The Function of NSAIDs including Celecoxib as Therapies for Metastatic Cancer
Author Pritchard, Rhys
Published 2019-11
Thesis Type Thesis (PhD Doctorate)
School School of Medical Science
DOI https://doi.org/10.25904/1912/946
Copyright Statement The author owns the copyright in this thesis, unless stated otherwise.
Downloaded from http://hdl.handle.net/10072/389567
Griffith Research Online https://research-repository.griffith.edu.au
The Function of NSAIDs including
Celecoxib as Therapies for Metastatic
Cancer
Rhys Pritchard Master of Medical Research – Griffith University, Gold Coast
School of Medical Science Griffith Health Griffith University
Submitted in fulfilment of the requirements of the degree of Doctor of Philosophy
March 2019
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Abstract
Introduction Hypoxia is a naturally occurring event in solid tumours due to aberrant growth rates, unchecked proliferation and unregulated vascularity. Intratumoural hypoxia has been shown to contribute to malignant progression through the regulation of hypoxia-inducible factors (HIFs), transcription factors that in turn regulate a variety of stem-like and promigratory genes. Several recent meta- analyses of cancer patients administered Non-Steroidal Anti Inflammatory Drugs (NSAIDs) over the long term show a reduction in both pre and post-operative risk ratios (RR) demonstrating that
NSAIDs have anti-cancer activity. The main function of NSAIDs is as a pain relieving medication by inhibiting cyclooxygenase (COX). This was originally believed to be the cause for their anti-cancer activity as COX enzymes are known to be upregulated in a variety of cancers.
However, several groups have contested this theory with a variety of methods including; using
NSAID derivatives that do not inhibit COX, using amounts that are either above or below that required to inhibit COX enzymes, and by studies with COX-2 null animals or cell lines. Given the above observations for the anticancer activity of NSAIDs, it was important to understand more precisely the mechanism(s) through which NSAIDs may act as a cancer treatment.
Therefore, 5 NSAIDs and 1 non-COX-2 inhibitory NSAID derivative were examined for their mechanisms of action as anticancer drugs in vitro using murine melanoma and breast cancer cell lines as models.
Methods B16F10 cells were transfected with an octamer-binding transcription factor 4 (Oct4) enhanced green fluorescent protein (EGFP) conjugated plasmid and were subjected to hypoxia. The
2 of 329 highest Oct4 expressing cells were then sorted via fluorescence activated cell sorting (FACS) and were observed to maintain stable expression in normoxic culture. Spheroids and monoclonal cell populations were isolated to examine their Oct4 expression profiles. These hypoxic-derived
Oct4 positive cells were established as cell lines and tested in an animal model to determine whether there was an increase in their rate of metastasis. A scratch assay was employed to determine if the hypoxic derived Oct4 expressing cells were more migratory than their wild-type counterparts. The hypoxic derived cells as well as the 4T1.2 cell line, a more metastatic variant of the breast cancer 4T1 cell line, were tested against a variety of NSAIDs to determine their cytotoxicity against these cell lines. The cytotoxicity, apoptosis-inducing and reactive oxygen species (ROS) producing effects of NSAIDs were measured in a variety of assays. Testing for the effects of the NSAIDs on mitochondria was also undertaken using the Seahorse metabolic flux analyser. Several interesting effects on cell mitochondria were observed and imaged using fluorescence and confocal microscopy. The ability of the NSAIDs to reduce the incidence of metastases in a murine lung model was also examined.
Results The B16F10 cells subjected to hypoxia and rounds of sorting by FACS stably expressed Oct4 as a marker of stemness in ~85% of the population. This value could be increased by further selecting after incubation under hypoxic conditions. However, this value remained stable when incubating in standard normoxic culture conditions. Isolation of monoclonal cell populations and spheroids also failed to produce a singular Oct4 expressing population that would express Oct4 in the entire population. Hypoxically cycled cells did not exhibit enhanced migration as compared to the wild-type population.
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Analyses of the cytotoxic anticancer effects of the NSAIDs showed a wide range of IC50 values for the cells and hypoxic phenotypes tested. The B16F10-Oct4EGFP hypoxic cell line did not show significant differences in its sensitivity to the effects of NSAIDs as compared to the wild- type population. However, the 4T1.2 metastatic variant was more sensitive to two NSAIDs, celecoxib and sulindac. Treating cells with several of the NSAIDs was shown to induce ROS from the mitochondria, before the onset of apoptosis. Pre-treatment with a manganese superoxide dismutase (MnSOD) mimetic prevented the NSAID induced increase in ROS, and also partially preserved cell viability following NSAID treatment. Celecoxib was selected as the best candidate of the five NSAIDs for further study and it was demonstrated that celecoxib had a wide range of effects on the cancer cell mitochondria and levels of oxidative phosphorylation. Preliminary testing in a murine model of melanoma at the doses of celecoxib selected did not show a reduction in the resulting number of lung metastatic colonies compared to the untreated controls.
Discussion As the five NSAIDs did not show altered cytotoxicity against the hypoxic cycled cells, it is possible that any changes in cellular metabolism induced by hypoxia did not affect the targeting of mitochondrial respiration and sensitivity to drug treatment. Moreover, the hypoxic selection process could not generate a distinct or uniquely homogeneous cell phenotype, even after cell sorting by flow cytometry, single cell cloning or the isolation of cell spheroids. Rather, the hypoxic derived cells remained as heterogeneous populations equally sensitive to the effects of the NSAIDs. It is possible that the “stem-like” cells in these populations respired more slowly or switched their metabolism from oxidative phosphorylation to glycolysis, both of which could make them resistant to the ROS generating effects of the NSAIDs. The B16F10 cell line showed a more adaptable phenotype to hypoxia, and it is possible that eradicating the “stem-like”
4 of 329 population within would cause the more mature cell phenotypes to dedifferentiate and replenish the levels of cancer stem cells – this is in fact the method used to generate these cultures, using hypoxic stress and selection as opposed to that induced by drug treatment.
The NSAIDs were clearly shown to be potent inducers of mitochondrial superoxide production in the cancer cells, with this increase linked to caspase activation and apoptotic cell death. The generation of ROS occurred in a “burst” over the short term, with marked effects on the cell mitochondria. Celecoxib was by far the most potent inducer of cytotoxicity and increased ROS and was therefore the focus of further studies. Several interesting results were observed in cells treated with celecoxib under confocal microscopy with the mitochondria clumping together or undergoing fusion following treatment. In this manner, it appeared that the cells were attempting to mitigate against the extreme load of ROS induced by celecoxib, packaging, exporting or containing these damaged mitochondria via auto/mitophagy to reduce the genotoxic stress and to preserve cell health. The significant effects of celecoxib on the cancer cell mitochondria were confirmed using the Seahorse, which indicated that celecoxib caused acute effects on mitochondria in whole cells.
Treatment of a murine lung metastatic melanoma model with celecoxib did not show a reduction in the amount of lung metastases. However, several other groups have shown that combining celecoxib with other well-known cancer therapeutics (such as doxorubicin) produced a synergistic response. Whilst the NSAIDs – and particularly celecoxib – represent a valuable addition to the plethora of anticancer drugs available, they may be best suited to use as an adjuvant, or in combination as opposed to as a standalone cancer therapy. The combination of
NSAID with other chemotherapeutics could provide off target effects besides those commonly ascribed to NSAIDs, and could be optimally applied in combination with DNA damaging or
5 of 329 receptor targeted cancer therapies. When combined with the actions of the NSAIDs, together these treatments will likely result in greater effectiveness and/or a reduction in side effects.
Statement of Originality
This work has not previously been submitted for a degree or diploma in any university. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made in the thesis itself.
X Rhys Pritchard PhD Candidate
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Table of Contents
The Function of NSAIDs including Celecoxib as Therapies for Metastatic Cancer ...... 1 Abstract ...... 2 Introduction ...... 2 Methods ...... 2 Results ...... 3 Discussion ...... 4 Acknowledgments...... 15 Curriculum Vitae ...... 19 Grants & Awards ...... 20 Chapter One ...... 26 Literature Review...... 26 Introduction ...... 27 Breast Cancer Statistics ...... 28 Solid Tumours ...... 29 Common Mutations Found in Solid Tumours ...... 30 The Tumour Microenvironment ...... 31 Vascular Endothelial Growth Factor ...... 32 Altered Cellular Energetics in Cancer ...... 33 Matrix Metalloproteinases Promote Cancer Cell Migration ...... 33 Release of Exosomes and the Secondary Site ...... 33 Routes for Cancer Metastasis ...... 34 Hypoxia and Cancer ...... 37 Hypoxia and Solid Tumours ...... 37 Hypoxia-inducible Factors ...... 40 Regulation of the Hypoxia-inducible Factors ...... 41 The Aryl Hydrocarbon Nuclear Translocator (HIF-β) Subunit ...... 42 Hypoxia-inducible Factor 3α and Negative Regulation ...... 43 Hypoxia-inducible Factors and Role in Cancer Metastasis ...... 44 Hypoxia-inducible Factors Induce Changes in Cancer Metabolism ...... 48
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Octamer-Binding Transcription Factor 4 (Oct4) ...... 50 HIF Regulates Oct4 as a Major Factor Promoting EMT and Cancer Stem Cell Production. 51 NSAIDs as a Cancer Treatment ...... 52 Introduction ...... 52 Mechanisms of Anticancer Action ...... 53 COX Inhibition and VEGF ...... 55 The Pro-apoptotic action of NSAIDs ...... 56 Non-COX-2 inhibitory NSAID Derivatives with Anticancer Activity ...... 57 Carbonic Anhydrases can be Inhibited by NSAIDs ...... 58 Other Targets of NSAIDs ...... 58 Cell Cycle and Metabolism ...... 59 Celecoxib’s Proposed Mechanism(s) of Anticancer Activity ...... 59 The Role of ROS in the Mechanisms of NSAID Action and Influence on Cell Cycle in Cancer Cells ...... 60 NSAID Effects on ROS Production and the Cellular Antioxidant Defense Systems ...... 62 Preclinical and Clinical Data Supporting the Anticancer Activity of NSAIDs...... 65 Longitudinal Studies of Cancer Treatment with NSAIDs...... 66 The Role of Mitochondria in Cellular ROS production...... 67 The Mitochondria ...... 67 Celecoxib’s non-COX-2 inhibitory Derivative DMC is a more Potent Anticancer Drug .... 69 Celecoxib’s Effects on Hematopoietic Cancers ...... 69 Repurposing Drugs for Oncology (ReDO) ...... 70 Importance of Cancer Staging and Celecoxib Treatment ...... 72 Celecoxib is FDA Approved for Colorectal Cancer Treatment ...... 73 Current Clinical Trials ...... 74 Criteria for the Selection of Celecoxib ...... 75 Chapter Two...... 77 Methods...... 77 Cell Culture...... 80 Restriction Digest, Plasmid Extraction and Transfection ...... 80 Hypoxic Incubation ...... 82 Cobalt Chloride Testing...... 83 Isolation of Single Cells and Spheroids ...... 84
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Scratch Assay ...... 85 Animal Cancer Model Studies ...... 86 Drug Solubilisation ...... 86 Cytotoxicity ...... 89 Apoptosis ...... 89 Membrane Potential ...... 90 Determination of Cellular ROS Levels ...... 90 Fluorescent and Confocal Microscopy ...... 91 Confocal Microscopy and Cytometry using MitoSOX and MitoSpy ...... 92 Acridine Orange Staining ...... 92 Caspase-Glo® 3/7 Assay ...... 93 MnTMPyP Antioxidant Treatment ...... 93 Seahorse XFp Cell Mito Stress Test ...... 94 Animal Study ...... 94 Statistical Analysis ...... 95 Chapter Three...... 96 Results: Hypoxia and Cancer Stem Cells ...... 96 Hypoxia and Cancer Stem-cells ...... 97 Introduction ...... 97 Aims...... 97 Stable Expression of EGFP in the B16F10 Cell Line 2VB5 ...... 99 Oct4EGFP is Inducible via Pseudo Hypoxia ...... 101 Hypoxic Spheroids Highly Express Oct4 EGFP and are Heterogeneous ...... 104 Isolated Clones Largely Reform their Parent Population ...... 105 The B16F10 2VB5 Phenotype does not Demonstrate Increased Migration over the Oct4EGFP Containing Phenotype...... 110 Neither B16F10wt nor 2VB5 Phenotypes Metastasise from a Primary s.c. Injection Site . 112 Discussion ...... 114 Summary ...... 114 B16F10 Cells Stably Express Oct4EGFP after Several Rounds of Hypoxic and Normoxic Incubation ...... 115
