 times larger that the 5nm particle. The third graph shows the result of an intensity distribution. The area of the peak for the 50nm particles is now 1,000,000 times larger the peak for the 5nm (1:1000000 ratio). This is because large particles scatter much more light than small particles

Figure 12.5 Example of Nicomp 380ZLS data out-put. Gaussian distribution analysis of nanoparticles. Mean diameter and Variance (P.I.) are data most important in nanocarrier analysis.

Figure 12.6 Diagram showing the ionic concentration and potential difference as a function of distance from the charged surface of a particle suspended in a dispersion medium.

Figure 12.7 Example of Nicomp 380ZLS data out-put. Zeta Potential analysis of nanoparticles. Red boxes indicate critical data.

Figure 12.8 Recommended Molecular weight cut-off (MWCO) of dialysis membrane for nanocarrier purification.

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Figure 12.9 Density gradient centrifugation for nanocarrier purification. Nanocarriers, free polymer and free drug are separated using varying centrifuge g-forces. Density gradient centrifugation methods need to optimized to ensure proper separation of each excipient occurs and no overlap occurs.

Figure 12.10 Vivaspin method for nanocarrier purification. Nanocarrier formulation is placed in top of vivaspin (with recommended MWCO filter) and centrifuged at recommended settings. Supernatant is collected and analyzed for free drug to determine entrapment and loading efficiency of nanocarriers. Free polymer and nanocarriers are trapped in membrane filter.

Figure 12.11 Example of chromatograms (@345nm) obtained to determine entrapment efficiency and drug loading during formulation experiments. DFMO derivative (TNP-DFMO-TNP, #2) at 345nm with a retention time of 11.91 minutes versus absorbance height (mAU). Etoposide (#3) at 283nm with a retention time of 13.9 minutes versus absorbance height (mAU). TNBSA (#1) has a retention time of 2 minutes at 345nm. Total run-time was 18 minutes.

Figure 12.12 Example of chromatograms (@283nm) obtained to determine entrapment efficiency and drug loading during formulation experiments. Etoposide (#3) at 283nm with a retention time of 13.9 minutes versus absorbance height (mAU). DFMO derivative (TNP-DFMO-TNP, #2) at 345nm with a retention time of 11.91 minutes. TNBSA (#1) has a retention time of 2 minutes at 345nm. Total run-time was 18 minutes.

Figure 12.13 Overall illustration of hybrid nanocarrier formulation process containing both DFMO and Etoposide in its albumin core (yellow sphere). Each formulation step will be discussed in greater detail in their respective sections. BSA nanocarriers (yellow) will be contain DFMO and Etoposide within its core. Chitosan (teal) will coat the BSA nanocarrier, to allow conjugation of PEG (pink) to the amino acid backbone found on the chitosan shell. The final product will be conjugated with iRGD peptides (y-shaped markers) for a targeted approach to NB tumors.

Figure 12.14 Desolvation method Bovine serum albumin nanoparticle formation using simple coacervation (desolvation method).

Figure 12.15 Desolvation method Bovine serum albumin nanoparticle formation using simple coacervation (desolvation method).

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Figure 12.16 Formation of Chitosan nanoparticles by ionotropic gelation method with Tripolyphosphate (TPP) crosslinking excipient 18.

Figure 12.17 Effects of various non-diluted desolvating agents (ethanol, acetone, and methanol) on mean particle size and mean polydispersity index using 10% BSA solution (1mL, each) at 650 RPM (small paddle stirrer, magnetic cross bar OR magnetic stir bar), 1 mL/min continuous flow rate of desolvating agent with a total stir time of 1h (for complete evaporation of solvent). Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5% (not all experiments).

Figure 12.18 Turbidity of BSA nanocarrier formulations (left to right; methanol, acetone and ethanol)

Figure 12.19 Combination of desolvating agents (acetone & methanol) and its effects on particle size (yellow) and polydispersity index (blue) using 10% BSA solution (1mL) at 650 RPM (small paddle stirrer), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%

Figure 12.20 Combination of desolvating agents (ethanol & methanol) and its effects on particle size (yellow) and polydispersity index (blue) using 10% BSA solution (1mL) at 650 RPM (small paddle stirrer), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%.

Figure 12.21 Combinations of desolvating agents (ethanol & acetone) and its effects on particle size (yellow) and polydispersity index (blue) using 10% BSA solution (1mL) at 650 RPM (cross bar), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%.

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Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%

Figure 12.23 Particle size results of 1% & 4% w/v BSA in DI-H2O (40mL each). Stir rate at 600 RPM (small paddle stirrer), 1mL/min continuous flow of desolvating agent (methanol) into glass beaker containing %BSA solution. Methanol selected based on drug of interest (Etoposide) solubility in organic solvents.

Figure 12.24 Polydispersity Index (PdI) results of 1% & 4% w/v BSA in DI-H2O (40mL each). Stir rate at 600 RPM (small paddle stirrer), 1ml/min continuous flow of desolvating agent (methanol) into glass beaker containing %BSA solution. Methanol selected based on drug of interest (Etoposide) solubility in organic solvents.

Figure 12.25 Illustration of current nanocarrier formulation step. “Phase 1” of nanocarrier development will be discussed in this section. BSA (yellow sphere) and CS (teal) nanocarriers containing no drug.

Figure 12.26 Means of Means plot (particle size, PS) of Taguchi orthogonal array design of experiment 33 (3 level, 3 factor) for the development of bovine serum albumin (BSA) nanocarriers. Each factor has 3 levels; 200, 400, and 600 RPM stir rate factor, 6, 8, and 10mL for desolvating agent factor and 15, 30, and 45-minute stir time factor. These factors were deemed most influential on particle size (PS) and polydispersity index (PdI) based on literature review 2. Desolvating agent (methanol) flow rate set at 1mL/min (continuously, not drop-wise, into solution). 10% w/v BSA used (10mL). Factors ranked in order of greatest influence (rank #1) on responses (PS & PdI) to lease influence (rank #3).

Figure 12.27 Means of Means plot (polydispersity index, PdI) of Taguchi orthogonal array design of experiment 33 (3 level, 3 factor) results for the development of bovine serum albumin (BSA) nanocarriers. Each factor has 3 levels; 200, 400, and 600 RPM stir rate factor, 6, 8, and 10mL for desolvating agent factor and 15, 30, and 45-minute stir time factor. These factors were deemed most influential on particle size (PS) and polydispersity index (PdI) based on literature review 2. Desolvating agent (methanol) flow rate is set at 1mL/min (continuously, not drop-wise, into solution). 10% w/v BSA used (10mL). Factors ranked in order of greatest influence (rank #1) on responses (PS & PdI) to lease influence (#3).

Figure 12.28 Illustration of current nanocarrier formulation step. “Phase 2, 3, & 4” of nanocarrier development will be focused on.

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Figure 12.29 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 2” nanocarrier development.

Figure 12.30 HPLC chromatograms of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA-D). HPLC analysis conducted to determine entrapment efficiency of BSA-D. BSA-D were purified using vivaspin method and supernatant treated with TNBSA reagent (according to previously described section). TNP- DFMO-TNP adduct was quantified and analyzed via HPLC to determine entrapment efficiency of HNC- D. TNP-DFMO-TNP has a retention time of 11.2 minutes at 345nm. Absorbance area (mAU*min) were calculated and used to determine %EE.

Figure 12.31 Linearity graph of standard curve parameters of a) DFMO derivative (TNP-DFMO-TNP) and b) Etoposide quantified using Dionex Ultimate 3000 HPLC at 345nm and 283nm, respectively. Linearity was found in a range of 10 to 60ug/mL using absorbance area (mAU*min). Linearity range were performed in triplicates for each drug. Standard curves used to determine entrapment efficiencies of formulations. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were evaluated for both absorbance readings.

Figure 12.32 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA-D). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. a) Particle size (pink), b) zeta potential (blue), c) polydispersity index (green), d) entrapment efficiency (yellow).

Figure 12.33 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA-D). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. Over-lay of all important BSA-D nanocarrier data: a) Particle size (pink), b) zeta potential (blue), c) polydispersity index (green), d) entrapment efficiency (yellow).

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Figure 12.34 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 3” nanocarrier development.

Figure 12.35 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA-D-E). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. a) Particle size (pink), b) zeta potential (blue), c) polydispersity index (green), d) entrapment efficiency (yellow).

Figure 12.36 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA-D-E). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. Over-lay of all important BSA-D nanocarrier data: a) Particle size (pink), b) zeta potential (blue), c) polydispersity index (green), d) entrapment efficiency (yellow).

Figure 12.37 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 4” nanocarrier development.

Figure 12.38 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA-D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been added to each run. a) mean particle size, b) mean zeta potential, c) mean polydispersity index (PdI)

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Figure 12.39 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA-D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been added to each run.

Figure 12.40 Linearity study of chitosan coated BSA-D-E nanocarriers for the quantification of total amine groups present on HNC surface using TNBSA colorimetric assay in Biotek plate reader at 345nm. Linearity was found in a range of 100 to 500ug/mL with a linear regression value (R2) of 0.995. Varying concentrations of Chitosan (200uL each) treated with 800uL borate buffer 8.5, 250uL TNBSA stock solution (0.025% w/v) and allowed to react for 2h at 37°C. Samples were read in a 96-well plate within 10 minutes of reaction time. Run order #10 were purified via vivaspin method. HNC were re-suspended in DI-H2O and treated with same conditions as chitosan concentrations.

Figure 12.41 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 5” nanocarrier development. This phase will not focus on attaching PEG to the nanocarrier at the moment. Phase 6 will focus on both PEGylation and iRGD peptide conjugation

Figure 12.42 Linearity graph of linearity study of DFMO derivative (TNP-DFMO-TNP) quantified using Barium-Iodine assay in a Biotek plate reader at 345nm. Linearity was found in a range of 2 to 7.5ug/mL at 535nm with a linear regression value (R2) of 0.996.

Figure 12.43 Illustration of current nanocarrier formulation step. This section will focus on “Phase 6” of nanocarrier development.

Figure 12.44 Linearity graph of linearity study of DFMO derivative (TNP-DFMO-TNP) quantified using Barium-Iodine assay in a Biotek plate reader at 345nm. Linearity was found in a range of 2 to 7.5ug/mL at 535nm with a linear regression value (R2) of 0.996.

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Figure 12.45 Linearity study of iRGD peptide quantified using BCA protein assay in a Biotek plate reader at 562nm. Linearity was found in a range of 20 to 60ug/mL with a linear regression value (R2) of 0.996.

Figure 12.46 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in DI-H20. 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

Figure 12.46a Flow cytometry analysis of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. Overlay of controls and HNC formulations: Be2c cells alone (yellow), hybrid nanocarrier loaded with FITC (green, HNC-FITC), iRGD saturated Be2c cells followed by treatment with High iRGD-HNC (pink), Low conjugated iRGD- PEG-HNC (blue), Medium conjugated iRGD-PEG-HNC (black), and High conjugated iRGD-PEG-HNC (red).

Figure 12.46b Normalized flow cytometry results of HNC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Graphpad Prism 5 used for plotting of raw data. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N-Be(2)c cells alone. **(p-value ≤ 0.05) shown to statistically significant. Control against #5 (high conjugated iRGD-HNC-FITC) shown to be statistically significant (p-value = 0.0011) and #5 against #7 thru #11 also statistically significant (p-value = 0.0038)

47 | Page and % CV calculated in a Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

Figure 12.48 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in 0.9% NaCl (normal saline). 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

Figures 12.49 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in 10% w/v FBS. 100uL of final PEG-HNC-D-E formulation suspended in 100uL of media and 800uL of DI-H2O to further dilute FBS. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

Figure 12.50 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in various media (DI-H2O, PBS 7.4, 0.9% NaCl and 10% FBS). 100uL of final PEG-HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table X. Mean particle size ± SD plotted.

Figure 12.51 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in various media (DI-H2O, PBS 7.4, 0.9% NaCl and 10% FBS). 100uL of final PEG-HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table X. Mean zeta potential ± SD plotted.

Figure 12.52 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in various media (DI-H2O, PBS 7.4, 0.9% NaCl and 10% FBS). 100uL of final PEG-HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle

48 | Page sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table X. Mean polydispersity index (PdI) ± SD plotted.

Figure 12.53 In vitro release studies of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC- D-E) in various phosphate buffered saline solutions. Qualitative images shown to the left of TNP-DFMO-TNP adduct (yellow) of drug release at various time points. Solution contains Etoposide drug which has been shown to not interact with TNBSA reagent (HPLC section). a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) (left to right, vials 1 to 10). b) PBS 5.4 without GSH (vials 11 to 20). c) PBS 7.4 w/10mM GSH (vials 21 to 30). d) PBS 7.4 w/o GSH (vials 31 to 40). e) PBS 7.4 w/20uM GSH (blood conditions) (vials 41 to 50). f) Free drug TNP- DFMO-TNP adduct and Etoposide 60ug/mL each (vials 51 to 60)

Figure 12.54 HPLC chromatogram (@345nm) representation of drug release profiles of final formulation (PEG-CS-BSA-D-E) HNC at various time points over 72h in several buffers with or without the presence of glutathione (GSH). DFMO derivative (TNP-DFMO-TNP, #2), retention time of 11.9 minutes, and Etoposide (retention time of 13.9 minutes, #3) elucidation at 345nm and 283nm, respectively Chromatograms 1 through 3 represent reference standards (controls), borate buffer 10.2, TNBSA (#1) in borate buffer 10.2, 0.5mg/mL DFMO in double distilled deionized water (not derivative). Remaining chromatograms are as follows; a) PBS 5.4 with 10mM GSH (chromatograms 4 through 14), b) PBS 5.4 w/o GSH (15 through 24), c) PBS 7.4 with 10mM GSH (25 through 34), d) PBS 7.4 w/o GSH (35 through 44), e) PBS 7.4 w/20uM GSH to mimic blood condition levels (45 through 54), f) PBS 7.4 containing free drugs Etoposide (60ug/mL) and DFMO derivative (TNP-DFMO-TNP, 60ug/mL) (55 through 64). Total run-time of 18 minutes.

Figure 12.55 Linearity graph of standard curve parameters of a) DFMO derivative (TNP-DFMO-TNP) and b) Etoposide quantified using Dionex Ultimate 3000 HPLC at 345nm and 283nm, respectively. Linearity graphs will be utilized to quantify drug for drug release profiles. Linearity was found in a range of 10 to 60ug/mL using absorbance area (mAU*min). Linearity range were performed in triplicates for each drug. Standard curves used to determine entrapment efficiencies of formulations. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were evaluated for both absorbance readings.

Figure 12.56 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

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Figure 12.57 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.58 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. b) PBS 5.4 without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.59 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 without glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.60 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. Media: PBS 5.4 with and without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.61 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) and without GSH at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. PBS 7.4 containing 20uM GSH represent drug release profiles at blood condition levels. PBS 7.4 containing free drug (60ug) used as a control for drug release profiles. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.62 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. c) PBS 7.4 with 10mM GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

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Figure 12.63 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 7.4 containing 10mM glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.64 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. d) PBS 7.4 without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.65 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 7.4 without glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.66 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. Media: PBS 7.4 with and without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.67 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 7.4 containing 10mM glutathione (GSH) and without GSH at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. PBS 7.4 containing 20uM GSH represent drug release profiles at blood condition levels. PBS 7.4 containing free drug (60ug) used as a control for drug release profiles. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.68 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. e) PBS 7.4 with 20uM GSH (blood levels) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

51 | Page glutathione (GSH) to represent blood condition levels at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.70 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. f) PBS 7.4 with 60ug of free drug (each) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.71 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 7.4 with free drug (60ug of each drug) at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.72 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. Media: PBS 7.4 with 20uM GSH (blood levels) and PBS 7.4 with 60ug of free drug (each) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.73 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. In vitro release in PBS 5.4 & 7.4 with or without glutathione (GSH) at 345nm for TNP-DFMO-TNP quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.74 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. In vitro release in PBS 5.4 & 7.4 with or without glutathione (GSH) at 283nm for Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

Figure 12.75 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell- line treated with free DFMO (0.405mM, column 4), Etoposide (230nM, column 5), combination of both drugs (0.04mM + 30nM, DFMO and Etoposide, respectively, column 6). Hybrid nanocarriers containing no drug (HNC-placebo, column 7) followed by HNC-D (0.4mM DFMO, column 8), HNC-D-E (0.04mM

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DFMO and 40nM Etoposide respectively, column 9), PEGylated-HNC-D-E (0.04M DFMO + 40nM Etoposide, column 10), and iRGD peptide conjugated-PEG-HNC-D-E (0.04mM DFMO + 40nM Etoposide, column 11). Controls (no drug or nanocarriers) were in columns 2 and 3. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Well. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells were incubated with respective treatment for 72 h. MTS reading were conducted 2h post- treatment with MTS reagent (20uL of MTS reagent used). Experiment was conducted in triplicates (a, b, c represents independent experiments) with mean ± SD reported.

Figure 12.76 In vitro analysis of free drugs, DFMO (IC50 alone, 0.405mM) and Etoposide (IC50 value, 230nM) compared against various hybrid nanocarrier (HNC) formulations. Treatment conducted over 72h period. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). MTS readings were conducted 2h post-treatment with MTS reagent (20uL of reagent used). Experiment conducted in triplicates with mean ± SD plotted.

Figure 12.77 MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell-line treated with free DFMO (1.5mM, column 4), Etoposide (3nM, column 5), combination of both drugs (0.4mM + 0.5nM, DFMO and Etoposide, respectively, column 6). Hybrid nanocarriers containing no drug (HNC-placebo, column 7) followed by HNC-D (0.4mM DFMO, column 8), HNC-D-E (0.04mM DFMO and 0.5nM Etoposide respectively, column 9), PEGylated-HNC-D-E (0.04M DFMO + 0.5nM Etoposide, column 10), and iRGD peptide conjugated-PEG-HNC-D-E (0.04mM DFMO + 0.5nM Etoposide, column 11). Controls (no drug or nanocarriers) were in columns 2 and 3. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). MTS reading were conducted 2h post-treatment with MTS reagent. Experiment was conducted in triplicates (a, b, c represents independent experiments) with mean ± SD calculated.

Figure 12.78 In vitro analysis of free drugs, DFMO (IC50 alone, 1.5mM) and Etoposide (IC50 value, 3nM) compared against various hybrid nanocarrier (HNC) formulations. Treatment conducted over 72h period. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). MTS readings were conducted 2h post-treatment with MTS reagent (20uL of reagent used). Experiment conducted in triplicates with mean ± SD plotted.

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Figure 12.79 Flow cytometry analysis of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. a) All controls; Be2c cells alone (yellow), Be2c cells destroyed (black, 7000RPM for 1h + UV radiation), hybrid nanocarrier loaded with FITC (green, HNC-FITC), Be2c cells treated with FITC only (red), and iRGD saturated Be2c cells followed by treatment with High iRGD-PEG-HNC (pink). b) Be2c cells alone (yellow), Low conjugated iRGD-PEG-HNC (blue), Medium conjugated iRGD-HNC (black), and High conjugated iRGD-HNC (red). c) Overlay of controls and HNC formulations: Be2c cells alone (yellow), hybrid nanocarrier loaded with FITC (green, HNC-FITC), iRGD saturated Be2c cells followed by treatment with High iRGD-HNC (pink), Low conjugated iRGD-PEG-HNC (blue), Medium conjugated iRGD-PEG-HNC (black), and High conjugated iRGD-PEG-HNC (red).

Figure 12.80 Flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Graphpad Prism 5 used for plotting of raw data. Experiments were done in triplicates with mean ± SD reported. **(p-value ≤ 0.05) shown to statistically significant. Control against #5 (high conjugated iRGD-HNC-FITC) shown to be statistically significant (p-value = 0.0011) and #5 against #6 also statistically significant (p-value = 0.0038)

Figure 12.81 Normalized flow cytometry results of HNC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Graphpad Prism 5 used for plotting of raw data. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N-Be(2)c cells alone. **(p-value ≤ 0.05) shown to statistically

54 | Page significant. Control against #5 (high conjugated iRGD-HNC-FITC) shown to be statistically significant (p-value = 0.0011) and #5 against #6 also statistically significant (p-value = 0.0038)

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LIST OF ABBREVIATIONS Abbreviation Description NB Neuroblastoma BSA Bovine serum albumin CS Chitosan D α-Difluoromethylornithine E Etoposide PEG Pegylation-5000MW (molecular weight) COOH-PEG Carboxy-PEG5000 COOH-PEG-NH2 Carboxy-PEG5000-Mono-Amine COOH-PEG-AMAS Carboxy-PEG5000-N-α-maleimidoacetl-oxysuccinimide ester iRGD peptide Arginine-glycine-aspartic (RGD) amino-aid sequence, cyclic peptide BSA-D Bovine serum albumin nanocarriers loaded with DFMO BSA-D-E Bovine serum albumin nanocrriers loaded with DFMO and Etoposide CS-BSA-D-E Chitosan coated, bovine serum albumin nanocarriers loaded with DFMO and Etoposide HNC Hybrid nanocarrier (contains chitosan and bovine serum albumin polymers) HNC-D Hybrid nanocarrier loaded with DFMO HNC-D-E Hybrid nanocarrier loaded with DFMO and Etoposide PEG-HNC-D-E PEGylated hybrid nanocarier loaded with DFMO and Etoposide iRGD-PEG-HNC-D-E iRGD peptide conjugated, PEGylated hybrid nanocarrier loaded with DFMO and Etoposide AMAS N-α-maleimidoacetl-oxysuccinimide ester EDC 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide) NHS N-hydroxy succinimide FITC Fluorescein Isothiocyanate iRGD-PEG-HNC-FITC iRGD conjugated, PEGylated hybrid nanocarriers loaded with Fluorescein Isothiocyanate TNBSA assay 2, 4, 6-trinitrobenzene sulfonic acid assay BCA protein assay Bicinchoninic acid protein assay

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FLOW DIAGRAM OF THESIS (GENERAL OVERVIEW, hyperlinks in blue font)

Proposed Final Formulation: [iRGD- Literature Review and Chapters 1 to 10 PEG-CS-BSA-D-E Proposed Hypothesis HNC]

[Derivatization of DFMO using TNBSA Quantification of Free Drug Chapter 11 assay, HPLC, Plate (DFMO & Etoposide) Reader]

[Determination of IC50 values, Determination of In vitro Cytotoxicity Studies Chapter 12 Synergistic, Additive of Free Drug or Antagonistic Effect of Drugs]

[Characterization, Preparation and Hybrid Nanocarriers Chapter 13 Evaluation of HNC Formulation Formulations]

[Summary, Future Direction, Closing Conclusion Chapters 14 Remarks]

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1. INTRODUCTION Nanotechnologies were first described in the 1960s through liposomal carriers assisting in the delivery of proteins and drugs to various diseases 19. Since then, the field has made a significant impact on the development of drug delivery systems and clinical therapeutics for cancer therapy 19-21. Currently, there are over two dozen nanotechnology-based therapeutic products approved by the Food and Drug Administration (FDA) for clinical use with more being evaluated under clinical trials 20-22. Some notable examples of chemotherapeutic nanocarriers on the market include doxorubicin (DOX) encapsulated liposomal nanocarriers Doxil 23 and paclitaxel (PTX)-bound albumin nanocarriers Abraxane 24, both administered intravenously (i.v.) for the treatment of various cancers. Further advances in the biocompatibility of these nano-scale drug carriers have allowed for safer, more efficient delivery of a variety of chemotherapeutic drugs. Advantages in nanocarrier assisted delivery of these drugs, particularly at the systemic level, include longer circulation half-lives, improved pharmacokinetics, and reduced adverse side effects 21, 25, 26. Nanocarriers may also take advantage of the enhanced permeability and retention (EPR) effect caused by “leaky” tumor vasculatures, increasing drug accumulation at the tumor site 27, thereby improving pharmacokinetics, and reducing dose and associated toxicities.

In recent years, researchers have been exploring different approaches to delivering multiple therapeutic agent loaded nanocarriers for cancer therapy 25. The use of multiple drugs may suppress the phenomenon known as cancer chemo-resistance that is accountable for the majority of failed cases for cancer therapy 25. Cancer cells have been observed to show a diminished response over a period of chemo-treatment as they acquire defense mechanisms by enhancing self-repair pathways, overexpressing drug efflux pumps, increasing drug metabolism or expressing altered drug targets 25. Combination chemotherapy has been adopted in clinics as a primary cancer treatment regimen to help overcome and reduce cancer drug resistance for an overall improved therapeutic effectiveness 26. If multiple drugs were applied with different molecular targets, then genetic barriers could be raised to overcome the cancer cell mutations, thereby delaying the cancer adaptation process. It has also been demonstrated that -in the treatment -with multiple drugs that target the same cellular pathways, the drugs do function synergistically, yielding an improved therapeutic efficacy and increased target selectivity 26. However, with all their benefits, current combination chemotherapies do have their shortcomings. Dosing and scheduling optimization may be extremely difficult due to the varying pharmacokinetics, bio-distributions, and membrane transport properties among various drug molecules 26, 27. Furthermore, highly potent drug combinations are often associated with severe side effects. These challenges have driven researchers, engineers, and clinicians to investigate rationalized approaches to using the targeted nanotechnology with combination chemotherapy for a more precise and effective route of cancer treatment.

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This article reviews the latest status of targeted nanocarrier-assisted co-delivery of multiple drugs in cancer therapy and imaging. The focus of this article is distinct from the broader generalization of targeted nanocarrier-based combination therapy, which touches on co-administration of multiple different single drug-containing vehicles, as recently discussed in a review by Greco et al. 28. We emphasize a targeted approach to multidrug/siRNA-containing nanocarriers over delivery of single agent loaded nanocarriers due to the vehicle uniformity, ratio-metric drug loading and temporal drug release. All of these features carry significant therapeutic implications and will be discussed in detail.

1.2 Brief overview of Neuroblastoma Neuroblastoma (NB) is the most common extra-cranial solid cancer in childhood and infancy with patients having an average age of 17 months 29. Most are diagnosed with advanced stage NB when tumor progression is aggressive, making treatment of NB even more difficult. The long-term survival rate for these patients is low, despite the advances in standard treatments (chemotherapy, surgery, stem cell transplants, and antibody based therapy) 30. Up to 45% of NB patients are in the high-risk category with full form MYCN gene amplification being observed. Due to poor survival rates and adverse side effects of current chemotherapy, an effective and safe alternative drug delivery strategy should be developed.

1.3 Cancer Therapy Cancer is a major public health problem since it is the second leading cause of illness-related death, only exceeded by heart disease 31. The pathogenesis of cancer involves the structural and quantitative alterations in cellular molecules that control different aspects of cell behavior 32. Molecular changes that cause the development and progression of cancer have been commonly linked to genetic alterations 31. Research efforts are on-going to identify common genetic modifications and the underlying target genes involved in cancer pathways. Alterations in a person’s genetic makeup may be inherited, as in hereditary cancers, or induced by endogenous and exogenous carcinogenic factors as in most sporadic cancers 31. There are six essential changes in cell physiology suggested to collectively dictate malignant growth; self-sufficiency in growth signals, insensitivity to anti-growth signals, tissue invasion and metastasis, limitless replicative potential, sustained angiogenesis and evading apoptosis 32.

Chemotherapeutic agents used in current clinical practice have played a significant role in reducing mortality/morbidity and in increasing patients’ quality of life 33. Despite the recent advances in early diagnosis and in clinical protocols for cancer treatment, the development of anticancer agents that combine efficacy, safety and convenience for the patient remains a great challenge 34.

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Most anticancer drugs have narrow therapeutic index, develop multidrug resistance (MDR) and present non-specific bio-distribution upon i.v. administration leading to severe side effects to healthy tissues, mainly bone marrow and gastrointestinal tract 33. These limitations of conventional chemotherapeutic strategies frequently result in suboptimal dosing, treatment delay or discontinuance and reduced patient compliance to therapy 34.

1.4 Mechanisms of drug resistance Resistance can manifest as a result of decreased drug activity and can be primary (present prior to drug exposure, with the tumor insensitive to initial treatment) or acquired (tumor resistance developing during or after the course of treatment). This innate and/or adaptive resistance to chemotherapy critically limits treatment outcomes and remains a key challenge for clinicians 35. Because a particular mechanism can affect agents from completely unrelated classes of chemotherapy agents, subsequent treatment options may be compromised 35. This so-called MDR phenomenon constrains the efficacy of anthracyclines, taxanes, and several other cytotoxic and biologic agents 36. On a cellular level, there are multiple active mechanisms of resistance, which include increased activity of efflux pumps, such as adenosine-triphosphate (ATP) dependent transporters or reduced drug influx; activation of detoxifying proteins, such as cytochrome P450 mixed function oxidases; activation of mechanisms that repair drug induced DNA damage; and disruptions in apoptotic signaling pathways, which may decrease susceptibility to drug-induced cell death 35.

Alterations in drug efflux mechanisms are a common cause of MDR 37. Overexpression of ATP-binding cassette (ABC) transporter proteins, such as P-glycoprotein (P-gp), and MDR-associated protein 1 (MRP1) may be involved 38. ABC transporters act by pumping anticancer agents out of the intracellular milieu into the extracellular matrix, thereby preventing the agents from reaching their minimally effective intracellular concentrations 37. Substrates for P-gp include anthracyclines, taxanes, antimetabolites, and vinca alkaloids 38. In a meta-analysis of 31 breast cancer clinical trials, overexpression of P-gp was associated with 3-fold increased risk of failure to respond to chemotherapy, and its expression was noted to increase after chemotherapy exposure 39. Although MRP1 expression is increased in chemotherapy-naive tumors, its expression has shown to increase with exposure to cytotoxic agents 38. MRP1 has been shown to confer resistance to anthracyclines and vinca alkaloids, but not taxanes 38.

The chemotherapy-resistant phenotype of cancer cells has been developed by multiple gene aberration 40. Although multidrug and taxane resistance mechanisms are among the best characterized, agents targeted against MDR have yielded poor results 41. Since it is recognized that multiple genetic defects namely, DNA

60 | Page mutations, translocations, truncations, deletions, or duplications are present in cancer cells, the role of drug- induced epigenetic aberrations such as histone posttranslational modifications, DNA hypermethylation, and subsequent gene silencing is of increasing importance 42-44. Epigenetic changes can occur rapidly upon chemotherapy exposure 44. This article is focused on nanocarrier based combination therapy for cancer. The mechanism of MDR is explained in detail in literature.

1.5 Combination chemotherapeutics There are several potential advantages to combination chemotherapeutics, such as reversal of drug resistance, synergistically acting drugs, and improving efficacy as compared to single drug therapy 28. However, with each drug having its own distinct pharmacokinetic profile, the synergistic drug ratio optimized for In vitro analysis will undoubtedly change after the conventional administration of drug “cocktails,” which may lead to insufficient therapeutic results in vivo 28. Polymer and/or lipid-based nanoscale systems that have been previously developed for single drug therapy are now being utilized for co-delivery of more than one drug 45. Mayer et al. have successfully tuned the relative dosage of various drugs in single particle levels, and simultaneously delivered them to target sites with a maintained drug ratio 45. When it comes to other drug combinations, novel delivery vehicles must be developed having desired functionalities that allow for the co-encapsulation of both hydrophobic and hydrophillic drugs, active targeting, and/or controlled drug release 20. These functionalities of the nanocarrier are essential for the co-delivery of nucleic acids and drugs, both of which require intracellular delivery to elicit their therapeutic effects 46, 47. For example, when co-delivering chemotherapy and RNAi therapy for the treatment of multidrug resistant cancers, it is ideal that the nanocarrier first releases siRNA to reduce the expression of MDR transporters followed by the release of the anticancer drugs 47.

Co-delivery may also give the ability to combine both targeted imaging and therapeutic agents for the development of thernostics nanocarriers, allowing for the simultaneous visualization of sites targeted nanocarriers and delivery of therapeutic agents 48. Theranostics technology is innovative in concept and holds signiﬁcant promise for making large medical impacts within the next few decades. Thernostics may provide us with crucial information on intracellular targets, visualization that the therapeutic agents are efficiently reaching their target sites, and enabling effective early detection and treatment of various cancers and diseases 48. Present day research is mainly focused on the design of such multifunctional nano-systems and proof-of-concept tests; 49-52 however, more systematic in vivo studies are needed. Future research in the area of multifunctional nanocarriers will also help to trace the absorption, distribution, metabolism, and excretion of nanocarriers in vivo. Understanding the pharmacokinetics of the drug and its drug delivery system will help improve - formulations, estimate clinical doses, and guarantee safety to patients 53.

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Presently, radionuclide labeling is the only technique that can be used to provide in situ quantitative information-, but radio emitters may be too unstable to conjugate with nano-materials 53. With the help of recently developed in vivo imaging probes like magnetic nanocarriers, 54, 55 quantum dots, 56, 57 gold nanocarriers, 58, 59 and carbon nanotubes, 60, 61 more imaging modalities may become available to track the distribution of nano-therapeutics in the body.

1.6 Small molecule drugs of interest: α-Difluoromethylornithine (DFMO) and Etoposide Dr. Andre Bachmann showed that the FDA-approved trypanosome drug α-difluoromethylornithine (DFMO) exhibits strong anticancer activity against MYCN-amplified NB cells by activation of the 30, 62, 63 polyamine-regulated p27/Rb signaling pathway that leads to G1 cell cycle arrest . DFMO is a suicide inhibitor of ornithine decarboxylase (ODC), a rate-limiting enzyme in the biosynthesis of polyamines, and has proven effective as a therapeutic agent 30, 64-66. ODC gene expression is directly activated by MYCN which further suggests that MYCN gene amplification is connected to high ODC expression. The upregulation of ODC subsequently produces high polyamine levels that contribute to the malignant phenotype and the maintenance of NB tumorgenesis. Based on this MYCN-ODC connection it is suggested that ODC may be a suitable new target for the treatment of NB.

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Figure 1. Neuroblastoma cell culture studies. a) Cell viability of NB cell lines: Be2C (390nM Etoposide, 20mM DFMO), LA1-55n (98 nM Etoposide, 2.5 mM DFMO), SMS-KCNR (98 nM Etoposide 10 mM DFMO). b) Western blot analysis of NB cell line SK-N-SH using p27, caspase 3, PARP, and GAPDH antibodies. DFMO (D), 5 mM; Etoposide (E), 50 µg/mL. Data in (A) in collaboration with Dr. Andre Bachmann, Dr. G. Sholler, Helen DeVos Children’s Hospital, Grand Rapids, MI, USA.

NB xenograft studies with DFMO and Etoposide in 2008 by the Bachmann lab and his collaborator Dr. Giselle Sholler, a pediatric oncologist (Helen DeVos Children’s Hospital & Van Andel Institute, Grand Rapids, MI) (Fig. 2) 67 as well as reports by two independent groups using the transgenic TH-MYCN NB mouse model confirmed the effectiveness of DFMO 68, 69. Due to the lack of effective therapies for relapsed/refractory NB patients, the preclinical effectiveness of DFMO, and the well-documented high safety profile of DFMO, Drs. Bachmann and Sholler advanced DFMO/Etoposide to a phase I NB clinical trial (completed in Dec 2012, publication in preparation). In this trial, soluble DFMO is given orally (dissolved in lemonade) allowing patients to take this medicine in the comfort of their homes. Despite significant progress and some promising responses in NB patients, DFMO bears constraints as it is a polar drug with a short serum half-life (2-4 h) 70. In addition, the renal clearance (83%) of DFMO further reduces its efficacy 71. Thus, the availability of DFMO is reduced at the tumor site, which necessitates the repeated administration at high concentrations. Moreover, DFMO exerts mostly cytostatic effects in most cancers and therefore calls for the combination with a cytotoxic drug, for example, Etoposide which showed synergistic effects In vitro and additive effects in vivo (Figs. 1 and 2) 67. Etoposide, a topoisomerase inhibitor is often used in front-line therapy in the treatment of NB. However, Etoposide has poor water solubility, a short biological half-life (~4h), intra- and inter-patient variable bioavailability (25-75%) and associated adverse effects at higher doses 72, 73. The use of DFMO/Etoposide in vivo is currently limited due to the short half-lives (fast elimination/clearance) of both drugs which may explain why antitumor effects in animals were not synergistic as observed in cell cultures (Figs. 1 and 2).

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b) Figure 2. Neuroblastoma xenograft studies. Nude mice were injected with 1 x 107 SMS-KCNR neuroblastoma cells subcutaneously and treated with 1) vehicle, 2) 40mg/kg Etoposide on Day 1 and 30 intraperitoneally, 3) 2% DFMO in drinking water, or 4) the combination of Etoposide and DFMO. Images (right panel) show control animals (top, yellow arrows) and DFMO/Etoposide-treated animals (bottom, green arrows). Data in collaboration with Dr. G. Sholler, Helen DeVos Children’s Hospital, Grand Rapids, MI, USA.

The conventional routes of administration (oral, parenteral) of the drug solution lead to drug distribution throughout the body tissues limiting the availability of the therapeutic drug concentration at tumor tissues

64 | Page and thus results in poor efficacy 74, 75. Therefore, for the first time we propose in this study the targeted co- delivery of synergistically acting DFMO and Etoposide to NB using nanocarriers to overcome the limitations of these drugs. Although the concept of dual drug delivery for cancer therapy is not new, the dual drug delivery using targeted nanocarriers has not been explored so far for NB therapy. Unlike passive nanocarriers, the DFMO- and Etoposide-loaded nanocarriers will be coupled with PEGylated iRGD peptides that specifically recognize the NB overexpressed NRP-1 receptor 76, thus enhancing the specific drug delivery to NB tumors while sparing normal cells.

1.7 Synergistic effects of DFMO and Etoposide in vitro and in vivo Dr. Bachmann began first experiments in 2002 with DFMO in NB cells In vitro due to the intriguing MYCN-ODC connection in NB 63, 77. Results were encouraging and led to NCI-R01 funding in 2006. Additional investigations confirmed the effectiveness of polyamine inhibitors (DFMO or SAM486A) in NB and explained the underlying molecular mechanisms that are engaged and likely accounting for the observed tumor cell death 78-82. In 2008, Dr. Bachmann teamed up with Dr. Giselle Sholler, a pediatric oncologist, who primarily enrolls relapsed NB patients in her clinical studies. Together, they demonstrated strong evidence for DFMO’s ability to reduce NB tumor burden in xenografted mice (Fig. 2a). Synergistic effects were noted In vitro when DFMO was combined with Etoposide, the latter of which is commonly used in front-line treatment of NB patients (Fig. 1a) 67. These inhibitory effects were mediated via p27- 63 mediated G1 cell cycle arrest (DFMO) as previously published by the Bachmann lab or apoptosis (Etoposide). In vivo, the combination of both drugs resulted in improved suppression of NB tumors in mice (Fig. 2b).

Importantly, similar DFMO studies in mice were confirmed independently by the Hogarty lab (Children’s Hospital of Philadelphia) and by the Cleveland lab (St. Jude Children’s Research Hospital/Scripps Florida) using the transgenic TH-MYCN NB mouse model 68, 69, thus further confirming the validity of the ODC drug target and the effectiveness of DFMO in NB. Also of note, synergistic effects of DFMO/Etoposide were earlier reported by the Gerner lab at the University of Arizona in leukemic cells 83.

1.8 Combination chemotherapy nanocarriers against multi-drug resistant (MDR) cancer Multifunctional nanocarriers co-delivering combinations of chemotherapy agents and chemo-sensitizing agents have been shown to be successful in reversing MDR both in vitro and in vivo 84, 85. The two underlying mechanisms through which cancer cells acquire MDR to multiple structurally and mechanistically different drugs, among the many cellular mutations that diminish the effectiveness of anticancer drugs, are by the over-expression of multidrug transporters and the altered apoptosis cycle 86.

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MDR that are transporter-dependent have an up-regulated level of transmembrane drug efflux pumps, part of the ABC-superfamily that actively export drugs to reduce their effective intracellular concentration. Many anticancer drugs are affected by these transporters 86. For example, the ATP-driven P-gp, is overexpressed in liver, pancreatic, ovarian and gastrointestinal cancers, and readily pumps out DOX , PTX, and Vinblastine 86. Pro-survival mutations such as the deregulation of a human proto-oncogene located on chromosome 18, BCL2, and nuclear factor kappa B (NF-kB), found in apoptotic pathway-dependent MDR, enable cancer cells to tolerate drug-inflicted injuries and significantly decrease their apoptotic response 86- 92. A number of chemo-sensitizers have been developed to date which inhibit drug-efflux pumps and help to restore the proper apoptotic signaling within cancer cells. The emergence of siRNA as gene therapy has also made possible the silencing of MDR related genes 92. Multifunctional nanopaticles that combine these MDR modulators and cytotoxic drugs have the ability to sensitize MDR cancer cells to the chemotherapeutic payloads.

1.9 Overview of iRGD Peptide as a potential Tumor Target for Neuroblastoma treatment Tumor-specific tissue-penetrating peptides deliver drugs into extravascular tumor tissue by increasing tumor vascular permeability through interaction with neuropilin (NRP). Prototypic tumor-penetrating peptide iRGD (amino acid sequence: CRGDKGPDC) potently inhibits spontaneous metastasis in mice. The anti-metastatic effect was mediated by the NRP-binding RXXK peptide motif (CendR motif), and not by the integrin-binding RGD motif. iRGD inhibited migration of tumor cells and caused chemorepulsion in vitro in a CendR and NRP-1-dependent manner. The peptide induced dramatic collapse of cellular processes and partial cell detachment, resulting in the repellent activity. These effects were prominently displayed when the cells were seeded on fibronectin, suggesting a role of CendR in functional regulation of integrins. The anti-metastatic activity of iRGD may provide a significant additional benefit when this peptide is used for drug delivery to tumors.

2. HYPOTHESIS, OBJECTIVES, AND RATIONALE The objective is to develop a superior, tumor-targeted formulation of DFMO and Etoposide for the treatment of NB. To this end it is hypothesized that the development of stable, iRGD peptide-guided pegylated hybrid nanocarriers will reproducibly target and deliver DFMO and Etoposide to NB tumors and will result in a significant improvement of anticancer activity, reduced adverse side effects and overcoming current constraints associated with high doses and PK parameters. DFMO, a cytostatic drug, is a suiside inhibitor of ornithine decarboxylase (ODC). The activation of the polyamine regulated p27/Rb signaling pathway lead to G1 cell cycle arrest. ODC is directly activated by MYCN that is over-expressed in 45% of high-risk NB patients. Due to this ODC-MYCN connection, it is hypothesized that the down-regulation of

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ODC should lead to the down-regulation of MYNC and overall down-regulation of polyamine biosynthesis. The overall result should be a decrease the NB tumorgenesis as a whole. Etoposide, a cytotoxic topoisomerase II inhibitor drug, will further improve anticancer activity by promoting apoptosis through ALK pathway knockdown. NB cells are kept viable through the ALK pathway even after treatment with DFMO. Both drugs work synergistically together through their respective pathways and should result in significant anticancer activity against NB tumors.

The hypothesis will be tested using two main objectives, with objective one done in two parts. Objective 1A: Preparation and Characterization of stable Hybrid Nanocarriers (HNC) containing DFMO and Etoposide (HNC-D-E). Objective 1B: Conjugation of PEGylated iRGD peptides to stable, fully characterized HNC-D-E Formulation of Objective 1A (iRGD-PEG-HNC-D-E). Evaluation of iRGD-PEG-HNC-D-E nanocarriers. Objective 2: In vitro evaluation of iRGD-PEG-HNC-D-E Formulations against various Neuroblastoma Cell-lines and controls. Evaluation of physiochemical properties of final formulation.

Figure 2a. Illustration of proposed final nanocarrier formulation (iRGD-PEG-HNC-D-E). DFMO and Etoposide drugs (center of yellow sphere) are entrapped within bovine serum albumin (BSA)

67 | Page nanocarrier (yellow sphere) with a chitosan (CS) coating (green shell). Nanocarrier is PEGylated (pink) followed by iRGD peptide (cyclic molecule) conjugation to PEGylated molecule. Final nanocarrier formulation will be iRGD peptide conjugated, PEGylated hybrid chitosan coated bovine serum albumin nanocarrier loaded with DFMO and Etoposide (iRGD-PEG-HNC-D-E).

The innovative aspects of this project include the pegylated iRGD peptide-guided and targeted co-delivery of DFMO and Etoposide. This integrated approach is designed to overcome the current constraints (i.e. short half-life, high clearance and need for high doses) associated with both drugs. If successful, the new targeted formulations will have a high impact with potential advancement to the clinic.

Yu et al. reported the formulation of a stable self-assembled nanogel based on albumin and chitosan 93, 94. In contrast, the proposed DFMO (D) and Etoposide (E) loaded HNC (HNC-DE) will encapsulate the Etoposide in the albumin core and DFMO in the outer chitosan coating, thus enabling the co-delivery of these agents with different physiochemical properties to NB. In addition, the amine groups of chitosan provide flexibility for further conjugation of targeting ligands, and the protonation of amine groups in the acidic environment of tumors will further facilitate uptake 95, 96 as well as endosomal escape of nanocarriers 97.

The endosomal escape of nanocarriers after internalization delivers the synergistically acting drugs into the cytosol hence avoiding the degradation by lysosomes. The cationic nanocarriers with high zeta potential (~35 mV) were found to undergo aggregation by adsorption of plasma proteins 98. The conjugation of polythethylene glycol (PEG, MW 5000 chains) to delivery systems has been well reported to be optimal for increasing half-life and overcome the clearance by the reticuloendothelial system 99. In addition, PEG (MW 5000 chains) conjugation with delivery systems has also been demonstrated to increase salt and serum stability including the prevention of aggregation of cationic nanocarriers 99. Due to the surface curvature attained with PEG coating, the accessibility of the surface to surrounding proteins and the net electrical charge of the PEGylated particles is significantly reduced 100, 101. Therefore, the PEGylation of cationic HNC will help to overcome the in vivo aggregation issues. iRGD peptide anchoring on the surface of HNC will further help in attaining localized and site specific delivery of both the drugs (Fig.1). The co-delivery of multiple drugs via the same nanocarrier has several advantages (targeted delivery of drugs, synergistic therapeutic effects, suppressed drug resistance, and the ability to control drug exposure) compared to delivering a single drug through different co-administered nanocarriers.

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3. LITERATURE REVIEW 3.1 CURRENT NANOCARRIERS AS MULTIFUNCTIONAL DRUG DELIVERY SYSTEMS Nanoparticulate systems such as liposomes, polymeric micelles, polymer–drug nano-conjugates, and dendrimers have led to about two dozen clinically approved therapeutic products 25. These chapters will discuss nanocarriers that have been demonstrated to carry two or more types of therapeutic payloads for the treatment of various cancers. Controlled combinatorial drug delivery share the common aim in promoting synergism-; however, each drug platform has its unique strength and characteristics. The different particle structures, materials, and preparation processes are emphasized in this article to provide design considerations toward developing combinatorial nanoparticulate systems. The structure of most commonly used nanocarrier systems such as liposome, polymeric micelle, polymer–drug nano-conjugate, and dendrimers has been represented in Figure 1. A wide-range of nanocarriers have also been discussed in literature which utilize different physiochemical properties to chemotherapy 102 but this section will mainly focus on multifunctional nanocarriers described earlier103-108.

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3.2 Liposomes Liposomes are spherical vesicles consisting of amphiphilic phospholipid bilayers 109. The most common building blocks for liposomal preparation are phosphatidylcholine and phosphatidylethanolamine with cholesterol being used as a frequent additive to modify the rigidity of the lipid membranes. Liposomal nanocarrier drug delivery systems have been used for the treatment of various diseases, including cancer. Liposomes may also be formed through the rehydration of lipid films to form multilamellar vesicles (MLV), which undergo further mechanical extrusions to form unilaminar vesicles 109. The end structure of this procedure produces a lipid bilayer having an inner aqueous core, with the capability of carrying lipophilic and hydrophilic drugs, respectively. Liposomal drug loading can be accomplished either through active extrusion or through passive diffusion 109. In the active extrusion approach, drugs are suspended along with the phospholipids in aqueous solution. The mixture of MLV and drugs -is then extruded through membranes with a defined pore size to form drug-loaded liposomes 109. Liposomes are first prepared and then mixed with solubilized drugs in the passive diffusion approach. The drug molecules then enter the liposome by diffusion through the lipid bilayers. Liposomes loaded with multiple chemotherapeutic agents can use either active or passive loading schemes for the formulation of combinatorial nanocarriers followed by the removal of the unloaded drug. For example, in the preparation of Cytarabine:Daunorubicin liposome injection (CPX-351), a combinatorial liposome for leukemia treatment, cytarabine is hydrated and extruded with the lipid components yielding cytarabine-loaded liposomes. These liposomes are then incubated with daunorubicin to achieve dual-drug encapsulation 110. CPX-351 will be described in greater detail in the liposome section of this article. Currently liposomes are the only nanocarrier-based combinatorial drug delivery platform that has entered clinical trials 110.

The prevalence of MDR in cancer patients, both prior to treatment and de novo 111, 112, fueled the application of combinatorial chemotherapy to treat cancer as an alternative to increased doses of chemotherapeutics associated with life threatening side effects 113-115.

Chen et al. studied the co-delivery of 3 different siRNA and one miRNA 116. In their study, liposome- polycation-hyaluronic acid nanocarriers (LPH-NP) were developed and targeted by post insertion of DSPE- PEGGC4, the co-delivery of 3 different siRNA and one miRNA was achieved. LPH-NP showed a 80% reduction in tumor volume as compared to control. Their work allowed for the simultaneous study by targeting multiple pathways; proliferation pathways with Cellular-myc (C-myc) siRNA and miR34a miRNA 117, 118, apoptosis with mouse double minute 2 homolog (MDM2) siRNA 119, and angiogenesis using vascular endothelial growth factor (VEGF) siRNA 120. Liposomal co-delivery of apoptosis resistance

70 | Page inhibitor PD0325901 with siRNA against the apoptosis regulator myeloid cell leukemia sequence 1 (Mcl- 1) and the mitogen-activated extracellular kinase (MEK) resulted in significant enhanced tumor growth inhibition as compared to each treatment alone 121. Chen et al. group also developed trilysinoyl oleyamide (trilysine peptide linked to oleyamine by a peptide bond) based PEGylated liposomes for co-delivery of Mcl-1 siRNA and the histone deacytylase inhibitor suberoylanilide hydroxamic acid (SAHA) 122. The PEGylated liposomes were administered i.v. and -showed a significant reduction in tumor growth as compared to SAHA or scrambled siRNA loaded liposomes. Xiao and coworkers did a similar approach by using targeted liposomes to co-deliver DOX and DNA encoding a dominant mutant of survivin for the treatment of lung cancer [66]. The liposomal drug delivery system conjugated truncated basic fibroblast growth factor (tbFGF) peptides, that recognize the bFGF receptor over-expressed in lung cancers, for a targeted approach along with DOX and pDNA encoding for a dominant negative mutant of surviving to counter surviving-mediated apoptosis resistance 123. Co-delivering both chemotherapeutic agents produced an increased therapeutic response against Lewis lung carcinoma tumors –over liposomes with either agent alone.

Saad et al. took a further step in the combination of an anticancer agent with the modulation of drug resistance by formulating peptide-targeted liposomes encapsulating DOX or cisplatin together with oligonucleotides against Bcl-2 and MDR1, two main drug resistance mechanisms of cancer cells 124. The efficacy of combining a targeted chemotherapy with a gene therapy were evaluated using xenografts established from human ovarian malignant ascites 124. Cisplatin or DOX-loaded targeted liposomes, with the inclusion of either Bcl-2 or MDR1 antisense oligonucleotides, decreased primary tumor volume and intraperitoneal metastases load. Tumor growth was further inhibited with targeted liposomes containing DOX or cisplatin, Bcl-2 and MDR1 antisense oligonucleotides together resulting in the complete prevention of the development of detectable intraperitoneal metastases or ascites 124. Saad et al. first proposed this liposomal system as a platform for personalized cancer therapy. These liposomal formulations would contain antisense oligonucleotides targeting individually relevant resistance mechanisms.

Sawant et al. formulated PEGylated liposomes co-loaded with a palmitoyl-ascorbate conjugate and PTX 125. The therapeutic efficacy of co-delivering both agents against 4T1 mammary carcinoma was evident at 10mg/kg as compared to PTX or palmitoyl-ascorbate-loaded liposomes alone. The liposomal formulation, Atu027, was developed by Silence Therapeutics, London, UK and showed promising results in neuroendocrine and breast cancer patients during phase 1 clinical trials126. The liposomal formulation contains siRNA against protein kinase N3, a downstream effector of the mitogenic PI3K/PTEN pathway involved in prostate cancer metastasis 127, 128. Atu027 was composed of 2-O-methyl-stabilized siRNA

71 | Page encapsulated in cationic liposomes (50mol% cationic lipid-Larginyl-2,3-L-diaminopropionic acid-N- palmitoyl-N-oleylamidetrihydrochloride (AtuFECT01), 49mol% co-lipid 1,2-diphytanoyl-sn-glycero-3- phosphoethanolamine (DPhyPE), and 1 mol% DSPE-PEG2000) 128. This formulation showed tumor regression during phase I clinical trials and –has entered phase II clinical trials with a focus on breast cancer patients 129.

Dai et al. co-delivered an antiangiogenic and anticancer agent using targeted PEGylated liposomes 130. The combinatorial delivery of the antiangiogenic agent, combrestin A-4 in the lipid bilayer, and the anticancer drug, DOX in the aqueous core, resulted in increased therapeutic efficacy against breast cancer cells. Hu et al. also combined liposomal delivery of honokiol with irradiation for maximal therapeutic efficacy against lung cancer 131. It was hypothesized that the co-delivery of this formulation would combine the destruction of tumor cells by irradiation followed by the inhibition of irradiation-induced neo-angiogenesis by honokiol 132. These PEGylated honokiol-loaded and radiotherapy showed an increase in survival of Lewis lung carcinoma-bearing mice as compared to honokiol or radiotherapy liposomes alone. The formulation resulted in an overall decrease of angiogenesis in vivo 130. Maitani et al. followed a similar approach and also combined an anticancer agent with an antiangiogenic agent. Maitani et al. co-loaded irinotecan, the anticancer agent, and sunitinib, antiangiogenic agent within liposomes for the treatment of pheochromocytoma neuroendocrine tumors in vivo 133. The co-delivery of both agents showed higher therapeutic effectiveness within tumors versus administration of sunitinib liposomes plus irinotecan liposomes alone. The co-delivery of both agents in a liposome also had higher drug accumulation at the site of action as compared to free drug. Similarly, folate-targeted DOX-loaded liposomes co-loaded with a bi-functional peptide capable of vascular disruption and antitumor activities were more effective against KB human nasopharyngeal carcinoma in vivo than untargeted co-loaded liposomes than either monotherapy 134. RGD-targeted liposomes co-loaded with DOX and the vascular disrupting drug combrestatin A-4 increased tumor regression of B16F10 melanoma compared to untargeted co-loaded liposomes or targeted liposomes with either drug 135.

As mentioned earlier, CPX-351, a liposomal formulation developed by Celator Pharmaceuticals Inc. (Princeton, NJ) co-loaded with cytarabine and daunorubicin (5:1 molar ratio), was found to be effective in the treatment of acute myeloid leukemia (AML) 136-139. The same company co-loaded the weakly acidic drug, 5-fluoroorotic acid and the amphiphatic drug, irinotecan (CPT-11) at a 5:1 ratio within PEGylated liposomes. These drugs showed synergism with increased therapeutic efficacy than free drug cocktails in vivo 139, 140. Liposomes were first prepared before active loading of CPT-11 by a pH gradient method, with protonated CPT-11 being retained in the liposomes after complex formation with 5-fluoroorotic acid. An

72 | Page increase in mice survival was observed when treated with co-loaded liposomes as compared to the combination with separate liposomes. However, the therapeutic efficacy was –less than with liposomes loaded with 5-fluoroorotic acid only. It may be because the 5-fluoroorotic acid content had to be lowered for CPT-11 co-loading. This further demonstrates the difficulty of reproducing a synergy with liposomes relative to free drugs. CPX-351 has been tested in phase I trial with acute leukemia patients with the 5:1 ratio being maintained in plasma for 24 h. CPX-351 induced complete responses in 9 out of 43 patients during these trials 140. Celator Pharmaceuticals also developed CPX-1, a liposomal formuulation co-loaded with irinotecan and floxuridine agents (1:1 molar ratio). CPX-1 is currently in phase I clinical trials with the drug ratio of 1:1 being maintained in plasma for up to 12 h after infusion. Phase I trials showed a positive clinical response in patients with colorectal cancer when treated with CPX-1 141. It should be noted that the high therapeutic efficacy of liposome encapsulating two anticancer drugs was always correlated with the maintenance of their synergistic molar ratio in plasma and therapeutic efficacy in preclinical and 141 as well as clinical studies 138, 140, 141 which indicates that the optimization of drug loading and liposomal stability are essential for effective combination therapy. Falcao et al. co-delivered the Bcl-2 antisense oligodeoxynucleotide G3139 and the pro-apoptotic peptide D-(KLAKKLAK)-2 142. The research group used the electrostatic properties of the therapeutic molecules to their advantage. The authors formulated a negatively charged complex between G3139 and the peptide before mixing with the positively charged liposomes. Co-loaded liposomes were then injected intratumoral leading to enhanced tumor growth suppression as compared to liposomes containing a single agent and free drug.