Pseudo Hypoxic Stress using CoCl2 Increased Oct4EGFP Expression in both Hypoxic and Normoxic B16F10 Cells ...... 116
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Scratch Assay ...... 118 Animal Work ...... 119 Chapter Four ...... 121 Results: NSAIDs as a Cancer Therapy ...... 121 NSAIDs as a Cancer Therapy ...... 122 Introduction ...... 122 Aims...... 124 Solubility Study ...... 126 Optimization of Cytotoxicity Assays ...... 128
IC50 and GI50 NSAIDs ...... 132 Apoptosis in Response to NSAID Treatment ...... 142 Observation of ROS levels after NSAID Treatment ...... 144 Effects of NSAID Treatment on Mitochondrial Membrane Potential ...... 151 Discussion ...... 154 Summary ...... 154 Comparison between Metastatic and Hypoxic Phenotypes ...... 154 NSAIDs Cytotoxic Effects on Cancer Cells ...... 155 Clinical Relevance of Celecoxib’s Anti-Cancer Activity to Drug Pharmacokinetics in Humans ...... 157 Efficiency of the Sytox Assay ...... 159 Mitochondrial Membrane Potential ...... 159 Chapter Five ...... 161 Results: Celecoxib as a Cancer Therapy ...... 161 Celecoxib as a Cancer Therapy ...... 162 Introduction ...... 162 Aims...... 163 Celecoxib’s Effects on Apoptotic Pathway ...... 163 Celecoxib and Dimethyl Celecoxib have Dose Dependent Effects on Cell Viability at Short Time Points ...... 167 The SOD Mimetic MnTMPyP Significantly Reduces the Amount of ROS Induced by Celecoxib and Increases Cell Viability Post Celecoxib Treatment...... 170 DMC is a More Potent Inducer of Mitochondrial Superoxide than Celecoxib ...... 176 MitoSOX Signal is of Mitochondrial Origin with Little Translocation to the Nucleus ...... 178
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Celecoxib Strongly Affects Mitochondria in Whole Cells when Measured over Short Time Points ...... 181 Preliminary Animal Work ...... 189 Discussion ...... 190 Summary ...... 190 Celecoxib’s Effects on Apoptotic Pathway ...... 191 The SOD Mimetic MnTMPyP Significantly Reduces the Amount of ROS Induced by Celecoxib and Increased Cell Viability Post Celecoxib Treatment...... 192 DMC is a More Potent Inducer of Mitochondrial Superoxide than Celecoxib ...... 193 MitoSOX Signal is of Mitochondrial Origin with Little Translocation to the Nucleus ...... 194 Celecoxib has Rapid Effects on Mitochondrial Morphology ...... 194 Celecoxib Strongly Affects Mitochondria in Whole Cells when Measured over Short Time Points ...... 196 Preliminary Animal Work ...... 197 Chapter Six...... 199 Conclusion ...... 199 Summary ...... 200 Current and Future Directions ...... 204 Conclusion ...... 207 References ...... 210 Appendix I ...... 220 Appendix II ...... 223 Appendix III ...... 236 Appendix IV...... 239 Appendix V ...... 285 Appendix VI...... 303
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List of Tables
Table 1: Frequency of Metastasis to Distal Sites for Melanoma and Breast Cancers ...... 36 Table 2: pO2 (%) Available at Tissues ...... 39 Table 3: Genes Inducible by HIFs that are involved in Promoting Cancer Malignancy and Migration...... 47 Table 4: Reagents used in this Study ...... 78 Table 5: Materials used in this Study ...... 79 Table 6: Stock Solubilisation of Drugs used in this Study ...... 88 Table 7: Solubility of Drugs used in this Study ...... 88 Table 8: Recommended Daily Dosing of NSAIDs vs Cmax at Tissues ...... 131 Table 9: Dose Depended Increase in Superoxide Production in Response to NSAID Treatment ...... 148
List of Figures
Figure 1: Tumour Hypoxia and Constitutive HIF Expression Contributes to Metabolic Reprogramming and Metastasis ...... 45 Figure 2: Anticancer Mechanisms of NSAIDs ...... 54 Figure 3: NSAIDs Effects on Metastatic Cancer Mitochondria and Antioxidant Systems ...... 64 Figure 4: Intermittent Hypoxia and Effect on Metastatic Cell Mitochondria and Apoptosis ...... 68 Figure 5: Plasmid Vector Map phOct4-EGFP ...... 82 Figure 6: B16F10wt, Oct4 Normoxic, 2VB5 Hypoxic and 2VB5 Hypoxic + 48 h Hypoxia Oct4EGFP Expression Profiles ...... 101 Figure 7: B16F10 Oct4 Normoxic and 2VB5 Hypoxic Oct4EGFP Expression Profiles in Response to CoCl2 Treatment ...... 102 Figure 8: Cytometry Profiles of Normoxic and 2VB5 Cells after CoCl2 Treatment ...... 103 Figure 9: Isolated Spheroids and Spheroids Maintain their Morphology after Passaging ...... 105 Figure 10: B16F10 Oct4 Normoxic and 2VB5 Hypoxic Single Cell Clone Isolates EGFP Expression Profile. B16F10 2VB5 Hypoxic Spheroid Isolates EGFP Expression Profile ...... 108 Figure 11: Isolated Single B16F10 2VB5 Cells ...... 110
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Figure 12: B16F10 Oct4 Normoxic vs 2VB5 Hypoxic Migration ...... 111 Figure 13: B16F10wt vs 2VB5 Hypoxic Primary Tumour Formation and Survival Time from first Observed Tumour Measurement ...... 114 Figure 14: Structure of the NSAIDS used in this Study ...... 125 Figure 15: Different Forms and Structure of Cyclodextrins that were Tested for Drug Dilutions ...... 127 Figure 16: Optimization of the Sytox Cytotoxicity Assay and Cyclodextrin Cytotoxicity after Repeated Testing ...... 130 Figure 17: B16F10wt and 2VB5 Hypoxic, 4T1wt and 4T1.2 Cell Lines and Phenotypes Response to NSAID Treatment ...... 134 Figure 18: Comparison between B1610 and 2VB5 Hypoxic Phenotypes in Response to NSAID Treatment ...... 136 Figure 19: Comparison between 4T1 and 4T1.2 Phenotypes in Response to NSAID Treatment ...... 138 Figure 20: Bright-Field and Fluorescent Images of B16F10wt Cells in Response to NSAID Treatment at 200 µM post 48 h ...... 139 Figure 21: Bright-Field and Fluorescent Images of 4T1wt Cells in Response to NSAID Treatment at 200 µM post 48 h ...... 141 Figure 22: Apoptosis induced by NSAIDs using IC50 Values or 50 µM at Multiple Timepoints ...... 144 Figure 23: Cytosolic ROS induced by NSAID Treatment at both 2 h and 24 h in both B16F10wt and 4T1wt Cell Lines ...... 145 Figure 24: Mitochondrial Superoxide Produced in both B16F10wt and 4T1wt cells at 2-6 h post Treatment using 50 µM of NSAIDs ...... 147 Figure 25: Superoxide Production over time in Response to 50 µM NSAID Treatment ...... 149 Figure 26: Fluorescent Microscopy of Superoxide Induction in Response to NSAID Treatment ...... 151 Figure 27: Mitochondrial Membrane Potential in Response to NSAID treatment 50 µM after 2 h. Relative Difference in Mitochondrial Membrane Potential between the B16F10 and 4T1 cell lines ...... 153 Figure 28: Apoptosis and Caspase in Response to Celecoxib Treatment ...... 165 Figure 29: Apoptosis after Celecoxib Treatment ...... 166 Figure 30: Single Strand DNA Breaks and Lysosome Formation post Celecoxib Treatment ... 167 Figure 31: Reduction in Cell Viability Measured with MT-Glo Reagent over 24 Hours vs Celecoxib & DMC ...... 170 Figure 32: Dose Dependent Increase in Superoxide Measured with DHE after 1 Hour ...... 171 Figure 33: MnSOD Mimetic MnTMPyP Significantly Abrogates the Superoxide Increase Caused by Celecoxib at 2 h and 4 h ...... 172 Figure 34: DHE Staining after Celecoxib and MnTMPyP Treatment ...... 173 Figure 35: MnSOD Mimetic MnTMPyP Significantly Abrogates the Superoxide Increase Caused by aTS at 3 h and Preserves B16F10 cell Health after 48 h ...... 175 Figure 36: DMC is more Potent at Inducing Superoxide than Celecoxib ...... 177
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Figure 37: Superoxide Produced by Celecoxib is Specific to the Mitochondria, with Little Nuclear Translocation ...... 179 Figure 38: Increase in MitoSOX Signal and Mitochondrial Fusion via Confocal Microscopy . 180 Figure 39: Seahorse Mitostress Test on B16F10 Cells after Celecoxib 100 µM Treatment ...... 185 Figure 40: Seahorse Mitostress Test on 4T1 Cells after Celecoxib 100 µM Treatment ...... 188 Figure 41: In Vivo Celecoxib Dosing after B16F10 Inoculation via Tail-Vein Injection ...... 190 Figure 42: Timeline of Proposed Effect of Celecoxib in Vitro ...... 203 Figure 43: Proposed Method of Utilizing Celecoxib as an Adjuvant Therapy with Chemo/radio Therapies ...... 209 Figure 44: Oct4EGFP Plasmid Transfection, Hypoxic Cycling and Antibiotic Selection of the B16F10 Oct4EGFP Cell Phenotype...... 221 Figure 45: Overgrowth, Sorting and Stable Oct4EGFP Expression in the B16F10 2VB5 Hypoxic Cell Phenotype ...... 222 Figure 46: Increase in Sytox Signal over Time in the B16F10 Cell Line in Response to Celecoxib and Diclofenac ...... 225 Figure 47: Increase in Sytox Signal over Time in the B16F10 Cell Line in Response to Nimesulide and Sulindac ...... 227 Figure 48: Increase in Sytox Signal over Time in the B16F10 Cell Line in Response to Salicylate ...... 228 Figure 49: Increase in Sytox Signal over Time in the 4T1 Cell Line in Response to Celecoxib and Diclofenac ...... 230 Figure 50: Increase in Sytox Signal over Time in the 4T1 Cell Line in Response to Nimesulide and Sulindac ...... 232 Figure 51: Increase in Sytox Signal over Time in the 4T1 Cell Line in Response to Salicylate233 Figure 52: Cytosolic ROS Measured using CellROX is Similar to that Produced Using DCF. Mitochondrial Membrane Potential in Response to NSAID Testing at 24 h and 72 h ...... 234 Figure 53: Salicylate Tested at 5 mM slows Growth Rates but Does Not Induce Cell Death in the B16F10 Cell Line ...... 235 Figure 54: Full Well Imaging of Acridine Orange Assay ...... 237 Figure 55: Full Well Imaging of MnTMPyP DHE Assay ...... 238
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Acknowledgments
I would like to thank my supervisors Nigel McMillan, Steve Ralph and Pauline Kelly for all of their knowledge and assistance over the years, as well as for providing advice and corrections to this manuscript. Past and present members of the laboratory, including; Vuk Bortnik and Bardia
Kolahdooz for assistance with cytotoxicity assays and for being diligent students; Adriana
Pliego-Zamora for assistance with early cytometry work and Sam Nozuhur for being a diligent student. Our collaborators, Rafael Moreno-Sánchez and Sara Rodríguez-Enríquez for providing meetings and discussions regarding our work, as well as supplying data and proof-reading manuscripts.
Research and support staff around the university; Jelena Vider for assistance with microscopy, cytometry and FACS; Cameron Flegg for assistance with confocal microscopy; Pauline Kelly for assistance with cytometry, locating and procuring equipment; Bradly Patterson for assistance with materials in the laboratory; Ruth Lambrechts for training in cytometry and Paulina Janeczek for advice regarding plasmids and antibiotic resistance.
Other teams and groups around campus; Lirio Calderon-Gomez and Sarah Bydder for allowing me to instruct and demonstrate for their laboratory classes, as well as discussions and advice;
Tony Farrell, Anna Orthmann and Karen Wolter from the Science Store for assistance with procuring materials, and discussions; Fran Humphries from MSC for assistance with student inquiries; Jason Peart for discussions, assistance with GGRS matters and for being a great HDR convener; Mark Forwood for advice, discussions and assistance with MSC issues.
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To my friends; Tracie Cheng, Josh Barnier, Jana Barnier, Daniel Wuiske and Jeremy Watson, thanks for putting up with me over the years, the beers and the trivia – yes, if this gets accepted, I am going to make you all call me Doctor.
Most of all to my family, it has been a very long road with many difficulties, hardships and challenges and I would not be here if it wasn’t for all of your unwavering support.
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Publications
NSAID celecoxib: a potent mitochondrial pro-oxidant cytotoxic agent sensitizing metastatic cancers and cancer stem cells to chemotherapy. Stephen John Ralph, Sam Nozuhur, Rafael Moreno-Sánchez, Sara Rodríguez-Enríquez, Rhys Pritchard, J Cancer Metastasis Treat 2018;4:49
Celecoxib inhibits mitochondrial O2 consumption, promoting ROS dependent death of murine and human metastatic cancer cells via the apoptotic signalling pathway. Rhys Pritchard, Sara Rodriguez-Enriquez, Silvia C. Pacheco-Velazquez, Vuk Bortnik, Rafael Moreno-Sanchez and Stephen J. Ralph. Biochem Pharmacol, 2018. 154: p. 318-334
Redox State Influence on Human Galectin-1 Function. Xing Hua, Stacy A. Scott, Rhys Pritchard, Todd A. Houston, Stephen J. Ralph and Helen Blanchard. Biocimie, 2015 Sep; 116:8-16
Hitting the Bull’s-Eye in Metastatic Cancers-NSAIDs Elevate ROS in Mitochondria, Inducing Malignant Cell Death. Stephen J. Ralph, Rhys Pritchard, Sara Rodriguez-Enriquez, Rafael Moreno-Sanchez and Raymond K. Ralph. Pharmaceuticals, 2015; 8:62-106
STAT5 Activates the c-myc Proximal Promoter: Elevated STAT5 or c-myc Expression Relative to STAT1 is Linked with Reduced Survival of Melanoma Patients given IFN Therapy. Ibtisam Ghazawi, Albert Mellick, Samuel Cutler, James Doecke, Jeanette Raleigh, Pauline Kelly, Rhys Pritchard, Grant McArthur, Stephen J. Ralph (submitted manuscript, review in progress).
Hypoxia Induces Oct4 Expression through HIF Mediated Pathways and is Associated with an Increase in Metastatic Incidence and Melanoma Progression Rhys Pritchard, Michael Lousik, Bardia Kolahdooz, Christopher Wall and Stephen J. Ralph (manuscript in preparation)
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Conference Attendance
International Student Research Forum, 2018 – Gold Coast, Australia Conference Organiser, Committee Member and Session Chair
International Society for Cancer and Metabolism, 2017 – Bertinoro, Italy
Presenter, Title: Celecoxib Inhibits Mitochondrial O2 Consumption, Promoting Superoxide Production and Causing Extensive Apoptosis of Metastatic Cancer Cells
Australasian Melanoma Conference, 2016 – Sydney, Australia Presenter, Title: The Function of NSAIDs as a Cancer Treatment
Gold Coast Health and Medical Research Conference, 2016 – Gold Coast, Australia Presenter, Title: NSAIDs Inhibit Mitochondrial Function Promoting Superoxide Production and Apoptosis in Melanoma and Breast Cancer Cells
Brisbane Cancer Conference, 2016 – Brisbane, Australia Attendance only
Gold Coast Health and Medical Research Conference, 2015 – Gold Coast, Australia Poster Presentation, Title: NSAIDs Induce ROS Production and Malignant Cell Death in Murine Melanoma and Breast Cancer Models
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Curriculum Vitae
Research Support Officer May 2017 - Present Griffith University – Gold Coast, QLD
Sessional Academic, Tissue Culture Workshop March 2018 – Present Griffith University – Gold Coast, QLD
HDR Student Health and Safety Representative January 2018 – December 2018 Griffith University – Gold Coast, QLD
Sessional Academic (Senior), 3014MSC February 2017 – Present Griffith University – Gold Coast, QLD
Research Support Assistant February 2017 – May 2017 Griffith University – Gold Coast, QLD
Technical Services Assistant Nov 2016 – February 2017 Griffith University – Gold Coast, QLD
Sessional Academic, 3014MSC Feb 2015 – June 2016 Griffith University – Gold Coast, QLD
Sessional Academic, 7001HSV July 2015 – Nov 2015 Griffith University – Gold Coast, QLD
Asset and Stocktaking Staff April 2015 – July 2017 Griffith University – Gold Coast, QLD
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Grants & Awards
MSC Merit Grant 2018 $3,000 to support research project
Travel Award, ISCaM 2017 2017
Australian Postgraduate Award Scholarship 2015 – 2018
Travel Award, Gold Coast Health and Medical Research Conference 2016
Travel Award, International Student Research Forum, Beijing 2016
Strategic Seed Grant, MBoD, Menzies Health Institute Queensland 2015 $15,000 to support research project
Strategic Research Grant Award, Griffith University 2015 $5,000 to fund the completion of novel research papers
Travel Award, Gold Coast Health and Medical Research Conference 2015
Outstanding Academic Achievement, Dean’s Commendation 2015 Griffith University
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List of Abbreviations
2VB5 Second Sort Very Bright Isolate Five ATP Adenosine Tri-Phosphate AKT Protein Kinase B αTS Alpha Tocopheryl Succinate ANT Adenine Nuclear Translocator Ang2 Angiogenin BCL-2 B-Cell Lymphoma BFGF Basic Fibroblastic Growth Factor BRAF Beta-Rapidly Accelerated Fibrosarcoma Kinase BRCA Breast Cancer Gene BSA Bovine Serum Albumin Ca2+ Calcium CAM Cell Adhesion Molecule CCCP Carbonyl cyanide m-chlorophenyl hydrazone CDC25 Cell Division Cycle Protein 25 CDK Cyclin-dependent Kinase CDK2NA Cyclin-dependent Kinase Inhibitor 2A CKI Cyclin-Dependent Kinase Inhibitors CD Cluster of Differentiation CHEK2 Checkpoint Kinase 2 CSC Cancer Stem Cell COX Cyclooxygenase cMYC Myelocytomatosis Proto-Oncogene Protein DBD DNA Binding Domain d.d Double Distilled DHM 1,2 Dimethylhydrazine
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DMC Dimethyl-Celecoxib DMEM Dulbecco’s Modified Eagle’s Medium DMSO Dimethyl Sulfoxide DNA Deoxyribonucleic Acid DOX Doxorubicin EGFP Enhanced Green Fluorescent Protein EGFR Epithelial Growth Factor Receptor EGR-1 Early Growth Response protein 1 EPO Erythropoietin ERK Extracellular-signal Regulated Kinase FACS Fluorescence-activated Cell Sorter FCS Fetal Calf Serum FDA Food and Drug Administration FITC Fluorescein Isothiocyanate Gal-1 Galectin-1 GRP78 Glucose-Regulated Protein 78kDa GSH Glutathione HER Human Epidermal Growth Factor Receptor HGF Hepatocyte Growth Factor HIF Hypoxia-Inducible Factor HIF-1α Hypoxia-Inducible Factor 1-Alpha HIF-2α Hypoxia-Inducible Factor 2-Alpha HEPES 2-[4-(2-hydroxyethyl)piperazinyl-1]-ethanesulphonic acid hTERT Human Telomerase Reverse Transcriptase
IC50 Inhibitory Concentration 50% ICA Islet Cell Autoantigen IGF-1 Insulin-Like Growth Factor 1 IL8 Interleukin 8
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LPA Lipoprotein A mAB Monoclonal Antibody MAPK Mitogen-Activated Protein Kinase MC1R Melanocortin 1 Receptor MDM Mouse Double Minute Homologue MEK Mitogen-Activated Protein Kinase Kinase miRNA Micro Ribonucleic Acid MITF Microphthalmia-Associated Transcription Factor MMP Matrix Metalloproteinase mRNA Messenger Ribonucleic Acid MToR Mammalian Target of Rapamycin MTS1 Multiple Tumour Suppressor 1 MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide NAC N-Acetyl-L-Cysteine NADPH Nicotinamide Adenine Dinucleotide Phosphate NAG-1 NSAID-Activated Gene NANOG Homeobox Protein NANOG NHE-1 Sodium/Hydrogen Exchanger 1 NMSC Non-Melanoma Skin Cancer NOX Nitrogen Oxide NSAIDs Non-Steroidal Anti-Inflammatory Drugs NTR Neurotrophin receptor NBCS New Born Calf Serum Oct4 Octamere Binding Transcription Factor 4 ODDD Oxygen Dependent Degradation Domain OxPhos Oxidative Phosphorylation P21 Cyclin-Dependent Kinase Inhibitor 1 p27 Cyclin-Dependent Kinase Inhibitor 1B
23 of 329 pAb Polyclonal Antibody PALB2 Partner and Localizer of BRACA2 PAS Per-Arnt-Sim PBS Phosphate Buffered Saline PDGF Platelet Derived Growth Factor PDH Pyruvate Dehydrogenase PGC-1a Peroxisome Proliferator-Activated Receptor Gamma Co-activator 1-Alpha PI Propridium Iodide PI3K Phosphophoinositide 3-Kinase PKB Protein Kinase B PTPC Permeability Transition Pore Complex PTEN Phosphatase and Tensin Homologue Px Peroxicam P53 Tumour Protein p53 RAF Rapidly Accelerated Fibrosarcoma Kinase RECK Reversion-Inducing-Cystine-Rich Protein RNA Ribonucleic Acid ROS Reactive Oxygen Species SCC Squamous Cell Carcinoma SEER Surveillance, Epidemiology, and End Results Program Snail Zinc Finger Protein SNAI1 SNP 309 Single Nucleotide Polymorphism 309 SOX-2 Sex determining region Y Box 2 STK11 Serine/Threonine Kinase 11 TGFβ Tumour Growth Factor Beta Trp-1 Tyrosinase-Related Protein 1 TMRE Tetramethylrodamine TNF Tumour Necrosis Factor
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UADT Upper Aerodigestive Tract VEGF Vascular Endothelial Growth Factor XP Xeroderma Pigmentosum
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Chapter One
Literature Review
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Introduction
All statistics were adapted from Cancer Australia, a department of the Australian Government. canceraustralia.gov.au/statistics
Melanoma Statistics
Melanoma is expected to reach 11.0% of all new cancer diagnoses and 3.5% of cancer related deaths by the year 2019, with 55,128 Australians diagnosed melanoma during the period 2010-
2014. In Australia, the incidence of melanoma continues to rise with 15,229 new cases reported
(8,899 male, 6,330 female) by the end of 2019. During the 2015 period, the standardised incidence rate was 52 cases per every 105 Australians (63 male, 42 female) with this figure also
52 cases for every 105 persons (63 male, 42 female) in the year 2019. Melanoma was documented as the fourth most commonly diagnosed cancer in Australia for 2015, with this statistic remaining stable for projections based in 2019. These figures are alarming as statistics document a much higher prevalence of melanoma in Australia as compared to the rest of the world (19 th highest worldwide), and other developed countries such as the UK (5 th most commonly diagnosed) and the US (7 th most commonly diagnosed). However, despite a reduction in incidence of almost all other more frequently diagnosed cancers, malignant melanoma incidence remains on the rise the world over.
By 2019, estimations predict that up to 1 in 17 (1 in 13 males, 1 in 21 females) Australians are at risk of being diagnosed with melanoma of the skin by the time they reach 85, with the incidence and risk generally mirroring advancing age. This statistic is made even more relevant because of the known advancement of Australia’s aging population. For the recorded period of 2016, there were 1,281 deaths attributed to melanoma in Australia (1,190 male, 536 female), with this incidence also predicted to increase to 1,675 (1,160 males and 515 females) by the year 2019. In
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2016, the mortality rate due to melanoma was 5.9 deaths for every 105 individuals (9.0 male, 3.4 for female) with an expected increase to 6.1 (9.2 male, 3.5 female) in 2015. This makes melanoma the 12 th most frequent case of cancer related death in Australia. This then places the risk of dying of melanoma by the age of 85 by the year 2019 at 1 in 134 (1 in 89 males and 1 in
246 females). Longitudinally, melanoma diagnoses have increased more than three-fold since
1982 (3,534 cases) as compared to statistics from 2011 (11,570), with the population increasing by less than half over the same period. This raises the incidence of melanoma to 52 persons per every 105 of the population in 2019, compared to only 27 cases per 105 in 1982, with the number of related deaths following suit at 315 (1968) and 1,515 (2011). Melanoma is also one the most frequent causes of cancer related deaths among adolescents and young adults, markedly impacting on the lives of young people and their families.
Breast Cancer Statistics Breast cancer is the leading type of cancer for women worldwide and accounts for 25% of all cancer cases in women worldwide. In Australia, breast cancer diagnoses are projected to reach
19,535 by the end of 2019 and constitute a total of 14% of all cancer related diagnoses and 6.2% of all cancer related deaths. There was a total of 71,943 Australians diagnosed with breast cancer during the 2010-2014 period. There will be an estimated 19,535 new cases of breast cancer diagnosed in 2019 (164 male, 19,371 female). The standardised incidence rate was 65 cases for every 105 individuals (1.2 males, 124 female) during the year 2015. This figure is projected to decrease slightly on a per capita basis to 59 cases per every 105 individuals (1.1 male, 115 female). Breast cancer was documented as the highest incidence of cancer diagnosis in Australia for the 2019. In 2015, the risk of an individual being diagnosed with breast cancer by their 85 th year is estimated to be 1 in 82 (1 in 3,455 male, 1 in 43 female). Breast cancer diagnoses are seen
28 of 329 to increase with advancing age until the age bracket of 65-69, following this, a decreasing trend is observed. In 2016, there were 3,004 deaths related to breast cancer in Australia (28 male,
2,976 female). By the end of 2019, this figure is projected to rise to 3,090 (32 male, 3,085 female). The age-related mortality for the same period is projected at 68 deaths per 105 individuals (1.1 male, 131 female). In 2019, breast cancer was seen to account for the 4 th highest number of deaths among cancer related mortality. During the same period, it is estimated that the risk of breast cancer related death by their 85 th year will be 1 in 82 (1 in 3,455 male, 1 in 43 female).
Longitudinally, the number of breast cancer cases increased from the period 1968 at 1,435 new case to 3,004 in 2016. Over the same time course, the standardised incidence rate also increased from 44 cases per 105 persons to 60 cases per 105 persons. The number of breast cancer related deaths have increased over time from 1,435 in 1968 to 3,090 in 2019. During the same period the standardised incidence of breast cancer related deaths was seen to decrease from 17 per 105 persons to 11 per 105. In Australia during the period 2011-2015 the five-year survival rates for patients with breast cancer were up to 91%, a drastic improvement as compared to the rates for the period between 1982-1986 in which the five-year survival prediction was 72%. Despite obvious improvements, the five-year survival for malignant breast cancers remains low.
Solid Tumours Cancers and particularly solid tumours vary extensively in their heterogeneity, growth rates, metabolic make-up, migration and metastatic capabilities. The aberrant growth pattern, modified signaling axis, demand for nutrients and growth mechanics place certain stressors on the tumour that must be met for growth and spread to continue. Cellular survival mechanisms such as hypoxia-inducible factors (HIF’s), various growth factors, matrix regulators and anti-oxidative
29 of 329 defenses are routinely found altered in solid tumours and provide the opportunity of tumour survival, proliferation, invasion and finally metastasis. As such, each of these mechanisms will be introduced briefly below as being common factors of the initiation, proliferation and spread of most solid tumours of epithelial origin
Common Mutations Found in Solid Tumours Virtually all cancers are derived by somatic cell mutations that arise from genotoxic or cytotoxic stress. While the list of tumour associated mutations is vast, somewhat tumour specific and ever expanding, there are a few commonalities across all solid tumours that should be considered. P53 is commonly found mutated in a vast array of cancers [1-3]. The p53 protein is chiefly responsible for restricting the progression of the cell cycle while any damaged DNA is repaired, or induces apoptosis if DNA cannot be repaired. P53 expression is also thought to relate to the stemness of the cell, with the lack of cell cycle regulation prompting dedifferentiation and making reprogramming easier [1].
Hypoxia has also been shown to negatively impact on the levels of p53, suppressing p53 and further contributing to a cancer stem cell (CSC) phenotype. Mitogen activated protein kinase/Extracellular regulated kinase (MAPK/ERK) signaling pathways are also extremely common, affecting melanoma, colorectal, ovarian and thyroid tumours [4]. Aberration in the
MAPK/ERK signal involve an oncogenic Raf molecule beta rapidly accelerated fibrosarcoma
(BRAF) phosphorylating the downstream pathway that is activated through extracellular signaling [5].
Typically, mutations common to all solid tumours comprise of three basic elements
1. The ability to sustain genotoxic stress and resist apoptosis in the presence of damaged
DNA
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2. Alteration in the cell cycle that allows for unchecked proliferation
3. Mutations that allow the cell to become more “stem-like” and/or encourage a
dedifferentiated, pro-migratory phenotype
The Tumour Microenvironment The tumour microenvironment represents all the support cells and underlying matrix including, immune cells, fibroblasts, blood vessels, connective tissues, basal and cell adhesion proteins, minerals and fluid. The tumour microenvironment is demonstrated to support the tumour in several different ways. For example, it favors the altered tumoural energetic requirements through a decrease in pH and elevated lactate production due to heightened levels of glycolysis
[6]. This same reduction in pH is also thought to facilitate migration and alteration of the extra cellular matrix (ECM) [7]. Associated with the growing tumour are host fibroblastic cells typically associated with the location of the tumour (pericytes, mesenchymal cells, and myocytes). The ECM secretory function of the fibroblasts is “hijacked” by the associated tumour, supporting ECM remodeling matrix metallo-proteinases (MMPs), paracrine signaling, vascular and fibroblastic growth factors [8]. The tumour associated fibroblasts also aid in immune evasion through inhibition of cytotoxic T-cells and natural killer cells.
The spatial location, distribution of blood vessels, dynamic nature of the matrix and the proliferation of the tumour present considerable difficulties in the treatment of solid tumours.
Application of drugs through oral or intravenous routes may not be sufficient to reach the vast majority of any sizable tumour, especially if the center of the tumour is hypoxic or necrotic [9].
In this fashion, the reduced and commonly aberrant vasculature of the tumour may contribute to a reduction in the delivery of antineoplastic agents or will affect only the outmost rapidly proliferating tumour cells. Furthermore, this ablation of the outer most layers of the tumour
31 of 329 promotes an inflammatory environment and exposes the innermost and more stem-like cells to the blood stream, possibly promoting metastasis [10]. The testing of anticancer therapeutics is typically performed in vitro on a homogeneous cell culture without the underlying EMC and may aid to explain why several promising therapies do not perform well in large animal models and clinical trials.
Vascular Endothelial Growth Factor Cancers, and in particular rapidly proliferating tumours, incur states of altered metabolic flux due to their aberrant growth patterns, spread and dysplasia. Therefore, it is vital to the tumour bulk for sufficient supply of nutrients to maintain the rapidly proliferating tumour population. For small tumours to reach a critical size, they must upregulate growth factors such as vascular endothelial growth factor (VEGF) and fibroblastic growth factor (FGF) that are secreted into the surrounding matrix and result in endothelial cell proliferation [11]. All members of the VEGF subfamily stimulate cellular responses through tyrosine kinase receptors (VEGFRs) on the cell surface. Proteases are also secreted by the cell to facilitate the degradation of the surrounding matrix. VEGF as well as Delta-like ligand 4 (DII4) interact with Tip cells to facilitate rearrangement of the cytoskeleton, filopodia and lamellipodia, promoting chemotaxis [12].
Combined, these mechanisms allow the endothelial cells to reach the tumour site and recruit circulating endothelial progenitors to form new blood vessels helping to support the tumour. This not only supplies the tumour with the oxygen and nutrients that it requires, but also facilitates growth into surrounding tissues and provides a conduit for metastasis, linking the tumour bulk to the circulatory system. Furthermore, this dynamic process of varying and cyclic oxygen and nutrient deprivation has been shown to drive the formation of more metastatic phenotypes and promotes cellular migration [13].
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Altered Cellular Energetics in Cancer Alterations in cellular energetics and cellular metabolism have been well established observations in solid tumours. The first incidence of this was noted by Otto Heinrich Warburg in
1927 and eponymously named the “Warburg Effect” [14]. The theory revolves around the noted increase in glucose fermentation (typically an anaerobic process) in cancerous cells even in the presence of oxygen [15]. The effect was more noticeable in rapidly proliferating and malignant tumours and was proposed as responsible for the formation of cancers. However, conventional research challenged this assumption and the Warburg effect is now considered a consequence of driver mutations, damage to the mitochondria, suppression of mitochondrial function through mtDNA damaging mutations due to the associated hypoxia.
Matrix Metalloproteinases Promote Cancer Cell Migration The upregulation of matrix metalloproteinases (MMPs) is known to be an integral process in the invasiveness of cancer cells by enabling extracellular matrix remodelling that facilitates chemotaxis. MMP-9 is downstream of the hypoxia response element (HRE) and is found to be overexpressed alongside hypoxia-inducible factor alpha (HIF-1α) after hypoxic incubation [16].
MMP-9 expression is also linked to increased invasiveness, since short interfering ribonucleic acid (siRNA) knockdown of MMP-9 in HIF-1α positive cells decreased motility. Furthermore,
HIF-1α has been shown to stabilise other MMPs and proteins such as MMP-7, MT-MMP and
ETS-1, that all aid in promoting cellular motility [8].
Release of Exosomes and the Secondary Site Complimentary to this process, exosomes are released from the primary tumour sites, which are believed to prime at distal metastatic sites, according to the seed/soil hypothesis [17]. Exosomes provide a mechanism for secreted protein and miRNA transport that can act as tumour promoters
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[18]. The excretion of such proteins may impact on distal cells and their signalling by promoting a microenvironment favourable to the seeding of circulating tumour cells, providing a so called
“niche”. The primed tumour site is then an ideal recipient for metastatic cells in the circulation which extravasate and seed into the newly primed site [19]. The initial seeded cancer cell begins to multiply anew forming a tumour of clinical relevance known as a secondary or metastatic tumour. This ability is shared by most primary tumours, although the frequency with which they do so is markedly different between cancers from different tissue origins because of specific cell types, their unique set of mutations and inter-individual variation. A basal cell carcinoma or lipoma may almost never metastasise, yet the cancers that form the basis of this project originated as melanomas or breast cancer, are well characterised and highly metastatic with poor prognoses at advancing stages [20, 21].