Bajelan et al. co-encapsulated stealth nanoliposomes containing PSC 833 (Valspodar), an efficient MDR modulator, and DOX in order to increase the effectiveness and decrease adverse effects of the anticancer drug 143. Different methods for liposome preparation were tested in an attempt to increase the encapsulation efficiency of both therapeutic agents with different parameters such as drug to lipid molar ratio, cholesterol mole percent and lipid compositions, being investigated. The final formulation had a lipid composition of egg phosphatidylcholine (EPC):disteroylphosphoethlamine (DSPE)-PEG2000:cholesterol (60:5:30 %mol) that was prepared by the thin layer film hydration method. Empty liposomes were fist prepared with DOX and PSC 833 loaded after using ammonium sulfate gradient and remote film loading methods, respectively. An In vitro cytotoxicity study of various liposomal formulations as well as drugs, solutions against theresistant human breast cancer cell line, T47D/TAMR-6, were evaluated using MTT assay. The best formulation showed a narrow size distribution with average diameter of 91.3 ± 0.2 nm with zeta potential of -6 ± 1.2, and with the encapsulation efficiency for DOX and PSC 833 - more than 95% and 65.5%, respectively. In DOX-resistant T47D/TAMR-6 cells, dual-agent stealth liposomes showed significantly greater cytotoxicity (P < 0.05) than free DOX and liposomal DOX plus free PSC 833 treatments. Cell

73 | Page viability assays of dual-agent stealth liposomes showed an approximate 60% decrease as compared to the control with free DOX and PSC 833 solutions displaying a 40% decrease in cell viability. Co-encapsulation of DOX and PSC 833 presents a promising anticancer formulation, capable of effective reversal of drug resistance, and should be explored further in therapeutic studies with animal tumor xenograft models.

Finally, the co-delivery of magnetic fluid hyperthermia and photodynamic therapy liposomes144 using magnetic fluid and zinc phthalocyanine as the photosensitizer demonstrated superior activity In vitro of combined light and magnetic stimuli over their separate applications 145. This approach suggests a new treatment modality for enhanced tumor therapy.

3.3 Polymeric micelles Micelles are colloidal particles with a size of about 5–150 nm that consist of self-assembled aggregates of amphiphilic molecules or surfactants 146. At low concentrations these amphiphiles may exist as unimers in aqueous media 146. As the concentration increases, thermodynamic processes drive the formation of aggregates. These aggregates sequester hydrophobic regions into the core surrounded by a hydrophilic corona or shell. The critical micelle concentration (CMC) is the concentration at which aggregation occurs. Pharmaceutical formulations use low molecular weight surfactants (i.e. polysorbates, sodium dodecyl sulfate, etc.) with relatively high CMCs in the range of 10−3 to 10−4M, primarily as excipients to increase the aqueous solubility of poorly water soluble drugs 146. The core of these micelles encapsulate hydrophobic drugs which also associate with the hydrophobic regions of the micelle. However, after administration, dilution of a given pharmaceutical formulation occurs rapidly, and as the micelle concentration drops below its CMC, its stability will be compromised 146.

Work by Kataoka 147, Kabanov 148, and authors demonstrated the potential use of amphiphilic polymers as drug carriers. As described earlier, the polymeric micelles are mostly composed of block-copolymers with a hydrophobic and hydrophilic constituent that self-assemble into a hydrophobic core surrounded by the hydrophilic shell (Fig. 1)3. Micellar unimer units can be assembled in a variety of ways, such as- A–B diblock copolymers, A-B-A triblock copolymers, and grafted copolymers. One of the major advantages to using polymeric micelles, as compared to the traditional low molecular weight surfactant derived systems, is their increased stability. Polymeric micelles commonly exhibit CMCs in the 10−6 to 10−7M range 149. The ideal polymeric micelle should display the following-: higher drug loading ability, controlled drug release, and suitable biological compatibility and stability. The characteristics and lengths of the hydrophilic and hydrophobic block polymers primarily determine the physiochemical properties of the polymeric micelles. The most commonly utilized hydrophilic polymer is Polyethylene glycol (PEG). Due to PEG’s highly

74 | Page hydrated nature, it is able to resist uptake by the reticuloendothelial system (RES) 149. There are a number of other hydrophilic polymer chemistries currently being applied for this very reason-: poly(N-vinyl-2- pyrrolidone) (PVP) 150, poly(vinyl alcohol) (PVA) 151, and poly(ethyleneimine) (PEI) 152. PEG remains the polymer of choice due to its widespread acceptance and availability. The hydrophobic core of the polymeric micelles uses a large variety of hydrophobic block polymers, - which include- propylene oxide, L-lysine, caprolactone, D,L-lactic acid, styrene, aspartic acid, β-benzoyl-Laspartate, and spermine among others 153. More hydrophobic unimers, such as styrene, tend to form micelle cores spontaneously, whereas less hydrophobic unimers (i.e. lysine) will first interact via electrostatic interactions with hydrophobic drug molecules, before formation of a micelle 154. CMC tends to depend more on the type and length of the hydrophobic block, with lower CMCs associated with greater hydrophobicity and increased hydrophobic block length 155, 156.

The majority of polymer micelles investigated -form no covalent bond between the drug and the micellar carrier, as polymer drug conjugates do, and technically cannot be classified as conjugates. There are, however, a number of polymeric micelles where the therapeutic agent is covalently bound to the hydrophobic chains in the micelle core. For example, work by Mikhail et al. focused on poly-(ethylene glycol)-b-poly(ε-caprolactone) polymeric micelles containing chemically conjugated DTX 157. Cationic ring-opening polymerization was implemented to first synthesize PEG-b-polycaprolactone (PCL). Once polymerization was complete, the terminal hydroxyl of PCL was reacted with succinic anhydride to form a terminal carboxylic acid. The terminal end was - subsequently coupled to 2’ hydroxyl of the therapeutic agent, DTX, a potent anti-mitotic chemotherapy agent. The conjugated DTX coupled to its hydrophobic block polymer resulted in higher drug loading as well as increased stability which was evident by a reduced release rate of DTX from the hydrophobic core.

Polymeric micelles are undergoing continued advances in the nanotechnology field. A trend has been shown towards the development of “smart” polymeric micelles, - with their ability to recognize and target specific tissues and their response to various biological stimuli, characteristics which -have been elaborated on –in the section dealing with polymeric targeting -. Another use of polymeric micelles involves the formation of poly-ion complex (PIC) micelles, wherein the micelle core is composed of a polycation block, for the delivery of negatively charged DNA or small interfering RNA (siRNA) 158, 159. Polymeric micelles based on N-(2-Hydroxypropyl)-methacrylamide (HPMA) copolymers have also been described. Poly HPMA can be generated either with the hydrophilic block comprising the shell 160-163 or as the hydrophobic core after chemical modification 164, 165. Poly HPMA micelles have shown to encapsulate a variety of

75 | Page hydrophobic drugs; however, the majority of the data on the activity of these systems to date have been obtained In vitro 165-167 and more in vivo data is needed to ascertain their potential as carriers.

Lee et al. employed cationic micellar nanocarriers as carriers to co-deliver PTX and Herceptin for achieving targeted delivery of PTX to human epidermal growth factor receptor-2 (HER2/neu)-overexpressing human breast cancer cells, and enhanced cytotoxicity through synergistic activities 168. PTX-loaded nanocarriers had an average size less than 120 nm and a zeta potential of about 60 mV. Herceptin was complexed onto the surface of the nanocarriers. The drug-loaded nanocarrier/Herceptin complexes remained stable under physiologically-simulating conditions with sizes at around 200 nm. Their formulated nanocarriers delivered Herceptin much more efficiently than BioPorter, a commercially available lipid-based protein carrier, and displayed a much higher anti-cancer effectiveness. Lee et al. Daily treatment, twice-repeated, with Herceptin showed significantly higher cytotoxicity especially in HER2-overexpressing breast cancer cells when compared to single treatment. Anticancer effects of this co-delivery system was investigated in human breast cancer cell lines with varying degrees of HER2 expression level, namely, MCF7, T47D and BT474 168. The co-delivery of Herceptin increased the cytotoxicity of PTX and this enhancement showed a dependency on their HER2 expression levels. Targeting ability of this co-delivery system was demonstrated through confocal images, which showed significantly higher cellular uptake in HER2-overexpressing BT474 cells as compared to HER2-negative HEK293 cells. This co-delivery system may have important clinical implications against HER2-overexpressing breast cancers 168.

An advantage of polymeric micelles as compared to other polymeric drug carriers is their relative ease of fabrication, due to their inherent self-assembly properties. This has resulted in a number of polymeric micelles currently under clinical investigation 169. However, further investigations are warranted to explore the use of micellar systems to co-deliver the chemotherapeutic agents.

3.4 Poly(lactic-co-glycolic acid)-based nanocarriers Poly(lactic-co-glycolic acid) (PLGA) is one of the most successfully developed biodegradable polymers 170. Various polymers developed may be used to formulate polymeric nanocarriers-; however, PLGA has attracted considerable attention due to its properties: (I) biodegradability and biocompatibility, (II) FDA and European Medicine Agency approval in drug delivery systems for parenteral administration, (III) well described formulations and methods of production adapted to various types of drugs e.g. hydrophilic or hydrophobic small molecules or macromolecules, (IV) protection of drug from degradation, (V) possibility of sustained release, (VI) possibility to modify surface properties to provide –stealthiness and/or better

76 | Page interaction with biological materials and (VII) possibility to target nanocarriers to specific organs or cells 170.

Schleich et al. developed dual PTX/superparamagnetic iron oxide (SPIO)-loaded PLGA-based nanocarriers for a theranostic purpose (Fig. 2). Their formulation produced nanocarriers with a spherical morphology and a size of 240 nm. The PTX and iron loading were 1.84 ± 0.4 and 10.4 ± 1.93 mg/100 mg, respectively 5. Relaxometry studies and phantom MRI demonstrated their efficacy as T2 contrast agent. Co-loaded PLGA-based nanocarriers showed significant cellular uptake by CT26 colon carcinoma cells executed by Prussian blue staining and fluorescent microscopy. While SPIO did not show any toxicity in CT26 cells, PTX-loaded nanocarriers displayed cytotoxic activity. PTX-loaded nanocarriers, at a concentration of 5 mg/kg, with or without co-encapsulated SPIO induced in vivo a regrowth delay of CT26 tumors (colon carcinoma) 5. Together these multifunctional nanocarriers may be considered as future nano-medicine for simultaneous molecular imaging, drug delivery and real-time monitoring of therapeutic effectiveness within patients.

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Figure 3.1 Schematic representation of SPIO/PTX-loaded PLGA-based nanocarriers. Reprinted with permission from ref. 4, N. Schleich, P. Sibret, P. Danhier, B. Ucakar, S. Laurent, R. N. Muller, C. Jerome, B. Gallez, V. Preat, and F. Danhier, Dual anticancer drug/superparamagnetic iron oxide- loaded PLGA-based nanocarriers for cancer therapy and magnetic resonance imaging. Int. J. Pharm. 447, 94-101 (2013). CopyrightatElsevier.

Zhu et al. report a strategy to make use of PLGA nanocarriers (PLGA NPs) for co-delivery of docetaxel (DTX) as a model anticancer drug together with d-alpha-tocopheryl-co-poly-(ethylene glycol) 1000 succinate (TPGS) (Fig. 3) 5. Vitamin E TPGS plays a role as a pore-forming agent in the nanocarriers which may result in smaller particle size, faster drug release and a higher drug encapsulation efficiency. It also acts a bioactive agent that may inhibit P-gp to help overcome MDR of cancer cells. DTX-loaded PLGA NPs were prepared by the nanoprecipitation method, encapsulating 0, 10, 20 and 40% TPGS and then characterized for size and size distribution, surface morphology, physical status and encapsulation efficiency of the therapeutic agent in the nanocarriers. It was found that all four formulations had a size ranging from 100-120 nm and entrapment efficiencies between 85-95% with a drug loading level around 10%. In vitro evaluation showed that the 48 h IC50 values of free DTX and the DTX-loaded PLGA NPs of 0, 10, 20% TPGS were 2.619 and 0.474, 0.040, 0.009 μg/mL respectively, which means that PLGA NPs formulations could be 5.57 fold more effective than free DTX. Also, DTX-loaded PLGA NPs of 10 or 20% TPGS were 11.85 and 52.7 fold more effective than DTX-loaded PLGA NPs containing no TPGS (therefore, 66.0 and 284 fold enhanced effectiveness than the free DTX alone). Nude mice with HeLa cell xenograft tumor model and immuno-histological staining analysis further confirmed the advantages of the strategy of co-delivery of anticancer drugs with TPGS utilizing PLGA NPs 6.

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Figure 3.2 Schematic graph of TPGS functions as a pore former and promotes anti-tumor activity of DTX-loaded Nps. Reprinted with permission from ref. 5, H. Zhu, H. Chen, X. Zeng, Z. Wang, X. Zhang, Y. Wu, Y. Gao, J. Zhang, K. Liu, R. Liu, L. Cai, L. Mei, and S.-S. Feng, Co-delivery of chemotherapeutic drugs with vitamin E TPGS by porous PLGA nanocarriers for enhanced chemotherapy against multi-drug resistance. Biomaterials. 35, 2391-400 (2014). CopyrightatElsevier.

Wang et al. reported core-shell nanocarriers that were doubly emulsified from an amphiphilic copolymer methoxy poly(ethylene glycol)-poly(lactide-co-glycolide) (mPEG-PLGA). These mPEG-PLGA nanocarriers offered advantages as described earlier; they were easy to fabricate by the improved double emulsion method, biocompatible, and showed high loading efficacy 6. The mPEG-PLGA nanocarriers were formulated to co-deliver hydrophilic DOX and hydrophobic PTX (Fig. 4). Co-loaded nanocarriers possessed a lower polydispersity of 0.1, indicating the controlled size distribution of nanocarriers. . Studies on drug release and cellular uptake of the co-loaded system demonstrated that both drugs were effectively internalized and released drugs simultaneously in the cells. Furthermore, the co-loaded nanocarriers suppressed tumor cell growth significantly, as compared to - the delivery of either free DTX or PTX at the same concentrations, indicating a synergistic effect. Moreover, the nanocarriers loading drugs with a DTX/PTX concentration ratio of 2:1 showed the highest antitumor activity against three different types of tumor cells-: A549 human lung cancer cells, B16 mouse melanoma cells and HepG2 human hepatocellular carcinoma cells. These mPEG-PLGA nanocarriers may have potential in clinical implications for co- delivery of multiple anti-tumor drugs with different properties 171.

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Figure 3.3 Illustration of biodegradable amphiphilic copolymer NPs loaded with both DOX and TAX using improved double emulsion method. Emulsification procedure used to generate double emulsions. Step (I), generating water-in-oil for encapsulations of DOX; Step (II), generating water- in-oil-in-water for encapsulations of TAX. Green represents the oil phase containing amphiphilic copolymer and red the aqueous phase containing DOX. Reprinted with permission from ref. 6, H. Wang, Y. Zhao, Y. Wu, Y.-l. Hu, K. Nan, G. Nie, and H. Chen, Enhanced anti-tumor efficacy by co- delivery of doxorubicin and paclitaxel with amphiphilic methoxy PEG-PLGA copolymer nanocarriers. Biomaterials. 32, 8281-90 (2011). CopyrightatElsevier.

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Roy et al. reported better tumor regression and enhancement of antitumor immune response at the tumor microenvironment by co-delivering PTX and a toll-like receptor-4 (TLR4) agonist using a PLGA based nanocarrier preparation (TLNP) 172. TLR agonists have shown to activate macrophages and dendritic cells to generate an antitumor immune response. TLR also plays a very crucial role -in inducing both innate and adaptive immune response against cancer. The PLGA based nanocarriers entrapping both therapeutic agents had a mean diameter of 255 nm with a polydispersity index of less than 0.1. Particle characterization showed high encapsulation of PTX and TLR4, 87.43% and 62.14% respectively, with retention of their biological activities. In vivo tumor regression studies demonstrated the clear benefit of TLNP over free PTX and TLR4. B16-F10 melanoma cells were inoculated into the right flank of 6 to 8- week old C57BL/6 mice. The mean tumor weight of the TLNP treated animals was found to be 0.68 g, whereas that of PTX alone treated animals was 1.8 g. Survival of the TLNP- treated tumor- bearing mice was also found to be significantly higher than that of PTX treated animals. 70% of tumor- bearing mice treated with TLNP survived 30 days after treatment, whereas only 50% of PTX- treated and 30% of TLR4 agonist- treated mice survived 30 days post-treatment. These data suggest that combined chemo-immunotherapy with TLNP had better anticancer efficacy as compared to commercial PTX. In vivo results are promising and could pave the way for novel chemo-immunotherapeutic treatment -modalities.

3.5 Mesoporous silica-based nanocarriers (MSNPs) Kresge et al. 173 described the means of combining sol-gel chemistry with liquid-crystalline templating, creating a new class of ordered porous molecular sieves characterized by periodic arrangements of uniformly sized mesopores (defined by IUPAC as pores with diameters between 2 and 50 nm) incorporated within an amorphous silica matrix 173. The controlled synthesis of spherical and other shaped mesoporous silica nanocarriers (MSNPs) has since been achieved using solution routes or an aerosol based evaporation- induced self-assembly (EISA) process 174, 175, with surfaces of the pore being modified with a wide range of chemical moieties based mainly on silane coupling chemistries. In any case, a successful biocompatible nanocarrier must exhibit low toxicity, size uniformity, large capacity for diverse cargos, high traceability, colloidal stability, selective cell-specific binding and internalization, and triggered cargo release 174, 176.

Ma et al. described a hollow mesoporous silica nanocarrier (HMSNP) based targeted drug/siRNA co- delivery system, aimed at overcoming MDR in ovarian cancer cells 173. Perpendicular nanochannels connecting to the internal hollow cores were formed within the HMSNPs, facilitating drug loading and release. It was shown that the extra volume of the hollow core enhances the drug loading capacity by almost two fold as compared with conventional MSNP. The surface of the HMSNPs were coated with folic acid

81 | Page conjugated to polyethyleneimine (PEI-FA) under neutral conditions using electrostatic interactions between the phosphate groups on the HMSNP surfaces and the partially charged amino groups of PEI-FA, thereby blocking the mesopores and preventing leakage of the loaded drugs. Folic acid not only prevents drug leakage but also acts as a target ligand that allows HMSNP selective binding and internalization in the cancer cells. HMSNPs coated with PEI-FA showed enhanced siRNA binding capability on account of electrostatic interactions between the amino groups of PEI-FA and siRNA, as compared with that of conventional MSNPs. This electrostatic interaction helped to achieve the pH-controlled release of loaded drugs. In vitro pH-responsive drug/siRNA co-delivery experiments were conducted with two cancer cell lines-, HeLa cervical cancer cell lines having higher folic acid receptor expression and MCF-7 breast cancer cell lines with lower folic acid receptor expression. The pH-responsive intracellular drug/siRNA release greatly minimizes the prerelease and possible adverse side effects of the delivery system and its payloads. The co-delivery of DOX and siRNA against the Bcl-2 protein into HeLa cells was achieved via folic acid receptor mediated endocytosis. It was shown that the expression of the anti-apoptotic protein Bcl-2 was successfully suppressed, leading to enhanced therapeutic efficacy of DOX. Thus, the multifunctional nanocarrier shows promising potentials for controlled and targeted co-delivery of drug and gene in cancer treatment 173.

Meng et al. used a similar technique involving both chemo and gene therapy to effectively overcome MDR in human breast cancer xenografts. Meng et al. developed a MSNPs co-loaded with DOX and siRNA that targets the P-gp 174. For the selection of the siRNA that targets P-gp, among a series of drug resistant targets, high throughput screening was performed in a MDR breast cancer cell line, MCF-7/MDR. Formulated MSNPs displayed a size of 50nm with conjugation to polyethyleneimine-polyethylene glycol (PEI-PEG) copolymer. This conjugation protected the co-delivery of bound DTX and P-gp siRNA to the tumor site in MCF-7/MDR xenograft model. The effective biodistribution and reduced reticuloendothelial uptake, as a result of the MSNPs design, allowed Meng and coworkers to achieve an 8% enhanced permeability and retention effect at the tumor site. The co-delivery of both therapeutic agents resulted in synergistic inhibition of tumor growth in vivo as compared to free DTX or MSNPs loaded with either drug or siRNA alone. Multiple analysis of xenograft biopsies revealed significant P-gp knockdown at heterogeneous tumor sites. These regions correspond to the intracellular release of DTX and induced apoptosis. Meng and coworkers emphasized that the heterogeneity originates in the tumor microenvironment, which influences the vascular access, rather than heterogeneous P-gp expression in the MDR cells 174. Similar to Ma et al., these data provide proof-of-principle testing for the use of a dual drug/siRNA loaded nanocarriers to overcome MDR in a xenograft model. This study also provided the first detailed analysis of the impact of heterogeneity in the tumor microenvironment on the efficacy of siRNA delivery in vivo 174.

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MSNPs can have an array of multifunctional modular designs, suggesting that the next generation of nanocarriers will have multicomponent cargos that deliver their payload to target cells through the active recruitment of targeting ligands combined with biologically triggered responses that actuate molecular valves. The combination of molecular machines and increasingly complex and biomimetic supported lipid bilayers, -such as those derived from red blood cells, may allow unprecedented engineering of nanocarrier/cellular interactions and provide a universal platform for theranostics and personalized medicine.

3.6 Polymer-drug nano-conjugates Polymer–drug nano-conjugates -are the chemical conjugation of the therapeutic drug and polymer by a covalent bond. Polymer–drug nano-conjugates -have been widely explored for delivery of anticancer drugs for the treatment of various cancers 177. One of the major advantages of polymer-drug nano-conjugates is the ability to escape filtration from the kidneys, resulting in increased blood circulation time. Increased blood circulation times allow for anticancer conjugates-to accumulate at the site of action, the tumor, by taking advantage of the EPR effect 177. However, polymer-drug conjugates must also eventually be eliminated from the body to avoid any potential long term adverse side effects -the drug or polymer may elicit. Incorporating biodegradable systems allows for these conjugates, of a sufficient size, to - evade renal filtration - while allowing subsequent degradation and elimination from the body. These conjugates should have degradation rates slow enough to allow adequate biodistribution and accumulation at the site of action. The degradation of these conjugates should also result in the production of non-toxic degradation products that are eliminated from the body. A number of biologically degradable bonds have been described (Fig. 5A). The biodegradation of these conjugates usually occurs via hydrolysis, enzymatic cleavage, or reductive degradation. Some biodegradable polymers have been studied 178, 179 and include- poly-α-amino acids such as poly(L-lysine) 180, poly(L-glutamic acid) 181, and poly((N-hydroxyalkyl)glutamine) 182 as well as carbohydrate polymers such as dextrins 183, hydroxyethylstarch (HES) 184, polysialic acid 185, and the polyacetal Fleximer® 186.

OPAXIOTM (formerly branded XYOTAX) is a biodegradable polymer-drug nano-conjugate currently under phase III clinical development in the United States. OPAXIOTM is a conjugate of poly(L-glutamic acid) and the anticancer drug PTX 187. The selection of poly(L-glutamic acid) was based on the biodegradation to L- glutamic acid which can then enter normal cellular metabolism. PTX was conjugated via an ester bond to the γ-carboxylic acid side chains of poly(L-glutamic acid). Due to the conjugation via the 2’ hydroxyl of PTX, the conjugate is unable to bind tubulin and elicit a pharmacological response, rendering it inactive. In

83 | Page one particular example, the poly(L-glutamic acid) conjugate, having a molecular weight of 48 kDa and containing approximately 37% PTX by weight, -maintains water solubility. During preclinical investigation of this formulation, the conjugate demonstrated a higher maximum tolerated dose (MTD) and was more efficacious than PTX formulated in Cremophor EL/ethanol alone. Phase III clinical trials 188-192 are still evaluating OPAXIO™ within prostate, breast, ovarian, colorectal, and lung cancer patients.

Biodegradable derivatives are being explored for more commonly used polymers such as PEG and HPMA copolymers. Biodegradable multi-arm PEGs containing ester bonds between PEG chains have entered clinical trials 193. -Research has also been done to see if biodegradable polymers consisting of small molecular weight PEG blocks can be linked together via enzymatically cleavable oligopeptide groups while linked to DOX 194. Ulbrich et al. utilized a variety of -approaches to synthesize biodegradable HPMA copolymer-drug conjugates. Such approaches include graft systems containing oligopeptide sequences and/or reductive disulfide bonds 195, and the generation of biodegradable star HPMA copolymer-drug conjugates 196. In a similar technique, poly-(amido amine) (PAMAM) dendrimers were modified with poly- HPMA grafts via enzymatically cleavable or reducible linkers. This allowed for degradation of the high molecular weight polymer. These star polymer conjugates displaying DOX showed prolonged blood circulation, increased tumor accumulation, and anti-tumor efficacy in lymphoma tumor bearing mice 197.

Biodegradable multiblock poly(HPMA) conjugates were also generated via a combination of RAFT polymerization and click chemistry 7, 198. The synthesis of multiblock poly-(HPMA) was performed in three major steps (Fig. 5B). RAFT polymerization of HPMA was first performed using an enzyme-sensitive, Gly-Phe-Leu-Gly containing chain transfer agent with a terminal alkyne. Following polymerization, a post- polymer modification was performed to introduce a terminal azide, resulting in an α-alkyne, ω-azido- telechelic poly-(HPMA). In the final step, a biodegradable multiblock poly-(HPMA) was synthesized by click chemistry in the presence of a copper catalyst. It was shown that the end product, multiblock poly- (HPMA), had a molecular weight of 291 kDa and a polydispersity index of 1.11. Upon incubation with model lysosomal enzymes, poly-(HPMA) segments of similar molecular weights (42 kDa) were formulated 198. These results demonstrate how advances in chemistry (i.e. RAFT polymerization and click chemistry) can be utilized to synthesize newer biodegradable polymer-drug conjugates with well-defined physicochemical properties. The polymer–drug conjugate and its derivatives can then be implemented for the co-delivery of multiple drugs.

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Wang et al. demonstrated the potential use of polymer-drug conjugates for combinatorial chemotherapy 199. Their research group combined the bioactivities of both oxaliplatin and demethylcantharidin (DMC) and co-delivered them via a polymer-drug conjugate system. It has been shown that oxaliplatin was released from the polymer-drug conjugate within cancer cell by reduction to attack nuclear DNA 199. At the same time, a dose of DMC was hydrolyzed which block DNA damage-induced defense mechanisms by serine/threonine phosphatase 2A inhibition. In vitro studies showed that the polymer-drug conjugate with dual modes of action displayed increased cytotoxicity against SKOV-3 ovarian cancer cells than that of free oxaliplatin and DMC. The enhanced cytotoxicity of this polymer-drug conjugate was attributed to the synergistic effect between oxaliplatin and DMC, as well as the effective intracellular internalization of the micelles observed by confocal laser scanning microscopy (CLSM) imaging.

3.7 Dendrimer based nanocarriers

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Dendrimers are branched polymeric macromolecules forming a star-like structure. Dendrimers’ unique structures allow conjugation of drugs to the surface, allowing for maximization of the potential of biological interactions. The synthesis of dendrimers can be done with a wide variety of chemistries, where the core, monomer units, and surface functionality determine the physiochemical characteristics 200. The most important factor in formulating dendrimers for drug delivery applications is their biocompatibility. Other physiochemical properties to be considered are-: solubility, surface group functionality, surface charge density, and stability of the dendrimers. Tomalia et al. first described the synthesis of PAMAM dendrimers in 1985 201, 202. Synthesis of dendrimers for each “generation” was performed in a step-wise fashion (Fig. 6B) resulting in dendrimers having precisely defined structures. As each synthetic step proceeds forward, increase in the generation resulted in a linear increase in radius and an exponential increase in surface groups 203. For example, for the synthesis of PAMAM dendrimers an ethylenediamine core is first generated which is then followed by a subsequent half-generation addition by reaction with methyl acrylate. Ethylenediamine is used for the final and complete generation reaction step before PAMAM dendrimers are produced (Fig. 6C). This precision in synthetic production is one of the major advantages of dendrimers, as compared to most linear polymers. The end product of these reactions often yields mono-dispered structures having polydispersity indices (Mw/Mn) of less than 1.05 204. Another advantage dendrimers exhibit -is the large number and density of functional groups displayed on their surface. These functional groups provides opportunities for conjugation of drugs 205, 206, targeting moieties 207, imaging agents 208, etc. (Fig. 6B).

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Much work with dendrimers focuses on their use for the encapsulation and formulation of drugs 209. Dendrimers often possess open cavities between adjacent branches of their hyper branched structure. These cavities allow for the encapsulation of drugs 210 and –have been found to improve the solubility of poorly soluble drugs. In addition, drugs which have been formulated with dendrimers (physically mixing) have been investigated as both transdermal 211 and oral 212 delivery systems. It has also been investigated that dendrimers with positively charged surface functionalities, such as PAMAM and poly-(ethyleneimine) dendrimers, may act as gene carriers 213, due to their ability to complex with negatively charged DNA.

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The covalent attachment of drugs to dendrimers has been widely investigated 207-211. Many chemotherapeutic agents have been attached to the surface of dendrimers to help increase - the drug’s aqueous solubility and to provide specific delivery to tumor tissues. Multifunctional drug delivery platforms have been investigated that utilize dendrimers conjugated with imaging agents, drugs, and targeting moieties 207. As described earlier, the synthesis of such conjugates begins with the ethylenediamine initiator core accompanied by repeated addition of methyl acrylate followed by subsequent methyl ester condensation with ethylenediamine to produce increasing generation PAMAM dendrimers (Fig. 6C). The resulting generation 5 (G5) dendrimer showed 128 primary amino groups on its surface. This will provide ample opportunity for further modification of the dendrimer’s surface. In an effort to improve biocompatibility, partial acetylation of the primary amino groups has been conducted in order to reduce the positive surface charge. The reaction was then followed by formation of a thiourea bond with fluorescein isothiocyanate (FITC) to enable In vitro imaging 208. PAMAM dendrimers were conjugated with folic acid, a targeting moiety, through the reaction of surface primary amines using an activated ester derivative of folic acid. The remaining primary amines were transformed into hydroxyl groups using a glycidolation reaction. Following this reaction, the chemotherapeutic agent, methotrexate, was attached by the formation of an ester bond. The characterization of the formulated dendrimers were carried out by- size exclusion chromatography coupled with multiangle laser light scattering, nuclear magnetic resonance, and UV spectrometry. These methods helped to determine the content of the drug, fluorescent probes, and targeting agent 214. In vitro analysis using confocal images revealed an increase in cellular uptake of tri-functional dendrimers when exposed to folic acid receptor expressing cells as compared to the untargeted controls 214. In vivo evaluation was then performed in CB-17 severe combined immunodeficiency (SCID) mice bearing human KB cancer cell (over-expressing folic acid receptor) xenografts. A decrease in tumor growth and increase in survival were observed in mice treated with the tri-functional dendrimer conjugate for up to 84 days as compared to mice treated with equivalent doses of free methotrexate 215. These results demonstrate that dendrimer-drug conjugates can be synthesized and utilized as a multifunctional drug delivery platform.

There have been increased interests for the use of dendrimers as a potential drug carrier to facilitate drug delivery across biological membranes. These biological membranes include- skin (transdermal) 211, 216, intestinal epithelial 217, 218, human placenta 219, and the blood-brain barrier 220-222. Biodegradable dendrimers 197, glycodendrimers 223, 224, amphiphilic dendrimers 225-227, and asymmetric dendrimers 228 were also investigated as potential drug carriers. Dendrimers formulated as multifunctional drug delivery systems that are functionalized with chemotherapeutic agents, targeting moieties, and imaging agents have been the subject of several recent reviews 211, 229, 230.

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There have been studies comparing dendritic carriers to more traditional polymeric carriers such as HPMA copolymers and PEG. In one study, branched and linear HPMA copolymer-DOX conjugates were evaluated for their anticancer activity against lymphoma and colorectal carcinoma cell lines. Results showed that branched HPMA copolymer-DOX conjugates demonstrated a 3 to 11 fold increase in anticancer activity as compared to linear HPMA copolymer-DOX 231. Another study compared the anticancer activity of G4-PTX dendrimers and PEG-PTX. G4-PTX demonstrated enhanced In vitro anticancer activity against breast cancer cell lines as compared to free PTX. However, PEG-PTX showed significantly reduced anticancer activity as compared to free PTX 232. These results demonstrate the unique potential of dendritic polymeric architectures as drug carriers.

Kaneshiro et al. have recently developed a new class of dendrimers, poly(l-lysine) dendrimers with a silsesquioxane cubic core (nanoglobules). These dendrimers have highly functionalized surfaces for attachment of various moieties along with compact globular and well-defined structures. These dendrimers can be used as versatile carriers for biomedical applications. In this study, a generation-3 (G3) nanoglobular dendrimer was used to conjugate a peptide c(RGDfK) with a PEG spacer for the co-delivery of DOX and siRNA. DOX was coupled to the RGD targeted nanoglobule via a degradable disulfide spacer to give G3- [PEG-RGD]-[DOX]. Results demonstrated that G3-[PEG-RGD]-[DOX] dendrimers had higher cytotoxicity as compared to free DOX at high doses in glioblastoma U87 cancer cells. For co-delivery, G3- [PEG-RGD]-[DOX] was further complexed with siRNA. These co-loaded dendrimers were internalized by U87 cancer cells as shown by confocal microscopy. The co-delivery of siRNA and DOX dendrimer complexes having the targeted conjugate resulted in 50% gene silencing efficiency in U87-Luc cancer cells as compared to those of control conjugates G3-[PEG-RGD] and G3-[DOX] with approximately 25% gene silencing efficiency for each. These nanoglobules show potential as a carrier for the co-delivery of nucleic acids and chemotherapeutic agents.

It has been shown that microRNAs are deregulated in different types of cancer with miR-21 being a key player in the majority of cancers. Previous findings showed that the down-regulation of miR-21 in glioblastoma cancer cells leads to the repression of cell growth followed by increased cellular apoptosis and cell-cycle arrest. Taking advantage of these findings, Ren et al. used PAMAM dendrimers as a carrier to co-deliver antisense-miR-21 oligonucleotide (as-miR-21) and 5-fluorouracil (5-FU) to human glioblastoma cancer cells for enhancement of cytotoxicity in 5-FU antisense therapy. MTT assay was used to analyze the inhibitory effect toward brain tumors and to quantify the measurements of cell apoptosis and invasion using the U251 human brain glioma cell line. PAMAM dendrimers were formulated and co-loaded with both therapeutic agents while still maintaining a complex smaller than 100nm in diameter. The co-

89 | Page delivery of as-miR-21 significantly improved the cytotoxicity of 5-FU with an 80% reduction in cell viability with increased apoptosis of U251 cells. The migration ability of the tumor cells was also decreased in the transwell assay. These results suggest that this co-delivery system will have important clinical applications for the treatment of miR-21-overexpressing glioblastoma.

Clinical translation of dendrimers, used as drug delivery based systems, have been limited mainly due to the concerns over their biocompatibility and toxicity. Some studies have shown that dendrimers exhibit a high affinity for metal ions, bile salts, lipids, nucleic acids, and proteins, that may disrupt biological processes and leading to toxicity 233. This molecular toxicity primarily depends on their surface functionalization. Dendrimers having a higher positive surface charge (~30+ mV) have been shown to elicit toxicities In vitro 234, 235 and in vivo 236, 237. Most work involving dendrimers currently focuses on surface modification to design more biocompatible dendrimers to help increase biocompatibility. In addition, the difficulty and expense associated with dendrimer synthesis needs to be addressed before clinical translation can be achieved.

3.8 Miscellaneous multifunctional nanocarriers Other multifunctional nanocarriers containing more than one therapeutic cargo for combinatorial chemotherapy include-oil nanoemulsions 238, 239, and iron oxide nanocarrier 84, 240. In oil emulsions, the hydrophobic drug mixture is homogenized along with oil. The drug will be loaded in the oil phase as a result of the nanoemulsion. The inorganic cores of iron oxide particles are functionalized with additional polymeric matrices to aid in carrying multiple drug payloads for combination chemotherapy. These miscellaneous nanocarriers are in the development stage with cytotoxicity studies conducted to help validate them as potential drug carriers in the treatment of various cancers and diseases.

Taratula et al. developed, synthesized, and tested multifunctional nanostructured lipid nanocarrier-based system (NLCS) for the delivery of DOX or PTX and siRNA directly into the lungs by inhalation 241. The formulated system contained- nanostructured lipid carriers (NLC); a DOX or PTX anticancer drug; siRNA targeted to MRP1 mRNA as a suppressor of pump drug resistance; siRNA targeted to BCL2 mRNA as a suppressor of nonpump cellular resistance and a modified synthetic analog of luteinizing hormone-releasing hormone (LHRH) as a targeting moiety specific to overexpressed receptors in the plasma membrane of lung cancer cells. Dynamic light scattering and atomic force microscopy studies revealed drug loaded NLC had a particle size of 110 ± 20 nm in diameter with a polydispersity index of 0.4. The NLCS formulations were tested In vitro using human lung cancer cells and in vivo utilizing mouse orthotopic model of human lung cancer. Signs of cytotoxicity were seen against lung cancer cell lines for NLC displaying a positive charge

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(+60.3 mV). Cell viability decreased by approximately 20% when incubated with NLC. NLC–siRNA complexes showed a decrease in zeta potential, +45.5 mV, while caging with PEG almost completely eliminated the charge of formulated nanocarriers. In contrast, nanocarriers containing the drug were highly toxic In vitro. Data revealed that PTX incorporated into tumor-targeted nanocarriers increased toxicity to cancer cells overexpressing LHRH receptors by 7.5-fold. Simultaneous suppression of BCL2 and MRP1 proteins by siRNA led to the further enhancement of In vitro cytotoxicity. In fact, cytotoxicity of LHRH– NLC–PTX–siRNAs (MRP1 and BCL2) complexes was 120 and 16 times higher when compared with free drug and LHRH–NLC–PTX, respectively. It was found that in untreated animals, lung tumor progressively grew reaching 117.1 ± 18.7 mm3. Mice with lung cancer underwent inhalation treatment, 8 times within 4 weeks. - LHRH–NLC alone with no anticancer drug did not change the progression of the lung tumor, leading to an increase in volume up to 113.6 ± 1.5 mm3. Conjugated PTX to the NLC targeted to tumor cells by LHRH and local delivery by inhalation significantly enhanced antitumor activity of PTX itself. After treatment with LHRH–NLC–PTX, the tumor size decreased at the end of the experiment down to 20.8 ± 4.4 mm3. Finally, the suppression of both pump and nonpump cellular drug resistance in lung cancer cells led to almost complete regression of the tumor. In fact, the tumor size in animals treated with LHRH– NLC–TAX–siRNAs (MRP1 and BCL2) shrank down to 2.6 ± 3.0 mm3. These findings indicate almost complete disappearance of lung tumors in experimental animals. The data obtained demonstrated high efficiency of proposed NLCS for tumor-targeted local delivery by inhalation of anticancer drugs and mixture of siRNAs specifically to lung cancer cells and, as a result, efficient suppression of tumor growth and prevention of adverse side effects on healthy organs.

Yu et al. formulated cationic solid lipid nanocarriers (cSLN) co-delivering PTX and siRNA 242. Emulsification solidification methods were used to prepare 1,2-dioleoyl-sn-glycero-3- ethylphosphocholine-based cSLN. PTX-loaded cSLN (PcSLN) did not significantly differ from those of empty cSLN without PTX (EcSLN), 140 nm and 151 nm, respectively. The use of cSLN increased cellular uptake of fluorescent dsRNA by 34.8-fold in human epithelial carcinoma KB cells, with PcSLN complexed to fluorescence-labeled dsRNA promoting the greatest uptake as compared to cells treated with naked fluorescent dsRNA 242. Specifically, 2.8 ± 0.3% of KB cells were fluorescence-positive after treatment with naked dsRNA, whereas 96.6 ± 1.0% and 91.3 ± 1.2% of cells were fluorescence-positive after the 4h treatment with EcSLN and PcSLN, respectively. The co-delivery of therapeutic siRNA, human MCL1- specific siRNA (siMCL1) was complexed with PcSLN with luciferase-specific siRNA (siGL2) complexed to EcSLN or PcSLN being used as a control. MCL1 mRNA levels were significantly reduced by 50% in KB cells treated with siMCL1 complexed to PcSLN, but not in groups treated with siMCL alone or siGL2 complexed to PcSLN. In vitro results showed that siMCL1 complexed to PcSLN exerted the greatest

91 | Page anticancer effects in KB cells, followed by siMCL1 complexed to EcSLN, siGL2 complexed to PcSLN, PTX alone, and siMCL1 alone. In vivo studies using KB cell-xenografted mice, intratumoral injection of PcSLN complexed to siMCL1 significantly reduced the growth of tumors. Control mice treated with saline had an average tumor volume of 1373.1 ± 241.0 mm3 on day 16 after inoculation. Intratumoral administration of siMCL1 complexed to EcSLN plus free PTX decreased tumor volume to 714.2 ± 230.0 mm3. The highest inhibition of tumor growth was observed following intratumoral co-delivery of PTX and siMCL1 using PcSLN, decreasing tumor volume to 172.0 ± 73.7 mm3. Taken together, these results demonstrate the potential of cSLN for the development of co-delivery systems of various lipophilic anticancer drugs and therapeutic siRNAs.

4. CURRENT PROGNOSIS AND THERAPEUTIC TREATMENTS FOR NEUROBLASTOMA 4.1 INTRODUCTION Neuroblastoma (NB), the most common extracranial solid tumor of childhood, is remarkable for its broad spectrum of clinical behavior 243, 244. Spontaneous regression or differentiation into benign ganglioneurons have been observed in some NB tumors 245-247. Stages 1 and 2 disease9 can be cured with surgery alone in most children10, 248. It has also been observed that most infants with disseminated disease have favorable outcomes following treatment with chemotherapy and surgery249, 250. However, children older than 1 year of age with advanced-stage NB die from progressive disease despite multimodality therapy 11. These clinical diversities correlates with numerous clinical and biological factors, including genetic abnormalities, tumor stage, patient age, and tumor histology9, 251-253. However, the molecular basis underlying the variability in tumor growth, clinical behavior, and responsiveness to therapy remains largely unknown.

Patients with localized disease and younger age have shown significant better outcomes. Investigators have speculated screening infants for NB would help lead to reduced mortality. Studies done in the 1980s demonstrated that NB could be detected through screening of catecholamines at 6 months of age and suggested that pre-clinical detection led to improved survival 254-256. However, the study conducted did not use population-based approaches for screening and no concurrent groups were evaluated. Subsequent trials demonstrated that incidence of diagnosis of NB was increased and that virtually all tumors detected by screening had favorable biological features 257, 258. This suggested that many tumor detected by screening were likely to undergo spontaneous regression and would never have been diagnosed clinically. To better answer the question as to whether routine screening for NB would help in reducing mortality, two prospective population-based, controlled trials were conducted in Germany and North America 259, 260. These studies demonstrated that screening infants at 3 weeks, 6 months, or 1 year of age did not reduce mortality due to NB. Interestingly, similar to previous reports conducted in the 1980s, almost all tumors

92 | Page detected by screening had favorable biological features. Thus, there appears no role for screening infants for NB disease.

Approximately 600 new cases of NB occur in U.S. each year with approximately one case per 7,000 births 261. NB tumors is derived from neural crest cells, and it most commonly arises in the adrenal medualla or paraspinal sympathetic ganglia. The etiology of NB remains obscure. Presently, no environmental influences or parental exposures that significantly impact on disease occurrence have been identified 261. NB disease usually occurs sporadically. However, in 1% to 2% of NB cases there is a family history 262, 263. It’s been shown that considerable biological and clinical heterogeneity is observed in the familial cases 253. Although the occurrence of familial NB suggests the presence of a unifying underlying genetic abnormality, present studies have failed to identify a specific tumor suppressor gene responsible for NB tumorigenesis 253, 264.

4.2 DIAGNOSTIC STUDIES AND TESTS The International Neuroblastoma Staging System (INSS) was developed in 1986 and revised in 1993 9, is used worldwide for the diagnosis of NB (Table 4). Diagnosis of NB can be made by either characteristic histolopathologic evaluation of tumor tissue and/or by the presence of tumor cells in a bone marrow aspirate/biopsy and elevated levels of urinary catecholamines. Some of the specific requirements for INSS diagnosis include bilateral bone marrow aspirations and biopsies, computed tomography of the body (excluding the head if clinically not indicated), bone scan, and metaiodobenzylguanadine (mIBG) scintography (Fig. 4) 9.

Table 4. International neuroblastoma staging system Stage Definition Localized tumor with complete gross excision, with or without microscopic residual disease; representative ipsilateral lymph nodes negative for tumor microscopically (nodes attached to and 1 removed with primary tumor may be positive). Localized tumor with incomplete gross excision; representative ipsilateral non-adherent lymph 2A nodes negative for tumor microscopically. Localized tumor with or without complete gross excision, with ipsilateral non-adherent lymph 2B nodes positive for tumor. Enlarged contralateral lymph nodes must be negative microscopically Unrectable unilateral tumor infiltrating across the midline*, with or without regional lymph node involvement; or localized unilateral tumor with contralateral regional lymph node involvement; or midline tumor with bilateral extension by infiltration (unresectable) or by lymph node 3 involvement Any primary tumor with dissemination to distant lymph nodes, bone, marrow, liver, skin, and/or 4 other organs (except as defined by stage 4S) Localized primary tumor (as defined for stage 1, 2A, or 2B) with dissemination limited to skin, 4S liver, and/or bone marrow+. Limited to infants <1 year of age

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*The midline is defined as the vertebral column. Tumors originating on one side and crossing the midline must infiltrate to or beyond the opposite side of the vertebral column. + Marrow involvement in stage 4S should be minimal, i.e., <10% of total nucleated red blood cells identified as malignant on bone marrow biopsy or on marrow aspirate. More extensive marrow involvement would be considered to be stage 4. The mIBG scan (if performed) should be negative in the marrow. Reprinted with permission from ref. 9. Brodeur GM, Pritchard J, Berthold F, et al. Revisions of the international criteria for neuroblastoma diagnosis, staging, and response to treatment. J Clin Oncol. 1993;11: 1466-1477.

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4.3 PROGNOSTIC FACTORS Stage and Age (Table 4.1) lists a number of clinical and biological prognostic factors for patients with NB. Like most malignancies, stage of cancer is the most important prognostic factor in NB 251. There are several retrospective analyses which confirmed the clinical relevance of the INSS staging system 265, 266. Age has been shown, at diagnosis, the only other independent clinical prognostic factor. Infants less than 1 year of age have significantly better disease-free survival rates than older children with equivalent stages of disease 267, 268. This observation has been observed for all stages of the cancer beyond localized tumors. Additional studies suggest that 1 to 2-year-old children with disseminated disease have a better outcome than children over 2 years of age 269.

Table 4.1 Prognostic factors in neuroblastoma Prognostic factor Favorable Unfavorable Reference Clinical factors Stage 1, 2, 4S 3, 4 Age <365 days >365 days 267,268 Tumor markers Ferritin Low High 270, 271 LDH Low High 272 NSE Low High 273 Histology Favorable Unfavorable 274 Biologic Factors MYCN oncogene Normal Copy Amplified 244, 275 DNA index >1.0 (hyperdiploid) 1.0 (diploid) 269, 276 Chromosome 1p Normal Deletion 277, 278 Chromosome 17q Normal Gain 279 TrkA expression High Low 253, 280, 281 TrkC expression High Low 282, 283 TrkB expression High/FL 284 CD44 expression High Low 285-287 MRP expression Low High 288 Vascularity Low High 289-292 Abbreviations: LDH = lactate dehydrogenase; NSE = neuron-specific enolase; FL = full-length transcript; MRP = multidrug-related protein.

4.3.1 Histology Shimada and colleagues devised a classification schema that relates the histopathologic features of the tumor to clinical behavior 274. NB Tumors may be classified as favorable or unfavorable depending on

96 | Page several factors; degree of neuroblast differentiation, Schwannian stroma content, mitosis-karyorrhexis index, and age at diagnosis. The International Neuroblastoma Pathology Classification system, a modified Shimada system, established in 1999, and the prognostic significance of this system has been confirmed 252. Although it remains unknown why unfavorable histology tumors are more clinically aggressive, amplification of the MYCN oncogene is strongly associated with unfavorable histology 293, 294.

4.3.2 MYCN Oncogene The presence of metastatic disease and poor prognosis of NB have been linked to MYCN gene amplification and occurs in approximately 20% of primary NB tumors 244, 275. These observations suggest that MYCN critically contributes to the clinically aggressive behavior of high-risk NB tumors, with laboratory studies validating this hypothesis 295, 296. The level of expression of MYCN has been shown to directly correlate with the growth potential of NB cells in vitro as well as in vivo 295-298. A role for MYCN in NB pathogenesis is further supported by studies demonstrating NB tumor development in transgenic mice with targeted expression of MYCN 299.

Although MYCN amplification clearly identifies a subset of NBs with highly malignant behavior, the clinical significance of greater MYCN expression in children with NB remains controversial 300-303. The reason for the discordant results may be due to disparities in patient populations, as the proportions of infants <1 year of age, patients with advanced-stage disease, and children with MYCN-amplified tumors differ in the various series. Most recently, it’s been observed that high levels of MYCN expression were found not to be predictive of a worse outcome in a retrospective analysis of patients with advanced-stage disease and normal MYCN copy number 304. Thus, the precise role that MYCN plays in non-amplified tumors remains unknown.

4.3.3 Tumor Cell Ploidy Cellular DNA content have been shown in several studies to be predictive of outcome in patients with NB, particularly in infants less than 1 year of age 269, 276, 305, 306. Hyperdiploidy, mostly in near-triploid constitution, is mainly observed in low-stage tumors of infants and is associated with excellent long-term survival. However, on the other hand, diploidy in the same age group is often associated with early treatment failure 276, 294, 307. While a correlation exists between diploidy and MYCN amplification, each factor has been validated as an independent prognostic variable 269, 294, 306.

4.3.4 Chromosome Abnormalities

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NB cell lines and primary tumors commonly have both gains and losses of genetic material. The gain of 17q genetic material is the most common genetic abnormality in primary NB. This abnormality is strongly associated with high-risk features and adverse outcome 253, 279. Consistent areas of chromosomal loss of heterozygosity (LOH) include chromosome band 1p36, 11q23, and 14q23-qter 253. Strong correlation has been observed between the allelic loss of 1p and high-risk NB features, including older age, metastatic disease, MYCN amplification, and unfavorable outcome 277, 308, 309. Two large independent studies have shown that the deletion of 1p was associated with unfavorable outcome in a univariate analysis, this factor was not prognostic after adjusting for MYCN copy number 309, 310. However, Caron and colleagues reported that loss of 1p was predictive of unfavorable outcome, independent of MYCN amplification 277. Recently, a large Children’s Cancer Group (CCG) study showed that 1p deletion independently predicted for lower event-free survival but not overall survival 278.

In contrast to 1p LOH, 11q LOH and 14q LOH are inversely correlated with MYCN amplification 311, 312. A univariate analysis revealed no survival disadvantage for patients whose tumors had 11q genetic loss. However, within the cohort of patients with normal MYCN copy number tumors, 11q LOH was associated with a significantly lower overall survival probability. The clinical relevance of 14q LOH still remains unclear.

4.3.5 Neurotrophins and Neurotrophin Receptors The Trk family of tyrosine kinases are critical mediators of neurotrophin signaling and play an essential role in normal neuronal development 313. It has been shown that differential expression of these neurotrophin receptors are highly associated with the variable biologic and clinical characteristics of NB 283. TrkA expression is inversely related to disease stage and MYCN amplification status 314, and accordingly, high trkA expression is associated with favorable prognosis 280, 281, 315. Similar, trkC is also highly expressed in biologically favorable NBs 282, 283, 316. Conversely, trkB is expressed primarily in advanced-stage tumors that are MYCN amplified 284, whereas it is expressed at low levels or in a truncated form in biologically favorable tumors 282, 283, 316.

4.4 RISK GROUP STRATIFICATION SYSTEM The Children’s Oncology Group (COG) Neuroblastoma Risk Stratification System is based on the International Risk Grouping System 317, and it is used for treatment stratification purposes. Patients are assigned into low, intermediate, and high-risk categories (and accordingly, phase III treatment protocols) based upon an analysis of age at diagnosis, INSS stage, histopathology, MYCN amplification status, and DNA index (Table 4.2).

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Table 4.2 Children’s Oncology Group: neuroblastoma risk-group schema

INSS Stage Age MYCN status Shimada histology DNA index Risk group

1 0–21 years Any Any Any Low

2A/B <365 days Any Any Any Low

365 days-21 years Normal Any - Low

365 days-21 years Amplified Favorable - Low

365 days-21 years Amplified Unfavorable - High

3 <365 days Normal Any Any Intermediate

<365 days Amplified Any Any High

365 days-21 years Normal Favorable - Intermediate

365 days-21 years Normal Unfavorable - High

365 days-21 years Amplified Any - High

4 <365 days Normal Any Any Intermediate

<365 days Amplified Any Any High

365 days-21 years Any Any - High

4S <365 days Normal Favorable >1 Low

<365 days Normal Any =1 Intermediate

<365 days Normal Unfavorable Any Intermediate

<365 days Amplified Any Any High

Reprinted with permission from the COG.

4.5 RISK-BASED TREATMENT 4.5.1 Low-Risk Disease Low-risk NB patients require minimal therapy318, 319. Previous Pediatric Oncology Group (POG) and CCG studies have shown that treatment with surgery alone resulted in survival (S) rates of > 95% for patients with stage 1 disease (Fig. 4.1)10, 248. The management of the infrequent patient with stage 1 or 2 disease with MYCN amplification remains controversial 248, 320, 321. Patients with MYCN-amplified stage 1 tumors have significantly worse event-free survival (EFS) and S rates, a subset may achieve long-term remission

99 | Page following surgery alone10, 320. These cases are rare and require continued prospective evaluation to clarify optimal management.

A high rate of spontaneous regression is seen in infants with stage 4S NB, and high survival rates have been reported in 4S infants whose tumors lack MYCN amplification 322, 323. However, Tonini and colleagues have reported favorable outcome in infants with MYCN-amplified stage 4S NB324. Newborns with small adrenal masses constitute a particularly favorable cohort of patients 325-327. Yamamoto and colleagues recently defined criteria for observing NB tumors detected by screening, and to date, all tumors have decreased in size or resolved spontaneously 328. Others have reported spontaneous regression of adrenal NBs detected antenatally by ultrasound 329. These observations made suggest that newborns with small or cystic localized NBs can be safely observed with a low risk of progression to advanced-stage disease. To prospectively test this hypothesis, the COG recently developed a clinical trial in which infants with small adrenal primary NBs will be observed rather than undergo major surgery.

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Excellent outcome is also seen in patients with stages 2A and 2B disease. Four-year EFS and S rates of 81% ± 4% and 98% ± 1.5%, respectively, were reported in previous CCG studies following treatment with surgery alone 248. POG studies, showed that localized disease was not completely resected (analogous to INSS stage 2A) and was treated postoperatively with chemotherapy. The estimated 3-year S rate for patients with hyperdiploid tumors that lacked MYCN amplification was 96% 249. Similarly, excellent outcomes for patients with localized NBs (defined as INSS stages 1, 2, and 3) were seen in the French NBL 90 Study 321. These findings support the reduction-in-therapy approach that is being tested in the current COG low-risk study. The overall objective of the COG low-risk study is to preserve the excellent survival rate for patients with low-risk NB by using surgery as the primary treatment approach, thereby minimizing the risks of acute and long-term chemotherapy-related morbidity for the majority of these patients.

4.5.2 Intermediate-Risk Disease In previous POG studies, treatment for infants with regional and metastatic disease was classified by MYCN amplification and tumor cell ploidy. Infants displaying hyperdiploid tumors were treated with cyclophosphamide and doxorubicin, whereas infants with diploid tumors received cisplatin and teniposide after an initial treatment course of cyclophosphamide plus doxorubicin 249. Wendy London and colleagues most recently analyzed patients enrolled in that study and showed an estimated 11-year S rates of 94% ± 5% and 52% ± 16% for patients with hyperdiploid and diploid tumors, respectively. A prospective CCG trial reported infants with regional and metastatic disease that were treated with a four-drug chemotherapy regimen, surgery, and local radiation to residual disease showed an S rate of 71% ± 7% 250. Infants with tumors that lacked MYCN amplification had a 93% ± 4% 3-year EFS rate, whereas those with amplified MYCN had a 10% ± 7% 3-year EFS rate (p < 0.0001). Results emphasized the clinical significance of NB tumor biology.

Patients older than 1 year with favorable biology regional tumors following treatment with surgery and chemotherapy have shown excellent S rates 318, 330. However, the use of adjuvant therapy for patients with regional disease was challenged in an institution study in which 88% of patients with INSS stages 2B and 3 tumors who lacked MYCN amplification survived without disease progression following just surgery alone 331. These observations suggest that chemotherapy may be safely reduced or eliminated for the majority of patients with biologically favorable regional tumors. Adjuvant chemotherapy and radiotherapy have been reduced in the current COG Intermediate-Risk Study in an effort to avoid associated acute and long-term complications while maintaining high cure rates. Intermediate-risk patients with favorable

101 | Page biology tumors are treated with a short course of chemotherapy (four cycles), while intermediate-risk patients with unfavorable biology receive a longer course of chemotherapy (eight cycles).

4.5.3 High-Risk Disease During the past 20 years, survival for high-risk children has improved modestly, although cure rates remain low 11, 318, 332, 333. The intensification of induction chemotherapy, megatherapy consolidation, and improved supportive care is believed to contribute to this improvement 334. Dose-intensity has been shown to correlate strongly with both response and progression-free survival, and response rates from 70%–80% have been seen with intensive multi-agent induction regimens 11, 335. Furthermore, several studies have suggested that intensification of consolidation therapy with autologous stem cell transplantation following myeloablative doses of chemotherapy with or without total body irradiation may also contribute to improved overall survival 332, 333, 336, 337. A report of 1,070 myeloablative procedures followed by stem cell rescue performed during the past 17 years from the European Group for Blood and Marrow Transplant, found a 2-year post- transplant survival rate of 49% and a 5-year survival rate of 33% 338. Recently, the superiority of myeloablative therapy and autologous bone marrow transplant over conventional dose chemotherapy was demonstrated in a randomized study conducted by the CCG 11. In that study, the 3-year EFS rate was significantly better for patients randomized to the transplant arm than for patients randomized to continuous chemotherapy (34% ± 4% versus 22% ± 4%, respectively, p = 0.034) (Fig. 4.2).

102 | Page et al. Treatment of high-risk neuroblastoma with intensive chemotherapy, radiotherapy, autologous bone marrow transplantation, and 13-cis-retinoic acid. Children's Cancer Group. N Engl J Med. 1999;341: 1165-1173.

Some investigators have treated patients with tandem cycles of high-dose therapy in conjunction with stem cell rescue in an effort to further dose intensify consolidation therapy. Grupp and colleagues conducted a single-arm trial of peripheral blood stem cell (PBSC)-supported tandem transplantation for high-risk NB patients. This demonstrated that tandem transplant was feasible in this patient cohort and that toxicity was acceptable 339. The estimated 3-year EFS rate from the date of diagnosis was promising at 58% (90% confidence interval, 40%–72%). Children’s Memorial Hospital in Chicago conducted another pilot study utilized triple-tandem cycles of high-dose therapy with PBSC rescue 340. With a median of 32 months’ follow-up, the estimated 3-year EFS rate from the time of diagnosis in that study was 57% ± 11%.

Unfortunately, despite intensive multimodality treatment, more than 50% of children with high-risk disease will relapse due to drug-resistant residual disease 11, 341. One of the most significant challenges in the treatment of high-risk NB is the complete eradication of refractory microscopic disease. The differentiation agent 13-cis-retinoic acid (RA) has been administered to high-risk patients following completion of consolidation therapy in an effort to treat chemotherapy-resistant tumor cells. A recently completed CCG study demonstrated that administration of this differentiation agent in the setting of minimal residual disease was clinically effective and resulted in a greater 3-year EFS rate (Fig. 4.3) 11. Preliminary data suggest that other biologic agents may also be clinically effective in the setting of minimal residual disease.

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Figure 4.3 Kaplan-Meier EFS curves from the time of second randomization into the CCG 3891 study for high-risk NB patients treated with 13-cis-retinoic acid following consolidation therapy versus no further therapy. Reprinted with permission 11. Matthay KK, Villablanca JG, Seeger RC, et al. Treatment of high-risk neuroblastoma with intensive chemotherapy, radiotherapy, autologous bone marrow transplantation, and 13-cis-retinoic acid. Children's Cancer Group. N Engl J Med. 1999;341: 1165-1173.

4.6 Treatment of Spinal Cord Compression Approximately 7%–15% of NB patients present with paraspinal tumors that extend through vertebral foramina either with or without associated spinal cord compression 342-344. Prompt resolution of spinal cord compression may prevent the development of permanent neurologic impairment in these children. Surgical resection either with or without laminectomy, chemotherapy, and radiation therapy are current therapeutic strategies to relieve spinal cord compression 343, 345-347. The optimal treatment approach for cord decompression remains unknown. Similar rates of neurologic recovery were observed in symptomatic patients following treatment with chemotherapy or laminectomy in a retrospective review of the POG experience. Although more orthopedic sequelae were observed in the children treated with laminectomy 348. Chemotherapy effectively relieved neurologic symptoms from cord compression due to NB were similarly reported by Plantaz and colleagues 349. Taken together, these results support a primary medical approach for the initial treatment of children with intraspinal NB tumors, with laminectomy reserved for those that fail chemotherapy.

4.7 Treatment of Opsoclonus/Myoclonus Syndrome

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The opsoclonus/myoclonus syndrome (OMS) that occurs coincident with NB is believed to be immune mediated. Approximately 60% of patients respond to adrenocorticotropic hormone or corticosteroid therapy. However, most patients have recurrences of their neurologic symptoms and develop developmental delays or mental retardation 350, 351. Several retrospective studies suggest that the administration of chemotherapy may improve the long-term neurologic outcome of this group of patients 352, 353. Several case reports have also indicated good responses to treatment with i.v. gammaglobulin 354. Recently, the COG designed a prospective study to determine if the addition of i.v. gammaglobulin to chemotherapy and steroids would improve the neurologic outcome for patients with NB tumors and coincident OMS.

4.8 NEW THERAPEUTIC AGENTS 4.8.1 Cytotoxic Agents Responses to topotecan, a topoisomerase I inhibitor, have been observed in patients with refractory or recurrent NB 355. Combinational therapy studies with topotecan plus cyclophosphamide or carboplatin have also shown to have activity against recurrent NB 326, 356. These results led to a COG pilot study designed to test the clinical efficacy of incorporating topotecan into an intensive induction regimen in newly diagnosed high-risk NB patients. The clinical efficacy of another topoisomerase I inhibitor, irinotecan, is currently being tested in COG phase I trials.

4.8.2 Retinoids Retinoids are natural and synthetic derivatives of vitamin A. All-trans-RA (ATRA) and 13-cis-RA treatments induced NB differentiation in vitro, downregulated MYCN mRNA expression, and lead to a sustained arrest of tumor cell proliferation 357-360. These observations prompted the development of clinical trials designed to test the clinical utility of 13-cis-RA in children with relapsed NB. The overall activity of 13-cis-RA in patients with high tumor burdens, in phase I and II trials, was disappointing 361, 362. However, in a subsequent randomized phase III study, 13-cis-RA was shown to improve the 3-year EFS rate when it was administered to patients with minimal residual disease following completion of consolidation therapy (Fig. 4.3) 11. Thus, 13-cis-RA appears to be most effective in the setting of minimal residual disease.

Synthetic retinoid fenretinide (4-HPR) has also shown to inhibit NB growth In vitro, and it is highly active against RA-resistant NB cell lines 358. Contrasting to 13-cis-RA and ATRA, 4-HPR induced apoptosis and necrosis 363. Furthermore, a recent report indicates that 4-HPR may also inhibit NB-induced angiogenesis 364. These results prompted Phase I and II trials to determine the clinical activity of this compound against NB. These trials are currently being conducted.

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4.8.3 Immunotherapy Targeted immunotherapy is another promising approach for the treatment of multidrug-resistant microscopic disease. Immunotherapy exploits tumor selectivity and has minimal cross-resistance and overlapping toxicities with chemotherapy. Disialoganglioside (GD2) antigen is expressed at a high density in the majority of human NB tumors which makes it a suitable target for immunotherapy 365. Several anti- GD2 monoclonal antibodies have been developed and tested in clinical trials 366. Initial studies were performed with murine monoclonal antibodies (3F8 and 14G.2a), and more recently, a human-murine chimeric antibody (ch14.18) was developed and tested 366. Therapeutic responses have been observed in phase I and phase II studies with both the murine and chimeric antibodies 367-370. In small series of patients, responses have been reported with radio-labelled 131I-3F8 antibody (8–28 mCi/kg) followed by autologous bone marrow rescue 8, 366, 367.

Cytokines have been combined with anti-GD2 antibodies in an effort to enhance response rates and to increase antibody-dependent cellular cytotoxicity (ADCC). GM-CSF has been shown to increase leukocyte number and enhance their anti-GD2 mediated ADCC 371. Therapeutic responses have been observed in trials using ch14.18 anti-GD2 antibody plus GM-CSF in patients with recurrent/refractory NB 367. Interleukin-2 (IL-2) has also been shown to augment lymphocyte-mediated ADCC 372. Enhancement of natural killer cell activity by IL-2 was observed in some patients treated with the combination of anti-GD2 and IL-2 373, 374. A randomized phase III trial is currently being conducted by COG to determine if the addition of ch14.18 anti-GD2 antibody and cytokines to 13-cis-RA in the setting of minimal residual disease will improve the outcome of high-risk NB patients.

Other targeted immunotherapy studies are being conducted with cytokine-modified NB cells, cytotoxic T lymphocytes, modified dendritic cells, and recombinant IL-2 375-378. Several small series studies utilizes IL-2 infused following myeloablative therapy and stem cell rescue 379. A ch14.18-IL-2 fusion protein has recently been generated to target delivery of cytokine therapy and achieve more effective concentrations of IL-2 in the tumor microenvironment 207. Preclinical studies have demonstrated that this fusion protein induces a cellular immune response that results in inhibited tumor growth. A COG phase I study testing the ch14.18-IL-2 fusion protein in relapsed NB patients is currently ongoing.

4.8.4 Radioiodinated mIBG Radiolabelled mIBG has been used to target delivery of radiotherapy, and responses have been observed 11, 380. Promising results have also been reported with combination radiolabelled mIBG and myeloablative

106 | Page chemotherapy followed by autologous stem cell rescue 381. Additional clinical trials are ongoing in North America and Europe that will hopefully determine the optimal dose, schedule, and timing of mIBG therapy.

4.8.5 Antiangiogenic Therapy Angiogenesis plays an important role in the growth and metastasis of malignant tumors 382. High-level expression of angiogenesis activators and high tumor vascularity have been shown to correlate with advanced-staged NB. Whereas low vascular tumor density correlates with localized disease and favorable outcome 289, 290. Preclinical studies have demonstrated that antiangiogenic agents effectively inhibit NB growth in vivo and that the optimal response may be in the setting of minimal residual disease 340, 383-386. These observations suggest that angiogenesis inhibitors may be effective in the treatment of patients with highly vascular NB tumors. Phase I studies testing a number of angiogenesis inhibitors are ongoing.

4.8.6 Late Effects of Therapy Although intensive multimodality treatment has resulted in improved survival of children with various types of cancer, including high-risk NB, follow-up of these survivors has uncovered notable adverse long-term sequelae related to treatment 261. These “late effects” have diverse manifestations that can significantly impair quality of life and lead to a greater rate of premature mortality 387, 388. Due to the complex nature of these late effects, it is imperative to follow cancer survivors in a comprehensive clinic that has a clear emphasis on these long-term issues. Musculoskeletal abnormalities, including scoliosis, osteoporosis, and bony and soft tissue hypoplasia, may occur as a result of surgery and/or radiotherapy. The chemotherapeutic regimens used in the treatment of NB include many agents with known long-term toxicities. Cardiopulmonary sequelae can result from anthracyclines or thoracic radiotherapy 389-391. Ototoxicity is a well-established toxicity of cisplatin. Renal-tubule-damaging chemotherapy, including ifosfamide and cisplatin, may lead to chronic electrolyte abnormalities, and these symptoms may be further exacerbated by abdominal radiotherapy and nephrectomy 391, 392. Alkylating agents and radiation clearly impair gonadal function which negatively impact sexual maturation and fertility 391. Growth hormone deficiency, premature menopause, thyroid and pituitary dysfunction, and obesity are other endocrine consequences of intensive multimodality anticancer therapy 391-393. Late effects of chemotherapy and radiation also include second malignant neoplasms. Treatment-related myelodysplasia and leukemia have been seen in NB patients following dose-intensive therapy 340, 394. Solid tumors are also observed in NB patients with one study indicating that NB was the most common first neoplasm among 23 patients with radiation-induced thyroid cancer 394. Some childhood cancer survivors also suffer chronically from the psychological effects of cancer, its treatment, and treatment-related cosmetic, functional, or other consequences 391. As the outcomes of high-risk NB patients improve, it becomes increasingly important to

107 | Page develop new therapeutic strategies that will lead to higher rates of survival as well as enhanced quality of life.

4.9 Summary Although substantial progress has been made in the treatment of children with low and intermediate-risk NB, cure rates for high-risk patients remain low. Research aimed at discovering new genes and pathways critical to NB tumorigenesis and drug resistance should be prioritized in an effort to identify new targets for therapeutic strategies. Hopefully, further development of innovative, biologically based treatment approaches will prove to be effective in the treatment of NB and result in improved survival of children with clinically aggressive NB.

5. CURRENT NANOCARRIER DELIVERY SYSTEMS FOR NEUROBLASTOMA A variety of nanocarrier systems are currently under investigation for cancer therapeutics 74, 75 and early clinical results showed enhanced efficacy and reduced side effects. The enhanced efficacy of nanocarriers is associated with enhanced permeation and retention effects (EPR, particle size <100 nm) due to the leaky vasculature in tumor tissue and improved pharmacokinetics (PK). The lipid- and polymeric-based nanocarriers have been widely studied for the treatment of cancer 395, 396. Nanocarrier-based systems such as Abraxane 397, Ambisome 398, and Doxil 399 are used in clinical settings. There are some reports on the use of nanocarriers for the treatment of NB using carbon nanotubes, dendrimers, and lipid nanocarriers 400, 401. However, the outcomes of these passively-targeted nanocarriers are hampered due to inefficient tumor cell internalization and toxicity to normal cells. In addition, folate and Apolipoprotein-E mediated nanocarriers have been reported for the treatment of NB 402, 403. However, these formulations have limited utility due to instability, the complex method of preparation, and bio incompatibility. Researchers have also evaluated targeted liposomes and silica nanocarriers for NB 404, 405. However, the major limitations of these formulations include low loading capacity and rapid drug leakage. In contrast, albumin and chitosan are hydrophilic, biocompatible, and biodegradable 406, 407, and are successfully used in patients. The use of these polymers may help in the translational application of these nanocarriers. While the use of albumin and chitosan in drug delivery is not new, the albumin-chitosan hybrid nanocarriers (HNC) approach to co- deliver the synergistically acting Etoposide (hydrophobic) and DFMO (hydrophilic) proposed is a novel concept and has not been reported.

108 | Page delivery of these agents with disparate physiochemical properties to NB. In addition, the amine groups of chitosan provide the potential for further conjugation of targeting ligands, and the protonation of amine groups in the acidic environment of tumors may further facilitate uptake 95, 96 as well as endosomal escape of nanocarriers 97.

The endosomal escape of nanocarriers after internalization delivers the synergistically acting drugs into the cytosol hence avoiding degradation by lysosomes. The cationic nanocarriers with high zeta potential (+35 mV) were found to undergo aggregation by adsorption of plasma proteins 98. The conjugation of polythethylene glycol (PEG, MW 5000) to delivery systems has been widely reported to be optimal for increasing serum half-life and reduce clearance by the reticulo-endothelial system 99. PEG (MW 5000) conjugation with delivery systems has been demonstrated to increase salt (stability in the presence of salt or stabilizing the salt and serum stability including the prevention of aggregation of cationic nanocarriers 99. Due to the surface curvature attained with PEG coating, the accessibility of the surface to surrounding proteins and the net electrical charge of the PEGylated particles is significantly reduced 100, 101. Therefore, the PEGylation of cationic HNC will help to overcome in vivo aggregation issues. iRGD peptides anchored on the surface of HNC to further help in attaining localized and site specific delivery of both the drugs to the NB tumors will be used in the proposed study. The co-delivery of multiple drugs via the same nanocarrier has several advantages (targeted delivery of drugs, synergistic therapeutic effects, suppressed drug resistance, and the ability to control drug exposure) compared to delivering a single drug through separate co-administered nanocarriers.

6. TARGETED MULTIFUNCTIONAL NANOCARRIERS IN COMBINATION CHEMOTHERAPEUTICS The modification of nanocarriers with ligands has been widely accepted to enhance the therapeutic efficacy of its payloads while reducing adverse side effects relative to conventional therapeutics 408. Ligand- conjugated nanocarriers not only have the ability to actively target specific cells but may also outperform first generation, non-targeted nanosystems. The necessity of targeted delivery depends on various factors (e.g., disease, drugs and the delivery vehicle); a vast array of important benefits have been demonstrated 21, 409-411. It has been shown-in cancer therapy that the presence of targeting ligands enhances the cellular uptake of nanocarriers through receptor mediated endocytosis even though the physiochemical properties of the nanocarrier determines its accumulation at the site of action 408, 409. As a result, higher intracellular drug concentration with increased therapeutic activity is observed, as bioactive macromolecules, such as DNA and siRNA, require intracellular delivery for bioactivity 408. Nanocarrier localization for endothelial targeting in cardiovascular diseases or immunological tissue targeting uses ligand-receptor interactions

109 | Page rather than the EPR 410. Ligand-mediated targeting is also of importance for the transcytosis of nanodrugs across endothelial and epithelial barriers (i.e., blood-brain barrier) 411. MDR have also been combated using targeted nanocarriers 21. Also, targeted nanocarriers with a long systemic circulation may be able to locate and destroy cancers cells that have metastasized elsewhere in the body. The clinical translation of targeted nanocarriers for treatment has been slower with four -nanocarrier systems now in phase I/II clinical trials 21. The main barrier for clinical translation of these formulation systems is the complexity behind the manufacturing of targeted nanocarriers. The fabrication of targeted nanopaticles requires multiple steps such as ligand coupling/insertion, purification and biomaterial assembly, which may cause batch-to-batch variation. A single-step synthesis of targeted nanocarriers was recently developed utilizing self-assembling pre-functionalized biomaterials that provided a simple and scalable manufacturing strategy 21, 412. Another important consideration is targeting ligands. The targeting ligand itself must be taken into consideration during formulation. The other variables that also must be considered are-cell specificity of the ligand, ligand biocompatibility, mass production, binding affinity, and its overall purity 413. The ideal ligand would be able to distinguish only the most overexpressed receptors on the target cell relative to healthy cells in order to achieve maximal specificity. There are other factors that could also influence cell targeting-: the ligand surface density and arrangement, as well as spacer type and length dividing ligand molecules and the nanocarriers 414. Nevertheless, with many advances in ligand engineering and screening, and nanocarrier optimization during formulation, targeted delivery will become a common therapeutic method in the next generation of drug therapy.

Targeting moieties are classified as proteins (mainly antibodies and their fragments), peptides, nucleic acids (aptamers), small molecules, or others (vitamins or carbohydrates) 415. Targeted delivery of nanocarriers - has widely used monoclonal antibodies (mAbs) as escort molecules, however, their utilization is hampered by large size and inefficient conjugation to the carrier. In turn, smaller-sized ligands such as peptides have attracted greater attention during formulation these days. The next sections discuss multifunctional nanocarriers delivering chemotherapeutic agents, for chemo/gene therapy or for imaging purposes, utilizing these targeting moieties. Their potential benefits and drawbacks will also be discussed.

6.1 Antibodies and antibody fragment-based targeted nanocarriers Antibodies have been used over the past several decades as the ligand of choice when it comes to a targeted ligand development. High selectivity and binding affinity for the target of interest are a direct result of the presence of two epitope binding sites in a single molecule. Some examples that have been developed and approved by the FDA for use as therapeutic antibodies -are Rituximab (Rituxan®) for non-Hodgkin’s lymphoma treatment 37, Trastuzumab (Herceptin®) for breast cancer treatment 38, Bevacizumab (Avastin®)

110 | Page designed to inhibit angiogenesis 416, and Cetuximab (Erbitux®) for advanced colorectal cancer treatment 417. The limitations associated with these therapeutic antibodies are the cost of manufacturing, high molecular weight and having batch-to-batch variation with the potential to induce an immunogenic response 415. To counter the immunogenic response, recent developments have engineered antibodies yielding humanized, chimeric, or fragmented antibodies.

A multifunctional targeted nanocarrier system was recently developed by Mi et al. 418. The formulation consisted of herceptin-conjugated nanocarriers of TPGS-cisplatin prodrug (HTCP NPs) for the targeted co- delivery of cisplatin, DTX and herceptin for the multimodality treatment of breast cancer of high HER2 overexpression 418. To stabilize the prodrug and to help facilitate herceptin conjugation, co-polymers poly- (lactic acid)-TPGS (PLA-TPGS) and carboxyl group-terminated TPGS (TPGS-COOH) were used in the polymeric matrix. The nanoprecipitation method was used to prepare high, moderate and low DTX versus cisplatin ratio HTCP NPs. The HTCP NPs showed a pH-sensitive release for both anticancer drugs. In vitro analysis was conducted using SK-BR-3 human breast adenocarcinoma and NIH3T3 mouse embryonic fibroblast cell lines to evaluate the therapeutic effects of HTCP NPs compared with Taxotere® and cisplatin alone. The HTCP NPs formulations of high, moderate and low DTX versus cisplatin ratios were analyzed with HTCP NPs of high DTX versus cisplatin ratio having the highest efficacy against selected cell lines. Using herceptin as a targeting ligand for HER2 overexpression, the targeted HTCP NPs demonstrated a lower IC50 value of DTX (90.0201+μg/mL) +cisplatin (0.00780 μg/mL) +herceptin (0.1629 μg/mL) against

SK-BR-3 cells (having high HER2 overexpression), than that of IC50 value of DTX (0.225+μg/mL) + cisplatin (0.0875μg/mL) + herceptin (1.827 μg/mL) against NIH3T3 cells (low HER2 overexpression), after 24h incubation 418. The similar approach of TPGS prodrug nanocarriers can also be applied for targeted co- delivery of other hydrophilic and hydrophobic drugs.

Similarly, miceller nanocarriers self-assembled from biodegradable and amphiphilic co-polymer poly-P- (MDS-co-CES) were recently developed by Lee et al. 168. These cationic micellar nanocarriers have been shown to deliver small molecular drugs and bio-macromolecules such as genes and functional proteins individually or simultaneously into various types of cells 168. In this study, the cationic micellar nanocarriers co-delivered PTX and herceptin to achieve a targeted delivery of PTX to HER2/neu-overexpressing human breast cancer cells, thereby enhancing cytotoxicity through synergistic activities. Formulated PTX-loaded nanocarriers had an average size less than 120 nm with a zeta potential of about 60 mV. The surface of drug-loaded nanocarriers were then complexed with Herceptin to target HER2 overexpressed cancer breast cancer cells. Under physiological conditions drug-loaded herceptin complex remained stable displaying an average size of around 200nm. BioPorter, a commercially available lipid-based protein carrier, was

111 | Page compared against formulated PTX-loaded Herceptin complexed nanocarriers. Results showed that the nanocarriers delivered Herceptin more efficiently than BioPorter and displayed an enhanced anticancer effectiveness. Treatments were repeated twice-daily with Herceptin formulations displaying significantly enhanced cytotoxicity in HER2-overexpressing breast cancer cells when compared against single drug- alone treatment. Further investigation was done - to evaluate the anticancer effects of co-delivered PTX- loaded Herceptin complex nanocarriers against human breast cancer cell lines with varying HER2 expressions levels, namely, MCF7, T47D, and BT474. It was observed that efficacy of co-delivered PTX and Herceptin was dependent on the HER2 expression levels. Confocal microscopy images revealed higher cellular uptake of formulated nanocarriers in HER2-overexpressing BT474 cancer cell lines as compared to HEK293 cells which express no HER2 receptors. Targeting ability of this co-delivery system was demonstrated through confocal imaging studies. This formulation may have important clinical implications against HER2-overexpressing breast cancers in the near future.

Hadjipanayis et al. co-delivered an anti-epidermal growth factor receptor (EGFR) deletion mutant antibody fabricated to amphiphilic triblock copolymer-coated iron oxide nanocarriers (IONPs) for targeted imaging and therapeutic treatment of glioblastoma 419. It has been shown that the EGFR variant III (EGFRvIII) deletion mutant is not expressed in normal brain tissue but is specifically expressed in malignant glioma cells. A polyclonal rabbit antibody was developed for the synthesis of the 14-amino-acid fusion junction sequence (EGFRvIIIAb) for the selective binding of the mutant EGFR protein. The purified EGFRvIIIAb was then covalently conjugated to the amphiphilic triblock copolymer-coated iron oxide nanocarriers 420. The final formulation yielded a stable glioblastoma-targeting theranostic agent (EGFRvIIIAb-IONPs) (Fig. 6A). Convection enhanced delivery (CED), a continuous method of injection under a pressure gradient formed by the fluid containing the therapeutic agent, was used to effectively deliver EGFRvIIIAb-IONPs to the intratumoral and peritumoral regions in the brain 421. This CED method helps to prevent nanocarriers from becoming trapped in the spleen, liver, or within circulating macrophages after I.V. administration while also bypassing the blood-brain barrier. CED is a method that is therefore used increasingly in the distribution of therapeutic agents for the treatment of malignant gliomas 422-424. Human U87ΔEGFRvIII glioma model tumors were implanted in athymic nude mice were used to test the accuracy of MRI monitoring and the efficacy of antitumor effects of EGFRvIII-IONPs. There was a decrease in the T2- weighted MRI signal after CED of EGFRvIII-IONPs, with a total area signal drop being observed 7 days after CED treatment, indicating the nanocarriers had dispersed from the area. Animals that underwent CED treatment with either EFFRvIIIAb or EGFRvIIIAb-IONPs had a significantly higher rate of survival, which may be a result of inhibition of EGFR -phosphorylation, whereas the CED untreated control or IONPs groups did not display an increase in survival rate (Fig. 6B – 6F). These results indicated that the MRI-

112 | Page guided CED of multifunctional EG-FRvIIIAb-IONPs results in the specific targeting of devastating brain tumors and may have potential for clinical applications.

Wei and Gao et al. used the similar targeted imaging and therapy method for delivery of multifunctional nanocarriers in the treatment of prostate cancer. A single chain anti-prostate stem cell antigen (PSCA) antibody (scAbP-SCA) is used as a specific ‘address tag’ for the targeted therapy and imaging of prostate 425. The prostate stem cell antigen is a prostate-specific glycosyl phosphatidyl-inositol-anchored glycoprotein that is marginally expressed in normal prostate and overexpressed in prostate cancer tissues 426. The multifunctional nanocarriers were prepared by cleaving intact AbPSCA with mercaptoethylamine (MEA), then linked to maleimide-PEG-carboxyl (MAL-PEG-COOH) with covalent conjugation to multifunctional polymeric vesicles formed by entrapping SPIO nanocarriers and DTX by amine-terminated PLGA. The final formulation yielded scAbP-SCA-DTX/SPIO-NPs having a size around 147 nm with SPIOs and DTX in the polymer matrix around 23 wt% and 6.02 wt%, respectively. A higher drug encapsulation efficiency was obtained by partitioning DTX into the oleic acid and oleylamine shell of the

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SPIOs, where it acted as a drug reservoir, giving a triphasic drug release pattern versus the common two- phase kinetic release pattern, which -includes burst effects of an initial release stage, as observed in vesicles without SPIOs. In vitro cytotoxicity studies revealed the anti-proliferative effects of the formulated multifunctional nanocarriers towards prostate cancer cell lines with an overall decrease in 80% cell viability as compared to non-treated cells. PC3 cells incubated with scAbPSCA-DTX/SPIO-NPs produced distinct darkened regions in the T2-weighted MRI as compared to polymeric vesicles without scAbPSCA or Endorem® (a commercial contrast, Guerbet, France) 425. These results demonstrated that the multifunctional scAbP-SCA-DTX/SPIO-NPs can be used as MRI contrast agents for prostate-targeted imaging and real-time monitoring of therapeutic effects.

In a similar approach, Chen and Shuai et al. used scAb as a targeting ligand in the design of multifunctional nanocarriers 427. Chen and Shuai et al. formulated a CD3 single chain antibody (scAbCD3) functionalized non-viral polymeric vector for gene delivery to T-cells 427. As done by Wei et al., the polymeric vector was first complexed with SPIONs, which was then used to condense the therapeutic agent, a gene plasmid, as a dual-purpose probe (MRI contrast agent and T lymphocyte targeted gene delivery). -The engagement of T- cell antigen receptors, such as the CD3 receptors found on mature T-cells, may lead to the initiation of anergy. These receptors can also potentially mediate targeted gene delivery to T-cells. Therefore, scAbCD3-conjugated, poly(ethylene glycol)-grafted polyethyleneimine (PEG-g-PEI)-coated SPIONs (scAbCD3-PEG-g-PEI-SPION) were synthesized using bio-conjugation and ligand exchange methods 428. The targeting multifunctional polyplexes (scAbCD3-PEG-g-PEI- SPION/DNA) then incorporated a diacylglycerol kinase (DGKα) gene that may potentially impair T-cell receptor (TCR) signaling, consequently resulting in the anergy of T cells 429, 430. T2-weighted MRI revealed that scAbCD3- immobilized polyplexes were efficiently taken up by target T-cells (HB8521) through CD3 receptor- mediated endocytosis. Flow cytometric analysis indicated high gene transfection efficiency of the targeted polyplexes (81.95%) as compared to polyplexes without scAbCD3 functionalization (7.39%). After DGKα genes were transferred into HB8521 cells, lower levels of cell proliferation and IL-2 expression were observed. This is mainly due to the response to immune stimulation in cells transfected with the targeted polyplexes -as compared to cells that hadn’t been pre-transfected during stimulation. These data demonstrate that MRI-visible targeted nanocarriers can dampen TCR-induced diacylglycerol signaling.

Immunoliposomes (antibody-directed liposomes) are common pharmaceutical carriers for targeted drug delivery having the ability to encapsulate both hydrophilic and hydrophobic therapeutic agents using simple preparation techniques 431. In vivo lung cancer targeted immunoliposomes were developed by Wu et al. using an anti-c-Met antibody 431. It has been shown that c-Met, the receptor for hepatocyte growth factor

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(HGF), is abundantly expressed in 25% of non-small cell lung cancer patients. The activation of this protein has been reported to trigger cancer cell proliferation, migration, and invasion 432, 433. Wu et al. prepared individual targeted therapeutic vehicles and imaging probes. The anti-c-Met single chain variable fragment (scFv) antibody was first identified by phage display (Ms20, Kd value; 9.14 nM). Cysteine residues were then fused for a site-direct conjugation with maleimide-modified PEG-terminated liposomal DOX. The final formulation resulted in Ms20-conjugated liposomal DOX (Ms20-LD). Their study also utilized inorganic quantum dots (QD) as a targeted diagnostic tool (Ms20-QD). Due to the fact that c-Met expression appears in angiogenic endothelium as well as in tumor cells 434, dual targeting properties, such as inhibition of tumor growth and prevention of angiogenesis, were observed in an Ms20-LD-injected H460-bearing SCID mouse xenograft model. It was also shown that Ms20-LD improved the chemo-therapeutic drug delivery by inhibiting c-Met-transient or c-Met-constitutive activation of cancer cells. This study showed the in vivo tumor homing of Ms20-QD, and it supported that Ms20 -provides selective delivery to solid tumors. – Thus, Ms20 shows potential as a lung tumor targeted theranostic agent.

6.2 Peptide based targeted nanocarriers Peptides are attractive targeting molecules due to their small size, low immunogenicity, ease of manufacture and -lower cost 435. There are several methods for identifying peptide-based targeting ligands. One of the most common methods is obtained from the binding regions of a protein of interest. The phage display techniques may also be used in identifying peptide-targeting ligands. During a phage display screen, the bacteriophages –present a variety of targeting peptide sequences in a phage display library (~1011 different sequences), with the target peptides being selected by using a binding assay 436. The cyclic peptide, Cilengitide, has an integrin binding affinity and is currently in phase II clinical trials for the treatment of non-small cell lung cancer and pancreatic cancer 433. Phase III clinical trials for the treatment of advanced solid tumors and non-Hodgkin’s lymphoma -have also commenced for an Adnectin for human VEGF receptor 2 (Angiocept), a 40 amino acid thermostable and protease-stable oligopeptide. Peptides have limitations as well such as a low target affinity and susceptibility to proteolytic cleavage. These issues may be improved by displaying the peptides multivalently or using D-amino acids during the synthesis process 436. Recently, peptides have been used to fabricate multifunctional nanocarriers for targeted cancer imaging and therapy.

Medarova et al. specifically designed a breast tumor-targeted nanocarrier that would - deliver siRNA to human breast cancer while simultaneously allowing the siRNA delivery process through noninvasive techniques 437. The co-loaded -nanocarriers were made of SPIONs for MRI monitoring, and loaded with Cy5.5 fluorescence dye for near-infrared (IR) optical imaging, and siRNA to target the tumor-specific anti-

115 | Page apoptotic gene BIRC5. The magnetic iron oxide nanocarriers have been used extensively in combination with optical fluorescent dyes as multimodal imaging probes for the benefits of rapid screening and higher sensitivity. The tumor-associated under-glycosylated mucin-1 (uMUC-1) antigen has been shown to be overexpressed in >90% of breast cancers and also in >50% of all cancers in humans 438. Therefore, researchers have decorated nanocarriers with uMUC-1-targeting EPPT synthetic peptides for selective tumor targeting of breast cancer. Superparamagnetic iron oxide nanocarriers with functionalized amine groups are cross-linked with a dextran coating (MN) with Cy5.5 dye conjuagted to its surface to produce MN-Cy5.5 nanocarriers (Fig. 6.1A). A heterofunctional cross-linker, N-succinimidyl 3-(2-pyridyldithio) propionate (SPDP), was then used to couple the thiol-modified, FITC-labeled EPPT peptides and siRNA to the MN-Cy5.5 nanocarrier. The final multifunctional co-loaded formulation, MN-EPPT-siBIRC5, exhibited super-paramagnetic and fluorescence properties. In vivo studies used mice with BT-20 tumors treated i.v. with the final formulation. The tumors were clearly imaged using the nanocarriers, as verified simultaneously by T2 MRI and near-IR optical imaging (Fig. 6.1B). It was shown that administration of the multifunctional nanocarriers once a week over a two-week period induced considerable levels of necrosis and apoptosis of the tumors themselves. This is a direct result of the siBIRC5-mediated inhibition of the anti-apoptotic survivin proto-oncogene which –resulted in a significant decrease in tumor growth rate (Fig. 6.1C). The tumor-targeted multifunctional imaging-capable nanocarrier displays the potential of MRI- guided tumor treatment. This application, along with other MRI-guided tumor treatments described, can be used to quantify changes in the tumor volume over the treatment schedule as well as guide selection of an optimal treatment schedule.

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Figure 6.1 A) Schematic diagram showing the synthesis of MN-EPPT-siBIRC5. B) Representative pre-contrast images and 24 h post-contrast T2-weighted images (top), and color-coded T2 maps (bottom) of the tumor-bearing mice i.v. injected with MN-EPPT-siBIRC5 (10 mg/kg Fe). C) Relative tumor volume measurements of MN-EPPT-siBIRC5- and MN-EPPT-siSCR-injected animals over the course of treatment. Reprinted with permission from ref. 212, M. Kumar, M. Yigit, G. Dai, A. Moore, and Z. Medarova, Image-guided breast tumor therapy using a small interfering RNA nanodrug. Cancer Res. 70, 7553-61 (2010). CopyrightatCancer Research.

Liu et al. evaluated porous silicon nanocarriers (PSi-NPs) as a potential carrier in multi-drug delivery for the co-loading of the hydrophobic drug indomethacin and the hydrophilic human peptide YY3-36 (PYY3- 36) 439. Their study showed that the sequential loading of these two drugs into PSi-NPs enhanced the drug

117 | Page release rate of each drug and also their amount permeated across Caco-2 and Caco-2/HT29 cell monolayers 439. Results showed that regardless of the loading approach used, dual or single loading into PSi-NPs, drug permeation profiles were in good correlation with the drug release behaviour. Permeation studies helped to indicate the critical role of the mucus intestinal layer and the paracellular resistance in the permeation of the therapeutic agents across the intestinal wall. It was also observed that the loading PYY3-36 greatly improved the cytocompatibility of the PSi-NPs. Conformational analysis revealed that the PYY3-36 still displayed biological activity after release from PSi-NPs and permeation across the intestinal cell monolayers. These results are the first to demonstrate the co-loading potential of PSi-NPs for simultaneous multi-drug delivery of both hydrophobic and hydrophilic therapeutic compounds.

Li et al. have reported that tetrandrine (Tet) effectively increases the stability of PTX-loaded nanocarriers when Tet is co-encapsulated with PTX into mPEG-PCL nanocarriers 440. Their study demonstrated that the synergistic antitumor effect of Tet and PTX against gastric cancer cells-provided the basis of coadministration of Tet and PTX using nanocarriers. It has been reported that the cellular chemo-resistance to PTX correlates with intracellular antioxidant capacity 440. Therefore, the depletion of cellular antioxidant capacity could enhance the cytotoxicity of PTX. Tet effectively induces intracellular ROS production 440. Their study provides a novel therapeutic strategy -based on “oxidation therapy” that it could amplify antitumor effects of PTX by employing Tet as a pro-oxidant. It was shown that more intracellular Tet accumulation by endocytosis of PTX/Tet-NPs than equivalent doses of free drug lead to more intracellular ROS induction, which efficiently enhanced the cytotoxicity of PTX through the sequential inhibition of ROS-dependent Akt pathways along with the activation of apoptotic pathways. The tumor inhibition is a result of synergistic action and mediated superior cytotoxicity of PTX/Tet-NPs over free drug. The preliminary results suggest that co-delivery of PTX and Tet via nanocarriers provided a novel therapeutic strategy based on “oxidation therapy” against gastric cancer and may be applied to other nanocarrier applications.

Taking advantage of the acidic extracellular tumor microenvironment (pH 5.8–7.1) may provide another strategy for increasing tumor selectivity. The acidic conditions around the tumor which -are caused by the hypoxic metabolic state, can provide a triggering signal for cancer-targeted drug delivery of nanocarriers 441-443. Zhang et al. designed a glioma targeting pH-sensitive siRNA nanovector using Caltex (CTX) based -on this strategy 444. A multifunctional iron oxide magnetic nanocarrier was coated with various types of functional molecules; the primary amine group-blocked polyethyleneimine (PEI) acting as the pH-sensitive layer, siRNA as a therapeutic payload with CTX as a tumor targeting ligand 444. Citra-conic anhydride (2- methylmaleic anhydride) was reacted with the primary amine group of PEI, providing a terminal

118 | Page carboxylate, which could then be hydrolyzed under acidic conditions. Under acidic conditions, the reversible charge conversion from positive to negative in a pH-sensitive manner- may help in reducing the cytotoxicity of PEI while minimizing nonspecific cellular up-take during physiological pH conditions 441, 445. The nanovectors were then synthesized using iron oxide nanocarriers with amine-functionalized previously coated with amine-terminated PEG. These primary amine groups were then reacted with Trauts reagent, providing thiol-modified NPs. Amine groups of PEI that remained unreacted after the citra- conylation reaction were activated with SPDP for conjugation onto the surface of the NPs. The formulation, pH-sensitive PEI-coated NPs, showed negligible cytotoxicity at pH 7.4 as a result of surface-exposed carboxylates on the NPs. However, cytotoxicity was triggered under acidic conditions where the NPs surface charge increased due to de-blocking of the primary amine groups and protonation of amine groups remaining in the PEI. Further conjugation with thiol-modified CTX and siRNA using succinimidyl ester- PEG-maleimide (NHS-PEG-MAL) linkages was -done to test the targeted delivery and therapeutic properties of the NPs. In vitro analysis of C6 cells using MRI scans incubated with NPs-PEI-siRNA-CTX displayed higher intracellular up-take than that of NP-PEI-siRNA, indicating that the presence of CTX on the surfaces of the NPs assisted in the cellular internalization of the nanovectors themselves. CTX- conjugated NPs also mediated selectivity in gene silencing effects. -Cells incubated with NP-PEI-siRNA- CTX at pH 6.2 showed a significant reduction in GFP gene expression as compared to gene expression almost unchanged in cells treated with the same nanovector at pH 7.4. These results suggest that the nanovector pH-based system shows a good safety profile and may potentially be used as a brain tumor targeted theranostic agent in future studies.

Nanoporous silica shows potential as an attractive drug delivery system due to -its high surface area and binding capacity for therapeutic and diagnostic agents as compared to liposomes of similar size. Nanoporous silica cores easily load multicomponent cargos and therefore produce nanocarriers that can potentially be used for targeted multicomponent delivery of therapeutic agents. Ashley et al. synergistically combined the features of mesoporous silica particles and liposomes by developing porous silica nanocarrier-supported lipid bilayers (protocells) approximately 100–150 nm in diameter (Fig. 6.2). The combination of these two distinct carriers helped to address the multiple challenges of targeted delivery 446. An SP94-targeted peptide -was then conjugated to the protocells. The SP94 peptide specifically binds to human hepatocellular carcinoma. Protocells were further conjugated with a histidine-rich fusogenic peptide which assists in endosomal escape once administered and also cytosolic dispersion of the encapsulated cargos. It was observed that the nanoporous support resulted in improved stability and enhanced lateral bilayer fluidity as compared to both liposomes and non-porous particles. As a result, it promoted multivalent interactions between the protocell and the target cancer cells while using only a minimal number of targeting

119 | Page peptides through peptide recruitment to the cell surface 446. A 1000-fold higher loading capacity of the drug DTX was observed in protocells due to their high surface area and porosity of their nanoporous cores when compared to liposomes of similar size. Protocells’ unique properties help to solve the problem of achieving higher targeting specificity with enhanced cytotoxicity against the target cancer cells while sparing normal healthy cells. Viability tests showed that protocells loaded with the therapeutic agent DTX maintained a 90% normal hepatocyte while killing over 97% MDR1+ hepatocellular carcinoma (Hep3B) 446. Results also showed that protocells without fluidity on the surface or DTX loaded liposomes, were less effective at killing Hep3B cells while showing high cytotoxicity against non-cancerous cell lines. Protocells loaded with DTX demonstrated targeted delivery while sparing healthy cells as compared with free drug and DTX- loaded liposomes. The combination of two nanocarriers for a targeted multicomponent delivery of therapeutic agents shows great promise in overcoming loading capacity of drugs with increased therapeutic efficacy against target cancer cells.

120 | Page silica core, as well as the ligands that can be displayed on the surface of the nanocarrier. Reprinted with permission from ref. 279, C. E. Ashley, E. C. Carnes, G. K. Phillips, D. Padilla, P. N. Durfee, P. A. Brown, T. N. Hanna, J. Liu, B. Phillips, M. B. Carter, N. J. Carroll, X. Jiang, D. R. Dunphy, C. L. Willman, D. N. Petsev, D. G. Evans, A. N. Parikh, B. Chackerian, W. Wharton, D. S. Peabody, and C. J. Brinker, The targeted delivery of multicomponent cargos to cancer cells by nanoporous particle- supported lipid bilayers. Nature materials. 10, 389-97 (2011). CopyrightatNature Publishing Group.

As previously described, the combining of two different functional nanocarriers which communicate with one another may be constructed to target a specific disease. Bhatia et al. designed such a nanosystem in which they used ‘signaling’ modules (gold nanorods, NRs, or tumor-targeted tissue factor, tTF) as tumor- activating agents for selective delivery and ‘receiving’ nanocarriers (magneto-fluorescent iron oxide nanoworms, NWs, or DOX-loaded liposomes, LPs) for targeted imaging or therapeutic agents (Fig. 6.3A) 50. These NWs -are elongated nanostructures formed by the assembly of iron oxide cores that exhibit strong magnetic properties and efficient tumor targeting 447. The multifunctional nanosystem contained two ‘signaling’ modules which activated the coagulation cascade in tumors, broadcasting the tumor’s location to receivers in circulation (Fig. 6.3B). External electromagnetic energy was converted into heat by NRs in circulation. The NRs passively target tumors and locally disrupt tumor vessels using the heat generated. Coagulation was induced upon the binding of the tTF to the angiogenic αvβ3 receptors. Coagulation regions -were then targeted by the receiving nanocarriers. Peptide substrates were then derivatized on NWs and LPs for the coagulation of trans-glutaminase FXIII or fibrin-binding. Results showed that after injection of signaling modules into MDA-MB-435 bearing mice at 45°C, ‘receiving’ NWs or LPs displayed prominent extravascular accumulation around the tumor which helped to amplify the therapeutic outcome (Fig. 6.3C and Fig. 6.3D). These results demonstrated a heat-dependent increase in the passive accumulation and specific biochemical recognition of the coagulation process 447. It was shown that the communication coagulation cascade helped to improve the accumulation of the receiving modules by a factor of 40 as compared to receiving modules without communication. The combining of two different functional nanocarriers which communicated with one another improved extravascular tumor accumulation while amplifying the therapeutic outcome. These results show great promise in the field of combining functionalized nanocarriers as a co-delivery method for the treatment of cancer.

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122 | Page communicate in vivo to amplify tumour targeting. Nature materials. 10, 545-52 (2011). CopyrightatNature Publishing Group.

6.3 Small molecules based targeted nanocarriers Small molecules are relatively inexpensive to manufacture and are capable of an infinite array of diverse structures and properties 415. Folic acid (folate) is a heavily studied small molecule that plays a major role as a targeting moiety for the delivery of therapeutic agents. This small molecule is a water-soluble vitamin B6 that is essential in humans for growth and rapid cell division, especially during embryonic development 436. Folate receptors are overexpressed on various tumor cells, allowing folate, which has a high binding affinity for folate receptors (Kd = 10–9 M), to be used as a targeting ligand for targeted delivery of imaging and therapeutic agents to tumors. Several cancer imaging agents and therapeutics that use folate as a targeting moiety are currently being tested in clinical trials such as 111In-DTPA-folate, 99mTc-folate conjugate (EC20), folate-linked fluorescent hepten (EC17), and diacetylvinylblastine hydrazide-folate conjugate (EC145) 415. Folate is one of the promising small molecule targeting ligandsused for co-delivery of therapeutic agents using organic or inorganic nanocarriers. Another class of small molecules which act as targeting ligands are carbohydrates. These small molecule targeting ligands can selectively recognize cell surface receptors such as lectin 448. Carbohydrates such as galactose, mannose, and arabinose may serve as effective targeting moieties in the treatment of liver diseases as they readily bind to the asialoglycoprotein receptor (ASGP-R) that is present only on hepatocytes at a high density, approximately 500,000 receptors per cell 449-452.

Cellular metabolism requires an essential vitamin, riboflavin, and studies have shown that the riboflavin carrier protein (RCP) is highly up-regulated in metabolically active cells 453, 454. Therefore, flavin mononucleotide (FMN), which is an endogenous RCP ligand, may be used as a small molecule targeting ligand for metabolically active cancer or endothelial cells. Kiessling et al. synthesized a dual probe nanocarrier using FMN-coated ultrasmall superparamagnetic iron oxide nanocarriers (FLUSPIO) as MRI/optical probes for prostate cancer detection in vivo 455. Phosphate groups of FMN were used to coat USPIO with guanosine monophosphate to impart stability to the nanocarrier. FLUSPIO had a final hydrodynamic radius of 97 ± 3 nm with an intense fluorescence emission band observed at 530 nm due to FMN. PC3 prostate cancer cells and human umbilical vein endothelial (HUVEC) cells were used for In vitro cellular uptake of FLUSPIO. Characterization was analyzed by MRI (3T), TEM, and fluorescence microscopy. A significantly increased R2 relaxation rate of both PC3 cells and HUVEC cells after 1h incubation with FLUSPIO -was observed compared to that of non-targeted USPIO 455. Free FMN reduced uptake of the nanocarriers considerably by competitive blocking of RCP. Fluorescence microscopy revealed

123 | Page an enhanced green fluorescence in the cells after FLUSPIO incubation. Endosomal localization of the nanocarriers is suggested due to the perinuclear fluorescence signal. These data are consistent with TEM results and suggest that FMN may serve as a versatile building block for tumor-targeted imaging and therapeutic modalities in multifunctional nanocarriers.

A dual contrast agent (nuclear imaging/ MRI) was developed by Jeong et al. using galactose-conjugated SPIONs to target hepatocytes in a mouse model 456. After i.v. injection, SPIONs are generally nonspecifically phagocytosed or endocytosed by the reticuloendothelial system in the liver, spleen, lymph, and bone marrow. Therefore, the evaluation of hepatocyte function under certain clinical conditions, such as partial liver transplant or hepatitis, is essential, and there is need for hepatocyte-selective imaging. Jeong et al. synthesized lactobionic acid (LBA) having a high affinity for ASGP-R. The LBA was immobilized onto SPIONs using amide linkages of the dopamine-modified SPIONs bearing a primary amine group and the LBA using 1-ethyl-3-(3-(dimethylamino)-propyl) carbodiimide/ N-hydroxysuccinimide (EDC/NHS) chemistry 456. Nanocarriers were radiolabeled with 99mTC via diethylene tri-amine pentaacetic acid (DTPA), which were further conjugated to the remaining amine groups of dopamine-SPIONs. In vivo micro-single photon emission computed tomography (SPECT)/CT images and T2-weighted MR images analysis of 99mTC-LBA-SPION, after tail vein injection, revealed that nanocarriers accumulated in the liver within a few minutes. The blocking of ASGP-R using free galactose was conducted in a competitive study showing a large decrease in liver uptake. These data suggest that ASGP-R facilitated the uptake of 99mTC-LBA-SPIONs. It was then confirmed by TEM imaging that LBA-SPIONs were located within the mitochondrial matrix as well as the cytoplasm. This indicated that ASGP-R helped to facilitate internalization of the nanocarriers into the hepatocytes.

Small molecule-targeting ligands must demonstrate high specificity and affinity towards cellular receptors. The development of such a targeting ligand has been proven to be a challenging task 415. Multivalent binding effects may be a way to help improve the targeting of small molecule-conjugated nanocarriers. This would entail conjugating multiple ligands on the nanocarrier surface. High-throughput screening is another strategy for selecting small molecule-targeting ligands having high affinity and specificity for specific receptors. Weissleder et al. used high-throughput screening, with fluorescent magnetic nanocarriers, against several small molecular ligands from a library of 146 small molecules (500 Da), that specifically bind to endothelial cells, activated human macrophages, and pancreatic cancer cells 457. Overall, small molecules are relatively inexpensive to produce and are capable of an infinite array of diverse structures and properties with great potential as a class of targeting moieties.

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6.4 Aptamer-based targeted nanocarriers Aptamers are small nucleic acid ligands (15–40 bases) that have high specificity to target binding sites due to the molecules’ ability to fold into unique conformations with three-dimensional structures 458. The systematic evolution of ligands by exponential enrichment (SELEX) is the selection process used to identify aptamers 459-462. Through this process, it is possible to select aptamers displaying high affinity and specificity for a target from libraries consisting of more than 1015 random oligonucleotides. Aptamers as a targeting moiety have many advantages over antibodies-: low immunogenicity, small size (~15 kDa), and easy scale-up preparation without batch-to-batch variations. Approximately more than 200 aptamers have been isolated to date 463, 464. AS1411, a nucleolin targeted aptamer, is in phase III of clinical development 465. Pegaptanib, a VEGF165 targeted aptamer, was approved by the FDA in 2004 for the treatment of neovascular macular degeneration 466-468. Aptamers also possess several deleterious properties such as rapid clearance from the blood due to nuclease degradation. To enhance aptamers’ bioavailability and pharmacokinetic properties, chemical modification with PEG or pyrimidine modifications at the 2’-fluorine position were conducted on the aptamer molecule itself 469. One of the best characterized aptamers used for targeted delivery -is 2’-fluoro-pyridine-RNA. These aptamers are generated against the extracellular domain of prostate-specific membrane antigen (PSMA) 470. The PSMA as targeting ligand was used for the delivery of DOX 471, incorporated into self-assembled polymeric nanocarriers 36, 472, 473, and quantum dots 49. Recent studies utilize a PSMA aptamer-siRNA chimera system that was extended at the 3’ end to contain a complementary nucleotide sequence directed toward the antisense strand of the siRNA 474.

Alexis et al. co-delivered DOX and DTX using biocompatible and biodegradable PLGA-b-PEG copolymer. The nanoprecipitation method was used to formulate DTX encapsulated NPs (~1 wt% Dtxl) having a diameter of 62 ± 1.5 nm. The surfaces of the nanocarriers were further functionalized with A10 PSMA aptamers which were pre-loaded with DOX 20. The final formulation, NP-(DTX)-Apt- (Fig. 6.4) was further analyzed for cellular uptake and In vitro cytotoxicity. A hydrophobic dye, NBD-cholesterol, was used to visualize cellular uptake of both drugs using fluorescence microscopy having a fluorescence emission spectrum (excitation/emission = 460 nm/534 nm). Two cell lines chosen for analysis were- LNCaP prostate adenocarcinomas cells, which -express PSMA antigens on their plasma membrane, as the target cell line and PC3 prostate adenocarcinomas cells, which show no expression of the PSMA antigen acting as a negative control. It was shown that NBD-cholesterol and DOX were effectively delivered into LNCaP cells via NP–Apt bioconjugates. There was no uptake of NBD observed in PC3 cells, with only a relatively small amount of DOX signal appearing in the PC3 nucleus which may represent a portion of free DOX released from the NP–Apt bioconjugates during incubation with cells. In vitro cytotoxicity studies revealed that NP- (DTX)-Apt- formulations were significantly cytotoxic in both cell lines as compared to all controls. The

125 | Page relative cell viability of NP-(DTX)-Apt- -was 54% in contrast to 58 %, 86%, and 100% using NP-(DTX)- Apt, NP-Apt-, and NP–Apt, respectively. Alexis et al. examined a novel targeted drug delivery system which consisted of NP–Apt bioconjugates that simultaneously delivered both hydrophobic PTX and hydrophilic nucleic acid intercalating DOX drugs to prostate cancer cell lines 20. This targeted co-delivery system may also allow for temporally distinct release of drugs, which may have implications for delivery to distinct anatomical locations.

Figure 6.4 Schematic illustration of A) the intercalation of a hydrophilic anthracycline drug, such as DOX within the A10 PSMA aptamer; B) the encapsulation of a hydrophobic drug, such as Dtxl, within the PLGA-b-PEG nanocarriers using the nanoprecipitation method; and C) nanocarrier– aptamer (NP–Apt) bioconjugates comprised of PLGA-b-PEG nanocarriers surface functionalized with the A10 PSMA aptamer for co-delivery of Dtxl and DOX. Both drugs can be released from the bioconjugates over time. Reprinted with permission from ref. 281, J. Zhou, M. L. Bobbin, J. C.

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Burnett, and J. J. Rossi, Current progress of RNA aptamer-based therapeutics. Frontiers in genetics. 3, 234 (2012). CopyrightatCancer Research.