Routes for Cancer Metastasis The culmination of the preceding factors results in a cancerous cell that has the potential to metastasise due to the acquisition of altered metabolism, ability to migrate and survive in the bloodstream, evading the immune system and forming a new lesion in a distal location from the primary tumour. Metastatic cancer is by far the largest cause of cancer-related deaths. The reasons for this are multifactorial and the most pertinent to this thesis are covered in greater detail in subsequent sections.
Metastasis most commonly occurs via the following three routes:
1. Lymphatic Spread
Spread to the lymphatic system provides cancerous cells with a route to other tissues in the body and is the most common form of metastasis for carcinoma, in contrast to sarcoma that rarely metastasises via this route. The lymphatic system drains into the circulatory system by way of
34 of 329 the azygous vein providing additional opportunities for metastatic cells to spread in this fashion and enter the circulation to reach distant organs.
2. Haematogenous Spread
Haematogenous spread is characterised by the migration of cells directly into the blood stream via the circulatory system. The venous system is invaded often due to the relative thickness of the vessel walls as compared to the arterial system. Certain cancer types that are close to circulatory blood flow have a greater propensity to enter the haematogenous system directly due to the juxtaposition with the high volume of blood flow. Cancers such as clear cell renal carcinomas often favour the haematogenous route. The pattern of metastasis from cancers utilising this pathway typically follows the route of venous flow. The haematogenous route is the most common form of metastasis utilised by sarcomas.
3. Transcoelomic
Transcoelomic metastasis is the spread of malignant tissues into a body cavity by penetrating the surface of adjacent peritoneal, pleural or subarachnoid spaces. This type of migration is rare and commonly only involves mesotheliomas or ovarian cancers.
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Table 1: Frequency of Metastasis to Distal Sites for Melanoma and Breast Cancers
Frequency (%)
Site of Metastasis Melanoma Breast Cancer
Skin or Subcutaneous 50-75 20
Lung 70-87 59-79
Liver 54-77 56-65
Brain 36-54 9-23
Bone 23-49 44-71
Gastrointestinal 26-58 18-32
Heart or Pericardium 40-45 9-21
Pancreas 38-53 14
Adrenal 36-54 31-49
Kidneys 35-48 18
Thyroid 25-39 13
References: [22-25]
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Hypoxia and Cancer
Hypoxia and Solid Tumours Hypoxia is a naturally occurring phenomenon in many tissues and organs throughout the body.
In fact, it is exceedingly rare that cells in the body are ever exposed to atmospheric (~21%) oxygen levels. Certain tissues in the body, particularly the skin, are found to naturally be hypoxic
(<5% O2) (See Table 2). Culturing cells at atmospheric O2 concentrations and under standard tissue culture conditions may contribute to many false positives and negatives and remains a point of contention for in vitro experimentation. An environment of hyperoxia could contribute to oxidative stress in cells resulting in higher rates of respiration, genotoxic stress, and mutation
[26]. Definitions used regarding oxygen tensions, metrics, units and partial pressures are interchangeable and in the scope of this document, oxygen is defined as a percentage of atmospheric oxygen, with mild hypoxia representing 1-5% and less than 1% being severely hypoxic.
Hypoxia can also arise from a variety of non-physiological events. Common among these are reduced arterial pressures that can arise due to pulmonary, cardiac or neurological conditions.
Anemia alters the efficiency of haemoglobin to bind oxygen and can also contribute to hypoxic conditions and low partial pressures. Carbon monoxide poisoning resulting in methaemoglobin accumulation reduces levels of haemoglobin in the blood stream and can result in hypoxia.
Hypoxia may also occur due to certain respiratory poisons (such as cyanide, antimycin, rotenone, oligomycin and sodium azide) that block respiration or electron transfer at sites of the oxidative phosphorylation and electron transport systems. Interestingly, this last mechanism is a widely used method to induce hypoxia both in cell biology and cancer drug discovery.
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In terms of solid tumours, hypoxia occurs through several mechanisms related to tumour growth, vascular regulation and metabolism. A rapidly proliferating tumour commonly outgrows the tightly regulated vasculature that supplies O2 to normal tissues. This aberrant growth causes regions of hypoxia and anoxia within the growing tumour, resulting in HIF upregulation and necrotic regions. The growing tumour may also occlude the surrounding vessels. Tumours typically account for the resulting lack of O2 through upregulation of angiogenic factors.
However, as this neoangiogenesis is not correctly regulated, due to altered tumour growth rates, the growth of these vessels is typically not sufficient to adequately supply the tumour with O2 supply throughout its entire mass. The altered metabolic dynamics of the tumour may also contribute to an environment of low O2. As rapidly proliferating tumour populations prefer glycolytic respiration, with the result producing high amounts of lactate, the increase in intratumoural pH can also create an environment of pseudo hypoxic stress.
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Table 2: pO2 (%) Available at Tissues
Tissue or Organ p02 (mmHg) Oxygen Saturation (%) pO2 (%)
Atmospheric N/A 100 21.0
Arterial Blood 90.0 96.9 20.3
Vevous Blood 40.0 74.9 15.7
Intracellular 1.0-4.0 0.6-2.8 0.1-0.6
Mitochondria <1.0 <0.8 0.1
Brain 30.0-48.0 57.4-83.4 12.1-17.5
Lung 104.0-108.0 98.0-98.2 20.6-20.6
Skin 8.0 6.8 1.4
Dermal Papillae 24.0 42.7 9.0
Liver 55.5 88.5 18.6
Kidney 72.0 94.3 19.8
Muscle 28.9 54.9 11.5
Bone Morrow 51.8 86.2 18.1
Large Intestine 57.6 89.5 18.8
Small Intestine 61.2 91.1 19.1
3 -1 -1 Oxygen Saturation Equation: SO2 = (23,400 * (pO2 + 150 * pO2) + 1) References: [26-30]
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Hypoxia-inducible Factors
Hypoxia-inducible Factors (HIFs) are the main regulators of intracellular O2 tensions and have wide ranging impacts on cells undergoing hypoxic conditions. Hypoxia-inducible factors are extensively studied transcription factors in cellular and cancer biology due to their multilayered effects on cells, ubiquitous nature and prevalence in solid tumour types. Hypoxia-inducible factors (HIF) are a group of three (HIF-1,-2 and -3) highly conserved transcription factors that bind to the hypoxia response element (HRE) in the promoter regions of specific hypoxia-induced genes [13]. The HRE constitutes a promoter region that codes for many genes that aid in the survival of the cell under low oxygen conditions (hypoxia).
Belonging to the Per-ARNT-Sim (PAS) family of helix-loop-helix (HLH) transcription factors,
HIFs comprise of three members that recognise and bind the same promoter regions of the induced genes, displaying similar outcomes. Missense mutations in the hydroxylation domains of
HIFs are known to induce neuroendocrine tumours and renal carcinomas through the disruption of HIF regulation, resulting in these proteins being stabilised [31, 32]. Under normoxia, HIFs are constantly produced and degraded in the cytosol, with a half-life of ~4-6 minutes. As oxygen levels decrease, HIF proteins become increasingly stabilised and accumulate in the nucleus, binding to the HRE in the promoter region of the HIF-inducible genes. Most of these genes encode for proteins that aid the cell by altering metabolism, such as glycolytic enzymes and transporters upregulated by HIF-1α [33]. In instances of sustained hypoxia, HIF-2α is known to upregulate stem cell factors and drug efflux proteins, as well as erythropoietin [34, 35]. HIFs have been shown to be vital for neonatal development, particularly in the development of the embryonic heart through regulation of catecholamine homeostasis that protects against heart failure in early development. HIFs also play major roles in wound healing, muscle growth, cell
40 of 329 differentiation, cell proliferation and cardiovascular protection in incidences of hypoxia from reduced or occluded vessels, and as such may not be ideal for targeted anticancer therapy.
Regulation of the Hypoxia-inducible Factors Prolyl hydroxylases (PHD) are a class of dioxygenases that under normoxia promote the degradation of HIFs. While all 3 known PHD isoforms perform catalytic hydroxylation of different HIF subtypes, PHD2 is the isoform recognised as mainly regulating the degradation of
HIF-1α. PHD1 primarily controls the regulation of HIF-2α and is therefore expressed differently in various cell types and tissues. PHDs are dependent on three cofactors for their catalytic function: Fe2+; 2-OG; and O2. In this regard, they are classified as oxygen sensing enzymes and in normoxic conditions hydroxylate HIF-1α at proline residues 564 and 402, marking it for ubiquination by the von-Hippel Lindau protein (VHL) and destruction by the 26s protease.
Under hypoxic conditions, this reaction is inhibited and HIF-1α becomes stabilised to form an
HLH transcription factor that binds to the HRE. In cancer cells, the high levels of ROS production are thought to oxidise Fe2+ and 2-oxoglutarate ( 2-OG) to Fe3+ and 2- hydroxyglutarate ( 2-HG) respectively. The oxidation of iron renders the catalytic center of PHD non-functional, while 2-HG has been shown to actively inhibit PHD as well as restricting 2-OG for use as a cofactor [36]. There also exists a mechanism of cofactor competition deemed pseudohypoxia where other enzymes in the TCA cycle effectively “use up” all of the available 2-
OG (or alpha-ketoglutarate (α-KG)), resulting in the stabilization of HIF-1α.
HIF-1α is hydroxylated in normoxia at Pro-402 by PHD1, PHD2 and at Pro-564 by PHD1,
PHD2 and PHD3 to facilitate HIF ubiquination and degradation via interaction with VHL. Asn-
803 may also be hydroxylated by hypoxia-inducible factor 1-alpha inhibitor (HIF1AN) in normoxia, this interaction interferes with crebs binding protein (CBP)/p300 to prevent
41 of 329 transcriptional activation and this mechanism may be blocked by Clioquinol [37]. HIF-1α may also be S-nitrosylated at Cys-800, which increases its interaction with p300 required for HIF-1 α transcriptional activity [38].
HIF-1 requires phosphorylation before binding to the HRE and phosphorylation at Ser-247 by
CK1 impairs aryl hydrocarbon nuclear translocator (ARNT) binding to it. GSK3-B and PLK3 mediated phosphorylation promotes proteasomal degradation of HIF-1α, which is also
SUMOylated by SUMO1 during hypoxia and this may be enhanced by RWDD3 interactions.
HIF-1α may also be deSUMOylated by SENP1 which leads to greater stability and transcriptional activity. Ubiquination occurs primarily at Lys-532 but also at Lys-185, Lys-251,
Lys-297, Lys377, Lys-538, Lys-547 and Lys-709.
HIF-2α hydroxylation occurs at Pro-405 and Pro-531 by PHD1, PHD2 and PHD3. As with HIF-
1α, these prolyl hydroxylations cause interaction with the VHL tumour suppressor and ubiquination, facilitating degradation in normoxia. Hydroxylation at Asn-847 inhibits its interaction with CBP/p300 preventing transcriptional activation. HIF-2α can by phosphorylated at multiple sites within its c-terminal transcriptional activation domain (C-TAD), altering transcriptional activity [39].
The Aryl Hydrocarbon Nuclear Translocator (HIF-β) Subunit The aryl hydrocarbon nuclear translocator (ARNT or HIF-β) is a constitutively expressed protein that typically forms a complex with the aryl hydrocarbon receptor (AhR). HIF-β is found constitutively active in cells and is not considered oxygen-dependent, unlike the HIF- subunits.
ARNT/HIF- also binds to the HIF- protein subunits to form complexes as a heterodimer of
HIF-α/β to provide the functionally active HIF transcription factors. This binding occurs through the central PAS region once the HIF-α complex becomes stabilised under conditions of hypoxia.
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There are two proposed methods of HIF-αβ localisation in the nucleus. The first involves stabilisation leading to an accumulation of HIF-α/β in the cytosol that then travels through the nuclear pores and binds to the HRE to facilitate transcription. An alternative to this mechanism stated by Caniggia (2000) proposed that the two subunits accumulating in the cytosol caused a greater amount of both in the nucleus, independent of heterodimerisation [40] . The individual subunits have been shown to leak back out of the nucleus, suggesting that dimerization is required for sustainable nuclear localisation and transcription of HRE genes. This second mechanism is in some way supported by the studies of Moroz et al. (2009) who showed that
PHD2 expression, the enzyme regulating HIF- levels is found in poorly differentiated tumours also as predominantly nuclear [41]. This might suggest that HIF degradation occurs in the nucleus and not the cytosol as previously thought. This mechanism would also lead to a swifter response from both the stabilisation of HIFs and dimerization. It would also enhance HIF degradation in the event that normoxia was restored, above that which would occur if the regulation was solely in the cytosol.
Hypoxia-inducible Factor 3α and Negative Regulation HIF gene transcription does not appear to be integral to regulation of HIF activity because the
HIF proteins are continuously being translated, with stabilisation of the HIF-α protein subunits determining the HRE mediated levels of gene expression. While this mechanism may appear wasteful – HIF-α proteins being continuously transcribed and translated, only to be degraded – it would serve to increase the responsiveness of the HRE regulated genes during acute hypoxia and aid in enhancing cell survival. However, the post-translational regulation of HIF-α protein involves several different mechanisms.
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The structure of the HIF-α protein contributes to the regulatory mechanisms by containing different regulatory domains. The central PAS region facilitates both dimerization with HIF-β and binding to the HRE DNA sequence. The PAS domain also acts as a HIF negative regulatory region by competitive binding with factors such as HIF-3α and IPAS that inhibit HIF activity
[42]. The HIF alpha-3 subunit lacks the transactivation domain found in factors containing either the alpha-1 or alpha-2 subunits such that factors containing the alpha-3 subunit are negative regulators of hypoxia-inducible gene expression. Multiple alternatively spliced transcript variants have been found for the HIF-3 α gene.
Hypoxia-inducible Factors and Role in Cancer Metastasis The HIF transcription factors regulate a vast array of genes encoding proteins downstream of hypoxic signaling that contain the HRE in their regulatory regions and include several key factors relevant to cancer staging, survival and progression (Table 3). Not surprisingly, these genes are typically those that would aid in cellular survival mechanisms in the event of low oxygen concentrations such as those involved in metabolism, apoptosis, angiogenesis, oxygen and nutrient delivery, as well as adaption to hypoxic conditions (Figure 1). The atypical growth of blood vessels contributes to the tumour microenvironment having inconsistent oxygen concentrations. HIFs are known to regulate VEGF and in syndicate with other melanoma expressed proangiogenesis and lymphogenesis molecules (Ang2, bFGF, c-MET, HGF, PAF,
LPA, IL8) that all contribute to metastasis.
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Figure 1: Tumour Hypoxia and Constitutive HIF Expression Contributes to Metabolic Reprogramming and Metastasis
PGC-1αmediated OxPhos activation and ROS generation promotes the metastatic cancer cell phenotype. Hypoxic non-metastatic cancer cells maintain a diminished level of mitochondrial metabolism. However, hypoxia causes PGC-1αand HIF-1α, HIF-2αoverexpression which induces in pro-metastatic cells the generation of a higher number of mitochondria, increased OxPhos flux for ATP synthesis and increased ROS levels, all leading to the epithelial- mesenchymal transition (EMT) and formation of highly metastatic cells. Abbreviations: OxPhos, oxidative phosphorylation; ROS, reactive oxygen species; HIF-1, Hypoxia-Inducible Factor 1- alpha; PGC-1, Peroxisome Proliferator activated Receptor Gamma Co-activator 1-alpha.
Melanocytes, ductal and lobular cells originating in the neural crest predisposes these cells to adopt a migratory phenotype. Several groups [43-45] have discussed this issue and have shown
45 of 329 that the expression of certain cell surface adhesion molecules (including MCAM/MUC18, L1-
CAM, ALCAM, NCAM, N-cadherin, VCAM, ICAM, CEA-CAM and VE-cadherin) aid the metastatic phenotype of epithelial-derived cells by enabling their motility, intravasation and vascular mimicry [19]. The same molecules allow for clumping in the bloodstream and at the secondary sites, protecting the inner cells from turbulence and allows for invasion into the parenchyma. Expression of MCAM/MUC18 has been shown to positively correlate with melanoma progression, with only 50% of nevi as opposed to 90% of metastatic melanoma tumours being positive. Patients at stage IV melanoma with MCAM/MUC18 expression in the bloodstream have a much poorer prognosis [46]. This mechanism is known to be supported by
HIF-2α through its up-regulation of stem cell factors (Oct4, SOX2, C-Myc, NANNOG) and extracellular matrix proteins (MMP-9, MMP-2 and carbonic anhydrase IX (CX-IX)) [47]. A functional conduit for metastasis is also provided by HIFs through the growth of new blood vessels (supported by VEGF and Ang-2 production). The culmination of these mechanisms results in a cell phenotype that is dedifferentiated, able to move through the extracellular matrix, and has the facility to easily metastasise.
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Table 3: Genes Inducible by HIFs that are Involved in Promoting Cancer Malignancy and Migration
Function Growth Oxygen/Nutrient Migratory, EMT Regulator/Apoptosis Metabolism Delivery and Stem-Like Miscellaneous Glucose transporters Insulin-like growth factor 1/2/3/4 VEGF Oct-4 Cyclooxygenase 2 IGF binding proteins 1/2/3 Adenylate kinase-3 VEGF-R Sox-2 Presenilin 1/2 p21 Aldoase Ang-2 Myc VL30
NIP3 Enolase 1 EPO Klf-4 p35
NIX Hexokinase 1/2 Transferrin NANNOG ETS-1
RTP801 Phosphoglycerate kinase-1 Tyrosine hydorxylase MMP-2/9 DEC 1/2 Collagen ENG Phospohofructokinase Adrenergin receptor Vimentin prolylhydrase
MOR1 Pyruvate kinase Heme oxidase c-Met
MDR-1 6-phosphofhructo-2-kinase Nitric oxide synthase AMF
Lactate dehydrogenase Endothelin-1 LRP-1 Glyceraldehyde-3- Plasminogen activator phosphate-dehydrogenase inhibitor-1 TGF-a
Carbonic anhydrase Adrenomedullin UPAR
Leptin MIC-2
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Hypoxia-inducible Factors Induce Changes in Cancer Metabolism Alterations in cellular energetics relating to cancerous tissues have long been known. The
Warburg hypothesis suggested that the root cause of cancer was inefficiency in cellular respiration caused by damage to the mitochondria. Cancerous tissues were thought to rely heavily upon glycolysis over the more efficient combination of oxidative phosphorylation
(OxPhos) and electron transport train (ETC) even in the presence of plentiful oxygen supplies.
This is no longer considered the case. In fact, tumour populations are commonly so difficult to eradicate due to their non-preferential use of metabolic substrates and adaptability depending on the conditions of their environment [48]. Oxidative phosphorylation in cancerous cells may be restricted by the inhibition of aconitase (for converting citrate to isocitrate) due to high levels of endogenous reactive oxygen species (ROS). This effectively limits OxPhos production in favour of the direct oxidation of pyruvate to lactate. This mechanism is markedly less efficient than electron transport and places a large demand for glucose on the rapidly respiring and dividing cancer cell population.
High levels of ROS are a common phenomenon in cancer cells, caused either by altered citric acid cycle (TCA) metabolic function or mutations in either tricarboxcillic acid (TCA) cycle or
ETC enzymes. High levels of ROS actively inhibit PHDs and promote HIF stabilisation. ROS oxidises Fe2+ and 2-OG to Fe3+ and 2-HG, restricting their availability for activating PHDs, the master regulators of HIF turnover. Molecular oxygen is also oxidised to superoxide that spontaneously reacts to peroxide, further reducing the available O2 to both PHD and for use in the TCA cycle. Interestingly, Niecknig (2012) provided data showing the HIF suppression by peroxide and detailed the reduction of HIF transactivation and HIF gene targets under constant
48 of 329 treatment with H2O2. The data from these studies suggested that the role of ROS in HIF regulation is multifactorial and not simply a promoter of HIF regulation through PHD inhibition.
However, these results are contradictory to those of Page et al. (2008) who showed that HIF-1α stability was increased through Ang-mediated generation of peroxide and a reduction in ascorbate, causing PHD inhibition.
Alpha-ketoglutaric acid and its anion alpha-ketoglutarate (α-KG, also commonly known as 2-
Oxoglutarate (2-OG)) are important intermediates in the TCA cycle and are also required as a cofactor for the correct functioning of the PHDs. A key feature of α-KG in the TCA cycle is that anaplerotic reactions can occur via the glutamate dehydrogenase (GHD) mediated transamination of glutamate into α-KG as an important mechanism for producing the ATP required for energy in cancer cells due to the truncation of oxidative phosphorylation and upregulated intake of glutamine [49]. Another important feature at this stage of the TCA cycle is that the reverse reaction is also possible, involving isocitrate dehydrogenase (IHD2) catalysing the reaction of α-
KG to citrate, reducing α-KG availability to PHD2 as a cofactor, and making citrate available for the production of acetyl-CoA to facilitate essential fatty acid synthesis.
Succinate dehydrogenase (SDH) is a tetrameric mitochondrial transmembrane protein involved in the TCA cycle, the reduction of FAD2+ to FADH2 and the formation of guanine tri-phosphate
(GTP), as well as comprising complex II of the ETC. In cancer, succinate dehydrogenase complexes (SDHC and SDHD), the two subunits on the intermembrane side, may become mutated causing a malfunction in the addition of electrons to ubiquinone (coenzyme Q10) and contributing to the production of ROS. Interestingly, subunits of SDH have been recognised to
49 of 329 function as tumour suppressors and mutations in either the D, C or B subunit have been shown to promote tumorigenesis [49]. The loss of SDH has been shown to stabilise HIF in normoxic conditions via the pseudohypoxic inhibition of PHDs caused by the build-up of succinate.
Treatment of SDH mutant cells with surplus α-KG can negate the competitive inhibitory effects caused by the build-up in succinate and restores PHD function to degrade the HIFs under normoxia [50].
Octamer-Binding Transcription Factor 4 (Oct4) Also known as POU5F1, Oct4 is a homeodomain transcription factor encoded by the POU5F1 gene on chromosome 6. Oct4 is chiefly involved in the maintenance of embryonic stem cells.
Oct4 is part of a family of transcription factors that bind the octameric DNA nucleotide sequence to facilitate gene transcription. Regulation of Oct4 is required to maintain a pluripotent phenotype, with knockdown of expression in mice embryos undergoing differentiation. Oct4 expression is also associated with advanced and poorly differentiated tumors and represents a negative indicator of prognosis.
Oct4 is recognised as one of the “Yamanaka Factors” and with three other transcription factors,
Sox2, Klf4 and c-Myc, is sufficient to induce cellular reprogramming into a pluripotent state.
Further refinement into induced pluripotent stem cells (iPSC) techniques determined that only
Oct4 and Klf4 were required to dedifferentiate adult neuronal stem cells. Ultimately, it was shown that only Oct4 was required for this transformation. Oct4 is therefore recognised as the most important of only four transcription factors that are vital to maintain stem cells and are able to dedifferentiate mature cells and induce pluripotency.
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HIF Regulates Oct4 as a Major Factor Promoting EMT and Cancer Stem Cell Production. Intratumoural hypoxia and HIFs contribute to more migratory and stem-like cell population, at least in part, by upregulating Oct4 expression, leading to the dedifferentiation of tumour cells.
HIF-1α has typically been implicated in primarily the acute response to hypoxia with metabolic change (Figure 1). During extended periods of hypoxia, HIF-2α becomes stabilised and has been shown to upregulate for all of the iPSC inducers or “Yamanaka Factors” (including Oct4), as well as others such as homeobox protein NANOG (NANOG). The promoter region of the Oct4 gene contains several HRE elements that HIF bind to in order to facilitate transcription and translation of the Oct4 protein, demonstrating the regulation of Oct4 via hypoxia through HIFs.
As a result of this, many different tumour types develop characteristics resembling human embryonic stem cells (hESC) when measured for stem cell markers. Furthermore, it appears that when HIFs are combined with the iPSC inducers that they are efficient at generating iPSC-like colonies that are also highly tumourigenic.
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NSAIDs as a Cancer Treatment
This section was extensively reviewed in the publication: Hitting the Bull’s-Eye in Metastatic Cancers-NSAIDs Elevate ROS in Mitochondria, Inducing Malignant Cell Death. Stephen J. Ralph, Rhys Pritchard, Sara Rodriguez-Enriquez, Rafael Moreno-Sanchez and Raymond K. Ralph. Pharmaceuticals, 2015; 8:62-106
Introduction NSAIDs are widely used medications the world over. Medically, their use typically pertains to the reduction of pain, a decrease in fever, anti-inflammatory properties and certain classes for their ability to prevent blood clots, heart attack and stroke. They are typically classified as cyclooxygenase (COX) inhibitors and mediate pain through their ability to inhibit prostaglandin synthesis, reducing pain through complex biochemical processes. The most common of the
NSAIDs are available as over-the-counter medications in most countries, with several others solely for prescription use. NSAIDs typically vary widely in their ability to inhibit either (or both) of the two COX isoforms (COX-1 and COX-2). As earlier non-specific COX inhibiting
NSAIDs are typically more associated with gastrointestinal disturbances, this led to the synthesis of a variety of COX-2 selective NSAIDs being produced [51]. However, as certain cancer types have markedly upregulated COX-2 enzyme function (up to 10-fold or greater), it was noted that these classes of NSAID also appear to be effective as a cancer treatment [52, 53].
It should be noted that the use and especially prolonged use of NSAIDs had been associated with several contraindication and adverse events. The effects are wide-ranging, but consist chiefly of renal, hepatic, gastrointestinal and cardiovascular adverse events. Several less common side- effects include erectile dysfunction, photosensitivity, allergy and hypersensitivity, irritable bowel
52 of 329 and high blood pressure. Note also that several Coxibs (an umbrella term for selective COX-2 inhibitors) were removed from the market due to a high rate of cardio thrombotic events shortly after their release [54, 55]. These increased risks (particularly from the Coxibs) are the result of an increase in thromboxane levels being unbalanced by prostacyclin which is reduced by COX inhibition. It is therefore paramount that any short or long-term use of NSAIDs is closely monitored by a physician. It is recommended that renal and hepatic function in tested before the implementation of any regiment involving NSAIDs and that the patient does not have a history of heart disease or stroke.
Mechanisms of Anticancer Action It is commonly reported that the mechanism of cancer reduction witnessed due to the use of
NSAIDs is due to COX inhibition [56]. While this may account for some of the events occurring in vivo, a lot of recent evidence states that this may not complete the entire story and that several other mechanisms may be at play. Comparisons of the relative anticancer activities and structure/function of the different NSAIDs have shown that their actions as anticancer agents usually involve use at higher or lower drug concentrations than those used to inhibit the COX enzymes, with the anticancer effects mainly independent of COX inhibition. Furthermore, several studies have NSAID derivatives that are effectively non-COX-2 inhibitory, have witnessed similar anti-neoplastic effects, as well as experiments on COX-null animals [57, 58].
The relative anticancer activities of different NSAIDs have been shown to vary considerably.
Different cancer cell types and stages appear to alter the efficacy of NSAIDs dramatically. This is further compounded without an absolute understanding of precisely how NSAIDs work. The current major mechanisms of NSAID function as anticancer agents are detailed below, along with the current preclinical and clinical data.
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Figure 2: Anticancer Mechanisms of NSAIDs The anti-cancer mechanisms of NSAIDs are multifaceted due to their antipyrogenic and COX-2 inhibiting functions having multiple effects on cell metabolism, angiogenesis and immune regulation.
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COX Inhibition and VEGF Cyclooxygenases (also commonly known as prostaglandin-endoperoxide synthases (PTGS)) belong to a small family of enzymes responsible for the formation of thromboxane, prostaglandins and prostacyclin (prostanoids) from arachidonic acid. The two COX enzymes differ dramatically in their cellular functions. COX-1 is constitutively expressed and found in most tissues and plays a role in several housekeeping functions, including the secretion of prostaglandins from the intestinal mucosa to prevent damage from the acidic conditions found in the gastrointestinal system. It is for this reason that the COX-1 selective NSAIDs (such as aspirin) are commonly associated with more prevalent gastrointestinal side-effects, such as ulcers. The discovery of the COX-2 isoform allowed for the generation of COX-2 specific
NSAID variants that greatly reduced the risk of gastrointestinal side-effects. However, this reduction in gastrointestinal side-effects did not translate to the other side-effects outlined above.
The ratios of COX-1 and COX-2 vary widely in inflamed vs normal tissue, perhaps explaining the relatively increased levels of COX-2 expression as a marker of cancer and metastatic progression. Reprogramming of the immune response to cope with sustained levels of inflammation is common in advanced stage and metastatic cancers, providing one mechanism whereby COX-2 selective NSAIDs may function better in the more advanced cancers [59].
Inhibition of the COX-2/PGE pathway found upregulated in a variety of cancer types is commonly associated with metastatic progression, involved in the growth of tumours and dissemination pathways including; carcinogenesis, metastatic spread and metabolism [60]. An
55 of 329 interesting mechanism has been postulated due to NSAIDs being used to treat deep vein thrombosis in cancer patients. It is believed that abnormal levels of tissue factor (TF) that is secreted by the metastatic cancers aids in shielding the circulating tumour cells in the blood stream and that the activation of coagulation promotes platelet aggregation, effectively shielding the metastatic cells from natural killer (NK) cell detection [61]. However, if this was a major mechanism for drug action, it would be more obviously held in common with the use of platelet inhibitors such as aspirin, which is not the case. In fact, it is observed that the more COX-2 selective drugs are better suited to showing antineoplastic capacity [56, 62].
The anti-inflammatory action of NSAIDs represents another possible mechanism for their antineoplastic activity. As cancers promote an anti-inflammatory state, with this state being outside of the positive benefits of inflammation commonly used by the immune system, reactivation of a more pro-inflammatory state by NSAIDs could prove beneficial. There are some studies that support this notion. By reducing inflammation and inhibiting the release of bradykinin and inhibiting thrombocytes, as well as chemotaxis of leukocytes, NSAIDs may help in modifying the pre-metastatic niche and contribute to inhibiting metastasis [63].
The Pro-apoptotic action of NSAIDs NSAIDs have also been shown induce apoptosis in a variety of different cancer cell lines derived from multiple sources. This induction of apoptosis has been demonstrated to be unrelated to
COX inhibition. Apoptosis has also been shown to be the major mechanism of chemoprevention in familial adenomatous polyposis (FAP) patients. The exact mechanism(s) of NSAID-mediated apoptosis in cancers is still highly debated. The dysregulation of the Wnt/-catenin signaling pathway may play a role [64]. Studies performed with both celecoxib and exisulind – the sulfone
56 of 329 derivative of sulindac – have been shown to suppress oncogenic b-catenin signaling [65]. This in turn affects the stem like portion of tumours reducing their plasticity and ability to renew by inducing apoptosis [66]. Other NSAIDs, such as aspirin, are shown to inhibit nuclear factor kappa beta (NF-κB) through ATP-competitive inhibition of inhibitor of nuclear factor kappa beta
(IKKB), an upstream regulator of NF-κB [67, 68]. This inhibits the cancer cells ability to undergo unchecked growth and proliferation, as well as mitigating inflammation and oxidative stress that again leads to apoptosis.