Kim et al. developed multimodal imaging probes that were capable of concurrent radionuclide imaging, MRI, and fluorescence imaging in vivo 475. The multifunctional nanocarriers used a magnetic cobalt ferrite core - encased by a silica shell which contained the fluorescent rhodamine. The nanocarriers were further modified with various organo-silicon compounds, such as (MeO)3Si-PEG or 3-aminopropyl triethoxysilane. An AS1411 aptamer was conjugated on the surface of nanocarriers and served as a nucleolin-targeting ligand 476 and p-SCN-Bn-NOTA for 67Ga-citrate incorporation provided MFR- AS1411. Multimodal nanocarriers were injected into C6-bearing nude mice, and specific tumor targeting of MFR-AS1411 was observed using radionuclide images via 67Ga radioactivity, 24 h post-injection. In contrast, nanocarriers containing mutant AS1411 (MFR-AS1411mt) were rapidly cleared from the bloodstream following i.v. administration to mice. MFR-AS1411-injected mice were further analyzed using MRI imaging techniques where T2-weighted images displayed black spots at the tumor site. Ex vivo fluorescence imaging, and high fluorescence signals from the intestine, liver, and tumors further confirmed these results that MFR-AS1411 demonstrated tumor-specific accumulation. The development of this multimodal imaging system offers the benefits of complementary modalities and eliminates the shortcomings of individual imaging modalities. Multimodal nanocarriers provides a broad range of diagnostic and therapeutic imaging possibilities in human applications 477.

Ellington et al. identified a newly anti-EGFR aptamer and its specific ‘escort’. Conjugation with gold nanocarriers (GNPs) demonstrates the internalization properties of this new aptamer 478. A RNA pool spanning 62 random sequence positions -was used to identify aptamers specific to EGFR. One aptamer predominated (aptamer J18) having a Kd value of 7 nM and was obtained after round 12 when analyzing selective binding species. GNPs (~20 nm) was conjugated to aptamer J18 by coating the GNPs with capture ONTs, followed by hybridization of an extended aptamer complementary to the capture ONTs 478. A431 cells incubated with aptamer J18-GNPs at 37°C were analyzed by flow cytometry and fluorescence microscopy with results indicating specific binding to the cell line. These results demonstrated that the internalization of GNPs is due to the aptamer directed toward cell surface EGFR, which could lead to internalization via receptor-mediated endocytosis 478. This finding suggests that receptor-specific nucleic acids can overcome non-specific absorption and internalization of GNPs, which convey chronic disadvantages during conventional therapy.

6.5 Miscellaneous targeted approaches

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The copolymer of N-acetyl D-glucosamine and D-glucuronic acid, Hyaluronic acid (HA), has been widely used as a targeting macromolecule for binding to cluster determinant 44 (CD44), -which is overexpressed in various tumors 479-481. Zhou et al. developed a thermo-responsive hybrid nanogel with HA as a targeting moiety for simultaneous temperature sensing, cancer cell targeting, fluorescence imaging, and combined chemo-photothermal treatment (Fig. 6.5) 482, 483. Templated Ag nanocarrier was used to prepare the spherical hybrid nanogel through synthesis using a thermo-responsive non-linear PEG-based hydrogel coating as a shell. Strong hydrogen bonding between HA and PEG oligomers on the shell surface helped to immobilize HA, followed by the addition of AuCl4– to the hybrid nanogel to form an Ag-Au bimetallic core 482. High drug loading capacity (46.5 wt%) was achieved in the Ag-Au-PEG-HA hybrid nanogels mainly due to the stabilization by hydrogen bonds between the ether oxygen atoms of the nonlinear PEG gel shell and the amide groups of Temozolomide (TMZ), a model drug used in the formulation. Confocal imaging of Ag- Au-PEG-HA hybrid nanogel-incubated B16F10 murine metastatic melanoma cells (CD44+) revealed significantly higher fluorescence intensity images as compared to nanogel without HA, demonstrating selective tumor targeting. Near-IR irradiation generalized localized heat during drug release profile studies and enhanced drug delivery by promoting a gradual transition from a hydrophilic to a hydrophobic PEG network 482. The gradual transition broke the PEG-TMZ bonds and also reduced the mesh size of the nanogels, further facilitating diffusion of the drug molecules from the nanocages. This combined chemo- photothermal treatment was investigated by measuring the cell viability of B16F10 cells incubated with empty or TMZ-loaded hybrid nanogels after near-IR irradiation. The combination of TMZ and photothermal treatment showed enhanced cytotoxicity as compared to other chemotherapy or photothermal treatments alone. It was shown that the combination therapy had significantly enhanced therapeutic efficacy as compared with the additive therapeutic index achieved from chemo- and photothermal therapies, suggesting that the nanogels displayed synergistic effects 482.

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Figure 6.5 Schematic illustration of multifunctional core–shell hybrid nanogels. The Ag–Au bimetallic NP (10 ± 3 nm) core is NIR resonant and highly fluorescent. The thermo-responsive nonlinear PEG-based gel shell cannot only manipulate the fluorescence intensity of Ag–Au NP core, but also trigger the release of drug molecules encapsulated in the gel shell under the local temperature increase of targeted pathological zones or the heat generated upon NIR irradiation. HA, a known targeting ligand, can be readily semi-interpenetrated into the surface networks of gel shell at a light penetration depth. Reprinted with permission from ref. 254, W. Wu, J. Shen, P. Banerjee, and S. Zhou, Core-shell hybrid nanogels for integration of optical temperature-sensing, targeted tumor cell imaging, and combined chemo-photothermal treatment. Biomaterials. 31, 7555-66 (2010). CopyrightatElsevier.

7. iRGD PEPTIDE FOR CANCER THERAPY The discovery of the structural basis of the recognition between integrin’s and their natural ligands together with the elucidation of the crystal structure of αvβ3 integrin and subsequent docking studies on this template have contributed to the rational design of a novel class of selective integrin inhibitors 484.

129 | Page sequence present in many natural ligands binding αvβ3receptor as fibrinogen, fibronectin,vitronectin, plasminogen, thrombospondin, prothrombin, MMP-2, laminin, osteopontin, etc 486. The RGD sequence is currently the basic module for a variety of molecules designed for the preferential binding to αvβ3integrin and other integrins 487. The affinity of RGD peptides for their ligands may be affected by steric conformation of the peptide 488. Besides direct interactions between additional flanking groups and their receptor, the conformational features of the RGD motif can also be modulated. Indeed, the cyclization is commonly employed to improve the binding properties of RGD peptides, conferring rigidity to the structure (Figure 7B). In linear peptides, the fourth amino acid alters the binding specificity and the nature of residues flanking the RGD sequence could influence receptor affinity, receptor selectivity, and other biological properties 488. Linear RGD peptide proved highly susceptible to chemical degradation. Since the rigidity conferred by cyclization prevents this, cyclic peptides are more stable, more potent, and more specific. In cyclic peptides, the RGD peptide sequence is flanked by other amino acids to build a ring system. These systems offer the possibility to present the RGD sequence in a specific conformation for a selected integrin 488. Cyclization of a linear RGD penta-peptide including one of the amino acids (Phe) in the unnatural D- conformation (D-Phe) resulted in the cyclic peptide c(RGDfK) developed by Kesslerand co-workers 489. Another RGD peptide ligand, the so-called RGD4C, has also been studied as targeting ligand. Never-the less, a disadvantage of this peptide is that this peptide can fold into different cyclic structures 487. Structures, chemical modifications, affinity for αvβ3, and implications in targeted therapies of the different linear and cyclic RGD peptides have been reviewed by Temming et al 487. Since the natural mode of interactions between integrin αvβ3 and RGD-containing proteins may involve multivalent binding sites, the idea to improve the integrin αvβ3 binding affinity with multivalent cyclic RGD peptides could provide more effective antagonists with better capability and higher cellular uptake through the integrin-dependent endocytosis pathway 488.

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RGD-based strategies include RGD antagonists, RGD conjugates, and RGD nanocarriers. These next few sections will overview these strategies and particularly to highlight the position of RGD-based nanocarriers in cancer therapy and imaging.

7.1 Antagonists (Non-Antibody) of αvβ3 Because of the expression of integrin’s in various cell types and their role in tumor angiogenesis and progression, integrin’s have become important therapeutic targets. Integrin antagonists currently preclinical studied or in clinical trials include (i) monoclonal antibodies (such as etaracizumab, Abegrin), (ii) RGD- based antagonists (peptidic or peptidomimetic), (iii) non-RGD antagonists (such as ATN-161, a non-RGD- based peptide inhibitor of integrin α5β1), and (iv) integrin-targeted therapeutics. Monoclonal antibodies or

131 | Page non-RGD antagonists as anti-integrin therapies have been reviewed by Avraamides et al. and Sheldrake and Patterson, respectively 486.

In preclinical studies, cilengitide effectively inhibited angiogenesis and the growth of orthotic glioblastoma 490. A cyclic RGD peptide antagonist of αvβ3 and αvβ5, cilengitide (EMD121974) showed favorable safety profiles and no-dose-limiting toxicities in phase I clinical trials 491. Cilengitide is currently being tested in phase II trials in patients with lung and prostate cancer 492 and glioblastomas 493. In addition, cilengitide has been shown to enhance radiotherapy efficiency in endothelial cell and non-small-cell lung cancer models 494. Cilengitide in combination with temozolomide and radiotherapy administered in patients with newly diagnosed glioblastoma has also demonstrated promising efficacy 495. Statement and opinion on clinical trials are discussed by Carter 492. Several additional antagonists are studied preclinical but are not tested in clinical trials yet. The peptidomimetic S247 is an αvβ3 antagonist inhibiting breast cancer bone metastasis, decreasing colon cancer metastasis and angiogenesis, and increasing survival in mice 496. The S137 peptidomimetic has shown anti-metastatic effects in xenograft tumor models 497.

Paradoxically, Reynolds et al. found that the continuous infusion of very low concentrations of RGD- mimetic inhibitors stimulates tumor growth and angiogenesis by promoting VEGF-induced endothelial cell migration 498. The enhanced tumor progression was the result of the increased tumorperfusion 499, which could be exploited to increase the delivery of chemotherapeutic agents. Indeed antiangiogenic agents, such as cilengitide, have been shown to be more effective when used in combination with chemotherapy (e.g., gemcitabine) 500. As mentioned by Desgrosellier and Cheresh, it is important to note that antiangiogenic therapies (such as cilengitide) might target multiple cell types in the tumor microenvironment, including the tumor cells themselves, and therefore their antitumor effects may not be entirely due to anti-angiogenic activity 499. Until now, with regard to preclinical and clinical studies, the efficacy of αvβ3 antagonists, as antiangiogenic cancer treatments, still remains unclear. β3and β5 knockout mice have shown that integrin inhibition may not be sufficient to completely block tumor angiogenesis 501.

Currently ongoing clinical trials will allow clarifications about the therapeutic potential of these antagonists, which have shown safety profiles and no side effects in humans 492. In the future, it will be necessary to develop not exclusively αvβ3 antagonists but dual antagonists of αvβ3 and αvβ5, since angiogenesis was shown to not be controlled by αvβ3 integrin’s alone 502. In addition, αvβ3 antagonists provide the opportunity to address chemo- and radiotherapeutics agents to tumor endothelium.

7.2 RGD-Targeted Delivery of Therapy

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Nanocarriers like liposomes, nanocarriers, micelles, etc. can be grafted at their surface with a targeting ligand such as an RGD-based sequence. Several advantages are attributable to these nanocarriers: (i) the size of these nanocarriers (20−400nm) leads to the “passive targeting” of tumors via the so-called enhanced permeability and retention (EPR) effect 503; (ii) because of the size of these systems, renal filtration is avoided, leading to prolonged blood circulation times and longer accessibility of the ligand to target receptors within the tissue 504; (iii) RGD-targeted nanocarriers may specifically address drugs to angiogenic endothelial cells and/or cancer cells by the binding of the RGD peptide to αvβ3 overexpressed by these cells, allowing the “active targeting” of the tumors 505; (iv) RGD-targeted nanocarriers can be internalized via receptor-mediated endocytosis, which is not possible with single peptide constructs or with non-targeted nanocarriers; this is particularly interesting for the intracellular delivery of drugs to cancer cells 487.

The iRGD peptide is a 9 amino acid-based cyclic, tumor specific homing, arginine-glycine-aspartic acid (RGD)-based peptide (CRGDKRGPDC), with tumor penetrating activity. The iRGD contains the RGD motif as well as the C-terminal end binding (CendR) motif that increases internalization. Upon administration, the RGD motif of the iRGD peptide is able to specifically target tumors by binding to alphavbeta3/alphavbeta5 integrins on tumor endothelium. In turn, iRGD is cleaved by specific tumor proteases, which exposes the positively charged CendR motif. This motif binds to neuropilin-1 (NRP-1), a receptor overexpressed on nueuroblstoma tumors. This increases vascular permeability of tumor blood vessels and promotes tumor penetration. Compared to other RGD peptides, this agent is able to both improve delivery and increase the accumulation of co-administered or conjugated chemotherapeutic agents in the tumor.

RGD-targeted nanocarriers have recently proven advantageous in delivering chemotherapeutics, peptides and proteins, nucleic acids, and irradiation.

7.2.1 Chemotherapy The rationale behind the design of RGD-targeted nanocarriers is the delivery of various pharmacological agents to the αvβ3-expressing tumor vasculature. The cytotoxic drug destroys the tumor vasculature, resulting in the indirect killing of tumor cells induced by the lack of oxygen and nutrients. The tumor growth might be inhibited by preventing tumors from recruiting new blood vessels as suggested by JudahFolkman 506. αvβ3 integrin is upregulated in angiogenic endothelial cells but also in several tumor cells, leading RGD-targeted nanocarriers to a potential double targeting. However, this double targeting is not yet exploited by systems delivering chemotherapeutics while it is described for integrin antagonists as etaracizumab or for RGD peptides 507, 508.

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Examples of different RGD-targeted nanocarriers are displayed in Table 7. It is important to note that the first results to show the inhibition of metastases with this kind of strategy were obtained with targeted nanocarriers loaded withdoxorubicin 509. The preferential activity of these nanocarriers on metastases suggests that growing metastatic tumors may have a greater dependence on angiogenic vessels. PLGA- basednanocarriers grafted with the R GD peptide have been designed for the delivery of paclitaxel. The targeting to the tumoral endothelium was demonstrated both In vitro and in vivo. Moreover, therapeutic efficacy has been demonstrated by effective retardation of TLT tumor growth and prolonged survival times of mice treated by paclitaxel-loaded RGD nanocarriers when compared to non-targeted nanocarriers 1.

Table 7. Non-exhaustive Examples of Recent Preclinical Studies of RGD-Targeted Nanocarriers Delivering Chemotherapeutics. Reprinted with permission from ref. 1. Danhier F, Vroman B, Lecouturier N, et al. Targeting of tumor endothelium by RGD-grafted PLGA-nanoparticles loaded with paclitaxel. J Control Release. 2009;140: 166-173

Nanocarrier Therapeutic Targeting Tumor Model Results Ref Agents Motif Nanoparticle Doxorubicin cRGD Pancreatic/renal Metastases are suppressed by disrupting 509 orthotopic the associated vasculature. mouse tumors Nanoparticles Paclitaxel GRGDS TLT The targeting of RGD grafted 1, 508 hepatocarcinom nanoparticles to tumoral endothelium a wasmore effective than nontargeted nanoparticles. Albumin Gemcitabine RGD BxPC3 The uptake of RGD nanoparticles was 510 Nanoparticles pancreatic found to be higher than cancer cells nontargetedones. The binding was mediated to αvβ3 receptor. Micelles Paclitaxel C(RGDfK) U87MG The antiglioblastoma eff ect of targeted 511 glioblastoma micelles was significantly longer thanwith other treatments. HPMA Geldanamycin C(RGDfK) DU145 prostate Tumor accumulation was increased as 512 conjugates tumor compared to the conjugate withoutRGDfK. Liposomes Paclitaxel cRGD A549 lung Targeted liposomes resulted in a lower 513 adenocarcinoma tumor microvessel density than control.

7.2.2 Peptides and Proteins Therapeutic proteins or peptides are becoming available for the treatment of cancer. However, several limitations exist including poor pharmacokinetics and side eﬀects. Some proteins, such as cytokines or

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TNF-α, show potent anticancer activity. Cell-speciﬁc targeting of proteins could enhance the antitumor activity while reducing the systemic side eﬀects.

7.2.3 Nucleic Acids Because of their great potential as therapeutics in the field of oncology, vectorization of nucleic acids has become a very productive area of research. Introduction of nucleic acids in tumor cells can either promote gene expression by bringing a gene that is not expressed or is under-expressed into cells, or silence expression of specific genes, such as oncogenes. These effects are mediated by DNA or RNAi mediators, respectively. In addition to their need to be carried through the blood flow to their site of activity aiming to avoid (i) opsonization and elimination by the RES, (ii) clearance, (iii) degradation by nucleases, and (iv) interaction with plasmatic proteins, nucleic acids should also be targeted to a specific organ, tissue, or type of cells 514. For these reasons, targeted nanosystems were designed. The specific and active targeting would diminish undesirable side effects, and reduce the necessary dose to observe an antitumor effect. In this perspective, the use of RGD peptide as a ligand to target angiogenesis-activated endothelial cells and tumoral cells via its binding to αvβ3 integrin’s is relevant.

The use of targeted nanosystems for gene therapy is a relatively new approach 514. DNA was complexed to PEI, a cationic polymer, to form polyplexes. When PEI was grafted with RGD moieties, VEGFR2 transfection into cells was enhanced 515. Chitosan and poly-L-lysine were also described in the literature recently as promising nucleic acid delivery systems 516, 517. Other types of nanocarriers have been studied, such as targeted liposomes, targeted dendrimers, or direct conjugation of RGD moieties on nucleic acid molecules 518, 519. They all showed evidence of enhancement of gene transfer In vitro and/or in vivo 520. It was demonstrated that addition of RGD moieties leads in cancerous cells to receptor-mediated endocytosis, explaining partly the increase in transfection 514.

In addition to being efficiently internalized by targeted cells, nucleic acids, either DNA or siRNA, were also therapeutically efficient, showing that they were delivered, still active, to their subcellular site of action, respectively the nucleus and the cytoplasm. Delivery of bio-therapeutics through αvβ3 integrin targeting showed enhancement in both antitumor effects and antiangiogenic effects according to the targeted gene. These results bring also evidence that RGD-targeted nanocarriers do interact with tumoral endothelium tissue but also with tumor tissue itself 520.

Even though an increasing number of nanocarriers are used for the intracellular delivery of nucleic acid, studies still demonstrated signiﬁcant toxicity such as cell contraction, mitotic inhibition, formation of

135 | Page aggregates in blood, and a tendency to induce inflammatory response. Efforts have been done to reduce this toxicity. However, their transfection efficiency needs further improvement for in vivo application 514.

7.2.4 Radionuclides Integrin antagonism may also beneﬁt radiotherapy. Exposure of tumors to irradiation causes transient upregulation of αvβ3on tumor blood vessel endothelium 494, 521. This upregulation may be used as a method of drug delivery or to enhance the eﬀects of radiotherapy 486. The αvβ3antagonistcilengitide has been shown to increase cell sensitivity to radiation in proportion to the level of integrin expression 494.

In general, an integrin αvβ3 targeted radiopharmaceutical can be divided into three parts: the targeting biomolecule (e.g. Cyclic RGD peptide), a linker, and a radio metal chelate. RGD-based targeted agents are designed for either diagnosis imaging or radionuclide therapy. Several clinically relevant radionuclides have been used for labeling bioactive peptides either for diagnostic imaging (99mTc, 111In, 66/68Ga, 18F, 123I, 64Cu) or for therapy (111In, 64/67Cu, 90Y, 177Lu, 213Bi). Radiopharmaceuticals can be used for identification of receptor-positive tumor lesions, treatment planning, and dosimetry. When labeled with a therapeutic radionuclide, the same peptide can be utilized for targeted radionuclide therapy. In this case, radiopharmaceuticals bind specifically to target receptors on tumor cells and deliver an effective radiation dose to tumor cells with minimal damage to normal tissues 522. Rajopaddhye and co-workers were the first to use cyclic RGD dimers as targeting biomolecules for the development of therapeutic (90Y and177Lu) radiotracers 488. The RGD peptide DOTA-E-[c(RGDfK)]2 was labeled with with 90Y for therapy experiments. The therapeutic efficacy of 37 MBq 90Y-DOTA-E-[c(RGDfK)]2 was compared with that of 37 MBq administered in five equal portions. No difference in tumor growth between the fractionated and the non-fractionated therapy was observed 523. Another example is the HPMA−RGD conjugates containing side chains for 99mTc (imaging) and 90Y (therapeutic). Treatment of in vivo DU145 xenografts showed significant decreases in tumor volume for 250 μCi 90Y doses when compared to control. HPMA−RGD conjugates inhibited αvβ3 mediated endothelial adhesion and remained active while HPMA homo-polymer showed no activity 524. Recently, RGD conjugate gold nanorods were designed to induce the radiosensitization in melanoma cancer cells by down-regulating αvβ3 expression in addition to induction of a higher proportion of cells within the G2/M phase 510.

7.2.5 Thernostics Antibodies, liposomes, nanocarriers, and micelles carrying contrast agents have already shown potential to detect diseases and visualize various important aspects for the drug delivery process. In addition, nanomedicines are being prepared to combine diagnostic and therapeutic agents. Applications of

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“nanotheranostics” are extended: nano-theranostics allow (i) the noninvasive evaluation of the biodistribution and the target site accumulation of nanocarriers; (ii) the monitoring and the quantification of the drug release; (iii) the facilitation of therapeutic intervention relying on triggered drug release; (iv) the prediction of therapeutic response; and (v) the longitudinal monitoring of the efficacy of therapeutic interventions 525. By the noninvasive assessment of the biodistribution and the target site distribution, nanotheranostics allow the optimization of drug delivery systems in order to improve the treatment of individual patients and to better understand several important aspects of drug targeting to pathological sites 526. Hence, Lee and colleagues developed “all-in-one” magnetic nanocarriers. These nanocarriers contained iron oxides as contrast agent, siRNA as therapeutic agent, an RGD-containing peptide as target ligands of the αvβ3 integrin’s, and a fluorescent dye for fluorescent microscopy 525. Other RGD-targeted nanotheranostics were studied such as HPMA−drug conjugate containing DY-615 as contrast agent 527or PLA micelles containing SPIO as contrast agent 51. Interestingly, RGD-targeted paramagnetic nanocarriers were designed for both delivering antiangiogenic therapy and detecting the tumor response. In this study, it was demonstrated that the characterization of angiogenesis with MR molecular imaging might identify tumors with low levels of neovasculature that may respond poorly to antiangiogenic therapy 528.

7.2.6 iRGD Cyclic Penetrating Peptide Interestingly, two recent papers 13, 529 have shown that the iRGD cyclic peptide has the potential to selectively deliver a large variety of therapeutic or diagnostic agents to a tumor site. The cyclic iRGD is constituted from CRGDK/RGPDC, containing a cryptic CendR motif, CRGDK/R that possesses CendR- like tissue and cell penetrating activities.

Intravenously injected compounds coupled to iRGD bound to tumor vessels and spread into the extravascular tumor parenchyma, whereas conventional RGD peptides (CRGDC and RGD-4C) only delivered the cargo to the blood vessels. In a first step, the intact peptide binds to the endothelial cell expressing αv integrin’s. In a second step, a protease cleaves iRGD and exposes the cryptic CendR motif, which can interact with the neuropilin-1 receptor and thereby increase tumor vascular permeability (Fig. 7.1). The proteolytically processed CRGDK fragment has lost most of its affinity to the integrin’s. Instead, the C RGDK fragment acquires an affinity for neuropilin-1 that is stronger than its residual affinity for αv integrin. These changes likely facilitate the transfer of CRGDK from integrin’s to neuropilin-1, and the resulting penetration activities. Studies on the time dependence of iRGD and penetration further supported the importance of αv integrin andneuropilin-1 expression in this process. M21 human melanoma cells expressing both αvβ3 and αvβ5 bound iRGD phage, whereas variants lacking expression of these integrin’s

137 | Page did not, conﬁrming the αv integrin dependency of iRGD binding. Importantly, tumor cells strongly positive for neuropilin-1 was particularly eﬀective at accumulating and retaining iRGD.

The potential of this tissue-penetrating peptide was demonstrated for preclinical applications by performing MRI and tumor treatment studies 13. Remarkably, this penetrating peptide works not only when conjugated to the payload but also when it is co-administered. Systemic injection with iRGD improved the therapeutic index of drugs of various compositions including small molecules (doxorubicin), nanocarriers (nab- paclitaxel (Abraxane) and doxorubicin liposomes) and a monoclonal antibody (trastuzumab). Thus, coadministration of iRGD may be a valuable way to enhance the eﬃcacy of anticancer drugs while reducing their side eﬀects, a primary goal of cancer therapy research.

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7.3 Summary of RGD Peptide as a Potential Ligand to Target Tumors The RGD peptide is an effective ligand for tumor targeting since it has been shown that integrin αvβ3isoverexpressed not only on tumoral endothelium but also on cancer cells, for a lot of cancer cell lines 499, 507. Nanocarriers grafted with the RGD peptide may thus be considered as double targeting system. To our knowledge, other largely described ligands such as folate or transferrin are only expressed on cancer cells. Moreover, integrin’s αvβ3 are known to be poorly expressed in non-angiogenesis activated endothelial cells. On the contrary, transferrin is expressed at elevated levels on cancer cells but also on brain capillaries, endocrine pancreas, or Kupffer cells of the liver 530. In addition, some ligands, such as folate, that are supplied by food, show naturally high concentrations in the human body and might compete with the nanocarrier-conjugated ligand for binding to the receptor, effectively reducing the intracellular concentration of delivered drug 531. The major advantage of the RGD nanocarriers is precisely this possible double targeting. First, endothelial cells are targeted because of their expression of the integrin αvβ3, and cancer cells (which also expressed the integrin αvβ3) are targeted after extravasation of nanocarriers. Second, the potential normalization resulting of antiangiogenic properties (RGD targeting and intrinsic property of some anticancer drugs) of nanocarriers could enhance the delivery of drugs into tumors. Furthermore, this is the rationale of many combinations of treatments tested in clinical trials. Indeed, in human, because of the slow growth of tumors (compared with tumor-bearing mice models), the maturation of tumor vasculature is more complete, and then antiangiogenic therapies combined with chemotherapy or radiotherapy are therefore a rational strategy for tumor eradication 532.

In conclusion, one of the major pitfalls in the field of tumor-targeted drug delivery relates to the fact that the EPR is often misinterpreted. The EPR effect is a highly heterogeneous phenomenon, which varies substantially from tumor model to tumor model, as well as from patient to patient. Another aspect relates to the overestimation of the potential usefulness of active drug targeting. Theoretically, the benefit of targeted nanocarriers is to be retained more efficiently and more rapidly than non-targeted ones. However, the introduction of targeting moieties often leads to an increase in immunogenicity and in protein adsorption. The main advantage of actively targeted nanocarriers over passively targeted formulations is that they are taken up by cancer cells more efficiently 508.

The approach of using RGD peptides and peptidomimetics, either in the targeted nanomedicine ﬁeld or as radiopharmaceuticals, has successfully been translated from preclinical studies to bedside, meaning that more progress is to be expected. Because of a large number of clinical trials performed to date and several approved formulations combined with other treatment modalities (such as standard chemotherapy or

139 | Page radiotherapy), it can be predicted that, in years to come, tumor-targeted strategies including nanomedicines will be integrated in combined modality anticancer therapy.

8. THERNOSTICS MULTIFUNCTIONAL NANOCARRIERS FOR CHEMOTHERAPY AND IMAGING Theranostics, the combination of therapeutic and imaging methods on a single level, have reached new possibilities thanks to recent advances in nanotechnology 533-535. These nanotechnology advancements incorporate imaging probes for the enhancement of image resolution and specificity towards target tissues. Nanocarriers conjugated to active targeting ligands usually make up these imaging probes 415, 536. Nanocarriers having no active target ligand coupled to -their surface will be passive targeting, mediated by the enhanced permeability and retention effect (EPR) 537, 538. Theranostic nanomedicine has the potential for simultaneous and real time monitoring of drug delivery, trafficking of drug and therapeutic responses.

Small molecule drugs often display many disadvantages including the lack of sufficient specificity to the tumor, severe and toxic side effects in healthy tissues, limited delivery of hydrophobic drugs to the tumor cells, and the development of drug-resistance 84, 539. It has been described in this review that NPs can provide a potential solution to these problems in traditional chemotherapy 84, 540, 541.One such solution is the development of theranostic NPs which incorporates imaging agents and drugs such as DOX or PTX - used for simultaneous imaging and targeted chemotherapy of diseases and cancers 542, 543.

As described, theranostic NPs can simultaneously provide cancer detection, drug delivery, and real-time evaluation of therapeutic efficacy. Kim et al. developed chitosan-based NPs (CNPs) that were labeled with Cy5.5, a NIR fluorescence dye for imaging, and encapsulated with PTX for cancer therapy (PTX–Cy5.5– CNP) to produce a multifunctional thernostic NPs (Fig. 9A through Fig. 9G) 14, 544-546. SCC7 tumor-bearing mouse models -were treated dose-dependently with PTX–Cy5.5–CNP to the tumor sites which -were then visualized using optical imaging technology. Repeated injections at three-day intervals modulated and increased the therapeutic efficacy of PTX–Cy5.5–CNP. Strong NIR fluorescence signals were observed in the targeted tumors. This optimal protocol of repeated injections of PTX–CNPs at three-day intervals greatly increased the drug concentration in targeted tumors which resulted in enhanced therapeutic efficacy to tumor tissues while minimizing toxicity to normal tissues. This demonstrated that the optimal dosage of the drug in question may be identified using theragnostic NPs, thereby increasing both effectiveness and safety of the drug. SCC7 tumor-bearing mouse models were also analyzed using NIR fluorescence imaging for direct monitoring of tumor growth in response to PTX–Cy5.5–CNP administration (Fig. 9.1A through

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Fig. 9.1D). The possibility -of determining the optimal dosage of drug for the individual patient at the right time using theragnostic NPs may hold promise in paving the way for personalized medicine.

Figure 9. A) Conceptual description of a theragnostic nanoscale particle designed for cancer imaging and treatment. The theragnostic chitosan-based nanocarriers (CNPs) can preferentially accumulate at the tumor tissue by the enhanced permeation and retention (EPR) effect due to their unique properties, such as stability in blood, deformability, and fast cellular uptake. B) Chemical structure of the glycol chitosan conjugates labeled with Cy5.5, a near-infrared fluorescent (NIRF) dye, and modified with hydrophobic 5β-cholanic acid. C) A TEM image of Cy5.5-labeled CNPs (1 mg/ml) in distilled water. D) Bright field and NIRF images of the Cy5.5-labeled CNPs in PBS. The NIRF image was obtained using a Cy5.5 filter set (ex = 674 nm, em = 695 nm). E) Time-dependant size

141 | Page distribution of Cy5.5-labeled CNPs in PBS at 37 °C was confirmed using dynamic light scattering. F) Filtration of water-soluble glycol chitosan (GC), CNPs, and polystyrene (PS) beads through filters of different pore sizes (0.8 μm, 0.45 μm, and 0.2 μm). The amount of each particle passed through the filters was quantified through NIRF intensity of the filtrate. (G) In vitro stability of the Cy5.5-labeled CNPs was determined using an SDS-PAGE test. Cy5.5-labeled GC polymers and CNPs were incubated in 10% serum for 6 h at 37 °C and their migratory positions were monitored using a Cy5.5 filter set. Reprinted with permission from ref. 14, K. Kim, J. H. Kim, H. Park, Y. S. Kim, K. Park, H. Nam, S. Lee, J. H. Park, R. W. Park, I. S. Kim, K. Choi, S. Y. Kim, K. Park, and I. C. Kwon, Tumor- homing multifunctional nanocarriers for cancer theragnosis: Simultaneous diagnosis, drug delivery, and therapeutic monitoring. J. Cntrl. Release. 146, 219-27 (2010). CopyrightatElsevier.

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143 | Page represents the bright field images of individual organs. A strong NIRF signal was observed in tumor tissues at all experimental times. D) Ex vivo imaging of SCC7 xenograft tumor showed higher NIRF signal than other organs at all time points. A quantification of in vivo targeting characteristics of Cy5.5-labeled CNPs was recorded as total photons per centimeter squared per steradian (p/s/cm2/sr) per milligram of each organ at all time points (n = 3 mice per group). All data represent mean ± s.e. Reprinted with permission from ref. 14, K. Kim, J. H. Kim, H. Park, Y. S. Kim, K. Park, H. Nam, S. Lee, J. H. Park, R. W. Park, I. S. Kim, K. Choi, S. Y. Kim, K. Park, and I. C. Kwon, Tumor-homing multifunctional nanocarriers for cancer theragnosis: Simultaneous diagnosis, drug delivery, and therapeutic monitoring. J. Cntrl. Release. 146, 219-27 (2010). CopyrightatElsevier.

Similarly, Chen et al. recently demonstrated pH-responsive NPs encapsulated with DOX to better understand drug release behavior and intracellular localization (Fig. 9.2) 15. Hydrophobic N-palmitoyl groups were conjugated to chitosan to prepare a PH-responsive polymer then followed by attachment with Cy5.5. PH-responsive polymers were able to self-assemble into NPs and encapsulate DOX within aqueous media, yielding DOX–Cy5–NPs. DOX (donor) and Cy5 (acceptor) in NPs were sufficiently close for energy transfer to occur (FRET on) at pH ≥ 7.0, whereas DOX and Cy5.5 were not in close proximity (FRET off) in the protonated form of DOX–Cy5–NPs at low pH 15. No fluorescence of DOX was observed, after internalization to cells, when DOX–Cy5–NPs was in the cavelolae/caveosomes (FRET on with high efficiency) and having a weak fluorescence in the cytosol when DOX–Cy5–NPs was in slightly acidic early endosome (FRET on with low efficiency). However, strong fluorescence signals were observed in the cytosol when DOX–Cy5–NPs was in acidic late endosomes/lysosomes (FRET off) (Fig. 9.3). This study indicated that theragnostic NPs employing the FRET technique can allow intracellular monitoring of drug release 15.

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Intravital microscopy has had a great deal of -success when it comes to examining cellular behavior and molecular signals under conditions simulating a natural environment in living animals at subcellular resolution 547-549. Whole body imaging using fluorescence or bioluminescence usually provides only macroscopic resolution as compared to intravital microscopy. Intravital -microscopy includes an in vivo CLSM used to directly assess in vivo distribution of the drug carrier or drug across various cellular locations. Intravital microscopy may also be used to understand the delivery mechanism of nanocarriers and -their

146 | Page payload to the targeted tissue 550, 551. Cabral et al. fabricated drug-loaded micelles composed of poly- (glutamic acid) and hydrophilic PEG block copolymer, and - used them for intra-vital imaging 16. Highly permeable tumors (C26) and poorly permeable tumors (BxPC3) were used to observe in vivo biodistribution and antitumor activity of drug-loaded micelles having a range of diameters. Alexa dye-labeled micelles were used for in vivo CLSM imaging. It was shown through real-time imaging via in vivo CLSM of a mouse, that various sized micelles (diameters of 30, 50,70 and 100 nm) penetrated through highly permeable tumors-; however, only 30 nm micelles accumulated in poorly permeable tumors to achieve an antitumor effect (Fig. 9.4A through Fig. 9.4G). These results indicated that in vivo CLSM can contribute to the analysis of cellular internalization, tissue penetration and the extravasation profile of NPs in living mice 15.

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Figure 9.4 In vivo real-time microdistribution of DACHPt/m with different diameters in tumours. a, b) Microdistribution of fluorescently labelled 30 nm (green) and 70 nm (red) micelles 1 h after

148 | Page injection into C26 (a) and BxPC3 (b) tumours. Their colocalization is shown in yellow. Right panels in a and b show fluorescence intensity profile from the blood vessel (0–10mm; grey area) to the tumour tissue (10–100 mm) in the selected region (indicated by a white rectangle) expressed as a percentage of the maximum fluorescence intensity attained in the vascular region (%Vmax). c, d) Z- stack volume reconstruction of C26 (c) and BxPC3 (d) tumours 1 h after co-injection of the fluorescent micelles. e) Magnification of the perivascular region (indicated by a white trapezium) of the z-stack volume image of BxPC3 tumours. f, g) Distribution of 30 and 70 nm micelles 24 h after injection into C26 tumours (f) and BxPC3 tumours (g). White arrows in g indicate 70 nm micelles localizing at perivascular regions. Right panels show fluorescence intensity profile from the blood vessel (0–10 mm; grey area) to the tumour tissue (10–100 mm) in the selected region (indicated by white rectangle). Reprinted with permission from ref. 16, H. Cabral, Y. Matsumoto, K. Mizuno, Q. Chen, M. Murakami, M. Kimura, Y. Terada, M. R. Kano, K. Miyazono, M. Uesaka, N. Nishiyama, and K. Kataoka, Accumulation of sub-100 nm polymeric micelles in poorly permeable tumours depends on size. Nature nanotechnology. 6, 815-23 (2011). CopyrightatNature Publishing Group.

During chemotherapy, theragnostic NPs are highly useful for providing real-time information on its location, release or efficacy of the contained drug and detecting residual tumor cells with various optical imaging techniques as shown in the above-mentioned studies. In addition, they enable the identification of the optimal dosage of the drug in question and may hold promise in the personalized medicines.

9. THERNOSTICS SUMMARY Theranostics, the combination of therapeutic and imaging methods on a single level, have reached new possibilities thanks to recent advances in nanotechnology 533-535. These nanotechnology advancements incorporate imaging probes for the enhancement of image resolution and specificity towards target tissues. Nanocarriers conjugated to active targeting ligands usually make up these imaging probes 415, 536. Nanocarriers having no active target ligand coupled to -their surface will be passive targeting, mediated by the enhanced permeability and retention effect (EPR) 537, 538. Theranostic nanomedicine has the potential for simultaneous and real time monitoring of drug delivery, trafficking of drug and therapeutic responses.

10. QUANTIFICATION OF α-DIFLUOROMETHYLORNITHINE (DFMO) AND ETOPOSIDE USING HIGH PERFORMANCE LIQUID CHROMATOGRAPHY (HPLC) AND PLATE- READER

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Introduction HPLC is a dominant analytical technique that have been widely practiced for five decades. Innovations such as ultrahigh-pressure liquid chromatography (UHPLC), liquid chromatography–mass spectrometry (LC–MS), two-dimensional liquid chromatography (2D-LC), chiral separations, core–shell columns, and novel stationary phases have helped drive HPLC to higher performance in diverse applications, yielding faster speed, higher resolution, greater sensitivity, and increased precision. The practice of HPLC is no longer limited to specialists or "chromatographers," but is now widely performed by students, chemists, biologists, production workers, and other novices in academia, research, and quality control laboratories.

Recently researchers have tried to find ODC inhibitors comparable to DFMO and thus there is a requisite for a simple spectrophotometric assay for easy and fast screening of inhibitors. Earlier, numerous methods have been reported for estimating ODC activity which can be categorized to radioactive and non- radioactive methods281, 552-567. Radioactive methods are hazardous (spurious CO2 release) while non- radioactive methods have many disadvantages involving sophisticated instruments, and cost-effectiveness. Hence, we tried to develop a simple, contemptible method. The assay is an improved, uncomplicated and cost- effective involving petite quantity of chemicals.

Etoposide is a semi synthetic derivative of epipodophyllotoxin and believed to act by the inhibition of topoisomerase enzyme and/or induction of direct DNA breaks568. It is preferably used for the treatment of patients with small cell lung cancer, testicular tumors, Kaposi’s sarcoma and lymphomas. Several HPLC methods were reported for etoposide with UV569, 570, fluorescence571, and electrochemical572, 573 detectors with complicated extraction procedures. Most of these methods were for the estimation of etoposide in biological matrix like blood574, plasma571, 574-576, urine577, CSF577, and leukemic cells577. Very few HPLC methods are reported for the estimation of etoposide in intravenous nanocarrier formulations578, 579. These methods were developed using phenyl and cyano columns; require internal standard for estimation of etoposide and retention times were high.

The main purpose of this chapter is to develop and validate reversed phase HPLC method which is simple, precise, sensitive and selective for the quantification of DFMO and Etoposide in nanocarrier formulations. The developed method can be easily used in routine quality control and for dissolution studies at very low concentrations of each drug. Suitable statistical tests were performed on validation data.

10.1.1 Derivatization of DFMO using TNBSA (2, 4, 6-trinitrobenzene sulfonic acid) assay for UV- detection

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Rationale A number of methods have been investigated for use in the estimation of free amino groups 580. One of these compounds is 2, 4, 6-trinitrobenzenesulfonic acid (TNBS). It was introduced by Okuyama and Satake 581 as a reagent for amino groups, specifically for those in amino acids and peptides. This reagent is water- soluble, reasonably stable, and reacts with amino groups under comparatively mild conditions to give an orange trinitrophenyl (TNP) derivative, which forms a stable yellow color at pH 10. However, the TNP derivative will also react with sulfite in a basic medium to yield a stable complex with maximum absorption near 425 nm 582. TNBS has been used in a number of methods for estimating amino acid nitrogen 583, 584. It does not react with ammonia and urea to any appreciable degree and is ideally suited for this purpose. Because of its solubility in water, it reacts with the amino groups in protein solutions.

An analytical method based on post-column derivatisation of DFMO with orthophthaldialdehyde (OPA) recently been developed using fluorescence detection and cation-exchange liquid chromatography (glass column packed manually with polystyrene–divinylbenzene cross-linked resin beads). This method was used for the measurement of DFMO in human plasma, CSF and urine 585. Fluorescence detection at excitation /emission wavelengths of 340/440 nm was followed by post-column derivatization with OPA. Sample preparation was done by protein precipitation of biological samples (100 ml) with trichloroacetic acid (20, 40%) or 5-sulfosalicylic acid. Total run time was 53 min. Sensitivity of the method was five nmol/ ml.

Altogether, the above mentioned methods suffer from one or more of the following shortcomings, namely, relatively large sample volume, low sensitivity, lack of an internal standard, and long or sophisticated sample preparation or chromatographic procedures 585.

A precise method has been developed for quantification of ornithine, a substrate structurally similar to DFMO that actively competes for the binding site on the ornithine decarboxylase enzyme 586. The method endowed a colorimetric end point that is non-destructive, indefinitely stable and perceptible to the naked eye. Through the observation that picrylsulfonic acid (2,4,6-trinitrobenzenesulfonic acid, TNBS) reacts at alkaline pH with amines and the amino groups to give colored trinitrophenyl (TNP) adducts 586. This method will allow for the observation of TNP adducts of DFMO (TNP-DFMO-TNP) yielding a uv-active product that is further quantified by HPLC procedures.

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Figure 10. Reaction of 2, 4, 6-trinitrobenzenesulfonic acid with a primary amine containing molecule to produce trinitrophenyl derivative. Trinitrophenyl molecule is UV-active at 345nm. TNBS protein- sulfite complex is formed by a simple one stage hydrolysis reaction in a base solution.

Materials Chemicals and reagents TNBSA stock solution (2, 4, 6-trinitrobenzene sulfonic acid, 5% w/v) was obtained from ThermoFisher Scientific (Sunnyvale, CA, USA) (Cat. No. 28997). HPLC grade methanol was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 67-56-1) and used throughout the study. Boric acid (Cat. No. 10043-35-3), sodium hydroxide (Cat. No. 1310-73-2), and sodium chloride (Cat. No. 7647-14-5) of analytical grade were purchased from VWR International (VWR, Radnor, PA, USA). The α- difluoromethylornithine (DFMO) drug was kindly provided by Dr. Dana-Lynn Koomoa-Lange (University of Hawaii at Hilo, HI, USA). Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA).

Equipment and chromatographic conditions The chromatographic system consisted of an Dionex Ultimate 3000 module (ThermoFisher Scientific, Sunnyvale, CA, USA) with an online degasser and an analytical auto-sampler WPS-3000(T)SL thermostated at 22°C. The Dionex module was coupled to an Ultimate 3000 Rapid Separation Diode Array Detector (DAD-3000RS) with Dionex Chromeleon chromatography data acquisition software (version 7.1) (ThermoFisher Scientific, Sunnyvale, CA, USA) for anaylsis of chromatography data. Separations were performed on a Phenomenex Kinetex XB-C18 (250 mm x 4.6 mm, particle size 5 µm) (Phenomenex, Torrance, CA, USA) (Cat. No. 00G-4605-E0) analytical column maintained at a temperature of 22°C. The gradient method utilized two mobile phases; ammonium acetate buffer (0.01M, pH 7) and HPLC grade methonal, both filtered through a 0.2 µm nylon filter membrane (Millipore, Bedford, MA, USA) before use. The flow rate was 1.0 mL/min and the assay total runtime was 14 minutes. Absorbance was measured at 345 nm.

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Methods Preparation of stock solutions, working solutions and calibration standards A stock solution of 0.5 mg/mL DFMO was prepared in ultrapure distilled deionized water (DI-water). The stock solutions are further diluted with borate buffer (pH 10.2) to obtain calibration standards with concentrations of 10, 20, 30, 40 and 50 µg/mL. The stock and calibration standards were prepared fresh before each analysis and stored away from daylight at 4°C. Borate buffer was prepared by dissolving on low heat; 3.09g boric acid and 2.19g sodium chloride in 500 mL of DI-water. Borate buffer pH was adjusted to 10.2 with sodium hydroxide and filtered through a 0.2 µm nylon filter membrane. TNBSA stock solution (5% w/v) were diluted further in borate buffer (pH 10.2) to obtain a working solution of 0.025% w/v final concentration. TNBSA was prepared fresh before each analysis and stored away from daylight at 4°C. Ammonium acetate buffer (0.01M, pH 7) was prepared by dissolving 0.77g ammonium acetate in 1L of DI-water. Ammonium acetate buffer (0.01M) was then filtered through a 0.2 µm nylon filter membrane.

Sample preparation Samples were prepared for HPLC-UV analysis using the TNBSA assay. Calibration standards prepared fresh in borate buffer (10.2) were aliquoted (800 µL each) into HPLC vials. Working TNBSA solution (0.025% w/v, 250 µL) were added into each calibration standard HPLC vial. The vials were placed in a 37°C water bathe and allowed to react for 2h.

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Figure 10.1 One-step hydrolysis reaction of 2, 4, 6-trinitrobenzenesulfonic acid (TNBSA) with primary amine containing α-difluoromethylornithine (DFMO) drug molecule yields Trinitrophenyl- DFMO-Trinitrophenyl (TNP-DFMO-TNP) derivative. TNP-DFMO-TNP molecule is UV-active at 345nm. 0.025% w/v TNBSA stock solution in DI-H2O used as reactant. DFMO suspended in borate buffer 10.2 allows for protonation of both primary amine groups. TNBS protein-sulfite complex is formed by a simple one stage hydrolysis reaction.

The trinitrophenyl protein-sulfite complexes resulting from reaction of TNBS with protein in the presence of sulfite are highly colored and exhibit maximum spectral absorbance at 345nm. The TNBS protein-sulfite complex is formed by a simple one stage hydrolysis reaction. Protein in concentrations as low as 0.2μg may be detected by the reaction 580. The colorimetric end point is non-destructive, indefinitely stable and perceptible to the naked eye.

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Method Validation The method was validated in accordance with the US Pharmacopoeia and the International Conference on Harmonization (ICH) guidelines.

Results 10.1.2 Quantification of DFMO derivative using Biotek plate-reader Quantification of TNP-DFMO-TNP derivative were performed in both BioTek Synergy plate reader and Dionex Ultimate 3000 HPLC. Both instruments helped to validate one another and either could be used for the quantification of the DFMO derivative. This chapter briefly describes the quantification of the TNP- DFMO-TNP adduct using a BioTek Synergy plate reader. At this point, both drugs (DFMO and Etoposide) are quantified separately to better understand their stability and properties on their own. A method is later described in the chapter to quantify both drugs using one analytical method.

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BioTek plate reader of TNP-DFMO-TNP at 345nm 1.6 1.4 1.2 1 0.8 y = 0.0205x + 0.2537 0.6

Absorbance R² = 0.997 0.4 0.2 0 0 10 20 30 40 50 60 70 Concentration (ug/mL)

A simple and straightforward method has been developed for the quantification of the TNP-DFMO-TNP adduct having a linear regression value of 0.997 (Fig. 10.2). The current method shows linearity over a range of 10 to 60ug/mL when analyzed using a BioTek plate reader at 345nm. The quantification of the TNP-DFMP-TNP adduct will then be analyzed using a Dionex Ultimate 3000 HPLC instrument (next section) followed by the quantification of DFMO derivative and Etoposide simultaneously utilizing only one procedure.

10.1.3 Quantification of DFMO derivative using HPLC Quantification of TNP-DFMO-TNP derivative were performed in both BioTek Synergy plate reader (previous section) and showed linearity over a range of 10 to 60ug/mL. This section will describe the quantification of the TNP-DFMO-TNP adduct analyzed using the Dionex Ultimate 3000 HPLC istrument. Both instruments helped to validate one another and either could be used for the quantification of the DFMO derivative. However, HPLC analysis may prove to be an more efficient and sensitive approach at

156 | Page quantifying the TNP-DFMO-TNP adduct. HPLC analysis will be used for simultaneous detection of both drugs; DFMO and Etoposide, using only one method (next section).

Table 10.1 Dionex Ultimate 3000 HPLC Gradient method for TNP-DFMO-TNP elucidation (40- minute total run-time) at 345nm. TNBSA reagent had a retention time of 2 minutes with the TNP- DFMO-TNP adduct having a retention time of 29 minutes. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP-DFMO-TNP derivative analyzed after 2h. Time (minutes) % Solvent A % Solvent B (Methanol) (0.01M Ammonium Acetate) 0 to 10 mins 10% 90% 10 to 20 mins 10% to 25% 90% to 75% 20 to 30 mins 25% to 50% 75% to 50% 30 to 40 mins 50% to 10% 50% to 90%

Figure 10.3 A representative chromatogram of DFMO derivative (TNP-DFMO-TNP, retention time of 30.35 minutes) and TNBSA reagent (retention time of 2 minutes) versus the Absorbance area (mAU*min) at 345nm. Chromatogram represents concentration range of 10 to 50ug/mL of TNP- DFMO-TNP adduct. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-

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H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP-DFMO-TNP derivative analyzed after 2h.

Table 10.2 Standard curve parameters for TNP-DFMO-TNP adduct in a range of 10 to 50ug/mL using absorbance area (mAU*min) at 345nm. Linearity range were performed in triplicates. The linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression was equal to 0.999 for all batches. Absorbance Absorbance Absorbance Absorbance Concentration Batch 1 Batch 2 Batch 3 (mAU*min) (μg/mL) (mAU*min) (mAU*min) (mAU*min) Mean ± SD 10 9.6947 9.7156 9.6878 9.6993 ± 0.014 20 19.2805 19.2925 19.2794 19.28413 ± 0.007 30 29.118 29.1289 29.1063 29.11773 ± 0.011 40 38.7902 38.8014 38.7896 38.79373 ± 0.006 50 48.8352 48.8421 48.8247 48.834 ± 0.008

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TNP-DFMO-TNP adduct at 345nm absorbance area (mAU*min)

60 Absorbance Batch 1 (mAU) y = 0.9779x - 0.1935 R² = 0.9999 50 Absorbance Batch 2 (mAU) y = 0.9776x - 0.1725 R² = 0.9999 Absorbance Batch 3 (mAU) 40 y = 0.9778x - 0.1976 R² = 0.9999 30

Absorbance areaAbsorbance (mAU*min) 10

0 0 10 20 30 40 50 60 TNP-DFMO-TNP concentration (ug/mL)

Figure 10.4 Linearity graph of standard curve parameters of DFMO derivative (TNP-DFMO-TNP) quantified using Dionex Ultimate 3000 HPLC at 345nm. DFMO drug were treated with 250uL of 0.025% w/v TNBSA solution in DI-H2O and borate buffer 10.2. Reaction proceeded over 2 hours at 37°C. TNP-DFMO-TNP derivative analyzed after 2h. Linearity was found in a range of 10 to 50ug/mL using absorbance area (mAU*min). Linearity range were performed in triplicates.

Table 10.3 Standard curve parameters for TNP-DFMO-TNP adduct in a range of 10 to 50ug/mL using absorbance area (mAU*min) at 345nm. The linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Label Slope Intercept r-square Batch 1 0.9779 0.1935 0.9999 Batch 2 0.9776 0.1725 0.9999 Batch 3 0.9778 0.1976 0.9999 Mean 0.9778 0.1879 0.9999 Std. Dev. 0.000153 0.01346 N/A N 3 3 3

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%CV 0.016 7.1634 N/A

Table 10.4 Bench top stability studies of TNP-DFMO-TNP adduct solution at two different concentrations of TNP-DFMO-TNP (0.250, 50.20 µg/mL) at 4 different time intervals; 0, 2, 4, and 6 hours. Absorbance area (mAU*min) are collected at 345nm. Data shows that the drug solution over a 6-hour period were stable within the experimental conditions of the developed method as depicted by CV (<3%). Further studies revealed TNP-DFMO-TNP derivative to be stable over 72h time frame. 0 h 2 h 4 h 6 h LC HC LC HC LC HC LC HC Concentration µg/mL µg/mL µg/mL µg/mL µg/mL µg/mL µg/mL µg/mL 0.255 50.31 0.256 50.33 0.257 50.33 0.256 50.24 0.256 50.25 0.254 50.28 0.255 50.24 0.255 50.26 0.251 50.32 0.252 50.24 0.253 50.34 0.251 50.31 Mean 0.254 50.29 0.254 50.28 0.255 50.30 0.254 50.27 SD 0.003 0.038 0.002 0.045 0.002 0.055 0.003 0.036 N 3 3 3 3 3 3 3 3 %CV 1.04 0.08 0.79 0.09 0.78 0.11 1.04 0.07 Nominal 0.250 50.20 0.250 50.20 0.250 50.20 0.250 50.20

Table 10.5 Data of within-batch precision and accuracy of TNP-DFMO-TNP adduct using one batch for each concentration. Absorbance area (mAU*min) are collected at 345nm. Data shows that the TNP-DFMO-TNP adduct solution was precise within the experimental conditions as depicted by CV (<3%). Accuracy was greater than 97% for all three concentrations. Label Low Concentration Medium Concentration High Concentration Chromatogram (ug/mL) (ug/mL) (ug/mL) Area (mAU*min) Area (mAU*min) Area (mAU*min) 1 0.244 5.52 50.23 2 0.241 5.55 50.29 3 0.254 5.54 50.32 4 0.243 5.56 50.17

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5 0.242 5.53 50.35 6 0.241 5.54 50.25 Mean 0.244 5.54 50.27 Std. Dev. 0.005 0.013 0.060 N 6 6 6 Nominal 0.250 5.50 50.20 %CV 1.8531 0.2330 0.1185 %Accuracy 97.67 99.27 99.86

Table 10.6 Data of between batches precision and accuracy of TNP-DFMO-TNP adduct using three separate batches at three different concentrations. Absorbance area (mAU*min) are collected at 345nm. Data shows that the TNP-DFMO-TNP adduct solution was precise within the experimental conditions as depicted by CV (<3%). Accuracy was greater than 99% for all three concentrations. Label Low Concentration Medium Concentration High Concentration (ug/mL) (ug/mL) (ug/mL) Batch 1 0.248 5.51 50.23 0.249 5.54 50.29 0.251 5.53 50.32 Batch 2 0.247 5.52 50.17 0.249 5.51 50.35 0.250 5.50 50.25 Batch 3 0.246 5.52 50.27 0.249 5.49 50.21 0.251 5.51 50.31 Mean 0.249 5.514 50.27 SD 0.002 0.015 0.057 N 9 9 9 Nominal 0.250 5.50 50.20 %CV 0.6796 0.2737 0.1142 %Accuracy 99.56 100.26 100.13

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Linearity and range The calibration curve was constructed by analyzing a series of derivative calibration samples to obtain concentrations ranging from 10 to 50μg/ml. The peak area of the DFMO derivative was used for plotting the linearity graph. The linearity was evaluated by linear regression analysis, which was calculated by the least square regression method.

Limit of Detection (LOD) and Limit of Quantification (LOQ) LOD (limit of detection) of DFMO derivative was determined directly by serial dilution method and was found 0.2μg/mL. LOQ (limit of quantification) of DFMO derivative was 0.2μg/mL. LOD and LOQ values were determined with suitable accuracy and precision between batches and within batches and data is given in Table 10.5 & Table 10.6. Bench top stability method was employed in stability studies of DFMO derivative. The drug at two different concentrations was studied in triplicate with an interval of 2 hours till 6 hours as given in Table 10.4. Data shows that the drug solution was stable within the experimental conditions of the developed method as depicted by CV (<3%).

Recovery Recovery studies were performed by analyzing DFMO derivative sample at concentrations of 0.250, 5.50, 50.20μg/ml. The recovery from each concentration was measured from the average of six injections.

Precision and Accuracy The precision and accuracy of the assay was determined by repeatability (intra-day) and intermediate precision (inter-day) using different sample of DFMO derivative (0.250, 5.50, 50.20μg/ml). For within day and between days’ precision six replicates from each concentration were assayed. The between day precision was determined by measuring the concentration from samples at six different days.

Stability Data shows that the DFMO derivative to be very stable in aqueous solution within the experimental conditions of the developed method as depicted by CV (<3%). TNP-DFMO-TNP derivative showed to be stable over a 72h time period.

Summary A number of methods have been investigated for use in the estimation of free amino groups 580. One of these compounds is 2, 4, 6-trinitrobenzenesulfonic acid (TNBS). It was introduced by Okuyama and Satake

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581 as a reagent for amino groups, specifically for those in amino acids and peptides. This reagent is water- soluble, reasonably stable, and reacts with amino groups under comparatively mild conditions to give an orange trinitrophenyl (TNP) derivative, which forms a stable yellow color at pH 10.

10.1.4 Detection and quantification of Etoposide using HPLC Rationale This chapter briefly describes the quantification of the Etoposide drug using the Dionex Ultimate 3000 HPLC instrument. At this point, both drugs (DFMO and Etoposide) are quantified separately to better understand their stability and properties on their own. A method is later described in the chapter to simultaneously quantify both drugs using one analytical HPLC method (next section).

Etoposide is a semi-synthetic derivative of epipodophyllotoxins obtained from plant Mandragora officianarum. It was introduced in clinical practice in early 1970’s and now used in a large number of human malignant diseases including leukemia, lymphomas and lung cancer 571. It inhibits topoisomerase II activity, the enzyme is involved in uncoiling DNA, thus affecting its repair and replication 577.

Several methods for the determination of etoposide include HPLC with UV detection 83, 569, 578, fluorescence detection 72, and electrochemical detection 576. It has also been determined by LC-MS method 587 and ELISA method 587. These previously published methods use mixture of expensive organic solvents or demand costly equipment 572, 573. There was a need to develop and validate a simple and cost effective HPLC method for the determination of etoposide. The present work therefore is an alternative to previously published work and is simple and cost effective using one organic solvent as mobile phase.

Materials Chemicals and reagents HPLC grade methanol was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 67- 56-1) and used throughout the study. The etoposide drug was VWR International (VWR, Radnor, PA,

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USA) (Cat. No. 80055-248) and used throughout the study. Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA).

Equipment and chromatographic conditions The chromatographic system consisted of an Dionex Ultimate 3000 module (ThermoFisher Scientific, Sunnyvale, CA, USA) with an online degasser and an analytical auto-sampler WPS-3000(T)SL thermostated at 22°C. The Dionex module was coupled to an Ultimate 3000 Rapid Separation Diode Array Detector (DAD-3000RS) with Dionex Chromeleon chromatography data acquisition software (version 7.1) (ThermoFisher Scientific, Sunnyvale, CA, USA) for anaylsis of chromatography data. Separations were performed on a Phenomenex Kinetex XB-C18 (250 mm x 4.6 mm, particle size 5 µm) (Phenomenex, Torrance, CA, USA) (Cat. No. 00G-4605-E0) analytical column maintained at a temperature of 22°C. The gradient method utilized two mobile phases; ultrapure distilled deionized water and HPLC grade methonal, both filtered through a 0.2 µm nylon filter membrane (Millipore, Bedford, MA, USA) before use. The flow rate was 1.0 mL/min and the assay total runtime was 10 minutes. Absorbance was measured at 283 nm.

Methods Preparation of stock solutions, working solutions and calibration standards A stock solution of 0.5 mg/mL Etoposide was prepared in 100% Methanol. The stock solutions are further diluted with methanol to obtain calibration standards with concentrations of 13, 26, 52, and 104 µg/mL. The stock and calibration standards were prepared fresh before each analysis and stored away from daylight at room temperature (~21 to 23°C).

Sample preparation Etoposide samples were prepared for HPLC-UV analysis in HPLC grade methanol. Calibration standards prepared fresh in methanol were placed into light protected HPLC vials. The vials were kept at room temperature (~21 to 23°C) with gentle stirring to allow full dissolution.

Table 10.7 Dionex Ultimate 3000 HPLC Isocratic method for Etoposide elucidation (10-minute total run-time) at 283nm having a retention time of 6.5 minutes. Time (minutes) % Solvent A % Solvent B (Methanol) (Ultrapure distilled deionized water) 0 to 10 mins 50% 50%

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Results

Figure 10.5 Chromatogram of Etoposide drug, retention time of 6.5 minutes) versus the absorbance area (mAU*min) at 283nm. Chromatogram represents concentration of 104ug/mL of Etoposide drug.

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Etoposide HPLC using MeOH:DI-H2O (1:1) Absorbance height (13, 26, 52 & 104 ug/mL) 250

200

150 y = 2.1825x + 1.0015 100 R² = 0.999

0 Absorbance area (mAU*min)area Absorbance 0 20 40 60 80 100 120 Concentration (ug/mL) a)

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Etoposide HPLC using MeOH:DI-H2O (1:1) Absorbance area (13, 26, 52 & 104 ug/mL) 1200

1000

800

600 y = 12.081x + 24.973 R² = 0.999 400

200 Absorbance height (mAU)height Absorbance 0 0 20 40 60 80 100 120 Concentration (ug/mL) b) Figure 10.7 a) Linearity graph of linearity study of Etoposide quantified using a Dionex Ultimate 3000 HPLC at 283nm with concentrations 13, 26, 52, and 104ug/mL versus absorbance area (mAU*min) and b) Absorbance height (mAU). Linearity was found in a range of 13 to 104ug/mL. Linear regression value (R2) of 0.999 were shown for both absorbance readings.

10.1.5 Simultaneous Detection and Quantification of DFMO derivative and Etoposide using HPLC Rationale Simultaneous quantification of both DFMO derivative (TNP-DFMO-TNP adduct) and Etoposide drugs using the Dionex Ultimate 3000 HPLC instrument and one analytical HPLC method. The HPLC analytical method developed in this section will be used for the determination of entrapment efficiency and loading capacity of nanocarrier formulations throughout the hybrid nanocarrier formulation process. Utilizing one method to quantify both drugs simultaneously will be time efficient and cost-saving (wasting of drugs through several experiments) during the formulation process.

167 | Page difluoromethylornithine (DFMO) drug was kindly provided by Dr. Dana-Lynn Koomoa-Lange (University of Hawaii at Hilo, HI, USA). Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA). The etoposide drug was VWR International (VWR, Radnor, PA, USA) (Cat. No. 80055-248) and used throughout the study. Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA).

Methods Preparation of stock solutions, working solutions and calibration standards of both drugs A stock solution of 0.5 mg/mL DFMO and Etoposide were prepared in ultrapure distilled deionized water (DI-water) and methanol, respectively. The stock solutions are further diluted with borate buffer (pH 10.2) to obtain calibration standards with concentrations of 10, 20, 30, 40, 50, and 60 µg/mL for each drug. The stock and calibration standards were prepared fresh before each analysis and stored away from daylight at 4°C. Borate buffer was prepared by dissolving on low heat; 3.09g boric acid and 2.19g sodium chloride in 500 mL of DI-water. Borate buffer pH was adjusted to 10.2 with sodium hydroxide and filtered through a 0.2 µm nylon filter membrane. TNBSA stock solution (5% w/v) were diluted further in borate buffer (pH 10.2) to obtain a working solution of 0.025% w/v final concentration. TNBSA was prepared fresh before each analysis and stored away from daylight at 4°C. Ammonium acetate buffer (0.01M, pH 7) was prepared by dissolving 0.77g ammonium acetate in 1L of DI-water. Ammonium acetate buffer (0.01M) was then filtered through a 0.2 µm nylon filter membrane.

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Sample preparation Samples were prepared for HPLC-UV analysis using the TNBSA assay. Calibration standards of both drugs were prepared fresh in borate buffer (10.2) were aliquoted (800 µL each) into HPLC vials. Working TNBSA solution (0.025% w/v, 250 µL) were added into each calibration standard HPLC vial. The vials were placed in a 37°C water bathe and allowed to react for 2h. Samples were analyzed after 2h reaction with TNP-DFMO-TNP derivative and etoposide showing stability at room temperature over a 72h period.

Results

Table 10.9 HPLC Gradient for DFMO derivative (TNP-DFMO-TNP), retention time of 27.9 minutes, and Etoposide, retention time of 31 minutes at 345nm and 283nm, respectively. TNBSA reagent had a retention time of 6.9 minutes at 345nm. Total run-time was 60 minutes for this HPLC procedure. Gradient method is further altered to minimize total run-time. Time (minutes) % Solvent A % Solvent B (Methanol) (0.01M Ammonium Acetate) 0 to 12 mins 10% 90% 12 to 22 mins 10% to 40% 90% to 60% 22 to 32 mins 40% to 60% 60% to 40% 32 to 52 mins 60% to 10% 40% to 90% 52 to 60 mins 10% 90%

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#1 TNBSA #2 TNP-DFMO-TNP #3 ETOPOSIDE

Figure 10.8 Chromatogram of HPLC procedures to quantify DFMO derivative (#2, TNP-DFMO- TNP) and Etoposide (#3). DFMO derivative (TNP-DFMO-TNP) at 345nm (10 to 60ug/mL) with a retention time of 27.9 minutes. TNBS (#1) at 345nm has a retention time of 2 minutes. Etoposide at 283nm (10 to 60ug/mL) w/retention time of 31 minutes. Total run-time was 60 minutes for this HPLC procedure.

Table 10.10 HPLC Gradient for DFMO derivative (TNP-DFMO-TNP), retention time of 11.9 minutes, and Etoposide (retention time of 13.9 minutes) elucidation at 345nm and 283nm, respectively. TNBSA reagent had a retention time of 6.9 minutes at 345nm. Total run-time was 18 minutes. Time (minutes) % Solvent A % Solvent B (Methanol) (Ammonium Acetate) 0 to 2 mins 10% 90% 2 to 5 mins 10% to 40% 90% to 60% 5 to 9 mins 40% to 50% 60% to 50% 9 to 13 mins 50% to 60% 50% to 40% 13 to 18 mins 60% to 10% 40% to 90%

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#1 TNBSA reagent

#2 Etoposide

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Table 10.11 DFMO derivative (TNP-DFMO-TNP) standard curve at 345nm. Linearity range from 10 to 60ug/mL versus absorbance area (mAU*min) and absorbance height (mAU). TNP-DFMO- TNP had a retention time of 11.91 minutes. Linearity range were performed in triplicates. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were shown for both absorbance readings. Retention Concentration Area Height Time (ug/mL) (mAU*min) (mAU) (min) 10 11.91 9.6947 60.11 20 11.89 19.2805 118.24 30 11.91 29.118 174.8 40 11.91 38.7902 230.2 50 11.91 48.8352 293.19 60 11.91 351.04

Table 10.12 Etoposide standard curve at 283nm. Linearity range from 10 to 60ug/mL versus absorbance area (mAU*min) and absorbance height (mAU). Etoposide had a retention time of 13.9 minutes. Linearity range were performed in triplicates. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were shown for both absorbance readings. Retention Concentration Area Height Time (ug/mL) (mAU*min) (mAU) (min) 10 13.9 6.0305 21.21 20 13.9 13.9726 51.63 30 13.9 22.0768 83.68 40 13.9 26.0368 115.00 50 13.9 34.4181 150.31 60 13.9 37.4185 180.00

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DFMO derivative (Pink) & Etoposide (Blue) at 345 and 283nm respectively 400

350 y = 5.814x + 1.1067 300 R² = 0.9997 250

200

150 Height Height (mAU) 100 y = 3.2037x - 11.826 50 R² = 0.9996

0 0 10 20 30 40 50 60 70 Concentration (ug/mL)

Discussion Simultaneous quantification of both DFMO derivative (TNP-DFMO-TNP adduct) and Etoposide drugs using the Dionex Ultimate 3000 HPLC instrument showed linearity over 10 to 60ug/mL with a linear regression (R2) value of 0.999 for both drugs. The HPLC analytical method developed is further used for the determination of entrapment efficiency and loading capacity of nanocarrier formulations during the hybrid nanocarrier formulation process. The developed method will be time efficient and cost-saving during nanocarrier development.

The interaction of the TNBSA reagent is limited to molecules containing primary amine groups. Etoposide is a 7-ringed molecule which contains no primary amine groups. The analytical method developed showed no interation of the TNBSA reagent with Etoposide drug (at 10ug/mL, Fig 11.10). This interaction is vital

173 | Page for proper quantification of both drugs. The nanocarrier formulations can therefore be purified and quantified using the one-step hydrolysis reaction of TNBSA assay with both drugs present at the same time.

The final HPLC gradient for DFMO derivative (TNP-DFMO-TNP) had a retention time of 11.9 minutes with etoposide having a retention time of 13.9 minutes at 345nm and 283nm, respectively. TNBSA reagent had a retention time of 6.9 minutes at 345nm with a total run-time of 18 minutes for each sample.

Previous developed methods were based on post-column derivatisation of DFMO with orthophthaldialdehyde (OPA) using fluorescence detection and cation-exchange liquid chromatography (glass column packed manually with polystyrene–divinylbenzene cross-linked resin beads). This method was used for the measurement of DFMO in human plasma, CSF and urine 585. Fluorescence detection at excitation /emission wavelengths of 340/440 nm was followed by post-column derivatization with OPA. Sample preparation was done by protein precipitation of biological samples (100 ml) with trichloroacetic acid (20, 40%) or 5-sulfosalicylic acid. Total run time was 53 min. Sensitivity of the method was five nmol/ ml.

Altogether, the above mentioned method suffer from one or more of the following shortcomings, namely, relatively large sample volume, low sensitivity, lack of an internal standard, and long or sophisticated sample preparation or chromatographic procedures 585.

The developed simulataneous method has shown to quantify both UV-inactive DFMO and etoposide at relatively low concentrations. The method endowed has a colorimetric end point that is non-destructive, indefinitely stable and perceptible to the naked eye. This method will be utilized throughout nanocarrier formulation for the quantification of both drugs within the same solution.

11. IN VITRO CYTOTOXICITY STUDIES OF DFMO AND ETOPOSIDE Introduction A significant advance in the field of early medicine was Paracelsus’ recognition that all compounds have the capacity to be poisonous depending upon dosage 588. This observation makes toxicity testing a necessary and critical industry practice to identify and define safety thresholds for all new potential chemotherapeutics. The advent of In vitro cytotoxicity testing has greatly streamlined this process and is now considered to be a nearly compulsory activity starting at target validation and continuing through medicinal modification.

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Unlike animal-based toxicology testing, there are clearer definitions and greater agreement for what constitutes cytotoxicity In vitro. Classically speaking, a compound or treatment is considered to be cytotoxic if it prevents cellular attachment, causes dramatic morphological changes, adversely affects replication rate, or leads to a reduction in overall viability 589. It should be noted that the manifestation of these effects is greatly dependent on length of compound exposure and mechanism of cytotoxicity 590.

A host of new assays have been described and utilized which measure biomarkers of cellular stress or specific signaling events more proximal to initial cytotoxic insult (i.e. glutathione, caspases) 591. These methods offer early indication of potential cytotoxicity, but are typically relegated to secondary screening because they are more difficult to employ as endpoint assays due to the transient nature of the biomarker and kinetic differences associated with cell death progression 592, 593. Therefore, assay chemistries predicated upon the detection of changes in membrane integrity remain the gold standard for In vitro cytotoxicity testing.

Many methods exist for the assessment of membrane integrity, including several classic dye inclusions, exclusion and lysosomal accumulation techniques 594, 595. Although well validated, these methods are poorly suited for high throughput screening (HTS) implementation due to low sensitivity, multiple processing steps or miniaturization problems associated with higher plate densities 596, 597. Recent advances in reagent formulations accommodate these miniaturized formats and are fully compatible with automated dispensing systems and integrated detection instruments. These reagents deliver the linearity, sensitivity, and robustness necessary for properly interrogating large chemical libraries for cytotoxic risk. The most acceptable assay format is known as “add-mix-measure”, whereby reagent chemistry is delivered directly to the test well.

11.1.1 Introduction to MTT and MTS cell proliferation assays A variety of tetrazolium compounds have been used to detect viable cells. The most commonly used compounds include: MTT, MTS, XTT, and WST-1. These compounds fall into two basic categories: 1) MTT which is positively charged and readily penetrates viable eukaryotic cells and 2) those such as MTS, XTT, and WST-1 which are negatively charged and do not readily penetrate cells. The latter class (MTS, XTT, WST-1) are typically used with an intermediate electron acceptor that can transfer electrons from the cytoplasm or plasma membrane to facilitate the reduction of the tetrazolium into the colored formazan product.

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11.1.2 MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide Cell Proliferation Assay The MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide) tetrazolium reduction assay was the first homogeneous cell viability assay developed for a 96-well format that was suitable for HTS613. The MTT tetrazolium assay technology has been widely adopted and remains popular in academic labs as evidenced by thousands of published articles. The MTT substrate is prepared in a physiologically balanced solution, added to cells in culture, usually at a final concentration of 0.2 - 0.5mg/ml, and incubated for 1 to 4 hours. The quantity of formazan (presumably directly proportional to the number of viable cells) is measured by recording changes in absorbance at 570 nm using a plate reading spectrophotometer. A reference wavelength of 630 nm is sometimes used, but not necessary for most assay conditions.

Viable cells with active metabolism convert MTT into a purple colored formazan product with an absorbance maximum near 570 nm (Fig. 11). When cells die, they lose the ability to convert MTT into formazan, thus color formation serves as a useful and convenient marker of only the viable cells. The exact cellular mechanism of MTT reduction into formazan is not well understood, but likely involves reaction with NADH or similar reducing molecules that transfer electrons to MTT 614. Speculation in the early literature involving specific mitochondrial enzymes has led to the assumption mentioned in numerous publications that MTT is measuring mitochondrial activity 615, 616.

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The formazan product of the MTT tetrazolium accumulates as an insoluble precipitate inside cells as well as being deposited near the cell surface and in the culture medium. The formazan must be solubilized prior to recording absorbance readings. A variety of methods have been used to solubilize the formazan product, stabilize the color, avoid evaporation, and reduce interference by phenol red and other culture medium components 598-600. Various solubilization methods include using: acidified isopropanol, DMSO, dimethylformamide, SDS, and combinations of detergent and organic solvent 598-601. Acidification of the solubilizing solution has the benefit of changing the color of phenol red to yellow color that may have less interference with absorbance readings. The pH of the solubilization solution can be adjusted to provide maximum absorbance if sensitivity is an issue 602; however, other assay technologies offer much greater sensitivity than MTT.

The amount of signal generated is dependent on several parameters including: the concentration of MTT, the length of the incubation period, the number of viable cells and their and metabolic activity. All of these parameters should be considered when optimizing the assay conditions to generate a sufficient amount of product that can be detected above background.

The conversion of MTT to formazan by cells in culture is time dependent (Fig 11.1).

Figure 11.1 Direct correlation of formazan absorbance with B9 hybridoma cell number and time- dependent increase in absorbance. Note: there is little absorbance change between 2 and 4 hours. Adapted from CellTiter 96® Non-Radioactive Cell Proliferation Assay Technical Bulletin #112.17

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Longer incubation time will result in accumulation of color and increased sensitivity up to a point; however, the incubation time is limited because of the cytotoxic nature of the detection reagents which utilize energy (reducing equivalents such as NADH) from the cell to generate a signal. For cell populations in log phase growth, the amount of formazan product is generally proportional to the number of metabolically active viable cells as demonstrated by the linearity of response in Figure 11.1. Culture conditions that alter the metabolism of the cells will likely affect the rate of MTT reduction into formazan. For example, when adherent cells in culture approach confluence and growth becomes contact inhibited, metabolism may slow down and the amount MTT reduction per cell will be lower. That situation will lead to a loss of linearity between absorbance and cell number. Other adverse culture conditions such as altered pH or depletion of essential nutrients such as glucose may lead to a change in the ability of cells to reduce MTT.

The MTT assay was developed as a non-radioactive alternative to tritiated thymidine incorporation into DNA for measuring cell proliferation 601. In many experimental situations, the MTT assay can directly substitute for the tritiated thymidine incorporation assay

However, it is worth noting that MTT reduction is a marker reflecting viable cell metabolism and not specifically cell proliferation. Tetrazolium reduction assays are often erroneously described as measuring cell proliferation without the use of proper controls to confirm effects on metabolism 603.

11.1.3 MTS (3-(4, 5-dimethylthiazoly-2yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H- tetrazolium) Cell Proliferation Assay More recently developed tetrazolium reagents can be reduced by viable cells to generate formazan products that are directly soluble in cell culture medium. Tetrazolium compounds fitting this category include MTS, XTT, and the WST series 17, 604, 605. These improved tetrazolium reagents eliminate a liquid handling step during the assay procedure because a second addition of reagent to the assay plate is not needed to solubilize formazan precipitates, thus making the protocols more convenient. The negative charge of the formazan products that contribute to solubility in cell culture medium are thought to limit cell permeability of the tetrazolium 606. This set of tetrazolium reagents is used in combination with intermediate electron acceptor reagents such as phenazine methyl sulfate (PMS) or phenazine ethyl sulfate (PES) which can penetrate viable cells, become reduced in the cytoplasm or at the cell surface and exit the cells where they can convert the tetrazolium to the soluble formazan product 607. The general reaction scheme for this class of tetrazolium reagents is shown in Figure 11.2

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Figure 11.2 Intermediate electron acceptor pheazine ethyl sylfate (PES) transfers electron from NADH in the cytoplasm to reduce MTS in the culture medium into an aqueous soluble formazan.17

In general, this class of tetrazolium compounds is prepared at 1 to 2mg/ml concentration because they are not as soluble as MTT. The type and concentration of the intermediate electron acceptor used varies among commercially available reagents and in many products, the identity of the intermediate electron acceptor is not disclosed. Because of the potential toxic nature of the intermediate electron acceptors, optimization may be advisable for different cell types and individual assay conditions. There may be a narrow range of concentrations of intermediate electron acceptor that result in optimal performance.

One of the advantages of the tetrazolium assays that produce an aqueous soluble formazan is that absorbance can be recorded form the assay plates periodically during early stages of incubation. Multiple readings may assist during assay development; but caution should be taken to return the plates to the incubator between readings to maintain a nearly constant environment. Extended incubations with the tetrazolium reagent beyond four hours should be avoided.

11.2 In vitro dose-response curves of DFMO and Etoposide drugs alone Rationale

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Chapter 10 focused on quantifying free DFMO and Etoposide drugs alone with no nanocarriers present. It also provided an analytical method for the derivatization of DFMO into its TNP-DFMO-TNP adduct using the TNBSA reagent. This chapter will focus on the effects each drug has on NB cell-lines both alone and in combination with one-another. The following data can then be applied to nanocarrier formulations.

Materials The α-difluoromethylornithine (DFMO) drug was kindly provided by Dr. Dana-Lynn Koomoa-Lange (University of Hawaii at Hilo, HI, USA). Etoposide drug was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 80055-248) and used throughout the study. Neuroblastoma cell-lines were prepared according to ATCC culture methods. SK-N-Be(2)c (ATCC, CRL-2268), SK-N-SH (ATCC, HTB-11), and IMR-32 (ATCC, CCL-127) NB cell-lines were cultured in RPMI medium (ThermoFisher, CA, USA) (Cat No. 11875093) containing 10% fetal bovine serum (FBS). Cell culture plates, 96-well (working volume of 200uL) were purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 734-1546) and used throughout all In vitro studies. MTS reagent were purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 10191-104) and prepared following assay instructions. MTS reagents were aliquoted into 1mL Eppendorf tubes and stored at -20°C until needed. MTS reagents were incubated in 37°C water bathe for 10 minutes before treating cells.

Methods SK-N-Be(2)c, and IMR-32 NB cell-lines were seeded at 1 x 104 cells per well with SK-N-SH cells seeded at 2 x 104 cells per well under sterile conditions. Cells were treated with respective concentrations of DFMO and Etoposide (Table 11) dissolved in RPMI media, prepared fresh before each experiment. MTS cell proliferation assay were conducted at 490nm to determine cell viability after 96h drug incubation. MTS assay were read at 2h post-treatment using a BioTek plate reader with Gen5 software for data interpretation. Experiments were done in triplicates with mean ± SD calculated. Log drug concentrations versus %effect (cell viability) were plotted using Graphpad Prism 5 software and IC50 values were obtained for each drug, for each NB cell-line.

Results

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Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. SK-N-Be(2)c DFMO Etoposide SK-N-Be(2)c in RPMI in RPMI (96-well plate) (mM) (nM) (96-well plate) (DFMO) (Etoposide) Rows: B, C, D Rows: E, F, G Column: Column: 12 0.025 5 12 11 0.05 15 11 10 0.1 20 10 9 0.25 50 9 8 0.5 100 8 7 1 250 7 6 5 500 6 5 10 1000 5 4 20 5000 4 Control (2, 3) 0 0 Control (2, 3)

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(100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM 100uL of final concentration

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.045 2.312 2.333 0.095 0.352 0.689 0.986 0.975 1.395 1.812 1.921 1.932 490

C 0.046 2.244 2.242 0.102 2.242 0.672 0.959 2.242 1.272 1.626 1.799 2.089 490

D 0.045 1.948 1.954 0.11 0.349 0.695 0.984 0.959 1.244 1.377 1.614 1.934 490

E 0.053 2.333 2.338 1.526 0.398 1.526 1.023 1.102 1.358 1.526 1.745 1.892 490

F 0.05 2.239 2.243 0.105 0.385 0.71 1.01 1.113 1.32 1.533 1.812 1.887 490

G 0.044 1.947 1.955 0.104 0.389 0.73 1.035 1.126 1.37 1.554 1.786 1.879 490

H 490 a) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM 100uL of final concentration (100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.044 1.962 2.341 2.23 0.342 0.685 1.819 0.971 1.389 1.818 1.934 1.924 490

C 0.048 2.252 2.238 0.117 0.352 0.962 0.976 0.928 1.276 1.631 1.802 2.078 490

D 0.045 2.242 1.954 0.118 0.356 0.701 0.969 0.963 1.252 1.368 1.617 1.941 490

E 0.055 1.95 2.334 1.812 0.405 0.729 1.032 1.112 1.363 1.532 1.751 1.887 490

F 0.05 2.245 2.243 0.103 0.398 0.704 1.018 1.119 1.329 1.541 1.804 1.88 490

G 0.046 1.942 1.95 0.116 0.393 2.23 1.041 1.13 1.369 1.561 1.778 1.874 490

H 490 b) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM Control (100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM 1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.047 1.95 2.225 1.947 0.348 0.678 0.989 1.962 1.39 1.82 1.919 1.924 490

C 0.046 2.331 1.96 0.12 0.335 0.966 0.969 0.938 1.268 1.612 1.806 2.078 490

D 0.042 1.941 1.951 0.125 0.356 0.687 0.983 0.962 1.254 1.365 1.624 1.921 490

E 0.054 2.338 2.351 0.111 1.389 0.729 1.031 1.112 1.349 1.534 2.251 1.887 490

F 0.051 2.245 2.238 0.103 0.378 0.717 1.017 1.118 1.329 1.541 1.804 1.878 490

G 0.042 1.958 1.947 1.387 0.375 0.725 1.042 1.136 1.375 1.562 1.793 1.869 490

H 490 c) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM Figure 11.3 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with varying concentrations of free DFMO (yellow) and Etoposide (pink) separately at 2 hour reading. Cells seeded at 5 x 103 per well. Experiment was done in triplicates with raw data shown above (a, b and c represent independent experiments).

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Table 11.1 Experimental results for DFMO and Etoposide drugs alone treating SK-N-Be(2)c cell- lines. Cells seeded at 5 x 103 per well and incubated for 24h prior to drug treatments. Cells incubated with respective drugs alone for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. Cell Viability (%) Cell Viability (%) DFMO Trial Trial Trial Mean % Etoposide Trial Trial Trial Mean % in RPMI 1 2 3 ± SD CV in RPMI 1 2 3 ± SD CV (mM) (nM) 0.025 91 92 93 92 ± 1 1 5 86 88 88 87 ± 1 1 0.05 81 83 84 83 ± 2 2 15 81 83 85 83 ± 2 2 0.1 73 75 75 74 ± 1 2 20 70 72 72 71 ± 1 2 0.25 59 60 61 60 ± 1 2 50 61 62 63 62 ± 1 2 0.5 43 43 44 43 ± 1 1 100 50 51 52 51 ± 1 2 1 44 44 45 44 ± 1 1 250 46 47 47 47 ± 1 1 5 30 35 35 33 ± 3 9 500 32 32 33 32 ± 1 2 10 14 14 14 14 ± 0 0 1000 16 17 16 16 ± 1 4 20 3 3 4 3 ± 1 17 5000 3 3 3 3 ± 0 0 Control 100 100 100 100±0 0 Control 100 100 100 100±0 0

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Table 11.2 Experimental set-up for DFMO and Etoposide drugs alone treating SK-N-SH cell-lines. Cells seeded at 1 x 104 per well and incubated for 24h prior to drug treatments. Cells incubated with respective drugs alone for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. SK-N-SH DFMO Etoposide SK-N-SH in RPMI in RPMI (96-well plate) (mM) (nM) (96-well plate) (DFMO) (Etoposide) Rows: B, C, D Rows: E, F, G Column: Column: 12 0.025 5 12 11 0.05 15 11 10 0.1 20 10 9 0.25 50 9 8 0.5 100 8 7 1 250 7 6 5 500 6 5 10 1000 5 4 20 5000 4 Control (2, 3) 0 0 Control (2, 3)

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(100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.074 1.801 1.942 0.495 0.752 1.121 1.464 1.535 1.699 1.872 1.948 1.92 490

C 0.082 1.891 1.894 0.436 1.939 1.133 1.446 1.464 1.611 1.786 1.87 1.82 490

D 0.079 1.838 1.659 0.472 0.766 1.131 1.468 1.519 1.699 1.745 1.816 1.87 490

E 0.078 1.914 1.949 0.085 0.084 0.236 0.513 1.935 1.029 1.277 1.551 1.717 490

F 0.085 1.891 1.896 1.274 0.087 0.256 0.504 0.855 1.17 1.28 1.574 1.723 490

G 0.098 1.835 1.652 0.085 0.096 0.284 0.57 0.847 1.015 1.21 1.587 1.789 490

H 490 a) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM (100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.07 1.823 1.958 0.501 0.758 1.114 1.478 1.958 1.688 1.882 1.854 1.931 490

C 0.078 1.878 1.887 0.445 0.765 1.138 1.454 1.458 1.619 1.774 1.863 1.814 490

D 0.075 1.855 1.645 1.273 0.758 1.141 1.471 1.528 1.678 1.756 1.802 1.877 490

E 0.072 1.889 1.951 0.091 0.079 0.242 0.514 0.817 1.024 1.268 1.932 1.731 490

F 0.084 1.878 1.91 0.08 0.092 0.248 0.508 0.867 1.022 1.274 1.564 1.734 490

G 0.094 1.865 1.662 0.077 1.956 0.276 1.274 0.84 1.014 1.219 1.572 1.778 490

H 490 b) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM (100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.069 1.902 1.954 0.505 0.743 1.13 1.454 1.547 1.687 1.863 1.923 1.914 490

C 0.077 1.877 1.884 0.441 1.921 1.141 1.453 1.471 1.617 1.802 1.865 1.818 490

D 0.081 1.848 1.662 0.487 0.774 1.144 1.471 1.523 1.696 1.824 1.824 1.862 490

E 0.082 1.925 1.957 1.548 0.074 0.229 0.521 1.577 1.041 1.217 1.541 1.702 490

F 0.086 1.884 1.897 0.077 0.091 0.245 1.924 0.847 1.026 1.279 1.568 1.727 490

G 0.095 1.852 1.658 0.079 1.542 0.274 0.564 0.839 1.012 1.221 1.579 1.789 490

H 490 c) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM Figure 11.5 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-SH NB cell- line treated with varying concentrations of free DFMO (yellow) and Etoposide (pink) separately at 2 hour reading. Cells seeded at 1 x 104 per well. Experiment was done in triplicates with raw data shown above (a, b and c represent independent experiments).

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Table 11.3 Experimental results for DFMO and Etoposide drugs alone treating SK-N-SH cell-lines. Cells seeded at 1 x 104 per well and incubated for 24h prior to drug treatments. Cells incubated with respective drugs alone for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. Cell Viability (%) Cell Viability (%) DFMO Trial Trial Trial Mean % Etoposide Trial Trial Trial Mean % in RPMI 1 2 3 ± SD CV in RPMI 1 2 3 ± SD CV (mM) (nM) 0.025 101 101 100 101±1 1 5 94 94 93 94 ± 1 1 0.05 102 99 101 101±2 2 15 84 84 83 84 ± 1 1 0.1 97 97 98 97 ± 1 1 20 66 66 65 66 ± 1 1 0.25 90 89 89 89 ± 1 1 50 56 53 53 54 ± 2 3 0.5 81 80 81 81 ± 1 1 100 44 43 57 48 ± 8 16 1 78 78 78 78 ± 0 0 250 25 24 26 25 ± 1 4 5 59 59 59 59 ± 0 0 500 10 10 9 10 ± 1 6 10 38 38 38 38 ± 0 0 1000 0.36 0.38 0.009 0 ± 0 84 20 22 22 22 22 ± 0 0 5000 0.13 0.22 0.26 0 ± 0 33 Control 99 100 100 100±0 0 Control 100 100 100 100±0 0

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Table 11.4 Experimental set-up for DFMO and Etoposide drugs alone treating IMR-32 cell-lines. Cells seeded at 5 x 103 per well and incubated for 24h prior to drug treatments. Cells incubated with respective drugs alone for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. IMR-32 DFMO Etoposide IMR-32 in RPMI in RPMI (96-well plate) (mM) (nM) (96-well plate) (DFMO) (Etoposide) Rows: B, C, D Rows: E, F, G Column: Column: 12 0.025 5 12 11 0.05 15 11 10 0.1 20 10 9 0.25 50 9 8 0.5 100 8 7 1 250 7 6 5 500 6 5 10 1000 5 4 20 5000 4 Control (2, 3) 0 0 Control (2, 3)

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(100uL media) Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM 100uL of final concentration

1 2 3 4 5 6 7 8 9 101112

A 490

B 0.048 0.618 0.544 0.187 0.279 0.315 0.408 0.418 0.439 0.507 0.571 0.545 490

C 0.045 0.569 0.544 0.177 0.555 0.298 0.379 0.423 0.449 0.408 0.543 0.561 490

D 0.045 0.507 0.545 0.178 0.272 0.305 0.349 0.42 0.483 0.408 0.412 0.501 490

E 0.046 0.571 0.561 0.085 0.148 0.151 0.157 0.171 0.191 0.175 0.195 0.279 490

F 0.045 0.543 0.503 0.083 0.153 0.418 0.158 0.569 0.182 0.22 0.567 0.272 490

G 0.045 0.408 0.501 0.415 0.145 0.141 0.167 0.158 0.405 0.209 0.194 0.272 490

H 490 a) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM 100uL of final concentration (100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM 100uL of final concentration

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.045 0.562 0.57 0.184 0.286 0.322 0.382 0.589 0.446 0.517 0.569 0.556 490

C 0.051 0.501 0.544 0.566 0.278 0.305 0.386 0.431 0.454 0.421 0.549 0.568 490

D 0.047 0.507 0.409 0.176 0.266 0.312 0.345 0.429 0.469 0.405 0.423 0.508 490

E 0.043 0.571 0.565 0.078 0.154 0.162 0.163 0.582 0.187 0.169 0.189 0.282 490

F 0.051 0.543 0.508 0.076 0.559 0.151 0.263 0.175 0.182 0.218 0.198 0.277 490

G 0.042 0.418 0.515 0.275 0.152 0.145 0.151 0.149 0.197 0.568 0.197 0.269 490

H 490 b) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM 100uL of final concentration (100uL Control 20mM 10mM 5mM 1mM 0.5mM 0.25mM 0.1mM 0.05mM 0.025mM 100uL of final concentration

1 2 3 4 5 6 7 8 9 10 11 12

A 490

B 0.051 0.543 0.549 0.176 0.268 0.324 0.384 0.427 0.424 0.576 0.425 0.541 490

C 0.062 0.409 0.544 0.187 0.575 0.304 0.368 0.435 0.454 0.404 0.548 0.422 490

D 0.041 0.501 0.545 0.183 0.259 0.308 0.357 0.429 0.489 0.414 0.419 0.514 490

E 0.064 0.571 0.543 0.092 0.134 0.164 0.147 0.164 0.174 0.168 0.198 0.283 490

F 0.074 0.547 0.403 0.568 0.386 0.158 0.562 0.169 0.189 0.214 0.385 0.269 490

G 0.05 0.412 0.501 0.079 0.153 0.149 0.171 0.154 0.376 0.562 0.189 0.254 490

H 490 c) 5uM 1uM 0.5uM 0.25uM 0.1uM 0.05uM 0.02uM 0.015uM 0.005uM 100uL of final concentration Figure 11.7 MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell-line treated with varying concentrations of free DFMO (yellow) and Etoposide (pink) separately at 2 hour reading. Cells seeded at 5 x 103 per well. Experiment were done in triplicates with raw data shown above (a, b and c represent independent experiments).

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Table 11.5 Experimental results for DFMO and Etoposide drugs alone treating IMR-32 cell-lines. Cells seeded at 5 x 103 per well and incubated for 24h prior to drug treatments. Cells incubated with respective drugs alone for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Experiment done in triplicates with mean ± SD represented. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. Cell Viability (%) Cell Viability (%) DFMO Trial Trial Trial Mean % Etoposide Trial Trial Trial Mean % in RPMI 1 2 3 ± SD CV in RPMI 1 2 3 ± SD CV (mM) (nM) 0.025 100 106 105 104±3 3 5 47 49 47 48 ± 1 2 0.05 95 99 81 92 ±9 10 15 30 31 30 30 ± 1 2 0.1 81 85 78 81 ± 4 4 20 32 31 30 31 ± 1 3 0.25 84 87 89 87 ± 3 3 50 29 30 28 29 ± 1 3 0.5 77 81 83 80 ± 3 4 100 24 25 23 24 ±1 4 1 68 69 70 69 ± 1 1 250 24 23 23 23 ± 1 2 5 53 57 57 56 ± 2 4 500 21 23 22 22 ± 1 5 10 47 49 46 47 ± 2 3 1000 21 23 19 21 ± 2 10 20 28 28 28 28 ± 0 0 5000 8 6 6 7 ± 1 17 Control 100 98 100 99 ±1 1 Control 100 100 100 100±0 0

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Discussion The present study revealed dose-response curves of DFMO and Etoposide, separately, against various neuroblastoma cell-lines (SK-N-Be(2)c, IMR-32, and SK-N-SH) disagreed with reported literature findings 576, 589.

DFMO and etoposide have been studied extensively throughtout the years. Previous reports have indicated the IC50 values to be at higher concentrations as compared to the results reported in this study. According to the Genomics of Drug sensitivity in Cancer project, the IC50 values of Etoposide against neuroblastoma cell-lines SK-N-SH and IMR-32 are 0.453 and 0.333uM, respectively. The current study showed SK-N- SH with an IC50 value of 76.5nM and IMR-32 at 3.02nM, nearly a 6 and 100-fold decrease in concentration as compared to the cancer project.

11.3 In vitro DFMO and Etoposide drug combination studies Rationale Up until now, both drugs, DFMO and Etoposide have been analyzed separately with the exception of HPLC analysis. This section will focus on drug combination studies of both drugs using their IC50 values found in the previous section (free drug on their own). These combinatorial studies will allow for determination

192 | Page of optimal drug-to-drug ratio needed to be effective at treating NB cell-lines. These studies will also conclude whether both drugs work synergistically, additive or antagonistic with one another.

Drug combination is most widely used in treating the most dreadful diseases, such as cancer and AIDS. The main aims are to achieve synergistic therapeutic effect, dose and toxicity reduction, and to minimize or delay the induction of drug resistance. Toxicity reduction and resistance minimization benefits could also be the outcomes of synergism. However, in one review article by Goldin and Mantel in 1957, seven different definitions for synergism were given, and in a more recent review by Greco and colleagues in 1995, 13 different methods for determining synergism were listed and none of them supported the others. The meaning of synergism has become an individual's preference. Faulty or unsubstantiated synergy claims are pervasive. This is serious because it is frequently referred to in patient therapy.

Without a standardized definition for synergism, it is argued that there will be a mess in making synergy claims, whether in publishing a scientific article, submitting a grant application, planning drug combination clinical trials for Food and Drug Administration approval, or asserting drug combination discovery to the Patent Office. It is also argued that in the absence of a clear “definition for synergism”, governmental agencies have no basis to regulate the drug combination synergy claims.

Materials The α-difluoromethylornithine (DFMO) drug was kindly provided by Dr. Dana-Lynn Koomoa-Lange (University of Hawaii at Hilo, HI, USA). The etoposide drug was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 80055-248) and used throughout the study. Neuroblastoma cell-lines were prepared according to ATCC culture methods. SK-N-Be(2)c (ATCC, CRL-2268), SK-N-SH (ATCC, HTB-11), and IMR-32 (ATCC, CCL-127) NB cell-lines were cultured in RPMI medium (ThermoFisher, CA, USA) (Cat No. 11875093) containing 10% fetal bovine serum (FBS). Cell culture plates, 96-well (working volume of 200uL) were purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 734-1546) and used throughout all In vitro studies. MTS reagent were purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 10191-104) and prepared following assay instructions. MTS reagents were aliquoted into 1mL Eppendorf tubes and stored at -20°C until needed. MTS reagents were incubated in 37°C water bathe for 10 minutes before treating cells (20uL per well).

Methods SK-N-Be(2)c, and IMR-32 NB cell-lines were seeded at 5 x 103 cells per well with SK-N-SH cells seeded at 1 x 104 cells per well in sterile conditions. Cells were treated with respective ratios of DFMO and

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Etoposide dissolved in RPMI media, prepared fresh before each experiment. MTS cell proliferation assay were conducted at 490nm to determine cell viability after 96h drug incubation. MTS assay were read at 2h post-treatment using a BioTek plate reader with Gen5 software for data interpretation. Experiments were done in triplicates with mean ± SD calculated. Log drug concentrations versus %effect (cell viability) were plotted using Graphpad Prism 5 software and IC50 values were obtained for each NB cell-line.

Results

Table 11.6 Experimental set-up for DFMO and Etoposide drug combination studies of SK-N-Be(2)c cell-lines. Cells seeded at 5 x 103 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment done in duplicates. SK-N-Be(2)c IC50 Drug concentration Percentage equivalent (DFMO, mM) of IC50 Drug (Etoposide, nM) value (%) DFMO IC50 0.4 100 IC5 0.04 10 IC10 0.08 20 IC15 0.12 30 Etoposide IC75 150 150 IC50 100 100 IC25 50 50 IC12.5 24 24 IC7.5 15 15 IC3 6 6 IC1 2 2 Control 0 0 0

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IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 150 100 50 24 15 6 2 nM Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.047 1.953 2.332 0.689 1.245 0.975 1.395 1.812 1.921 1.932 490 C 0.044 2.337 1.954 0.672 0.979 0.931 1.272 1.626 1.799 2.089 490 D 0.045 1.946 2.335 0.695 0.984 2.339 1.244 1.377 2.329 1.934 490

Plate 3 3 Plate E 0.054 2.333 2.336 0.689 0.986 0.975 1.395 1.818 1.921 1.932 490 F 0.05 2.237 2.243 1.248 0.979 0.931 1.272 1.244 1.799 2.089 490

0.1 ratio DFMO ratio 0.1 G 0.04 1.945 1.954 0.695 0.984 0.959 1.244 1.377 1.614 1.934 490 H 490 a) 0.04 0.04 0.04 0.04 0.04 0.04 0.04 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 150 100 50 24 15 6 2 nM Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.047 1.801 1.942 0.695 0.971 0.963 1.393 1.817 1.932 2.001 490 C 0.044 1.891 1.894 0.679 0.986 2.071 1.263 1.636 1.785 2.002 490 D 0.045 1.838 1.659 0.689 0.988 0.947 1.252 1.345 1.618 1.901 490

Plate 3 3 Plate E 0.054 1.942 1.949 0.687 1.613 0.967 1.388 1.824 1.931 1.903 490 F 0.05 1.894 1.896 0.664 0.956 0.927 1.26 1.634 1.784 1.856 490

0.1 ratio DFMO ratio 0.1 G 0.04 1.835 1.652 0.687 0.978 0.948 1.263 1.363 1.619 1.912 490 H 490 b) 0.04 0.04 0.04 0.04 0.04 0.04 0.04 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 150 100 50 24 15 6 2 nM Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.045 2.246 1.946 0.351 0.688 0.985 0.974 1.391 1.814 1.928 490 C 0.047 1.954 2.333 0.33 0.676 0.982 0.932 2.329 1.627 1.796 490 D 0.045 2.338 1.954 0.352 2.341 0.986 0.963 1.248 1.379 1.612 490

Plate 2 2 Plate E 0.053 1.946 2.336 1.248 0.685 0.984 1.248 1.392 1.812 1.92 490 F 0.051 1.954 2.243 0.338 0.676 0.976 0.936 1.274 1.624 1.798 490

0.2 ratio DFMO ratio 0.2 G 0.046 1.947 1.953 0.348 0.692 0.98 0.951 1.242 1.371 1.613 490 H 490 c) 0.08 0.08 0.08 0.08 0.08 0.08 0.08 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 150 100 50 24 15 6 2 nM Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.045 1.915 1.942 0.363 0.665 0.978 0.969 1.389 1.856 1.894 490 C 0.047 1.891 1.893 0.341 0.938 0.974 0.942 1.268 1.645 1.756 490 D 0.045 1.839 1.659 0.362 0.679 0.97 0.957 1.256 1.381 1.635 490

Plate 2 2 Plate E 0.053 1.942 1.949 0.348 0.674 1.889 0.967 1.388 1.863 1.912 490 F 0.051 1.891 1.898 0.329 0.665 0.956 0.924 1.284 1.632 1.769 490

0.2 ratio DFMO ratio 0.2 G 0.046 1.835 1.652 0.356 0.684 0.979 0.936 1.256 1.357 1.623 490 H 490 d) 0.08 0.08 0.08 0.08 0.08 0.08 0.08 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 150 100 50 24 15 6 2 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.048 1.894 1.942 0.078 1.945 0.721 0.996 0.945 1.41 1.856 490 C 0.044 1.659 1.894 0.112 0.378 0.772 0.942 0.927 1.32 1.584 490 D 0.046 1.949 1.659 0.121 0.374 0.71 0.921 1.899 1.25 1.377 490

Plate 1 1 Plate E 0.05 1.914 1.949 0.118 0.332 0.705 0.956 0.945 1.401 1.812 490 F 0.048 1.891 1.896 0.116 0.948 0.732 0.941 0.895 1.289 1.628 490

0.3 ratio DFMO ratio 0.3 G 0.043 1.835 1.652 0.131 0.363 0.741 0.975 0.963 1.286 1.375 490 H 490 e) 0.12 0.12 0.12 0.12 0.12 0.12 0.12 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 150 100 50 24 15 6 2 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.048 2.315 2.33 0.089 0.352 0.689 0.986 0.975 1.395 1.812 490 C 0.044 2.248 2.246 1.24 1.244 0.672 0.979 0.931 1.272 1.626 490 D 0.046 1.946 1.954 0.114 0.349 0.695 0.984 0.959 1.244 1.377 490

Plate 1 1 Plate E 0.05 2.333 2.338 0.09 0.352 0.689 2.33 0.975 1.395 2.329 490 F 0.048 1.956 1.946 2.338 0.332 0.672 0.979 0.931 1.272 1.626 490

0.3 ratio DFMO ratio 0.3 G 0.043 1.946 1.954 0.114 0.349 0.695 0.984 0.959 1.244 1.377 490 H 490 f) 0.12 0.12 0.12 0.12 0.12 0.12 0.12 mM DFMOI 100uL of final concentration Figure 11.9 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with varying concentrations of free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 5 x 103 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h. Experiment was done in duplicates with raw data shown

195 | Page above. Data set; a, c, and e represent one complete experiment at 0.1 (pink), 0.2 (blue), and 0.3 (green) IC50 equivalents of DFMO, respectively. Data set; b, d, and f represents duplicate experiment.

Table 11.7 Experimental results for DFMO and Etoposide drug combination studies of SK-N-Be(2)c cell-lines. Cells seeded at 5 x 103 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment was done in duplicates. DFMO (mM) SK-N-Be(2)c Cell Viability (%) Mean Cell Viability (%) ± SD 0.04 0.08 0.12 0.04 0.08 0.12 Etoposide Trial Trial Trial Trial Trial Trial (nm) 1 2 1 2 1 2 2 90 103 83 93 73 86 97 ± 9 88 ± 7 83 ± 9 6 82 95 75 86 60 71 89 ± 9 81 ± 8 73 ± 8 15 70 86 61 69 44 49 78 ± 11 65 ± 6 57 ± 4 24 59 69 43 49 45 50 64 ± 7 46 ± 4 47 ± 4 50 42 50 45 50 31 38 46 ± 6 48 ± 4 41 ± 5 100 44 51 31 34 14 17 48 ± 5 33 ± 2 24 ± 2 150 30 35 14 16 3 4 33 ± 4 15 ± 1 10 ± 1 Control 97 98 97 97 99 99 98 ± 1 97 ± 0 98 ± 0

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Table 11.8 Experimental set-up for DFMO and Etoposide drug combination studies of SK-N-SH cell- lines. Cells seeded at 2 x 104 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment was done in duplicates. SK-N-SH IC50 Drug concentration Percentage equivalent (DFMO, mM) of IC50 Drug (Etoposide, nM) value (%) DFMO IC50 7 100 IC5 0.7 10 IC10 1.4 20 IC15 2.1 30 Etoposide IC75 105 150 IC50 70 100 IC25 35 50 IC12.5 16.8 24 IC7.5 10.5 15 IC3 4.2 6 IC1 1.4 2 Control 0 0 0

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IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 105 70 35 16.8 10.5 4.2 1.4 Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.046 0.435 0.439 0.152 0.441 0.28 0.314 0.389 0.419 0.44 490 C 0.048 0.447 0.449 0.168 0.178 0.271 0.297 0.377 0.424 0.45 490 D 0.041 0.483 0.484 0.142 0.18 0.272 0.436 0.346 0.421 0.484 490

Plate 3 3 Plate E 0.046 0.437 0.439 0.378 0.444 0.28 0.316 0.396 0.419 0.438 490 F 0.047 0.444 0.445 0.166 0.176 0.273 0.298 0.374 0.424 0.448 490

0.1 ratio DFMO ratio 0.1 G 0.044 0.48 0.483 0.14 0.175 0.273 0.306 0.345 0.421 0.482 490 H 490 a) 0.7 0.7 0.7 0.7 0.7 0.7 0.7 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 105 70 35 16.8 10.5 4.2 1.4 Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.046 0.544 0.545 0.145 0.192 0.277 0.319 0.376 0.425 0.432 490 C 0.048 0.501 0.561 0.156 0.186 0.265 0.288 0.371 0.432 0.458 490 D 0.041 0.55 0.524 0.149 0.192 0.263 0.491 0.335 0.428 0.489 490

Plate 3 3 Plate E 0.046 0.561 0.561 0.161 0.179 0.275 0.321 0.389 0.412 0.585 490 F 0.047 0.507 0.505 0.491 0.169 0.263 0.292 0.369 0.419 0.438 490

0.1 ratio DFMO ratio 0.1 G 0.044 0.501 0.501 0.139 0.168 0.269 0.312 0.334 0.429 0.479 490 H 490 b) 0.7 0.7 0.7 0.7 0.7 0.7 0.7 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 105 70 35 16.8 10.5 4.2 1.4 Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.048 0.439 0.434 0.15 0.156 0.172 0.375 0.28 0.316 0.392 490 C 0.046 0.449 0.449 0.164 0.159 0.163 0.178 0.273 0.299 0.38 490 D 0.045 0.488 0.483 0.143 0.435 0.159 0.179 0.273 0.306 0.35 490

Plate 2 2 Plate E 0.046 0.44 0.435 0.149 0.156 0.17 0.186 0.434 0.314 0.39 490 F 0.044 0.449 0.449 0.168 0.159 0.16 0.176 0.271 0.297 0.378 490

0.2 ratio DFMO ratio 0.2 G 0.045 0.483 0.482 0.143 0.167 0.159 0.177 0.271 0.304 0.348 490 H 490 c) 1.4 1.4 1.4 1.4 1.4 1.4 1.4 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 105 70 35 16.8 10.5 4.2 1.4 Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.048 0.509 0.524 0.151 0.145 0.169 0.176 0.284 0.325 0.41 490 C 0.046 0.515 0.501 0.172 0.512 0.16 0.394 0.263 0.295 0.398 490 D 0.045 0.548 0.545 0.132 0.169 0.153 0.165 0.265 0.312 0.368 490

Plate 2 2 Plate E 0.046 0.523 0.502 0.155 0.148 0.163 0.192 0.286 0.316 0.543 490 F 0.044 0.528 0.542 0.152 0.138 0.398 0.181 0.279 0.292 0.389 490

0.2 ratio DFMO ratio 0.2 G 0.045 0.514 0.509 0.153 0.152 0.15 0.186 0.255 0.298 0.339 490 H 490 d) 1.4 1.4 1.4 1.4 1.4 1.4 1.4 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 105 70 35 16.8 10.5 4.2 1.4 Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.047 0.438 0.441 0.277 0.154 0.175 0.19 0.175 0.196 0.268 490 C 0.045 0.446 0.451 0.164 0.155 0.275 0.187 0.223 0.19 0.271 490 D 0.044 0.48 0.48 0.139 0.17 0.155 0.195 0.212 0.197 0.274 490

Plate 1 1 Plate E 0.046 0.438 0.438 0.153 0.154 0.17 0.195 0.179 0.196 0.28 490 F 0.043 0.444 0.447 0.276 0.16 0.161 0.184 0.221 0.19 0.277 490

0.3 ratio DFMO ratio 0.3 G 0.045 0.487 0.481 0.138 0.165 0.159 0.197 0.21 0.193 0.27 490 H 490 e) 2.1 2.1 2.1 2.1 2.1 2.1 2.1 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 105 70 35 16.8 10.5 4.2 1.4 Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.047 0.555 0.546 0.154 0.154 0.175 0.19 0.175 0.196 0.552 490 C 0.045 0.545 0.545 0.164 0.155 0.164 0.187 0.223 0.19 0.271 490 D 0.044 0.501 0.559 0.559 0.17 0.276 0.195 0.212 0.197 0.277 490

Plate 1 1 Plate E 0.046 0.545 0.561 0.153 0.154 0.17 0.195 0.179 0.196 0.28 490 F 0.043 0.54 0.552 0.167 0.16 0.161 0.184 0.221 0.19 0.277 490

0.3 ratio DFMO ratio 0.3 G 0.045 0.501 0.552 0.138 0.165 0.159 0.197 0.21 0.193 0.27 490 H 490 f) 2.1 2.1 2.1 2.1 2.1 2.1 2.1 mM DFMOI Figure 11.11 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-SH NB cell- line treated with varying concentrations of free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 2 x 104 per well. Cells incubated with respective drug combinations for 96h. Experiment was done in duplicates with raw data shown above. Data set; a, c, and e represent one

199 | Page complete experiment at 0.1 (pink), 0.2 (blue), and 0.3 (green) IC50 equivalents of DFMO, respectively. Data set; b, d, and f represents duplicate experiment.