Non-COX-2 inhibitory NSAID Derivatives with Anticancer Activity Due to cardiovascular toxicity and side effects from the use of Coxibs, several groups have attempted to use COX-2 independent derivatives such as 2,5-dimethyl-celecoxib (DMC), which lacks COX-2-inhibitory activity [52] When testing on various hematologic cancer cell lines
(U937, Jurkat, Hel, Raji, and K562), Sobolewski et al (2015) found that DMC was more effective than celecoxib at inducing apoptosis in the lines tested. Cell death was also deduced to be associated with Mcl-1 protein expression, a protein closely associated with the PI3K/Akt signaling axis that is vital among solid tumours including melanoma and breast cancer [58].
Furthermore, DMC was seen to induce endoplasmic reticulum (ER) stress, binding immunoglobulin protein (GRP78) expression and an alteration of the cell cycle with progression halting at the G1/S checkpoint. The same group also found that c-Myc and cyclin D1 were also downregulated, while an upregulation of CDKN1B (p27), a known inhibitor of cell cycle progression was observed.
Lastly, groups that have modified the NSAIDs have typically found that they have even more potent antineoplastic potential – a prime example of this is the DMC derivative of celecoxib, that has an IC50 value at least half that of celecoxib and does not greatly affect COX enzymes. It has
57 of 329 been seen that the structural requirements required to induce apoptosis are distinctly different from those that are required for COX inhibition. Notably, computer modelling has found a positive correlation between electrostatic potential of the heterocyclic head chain and apoptosis inducing potential (as seen with the additional methyl group in DMC) [69]. These interactions are counter to those required for COX binding and demonstrate that further molecules may be identified that have an increased effect on inducing cancer cell apoptosis and reducing negative side-effects [70].
Carbonic Anhydrases can be Inhibited by NSAIDs Several of the carbonic anhydrases can be inhibited by celecoxib in the low nanomolar range, far below celecoxib’s IC50 for COX-2 inhibition. As carbonic anhydrases assist in regulating cell homeostasis in respect to acid-base balance, they seem particularly crucial to cancerous cell in surviving and adapting to hypoxic and hypoglycemic stresses. The expression levels of carbonic anhydrases also correlate with tumour aggressiveness and poor patient survival rates [71].
Other Targets of NSAIDs Another target of celecoxib is the sarcoplasmic/ER Ca2+ ATPase (SERCA). Binding of celecoxib
(or its non-COX-2 inhibitory derivative DMC) to the SERCA, leads to a rapid release of calcium from the endoplasmic reticulum (ER) and activates the ER stress response, inducing apoptosis. Other mechanisms of NSAIDs induced apoptosis in a variety of different cell lines include; an increase in BAX and BAK levels, interaction with direct inhibitor of apoptosis protein (DIABLO), direct interact with Bcl-2, the extrinsic death receptor pathway, cell cycle arrest through inhibition of STAT3 phosphorylation, and dephosphorization of Akt and ERK2.
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Cell Cycle and Metabolism As well as their inhibition of COX enzymes and direct effects on the induction of apoptosis, many groups document NSAIDs as having powerful anti-proliferative effects on a variety of cell lines. Sulindac and its derivative NOSH-sulindac have been demonstrated to markedly inhibit the growth of a variety of cell lines with the derivate displaying efficacy at potencies 1000 - 9000 times higher than the parent molecule at inhibiting cancer cells at the G2/M checkpoint [72, 73].
Other studies reveal that 20 µg/ml celecoxib was sufficient to induce cell cycle arrest at S-phase and that this decrease was time dependent with an increase witnessed between treatment at 24 and 48 hours [74]. Celecoxib treatment was also found to down regulate MMP-2 and MMP-9 while upregulating RECK that not only increases apoptotic induction but also inhibits migratory cancer cells from forming metastasis [75, 76].
Many studies have used metabolic assays including MTT, DTT and crystal violet to determine
NSAIDs’ effects on cellular respiration. Zhou et al (2015) reveal that over a range of concentrations 0 - 80 µg/mL, celecoxib significantly inhibited the proliferation of MG-63 cells in a time and dose dependent fashion [77]. Ibuprofen treatment showed a significant reduction in the survival and metabolic processes in a variety of human prostate cancer cells [78]. Similar findings have also been documented for lung carcinoma [79], colorectal cancers [80], prostate cancers [81], glioma [82] and breast cancers [83], among a variety of NSAIDs tested to various efficacy.
Celecoxib’s Proposed Mechanism(s) of Anticancer Activity Previous reports have proposed a number of other targets for Celecoxib that may contribute and explain its anticancer actions besides COX-2 inhibition [84] including PDK-1 [85]; extrinsic apoptosis induction through DR5 and activation of caspase-8 [86]; intrinsic apoptotic induction
59 of 329 through mitochondrial mediated mechanisms [87] possibly involving direct interaction with the
Bcl-2 family [88]; activating ER-stress responses [89, 90]; affecting ion channels [91]; inhibiting
Intracellular Transporter Ca2+-pump from the Sarco-Endoplasmic Reticulum (SOCA, [92]); inhibiting JAK2/STAT3 phosphorylation [93] and the carbonic anhydrase family [71]. However, the results presented in the final chapter suggest that Celecoxib directly inhibits mitochondrial respiration and induces excess mitochondrial superoxide production leading to apoptosis. This may help to explain several of the other proposed mechanisms above, particularly those involving ER stress related responses and apoptosis. The ER stress response in response to an overload of Ca2+ is closely related to the levels of intracellular ROS production [92]. In fact, these processes are so closely linked that there is debate regarding which is the first trigger of apoptosis. In relation to apoptosis, it is possible the celecoxib does have some effect on anti- apoptotic proteins such as those in the Bcl-2 family. However, it is also possible that this is a downstream event, apoptosis being cause by the build-up of ROS triggering the intrinsic apoptotic cascade. When considering the actions of celecoxib in treating patients and in vivo, it is most likely that several of these mechanisms work in concert, to produce the antineoplastic effects witnessed.
The Role of ROS in the Mechanisms of NSAID Action and Influence on Cell Cycle in Cancer Cells The generation of ROS shown by many groups as either directly or indirectly induced by treatment with the NSAIDs may explain their effects on various stages of the cell cycle. Recent studies have documented a crucial involvement of ROS and enzymes required for ROS producing NADPH oxidase (NOX) complexes. ROS have been shown to influence cell cycle progression through the phosphorylation and ubiquination of CDKs and other cell cycle
60 of 329 regulatory molecules. The various effects of high ROS levels on the stability of DNA may also explain why many studies [94] have shown that NSAIDs can halt cell cycle progression at the
G2/S regulatory check point, this check being primarily responsible for the integrity of DNA before cytokinesis [95]. The elevation of ROS above normal levels has been shown to trigger a range of cellular responses including proliferation, cell cycle arrest, senescence, apoptosis and necrosis that is heavily dependent on the amount of ensuing oxidative damage, the time of exposure and the cell type [124].
Cyclin-dependent kinases (CDKs) of the serine/threonine family of kinases represent a specific set of enzymes that are required to control the major cell cycle checkpoints (G1, G1/S, S or
G2/M). Cyclin/CDK activity is regulated by multiple processes including; transcription, translation and ubiquitin-mediated degradation. CDK activity is also regulated by phosphorylation and its removal by CDC25 phosphatases and by binding of the cyclin-dependent kinase inhibitors CKIs. ROS have been shown to influence all of these processes and in turn affects cell proliferation through interaction with second messengers and cell cycle enzymes including p27, p21 and various MAP kinases [96]. ROS are also able to affect ubiquination and phosphorylation events, further compounding their role as cell cycle regulators.
The inhibition of ROS production by NOX4 can lead to the hyperphosphorylation and inactivation of CDC25 in melanoma cells. One study demonstrated the ability of ROS to abrogate the cell cycle through the use doxorubicin (DOX), a well know chemotherapeutic that induces apoptosis by promoting mitochondrial superoxide production [97]. The levels of superoxide were found to decrease ERK1/2 phosphorylation and their activity, in turn enhancing the ubiquination of Bcl-2. ROS was demonstrated to affect ubiquination in two different ways
[98]. Firstly, through phosphorylation directly affecting cell cycle and apoptotic proteins, and
61 of 329 secondly, by upsetting the redox balance affecting the negative feedback of the OxPhos system and S-thiolation of ligases [99, 100]. Ubiquination is essential for the regulation of CKI expression, namely p21, p27 and p57, and adequate regulation is therefore vital to normal cell cycle function.
Consistent over production of p21 has been shown to induce a senescent phenotype in both cancerous and somatic cells and is accompanied by increased levels of ROS [101]. Furthermore, sustained levels were shown to induce apoptosis in p53 null sarcoma cell lines, a process that was reversed through treatment with antioxidants [102]. Further studies using Arecoline, an inducer of ROS, have demonstrated regulation of the levels of both p21 and p27 causing cell cycle arrest at the G1/S checkpoint, supporting both the direct effects of p21 and p27 phosphorylation and the increase in DNA damage caused by rapidly elevated ROS levels as the reason for lack of cell cycle progression at this point in the cycle [103, 104].
NSAID Effects on ROS Production and the Cellular Antioxidant Defense Systems The evidence is clear from many studies that one of the first intracellular events to occur in
NSAID treated cancer cells involves metabolic changes (Figure 3), specifically in metastatic cells by decreasing levels of reduced glutathione (GSH) and increasing ROS production. This leads to an increased pro-oxidative state, and is followed by a decline in mitochondrial membrane potential (Δψm), release of cytochrome c and finally, apoptosis [105-107]. The data also indicates that increased ROS itself also leads to increased EGR-1, followed by p75(NTR) and NAG-1 expression, providing a feed-forward amplifier circuit promoting cancer cell death.
Moreover, structural modeling shows that sulindac or celecoxib can bind into the hydrophobic cleft formed by the BH3 domain of the pro-survival protein, Bcl-xL [108]. This observation is consistent with reports that the NSAIDs destabilise the pro-survival state by blocking and
62 of 329 promoting degradation of Bcl-xL and Bcl-2 to release the pro-death BH3 domain only proteins,
BID or BIM, thereby enhancing BAK or BAX activation, mitochondrial outer membrane pore
(MOMP) formation and apoptosis of cancer cells [109, 110]. The process of activation of
MOMP has been reviewed recently [111] and it is one essential component of the death-inducing mechanisms activated by the NSAIDs on cancer cells. The second component necessary for the full mitochondrial membrane permeability transition (MPT) is for the inner mitochondrial membrane channel or permeability transition pore complex (PTPC) to also become activated and is discussed in detail below.
The earliest actions of NSAIDs in cells are detected as destabilizing the redox balance and antioxidant defense mechanisms of the thioredoxin and glutathione (GSH/GSSG ratio) systems, resulting in a greater pro-oxidative state with increased ROS production. Several studies have shown that NSAIDs, such as aspirin and acetaminophen, in their reported therapeutic and cytotoxic concentration range, inhibit the enzymes involved in cellular redox control of both the thioredoxin [112] and glutathione systems, including glutathione reductase [113] and glutathione-S-transferase, resulting in increased GSSG and decreased GSH [114]. The net effect accentuates the pro-oxidative state and promotes the secondary increase in ROS production that enhances cancer cell death. In fact, the anticancer activity of a broad range of NSAIDs tested on human lung or leukemia cell lines correlates with their ability to be transported into cancer cells and inhibit glutathione-S-transferase [115]. The mitochondrial glutathione pool (~5 mM) is an essential redox system for protecting against oxidative damage, both by direct reaction with ROS or reactive nitrogen species (RNS) and as an electron donor for the antioxidant
63 of 329 thioredoxin/glutathione/glutaredoxin/peroxiredoxin systems (reviewed in [116]). Hence, the glutathione redox system is crucial for cancer cell survival (reviewed in [117]).
Figure 3: NSAIDs Effects on Metastatic Cancer Mitochondria and Antioxidant Systems NSAIDs as mitochondrially targeted drugs in metastatic cells. After NSAID treatment, a heightened pro-oxidative status is induced in the metastatic cells, but not in non-metastatic tumor cells. The events ensuing in the metastatic cells include decreasing levels of GSH, critical changes in the Cysteine-thiol/disulfide bond status of key proteins and increasing ROS production, which is followed by Ca2+ overload, collapse of Δψm, opening of the PTPC, release of cytochrome c and the other apoptosis-inducing factors leading to the death and elimination of these cells. Abbreviations: NSAIDS, non-steroidal anti-inflammatory drugs; GSH, reduced glutathione; ROS, reactive oxygen species, PTPC, mitochondrial permeability transition pore complex, MPT, mitochondrial membrane permeability transition.
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Preclinical and Clinical Data Supporting the Anticancer Activity of NSAIDs. Several pre-clinical studies with human xenografted cancer cell lines treated with NSAIDs have been reported. Aspirin (200 mg/kg/day) decreased RKO colon cancer cell growth and induced apoptosis. Combining flurbiprofen (100 ppm; 100 mg/Kg food) and sulindac (200 ppm) added in the diet of xenografted mice was more effective than either drug alone at slowing growth of the
SKOV-3 human ovarian carcinoma [118]. Diclofenac (18 mg/kg body weight) given intraperitoneally twice a week for 4 weeks or indomethacin (2.5 mg/kg) daily in their drinking water slowed the growth of HEY ovarian cancers [119]. Studies of human prostate cancer cell lines showed that sulindac was effective at arresting growth of LNCaP in nude mice [66].
Combination therapy in a Phase II study of carboplatin plus celecoxib in heavily pre-treated recurrent advanced stage ovarian cancer patients demonstrated that the treatment was well tolerated with promising response rates close to 30%, including 3 complete and 10 partial responses with median progression free survival and overall survival of 5 and 13 months, respectively [120]. Note that this study focused on advanced stage heavily pre-treated, recurrent cancers. In contrast, when used as a first-line therapy in a randomised Phase II trial of Stage IC to IV epithelial ovarian cancers, no significant difference between docetaxel and carboplatin versus docetaxel and carboplatin plus celecoxib was found [121]. It is likely that this occurred because these cancers had not yet progressed to the point where they had become pro-oxidative with higher PGC-1α/HIF-1α levels, increased OxPhos and greater ROS production. Hence, the
NSAIDs may be better suited for use in targeting more advanced highly metastatic cancer cells
65 of 329 after selection from prior rounds of chemotherapy, since the latter treatments engender higher pro-oxidative states than those found in early stages of cancers, before therapy.
Longitudinal Studies of Cancer Treatment with NSAIDs. There are several longitudinal studies which outline the benefit of either pre or postoperative use of NSAIDs to reduce particularly metastatic cancers. A recent (2015) meta-analysis, the largest of its kind to date performed, analyzed 16 studies from various cancer origins and a total of
202780 participants showed a reduced risk of distant metastasis in almost all cancer types. A large study comprising 2392 patients diagnosed with UADT cancers documents increased survival rates of Aspirin, COX-2 inhibitors and other NSAIDs when observing patients for a period of 94 months [122]. Aspirin treatment alone has been shown to reduce the risk of cancer related deaths by about 7%. These studies and others [123-125] demonstrate that NSAID prescriptions after cancer diagnosis was associated with a reduced all-cause mortality among cancer patients. NSAIDs have been demonstrated to reduce the risk of colorectal cancers, with celecoxib currently FDA approved for treatment [126]. As part of the Repurposing Drugs in
Oncology (ReDO) project, data regarding several of the NSAIDs have been gathered in studies that gauge their efficacy in treating various cancers. Diclofenac was shown to be effective in reducing the rates of fibrosarcoma, colorectal cancer neuroblastoma, ovarian cancer and serval others, but had a particularly significant effect on non-small cell lung cancers.