Table 11.9 Experimental results for DFMO and Etoposide drug combination studies of SK-N-SH cell-lines. Cells seeded at 1 x 104 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment was done in duplicates. DFMO (mM) SK-N-SH Cell Viability (%) Mean Cell Viability (%) ± SD 0.7 1.4 2.1 0.7 1.4 2.1 Etoposide Trial Trial Trial Trial Trial Trial (nm) 1 2 1 2 1 2 1.4 100 86 79 70 56 47 93 ± 10 75 ± 6 52 ± 6 4.2 91 79 63 55 36 31 85 ± 8 59 ± 6 34 ± 4 10.5 79 66 55 47 38 33 73 ± 9 51 ± 6 36 ± 4 16.8 63 54 32 28 36 30 59 ± 6 30 ± 3 33 ± 4 35 56 46 29 24 29 25 51 ± 7 27 ± 4 27 ± 3 70 32 28 28 22 28 24 30 ± 3 25 ± 4 26 ± 3 105 26 22 26 22 25 23 24 ± 3 24 ± 3 24 ± 1 Control 100 100 99 100 100 100 100 ± 0 100 ± 1 100 ± 0

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Table 11.10 Experimental set-up for DFMO and Etoposide drug combination studies of IMR-32 cell- lines. Cells seeded at 5 x 103 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment done in duplicates. IMR-32 IC50 Drug concentration Percentage equivalent (DFMO, mM) of IC50 Drug (Etoposide, nM) value (%) DFMO IC50 1.5 100 IC5 0.15 10 IC10 0.3 20 IC15 0.45 30 Etoposide IC75 4.5 150 IC50 3 100 IC25 1.5 50 IC12.5 0.75 25 IC7.5 0.45 15 IC3 0.18 6 IC1 0.06 2 Control 0 0 0

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IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 4.5 3 1.5 0.75 0.45 0.18 0.06 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.046 0.391 0.391 0.392 0.189 0.28 0.314 0.389 0.392 0.382 490 C 0.048 0.383 0.384 0.168 0.178 0.388 0.297 0.377 0.397 0.379 490 D 0.041 0.359 0.357 0.142 0.18 0.272 0.304 0.346 0.35 0.359 490

Plate 3 3 Plate E 0.046 0.397 0.393 0.398 0.185 0.28 0.316 0.396 0.39 0.387 490 F 0.047 0.376 0.374 0.166 0.389 0.273 0.298 0.374 0.378 0.376 490

0.1 ratio DFMO ratio 0.1 G 0.044 0.348 0.349 0.14 0.175 0.273 0.306 0.345 0.348 0.397 490 H 490 a) 0.15 0.15 0.15 0.15 0.15 0.15 0.15 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 4.5 3 1.5 0.75 0.45 0.18 0.06 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.046 0.445 0.425 0.162 0.421 0.275 0.325 0.374 0.388 0.392 490 C 0.048 0.432 0.431 0.174 0.169 0.433 0.293 0.356 0.375 0.432 490 D 0.041 0.426 0.428 0.148 0.173 0.263 0.314 0.359 0.345 0.363 490

Plate 3 3 Plate E 0.046 0.415 0.412 0.43 0.196 0.274 0.323 0.413 0.387 0.377 490 F 0.047 0.419 0.414 0.146 0.184 0.265 0.29 0.389 0.436 0.381 490

0.1 ratio DFMO ratio 0.1 G 0.044 0.429 0.431 0.141 0.179 0.417 0.312 0.357 0.335 0.35 490 H 490 b) 0.15 0.15 0.15 0.15 0.15 0.15 0.15 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 4.5 3 1.5 0.75 0.45 0.18 0.06 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.048 0.39 0.392 0.15 0.156 0.172 0.388 0.28 0.316 0.392 490 C 0.046 0.382 0.382 0.164 0.159 0.163 0.178 0.273 0.299 0.38 490 D 0.045 0.357 0.357 0.389 0.295 0.387 0.179 0.273 0.306 0.35 490

Plate 2 2 Plate E 0.046 0.399 0.39 0.149 0.156 0.17 0.186 0.385 0.314 0.39 490 F 0.044 0.376 0.377 0.168 0.159 0.16 0.176 0.271 0.297 0.378 490

0.2 ratio DFMO ratio 0.2 G 0.045 0.344 0.348 0.143 0.395 0.291 0.177 0.271 0.304 0.348 490 H 490 c) 0.3 0.3 0.3 0.3 0.3 0.3 0.3 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 4.5 3 1.5 0.75 0.45 0.18 0.06 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.048 0.431 0.427 0.345 0.15 0.179 0.179 0.279 0.322 0.401 490 C 0.046 0.424 0.438 0.169 0.165 0.161 0.17 0.414 0.305 0.415 490 D 0.045 0.422 0.423 0.154 0.172 0.165 0.169 0.359 0.309 0.359 490

Plate 2 2 Plate E 0.046 0.41 0.411 0.142 0.159 0.355 0.189 0.269 0.317 0.401 490 F 0.044 0.402 0.417 0.171 0.422 0.169 0.163 0.278 0.295 0.386 490

0.2 ratio DFMO ratio 0.2 G 0.045 0.439 0.429 0.155 0.162 0.154 0.175 0.263 0.306 0.355 490 H 490 d) 0.3 0.3 0.3 0.3 0.3 0.3 0.3 mM DFMOI 100uL of final concentration

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 4.5 3 1.5 0.75 0.45 0.18 0.06 nM Etoposide 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.047 0.389 0.387 0.154 0.154 0.175 0.19 0.175 0.196 0.268 490 C 0.045 0.386 0.381 0.381 0.155 0.164 0.372 0.223 0.19 0.271 490 D 0.044 0.354 0.356 0.139 0.17 0.155 0.278 0.212 0.197 0.274 490

Plate 1 1 Plate E 0.046 0.396 0.391 0.153 0.154 0.17 0.195 0.274 0.196 0.28 490 F 0.043 0.376 0.379 0.377 0.16 0.272 0.184 0.221 0.19 0.382 490

0.3 ratio DFMO ratio 0.3 G 0.045 0.347 0.348 0.138 0.165 0.159 0.197 0.21 0.193 0.27 490 H 490 e) 0.45 0.45 0.45 0.45 0.45 0.45 0.45 mM DFMOI

IC75 IC50 IC25 IC12.5 IC7.5 IC3 IC1 Control Control 4.5 3 1.5 0.75 0.45 0.18 0.06 nM Etoposide 100uL of final concentration 1 2 3 4 5 6 7 8 9 10 11 12 A 490 B 0.047 0.432 0.419 0.158 0.163 0.168 0.188 0.179 0.42 0.275 490 C 0.045 0.439 0.431 0.162 0.271 0.159 0.176 0.223 0.189 0.289 490 D 0.044 0.424 0.422 0.141 0.168 0.419 0.185 0.217 0.19 0.276 490

Plate 1 1 Plate E 0.046 0.417 0.418 0.16 0.153 0.168 0.19 0.181 0.198 0.275 490 F 0.043 0.412 0.417 0.275 0.157 0.155 0.188 0.22 0.182 0.262 490

0.3 ratio DFMO ratio 0.3 G 0.045 0.42 0.425 0.143 0.149 0.153 0.192 0.21 0.18 0.255 490 H 490 f) 0.45 0.45 0.45 0.45 0.45 0.45 0.45 mM DFMOI 100uL of final concentration Figure 11.13 MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell- line treated with varying concentrations of free DFMO and Etoposide separately at 2 hour reading. Cells seeded at 5 x 103 per well. Cells incubated with respective drug combinations for 96h. Experiment was done in duplicates with raw data shown above. Data set; a, c, and e represent one

203 | Page complete experiment at 0.1 (pink), 0.2 (blue), and 0.3 (green) IC50 equivalents of DFMO, respectively. Data set; b, d, and f represents duplicate experiment.

Table 11.11 Experimental results for DFMO and Etoposide drug combination studies of IMR-32 cell- lines. Cells seeded at 5 x 103 per well and incubated 24h prior to treatment. Cells incubated with respective drug combinations for 96h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment was done in duplicates. DFMO (mM) IMR-32 Cell Viability (%) Mean Cell Viability (%) ± SD 0.15 0.3 0.45 0.15 0.3 0.45 Etoposide Trial Trial Trial Trial Trial Trial (nm) 1 2 1 2 1 2 0.06 101 89 99 90 69 60 95 ± 8 95 ± 6 65 ± 6 0.18 100 88 79 70 45 38 94 ± 8 75 ± 6 42 ± 5 0.45 99 87 69 64 53 42 93 ± 8 67 ± 4 48 ± 8 0.75 79 70 41 34 44 37 75 ± 6 38 ± 5 41 ± 5 1.5 70 59 37 32 36 30 65 ± 8 35 ± 4 33 ± 4 3 41 36 34 31 35 30 39 ± 4 33 ± 2 33 ± 4 4.5 33 29 33 30 31 28 31 ± 3 32 ± 2 30 ± 2 Control 100 99 100 99 100 99 100 ± 1 100 ± 1 100 ± 1

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c) Figure 11.15 Dose response curves of MTS assay absorbance readings at 490nm in BioTek plate reader of a) Be(2)c, b) SK-N-SH, and c) IMR-32 NB cell-line treated with varying concentrations of DFMO and Etoposide combinations at 2 hour reading. Cells seeded at 5 x 103, 1 x 104, and 5 x 103 per well for Be(2)c, SK-N-SH, and IMR-32, respectively. Cells incubated with respective drug combinations for 96h. Log [Etoposide] versus % effect plotted with three varying concentrations of IC50 equivalent ratios of DFMO. New IC50 values were determined for each cell-line at their respective drug-to-drug concentrations. Each DFMO IC50 equivalent ration yielded a new IC50 value when combined with Etoposide. Experiment was done in duplicates (n=2).

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11.4 Determination of Synergistic, Additive or Antagonistic effect on Neuroblastoma Cell-Lines To test whether the combined treatment with DFMO and Etoposide induces synergistic cell death in NB, I treated SK-N-Be(2)c, SK-N-SH, and IMR-32 cells with different concentrations of DFMO and Etoposide. Two common methods were used to analyze drug-drug interactions, the isobologram and the combination index (CI) analysis. For both combination analyses, we measured the DFMO and Etoposide interaction at

50 % effect level. We first determined the single-agent IC50 concentration for DFMO and Etoposide in NB cell lines SK-N-Be(2)c, SK-N-SH, and IMR-32 (Fig. ) using an MTS cell viability assay after 96h of treatment. DFMO exhibited an IC50 value of 0.4054 mM for SK-N-Be(2)c, 5.523 mM for SK-N-SH, and

1.468 mM for IMR-32 cells. Etoposide showed an IC50 value of 227.4 nM for SK-N-Be(2)c, 76.5 nM for SK-N-SH, and 3.02 nM for IMR-32 cells.

Subsequently, DFMO and Etoposide were combined at different concentrations based on each IC50 value to treat the three NB cell lines, generated isobolograms, and calculated the CI values illustrating the observed synergy. The combination index levels are calculated using the two equations below with the suggested effect level determined using the combination index levels (Table X):

Equation 1: Etoposide IC50 equivalent: IC50 of Etoposide with DFMO combined IC50 of Etoposide alone

Equation 2: DFMO IC50 equivalent: Actual DFMO concentration used in experiment IC50 of DFMO alone

Table 11.12 Combination Index level and the suggested effect level.

Combination Effect Index Level CI > 1.3 antagonism CI = 1.1 to 1.3 moderate antagonism CI = 0.9 to 1.1 additive CI = 0.8 to 0.9 slight synergism CI = 0.6 to 0.8 moderate synergism CI = 0.4 to 0.6 synergism

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CI = 0.2 to 0.4 strong synergism

Table 11.13 Data of combination studies of DFMO and Etoposide using SK-N-Be(2)c, SK-N-SH and IMR-32 NB cell-lines. Combination index at 50% effect level used to determine evaluation effect level. Data calculated using equations 1 and 2. Data done in triplicates for each cell-line. Concentration, Combination Evaluation at 50% Etoposide DFMO IC50 Equivalent Index at 50% Effect Level IC50 (nM) (mM) NB Cell Line Etoposide DFMO Effect Level SK-N-Be(2)c 0.184 0.099 0.282 Strong Synergism 40.87 0.04 0.136 0.197 0.333 Strong Synergism 30.30 0.08 0.119 0.296 0.415 Synergism 26.68 0.12 SK-N-SH 0.408 0.127 0.534 Synergism 29.03 0.7 0.102 0.253 0.344 Strong Synergism 6.15 1.4 0.037 0.380 0.417 Synergism 0.90 2.1 IMR-32 2.399 0.102 2.50 Antagonism 6.31 0.15 0.253 0.204 0.46 Synergism 0.44 0.3 0.169 0.307 0.48 Synergism 0.12 0.45

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c) Figure 11.16 Combination studies of DFMO and Etoposide using SK-N-Be(2)c (a), SK-N-SH (b) and IMR-32 (c) NB cell-lines. Combination index at 50% effect level used to determine evaluation effect level. Data calculated using equations 1 and 2. Data done in triplicates for each cell-line. Line of

209 | Page additivity at combination index of 1. Data below the line of additivity shows synergism, and above shows antagonism. Data falling on or close to the line of additivity shows additive effects of the drugs.

Discussion Drug combination is most widely used in treating the most dreadful diseases, such as cancer and AIDS. The main aims are to achieve synergistic therapeutic effect, dose and toxicity reduction, and to minimize or delay the induction of drug resistance 45. Toxicity reduction and resistance minimization benefits could also be the outcomes of synergism. However, in one review article by Goldin and Mantel in 1957, seven different definitions for synergism were given, and in a more recent review by Greco and colleagues in 1995, 13 different methods for determining synergism were listed and none of them supported the others 28. The meaning of synergism has become an individual's preference. Faulty or unsubstantiated synergy claims are pervasive. This is serious because it is frequently referred to in patient therapy.

As shown in Fig. 11.15 and Table 11.13 DFMO and Etoposide combinations revealed synergism in all NB cell-lines, with the exception of IMR-32. SK-N-Be(2)c cells showed strong synergism when drug concentrations were below 0.08 mM and 40.87 nM, respectively. DFMO and Etoposide showed strong synergism in SK-N-SH cells when drug concentrations were below 1.4 mM and 6.15 nM, respectively. IMR-32 cells were the only cells to display antagonism at 0.15 mM and 6.31 nM, DFMO to Etoposide, respectively.

Synergisn is observed for DFMO and Etoposide against three NB cell-lines. These data will translate into final drug-to-drug ratio combination to be entrapped within the bovine serum albumin core of hybrid nanocarriers. Optimal drug-to-drug ratio combination will yield nanocarriers most effective during in vitro analysis of HNC formulation studies.

12. CHARACTERIZATION, PREPARATION, AND EVALUATION OF HNC FORMULATIONS 12.1 Characterization methods of HNC formulations The following chapter will utilize the information gathered in the previous chapters to characterize, prepare and evaluate the formulated nanocarriers. Having an understanding of the free DFMO and Etoposide on their own and in combination will make transitioning to nanocarrier formulation a more efficient and effective process. This particular section, characterization of nanocarriers, will aim at understanding the particle size, zeta potential, polydispersity index and other characteristics of the formulation process used as boundaries for the formulation process.

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12.1.1 Dynamic Light Scattering and Zeta Potential Measurements Dynamic Light Scattering (also known as PCS - Photon Correlation Spectroscopy) measures Brownian motion and relates this to the size of the particles. It does this by illuminating the particles with a laser and analyzing the intensity fluctuations in the scattered light.

If a small particle is illuminated by a light source such as a laser, the particle will scatter the light in all directions. If a screen is held close to the particle, the screen will be illuminated by the scattered light. Now consider replacing the single particle with thousands of stationary particles. The speckle pattern will consist of areas of bright light and dark areas where no light is detected.

What causes these bright and dark areas? The diagram below shows the propagated waves from the light scattered by the particles. The bright areas of light are where the light scattered by the particles arrive at the screen with the same phase and interferes constructively to form a bright patch. The dark areas are where the phase additions are mutually destructive and cancel each other out.

Figure 12. The diagram shows the propagated waves from the light scattered by the particles. The bright areas of light are where the light scattered by the particles arrive at the screen with the same phase and interferes constructively to form a bright patch. The dark areas are where the phase additions are mutually destructive and cancel each other out.

In the above example we said that the particles are not moving. In this situation the speckle pattern will also be stationary in terms of both speckle position and speckle size.

In practice, particles suspended in a liquid are never stationary. The particles are constantly moving due to Brownian motion. Brownian motion is the movement of particles due to the random collision with the

211 | Page molecules of the liquid that surrounds the particle. An important feature of Brownian motion for DLS is that small particles move quickly and large particles move more slowly. The relationship between the size of a particle and its speed due to Brownian motion is defined in the Stokes-Einstein equation.

As the particles are constantly in motion the speckle pattern will also appear to move. As the particles move around, the constructive and destructive phase addition of the scattered light will cause the bright and dark areas to grow and diminish in intensity or to put it another way, the intensity appears to fluctuate. The Nicomp 380zls system measures the rate of the intensity fluctuation and then uses this to calculate the size of the particles.

Within the instrument is a component called a digital correlator. A correlator basically measures the degree of similarity between two signals over a period of time.

If we compared the intensity signal of a particular part of the speckle pattern at one point in time (say time = t) to the intensity signal a very short time later (t+δt) we would see that the two signals are very similar or strongly correlated. If we then compared the original signal a little further ahead in time (t+2δt), there would still be a relatively good comparison between the two signals, but it will not be as good as at t + t. The correlation is therefore reducing with time.

Now consider the intensity of the signal at ‘t’, with the intensity at a much later time - the two signals will have no relation to each other as the particles are moving in random directions (due to Brownian motion). In this situation it is said that there is no correlation between the two signals.

With DLS we are dealing with very small time scales. In a typical speckle pattern, the length of time it takes for the correlation to reduce to zero is in the order of 1 to 10's of milliseconds. The "short time later" (δt) will be in the order of nanoseconds or microseconds.

If we compare the signal intensity at (t) with itself then we would have perfect correlation, as the signals are identical. Perfect correlation is reported as 1 and no correlation is reported as 0.

If we continue to measure the correlation at (t+3δt), (t+4δt), (t+5δt), (t+6δt), etc, the correlation will eventually reach zero. A typical correlation function of correlation against time is shown below.

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Figure 12.1 The signal intensity at (t) with itself then we would have perfect correlation, as the signals are identical. Perfect correlation is reported as 1 and no correlation is reported as 0.

How does the correlation function relate to the particle size? It was mentioned earlier that the speed of particles that are being moved by Brownian motion is related to size of the particles (Stokes-Einstein equation). Large particles move slowly, while smaller particles move quickly. What effect will this have on the speckle pattern? If large particles are being measured, then, as they are moving slowly, the intensity of the speckle pattern will also fluctuate slowly. And similarly if small particles are being measured then, as they are moving quickly, the intensity of the speckle pattern will also fluctuate quickly.

The graph below shows the correlation function for large and small particles. As can be seen, the rate of decay for the correlation function is related to particle size as the rate of decay is much faster for small particles than it is for large.

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After the correlation function has been measured this information can then be used to calculate the size distribution. The Nicomp 380zls software uses algorithms to extract the decay rates for a number of size classes to produce a size distribution.

A typical size distribution graph is shown below. The X axis shows a distribution of size classes, while the Y axis shows the relative intensity of the scattered light. This is therefore known as an intensity distribution.

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Although the fundamental size distribution generated by DLS is an intensity distribution, this can be converted, using Mie theory, to a volume distribution. This volume distribution can also be further converted to a number distribution. However, number distributions are of limited use as small errors in gathering data for the correlation function will lead to huge errors in distribution by number.

Intensity, volume and number distributions A very simple way of describing the difference between the intensity, volume and number distributions is to consider a sample that contains only two sizes of particles (5nm and 50nm) but with equal numbers of each size particle.

The first graph below shows the result as a number distribution. As expected, the two peaks are of the same size (1:1) as there is equal number of particles.

The second graph shown the result of the volume distribution. The area of the peak for the 50nm particles is 1000 times larger the peak for the 5nm (1:1000 ratio). This is because the volume of a 50nm particle is 1000 times larger than the 5nm particle (volume of a sphere is equal to 4/3π(r)3).

The third graph shows the result of an intensity distribution. The area of the peak for the 50nm particles is now 1,000,000 times larger the peak for the 5nm (1:1000000 ratio). This is because large particles scatter much more light than small particles.

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It is worth repeating that the basic distribution obtained from a DLS measurement is intensity all other distributions are generated from this.

Size distribution and zeta-potential of nanoparticles were measured by a commercial zeta-potential and particle size analyzer Nicomp 380ZLS particle sizer (Fig. 12.5). For particle size measurement, 0.6 ml of the nanoparticles dispersed in solution were collected in particle sizer glass tube and allowed to equilibrate for 30 minutes to an hour. Particle size was then analyzed using the Nicomp 380ZLS at room temperature.

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Figure 12.5 Example of Nicomp 380ZLS data out-put. Gaussian distribution analysis of nanoparticles. Mean diameter and Variance (P.I.) are data most important in nanocarrier analysis.

Zeta Potential of nanocarrier formulations Zeta potential is a measure of the magnitude of the electrostatic or charge repulsion/attraction between particles, and is one of the fundamental parameters known to affect stability. Its measurement brings detailed insight into the causes of dispersion, aggregation or flocculation, and can be applied to improve the formulation of dispersions, emulsions and suspensions.

Zeta potential is a scientific term for electrokinetic potential in colloidal dispersions. In the colloidal chemistry literature, it is usually denoted using the Greek letter zeta (ζ), hence ζ-potential. From a theoretical viewpoint, the zeta potential is the electric potential in the interfacial double layer (DL) at the location of the slipping plane relative to a point in the bulk fluid away from the interface. In other words, zeta potential is the potential difference between the dispersion medium and the stationary layer of fluid attached to the dispersed particle.

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The zeta potential is caused by the net electrical charge contained within the region bounded by the slipping plane, and also depends on the location of that plane. Thus it is widely used for quantification of the magnitude of the charge. However, zeta potential is not equal to the Stern potential or electric surface potential in the double layer, because these are defined at different locations. Such assumptions of equality should be applied with caution. Nevertheless, zeta potential is often the only available path for characterization of double-layer properties.

The zeta potential is a key indicator of the stability of colloidal dispersions. The magnitude of the zeta potential indicates the degree of electrostatic repulsion between adjacent, similarly charged particles in a dispersion. For molecules and particles that are small enough, a high zeta potential will confer stability, i.e., the solution or dispersion will resist aggregation. When the potential is small, attractive forces may exceed this repulsion and the dispersion may break and flocculate. So, colloids with high zeta potential (negative or positive) are electrically stabilized while colloids with low zeta potentials tend to coagulate or flocculate as outlined in the table

Figure 12.6 Diagram showing the ionic concentration and potential difference as a function of distance from the charged surface of a particle suspended in a dispersion medium.

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Figure 12.7 Example of Nicomp 380ZLS data out-put. Zeta Potential analysis of nanoparticles. Red boxes indicate critical data.

In general, greater the zeta potential value of a nanoparticulate system better is the colloidal suspension stability due to repulsion effect between charged nanoparticles. For zeta-potential measurement, 0.2 ml of nanoparticle solution was dispersed in 2 ml of distilled water at room temperature and allowed to sit for 30 minutes before analyzing.

12.1.2 Polydispersity Index (PdI) of nanocarrier formulations In physical and organic chemistry, the dispersity is a measure of the heterogeneity of sizes of molecules or particles in a mixture. A collection of objects is called uniform if the objects have the same size, shape, or mass. A sample of objects that have an inconsistent size, shape and mass distribution is called non-uniform. The objects can be in any form of chemical dispersion, such as particles in a colloid, droplets in a cloud, crystals in a rock, or polymer molecules in a solvent. Polymers can possess a distribution of molecular mass; particles often possess a wide distribution of size, surface area and mass; and thin films can possess a varied distribution of film thickness.

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A monodisperse, or uniform, polymer is composed of molecules of the same mass. Natural polymers are typically monodisperse. Synthetic monodisperse polymer chains can be made by processes such as anionic polymerization, a method using an anionic catalyst to produce chains that are similar in length. This technique is also known as living polymerization. It is used commercially for the production of block copolymers. Monodisperse collections can be easily created through the use of template-based synthesis, a common method of synthesis in nanotechnology.

A polymer material is denoted by the term polydisperse, or non-uniform, if its chain lengths vary over a wide range of molecular masses. This is characteristic of man-made polymers. Natural organic matter produced by the decomposition of plants and wood debris in soils (humic substances) also has a pronounced polydispersed character. It is the case of humic acids and fulvic acids, natural polyelectrolyte substances having respectively higher and lower molecular weights. Another interpretation of polydispersity index is explained in the article Dynamic light scattering (cumulant method subheading). In this sense, the PDI values are in the range from 0 to 1.

The polydispersity index (PdI) or heterogeneity index, or simply dispersity (Đ), is a measure of the distribution of molecular mass in a given polymer sample. Đ calculated is the weight average molecular weight (Mw) divided by the number average molecular weight (Mn). It indicates the distribution of individual molecular masses in a batch of polymers. Đ has a value equal to or greater than 1, but as the polymer chains approach uniform chain length, Đ approaches unity (1). For some natural polymers Đ is almost taken as unity. Đ (PDI) from polymerization is often denoted as:

PDI = Mw / Mn

Where Mw is the weight average molecular weight and Mn is the number average molecular weight. Mn is more sensitive to molecules of low molecular mass, while Mw is more sensitive to molecules of high molecular mass.

12.1.3 Determination of Entrapment Efficiency (%EE) and Loading Efficiency (%LE) The following equations were applied to calculate the entrapment efficiency (Equation 3) and loading efficiency (Equation 4). Entrapment efficiency defines the total amount of drug entrapped within the carrier (nanocarrier) as compared to intial amount of drug used. Loading efficiency is the ratio of drug to the weight of total nanocarrier system. For example: If the loading efficiency is 30%, it means that 30% of the nanocarriers weight is composed of the drug (i.e. each 1 mg nanocarrier contains 0.3 mg drug).

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Equation 3: % Entrapment Efficiency = (Initial Drug Concentration – Free Drug) X 100 Initial Drug Concentration

Equation 4: % Loading Efficiency = Weight of the drug in nanocarrier X 100 Weight of the nanocarriers

12.1.4 Purification via dialysis, Density Gradient centrifugation or Vivaspin method Dialysis Dialysis is a separation technique that facilitates the removal of small, unwanted compounds from macromolecules in solution by selective and passive diffusion through a semi-permeable membrane. A sample and a buffer solution (called the dialysate, usually 200 to 500 times the volume of the sample) are placed on opposite sides of the membrane. Sample molecules that are larger than the membrane-pores are retained on the sample side of the membrane, but small molecules and buffer salts pass freely through the membrane, reducing the concentration of those molecules in the sample. Changing the dialysate buffer removes the small molecules that are no longer in the sample and allows more contaminants to diffuse into the dialysate. In this way, the concentration of small contaminants within the sample can be decreased to acceptable or negligible levels.

Dialysis works by diffusion, a process that results from the thermal, random movement of molecules in solution and leads to the net movement from areas of higher to lower concentration (until an equilibrium is reached). In dialysis, unwanted molecules inside a sample-chamber diffuse through a semi-permeable membrane into a second chamber of liquid or dialysate. Because large molecules can not pass through the pores of the membrane, they will remain in the sample chamber. By contrast, the small molecules will freely diffuse across the membrane and obtain equilibrium across the entire solution volume, effectively reducing the concentration of those small molecules within the sample.

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Figure 12.8 Recommended Molecular weight cut-off (MWCO) of dialysis membrane for nanocarrier purification.

12.1.5 Density Gradient Centrifugation method for purification of nanocarriers Centrifugation is one of the most important separation techniques used widely in colloid science and in cellular and molecular biology. While objects denser than a liquid settle spontaneously due to gravity, this process can take very long; for very small particles (e.g., nanoparticles, nanotubes) where gravitational energy is commensurate with thermal energy, the particles will not settle at all. However, centrifugal forces can help particles to move radially away from the axis of rotation and can separate these particles by size and shape. The fact that particles of different sizes and/or shapes move with different velocities in the medium provides a basis for particle separation into distinct bands, though the quality of separation is poor if the particles are similar to remedy this, more powerful techniques are needed.

One such technique is the density gradient centrifugation, in which particles are centrifuged in a liquid column supporting a density gradient (such that the buoyant force varies within the tube). Density gradient can be created by careful layering of the different-concentration liquids on top of one another as a result, density increases from the top to the bottom of the tube.

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Vivaspin method for purification of nanocarriers Vivaspin Concentrators are disposable ultrafiltration devices for the concentration of biological samples. Vivaspin 500 is suitable for sample volumes of 100–500 µl and the Vivaspin 2 can handle samples up to 2 ml. Vivaspin 2 can effectively be used in either swing bucket or fixed angle rotor accepting 15 ml centrifuge tubes.

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Typical operation of Vivaspin: 1) Select the most appropriate membrane for your sample. For maximum recovery select a MWCO at least 50% smaller than the molecular size of the species of interest. 2) Fill concentrator with up to maximum volumes. (Ensure lid is fully seated). 3) Insert assembled concentrator into centrifuge 4) Centrifuge at recommended speed, taking care not to exceed the maximum g-force indicated by membrane type and MWCO. 5) Once the desired concentration is achieved, remove assembly and recover sample from the bottom of the concentrate pocket with a pipette. The filtrate tube can be sealed for storage.

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283nm with a retention time of 13.9 minutes versus absorbance height (mAU). TNBSA (#1) has a retention time of 2 minutes at 345nm. Total run-time was 18 minutes.

#3 #2

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12.2 PREPARATION METHODS OF HNC FORMULATIONS

12.2.1 Preparation Methods for HNC formulation The preparation methods of polymeric nanocarriers from a polymeric dispersion include emulsification/ solvent diffusion, solvent evaporation, nanoprecipitation, salting out, dialysis, and supercritical fluid (SCF) technology methods. The preparation methods of polymeric nanocarriers from polymerization of monomers are emulsion (including mini and micro), interfacial polymerization, and controlled/living radical polymerization (C/LRP). Ionotrophic gelation and coacervation are methods for polymeric nanocarrier preparation from hydrophilic polymers.

12.2.2 Selection of excipients (bovine serum albumin and chitosan) Bovine serum albumin (BSA) excipient Bovine serum albumin is widely used for drug delivery because of its medical importance, abundance, low cost, ease of purification, unusual ligand-binding properties and its wide acceptance in the pharmaceutical industry 608. BSA has a molecular weight of 69,323 Daltons and an isoelectric point (pI) of 4.7 in water (at 25 °C). It could be substituted by human serum albumin (HSA), avoiding possible immunologic response in vivo. BSA and HSA are homologous proteins which serve the same function in each mammal. HSA is the most abundant plasma protein (35–50 g/L human serum) with an average half-life of 19 days. HSA is a very soluble globular monomeric protein consisting of 585 amino acid residues with a relative molecular

226 | Page weight of 66,500 Da and contains 35 cysteinyl residues forming one sulfhydryl group and 17 disulfide bridges 609. It is not a standard protein since it is extremely robust towards pH (stable in the pH range of 4– 9), temperature (can be heated at 60 °C for up to 10 h) and organic solvents. BSA Nps will be formulated using the simple coacervation (desolvation method) process (Fig. 4). During the process, a continuous drop wise addition of desolvating agent (ethanol, acetone and methanol reported in literature) to an aqueous solution of albumin under continuous stirring until the solution becomes turbid. The addition of desolvating agent into the polymer solution causes albumin to phase separate due to its diminished water-solubility 608.

Figure 12.14 Desolvation method Bovine serum albumin nanoparticle formation using simple coacervation (desolvation method).

Figure 12.15 Desolvation method Bovine serum albumin nanoparticle formation using simple coacervation (desolvation method).

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Nanoparticles made of albumin offer several specific advantages: they are biodegradable, easy to prepare and reproducible. Due to the high protein binding of various drugs, the matrix of albumin nanoparticles can be used for effective incorporation of these compounds 610. Covalent derivatization of albumin nanoparticles with drug targeting ligands is possible, due to the presence of functional groups (i.e. amino and carboxylic groups) on the nanoparticle surfaces 611, 612. Also they are expected to be well tolerated, which is supported by clinical studies with registered HSA-based particle formulations such as Albunex™ 613 and Abraxane™ 614, 615. Furthermore, protein nanoparticle preparations especially HSA appear to be a suitable agent for gene therapy, because it might avoid undesired interactions with serum that are often encountered after intravenous injection of transfection complexes 616, 617.

Chitosan (CS) excipient Chitosan, a cationic biopolymer, consists of β-(1-4)-2-acetamido-2-deoxy-D-glucose unit which is main alkaline deacetylation product of chitin. Chitosan has advantage over other polysaccharides due to its non- toxicity, biocompatibility and biodegradability 18. Chitosan and its derivatives have become useful polysaccharides in the biomedical area. Chitosan is highly abundant and renewable sources for valuable polymeric starting blocks. Only chitosan or other ionic molecules combined with chitosan can be used in the formation of many polyionic hydrogels due to their sustainable drug release properties and good biocompatibility 18. The presence of hydroxyl and amine groups displays good cross-linkable sites for various cross-linking agents.

Benefits of nanocarrier formulated from Chitosan polymer:  Simple and inexpensive to manufacture and scale-up  No heat, high shear forces or organic solvents involved in preparation process  Reproducible and stable  Applicable to a broad category of drugs; small molecules, proteins and polynucleotides  Ability to lyophilize  Stable after administration  Non-toxic

Ionotropic gelation method for Chitosan Nps formulation Chitosan Nps prepared by ionotropic gelation technique was first reported by Calvo et al and has been widely examined and developed 18. The mechanism of chitosan Nps formation is based on electrostatic interaction between amine group of chitosan and negatively charge group of polyanion such as tripolyphosphate (Fig. 5). This technique offers a simple and mild preparation method in the aqueous

228 | Page environment. First, chitosan is dissolved in 1% v/v acetic acid. The anionic polymer (TPP) is then added and nanoparticles are spontaneously formed under mechanical stirring at room temperature. The size and surface charge of particles is modified by varying the ratio of chitosan and anionic polymers 18.

Figure 12.16 Formation of Chitosan nanoparticles by ionotropic gelation method with Tripolyphosphate (TPP) crosslinking excipient 18.

12.2.3 Determination of Variables Affecting HNC formulations (i.e. particle size, zeta potential, PdI) Rationale Several variable play a crucial role in particle size (PS) and polydispersity index (PdI) of bovine serum albumin (BSA) nanocarrier formulation. These variables include; desolvating agent (methanol, acetone, acetone) and type of stir method used (paddle sitr bar, magnetic stir bar, magnetic cross-bars) which have an influence on sheer force of solution stirring 2, 618, 619. These variables are analyzed in this section of the thesis. Optiml variable conditions will be determined at the end of this section and carried over to the start of hybrid nanocarrier (HNC) formulation. The experimental goals of these experiments are nanocarriers having a particle size less then 100nm with a polydispersity index no greater than 0.4.

Materials Bovine serum albumin (BSA) fraction V (ThermoFisher, CAS 9048-46-8) were used throughout all formulation procedures. BSA powder is kept at 4°C with fresh stock solutions prepared before each experiment. BSA powder were diluted in ultrapure distilled deionized water purified by a Milli-Q apparatus

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(Millipore, Bedford, MA, USA) to respective concentration (%weight to volume, %w/v). HPLC grade methanol was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 67-56-1) and used throughout the study. Ethyl alcohol (Ethanol) were purchased from VWR International (VWR, Radnor, PA, USA) (CAS 64-17-5) and used throughout the study. ACS grade Acetone was purchased from VWR International (VWR, Radnor, PA, USA) (CAS Number 67-64-1) and used throughout the study. BSA solutions were dissolved over several hours under gentle stirring at room temperature and used immediately once fully dissolved. Excess BSA solution were discarded.

Methods Respective BSA solution concentrations (%w/v) were placed in 50mL glass beaker with magnetic stir bar. Under constant stirring (650 RPM), desolvating agent were added continuously (not drop-wise) into stirring solution. Characteristic data (i.e. particle size, polydispersity index) were analyzed. The experimental goals of these experiments are nanocarriers having a particle size less then 100nm with a polydispersity index no greater than 0.4.

Statistical Analysis All formulation studies will be performed in triplicate with data reported as mean ± SD. Coefficient of Variance (CV) is calculated for triplicated experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%.

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Flow diagram 1. Tested variables most influential on bovine serum albumin (BSA) nanocarriers:

Bovine serum albumin (BSA) nanocarriers (no drug): Particle size (PS) <100nm, Polydispersity Index (PdI) < 0.4

Variables affecting BSA nanocarriers (PS & PdI): Desolvating agent (MeOH, EtOH, Acetone), stir type (paddle, magnetic bar, cross-bar)

Testing of desolvating agents: Methanol (MeOH), Ethanol (EtOH), and Acetone PS < 100nm, PdI < 0.4

Testing of combined desolvating agents: MeOH:EtOH, EtOH:Acetone, Acetone:MeOH PS < 100nm, PdI < 0.4

Testing of stir types: Paddle stir rod, magnetic stir bar, magnetic cross stir bar PS < 100nm, PdI < 0.4

Evaluation of most effective desolvating agent(s) and stir type Variables carried over to hybrid nanocarrier formulations

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Results

Table 12. Effects of various non-diluted desolvating agents on particle size (nm) and polydispersity index (PdI) using 10% BSA solution (1mL) at 650 RPM, small paddle stirrer, magnetic stir bar OR cross magnetic stir bar, 1 mL/min continuous flow rate of agent directly into the solution (not drop- wise) with a total stir time of 1h. Experimental conditions of the developed method show comparable data as depicted by CV (<5%) with the exception of the cross magnetic stir bar methods. Mean Particle size Polydispersity Index Particle Mean PdI Mean Non-diluted (nm) (PdI) size (nm), (n=3) %CV desolvating agent (n=3) (4 mL each) Trial Trial Trial Trial Trial Trial Mean avg. Mean avg. Size PdI 1 2 3 1 2 3 ± std. dev. ± std. dev. 1) 320.17 ± 321.5 319.1 319.9 0.498 0.637 0.635 0.590 ± 0.08 0.38 13.5 Ethanol 1.22 2) 254.3 260.2 262.7 0.336 0.238 0.242 259 ± 4.31 0.272 ± 0.05 1.66 20.4 Acetone 3) 31 31.4 31.2 0.462 0.508 0.490 31.2 ± 0.20 0.487 ± 0.02 0.64 4.76

Paddle Paddle Methanol 1) 111.87 ± 113.1 111.8 110.7 0.712 0.738 0.752 0.734 ± 0.02 1.07 2.77 Ethanol 1.2 2) 0.301 ± 277.7 281.8 283.5 0.318 0.304 0.282 281 ± 2.98 1.06 6.02 Acetone 0.018 3) 0.721 ± 41.4 40.7 40.6 0.728 0.719 0.717 40.9 ± 0.44 1.07 0.81

Magnetic Magnetic Methanol 0.005 1) 0.542 ± 74.3 73.1 73.8 0.591 0.527 0.508 73.7 ± 0.60 0.81 8.02 Ethanol 0.043 2) 258.1 275 231 0.527 0.535 0.562 254.7 ± 22 0.541 ± 0.01 8.7 3.4 Acetone 3) 0.779 ± 55.9 68 59 0.766 0.821 0.752 61 ± 6 10.3 4.7

Cross Cross Methanol 0.036

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Figure 12.18 Turbidity of BSA nanocarrier formulations (left to right; methanol, acetone and ethanol)

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Mixture of Mean Particle Particle size Polydispersity index Mean PdI desolvating Size (nm), Mean %CV (nm) (PdI) (n=3) agent(s) (n=3) (4 mL Trial Trial Trial Trial Trial Trial Mean avg. Mean avg. Size PdI each) 1 2 3 1 2 3 ± std. dev. ± std. dev. 1) 75% Acetone 160.7 159 157.8 0.457 0.460 0.462 159.17 ± 1.46 0.460 ± 0.002 0.92 0.55 25% MeOH 2) 50% Acetone 137.6 143.7 147.1 0.379 0.413 0.420 142.8 ± 4.81 0.404 ± 0.022 3.37 4.43 50% MeOH 3) 25% Acetone 47.2 45.9 46.1 0.289 0.287 0.298 46.4 ± 0.7 0.291 ± 0.006 1.51 2.01 75% MeOH

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Table 12.2 Combination of desolvating agents (ethanol & methanol) and its effects on particle size (nm) and polydispersity index (PdI) using 10% BSA solution (1mL) at 650 RPM (small paddle

235 | Page stirrer), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5% Mean Mixture of Particle size Polydispersity index Particle Mean PdI Mean %CV desolvating (nm) (PdI) Size (nm), (n=3) agent(s) (n=3) (4 mL each) Trial Trial Trial Mean avg. Mean avg. Trial 1 Trial 2 Trial 3 Size PdI 1 2 3 ± std. dev. ± std. dev. 1) 75% MeOH 46.7 46.7 46.9 0.480 0.480 0.480 46.77 ± 0.12 0.480 ± 0 0.25 0 25% EtOH 2) 50% 0.308 ± MeOH 75 75.2 73.8 0.301 0.298 0.325 74.67 ± 0.76 1.01 4.80 0.015 50% EtOH 3) 25% 144.17 ± 0.44 ± MeOH 148 147.1 137.4 0.441 0.434 0.444 4.08 1.17 5.88 0.005 75% EtOH

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Table 12.3 Combination of desolvating agents (ethanol & acetone) and its effects on particle size (nm) and polydispersity index (PdI) using 10% BSA solution (1mL) at 650 RPM (small paddle stirrer, magnetic stir bar, cross bar), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%. Mixture of Mean Particle size Polydispersity index Mean PdI Mean desolvating Particle Size (nm) (PdI) (n=3) %CV agent(s) (nm), (n=3) (4 mL Trial Trial Trial Trial Trial Trial Mean avg. Mean avg. Size PdI each) 1 2 3 1 2 3 ± std. dev. ± std. dev. 1) 75% EtOH 264.6 268.9 267.5 0.266 0.317 0.324 267 ± 2.19 0.302 ± 0.032 0.82 13.5 25% Acet.

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2) 50% EtOH 234.2 232.5 228 0.272 0.294 0.308 231.57± 3.20 0.291 ± 0.018 1.38 10.5 50% Acet. 3) 25% EtOH 214.1 210.7 209 0.299 0.309 0.310 211.27 ± 2.60 0.306 ± 0.006 1.23 6.23 75% Acet.

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Figure 12.22 All combinations of desolvating agents (ethanol & methanol and acetone) and its effects on particle size (blue) and polydispersity index (black line) using 10% BSA solution (1mL) at 650 RPM (paddle, magnetic stir bar, cross bar), 1 mL/min continuous flow rate of agent with a total stir time of 1h. Experiment done in triplicate with data plotted as mean ± SD. Experimental conditions of the developed method show comparable data as depicted with a CV <5%

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Table 12.4 Effects of desolvating agent (methanol) on 1% w/v Bovine Serum Albumin (BSA) in DI- H2O (started with 40mL 1% w/v BSA) under constant stir rate of 600 rpm in a 100mL glass beaker. Flow rate was set at 1mL/min continuously into the solution (not drop-wise). Experiment conducted to show desolvating effects of methanol on BSA. Experimental conditions obtained formulation goals for nanocarriers (highlighted) having particle sizes less than 100nm and PdI’s less than 0.4. MeOH Nicomp Gaussian % MeOH (v/v) added PdI (%distribution) (nm) concentration (ml) 5 11 (100%) 8 0.789 12.5 10 11 (100%) 8 0.748 25 15 11 (100%) 9 0.797 37.5 20 11 (100%) 11 0.841 50 25 11 (100%) 17 0.910 62.5 30 11 (100%) 25 0.960 75 35 11 (3%), 41 (97%) 32 0.285 87.5 40 11 (16%), 56 (84%) 41 0.323 100 45 11 (19%), 56 (81%) 43 0.327 112.5 50 11 (7%), 53 (93%) 49 0.194 125 55 11 (7%), 58 (93%) 51 0.245 137.5 60 11 (2%), 42 (93%) 45 0.213 150 65 11 (12%), 39 (88%) 44 0.437 162.5 70 11 (7%), 27 (28%), 146 (65%) 55 0.781 175 75 11 (5%), 26 (39%), 178 (57%) 60 0.561 187.5 80 11 (12%), 31 (44%), 136 (45%) 45 0.521 200 Control 11 (100%) 10 0.405 0

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Table 12.5 Effects of desolvating agent (methanol) on 4% w/v Bovine Serum Albumin (BSA) in DI- H2O (started with 20mL 4% w/v BSA) under constant stir rate of 600 rpm in a 100mL glass beaker. Flow rate was set at 1mL/min continuously into the solution (not drop-wise). Experiment conducted to show desolvating effects of methanol on BSA. Experimental conditions obtained formulation goals for nanocarriers (highlighted) having particle sizes less than 100nm and PdI’s less than 0.4. MeOH Nicomp Gaussian % MeOH (v/v) added PdI (%distribution) (nm) concentration (ml) 2.5 11 (100%) 7 0.694 12.5 5 11 (100%) 7 0.623 25 7.5 11 (100%) 8 0.663 37.5 10 11 (100%) 8 0.634 50 12.5 11 (100%) 17 0.766 62.5 15 11 (100%) 19 0.653 75 17.5 11 (30%), 98 (70%) 40 0.610 87.5 20 11 (16%), 79 (84%) 55 0.332 100 22.5 11 (15%), 72 (85%) 54 0.329 112.5 25 11 (24%), 54 (76%) 38 0.388 125 27.5 11 (100%) 31 0.384 137.5 30 11 (29%), 36 (71%) 33 0.445 150 32.5 13 (19%), 40 (41%), 135 (40%) 34 0.432 162.5 35 11 (100%) 32 0.416 175 37.5 11 (25%), 35 (75%) 33 0.394 187.5 40 11 (23%), 37 (78%) 33 0.391 200 Control 11 (100%) 10 0.405 0

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Discussion Several variables play a crucial role in particle size (PS) and polydispersity index (PdI) of bovine serum albumin (BSA) nanocarrier formulation. These variables include; desolvating agent (methanol, acetone, acetone) and type of stir method used (paddle sitr bar, magnetic stir bar, magnetic cross-bars) which have an influence on sheer force of solution stirring 2, 618, 619. These variables were analyzed in this section of the thesis. Optiml variable conditions was also determined and carried over to the start of hybrid nanocarrier (HNC) formulation. The experimental goals of these experiments were nanocarriers having a particle size less then 100nm with a polydispersity index no greater than 0.4.

Various non-diluted desolvating agents were evaluated. Three main desolvating agent reported in the literature were; ethanol, methanol and acetone. Ethanol produced the largest mean particle size (320nm) with a high mean PdI (0.6) using a paddle stirrer. A magnetic stir bar produced a smaller mean particle size

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(81nm) with an increase in PdI (0.73). For both paddle and magnetic stir types, acetone produced the lowest mean PdI (0.27 and 0.30, respectively) with a high mean particle size (260 and 281nm, respectively).

Methanol is observed to be the best non-diluted desolvating agent, producing a mean particle size of 31 to 41nm for both stir types, magnetic and paddle stirrer. However, methanol also produced a mean PdI (0.49 & 0.72, paddle and magnetic) which did not full-fill the experimental objectives. Magnetic stir bar is observed to increase PdI for ethanol and methanol making the paddle stir option ideal in PdI control for these two desolvating agents. The paddle stir bar will be utilized for the remainder of the desolvating agent studies.

Varying the concentrations between two desolvating agents, acetone and methanol, a shift in the particle size and polydispersity index range occurs. The higher concentration of methanol in solution causes a decrease in both the PdI and particle size (with the exception of 75% acetone, 25% methanol solution). However, a solution of non-diluted methanol (100% methanol) produces the highest PdI at 0.48 with the lowest mean particle size, 31.2 nm. The most effective dilution ratio appeared to be 25% acetone in 75% methanol giving a mean PdI of 0.29 with a mean particle size of 46.4nm.

12.2.4 Taguchi Orthogonal Array Design of Experiments (DoE) A Taguchi design is a designed experiment that lets you choose a product or process that functions more consistently in the operating environment. Taguchi designs recognize that not all factors that cause variability can be controlled. These uncontrollable factors are called noise factors. Taguchi designs try to identify controllable factors (control factors) that minimize the effect of the noise factors. During experimentation, you manipulate noise factors to force variability to occur and then determine optimal control factor settings that make the process or product robust, or resistant to variation from the noise factors. A process designed with this goal will produce more consistent output. A product designed with this goal will deliver more consistent performance regardless of the environment in which it is used.

A well-known example of Taguchi designs is from the Ina Tile Company of Japan in the 1950s. The company was manufacturing too many tiles outside specified dimensions. A quality team discovered that the temperature in the kiln used to bake the tiles varied, causing nonuniform tile dimension. They could not eliminate the temperature variation because building a new kiln was too costly. Thus, temperature was a noise factor. Using Taguchi designed experiments, the team found that by increasing the clay's lime content, a control factor, the tiles became more resistant, or robust, to the temperature variation in the kiln, letting them manufacture more uniform tiles.

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Taguchi designs use orthogonal arrays, which estimate the effects of factors on the response mean and variation. An orthogonal array means the design is balanced so that factor levels are weighted equally. Because of this, each factor can be assessed independently of all the other factors, so the effect of one factor does not affect the estimation of a different factor. This can reduce the time and cost associated with the experiment when fractionated designs are used.

Control factors are process or design parameters that you can control. In Taguchi designed experiments, the goal is to identify control factor settings that minimize the variability produced by uncontrollable factors, called noise factors. Examples of control factors are equipment settings, material used to manufacture the product, or product design features. Consider a cake mixture manufacturer who wants to optimize cake flavor under various conditions. Noise factors, which are out of the manufacturer's control, include the air temperature and humidity while the consumer is making the cake. Control factors, which are in the manufacturer's control include cake mixture ingredients. The manufacturer wants to determine control factors that reduce the effect of noise factors on cake flavor.

Delta (Δ) represents the overall change in a value. For example, if the low temperature on a particular day was 55 degrees and the high temperature was 75 degrees, this would give a delta of 20 degrees. Often, delta is considered the difference between an initial and end value, irrespective of fluctuations that might occur between these points. For example, on the first day of the month, a bank account contains a certain amount of money. Though numerous deposits and withdrawals are made as the month progresses, if on the last day of the month the balance is the same as it was at the first day of the month, the accountant could claim a balance delta of 0.

Flow diagram 2. iRGD conjugated, PEGylated hybrid nanocarriers loaded with DFMO and Etoposide (iRGD-PEG-HNC-D-E) formulation process. The current section will focus on the highlighted (yellow) aspect of the formulation process. Illustrations of current nanocarrier step depicted of the left axis.

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12.2.5 Development of bovine serum albumin (BSA) nanocarriers and chitosan (CS) nanocarriers using Taguchi Orthogonal Array Design of Experiments (DoE) Rationale The Taguchi orthogonal array design of experiments will be utilized to development BSA and CS nanocarriers separately without the presence of drugs. Factors that most influence important characteristic nanocarrier data (particle size, zeta potential, and polydispersity index) such as; desolvating agent volume and %BSA concentration 2, 618, 619, are tested in these experiments. Each step of the formulation process is

246 | Page broken down into 6 phases (described below). Each section will focus on one or more phases at a time (flow diagram will be highlighted).

Materials Bovine serum albumin (BSA) fraction V (CAS 9048-46-8) were used throughout all formulation procedures. BSA powder is kept at 4°C with fresh stock solutions prepared before each experiment. BSA powder were diluted in ultrapure distilled deionized water purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA) to respective concentration (%weight to volume, %w/v). HPLC grade methanol was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 67-56-1) and used throughout the study. Ethyl alcohol (Ethanol) were purchased from VWR International (VWR, Radnor, PA, USA) (CAS 64-17-5) and used throughout the study. ACS grade Acetone was purchased from VWR International (VWR, Radnor, PA, USA) (CAS Number 67-64-1) and used throughout the study. BSA solutions were dissolved over several hours under gentle stirring at room temperature and used immediately once fully dissolved. Excess BSA solution were discarded.

12.2.6 Phases of HNC formulation (explanation of flow diagram) Phase 1: The 1st phase of development treated each nanocarrier as separate entities; bovine serum albumin (BSA) nanocarriers and chitosan (CS) nanocarriers alone. No drugs were used during phase 1 and no combination of polymers were conducted in these experiments. Characteristic nanocarrier data were collected; particle size, zeta potential, polydispersity index, and entrapment efficiency (when applicable). Characteristic data were analyzed in all phases of the formulation process. These experiments determined factors influencing these characteristic data (i.e. volume of desolvating agent, % w/v BSA, etc).

Phase 2: With the successful completion of phase 1 (met established particle size, zeta potential, and polydispersity index goals), phase 2 can commence. Phase 2 focused on bovine serum albumin loaded DFMO nanocarriers (BSA-D). One is drug (DFMO) is utilized for this phase to observe the entrapment efficiency capacity of BSA nanocarriers. A high entrapment efficiency (>90%) formulation will be needed

247 | Page to proceed to phase 3. Characteristic data were also analyzed to determine an optimal formulation; particle size (<100nm), polydispersity index (<0.4). These characteristic goals will be carried over for the remainder phases of the formulation process.

Phase 3: With the characteristic goals met in phase 2, phase 3 can begin. Phase 3 utilizes both drugs, DFMO and Etoposide with the bovine serum albumin nanocarrier (BSA-D-E). Bovine serum albumin, as described in the introduction, can act as both a hydrophilic and hydrophobic carrier of small molecule drugs. Taking advantage of these properties, both drugs should entrap into the “core” of the BSA nanocarrier. Entrapment efficiencies based-off of IC50 values obtained during In vitro studies of free drug will be taken into consideration during this phase of formulation. Enough of each drug must be entrapped within the BSA nanocarrier to be effective, if not more effective, for future In vitro studies. Obtaining entrapment efficiency values equal or greater than the established IC50 values of NB cell-lines, along with characteristic goals (of phase 2) will allow for continuaion into phase 4 of formulation.

Phase 4: Coating of chitosan (CS) onto the surface of BSA nanocarriers is conducted in this phase. Ionotrophic gelation method (described earlier) will be used for this phase. Briefly, BSA nanocarriers (containing both drugs, BSA-D-E) having a negative zeta potential will be non-covalently cross-linked through ionic interaction with positively charged chitosan polymer. The formulation of these hybrid nanocarriers loaded with DFMO and Etoposide (HNC-D-E) will undergo characteristic data analysis (phase 2 goals) to determine optimal formulation to be used in phase 5.

Phase 5: PEGylation (PEG-5000) will be bound to the surface of the chitosan shell of the hybrid nanocarier provided by the amino acid backbone of the chitosan polymer. PEGylated nanocarriers have been shown to escape reticuloendothelial uptake (macrophage system) through “shielding” of the nanocarrier by absorption of water molecules within the circulatory system, thereby preventing protein absorption and clearance by the immune system. The same characteristic goals of phase 2 are applied to this phase. Drug release profiles will be conducted during this phase of formulation. The optimal PEGylated hybrid nanocarrier containing both drugs (PEG-HNC-D-E) will be utilized for phase 5. Some aspects of this phase will be altered during phase 6.

Phase 6: The final formulation step will focus on iRGD peptide conjugation to the optimal PEGylated hybrid nanocarrier formulation containing both drugs (iRGD-PEG-HNC-D-E). Phase 5 and 6 coincide with one another. In order to change the density of iRGD peptide on the surface of the hybrid nanocarrier, the amount of PEGylated units must be adjusted. These steps will be described in greater detail in their

248 | Page respective section. The same characteristic data goals of phase are also applied to this phase. The optimal formulation will be evaluated and used for future In vitro and flow cytometry studies.

Statistical Analysis All formulations studies will be performed in triplicate and the data will be reported as mean ± SD. Coefficient of Variance (CV) is calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV <5%.