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The Role of Mitochondria in Cellular ROS production.
This section was extensively reviewed in the publication: NSAID celecoxib: a potent mitochondrial pro-oxidant cytotoxic agent sensitizing metastatic cancers and cancer stem cells to chemotherapy. Stephen John Ralph, Sam Nozuhur, Rafael Moreno-Sánchez, Sara Rodríguez-Enríquez, Rhys Pritchard, J Cancer Metastasis Treat 2018;4:49
The Mitochondria The function of mitochondria in cell biology is considered exoteric and will not be covered in detail here. Basically, mitochondria are cell organelles ubiquitously found in almost all cell types and are chiefly responsible for the production of cellular energy as ATP from respiration.
Proposed to have originated as prokaryotic cell types (known as the Endosymbiotic theory), mitochondria evolved as endosymbionts taken into eukaryotic cells and are now vital to their function. Mitochondria possess their own DNA (mtDNA) mainly related to the expression of proteins, tRNA and enzymes. The total oxidation of pyruvate allows for the production of ATP through utilization for oxidative phosphorylation and the ETC during which oxygen is the final electron acceptor, with ATP amounts up to 15 times more efficiently produced than that provided by anaerobic metabolism. This process is also known to generate the oxygen radical superoxide as a by-product, occurring during cytotoxic stress, aging, ischemic reperfusion and the generation and progression of cancer. However, due to the oxidative stress that this induces, particularly in metastatic cancers, it becomes possible to use this to advantage by further increasing intracellular ROS production, overloading these cancer cells to eliminate them.
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Figure 4: Intermittent Hypoxia and Effect on Metastatic Cell Mitochondria and Apoptosis Intermittent hypoxia within the primary tumor microenvironment as a driver of mitochondrial ROS production and metastatic reprogramming. Mitochondrial ROS is produced extensively in cells undergoing rounds of intermittent hypoxia. In a similar manner to ischemia/reperfusion in normal cells, the intermittent hypoxia of early primary cancer cells causes readjustments in redox homeostasis by increasing ROS activated NRF2 release from the outer redox hub (KEAP1/PGAM5) on the mitochondria, NRF2 transport to the nucleus and transcriptional activation of a large number of antioxidant defense response, including the GSH and Trx systems to counteract and detoxify the ROS. In addition, Bcl-2 and Bcl-XL are stabilized to promote cell survival under the conditions of pro-oxidative stress. NRF: nuclear respiratory factor; ROS: reactive oxygen species; Trx: thioredoxin; GSH: reduced glutathione
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Celecoxib’s non-COX-2 Inhibitory Derivative DMC is a more Potent Anticancer Drug Previous studies have reported that Celecoxib is cytotoxic for cancer cells independent of its effects on cyclooxygenase and particularly as the non-inhibitory analogue Dimethyl celecoxib has shown greater anticancer activity [127]. Similar to the other NSAIDs, structurally related homologs of celecoxib exist with even greater potency as anticancer agents, but they do not bind or inhibit COX’s. For example, dimethyl celecoxib is a non-COX-2 inhibitory celecoxib derivative containing an additional methyl group compared to the prototypic 3-methylcelecoxib.
Zhu et al (2002) showed that modifying the side groups and enlargement of the hydrophobic aryl moiety by adding the second methyl group (as 2,5-dimethylcelecoxib or more specifically 4-(5-
(2,5-Dimethylphenyl)-3-(trifluoromethyl)-1H-pyrazol-1-yl)benzenesulfonamide) promoted apoptosis more effectively than celecoxib [85]. This mechanism contrasts with the action of celecoxib in COX-2 inhibition, which has stringent requirements regarding the stereo-specific arrangement of the 3’ methyl group on celecoxib and the benzene sulphonamide moiety. Another non-COX-2 inhibitory homolog of celecoxib, E7123 or 4-(5-(2,5-dimethylphenyl)-3-
(trifluoromethyl)-4,5-dihydro-1H-pyrazol-1-yl)benzenesulfonamide was also much more potent than celecoxib in killing cancer cells [128-130].
Celecoxib’s Effects on Hematopoietic Cancers While the focus of this thesis, and much of the interest surrounding the use of celecoxib as an anti-cancer drug, is predominantly focused on solid tumours, it is prudent to touch on celecoxib’s use in hematopoietic cancers also. Waskewich et al (2002) show that the antiproliferative effect of celecoxib (and rofecoxib) are similar among hematopoietic and epithelial cell lines [131].
Interestingly, they were able to demonstrate no detectable COX-2 in most of the hematopoietic cell lines used, and that the IC50 values fell with the 35-65uM range regardless of tissue origin.
Another group [132] more recently demonstrated that celecoxib was able to induce apoptosis and
69 of 329 antiproliferative effects in the five hematopoietic cell lines that they tested. This group go on to demonstrate a reduction in apoptosis inducing effects when combined with curcumin, demonstrating the need for effective and synergistic drug combinations in clinical trials and the need for extensive in vitro testing of compounds. Note also that the proposed mechanism of anticancer action of curcumin in that of an antioxidant and anti-inflammatory agent.
Interestingly, this protective effect was witnessed by another group using the same cell line
(U937) when tested with celecoxib, nimesulide and dimethyl celecoxib. However, there is emerging evidence [58, 133] that the mechanism of the drug in question, etoposide, is not simply inhibition of topoisomerase II, but is also concerned with cellular swelling, necrosis, alterations in mitochondrial mass and mtDNA and ROS. Again, proving the need to more completely understand a drugs mechanism(s) of action before using them in combination. Several groups have also demonstrated antiproliferative and apoptosis inducing effects of celecoxib chronic myelogenous leukemia (CML) [58], acute leukemia [134], lymphoma [135, 136] and has arisen in several clinical trials (ClinicalTrials.gov).
Repurposing Drugs for Oncology (ReDO) The selection of celecoxib as the focus of this final chapter follows the criteria outlined as the focus of the ReDO system. Based on the pharmacology, bioavailability and actual concentrations of drug that is present in the plasma, as well as several other factors such as higher COX-2 selectivity, lower IC50 in the cell lines tested, and several other groups reporting similar findings, celecoxib was determined to be the most promising.
The criteria of the ReDO project and their relation to the selection of celecoxib as the focus are roughly as follows:
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1. The drugs are well-known, with years of clinical use and data at the disposal of
researchers and clinicians. Although older drugs are sometimes favoured because of this,
celecoxib was FDA approved in1998 and was a major drug for Pfizer 2004. Although
this does make celecoxib relatively new compared to others such as aspirin, a basic
search of “celecoxib cancer” will provide 1223 search results over the preceding 10
years, with the anti-cancer actions of celecoxib suggested as far back as 1996.
2. That the drugs show a good toxicology profile and are well tolerated for chronic dosing.
While other drugs of the Coxib family were taken off the market due to adverse cardiac
events, celecoxib remains on the market and has similar (if not lesser) side-effect and
contraindications as those witnessed with the use of other NSAIDs.
3. There is a plausible mechanism of action. Several of these have been proposed for
NSAIDs and celecoxib and elucidated upon in this chapter and the preceding ones.
Further to this, a novel mechanism follows from the final experimental chapter of this
thesis. Further still, theory surrounding the proposed mechanism of action should be
taken into consideration to provide off-target, complementary and synergistic effects for
the combination of drugs, without increasing patient toxicity, if possible. This was taken
into consideration when selecting the combination of agents in this thesis, with DNA
damage or inhibition of DNA repair enzymes as the main mechanism of action described
using doxorubicin and 5-FU and not for celecoxib.
4. Strong evidence in vitro, in vivo and in clinical data both epidemiological, and from
clinical trials, with patient data considered significantly more highly that in vivo data, and
in vivo data being given more weight than in vitro studies. This has been discussed in
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previous sections and celecoxib is currently the focus of several clinical trials
(ClinicalTrials.gov).
5. There is evidence that the drug will work at relevant physiological levels. Celecoxib was
by far the closest to relevant levels of the NSAIDs tested based on available levels in the
serum (Table 7). This criterion also documents practical routes of transmission that are
achievable in patients and do not provide significant toxicity.
Importance of Cancer Staging and Celecoxib Treatment The reasons for the consistent differences observed between pre- and post-diagnostic use or pre- versus post-operational use, with post-use showing a much lower relative risk of cancer related mortality have yet to be conclusively identified. However, we propose that one essential basis for these differences relates to the effectiveness of the drugs with the timing of treatment (post being more important and NSAIDs are much more effective in this situation) together with the extent of metastatic burden of the disease (with the NSAIDs showing activity predominantly greater effective benefit in the context of metastatic disease for the reasons outlined below). Importantly, overall in the above large-scale study, comparing to the reference non-user group, those cancer patients prescribed NSAIDs showed a significant and marked reduction in their subsequent risk from developing metastatic tumours (RR = 0.623; CI: 0.515-0.753, p < 0.001). From these studies and many others, it can be concluded that in most cases the outcomes clearly demonstrate the benefits from NSAID prescriptions after cancer diagnosis, which are commonly associated with lower all-cause mortality amongst cancer patients. The lowering of post-diagnostic cancer with NSAID use applies not only to FAP and colorectal cancer but also to breast; prostate; melanoma; oesophageal; gastrointestinal and endometrial cancers. Clearly, if the NSAIDs are utilised and administered with the correct timing and for the appropriate stages of advanced
72 of 329 disease, they should work across all types of cancers and lower the burden caused by metastatic disease.
Different cancer cell types and stages alter the efficacy of the NSAIDs considerably when tested as anticancer agents, particularly when the preponderance of beneficial effects in the clinical setting of metastatic malignant disease post-cancer diagnosis is realised. This situation has, until now, been further compounded by a lack of a precise understanding of how the NSAIDs act to kill cancer cells (for review [137-140]). Current understanding of NSAID function as anticancer agents remains limited as does clinical data from human trials in advanced cancer. The mounting evidence is clear that NSAIDs, and particularly celecoxib, significantly enhance advanced cancer patient responses to the existing commonly used chemotherapies and lower the burden of metastatic disease [141-143].
Celecoxib is FDA Approved for Colorectal Cancer Treatment Celecoxib is currently FDA approved for the treatment of colorectal cancer (CRC) and familial adenomatous polyposis (FAP), with several past and current clinical trials presenting contentious conclusions. Early large-scale clinical trials demonstrate a 33-45% reduction in polyp recurrence in patients treated with celecoxib (400mg) each day for six months. However, the treatment groups were also shown to have elevated cardiovascular events. Other early (2000) clinical trials consisting of 77 patients given either 100mg or 400mg of celecoxib twice daily for six months showed a significant reduction in the 400mg celecoxib group in the surface area volume of polyps as compared to the placebo group, with the incidence of adverse events similar among the groups. A similar study completed in the primary phase in 2006 conducted by the National
Institute of Cancer (NIC) tested celecoxib’s effect on the prevention of cancer in patients with
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FAP. This phase 3 study involved 1170 patients given either 400mg, 200mg or a placebo twice daily for three years to determine if the reduction in polyp formation and size had significant reduction [144]
Current Clinical Trials There is a current (last updated December 2017, estimated completion date November 2022) phase 3 clinical trial on the effects of celecoxib involving 2590 breast cancer patients being conducted by the Imperial College of London (European Celecoxib Trial in Primary Breast
Cancer as part of the REACT – Randomized EuropeAn Celecoxib Trial). The study utilized celecoxib 400mg twice daily for a period of two years after chemotherapy and/or radiotherapy to reduce prostaglandin mediated inflammation and reduce the tumours ability to survive post- therapy.
A small study in 2006 of 27 patients with incurable metastatic melanoma given oral celecoxib,
200mg daily, demonstrated tumour regression in 7 patients with 2 complete, 2 partial and 3 stable responses. Note that several of these patients had received prior CancerVax therapy and the does not appear to be a placebo-controlled group in this study. Another study in 2006 combined temozolomide (TMZ) with celecoxib for the treatment of advanced melanoma in a phase 2 clinical trial. Patients (52) received 200mg/m2 of TMZ per day for 5 days every four weeks and celecoxib (400mg) twice daily continued until progression. The study saw 11 objective responses, five complete responses and six partial responses, with a further twenty patients having stabilization of their disease and 19 progressing. Note again that this was not a randomised, placebo controlled, double blinded study.
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Several studies were also found involving celecoxib in the management of several other non- melanoma skin and breast cancers. A basic search of “cancer” and “celecoxib” provides results for 218 studies for either the prevention, treatment, management/reduction of symptoms or the reduction of cancer recurrence for a wide range of cancers including: breast, bladder, pancreatic, colorectal, lung, head and neck, prostate, ovarian, uterine, liver and bile duct, cervical and renal.
Celecoxib is also currently being combined with a wide range of commonly known therapeutics such as: cisplatin, gemcitabine, carboplatin, paclitaxel, docetaxel, doxorubicin, erlotinib, capecitabine, 5-fluorouracil and others, as well as various radiotherapies [145, 146]. Several (7) early trials and pilot studies are either currently recruiting or underway involving the use of immunotherapies combined with celecoxib, including: nivolumab, ipilimumab, calcitriol, allogenic tumour cell vaccine (K562) and pembrolizumab, in a variety of malignant neoplasms including mesothelioma, esophageal cancer, pleura and lung cancers and metastatic liver cancer.
Celecoxib therefore has a sound basis and is the focus of a great deal of research the world over regarding its status as an anti-cancer drug for a wide variety of solid tumors, as a prophylactic measure, to treat cancer directly on its own, to treat cancer in combination with a variety of other chemotherapies, radiotherapies and immunotherapies, to reduce patient symptoms and to reduce the incidence of cancer recurrence.
Criteria for the Selection of Celecoxib It may then be worthwhile to note why celecoxib requires further investigation in vitro, in the face of so many current clinical trials. The refinement of a drugs mechanism(s) arms clinicians with a much greater understanding of when/how a drug should be used, and in what dosage and combinations. Several early clinical trials involving the use of NSAIDs have seen indifferent results, possibly due to several factors (reviewed [147]):
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1. The specific type of NSAID used. Not all of the NSAIDs are created equally in
their abilities to inhibit COX and, more importantly, COX-2.
2. The dosage of the NSAID is not clinically relevant when it has been compared with
data generated in vitro in in animal models.
3. The timing of the administration of the NSAIDs was too short, or patients were
taken off NSAID therapy before meaningful results could arise.
4. The NSAID used was poorly tolerated and the treatment was ceased due to toxicity.
5. The trials looked at the use of NSAIDs in primary cancers as opposed to metastatic
and advanced cancers where they prove more effective.