Results

Phase 1 Results BSA nanocarrers (no drug) Chitosan nanocarriers (no drug)

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4 400 6 30 5 400 8 45 6 400 10 15 7 600 6 45 8 600 8 15 9 600 10 30

Table 12.7 Results of Taguchi orthogonal array design of experiment 33 (3 level, 3 factor) for the development of bovine serum albumin (BSA) nanocarriers. These factors were deemed most influential on particle size (PS) and polydispersity index (PdI) based on literature review 2. Desolvating agent (methanol) flow rate set at 1mL/min (continuously, not drop-wise, into solution). 10% w/v BSA used (10mL). Data reported as mean ± SD. Coefficient of Variance (CV) calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%. Mean Particle size Polydispersity index Particle Mean PdI Mean Run (nm) (PdI) Size (nm), (n=3) %CV Order (n=3) Trial Trial Trial Trial Trial Trial Mean avg. Mean avg. PS PdI 1 2 3 1 2 3 ± std. dev. ± std. dev. 1 48.7 45.3 42.7 0.295 0.304 0.308 45.5 ± 3 0.302 ± 0.007 6.6 2.2 2 45.1 47.4 43.4 0.235 0.256 0.247 45.3 ± 2 0.246 ± 0.010 4.4 4.3 3 63.5 66.9 65.8 0.412 0.432 0.425 65.4 ± 1.7 0.423 ± 0.010 2.7 2.4 4 59.3 62.5 60.8 0.3 0.309 0.315 60.8 ± 1.6 0.308 ± 0.007 2.6 2.5 5 53.7 56.5 54.3 0.310 0.321 0.343 54.8 ± 1.5 0.325 ± 0.017 2.7 5.2 6 43.5 41.8 42.9 0.171 0.191 0.162 42.7 ± 0.8 0.175 ± 0.015 2.0 8.5 7 58.2 54.7 55.9 0.243 0.232 0.254 56.2 ± 1.8 0.243 ± 0.011 3.2 4.5 8 43.1 40.6 41.7 0.201 0.210 0.236 41.8 ± 1.3 0.216 ± 0.018 3.0 8.4 9 52.4 53.8 50.3 0.126 0.143 0.137 52.1 ± 1.8 0.135 ± 0.008 3.4 6.4

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Main Effects Plot for Means Data Means

Stir Rate Volume agent (mL) 60

45 200 400 600 6 8 10 Stir time (mins) 60 Mean of MeansMean of

45 15 30 45

Response Table for Means for Particle Size (nm)

Volume agent Stir time Level Stir Rate (mL) (mins) 1 52.43 69.33 45.10 2 52.17 47.30 52.27 3 65.17 53.13 72.40 Delta 13.00 22.03 27.30 Rank 3 2 1

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Main Effects Plot for Means Data Means Stir Rate Volume agent (mL) 0.35

0.30

0.25

0.20

0.15 200 400 600 6 8 10 Stir time (mins) 0.35 Mean of MeansMean of 0.30

0.25

0.20

0.15 15 30 45

Response Table for Means for Polydispersity Index (PdI)

Volume Stir time Level Stir Rate agent(mL) (mins) 1 0.3140 0.3650 0.2223 2 0.2603 0.2487 0.2203 3 0.2757 0.2363 0.4073 Delta 0.0537 0.1287 0.1870 Rank 3 2 1

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PS PdI PS PdI PS PdI PS PdI PS PdI PS PdI PS PdI PS PdI PS PdI

15 min 15 50.55 0.325 37.93 0.297 43.77 0.225 50.28 0.272 37.67 0.183 43.50 0.171 53.87 0.259 41.25 0.171 47.08 0.158

30 min 30 57.72 0.323 45.1 0.235 50.93 0.223 57.45 0.269 44.83 0.181 50.67 0.169 61.03 0.257 48.42 0.169 54.25 0.156

45 min 45 68.43 0.482 55.82 0.394 61.65 0.382 68.17 0.429 55.55 0.340 61.38 0.328 71.75 0.416 59.13 0.328 64.97 0.315

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Table 12.9 Using the predicted experimental outcomes (table x), a new experimental set-up was conducted to validate the generated predicted results. These factors were deemed most influential on particle size (PS) and polydispersity index (PdI) based on literature review 2. Desolvating agent (methanol) flow rate set at 1mL/min (continuously, not drop-wise, into solution). 10% w/v BSA used (10mL). Volume Response 1 Run Stir rate Stir time Response 2 desolvating (particle Order (RPM) (min) (PdI) agent (mL) size, nm) 10 400 8 15 Data Table Data Table 11 400 10 15 12 400 8 30 13 400 10 30 14 600 8 15 15 600 10 15 16 600 8 30 17 600 10 30

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Table 12.10 Results to validate predicted experimental outcomes (table x) generated by Minitab 16 software. Desolvating agent (methanol) flow rate is set at 1mL/min (continuously, not drop-wise, into solution). 10% w/v BSA used (10mL). Data reported as mean ± SD. Coefficient of Variance (CV) calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%. Mean Particle size Polydispersity index Particle Mean PdI Mean Run (nm) (PdI) Size (nm), (n=3) %CV Order (n=3) Trial Trial Trial Trial Trial Trial Mean avg. Mean avg. PS PdI 1 2 3 1 2 3 ± std. dev. ± std. dev. 10 42 45 39 0.225 0.246 0.210 42 ± 3 0.227 ± 0.018 7.1 8.0 11 47.6 46 48 0.151 0.178 0.173 47 ± 1 0.167 ± 0.014 2.2 8.6 12 42 48 47 0.165 0.134 0.154 46 ± 3 0.151 ± 0.016 7.0 10.4 13 43.5 40 45 0.168 0.131 0.147 43 ± 3 0.149 ± 0.019 6.0 12.5 14 45.2 39 46 0.227 0.196 0.207 43 ± 4 0.210 ± 0.016 8.8 7.5 15 51 59 55 0.243 0.212 0.223 55 ± 4 0.226 ± 0.016 7.3 7.0 16 47.2 42 45 0.161 0.196 0.177 45 ± 3 0.178 ± 0.018 5.8 9.8 17 40.6 43 42 0.185 0.223 0.194 42 ± 1 0.201 ± 0.020 2.9 9.9

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Table 12.11 The following table represents experimental outcomes (Mean ± SD) versus predicted values generated by Minitab 16 software. Accuracy was greater than 77% and 71% for particle size and polydispersity index, respectively. Predicted Results % Accuracy Experimental Results (Minitab 16 software) Mean Particle Polydispersity Run Mean PdI Particle Size Particle Polydispersity size Index Order (n=3) (nm), (n=3) size Index (nm) (PdI) Mean avg. Mean avg. (nm) (PdI) ± std. dev. ± std. dev. 10 42 ± 3 0.227 ± 0.018 37.67 0.183 88.5 76.0 11 47 ± 1 0.167 ± 0.014 43.50 0.171 91.5 97.9 12 46 ± 3 0.151 ± 0.016 44.83 0.181 98.1 83.4 13 43 ± 3 0.149 ± 0.019 50.67 0.169 84.5 88.0 14 43 ± 4 0.210 ± 0.016 41.25 0.171 94.8 77.2 15 55 ± 4 0.226 ± 0.016 47.08 0.158 83.2 57.0 16 45 ± 3 0.178 ± 0.018 48.42 0.169 92.4 94.7 17 42 ± 1 0.201 ± 0.020 54.25 0.156 77.2 71.4

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0.15 89 62 55 93 133

(mg/mL) 0.25 N/A N/A 1265 61 91

H2O) H2O) ripolyphosphate (in DI- (in ripolyphosphate

T 0.35 N/A N/A 7241 295 68

The ionotropic gelation method is commonly used to prepare CS nanoparticles. In acidic solution, the + NH2 backbone of a CS molecule is protonized to be –NH3 , it interacts with an anion such as tripolyphosphate (TPP) or bovine serum albumin (BSA) by ionic interaction to form nano or microspheres. 18 This method is very simple and mild. In addition, reversible physical cross-linking by electrostatic interaction, instead of chemical cross-linking, is applied to prevent possible toxicity of reagents and other undesirable effect. 18

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Flow diagram 3. Formulation process. The following sections will focus on the highlighted (yellow) aspects of the HNC formulation:

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12.2.7 Development of Hybrid nanocarriers loaded with DFMO and Etoposide (HNC-D-E) using Taguchi Orthogonal Array Design of Experiments (DoE) Phases 2, 3 & 4 BSA-D BSA-D-E HNC-D-E

Figure 12.28 Illustration of current nanocarrier formulation step. “Phase 2, 3, & 4” of nanocarrier development will be focused on.

12.2.8 Optimization of HNC-D-E using Taguchi orthogonal array and predicted full factorial DoE This section will focus on phases 2 through 4 (flow diagram) of the formulation process. The development of the final formulation (iRGD-PEG-HNC-D-E) will be done in a step-wise process. The nanocarrier formulation is broken down into 6 phases, each phase adding a component of the nanocarrier.

Phases this section will focus on: Phase 2: With the successful completion of phase 1 (met established particle size, zeta potential, and polydispersity index goals), phase 2 can commence. Phase 2 focused on bovine serum albumin loaded DFMO nanocarriers (BSA-D). DFMO is utilized for this phase to observe the entrapment efficiency capacity of BSA nanocarriers. A high entrapment efficiency (>90%) formulation will be needed to proceed to phase 3. Characteristic data were also analyzed to determine an optimal formulation; particle size (<100nm), polydispersity index (<0.4). These characteristic goals will be carried over for the remainder phases of the formulation process.

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Methods Taguchi DoE are set-up for the development of BSA-D, BSA-D-E, and HNC-D-E formulation procedures. The DoE are explained in each section with experimental outcomes described after the DoE. Respective BSA solution concentrations (%w/v) were placed in 50mL glass beaker with magnetic stir bar. Under constant stirring (650 RPM), desolvating agent were added continuously (not drop-wise) into stirring solution. Characteristic data (i.e. particle size, polydispersity index) were analyzed. The experimental goals of these experiments are nanocarriers having a particle size less then 100nm with a polydispersity index no greater than 0.4.

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Results

Phase 2: BSA-D Results Bovine serum albumin nanocarriers loaded with DFMO (BSA-D)

Figure 12.29 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 2” nanocarrier development.

Table 12.13 Cost of experimental setup (DFMO only) *. To run a 9-beaker Taguchi orthogonal array DoE, approximately 20mL of drug (DFMO) solution is needed. Cost varies with starting drug concentration. Based on previous in vitro dose-response data on NB cell-lines, 5mM will be used for further experiments. DFMO Cost of Volume of DFMO concentration DFMO DFMO solution concentration (mM) solution ($) (mL) (mg/mL) 1mM $17.71 for 20mL 0.18217mg/mL

2.5mM $44.27 for 20mL 0.45543mg/mL

5mM $88.53 for 20mL 0.91085mg/mL

10mM $177.06 for 20mL 1.8217mg/mL

20mM $354.12 for 20mL 3.6434mg/mL

40mM $708.24 for 20mL 7.2868mg/mL

*2 grams of DFMO cost $9,720 at Sigma-Aldrich. Calculations based on Sigma-Aldrich price.

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Table 12.14 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA-D). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. Run volu volu MeOH Final Dru Final Final Total Total Orde me of me concentrati volu g to DFMO DFMO amou drug r BSA MeO on (% v/v) me add concentrati concentrati nt of in in DI- H to for all fro on (mM) on drug solutio H20 add (mL) m (mg/mL) in n (ug) (mL) (mL) 5m solutio M n (mg) stoc k (mL ) 1 10 10 100 11 1 0.455 0.0828045 0.9108 910.85 5 2 10 12 120 12 2 0.833 0.1518083 1.8217 1821.7 3 10 14 140 14 4 1.429 0.2602429 3.6434 3643.4 4 10 10 100 11 1 0.455 0.0828045 0.9108 910.85 5 5 10 12 120 12 2 0.833 0.1518083 1.8217 1821.7 6 10 14 140 14 4 1.429 0.2602429 3.6434 3643.4 7 10 10 100 11 1 0.455 0.0828045 0.9108 910.85 5 8 10 12 120 12 2 0.833 0.1518083 1.8217 1821.7 9 10 14 140 14 4 1.429 0.2602429 3.6434 3643.4

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TNBSA TNP-DFMO-TNP adduct reagent @ 345nm, retention time of 11.2 minutes

Figure 12.30 HPLC chromatograms of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA- D). HPLC analysis conducted to determine entrapment efficiency of BSA-D. BSA-D were purified using vivaspin method and supernatant treated with TNBSA reagent (according to previously described section). TNP-DFMO-TNP adduct was quantified and analyzed via HPLC to determine entrapment efficiency of HNC-D. TNP-DFMO-TNP has a retention time of 11.2 minutes at 345nm. Absorbance area (mAU*min) were calculated and used to determine %EE.

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DFMO derivative (TNP-DFMO-TNP adduct) @ 345nm standard curve using HPLC analysis. Concencentration vs. absorbance area (mAU*min)

60 50 40 30 y = 0.9779x - 0.1935 20 R² = 0.9999 10 0 0 10 20 30 40 50 60 Absorbance Absorbance area (mAU*min)

Concentration (ug/mL) a)

Etoposide @ 283nm standard curve using HPLC analysis. Concencentration vs. absorbance area (mAU*min) 40 35 30 25 20 y = 0.6884x - 0.6014 15 R² = 0.996 10 5 0

Absorbance Absorbance area (mAU*min) 0 10 20 30 40 50 60 Concentration (ug/mL) b) Figure 12.31 Linearity graph of standard curve parameters of a) DFMO derivative (TNP-DFMO- TNP) and b) Etoposide quantified using Dionex Ultimate 3000 HPLC at 345nm and 283nm, respectively. Linearity was found in a range of 10 to 60ug/mL using absorbance area (mAU*min). Linearity range were performed in triplicates for each drug. Standard curves used to determine entrapment efficiencies of formulations. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were evaluated for both absorbance readings.

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Table 12.15 Results of HPLC analysis of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA- D). HPLC analysis conducted to determine entrapment efficiency of BSA-D. BSA-D were purified using vivaspin method and supernatant analyzed for free drug. Run Free DFMO in solution Free DFMO in Free DFMO in Free DFMO in Order using Area (mAU*min) solution using solution using solution using (mg) Area Area (mAU*min) Area (mAU*min) (mAU*min) (ug) (mg/mL) (ug/mL) 1 0.56305 563.05 0.0512 51.19 2 1.4561 1456.1 0.1213 121.34 3 3.31064 3310.64 0.2365 236.47 4 0.05345 53.45 0.0049 4.86 5 0.99583 995.83 0.0830 82.99 6 2.8105 2810.5 0.2008 200.75 7 0.01415 14.15 0.0013 1.29 8 0.93714 937.14 0.0781 78.10 9 2.783 2783 0.1988 198.79

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Table 12.16 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA-D). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. The highlighted formulation represents results within the goals of the experiment (PS <100nm, PdI < 0.3, %EE > 90%). Run zeta Entrapme Particl Polydispersi %BS Amount Amount Amount Orde potenti nt e Size ty Index A of of of r al (mV) Efficiency (nm) (PdI) (w/V) DFMO DFMO DFMO (%EE) in DI- entrappe entrappe entrappe H20 d in d in d in solution solution solution (mM) (mg) (ug) 1 -10 38.18 46 0.446 1 0.174 0.3478 347.80 2 -15 20.07 49 0.458 1 0.167 0.3656 365.60 3 -18 9.13 52 0.513 1 0.130 0.33276 332.76 4 -5 94.13 61 0.225 4 0.428 0.8574 857.40 5 -12 45.34 57 0.249 4 0.378 0.82587 825.87 6 -14 22.86 59 0.251 4 0.327 0.8329 832.90 7 -2 98.45 60 0.799 7 0.447 0.8967 896.70 8 -13 48.56 45 0.661 7 0.405 0.88456 884.56 9 -14 23.62 43 0.643 7 0.337 0.8604 860.40

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Figure 12.32 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO (BSA-D). 2 a) factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v b) starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. a) Particle size (pink), b) zeta potential (blue), c) c) polydispersity index (green), d) entrapment efficiency (yellow).

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Results

Phase 3: BSA-D-E Results Bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA-D-E)

Figure 12.34 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 3” nanocarrier development.

Table 12.17 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (BSA- D-E). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. Total volume of starting %BSA solution was 10mL. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. Run volume Final DFMO to Etoposide Final DFMO Final Order MeOH volume add from to add concentration in Etoposide to add for all 5mM from solution (mM) concentration 2mg/mL in solution (mL) (mL) stock in MeOH (mM) (mL) stock (mL)

1 10 11 1 1 0.455 0.309 2 12 12 2 1 0.833 0.283 3 14 14 4 1 1.429 0.243 4 10 11 1 1 0.455 0.309 5 12 12 2 1 0.833 0.283 6 14 14 4 1 1.429 .243 7 10 11 1 1 0.455 0.309 8 12 12 2 1 0.833 0.283 9 14 14 4 1 1.429 0.243

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1 0.5864 1.4722 2 1.4981 1.4406 3 3.3467 1.4624 4 0.0784 0.7457 5 1.0108 0.711 6 2.8189 0.7235 7 0.0450 0.6902 8 0.9674 0.7044 9 2.8189 0.6811

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Table 12.19 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA-D- E). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. Total volume of starting %BSA solution was 10mL. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. The highlighted formulation represents results within the goals of the experiment (PS <100nm, PdI < 0.3, %EE > 90%). Run zeta DFMO Etoposide Particl Polydispersit Amount Amount Orde potentia Entrapmen Entrapmen e Size y Index of DFMO of r l (mV) t Efficiency t Efficiency (nm) (PdI) entrappe Etoposide (%EE) (%EE) d in entrappe solution d in (mM) solution (mM) 1 -13 36 26 55 0.389 0.162 0.082 2 -12 18 28 54 0.398 0.148 0.079 3 -15 8 27 58 0.478 0.116 0.065 4 -8 91 63 68 0.267 0.415 0.194 5 -10 45 65 55 0.321 0.371 0.183 6 -13 23 64 63 0.278 0.323 0.155 7 -6 95 66 64 0.687 0.432 0.202 8 -12 47 65 51 0.643 0.391 0.183 9 -13 23 66 49 0.689 0.323 0.160

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Figure 12.35 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA-D-E). a) 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. b) These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. a) Particle size (pink), b) zeta potential (blue), c) polydispersity index c) (green), d) entrapment efficiency (yellow).

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Figure 12.36 Results of Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of bovine serum albumin nanocarriers loaded with DFMO and Etoposide (BSA- D-E). 2 factors: volume of desolvating agent (methanol) used and %BSA w/v starting concentration. Each factor has 3 levels; 10, 12, and 14mL for desolvating agent factor and 1%, 4%, and 7% for %BSA w/v starting concentration. These factors were deemed most influential on drug loading and entrapment efficiency based on previous experiments. Over-lay of all important BSA-D nanocarrier data: a) Particle size (pink), b) zeta potential (blue), c) polydispersity index (green), d) entrapment efficiency (yellow).

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Table 12.20 Reproducibility of Run Order #4 of BSA-D-E. Experiment was done in quadruplicates (n=4) with mean ± SD reported. Coefficient of Variance (CV) calculated for quadruplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%. Run zeta DFMO Etoposide Particl Polydispersit Amount Amount Order potent Entrapmen Entrapmen e Size y Index of DFMO of ial t Efficiency t Efficiency (nm) (PdI) entrappe Etoposide (mV) (%EE) (%EE) d in entrappe solution d in (mM) solution (mM) 4 -12 96 57 65 0.289 0.438 0.231 4 -15 94 53 59 0.301 0.429 0.240 4 -9 89 59 57 0.258 0.406 0.224 4 -8 91 63 68 0.267 0.415 0.194 Mea -11 93 58 62 0.279 0.422 0.222 n ± SD 3 3 4 5 0.020 0.014 0.020 %C 29 3 7 8 7 3 9 V

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Results

Phase 4: HNC-D-E Results Chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide (HNC-D-E)

Figure 12.37 Illustration of current nanocarrier formulation step. This section will focus on the results of “Phase 4” nanocarrier development.

Table 12.21 Chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide (HNC-D-E) will be developed using Run Order #4 (from BSA-D-E section). BSA-D-E nanocarriers will be coated with varying concentrations of chitosan then cross-linked with Tripolyphosphate (TPP). A molar ratio of 1:5.7 (CS:TPP) produced the smallest particle sizes (Phase 1, CS nanocarriers). These data will be implemented into chitosan coating experiments. Run volume Final DFMO to Etoposide Final DFMO Final Order MeOH volume add from to add concentration in Etoposide to add for all 5mM from solution (mM) concentration 2mg/mL in solution (mL) (mL) stock in MeOH (mM) (mL) stock (mL)

4 10 11 1 1 0.455 0.309

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Table 12.22 Experimental set-up of taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA-D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been added to each run. Run Chitosan (CS) Volume Particle Size Zeta Potential Polydispersity Order concentration of CS (nm) (mV) Index (mg/mL) solution (PdI) used (mL) 10 0.10 1 Data Table Data Table Data Table 11 0.20 1 12 0.30 1 13 0.10 3 14 0.20 3 15 0.30 3 16 0.10 6 17 0.20 6 18 0.30 6

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Table 12.23 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA-D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been added to each run. Run Chitosan (CS) Volume Particle Size Zeta Potential Polydispersity Order concentration of CS (nm) (mV) Index (mg/mL) solution (PdI) used (mL) 10 0.10 1 76 +3 0.321 11 0.20 1 88 +7 0.365 12 0.30 1 95 +9 0.376 13 0.10 3 85 +8 0.332 14 0.20 3 109 +16 0.379 15 0.30 3 127 +19 0.398 16 0.10 6 99 +12 0.487 17 0.20 6 118 +22 0.534 18 0.30 6 147 +28 0.586

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Figure 12.38 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: concentration of chitosan solution (mg/mL), and total volume of chitosan solution to a) add (mL). Each factor has 3 levels; 0.10, 0.20, and 0.30mg/mL for concentration of chitosan solution (mg/mL) factor, 1, 3, and 6mL total volume of chitosan solution to add (mL) factor. Total volume of starting BSA-D-E purified (via dialysis, Run Order #4) solution was 5mL per run. These factors were deemed b) most influential on particle size (nm) based on previous experiments. Chitosan solution is prepared in 1%v/v acetic acid and dissolved under constant stirring over-night. TPP is not a factor and will be maintained at 1:5.7 molar ratio (CS:TPP) once all of the chitosan solution have been c) added to each run. a) mean particle size, b) mean zeta potential, c) mean polydispersity index (PdI)

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Table 12.24 Reproducibility of Run Order #10 of HNC-D-E. Experiment was done in triplicates (n=3) with mean ± SD reported. Coefficient of Variance (CV) calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%. Run zeta DFMO Etoposide Particl Polydispersit Amount Amount Order potent Entrapmen Entrapmen e Size y Index of DFMO of ial t Efficiency t Efficiency (nm) (PdI) entrappe Etoposide (mV) (%EE) (%EE) d in entrappe solution d in (mM) solution (mM) 10 +9 N/A N/A 72 0.358 N/A N/A 10 +8 N/A N/A 65 0.326 N/A N/A 10 +3 N/A N/A 69 0.343 N/A N/A Mea +7 N/A N/A 69 0.342 N/A N/A n ± SD 3 N/A N/A 4 0.016 N/A N/A %C 48 N/A N/A 5 5 N/A N/A V

12.2.8.1 Quantification of amine groups present on run order #10 of chitosan coated bovine serum albumin loaded with DFMO and Etoposide (HNC-D-E) using Established TNBSA colorimetric assay Rationale Determiation of total amino acid groups present on the surface of nanocarriers will help to determine total amount of PEGylated molecules allowed to conjugate to nanocarrier surface. Data will allow for proper conjuation of PEG molecules for final nanocarrier formulations.

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International (VWR, Radnor, PA, USA) (Cat. No. 67-56-1) and used throughout the study. Boric acid (Cat. No. 10043-35-3), sodium hydroxide (Cat. No. 1310-73-2), and sodium chloride (Cat. No. 7647-14-5) of analytical grade were purchased from VWR International (VWR, Radnor, PA, USA).

Methods Sample preparation Samples were prepared for UV analysis in Biotek plate reader using the established TNBSA assay. Calibration standards prepared fresh in borate buffer (10.2) were aliquoted (800 µL each) into HPLC vials. Working TNBSA solution (0.025% w/v, 250 µL) were added into each calibration standard HPLC vial. The vials were placed in a 37°C water bathe and allowed to react for 2h.

Results

Table 12.25 Linearity study of chitosan coated BSA-D-E nanocarriers for the quantification of total amine groups present on HNC surface using TNBSA colorimetric assay in Biotek plate reader at 345nm. Linearity was found in a range of 100 to 500ug/mL with a linear regression value (R2) of 0.995. Varying concentrations of Chitosan (200uL each) treated with 800uL borate buffer 8.5, 250uL TNBSA stock solution (0.025% w/v) and allowed to react for 2h at 37°C. Samples were read in a 96- well plate within 10 minutes of reaction time. Run order #10 were purified via vivaspin method. HNC were re-suspended in DI-H2O and treated with same conditions as chitosan concentrations. Chitosan (CS) concentration Absorbance Amine groups present (treated with TNBSA) (@ 345) per mL (ug/mL) (1:1 molar ratio) (CS:TNBSA) 100 0.217 2.05 x 1017 200 0.272 4.11 x 1017 300 0.336 6.16 x 1017 400 0.398 8.21 x 1017 500 0.479 1.03 x 1018 Run Order #10 (Purified) 0.1979 1.54 x 1017

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Figure 12.40 Linearity study of chitosan coated BSA-D-E nanocarriers for the quantification of total amine groups present on HNC surface using TNBSA colorimetric assay in Biotek plate reader at 345nm. Linearity was found in a range of 100 to 500ug/mL with a linear regression value (R2) of 0.995. Varying concentrations of Chitosan (200uL each) treated with 800uL borate buffer 8.5, 250uL TNBSA stock solution (0.025% w/v) and allowed to react for 2h at 37°C. Samples were read in a 96- well plate within 10 minutes of reaction time. Run order #10 were purified via vivaspin method. HNC were re-suspended in DI-H2O and treated with same conditions as chitosan concentrations.

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Flow diagram 4. Formulation process. The following sections will focus on the highlighted (yellow) aspects of the HNC formulation:

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Phase 5: PEG-HNC-D-E PEGylated Chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide (PEG-HNC-D-E)

12.2.9 Quantification of free Polyethylene glycol (PEG) Rationale The conjugation of polyethylene glycol (PEG, MW 5000) to delivery systems has been widely reported to be optimal for increasing serum half-life and reduce clearance by the reticuloendothelial system 99. In addition, PEG (MW 5000) conjugation with delivery systems has been demonstrated to increase salt and serum stability including the prevention of aggregation of cationic nanocarriers 99. Due to the surface curvature attained with PEG coating, the accessibility of the surface to surrounding proteins and the net electrical charge of the PEGylated particles is significantly reduced 100, 101 Therefore, the PEGylation of cationic HNC will help to overcome in vivo aggregation issues.

Materials Mono-amine-carboxy-Polyethylene glycol (COOH-PEG-5000-NH2) having a molecular weight of 5000 (PEG-5000) were purchased from Sigma-Aldrich (CAS No. 80506-64-5) and stored at -20°C. Barium chloride (Cas No. 10361-37-2) of analytical grade, Iodine (Cas No. 7553-56-2) of ACS grade and Potassium Iodide (Cas No. 7681-11-0) of ACS grade were purchased from VWR International. Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA).

Methods Quantification of unbound PEG using Barium-Iodine Assay The free PEG was determined according to the procedure of Sims and Snape620 with some modifications. The barium chloride solution was prepared by dissolving the solute in 1 M hydrochloric acid to form a 5% (w/v) solution, while the iodine solution was prepared by dissolving 1.27 g iodine in 100 ml of 2% (w/v) potassium iodide. Samples were diluted with distilled water to final concentrations of PEG within the range of 0 to 7.5ug/ml. To a 800ul sample, 200ul barium chloride solution and 100ul iodine solution were added in turn. The reagent blank was prepared as above with distilled water instead of sample. Solutions

284 | Page were agitated to ensure adequate mixing. Color was allowed to develop for 15 min at room temperature, and then absorbance was read at 535 nm in the BioTek plate reader. Un-activated PEG, which has the same molecular weight with the free PEG, was used to prepare a standard curve. The concentration of free PEG was estimated from the standard curve (free PEG separated from HNC formulations via dialysis).

Results

Table 12.26 Linearity study of DFMO derivative (TNP-DFMO-TNP) quantified using Barium-Iodine assay in a Biotek plate reader at 535nm. Linearity was found in a range of 2 to 7.5ug/mL with a linear regression value (R2) of 0.996. Free PEG Absorbance Concentration (@ 535) (ug/mL) 2 0.172 3 0.212 4 0.259 5 0.304 6 0.363 7.5 0.441

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Phase 6: iRGD-PEG-HNC-D-E iRGD-PEGylated Chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide (iRGD-PEG-HNC-D-E)

Figure 12.43 Illustration of current nanocarrier formulation step. This section will focus on “Phase 6” of nanocarrier development.

12.2.10 Preparation of iRGD peptide conjugated PEGylated HNC-D-E (iRGD-PEG-HNC-D-E) Rationale The delivery of drugs directly to the tumors while sparing normal cells is essential to improve the outcome of NB therapy and to reduce adverse effects. Nanotechnology and combination therapy are two major fields that show great promise in the treatment of cancer. The delivery of drugs via nanocarriers helps to improve drug’s therapeutic effectiveness while reducing adverse side effects associated with high dosage by

286 | Page improving their pharmacokinetics. Taking advantage of molecular markers over-expressing on tumor tissues compared to normal cells, an “active” molecular marker targeted approach would be - beneficial for cancer therapy. These actively targeted nanocarriers would increase drug concentration at the tumor site, improving efficacy while further reducing chemo-resistance. The multidisciplinary approach may help to improve the overall efficacy in cancer therapy.

Tumor-specific tissue-penetrating peptides deliver drugs into extravascular tumor tissue by increasing tumor vascular permeability through interaction with neuropilin (NRP). Here we report that a prototypic tumor-penetrating peptide iRGD (amino acid sequence: CRGDKGPDC) potently inhibits spontaneous metastasis in mice. The anti-metastatic effect was mediated by the NRP-binding RXXK peptide motif (CendR motif), and not by the integrin-binding RGD motif. iRGD inhibited migration of tumor cells and caused chemorepulsionIn vitro in a CendR and NRP-1-dependent manner. The peptide induced dramatic collapse of cellular processes and partial cell detachment, resulting in the repellent activity. These effects were prominently displayed when the cells were seeded on fibronectin, suggesting a role of CendR in functional regulation of integrins. The anti-metastatic activity of iRGD may provide a significant additional benefit when this peptide is used for drug delivery to tumors.

Materials AMAS (N-α-maleimidoacet-oxysuccinimide ester) purchased from ThermoFisher (Cat. No. 22295) and is used as an amine-to-sulfhydryl cross-linker. EDC (1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide) and NHS (N-hydroxy succimide) reaagents were purchased from VWR international. Mono-amine-carboxy- Polyethylene glycol (COOH-PEG-5000-NH2) having a molecular weight of 5000 (PEG-5000) were purchased from Sigma-Aldrich (CAS No. 80506-64-5) and stored at -20°C. Barium chloride (Cas No. 10361-37-2) of analytical grade, Iodine (Cas No. 7553-56-2) of ACS grade and Potassium Iodide (Cas No. 7681-11-0) of ACS grade were purchased from VWR International. Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA).

Methods Fresh hybrid nanocarrier formulations loaded with both drugs were prepared (as described in HNC-D-E section) and purified using dialysis. Nanoparticles were stored at 4°C until ready for use. Mono-amine- carboxy Polyethylene glycol (COOH-PEG-NH2) mixed in a glass beaker with AMAS reagent, both dissolved in PBS 7.4 solution, at a 1 to 1 molar ratio. NHS ester groups of the AMAS reagent conjugates with the primary amine groups of the mono-amine carboxy PEG. The product will be carboxy-PEG-AMAS byproduct (COOH-PEG-AMAS) with stable amide bonds. No excess reagents should be present due to the

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1 to 1 molar ratio complete reaction of both products. The carboxy group of COOH-PEG-AMAS is then activated by EDC (0.55mM) and NHS (2mM) reagents. Purified HNC-D-E is then added to the solution of activated COOH-PEG-AMAS forming a bond between the amino-acid backbone of chitosan with the carboxy group of the PEG byproduct. During this step, activated COOH-PEG-AMAS and activated COOH-PEG (carboxy-PEG5000) are varied in different ratios (3 different mM ratios) to vary the amount of AMAS present on the HNC surface. Varying the amount of AMAS present on the surface of the HNC will allow for diffrenet degrees of iRGD peptide conjugation. The resulting byproduct will be AMAS- PEG-HNC-D-E (at 3 different ratios of AMAS on HNC surface) and purified via dialysis (remove excess EDC, NHS, unreacted COOH-PEG, and unreacted COOH-PEG-AMAS reagents). The final reaction will be the conjugation of iRGD to the AMAS found on the HNC surface. iRGD (with cysteine ends) is dissolved in PBS 7.4 and added into purified AMAS-PEG-HNC-D-E solution. The maleimide group of the AMAS will react with the sulfhydryl group found on the cysteine ends of the iRGD peptide. Since AMAS varied in 3 different formulations, the resulting product will have 3 varying degrees of iRGD conjugation on the HNC surface. These varying degrees of iRGD will be classified as low, medium, and high iRGD conjugated HNC and used for future experiments. The final product will be iRGD-PEG-HNC- D-E nanocarriers with 3 varying degrees of iRGD peptide. This product is purified via 14kD MWCO dialysis bag to remove excess reagents (iRGD peptide). The free reactants will be quantified (mainly PEG) to determine amount of PEG conjugated to the surface

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Flow Diagram 5. iRGD-PEG-HNC-D-E formulation procedures

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Results

Table 12.27 Reproducibility of Run Order #10 of HNC-D-E. Data was extracted from previous section, HNC-D-E. Formulation produced in a 50mL batch, purified via dialysis, and stored at 4°C to prevent drug release. This formulation will be separated into 3 separate batches (5mL each beaker) for iRGD peptide conjugation and PEGylation. Experiment was done in triplicates (n=3) with mean ± SD reported. Coefficient of Variance (CV) calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%. Run zeta DFMO Etoposide Particl Polydispersit Amount Amount Order potent Entrapmen Entrapmen e Size y Index of DFMO of ial t Efficiency t Efficiency (nm) (PdI) entrappe Etoposide (mV) (%EE) (%EE) d in entrappe solution d in (mM) solution (mM) 10 +9 N/A N/A 72 0.358 N/A N/A 10 +8 N/A N/A 65 0.326 N/A N/A 10 +3 N/A N/A 69 0.343 N/A N/A Mea +7 N/A N/A 69 0.342 N/A N/A n ± SD 3 N/A N/A 4 0.016 N/A N/A %C 48 N/A N/A 5 5 N/A N/A V

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Table 12.28 Taguchi orthogonal array design of experiment 32 (3 level, 2 factor) set-up for the development of PEGylated chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (PEG-HNC-D-E). 2 factors: total volume of carboxy-PEG (COOH-PEG, mL, 1mM), and total volume of AMAS-PEG-COOH (mL, 1mg/mL). Each factor has 3 levels; 0.5, 3, and 5mL for total volume of COOH-PEG factor, 0.5, 2.5, 5mL total volume of AMAS-PEG-COOH (mL) factor. Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run. Run Carboxy-PEG COOH-PEG-AMAS, Particle Size Zeta Polydispersity Order (COOH-PEG, 1mg/mL) (mL) (nm) Potential Index 1mg/mL) (mV) (PdI) (mL)

19 0.5 0.5 Data Table Data Table Data Table 20 3 0.5 21 5 0.5 22 0.5 2.5 23 3 2.5 24 5 2.5 25 0.5 5 26 3 5 27 5 5

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Run Carboxy-PEG COOH-PEG-AMAS, Particle Zeta Polydispersity Order (COOH-PEG, 1mg/mL) (mL) Size (nm) Potential Index 1mg/mL) (mL) (mV) (PdI)

19 0.5 0.5 75 +10 0.321 20 3 0.5 79 +12 0.365 21 5 0.5 89 +15 0.376 22 0.5 2.5 78 +9 0.332 23 3 2.5 84 +13 0.379 24 5 2.5 87 +19 0.398 25 0.5 5 85 +13 0.487 26 3 5 90 +17 0.534 27 5 5 89 +24 0.586

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Table 12.30 Results of Biotek reader analysis of taguchi orthogonal array design of experiment 32 (3 level, 2 factor) results for the development of chitosan coated bovine serum albumin nanocarriers loaded with DFMO and Etoposide drugs (HNC-D-E). 2 factors: total volume of carboxy-PEG (COOH-PEG, mL, 1mg/mL), and total volume of AMAS-PEG-COOH (mL, 1mg/mL). Each factor has 3 levels; 0.5, 3, and 5mL for total volume of COOH-PEG factor, 0.5, 2.5, 5mL total volume of AMAS-PEG-COOH (mL) factor. Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run. Biotek plate reader analysis conducted to determine unreacted COOH-PEG and unreacted COOH-PEG-AMAS of HNC-D-E using Barium- Iodine assay (@535nm). Barium-Iodine assay will not distinguish between COOH-PEG and COOH- PEG-AMAS molecules, therefore, total PEG is calculated. Absorbance area were collected from diluted solutions. A dilution factor of 1000 is calculated into Total unreacted PEG data. Run Total Unreacted Total Unreacted Amount of PEG Order COOH-PEG and COOH-PEG and mlecules bound to COOH-PEG-AMAS in COOH-PEG- HNC surface solution using AMAS in (per mL) Absorbance (535nm) solution using (dilution factor of 1000) Absorbance (535nm) (ug/mL) 19 0.091 497 6.06 x 1016 20 0.215 3023 5.74 x 1016 21 0.313 5021 5.77 x 1016 22 0.189 2487 6.18 x 1016 23 0.317 5008 5.92 x 1016 24 0.409 6947 6.65 x 1016 25 0.311 4968 6.41 x 1016 26 Too concentrated Too concentrated N/A 27 Too concentrated Too concentrated N/A

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12.2.11 Determination of Surface Bound Peptides per HNC using BCA protein assay Determination of surface bound iRGD peptides per HNC will be carried over for in vitro and flow- cytometry analysis. Total surface bound peptides will be quantified using BCA protein assay (unbound peptide). Peptides will be conjugated as previously described (section 12.2.12). Briefly, iRGD (with cysteine ends) is dissolved in PBS 7.4 and added into purified AMAS-PEG-HNC-D-E solution. The maleimide group of the AMAS reacts with the sulfhydryl group found on the cysteine ends of the iRGD peptide. Since AMAS is varied in 3 different formulations, the resulting product will have 3 varying degrees of iRGD conjugation on the HNC surface. These varying degrees of iRGD will be classified as low, medium, and high iRGD conjugated HNC and used for future experiments. The final product will be iRGD-PEG-HNC-D-E nanocarriers with 3 varying degrees of iRGD peptide.

Quantification of total PEG present in the previous section failed to quantify COOH-PEG and COOH-PEG- AMAS molecules separately. However, the total PEG molecules present on the surface of the HNC per mL were calculated at approximately 6.10 x 1016 molecules (mean average). These data give an insight as to how many PEG molecules are bound to run order #10 used throughout the PEGylation process. Adjusting the ratio of bound COOH-PEG to COOH-PEG-AMAS on the HNC surface, knowing the total possible PEG molecules bound to the surface, will allow for varying degrees of peptide conjugation to the surface of the HNC (peptide conjugates to AMAS).

Materials iRGD peptide purchased from Peptide 2.0 (Chantilly, VA) at 95% purity having an amino acid sequence of CRGDKGPDC. Peptide is stored at -20°C until ready for use. AMAS (N-α-maleimidoacet- oxysuccinimide ester) purchased from ThermoFisher (Cat. No. 22295) and is used as an amine-to- sulfhydryl cross-linker. EDC (1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide) and NHS (N-hydroxy succimide) reaagents were purchased from VWR international. Mono-amine-carboxy-Polyethylene glycol (COOH-PEG-5000-NH2) having a molecular weight of 5000 (PEG-5000) were purchased from Sigma- Aldrich (CAS No. 80506-64-5) and stored at -20°C. Barium chloride (Cas No. 10361-37-2) of analytical grade, Iodine (Cas No. 7553-56-2) of ACS grade and Potassium Iodide (Cas No. 7681-11-0) of ACS grade were purchased from VWR International. Ultrapure distilled deionized water was purified by a Milli-Q apparatus (Millipore, Bedford, MA, USA).

294 | Page carboxy Polyethylene glycol (COOH-PEG-NH2) mixed in a glass beaker with AMAS reagent, both dissolved in PBS 7.4 solution, at a 1 to 1 molar ratio. NHS ester groups of the AMAS reagent conjugates with the primary amine groups of the mono-amine carboxy PEG. The product will be carboxy-PEG-AMAS byproduct (COOH-PEG-AMAS) with stable amide bonds. No excess reagents should be present due to the 1 to 1 molar ratio complete reaction of both products. The carboxy group of COOH-PEG-AMAS is then activated by EDC (0.55mM) and NHS (2mM) reagents. Purified HNC-D-E is then added to the solution of activated COOH-PEG-AMAS forming a bond between the amino-acid backbone of chitosan with the carboxy group of the PEG byproduct. During this step, activated COOH-PEG-AMAS and activated COOH-PEG (carboxy-PEG5000) are varied in different ratios (3 different ratios) to vary the amount of AMAS present on the HNC surface. Varying the amount of AMAS present on the surface of the HNC will allow for diffrenet degrees of iRGD peptide conjugation. The resulting byproduct will be AMAS-PEG- HNC-D-E (at 3 different ratios of AMAS on HNC surface) and purified via dialysis (remove excess EDC, NHS, unreacted COOH-PEG, and unreacted COOH-PEG-AMAS reagents). The final reaction will be the conjugation of iRGD to the AMAS found on the HNC surface. iRGD (with cysteine ends) is dissolved in PBS 7.4 and added into purified AMAS-PEG-HNC-D-E solution. The maleimide group of the AMAS will react with the sulfhydryl group found on the cysteine ends of the iRGD peptide. Since AMAS varied in 3 different formulations, the resulting product will have 3 varying degrees of iRGD conjugation on the HNC surface. These varying degrees of iRGD will be classified as low, medium, and high iRGD conjugated HNC and used for future experiments. The final product will be iRGD-PEG-HNC-D-E nanocarriers with 3 varying degrees of iRGD peptide. This product is purified via 14kD MWCO dialysis bag to remove excess reagents (iRGD peptide). The free reactants will be quantified (mainly PEG) to determine amount of PEG conjugated to the surface

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Table 12.31 Expermental set-up of Biotek reader analysis of carboxy-PEG (COOH-PEG, mL, 1mg/mL), and total volume of AMAS-PEG-COOH (mL, 1mg/mL) estimation based-off previously obtained data (approximately 6.10 x 1016 molecules of PEG binds per mL of run order #10 formulation). The total volume of COOH-PEG (mL) and total volume of AMAS-PEG-COOH (mL) will vary in 3 different ratios (low, medium, high) to vary total AMAS present on surface of HNC (iRGD peptide conjugates to AMAS, varying its ratio wil give varying degrees of iRGD peptide on HNC surface). Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run. Biotek plate reader analysis conducted to determine total unreacted COOH-PEG and unreacted COOH-PEG-AMAS of HNC-D-E using Barium-Iodine assay (@535nm). Barium-Iodine assay will not distinguish between COOH-PEG and COOH-PEG-AMAS molecules, therefore, total PEG is calculated. Absorbance area were collected from diluted solutions. A dilution factor of 1000 is calculated into Total unreacted PEG data. iRGD peptide will be quantified at 562nm using BCA protein assay. Run Etimation Etimation Total Total iRGD Amount of Amount Order of total of Total COOH- COOH- peptide PEG of PEG COOH- COOH- PEG PEG- added after mlecules mlecules PEG to be PEG- needed AMAS PEGylation bound to bound bound to AMAS to (1mg/mL needed (100ug/mL) HNC to HNC HNC be bound stock (1mg/mL (mL) surface surface surface to HNC solution) stock (per mL) (per (per mL) surface (mL) solution) mL) (per mL) (mL) 28 (Low ~5.0 x 1016 ~1.0 x 0.415 0.083 1 Data Table Data AMAS) 1016 Table 29 ~3.0 x 1016 ~3.0 x 0.250 0.250 1 (Med. 1016 AMAS) 30 (High ~1.0 x 1016 ~5.0 x 0.083 0.415 1 AMAS) 1016

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Table 12.32 Linearity study of iRGD peptide quantified using BCA protein assay in a Biotek plate reader at 562nm. Linearity was found in a range of 20 to 60ug/mL with a linear regression value (R2) of 0.996. Free iRGD peptide Absorbance Concentration (@ 562) (ug/mL) 20 0.162 30 0.203 40 0.248 50 0.289 60 0.340

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Table 12.33 Results of carboxy-PEG (COOH-PEG, mL, 1mg/mL), and total volume of AMAS-PEG- COOH (mL, 1mg/mL) estimation based-off previously obtained data (approximately 6.10 x 1016 molecules of PEG binds per mL of run order #10 formulation). The total volume of COOH-PEG (mL) and total volume of AMAS-PEG-COOH (mL) will vary in 3 different ratios (low, medium, high) to vary total AMAS present on surface of HNC (iRGD peptide conjugates to AMAS, varying its ratio wil give varying degrees of iRGD peptide on HNC surface). Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run. Biotek plate reader analysis conducted to determine total unreacted COOH-PEG and unreacted COOH-PEG- AMAS of HNC-D-E using Barium-Iodine assay (@535nm). Barium-Iodine assay will not distinguish between COOH-PEG and COOH-PEG-AMAS molecules, therefore, total PEG is calculated. Absorbance area were collected from diluted solutions. A dilution factor of 1000 is calculated into Total unreacted PEG data. iRGD peptide will be quantified at 562nm using BCA protein assay. Run Etimatio Etimatio Total Total iRGD Amount Theorectica Order n of total n of Total COOH- COOH- peptide of PEG l amount of COOH- COOH- PEG PEG- added molecules iRGD PEG to PEG- needed AMAS after bound to peptide be bound AMAS to (1mg/m needed PEGylatio HNC molecules to HNC be bound L stock (1mg/m n surface bound to surface to HNC solution) L stock (100ug/mL (per mL) HNC (per mL) surface (mL) solution) ) (mL) surface (per mL) (mL) (per mL) 28 5.0 x 1016 1.0 x 1016 0.415 0.083 1 5.87 x 1016 ~1.0 x 1016 (Low AMAS ) 29 3.0 x 1016 3.0 x 1016 0.250 0.250 1 5.92 x 1016 ~3.0 x 1016 (Med. AMAS ) 30 1.0 x 1016 5.0 x 1016 0.083 0.415 1 5.96 x 1016 ~5.0 x 1016 (High AMAS )

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Table 12.34 Results of carboxy-PEG (COOH-PEG, mL, 1mg/mL), and total volume of AMAS-PEG- COOH (mL, 1mg/mL) estimation based-off previously obtained data (approximately 6.10 x 1016 molecules of PEG binds per mL of run order #10 formulation). The total volume of COOH-PEG (mL) and total volume of AMAS-PEG-COOH (mL) will vary in 3 different ratios (low, medium, high) to vary total AMAS present on surface of HNC (iRGD peptide conjugates to AMAS, varying its ratio wil give varying degrees of iRGD peptide on HNC surface). Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run. Biotek plate reader analysis conducted to determine total unreacted COOH-PEG and unreacted COOH-PEG- AMAS of HNC-D-E using Barium-Iodine assay (@535nm). Barium-Iodine assay will not distinguish between COOH-PEG and COOH-PEG-AMAS molecules, therefore, total PEG is calculated. Absorbance area were collected from diluted solutions. A dilution factor of 1000 is calculated into Total unreacted PEG data. iRGD peptide will be quantified at 562nm using BCA protein assay. Run Order iRGD Amount Theorectical BCA Amount of peptide of PEG amount of iRGD protein iRGD added after molecules peptide molecules analysis of peptide PEGylation bound to bound to HNC Free iRGD molecules (100ug/mL) HNC surface peptide bound to (mL) surface (per mL) molecules HNC (per mL) (per mL) surface (absorbance (per mL) @ 562nm) 28 (Low AMAS) 1 5.87 x 1016 ~1.0 x 1016 0.467 1.02 x 1016 29 (Med. AMAS) 1 5.92 x 1016 ~3.0 x 1016 0.322 2.98 x 1016 30 (High AMAS) 1 5.96 x 1016 ~5.0 x 1016 0.176 4.95 x 1016

12.2.12 Optimization of iRGD peptides on HNC surface for in vitro internalization Determination of surface bound iRGD peptides per HNC will be carried over for in vitro and flow- cytometry analysis. Total surface bound peptides will be quantified using BCA protein assay (unbound peptide). Peptides will be conjugated as previously described (section 12.2.12). Briefly, iRGD (with cysteine ends) is dissolved in PBS 7.4 and added into purified AMAS-PEG-HNC-D-E solution. The maleimide group of the AMAS reacts with the sulfhydryl group found on the cysteine ends of the iRGD

299 | Page peptide. Since AMAS is varied in 3 different formulations, the resulting product will have 3 varying degrees of iRGD conjugation on the HNC surface. These varying degrees of iRGD will be classified as low, medium, and high iRGD conjugated HNC and used for future experiments. The final product will be iRGD-PEG-HNC-D-E nanocarriers with 3 varying degrees of iRGD peptide.

Methods Fresh hybrid nanocarrier formulations loaded with both drugs were prepared (as described in HNC-D-E section, run order #10 used) purified using dialysis and stored at 4°C until ready to be used. Mono-amine- carboxy Polyethylene glycol (COOH-PEG-NH2) mixed in a glass beaker with AMAS reagent, both dissolved in PBS 7.4 solution, at a 1 to 1 molar ratio. NHS ester groups of the AMAS reagent conjugates with the primary amine groups of the mono-amine carboxy PEG. The product will be carboxy-PEG-AMAS byproduct (COOH-PEG-AMAS) with stable amide bonds. No excess reagents should be present due to the 1 to 1 molar ratio complete reaction of both products. The carboxy group of COOH-PEG-AMAS is then activated by EDC (0.55mM) and NHS (2mM) reagents. Purified HNC-D-E is then added to the solution

300 | Page of activated COOH-PEG-AMAS forming a bond between the amino-acid backbone of chitosan with the carboxy group of the PEG byproduct. During this step, activated COOH-PEG-AMAS and activated COOH-PEG (carboxy-PEG5000) are varied in different ratios (3 different ratios) to vary the amount of AMAS present on the HNC surface. Varying the amount of AMAS present on the surface of the HNC will allow for diffrenet degrees of iRGD peptide conjugation. The resulting byproduct will be AMAS-PEG- HNC-D-E (at 3 different ratios of AMAS on HNC surface) and purified via dialysis (remove excess EDC, NHS, unreacted COOH-PEG, and unreacted COOH-PEG-AMAS reagents). The final reaction will be the conjugation of iRGD to the AMAS found on the HNC surface. iRGD (with cysteine ends) is dissolved in PBS 7.4 and added into purified AMAS-PEG-HNC-D-E solution. The maleimide group of the AMAS will react with the sulfhydryl group found on the cysteine ends of the iRGD peptide. Since AMAS varied in 3 different formulations, the resulting product will have 3 varying degrees of iRGD conjugation on the HNC surface. These varying degrees of iRGD will be classified as low, medium, and high iRGD conjugated HNC and used for future experiments. The final product will be iRGD-PEG-HNC-D-E nanocarriers with 3 varying degrees of iRGD peptide. This product is purified via 14kD MWCO dialysis bag to remove excess reagents (iRGD peptide). The free reactants will be quantified (mainly PEG) to determine amount of PEG conjugated to the surface.

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Results

Table 12.35a Results of carboxy-PEG (COOH-PEG, mL, 1mg/mL), and total volume of AMAS-PEG- COOH (mL, 1mg/mL) estimation based-off previously obtained data (approximately 6.10 x 1016 molecules of PEG binds per mL of run order #10 formulation). The total volume of COOH-PEG (mL) and total volume of AMAS-PEG-COOH (mL) will vary in 3 different ratios (low, medium, high) to vary total AMAS present on surface of HNC (iRGD peptide conjugates to AMAS, varying its ratio wil give varying degrees of iRGD peptide on HNC surface). Total volume of starting HNC-D-E purified (via dialysis, Run Order #10, section HNC-D-E) solution was 5mL per run. Biotek plate reader analysis conducted to determine total unreacted COOH-PEG and unreacted COOH-PEG- AMAS of HNC-D-E using Barium-Iodine assay (@535nm). Barium-Iodine assay will not distinguish between COOH-PEG and COOH-PEG-AMAS molecules, therefore, total PEG is calculated. Absorbance area were collected from diluted solutions. A dilution factor of 1000 is calculated into Total unreacted PEG data. iRGD peptide will be quantified at 562nm using BCA protein assay. Run Order iRGD Amount Theorectical BCA Amount of peptide of PEG amount of iRGD protein iRGD added after molecules peptide molecules analysis of peptide PEGylation bound to bound to HNC Free iRGD molecules (100ug/mL) HNC surface peptide bound to (mL) surface (per mL) molecules HNC (per mL) (per mL) surface (absorbance (per mL) @ 562nm) 28 (Low AMAS) 1 5.87 x 1016 ~1.0 x 1016 0.467 1.02 x 1016 29 (Med. AMAS) 1 5.92 x 1016 ~3.0 x 1016 0.322 2.98 x 1016 30 (High AMAS) 1 5.96 x 1016 ~5.0 x 1016 0.176 4.95 x 1016 #7 New Formula 1 5.78 x 1016 ~6.0 x 1016 0.165 5.98 x 1016 #8 New Formula 1 5.89 x 1016 ~7.0 x 1016 0.155 6.89 x 1016 #9 New Formula 1 5.86 x 1016 ~7.5 x 1016 0.143 7.34 x 1016 #10 New Formula 1 5.80 x 1016 ~8.0 x 1016 0.131 7.97 x 1016 #11 New Formula 1 5.75 x 1016 ~10 x 1016 0.102 9.87 x 1016

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Figure 12.46a Flow cytometry analysis of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. Overlay of controls and HNC formulations: Be2c cells alone (yellow), hybrid nanocarrier loaded with FITC (green, HNC-FITC), iRGD saturated Be2c cells followed by treatment with High iRGD-HNC (pink), Low conjugated iRGD-PEG-HNC (blue), Medium conjugated iRGD-PEG-HNC (black), and High conjugated iRGD-PEG-HNC (red).

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Fluorescence Intensity Mean (530nm Filter) Fluorescence

Label Trial 1 Trial 2 Trial 3 Intensity ± SD SK-N-Be(2)c Cells alone 7,308 6,799 6,334 6,814 ± 487 Destroyed SK-N-Be(2)c Cells 4,277 4,289 5,101 4,556 ± 472

FITC ONLY treated 421,811 399,384 378,831 400,009 ± 21,496 HNC-FITC treated 15,268 15,610 15,294 15,391 ± 190 iRGD Saturated, then High iRGD- 20,087 20,260 18,182 19,510 ± 1,153

Controls PEG-HNC treated Low conjugated iRGD-PEG-HNC- 50,394 55,284 51,375 52,351 ± 2,587 FITC Medium conjugated iRGD-PEG-HNC- 94,578 95,801 99,323 96,567 ± 2,464 FITC High conjugated iRGD-PEG-HNC- 234,006 248,824 222,547 235,126 ± 13,174 FITC #7 New formula (5.98 x 1016 peptides) 256,976 260,543 258,765 258,761 ± 1,783 #8 New formula (6.89 x 1016) 290,546 300,760 295,879 295,728 ± 5,108 #9 New formula (7.34 x 1016) 289,089 300,768 296,780 295,546 ± 5,936 #10 New formula (7.97 x 1016) 290,768 294,567 298,768 294,701 ± 4,001 #11 New formula (9.87 x 1016) 293,476 298,567 294,587 295,543 ± 2,676

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Table 12.35c Normalized flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell-lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N-Be(2)c cells alone.

Normalized Fluorescence Mean Intensity (530nm Filter) Fluorescence

Label Trial 1 Trial 2 Trial 3 Intensity ± SD SK-N-Be(2)c Cells alone 1.072 0.997 0.929 0.999 ± 0.071 Destroyed SK-N-Be(2)c Cells 0.627 0.629 0.748 0.668 ± 0.069 FITC ONLY treated 61.904 58.612 55.596 58.703 ± 3.154 HNC-FITC treated 2.241 2.291 2.244 2.244 ± 0.027 iRGD Saturated, then High iRGD- 2.947 2.973 2.668 2.668 ± 0.169

Controls HNC treated Low conjugated iRGD-PEG-HNC- 7.395 8.113 7.539 7.682 ± 0.379 FITC Medium conjugated iRGD-PEG-HNC- 13.879 14.059 14.576 14.171 ± 0.361 PEG High conjugated iRGD-PEG-HNC- 34.341 36.516 32.660 34.505 ± 1.933 FITC #7 New formula (5.98 x 1016) 37.713 38.236 37.975 37.975 ± 0.261 #8 New formula (6.89 x 1016) 42.640 44.139 43.422 43.400 ± 0.750 #9 New formula (7.34 x 1016) 42.426 44.140 43.554 43.373 ± 0.871 #10 New formula (7.97 x 1016) 42.672 43.230 43.846 43.249 ± 0.587 #11 New formula (9.87 x 1016) 43.070 43.817 43.233 43.371 ± 0.392

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Figure 12.46b Normalized flow cytometry results of HNC formulations against SK-N-Be(2)c cell- lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Graphpad Prism 5 used for plotting of raw data. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N-Be(2)c cells alone. **(p-value ≤ 0.05) shown to statistically significant. Control against #5 (high conjugated iRGD-HNC-FITC) shown to be statistically significant (p-value = 0.0011) and #5 against #7 thru #11 also statistically significant (p-value = 0.0038)

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12.3 EVALUATION METHODS OF PEG-HNC-D-E FORMULATIONS The aim of this chapter is to evaluate the final nanocarrier formulation; PEGylated hybrid nanocarriers loaded with DFMO and Etoposide (PEG-HNC-D-E). Evaluation includes: stability of particle size, charge and dispersal in various biological media.

12.3.1 Stability of PEG-HNC-D-E in biological media and phosphate buffers Rationale The objective of this study is to investigate the effect of various biological media and phosphate buffers on the changes in particle size, zeta potential and polydispersity index (PdI) on PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E). This study will determine the stability of the final formulation and its potential behavior in future In vitro and in vivo studies.

Materials Freshly prepared nanocarrier formulation (PEG-HNC-D-E) were prepared and stored at 4°C in double distilled deionized water (experimental solution, Millipore, Bedford, MA, USA) before stability study. Biological media and phosphate buffers were prepared and stored at 4°C and room temperature, respectively. Fetal bovine serum (FBS, ThermoFisher, Waltman, MA, USA) diluted in ultrapure DI-H2O for a final concentration of 10% w/v and store at 4°C. Phosphate buffered saline (PBS) and 0.9% sodium chloride (normal saline) were prepared according to established protocols and stored at room temperature.

Methods 100uL of final nanocarrier formulation were added to 900uL of media in centrifuge tube, with the exception of 10% FBS media. 100uL of formulation were added to 100uL of FBS then place in 800uL of DI-H2O (FBS needed to be diluted before analysis in particle sizer). Each mixture was placed in capillary tube and allowed to settle for 10 minutes. Mixtures were analyzed in Nicomp 380 zls particle sizer for particle size, zeta potential and polydispersity index (PdI) at various time points.

Results

The following data represents stability studies in various biological media and phosphate buffers. Each table and figure is described in detail. A final discussion of this investigation is found at the end of these

307 | Page data. Triplicates were conducted for each experiment with a coefficient of variance (CV) of less than 5% showing the degree of variation from one data series to another is acceptable.

Table 12.35 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC- D-E) in DI-H20. 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table 12.39 Media DI-H20 Particle size Polydispersity Index (nm) Zeta Potential (mV) (PdI) Time Trial Trial Trial Trial Trial Trial Trial Trial Trial (hour) 1 2 3 1 2 3 1 2 3 0 88 88 85 15 22 12 0.323 0.345 0.321 1 92 87 86 12 18 10 0.326 0.358 0.336 8 87 86 84 11 15 13 0.368 0.389 0.375 24 86 89 87 10 8 7 0.421 0.440 0.415 48 82 90 91 8 11 12 0.450 0.462 0.454 72 89 92 90 9 8 7 0.460 0.469 0.455 96 93 94 93 6 9 7 0.451 0.457 0.435 120 96 91 92 7 5 9 0.438 0.445 0.418

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Figure 12.46 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D-E) in DI-H20. 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV a) calculated in a Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

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Table 12.36 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC- D-E) in PBS 7.4. 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table 12.39 Media PBS 7.4 Particle size Polydispersity Index (nm) Zeta Potential (mV) (PdI) Time Trial Trial Trial Trial Trial Trial Trial Trial Trial (hour) 1 2 3 1 2 3 1 2 3 0 93 90 89 5 9 11 0.321 0.352 0.342 1 95 92 91 3 6 5 0.317 0.345 0.341 8 91 94 94 4 7 3 0.365 0.347 0.321 24 90 96 93 6 10 8 0.355 0.354 0.324 48 87 89 87 8 12 11 0.345 0.323 0.290 72 88 90 86 2 5 6 0.328 0.336 0.324 96 86 91 84 4 6 9 0.301 0.341 0.311 120 84 90 89 5 8 4 0.295 0.326 0.321

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Figure 12.47 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D-E) in PBS 7.4. 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV a) calculated in a Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

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Table 12.37 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC- D-E) in 0.9% NaCl (normal saline). 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table 12.39 Media 0.9% NaCl Particle size Polydispersity Index (nm) Zeta Potential (mV) (PdI) Time Trial Trial Trial Trial Trial Trial Trial Trial Trial (hour) 1 2 1 2 3 3 1 2 3 0 88 87 86 25 22 20 0.523 0.562 0.512 1 91 91 89 28 26 25 0.535 0.545 0.531 8 93 94 90 30 31 29 0.521 0.560 0.518 24 95 95 92 27 28 26 0.510 0.542 0.524 48 96 93 93 22 29 25 0.527 0.562 0.542 72 95 96 94 26 20 23 0.514 0.546 0.523 96 94 94 96 18 16 15 0.510 0.561 0.541 120 96 91 97 24 22 26 0.522 0.514 0.519

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Figure 12.48 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D-E) in 0.9% NaCl (normal saline). 100uL of final PEG-HNC-D-E formulation suspended in 900uL of media. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % a) CV calculated in Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

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Table 12.38 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC- D-E) in 10% w/v FBS. 100uL of final PEG-HNC-D-E formulation suspended in 100uL of media and 800uL of DI-H2O to further dilute FBS. Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table 12.39 Media 10% FBS Particle size Polydispersity Index (nm) Zeta Potential (mV) (PdI) Time Trial Trial Trial Trial Trial Trial Trial Trial Trial (hour) 1 2 3 1 2 3 1 2 3 0 88 88 87 2 1 3 0.589 0.612 0.622 1 96 98 95 -5 -8 4 0.614 0.623 0.645 8 98 106 98 -8 -5 2 0.620 0.649 0.623 24 102 108 104 -6 -7 -5 0.589 0.596 0.614 48 105 104 109 1 -2 -8 0.615 0.580 0.591 72 106 106 110 -4 -8 -6 0.624 0.594 0.562 96 104 105 109 -9 -10 -9 0.610 0.602 0.587 120 103 107 108 -3 -8 -5 0.597 0.615 0.589

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Figures 12.49 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D-E) in 10% w/v FBS. 100uL of final PEG-HNC-D-E formulation suspended in 100uL of media and 800uL of DI-H2O to further dilute FBS. Sample measured in Nicomp 380 zls particle sizer at 10 a) minutes. Experiment done in triplicates with mean ± SD and % CV calculated in Table 12.39 a) mean particle size ± SD, b) mean zeta potential ± SD, and c) mean polydispersity index (PdI) ± SD plotted.

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Table 12.39 Stability data of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG- HNC-D-E) various media: DI-H2O, PBS 7.4, 0.9% NaCl, and 10% w/v FBS. 100uL of final PEG- HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD reported. Coefficient of Variance (CV) calculated for triplicate experiments. Experimental conditions of the developed method show comparable data as depicted with a CV < 5%. Ti me Mean Particle ± % Mean Zeta ± % Mean Polydispersity ± % (h) Size (nm) SD CV Potential (mV) SD CV Index (PdI) SD CV Media Media

0 87.00 1.7 1.9 16.33 5.1 31.4 0.33 0.0 4.0 3 9 3 2 1 4 1 88.33 3.2 3.6 13.33 4.1 31.2 0.34 0.0 4.8 1 4 6 2 2 1 8 85.67 1.5 1.7 13.00 2.0 15.3 0.38 0.0 2.8 3 8 0 8 1 3 24 87.33 1.5 1.7 8.33 1.5 18.3 0.43 0.0 3.0 3 5 3 3 1 7 48 87.67 4.9 5.6 10.33 2.0 20.1 0.46 0.0 1.3 3 3 8 5 1 4 72 90.33 1.5 1.6 8.00 1.0 12.5 0.46 0.0 1.5 3 9 0 0 1 4 96 93.33 0.5 0.6 7.33 1.5 20.8 0.45 0.0 2.5 8 2 3 3 1 4 12 93.00 2.6 2.8 7.00 2.0 28.5 0.43 0.0 3.2 DI-H2O DI-H2O 0 5 4 0 7 1 3 0 90.67 2.0 2.3 8.33 3.0 36.6 0.34 0.0 4.6 8 0 6 6 2 8 1 92.67 2.0 2.2 4.67 1.5 32.7 0.33 0.0 4.5 8 5 3 3 2 3 8 93.00 1.7 1.8 4.67 2.0 44.6 0.34 0.0 6.4 3 6 8 1 2 2 24 93.00 3.0 3.2 8.00 2.0 25.0 0.34 0.0 5.1 0 3 0 0 2 2 48 87.67 1.1 1.3 10.33 2.0 20.1 0.32 0.0 8.6 5 2 8 5 3 7 72 88.00 2.0 2.2 4.33 2.0 48.0 0.33 0.0 1.8 0 7 8 4 1 6 96 87.00 3.6 4.1 6.33 2.5 39.7 0.32 0.0 6.5 1 4 2 4 2 5 12 87.67 3.2 3.6 5.67 2.0 36.7 0.31 0.0 5.3 PBS 7.4 PBS 0 1 7 8 4 2 0 0 87.00 1.0 1.1 22.33 2.5 11.2 0.53 0.0 4.9 0 5 2 7 3 4 1 90.33 1.1 1.2 26.33 1.5 5.80 0.54 0.0 1.3 5 8 3 1 4 8 92.33 2.0 2.2 30.00 1.0 3.33 0.53 0.0 4.4 8 5 0 2 0 24 94.00 1.7 1.8 27.00 1.0 3.70 0.53 0.0 3.0 0.9% NaCl 0.9% NaCl 3 4 0 2 5

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48 94.00 1.7 1.8 25.33 3.5 13.8 0.54 0.0 3.2 3 4 1 6 2 3 72 95.00 1.0 1.0 23.00 3.0 13.0 0.53 0.0 3.1 0 5 0 4 2 3 96 94.67 1.1 1.2 16.33 1.5 9.35 0.54 0.0 4.7 5 2 3 3 8 12 94.67 3.2 3.4 24.00 2.0 8.33 0.52 0.0 0.7 0 1 0 0 0 8 0 87.67 0.5 0.6 2.00 1.0 50.0 0.61 0.0 2.7 8 6 0 0 2 8 1 96.33 1.5 1.5 -3.00 6.2 - 0.63 0.0 2.5 3 9 4 208. 2 4 17 8 100.67 4.6 4.5 -3.67 5.1 - 0.63 0.0 2.5 2 9 3 139. 2 3 95 24 104.67 3.0 2.9 -6.00 1.0 - 0.60 0.0 2.1 6 2 0 16.6 1 5 7 48 106.00 2.6 2.5 -3.00 4.5 - 0.60 0.0 3.0 5 0 8 152. 2 1 75 72 107.33 2.3 2.1 -6.00 2.0 - 0.59 0.0 5.2 1 5 0 33.3 3 3 3 96 106.00 2.6 2.5 -9.33 0.5 - 0.60 0.0 1.9 5 0 8 6.19 1 5 12 106.00 2.6 2.5 -5.33 2.5 - 0.60 0.0 2.2 0 5 0 2 47.1 1 2 10% w/v FBS 10% w/v 9

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Figure 12.50 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG- HNC-D-E) in various media (DI-H2O, PBS 7.4, 0.9% NaCl and 10% FBS). 100uL of final PEG- HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table X. Mean particle size ± SD plotted.

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Figure 12.51 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG- HNC-D-E) in various media (DI-H2O, PBS 7.4, 0.9% NaCl and 10% FBS). 100uL of final PEG- HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table X. Mean zeta potential ± SD plotted.

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Figure 12.52 Stability of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG- HNC-D-E) in various media (DI-H2O, PBS 7.4, 0.9% NaCl and 10% FBS). 100uL of final PEG- HNC-D-E formulation suspended in 900uL of respective media, with the exception of 10% FBS, which was diluted further (100uL sample + 100uL 10% FBS + 800uL DI-H2O). Sample measured in Nicomp 380 zls particle sizer at 10 minutes. Experiment done in triplicates with mean ± SD and % CV calculated in a Table X. Mean polydispersity index (PdI) ± SD plotted.

Discussion

12.3.2 In vitro Release Profiles of PEG-HNC-D-E Formulations in various phosphate buffers Rationale As with most dosage forms, product quality and performance may be verified through several in vivo and/or in vitro experiments. Of these, drug release kinetics provides critical information about dosage form behavior and is a key parameter used to assess product safety and efficacy. Due to the expense, time, labor, and need for human subjects/animals when performing in vitro measurements of drug release kinetics, in

320 | Page vitro release is gaining greater attention as a surrogate test for product performance. Indeed, in vitro release testing is commonly used as a predictor of in vivo behavior, historically with traditional dosage forms like capsules and tablets (i.e., dissolution), and more recently with novel dosage forms like injectable biodegradable microspheres and implants570. Generally, in vitro release studies are performed at 37°C (physiological temperature), though in some instances testing at elevated temperatures has been explored to characterize drug release from a variety of dosage forms 42.

Without exception, in vitro release testing is an important analytical tool that is used to investigate and establish product behavior during the various stages of drug product development, as well as life cycle management. When designed appropriately, an in vitro release profile can reveal fundamental information on the dosage form and its behavior, as well as provide details on the release mechanism and kinetics, enabling a rational and scientific approach to drug product development. Understandably, for complex dosage forms like nanoparticulates, in vitro release testing assumes greater significance.

Materials PEG-HNC-D-E formulations were prepared as described earlier. Purified nanocarriers were analyzed via HPLC to determine total amount of drug, DFMO and Etoposide, contained. Formulations were stored at 4°C to prevent further release of entrapped drugs. Formulations were used within one week and excess formulation discarded. Release media were prepared fresh and stored at room temperature. 1.5mL HPLC glass vials and 20mL glass vials were used to perform release studies. Formulations and release media were placed in HPLC vials, a 50kDa dialysis membrane (Pierce, Rockford, IL) is then placed over the vial and secured with an open lid. The HPLC vial is inverted into 20mL glass vial containing PBS solution (sink compartment). Magnetic stir bar is placed in sink compartment and set at 100rpm. All studies were performed at 37°C at pre-determined time points. Sample were collected in 1mL Eppendorf centrifuge tubes for analysis via HPLC.

Methods Drug release studies of PEG-HNC-D-E formulations were conducted using a previously described technique 608. To measure the release profile, nanocarrier solutions at a concentration of 11.8 and 17ug/150uL (DFMO and Etoposide, respectively) were suspended in respective release media in 1.5mL HPLC glass vials with molecular cutoff of 50 kDa (Pierce, Rockford, IL) placed over the surface of the HPLC vial and secured with a lid. The formulation was subjected to dialysis against 15mL of release phosphate buffer saline (PBS 7.4) with gentle stirring (100rpm) at 37°C. PBS was changed periodically during the process. At pre-determined times, 200μL of solution was removed from the PBS solution (sink

321 | Page compartment) and fresh PBS were added. Extracted samples were derivatized with established HPLC- TNBSA assay and analyzed via HPLC as previously described. Absorbance area (mAU*min) were obtained from each sample and dug release was calculated using linear standard curves previously obtained. Total drug release was calculated and plotted for each drug and each release media separately.

Results The following data represents stability studies in various media and phosphate buffers. Each table and figure is described in detail. A final discussion of this investigation is found at the end of these data.

Figure 12.53 In vitro release studies of PEGylated hybrid nanocarrier containing DFMO and Etoposide (PEG-HNC-D- E) in various phosphate buffered saline solutions. a) Qualitative images shown to the left of TNP-DFMO-TNP adduct (yellow) of drug release at various time points. Solution contains Etoposide drug which has been shown to not interact b) with TNBSA reagent (HPLC section). a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) (left to right, vials 1 to 10). b) PBS 5.4 without GSH (vials 11 to 20). c) c) PBS 7.4 w/10mM GSH (vials 21 to 30). d) PBS 7.4 w/o GSH (vials 31 to 40). e) PBS 7.4 w/20uM GSH (blood conditions) (vials 41 to 50). f) Free drug TNP-DFMO-TNP d) adduct and Etoposide 60ug/mL each (vials 51 to 60)

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#3 f e d c b a

Figure 12.54 HPLC chromatogram (@345nm) representation of drug release profiles of final formulation (PEG-CS-BSA-D-E) HNC at various time points over 72h in several buffers with or without the presence of glutathione (GSH). DFMO derivative (TNP-DFMO-TNP, #2), retention time of 11.9 minutes, and Etoposide (retention time of 13.9 minutes, #3) elucidation at 345nm and 283nm, respectively Chromatograms 1 through 3 represent reference standards (controls), borate buffer 10.2, TNBSA (#1) in borate buffer 10.2, 0.5mg/mL DFMO in double distilled deionized water (not derivative). Remaining chromatograms are as follows; a) PBS 5.4 with 10mM GSH (chromatograms 4 through 14), b) PBS 5.4 w/o GSH (15 through 24), c) PBS 7.4 with 10mM GSH (25 through 34), d) PBS 7.4 w/o GSH (35 through 44), e) PBS 7.4 w/20uM GSH to mimic blood condition levels (45 through 54), f) PBS 7.4 containing free drugs Etoposide (60ug/mL) and DFMO derivative (TNP- DFMO-TNP, 60ug/mL) (55 through 64). Total run-time of 18 minutes.

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DFMO derivative (TNP-DFMO-TNP adduct) @ 345nm standard curve using HPLC analysis. Concencentration vs. absorbance area (mAU*min)

60 50 40 30 y = 0.9779x - 0.1935 20 R² = 0.9999 10 0 0 10 20 30 40 50 60 Absorbance Absorbance area (mAU*min)

TNP-DFMO-TNP concentration (ug/mL) a)

Etoposide @ 283nm standard curve using HPLC analysis. Concencentration vs. absorbance area (mAU*min) 40 35 30 25 20 y = 0.6884x - 0.6014 15 R² = 0.996 10 5 0

Absorbance Absorbance area (mAU*min) 0 10 20 30 40 50 60 Etoposide concentration (ug/mL) b) Figure 12.55 Linearity graph of standard curve parameters of a) DFMO derivative (TNP-DFMO- TNP) and b) Etoposide quantified using Dionex Ultimate 3000 HPLC at 345nm and 283nm, respectively. Linearity graphs will be utilized to quantify drug for drug release profiles. Linearity was found in a range of 10 to 60ug/mL using absorbance area (mAU*min). Linearity range were performed in triplicates for each drug. Standard curves used to determine entrapment efficiencies of formulations. Linearity was evaluated by linear regression analysis, which was calculated by the least square regression method. Linear regression value (R2) of 0.999 were evaluated for both absorbance readings.

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325 | Page a) Table 12.40 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample. DFMO release @ 345nm Etoposide release @ 283nm Media: PBS 5.4 with 10mM GSH Media: PBS 5.4 with 10mM GSH Time Absorbance % Total drug Absorbance % Total drug Time point area released area released point (h) (mAU*min) (area, mAU*min) (mAU*min) (area, (h) mAU*min) 0 0 0 0 0 0.25 0.7111 7.40 2.9886 18.64 0.25 0.5 0.7105 7.40 5.7559 36.11 0.5 1 1.7390 17.39 5.7545 36.11 1 2 2.3376 23.87 5.7559 36.11 2 4 3.9679 38.79 6.4599 42.88 4 8 5.3664 51.82 7.6276 52.06 8 16 7.1140 67.70 9.0828 62.73 16 24 8.6240 81.63 10.7248 74.37 24 48 9.9913 94.40 13.4939 91.85 48 72 10.3376 98.82 14.3823 99.58 72

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327 | Page a) Figure 12.57 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 containing 10mM glutathione (GSH) at 345nm and 283nm for TNP-DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at

328 | Page b) Table 12.41 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. b) PBS 5.4 without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG- HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample. DFMO release @ 345nm Etoposide release @ 283nm Media: PBS 5.4 without GSH Media: PBS 5.4 without GSH Time Absorbance % Total drug Absorbance % Total drug Time point area released area released point (h) (mAU*min) (area, mAU*min) (mAU*min) (area, (h) mAU*min) 0 0 0 0 0 0 0.25 0.6661 7.03 2.7941 17.62 0.25 0.5 0.6655 7.03 5.6241 35.42 0.5 1 1.0460 11.72 5.6236 35.42 1 2 1.3268 15.60 5.6241 35.42 2 4 1.8134 21.17 5.8294 37.47 4 8 2.4666 28.10 5.8838 40.87 8 16 3.2367 35.98 6.2823 46.06 16 24 4.1758 45.25 6.7283 51.50 24 48 5.2062 55.26 7.2442 57.29 48 72 6.3050 65.83 7.7527 63.05 72

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330 | Page b)

Figure 12.59 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 5.4 without glutathione (GSH) at 345nm and 283nm for TNP- DFMO-TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

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a & b)

332 | Page a & b)

and Etoposide (bottom) quantification. PBS 7.4 containing 20uM GSH represent drug release profiles at blood condition levels. PBS 7.4 containing free drug

333 | Page c) Table 12.42 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. c) PBS 7.4 with 10mM GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG- HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample. DFMO release @ 345nm Etoposide release @ 283nm Media: PBS 7.4 with 10mM GSH Media: PBS 7.4 with 10mM GSH Time Absorbance % Total drug Absorbance % Total drug Time point area released area released point (h) (mAU*min) (area, mAU*min) (mAU*min) (area, (h) mAU*min) 0 0 0 0 0 0 0.25 0.6330 6.76 2.7893 17.59 0.25 0.5 0.7265 7.58 5.7166 35.90 0.5 1 1.4606 15.17 5.7159 35.90 1 2 2.1816 22.65 5.7168 35.90 2 4 3.7410 36.99 6.3262 42.18 4 8 5.3269 51.55 7.2495 50.09 8 16 7.2308 68.71 8.8886 61.71 16 24 8.9780 84.58 10.4187 72.77 24 48 10.6176 99.58 12.9769 89.16 48 72 10.6181 99.58 13.9211 97.18 72

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335 | Page c)

points.

336 | Page d) Table 12.43 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. d) PBS 7.4 without GSH at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG- HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample. DFMO release @ 345nm Etoposide release @ 283nm Media: PBS 7.4 without GSH Media: PBS 7.4 without GSH Time Absorbance % Total drug Absorbance % Total drug Time point area released area released point (h) (mAU*min) (area, mAU*min) (mAU*min) (area, (h) mAU*min) 0 0 0 0 0 0 0.25 0.6041 6.52 2.6703 16.98 0.25 0.5 0.6037 6.52 5.5290 34.93 0.5 1 0.9448 10.90 5.5296 34.93 1 2 1.1942 14.52 5.5289 34.93 2 4 1.7032 20.27 5.7572 36.86 4 8 2.3727 27.33 5.8116 39.70 8 16 3.1194 35.02 6.0943 44.29 16 24 4.1337 44.90 6.5211 49.62 24 48 5.1546 54.83 7.0174 55.32 48 72 6.3556 66.24 7.4475 60.67 72

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338 | Page d)

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c & d)

340 | Page c & d)

(bottom) quantification. PBS 7.4 containing 20uM GSH represent drug release profiles at blood condition levels. PBS 7.4 containing free drug (60ug) used as a control for drug

341 | Page e) Table 12.44 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. e) PBS 7.4 with 20uM GSH (blood levels) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample. DFMO release @ 345nm Etoposide release @ 283nm Media: PBS 7.4 with 20uM GSH Media: PBS 7.4 with 20uM GSH (blood levels) (blood levels) Time Absorbance % Total drug Absorbance % Total drug Time point area released area released point (h) (mAU*min) (area, mAU*min) (mAU*min) (area, (h) mAU*min) 0 0 0 0 0 0 0.25 0.4765 5.48 2.5099 16.14 0.25 0.5 0.5172 6.73 5.4765 34.65 0.5 1 0.7424 10.16 5.9680 35.22 1 2 1.0570 14.31 5.9675 35.22 2 4 1.9442 23.15 6.0936 38.99 4 8 2.7700 31.49 6.2671 43.01 8 16 3.8760 42.12 6.5185 47.44 16 24 4.9385 52.40 6.8509 52.28 24 48 6.0262 62.88 7.1109 56.75 48 72 6.0255 71.73 7.4361 61.56 72

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343 | Page

Figure 12.69 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. a) In vitro release in PBS 7.4 with 20uM glutathione (GSH) to represent blood condition levels at 345nm and 283nm for TNP-DFMO- TNP (top) and Etoposide (bottom) quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

344 | Page f) Table 12.45 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. f) PBS 7.4 with 60ug of free drug (each) at 345nm and 283nm for TNP-DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points. Purified PEG-HNC-D-E contained approximately 11.8ug and 17ug, DFMO and Etoposide respectively per 150uL of sample. DFMO release @ 345nm Etoposide release @ 283nm Media: PBS 7.4 with 60ug free drug Media: PBS 7.4 with 60ug free drug Time Absorbance % Total drug Absorbance area % Total drug Time point area released (mAU*min) released point (h) (mAU*min) (area, mAU*min) (area, mAU*min) (h) 0 0 0 0 0 0 0.25 5.308 9.38 0.0149 1.49 0.25 0.5 9.990 8.31 0.2110 1.93 0.5 1 17.586 13.28 2.0623 5.94 1 2 33.025 26.64 6.9462 13.28 2 4 58.156 43.16 17.2881 26.49 4 8 116.786 100.26 37.8868 51.33 8 16 175.330 100.11 78.7857 100.48 16 24 233.670 99.76 119.5286 100.10 24 48 291.843 99.48 160.1588 99.82 48 72 349.764 99.05 200.6429 99.47 72

345 | Page

346 | Page f)

347 | Page

e & f)

Figure 12.72 In vitro release studies of PEGylated hybrid nanocarriers containing DFMO and Etoposide (PEG-HNC-D-E) in various phosphate buffered saline solutions. Media: PBS 7.4 with 20uM GSH (blood levels) and PBS 7.4 with 60ug of free drug (each) at 345nm and 283nm for TNP- DFMO-TNP and Etoposide quantification. Percentage total drug calculated from HPLC absorbance area (mAU*min) at various time points.

348 | Page

a, b, c, d, e & f)

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a, b, c, d, e & f)

Discussion As with most dosage forms, product quality and performance may be verified through several in vivo and/or in vitro experiments. Of these, drug release kinetics provides critical information about dosage form behavior and is a key parameter used to assess product safety and efficacy. Due to the expense, time, labor, and need for human subjects/animals when performing in vitro measurements of drug release kinetics, in

350 | Page vitro release is gaining greater attention as a surrogate test for product performance. Indeed, in vitro release testing is commonly used as a predictor of in vivo behavior, historically with traditional dosage forms like capsules and tablets (i.e., dissolution), and more recently with novel dosage forms like injectable biodegradable microspheres and implants570. Generally, in vitro release studies are performed at 37°C (physiological temperature), though in some instances testing at elevated temperatures has been explored to characterize drug release from a variety of dosage forms 42.

Drug release study was performed following dialysis bag method 109. Dialysis bag retains the PEG-HNC- D-E nanocarriers but allows the transfer of the dissolved/released drug molecules into the release media. Dialysis tube (molecular weight cut off - 50,000 Da) was prepared according to the protocol provided by Sigma and soaked in the release media overnight prior to the study. Release media varied between formulations; PBS 5.4 (with and without the presence of glutathione, GSH) and PBS 7.4 (with and without the presence of GSH) 15 ml of each media. It was maintained at an agitation of 100 rpm and temperature of 37±0.50 C. One end of the dialysis tube was tied and PEG-HNC-D-E nanocarriers dispersion equivalent to 1 mg of was placed in the tube. The entire media was replaced with fresh 25 ml of phosphate buffer (pH 7.4) at predetermined time intervals (0, 25, 0.5, 1, 2, 4, 6, 8, 16, 24, 48, 72 hours). Samples were analyzed using established HPLC protocol for simultaneous detection of both drugs.

12.3.3 In vitro Cytotoxicity Studies of various HNC formulations against SK-N-Be2c and IMR-32 Neuroblastoma Cell-lines Materials Nanocarrier formulations (iRGD-PEG-HNC-D-E) were prepared as described in previous sections. Nanocarrier formulations were purified via dialysis method and stored at 4°C. Formulations were used within one-week. The α-difluoromethylornithine (DFMO) drug was kindly provided by Dr. Dana-Lynn Koomoa-Lange (University of Hawaii at Hilo, HI, USA). The etoposide drug was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 80055-248) and used throughout the study. Neuroblastoma cell-lines were prepared according to ATCC culture methods. SK-N-Be(2)c (ATCC, CRL-

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2268), SK-N-SH (ATCC, HTB-11), and IMR-32 (ATCC, CCL-127) NB cell-lines were cultured in RPMI medium (ThermoFisher, CA, USA) (Cat No. 11875093) containing 10% fetal bovine serum (FBS) and maintained in an incubator supplied with 5% CO2/95% air humidified atmosphere at 37°. NB cell-lines were seeded at 1 x 104 cells per well and incubated 24h prior to treatment. The cells were then incubated with varying HNC formulations as well as free drug alone for 72 h. Cell culture plates, 96-well (working volume of 200uL) were purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 734-1546) and used throughout all In vitro studies. MTS reagent were purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 10191-104) and prepared following assay instructions. MTS reagents were aliquoted into 1mL Eppendorf tubes and stored at -20°C until needed. MTS reagents were incubated in 37°C water bathe for 10 minutes before treating cells (20uL per well). Untreated cells were taken as control with 100% viability and cells without addition of MTS were used as blank to calibrate the spectrophotometer to zero absorbance. Experiments were done in triplicates. The results were expressed as mean values ± standard deviation of 6 measurements.

Methods SK-N-Be(2)c, and IMR-32 NB cell-lines were seeded at 1 x 104 cells per well in sterile conditions and incubated 24h prior to treatment. The cells were then incubated with varying HNC formulations as well as free drug alone (IC50 values determined in previous sections) for 72 h. MTS cell proliferation assay were conducted at 490nm to determine cell viability. MTS assay were read at 2h post-treatment (20uL MTS reagent) using a BioTek plate reader with Gen5 software for data interpretation. Experiments were done in triplicates with mean ± SD reported. Respective free drug or formulation concentrations versus %effect (cell viability) were plotted using Graphpad Prism 5 software.

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Results

Table 12.46 Experimental set-up for In vitro DFMO, Etoposide and hybrid nanocarrier (HNC) formulation studies treating SK-N-Be(2)c cell-lines. Cells seeded at 1 x 104 per well and incubatd 24h prior to treatment. Cells incubated with respective drug , drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment done in triplicates. SK-N-Be(2)c Drug concentration (DFMO, mM) 96-well plate Drug/Formulation (Etoposide, nM) Row:Column (HNC, uL) DFMO (D) IC50 0.405 B-E:4 Etoposide (E) IC50 230 B-E:5 DFMO + Etoposide 0.04 + 30 B-E:6 HNC-Placebo 100 B-E:7 HNC-D 0.4mM (100uL) B-E:8 HNC-D-E 0.04mM + 40nM (100uL) B-E:9 PEG-HNC-D-E 0.04mM + 40nM (100uL) B-E:10 iRGD-PEG-HNC-D-E 0.04mM + 40nM (100uL) B-E:11 Control 0 B-E:2, 3

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1 2 3 4 5 6 7 8 9 10 11 12

B 0.059 0.432 0.469 0.234 0.233 0.228 0.43 0.215 0.228 0.234 0.205 0.046

C 0.045 0.46 0.439 0.226 0.222 0.232 0.453 0.228 0.239 0.242 0.21 0.046

D 0.05 0.49 0.463 0.224 0.223 0.232 0.436 0.227 0.225 0.225 0.217 0.046

E 0.049 0.453 0.456 0.229 0.225 0.233 0.439 0.236 0.228 0.234 0.222 0.054

F 0.052 0.51 0.465 0.223 0.231 0.226 0.435 0.235 0.224 0.223 0.214 0.052

G 0.051 0.467 0.44 0.209 0.22 0.229 0.445 0.22 0.228 0.228 0.201 0.045

H a)

1 2 3 4 5 6 7 8 9 10 11 12

B 0.046 0.686 0.666 0.25 0.257 0.242 0.509 0.263 0.264 0.288 0.293 0.044

C 0.045 0.702 0.638 0.265 0.228 0.247 0.536 0.246 0.245 0.254 0.273 0.045

D 0.045 0.592 0.505 0.234 0.213 0.234 0.521 0.231 0.232 0.238 0.289 0.045

E 0.045 0.648 0.539 0.225 0.218 0.247 0.527 0.25 0.263 0.238 0.295 0.046

F 0.046 0.597 0.515 0.233 0.218 0.233 0.592 0.231 0.242 0.228 0.28 0.044

G 0.044 0.543 0.527 0.24 0.212 0.24 0.654 0.244 0.231 0.26 0.306 0.048

H b)

1 2 3 4 5 6 7 8 9 10 11 12

B 0.1 0.575 0.65 0.248 0.263 0.291 0.564 0.256 0.283 0.276 0.321 0.049

C 0.047 0.66 0.644 0.256 0.262 0.289 0.542 0.271 0.27 0.261 0.304 0.048

D 0.045 0.583 0.642 0.247 0.248 0.257 0.585 0.252 0.253 0.255 0.3 0.051

E 0.062 0.561 0.607 0.248 0.245 0.249 0.606 0.241 0.247 0.258 0.296 0.046

F 0.046 0.547 0.641 0.237 0.238 0.236 0.644 0.239 0.249 0.252 0.313 0.045

G 0.045 0.588 0.536 0.254 0.256 0.237 0.536 0.237 0.246 0.267 0.281 0.045

H c) Figure 12.75 MTS assay absorbance readings at 490nm in BioTek plate reader of SK-N-Be(2)c NB cell-line treated with free DFMO (0.405mM, column 4), Etoposide (230nM, column 5), combination of both drugs (0.04mM + 30nM, DFMO and Etoposide, respectively, column 6). Hybrid nanocarriers containing no drug (HNC-placebo, column 7) followed by HNC-D (0.4mM DFMO, column 8), HNC- D-E (0.04mM DFMO and 40nM Etoposide respectively, column 9), PEGylated-HNC-D-E (0.04M DFMO + 40nM Etoposide, column 10), and iRGD peptide conjugated-PEG-HNC-D-E (0.04mM DFMO + 40nM Etoposide, column 11). Controls (no drug or nanocarriers) were in columns 2 and 3. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Well. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells were incubated with respective treatment for 72 h. MTS reading were conducted 2h post-treatment with MTS reagent (20uL of MTS reagent used). Experiment was conducted in triplicates (a, b, c represents independent experiments) with mean ± SD reported.

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Table 12.47 Experimental results for In vitro DFMO, Etoposide and hybrid nanocarrier (HNC) formulation studies treating SK-N-Be(2)c cell-lines. Cells seeded at 1 x 104 per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment done in triplicates. Cell Viability (%) SK-N-Be(2)c Drug concentration Trial Trial Trial Mean (DFMO, mM) 96-well plate 1 2 3 ± SD Drug/Formulation (Etoposide, nM) Row:Column (HNC, uL) DFMO (D) IC50 0.405 B-E:4 41 36 35 37 ± 3 Etoposide (E) IC50 230 B-E:5 42 32 36 37 ± 5 DFMO + Etoposide 0.04 + 30 B-E:6 43 35 37 38 ± 4 HNC-Placebo 100 B-E:7 93 93 96 94 ± 2 HNC-D 0.4mM (100uL) B-E:8 42 36 35 38 ± 4 HNC-D-E 0.04mM + 40nM (100uL) B-E:9 43 36 37 39 ± 4 PEG-HNC-D-E 0.04mM + 40nM (100uL) B-E:10 43 37 37 39 ± 3 iRGD-PEG-HNC-D-E 0.04mM + 40nM (100uL) B-E:11 38 44 45 42 ± 4 Control 0 B-E:2, 3 98 100 100 99 ± 1

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Figure 12.76 In vitro analysis of free drugs, DFMO (IC50 alone, 0.405mM) and Etoposide (IC50 value, 230nM) compared against various hybrid nanocarrier (HNC) formulations. Treatment conducted over 72h period. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). MTS readings were conducted 2h post- treatment with MTS reagent (20uL of reagent used). Experiment conducted in triplicates with mean ± SD plotted.

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Table 12.48 Experimental set-up for In vitro DFMO, Etoposide and hybrid nanocarrier (HNC) formulation studies treating IMR-32 cell-lines. Cells seeded at 1 x 104 per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment done in triplicates. IMR-32 Drug concentration (DFMO, mM) 96-well plate Drug/Formulation (Etoposide, nM) Row:Column (HNC, uL) DFMO (D) IC50 1.5 B-E:4 Etoposide (E) IC50 3 B-E:5 DFMO + Etoposide 0.4mM + 0.5nM B-E:6 HNC-Placebo 100uL B-E:7 HNC-D 0.4mM (100uL) B-E:8 HNC-D-E 0.04mM + 0.5nM (100uL) B-E:9 PEG-HNC-D-E 0.04mM + 0.5nM (100uL) B-E:10 iRGD-PEG-HNC-D-E 0.04mM + 0.5nM (100uL) B-E:11 Control 0 B-E:2, 3

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1 2 3 4 5 6 7 8 9 10 11 12

B 0.045 0.457 0.427 0.209 0.257 0.232 0.414 0.305 0.228 0.289 0.301 0.048

C 0.045 0.431 0.37 0.237 0.27 0.267 0.412 0.255 0.24 0.288 0.255 0.045

D 0.045 0.389 0.349 0.236 0.261 0.258 0.403 0.37 0.246 0.263 0.233 0.045

E 0.044 0.38 0.371 0.246 0.289 0.262 0.41 0.289 0.264 0.257 0.236 0.045

F 0.044 0.443 0.441 0.235 0.258 0.246 0.481 0.285 0.248 0.239 0.247 0.045

G 0.044 0.428 0.341 0.234 0.245 0.259 0.403 0.38 0.262 0.249 0.249 0.045

H a)

1 2 3 4 5 6 7 8 9 10 11 12

B 0.055 0.375 0.429 0.216 0.266 0.293 0.412 0.275 0.259 0.265 0.28 0.044

C 0.045 0.383 0.39 0.263 0.273 0.272 0.436 0.317 0.277 0.269 0.246 0.045

D 0.045 0.368 0.367 0.264 0.26 0.242 0.418 0.322 0.263 0.261 0.226 0.045

E 0.045 0.421 0.323 0.257 0.257 0.257 0.416 0.33 0.266 0.239 0.246 0.046

F 0.044 0.428 0.33 0.265 0.25 0.229 0.394 0.355 0.234 0.24 0.229 0.045

G 0.044 0.404 0.358 0.259 0.258 0.227 0.403 0.286 0.23 0.236 0.221 0.046

H b)

1 2 3 4 5 6 7 8 9 10 11 12

B 0.075 0.464 0.435 0.265 0.31 0.245 0.367 0.397 0.235 0.24 0.249 0.052

C 0.051 0.43 0.522 0.283 0.281 0.247 0.39 0.41 0.265 0.248 0.269 0.049

D 0.046 0.397 0.447 0.266 0.263 0.252 0.352 0.422 0.251 0.266 0.242 0.045

E 0.045 0.416 0.517 0.23 0.258 0.244 0.362 0.325 0.25 0.234 0.245 0.048

F 0.044 0.427 0.518 0.233 0.246 0.245 0.388 0.33 0.258 0.253 0.243 0.045

G 0.045 0.514 0.417 0.244 0.246 0.24 0.387 0.357 0.261 0.264 0.223 0.048

H c) Figure 12.77 MTS assay absorbance readings at 490nm in BioTek plate reader of IMR-32 NB cell- line treated with free DFMO (1.5mM, column 4), Etoposide (3nM, column 5), combination of both drugs (0.4mM + 0.5nM, DFMO and Etoposide, respectively, column 6). Hybrid nanocarriers containing no drug (HNC-placebo, column 7) followed by HNC-D (0.4mM DFMO, column 8), HNC- D-E (0.04mM DFMO and 0.5nM Etoposide respectively, column 9), PEGylated-HNC-D-E (0.04M DFMO + 0.5nM Etoposide, column 10), and iRGD peptide conjugated-PEG-HNC-D-E (0.04mM DFMO + 0.5nM Etoposide, column 11). Controls (no drug or nanocarriers) were in columns 2 and 3. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). MTS reading were conducted 2h post-treatment with MTS reagent. Experiment was conducted in triplicates (a, b, c represents independent experiments) with mean ± SD calculated.

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Table 12.49 Experimental results for In vitro DFMO, Etoposide and hybrid nanocarrier (HNC) formulation studies treating IMR-32 cell-lines. Cells seeded at 1 x 104 per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). Cells read after 2h post-treatment with MTS reagent at 490nm in BioTek plate reader. Data were calculated with mean ± SD. Experiment done in triplicates. Cell Viability (%) IMR-32 Drug concentration Trial Trial Trial Mean (DFMO, mM) 96-well plate 1 2 3 ± SD Drug/Formulation (Etoposide, nM) Row:Column (HNC, uL) DFMO (D) IC50 1.5 B-E:4 53 62 50 55 ± 6 Etoposide (E) IC50 3 B-E:5 61 64 53 59 ± 6 DFMO + Etoposide 0.4mM + 0.5nM B-E:6 59 62 48 56 ± 7 HNC-Placebo 100uL B-E:7 105 110 79 98±17 HNC-D 0.4mM (100uL) B-E:8 75 80 79 78 ± 3 HNC-D-E 0.04mM + 0.5nM B-E:9 57 62 50 56 ± 6 (100uL) PEG-HNC-D-E 0.04mM + 0.5nM B-E:10 61 61 50 57 ± 6 (100uL) iRGD-PEG-HNC-D-E 0.04mM + 0.5nM B-E:11 58 58 48 55 ± 6 (100uL) Control 0 B-E:2, 3 100 100 100 100±0

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Figure 12.78 In vitro analysis of free drugs, DFMO (IC50 alone, 1.5mM) and Etoposide (IC50 value, 3nM) compared against various hybrid nanocarrier (HNC) formulations. Treatment conducted over 72h period. Cells seeded at 1 x 104 cells per well and incubated 24h prior to treatment. Cells incubated with respective drug, drug combinations or HNC formulation for 72h before analysis with MTS cell proliferation assay (20uL reagent per well). MTS readings were conducted 2h post- treatment with MTS reagent (20uL of reagent used). Experiment conducted in triplicates with mean ± SD plotted.

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Discussion Targeted drug delivery has been tested extensively in recent years. For example, targeted toxins are now available in brain tumor therapy and clinically approved nanoparticle-based cancer therapeutics, including liposomal formulations of anthracyclines, cytarabine, the nab formulation of paclitaxel, and the polymeric nanoparticle formulation of paclitaxel. However, in pediatric oncology, none of these has been studied in clinical trials nor approved by the regulatory authorities, although drug delivery exclusively to tumor cells is widely desired. Therefore, the RGD-liposomes described here could help to introduce these concepts, especially when treating young children and adolescents with cancer.

12.3.4 Cell-Associated Fluorescence (flow cytometry) for Cell Binding Assay studies using iRGD- PEG-HNC-FITC nanocarriers Rationale The modification of nanocarriers with ligands has been widely accepted to enhance the therapeutic efficacy of its payloads while reducing adverse side effects relative to conventional therapeutics 408. Ligand- conjugated nanocarriers not only have the ability to actively target specific cells but may also outperform first generation, non-targeted nanosystems. The necessity of targeted delivery depends on various factors (e.g., disease, drugs and the delivery vehicle); a vast array of important benefits have been demonstrated 21, 409-411. It has been shown-in cancer therapy that the presence of targeting ligands enhances the cellular uptake of nanocarriers through receptor mediated endocytosis even though the physiochemical properties of the nanocarrier determines its accumulation at the site of action 408, 409. As a result, higher intracellular drug concentration with increased therapeutic activity is observed, as bioactive macromolecules, such as DNA and siRNA, require intracellular delivery for bioactivity 408. Nanocarrier localization for endothelial targeting in cardiovascular diseases or immunological tissue targeting uses ligand-receptor interactions rather than the EPR 410. Ligand-mediated targeting is also of importance for the transcytosis of nanodrugs across endothelial and epithelial barriers (i.e., blood-brain barrier) 411. MDR have also been combated using targeted nanocarriers 21. Also, targeted nanocarriers with a long systemic circulation may be able to locate and destroy cancers cells that have metastasized elsewhere in the body. The clinical translation of targeted nanocarriers for treatment has been slower with four -nanocarrier systems now in phase I/II clinical trials 21. The main barrier for clinical translation of these formulation systems is the complexity behind the manufacturing of targeted nanocarriers. The fabrication of targeted nanopaticles requires multiple steps such as ligand coupling/insertion, purification and biomaterial assembly, which may cause batch-to-batch variation. A single-step synthesis of targeted nanocarriers was recently developed utilizing self-assembling pre-functionalized biomaterials that provided a simple and scalable manufacturing strategy 21, 412. Another important consideration is targeting ligands. The targeting ligand itself must be taken into consideration

361 | Page during formulation. The other variables that also must be considered are-cell specificity of the ligand, ligand biocompatibility, mass production, binding affinity, and its overall purity 413. The ideal ligand would be able to distinguish only the most overexpressed receptors on the target cell relative to healthy cells in order to achieve maximal specificity. There are other factors that could also influence cell targeting-: the ligand surface density and arrangement, as well as spacer type and length dividing ligand molecules and the nanocarriers 414. Nevertheless, with many advances in ligand engineering and screening, and nanocarrier optimization during formulation, targeted delivery will become a common therapeutic method in the next generation of drug therapy.

The RGD sequence (Arg-Gly-Asp) (Figure 7A) was first discovered in the early 1970s by E. Ruoslahti as a cell attachment site in fibronectin 485. Later, this sequence has been recognized as the minimal integrin sequence present in many natural ligands binding αvβ3receptor as fibrinogen, fibronectin,vitronectin, plasminogen, thrombospondin, prothrombin, MMP-2, laminin, osteopontin, etc 486. The RGD sequence is currently the basic module for a variety of molecules designed for the preferential binding to αvβ3integrin and other integrins 487. The affinity of RGD peptides for their ligands may be affected by steric conformation of the peptide 488. Besides direct interactions between additional flanking groups and their receptor, the conformational features of the RGD motif can also be modulated. Indeed, the cyclization is commonly employed to improve the binding properties of RGD peptides, conferring rigidity to the structure (Figure 7B). In linear peptides, the fourth amino acid alters the binding specificity and the nature of residues flanking the RGD sequence could influence receptor affinity, receptor selectivity, and other biological properties 488. Linear RGD peptide proved highly susceptible to chemical degradation. Since the rigidity conferred by cyclization prevents this, cyclic peptides are more stable, more potent, and more specific. In cyclic peptides, the RGD peptide sequence is flanked by other amino acids to build a ring system. These systems offer the possibility to present the RGD sequence in a specific conformation for a selected integrin 488. Cyclization of a linear RGD penta-peptide including one of the amino acids (Phe) in the unnatural D- conformation (D-Phe) resulted in the cyclic peptide c(RGDfK) developed by Kesslerand co-workers 489. Another RGD peptide ligand, the so-called RGD4C, has also been studied as targeting ligand. Never-the less, a disadvantage of this peptide is that this peptide can fold into different cyclic structures 487. Structures, chemical modifications, affinity for αvβ3, and implications in targeted therapies of the different linear and cyclic RGD peptides have been reviewed by Temming et al 487. Since the natural mode of interactions between integrin αvβ3 and RGD-containing proteins may involve multivalent binding sites, the idea to improve the integrin αvβ3 binding affinity with multivalent cyclic RGD peptides could provide more effective antagonists with better capability and higher cellular uptake through the integrin-dependent endocytosis pathway 488.

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Materials Nanocarrier formulations (iRGD-PEG-HNC-FITC) were prepared as described in previous sections with the exception that no drug was used for these experiments. Bovine serum albumin self-reacts with Fluorescein Isothiocyanate (FITC) to form BSA-FITC polymers. These polymers were purified via dialysis and used for the formulation of iRGD-PEG-HNC-FITC nanocarriers. Nanocarrier formulations were purified for any free reacts or polymers via dialysis method and stored at 4°C. Formulations were used within one-week. The α-difluoromethylornithine (DFMO) drug was kindly provided by Dr. Dana-Lynn Koomoa-Lange (University of Hawaii at Hilo, HI, USA). The etoposide drug was purchased from VWR International (VWR, Radnor, PA, USA) (Cat. No. 80055-248) and used throughout the study. Neuroblastoma cell-lines were prepared according to ATCC culture methods. SK-N-Be(2)c (ATCC, CRL- 2268) NB cell-line were cultured in RPMI medium (ThermoFisher, CA, USA) (Cat No. 11875093) containing 10% fetal bovine serum (FBS) and maintained in an incubator supplied with 5% CO2/95% air humidified atmosphere at 37°. Experiments were done in triplicates. The results were expressed as mean values ± standard deviation.

Methods Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h and throughout the duration of the experiment. Cells were then centrifuged (500RPM, 5 minutes) and washed twice with ice-cold PBS 7.4 solution (containing 2mg/mL glucose). Cells were then re-suspended in cold PBS 7.4 (w/glucose) and stored on ice until analysis. Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 individual cell fluorescence per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software was used for data interpretation and graphical analysis. Experiments were done in triplicates with mean ± SD reported.

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Results

Figure 12.79 Flow cytometry analysis of HNC- FITC formulations against SK-N-Be(2)c cell- lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, a) 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. a) All controls; Be2c cells alone (yellow), Be2c cells destroyed (black, 7000RPM for 1h + UV radiation), hybrid nanocarrier loaded with FITC (green, HNC-FITC), Be2c cells treated with FITC only (red), and iRGD saturated Be2c cells followed by treatment with High iRGD-PEG-HNC (pink). b) Be2c cells alone b) (yellow), Low conjugated iRGD-PEG-HNC (blue), Medium conjugated iRGD-HNC (black), and High conjugated iRGD-HNC (red). c) Overlay of controls and HNC formulations: Be2c cells alone (yellow), hybrid nanocarrier loaded with FITC (green, HNC- FITC), iRGD saturated Be2c cells followed by treatment with High iRGD-HNC (pink), Low conjugated iRGD-PEG-HNC (blue), Medium conjugated iRGD-PEG-HNC (black), and High c) conjugated iRGD-PEG-HNC (red).

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Fluorescence Intensity Mean (530nm Filter) Fluorescence

Label Trial 1 Trial 2 Trial 3 Intensity ± SD SK-N-Be(2)c Cells alone 7,308 6,799 6,334 6,814 ± 487 Destroyed SK-N-Be(2)c Cells 4,277 4,289 5,101 4,556 ± 472

FITC ONLY treated 421,811 399,384 378,831 400,009 ± 21,496 HNC-FITC treated 15,268 15,610 15,294 15,391 ± 190 iRGD Saturated, then High iRGD- 20,087 20,260 18,182 19,510 ± 1,153

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Table 12.51 Normalized flow cytometry results of HNC-FITC formulations against SK-N-Be(2)c cell- lines. Cells were seeded at approximately 1 million cells per mL in Eppendorf centrifuge tubes. Cell treatments were conducted on ice for 1h. Cells were then centrifuged and washed twice with cold PBS 7.4 solution (containing 2mg/mL glucose). Treated cells were analyzed in an Accuri C6 Flow Cytometer with a set count of 25,000 cells per treatment (HeNe laser, 530nm filter). Accuri C6 Plus software is used for data interpretation. Experiments were done in triplicates with mean ± SD reported. Normalized to SK-N-Be(2)c cells alone.

Normalized Fluorescence Mean Intensity (530nm Filter) Fluorescence

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Discussion Nanoparticulate systems such as liposomes, polymeric micelles, polymer–drug nano-conjugates, and dendrimers have led to about two dozen clinically approved therapeutic products 25. These chapters will discuss nanocarriers that have been demonstrated to carry two or more types of therapeutic payloads for the treatment of various cancers. Controlled combinatorial drug delivery share the common aim in promoting synergism-; however, each drug platform has its unique strength and characteristics. The different particle structures, materials, and preparation processes are emphasized in this article to provide design considerations toward developing combinatorial nanoparticulate systems. The structure of most commonly used nanocarrier systems such as liposome, polymeric micelle, polymer–drug nano-conjugate, and dendrimers has been represented in Figure 1. A wide-range of nanocarriers have also been discussed in literature which utilize different physiochemical properties to chemotherapy 102 but this dissetation mainly focused on multifunctional nanocarriers described earlier103-108.

13. CLOSING REMARKS, AND FUTURE DIRECTIONS 13.1 Summary Neuroblastoma (NB) is the most common extra-cranial solid cancer in childhood and infancy with patients having an average age of 17 months. Most are diagnosed with advanced stage NB when tumor progression is aggressive, making treatment of NB even more difficult. Up to 45% of patients are in the high-risk category with MYCN gene amplification being observed. The FDA-approved drug difluoromethylornithine (DFMO) exhibits anticancer activity against MYCN-amplified NB cells. DFMO is a suicide inhibitor of ornithine decarboxylase (ODC), a rate-limiting enzyme in the biosynthesis of polyamines. ODC gene expression is directly activated by MYCN suggesting that MYCN amplification is connected to high ODC expression. ODC expression produces high polyamine levels that contribute to the malignant phenotype and maintenance of NB tumorgenesis. This MYCN-ODC connection suggests that ODC may be a suitable new target for the treatment of NB with the administration DFMO. Etoposide, a topoisomerase inhibitor is often used in front-line therapy in the treatment of NB. The use of DFMO/Etoposide in vivo is currently limited due to the short half-lives (fast elimination/clearance) of both drugs which may explain why antitumor in vivo were not synergistic as observed in vitro.

I have shown that iRGD peptide-conjugated PEGylated polymeric hybrid nanocarriers loaded with synergistically acting DFMO and Etoposide drugs (iRGD-PEG-HNC-D-E) were characterized at 81±7nm in size, +12±2.5mV in zeta potential with a mean polydispersity index 0f 0.354±0.03. The developed nanocarriers had a 10 and 6-fold decrease in initial drug concentrations, DFMO and Etoposide respectively, with similar efficacy as compared to free drugs alone against various NB cell-lines over a 72h period. The

369 | Page current formulation shows stability suspended in phosphate buffer saline (PBS) 7.4 over 6 days. iRGD- PEG-HNC-D-E formulations can be modified (polymer: polymer ratio) to alter drug release profiles with the developed formula having a 90% release of both drugs after 72h in PBS 5.4 and 7.4 containing glutathione.

13.2 Closing Remarks Considerable effort has been made toward the research and development of multifunctional co-loaded chemo/gene therapy nanocarrier systems for cancer targeted imaging and therapy. Magnetic nanocarrier- based theranostic systems showed particular promise. The intrinsic magnetic properties lend themselves to diagnostic MRI applications, with their surfaces easily modified using a variety of targeting moieties, such as antibodies, peptides, small molecules, aptamers, or therapeutic agents utilizing a number of conjugation strategies. Also, magnetic nanocarriers can be degraded to Fe ions in the body particularly in the acidic compartments of cells (e.g. lysosomes), relieving potential toxicity of long-term residence of the nanocarriers themselves as compared to other inorganic nanocarriers such as gold and carbon-based formulations. The newer and advanced characterization methodologies are also needed, including pharmacokinetics and long-term toxicity studies. It is critical to be aware of the design parameters discussed in this review for preparation of nanocarriers for potential clinical uses. The costs required to integrate multiple components for co-loading or multifunctional properties are an additional consideration for commercial viability. One must also consider the regulatory hurdles encountered during clinical trials. The required regulatory processes become more complex with the multifunctionalities of the nanocarriers as they consist of multiple additional components and also claim multiple indications with a single nanocarrier. Nonetheless, there is high probability that multifunctional chemo/gene therapy nanocarrier systems for cancer-specific treatment will be used in the clinic setting in the near future. The multifunctional chemo/gene therapy approaches will help to meet unmet medical needs for effective cancer treatments with minimal adverse effects.

13.3 Future Directions The designing and tuning properties, that nanoparticles provide, that are not possible with other types of therapeutic drugs, and have shown a bright future as a new generation of cancer therapeutics. Furthermore, the development of multifunctional nanoparticles containing synergistic therapeutic agents may eventually render nanoparticles able to detect and kill cancer cells simultaneously. Although there are certain critical questions and many challenges remaining for the clinical development of nanoparticles, as more clinical data are available, further understanding in nanotechnology will certainly lead to the more rational design of optimized nanoparticles with improved selectivity, efficacy, and safety.

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15. APPENDIX A: PUBLICATIONS 1. Glasgow, M. D.; Chougule, M. B., Recent Developments in Active Tumor Targeted Multifunctional Nanoparticles for Combination Chemotherapy in Cancer Treatment and Imaging. J Biomed Nanotechnol 2015, 11 (11), 1859-98. 2. Gandhi NS, Glasgow M, Chougule MB. Nanocarrier based pulmonary gene delivery for lung cancer: therapeutic and imaging approaches. Cancer Therapeutics and Imaging: Molecular and Cellular Engineering and Nanobiomedicine edited by K. Rege. World Scientific Publishing, 2014.

16. SUPPLEMENTAL DATA 16.1.1 Fourier Transform Infrared Spectroscopy (FT-IR) Analysis of HNC formulations Results

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Figure X.

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