6. The combination of NSAID with chemotherapeutic was not complementary and did
not provide “off target” additive or synergistic effects
7. The type of cancer being treated was not receptive to therapy with NSAIDs
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Chapter Two
Methods
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Table 4: Reagents used in this Study
Reagent Manufacturer Country Lot # Sytox Green Life Technologies USA 1646682 Annexin-V BD Pharmigen AU 3239067 Acridine Orange Invitrogen USA 775222 MitoSOX Invitrogen USA 1802090 DHE Sigma Aldrich USA Not Visible DCF Sigma Aldrich USA 075M4092V TBHP Sigma Aldrich USA MKCD3314 MnTMpyP Abcam UK AB142212 NAC Life Technologies USA 1711803 α-TS Sigma Aldrich USA SLBH6145V Celecoxib Pure Chem Scientific USA 80007427 DMC Sigma Aldrich USA SZBD064XV Diclofenac Abcam UK AB120621 Nimesulide Abcam UK AB142926 Sulindac Abcam UK AB142950 Salicylate Abcam UK AB120746 Caspase-Glo® 3/7 Promega USA G8090 DMEM Gibco USA 10313-021 RPMI Gibco USA 11875-093 Trypsin Gibco USA 15400-054
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Table 5: Materials used in this Study
Item Manufacturer Country Lot/Ref # T-25 Flask Corning USA 430639 T-75 Flask Corning USA 431082 6-Well Plate Costar USA 3506 96-Well Plate Costar USA 3603 15 mL Falcon Corning USA 430791 50 mL Falcon Corning USA 430829 Freeze Vials Costar USA 3658 Ibidi 8-Well Slide Ibidi Germany 80826
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Cell Culture Murine melanoma B16F10 cells and 4T1 cells were maintained in DMEM (Gibco,
Massachusetts, USA) and RPMI (Gibco, Massachusetts, USA) respectively, supplemented with
6% heat-inactivated FBS (Gibco, Massachusetts, USA), 4% heat-inactivated NBCS (Gibco,
Massachusetts, USA), penicillin/streptomycin, 1.6 mM L-glutamate, supplemented with 1%
Glutamax (Gibco, Massachusetts, USA) and 20 mM HEPES buffer as full media and incubated at 37°C in a humidified atmosphere of 5% CO2. Cells were harvested via trypsin after washing twice with 1 x PBS and pelleted via centrifugation at 1250 rpm for 4 min. Cell counting and viability was determined using trypan blue dye exclusion and a haemocytometer [148]. For cell storage, cells were harvested by trypsin (Gibco, Massachusetts, USA) and counted before being pelleted to remove excess media. The supernatant was then discarded, and the cells were re- suspended at a concentration of 106/mL. Cells were slowly cooled in a Frosty Boy in freezer vials after resuspending in a mixture of 10% DMSO (Sigma Aldrich, St. Louis, Missouri, USA) and 90% FCS as freezing media until frozen and then stored at -80ºC. Cells were revived by warming the vial of cells to room temperature before transfer to a 15 mL Falcon tube (Corning,
New York, USA) containing 10 mL of pre-warmed media. Tubes were mixed by inversion before being centrifuged at 1250 rpm for 4 min to remove excess DMSO (Sigma Aldrich, St.
Louis, Missouri, USA). The supernatant was then discarded, and the cell pellet re-suspended in
1mL of full media and added to 4 mL of pre-warmed media in a T-25 flask (Corning, New York,
USA).
Restriction Digest, Plasmid Extraction and Transfection The Oct4-EGFP plasmid vector DNA was amplified in E.coli bacteria grown in 150 mL luria broth (LB) with kanamycin (50 ug/mL) supplemented in a 250 mL Erlenmeyer flask and placed
80 of 329 in an orbital shaker overnight. The extraction was performed using the Midi Plasmid Prep Kit from Qiagen (Qiagen, Hilden, Germany) following the manufactures instructions. Plasmid quantity and purity was measured using a nanodrop microvolume spectrophotometer (Thermo
Fisher Scientific, Massachusetts, USA). Restriction digest was performed using restriction enzymes; EcoR1, Cla1, Sal1 and HindIII and run on a 1% agarose gel to ensure the plasmid was the correct size and contained the correct insert and promoter region. Following this, cells were transfected using Genejet transfection reagent with 18 μg of pDNA in a 1:3 ratio with Genejet reagent. The pDNA was added to cultures with antibiotic and serum free media for a period of 4 hours with the media then being replaced with full complement media. Cells were observed for
EGFP expression after 48 hours using an Olympus Cell-M fluorescent microscope (Olympus,
Tokyo, Japan) in the FITC channel. Transfected cells were selected using G-418 for 28 days following determination of the correct dose (1200 µg/mL for the B16F10 line, see Appendix 1).
Cells were then maintained in 1/3 of the selection dose to promote plasmid retention.
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Figure 5: Plasmid Vector Map phOct4-EGFP Plasmid map for the Oct4-EGFP used in this study.
Hypoxic Incubation The Oct4 expressing B16F10 cells were generated by growth in hypoxic conditions. Cells were incubated in a tri-gas incubator (ASTEC, Fukuoka, Japan) at a constant humidified environment
82 of 329 of 5% CO2 and 1% O2 with remaining air replaced by Nitrogen from an N2 gas cylinder. Various conditions were tested, and it was determined that a hypoxic cycle of 3 days hypoxia and 1 day normoxia was the most efficient at inducing significant levels of Oct4-induced expression as determined by microscopy and flow cytometry for the levels of EGFP. Following the completion of the hypoxic cycling, cells were maintained in culture for a period of 35 days with analysis via microscopy to document spheroid formation and EGFP expression. Media in these cultures was changed every 48 h. At the completion of this period the cell cultures were harvested via trypsin and placed into 15 mL Falcon tubes before being pelleted as previously described. Pellets were resuspended in 1 mL FACS buffer (PBS, 1% FCS, 1 mM EDTA) and transferred to sterile 12 x
75 mm polystyrene tubes (Corning, New York, USA) and placed on ice. Cell phenotypes were sorted into their respective peaks (Appendix 1) by FACS using a MoFlo (Beckman Coulter,
California, USA) flow cytometer. These cells were then maintained in standard culture conditions until ~85% confluence was achieved. The highest EGFP expressing cells (second sort very bright isolate 5 (2VB5)) were then sorted again and allowed to grow to ~85% confluence.
The resulting cell population was analysed via cytometry using either a FACSCalibur or Fortessa flow cytometer (Becton Dickinson, New Jersey, USA) to observe EGFP expression when these cells are maintained in standard normoxic culture.
Cobalt Chloride Testing The Oct4-EGFP hypoxic (2VB5) and normoxic cells were tested using a variety of cobalt chloride (CoCl2) (Sigma Aldrich, St. Louis, Missouri, USA) concentrations to determine if the expression of EGFP could be increased by inducing a state of pseudohypoxia. B16F10 Oct4-
EGFP hypoxic (2VB5) and normoxic cells were seeded in 6-well sterile tissue culture treated plates (Costar, Washington, USA) at a density of 2 x 105 per well and incubated overnight to
83 of 329 establish growth. CoCl2 was prepared fresh before use in PBS at a stock concentration of 50 mM and added to plates drop wise in a variety of different concentrations of CoCl2 (25-500 µM).
After the addition, the plates were incubated for a further 24 hours. Cells were harvested via trypsin and prepared for cytometry in FACS buffer as previously described before being placed on ice and analysed using a BD Fortessa flow cytometer. Analysis was performed by comparing each sample versus non- CoCl2 treated samples corresponding to either cell phenotype depending on either normoxic or hypoxic Oct4-EGFP B16F10 cells were being analyzed. Untreated wild- type B16F10 cells were used as a calibrator in order to set-up the assay for cytometry.
Isolation of Single Cells and Spheroids Single cells were isolated by determining the appropriate number of cells per mL following harvesting and counting using a haemocytometer. Cells were then diluted in full media before adding 100 µL of sample into the wells of 96-well black wall plates (Costar, Washington, USA).
Confirmation of wells with single cells was performed visually using an Olympus IX53 microscope, and wells found with no cells or more than one cell were discarded. Single cells were then incubated in standard culture conditions until clonal colonies had formed and could be transferred into 6-well plates. Cells were allowed to reach ~80% confluence before being harvested via trypsinisation and analyzed for EGFP expression using a BD Fortessa flow cytometer as previously described.
Spheroids were isolated by collecting culture medium in which the spheroids became free floating in suspension after being exposed to hypoxia for 48 h. Samples of the spheroids were examined for trypan blue exclusion and low-level staining ensuring that the majority of the cells in each spheroid sample were alive. Spheroids that were free-floating were collected from the
84 of 329 media of post-hypoxic cultures in 15 mL Falcon tubes and diluted to 10 mL in fresh complete media and mixed by inversion. A 1 mL sample of this mixture was transferred directly to a T-25 flask with an additional 4 mL of fresh complete medium to observe growth patterns. The remaining mixture was centrifuged briefly (simply spun quickly, not set for any length of time).
The spheroids in the tube are macroscopically visible and collect in the bottom of the tube very quickly. The supernatant containing any live single cells, dead cells and cell debris was gently removed, leaving predominantly spheroids in the tube. The spheroids were then suspended in 1 mL of medium, before being diluted to 10 mL. This process was repeated 3 times. Following this the spheroids were again diluted in 10 mL of media, mixed thoroughly, and 1 mL of the mixture was distributed in 100 µL lots into the wells of 96-well plates. Wells containing single spheroids were identified by microscopy and allowed to grow to confluence before being transferred to 6-well plates. Following transfer, the resulting culture was harvested by trypsinization and analyzed using a BD Fortessa flow cytometer for changes in the population by
EGFP expression.
Scratch Assay A scratch assay was performed in 6-well plates seeding 106 B16F10wt or 2VB5 hypoxic cells.
The plates were then incubated in normoxic conditions as previously described for 48 h until
100% confluence was achieved. Confluence was confirmed by observation with microscopy and using the JuLi BR (NanoEnTek, Seoul, South Korea) confluence mapping function. Following this, a “scratch” was made at the approximate center of each well using a P200 pipette tip using the lid of the plate as a guide under sterile tissue culture conditions. The media was then replaced with fresh media following gentle washing with warm PBS to remove any cells floating as a result of the “scratch”. After optimization of the closure of the scratch following observation
85 of 329 with microscopy, it was determined that 6 h was sufficient to observe cell migration and 24 h saw the scratch nearly reformed. The data was therefore gathered at 0 h, 6 h and 24 h in order to measure cell migration. Fluorescent microscopy was also performed to identify whether cells more highly expressing Oct4EGFP were more inclined to migrate. Cells were also measured using the JuLi BR live cell monitoring system to assess for “wound healing” as indicated.
Following imaging and monitoring of the cells, the migration front was measured using a digital reticle or analyzed from the JuLi BR data as indicated.
Animal Cancer Model Studies Animal work was carried out in accordance with animal ethics permit MSC/15/AEC. Female
C57Bl6 mice at 8 weeks of age were distributed into family groups of three individuals. Animals were allowed access to food and water ad libitum. Cells were prepared at a density of 10x the injection volume per mL in PBS with 100 µL of this solution injected. Either B16F10 wild-type or hypoxic Oct4-EGFP cells, as indicated, were injected s.c. into the left-hand side flank in the volumes indicated using an 25g needle and syringe. Animals were monitored and recorded daily for signs of tumour growth. Animals were weighed every 48 h and monitored for any signs of ill health. Once tumours were observed, tumour growth was measured every 48 h with the use of calibers until the maximum allowable tumour growth was observed, at which point animals were culled. Autopsy was performed to observe tumour spread and migration to the peritoneum, liver and lungs. Primary tumours were excised and weighed.
Drug Solubilisation All drugs were solubilised as a standard stock at 25 mM concentrations. Salicylate (Abcam,
Cambridge, UK) and diclofenac (Abcam, Cambridge, UK) were solubilised in d.d. H2O.
Celecoxib (Pure Chem Scientific, North Carolina, USA), nimesulide (Abcam, Cambridge, UK)
86 of 329 and sulindac (Abcam, Cambridge, UK) were solubilised using a 100 mM stock solution of (2-
Hydroxypropyl)-β-cyclodextrin (Sigma Aldrich, St. Louis, Missouri, USA) with the addition of
100 µl of 1 mM NaOH. Solutions were then heated to 60℃ with periodic vortexing until stable preparations were formed. Solubilised drugs were aliquoted into 100 µl lots in Eppendorf tubes and stored at -20℃ until used in assays. Intermediate dilutions were made using either d.d. H2O or Hank’s Balanced Salt Solution (HBSS) (Gibco, Massachusetts, USA) before addition to wells at the concentrations described. Thawed drug stock solutions were used for a maximum of 1 week and stored at 4℃ before being disposed of and were not refrozen.
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Table 6: Stock Solubilisation of Drugs used in this Study
Drug MW g/mol Vehicle Stock Concentration mg/mL Celecoxib (Celebrex) 381.4 HBCD or DMSO 25mM 9.54 Dimethyl Celecoxib 409.4 HBCD or DMSO 25mM 10.24 Diclofenac Sodium Salt 318.1 DDH2O 25mM 7.95 Nimesulide 308.3 HBCD 25mM 7.71 Sulindac 340.4 HBCD 25mM 8.51 Sodium Salicylate 160.1 DDH2O 25mM 4.00 Doxorubicin 543.5 DDH2O 10mM 4.81 5-Fluorouracil 130.1 DMSO 25mM 3.25
Table 7: Solubility of Drugs used in this Study
Solubility Drug Water/PBS DMSO Ethanol/Methanol Celecoxib (Celebrex) <0.2mg/mL 16.6mg/mL 25mg/mL Dimethyl Celecoxib <0.2mg/mL 20mg/mL N/A Diclofenac sodium salt 50mg/mL 35mg/mL 35mg/mL Nimesulide <0.2mg/mL 68mg/mL 2.3mg/mL Sulindac <0.5mg/mL 30mg/mL 2mg/mL Sodium Salicylate 125mg/mL N/A 35mg/mL Doxorubicin 10mg/mL 100mg/mL 10mg/mL 5-Fluorouracil 8mg/mL 53mg/mL 0.8mg/mL
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Cytotoxicity
For each NSAID tested on the cancer cell lines, the cytotoxic IC50 values were determined using
96-well black walled, clear flat-bottomed plates. Cell death was determined with the use of Sytox green (Thermo Fisher Scientific, Massachusetts, USA) at a final concentration of 500 nM to differentiate viable from non-viable cell populations. Plates were read on a Flexstation 3
(Molecular Devices, California, USA) spectrophotometer every 24 h for a total of 72 h. IC50 values were based on the drug concentrations causing 50% reduction based on 100% live control vs. 100% dead (0.1% triton-x-100 treated, 40 mins) cell populations as determined by Sytox green dye exclusion and GI50 values were defined as the drug concentrations causing 50% growth inhibition of the treated cells compared to vehicle treated cell population solubilised as
100% by plotting dose-response curves over time in days of cell culture.
Apoptosis Apoptosis was determined using the FITC-Annexin V Apoptosis Detection Kit (Becton
Dickinson, New Jersey, USA). Cells were seeded into 6-well sterile tissue culture plates at a density of 2 x 105 cells per well and incubated for 24 h. NSAIDs were added at the concentration indicated and the plates were incubated for the indicated amount of time. Cells were harvested by trypsin and transferred to 15 mL Falcon tubes and pelleted via centrifugation as previously described. Cell pellets were then resuspended in 100 µl of 1x Binding Buffer after diluting the
10x Binding Buffer in distilled water. Resuspended solutions were then transferred to 1.5 mL
Eppendorf tubes. It was determined that 3 µL of FITC conjugated Annexin-V was sufficient to see good separation among the controls, and that concentrations as high as 5 µl may produce spectral overlap. 3 µl of the Annexin-V and 5 µl of the PI was therefore added to each of the
89 of 329 tubes apart from the unstained, single stained and negative controls. Each tube was gently vortexed and incubated at RT for 15 mins in the dark. Following this, single and dual stained positive controls that were generated by heat treatment were heated in a waterbath for 10 mins at
60ºC. At the completion of the incubation period, 400 µl of additional 1x Binding Buffer was added to each tube. The contents were then transferred to sterile 12 x 75 mm polystyrene tubes and the tubes placed on ice before analysis using a BD Fortessa flow cytometer. Single stained annexin-V and PI populations, as well as heat treated positive, untreated and unstained controls were used to set the gating for the cytometer.
Membrane Potential Mitochondrial membrane potential was determined using TMRE (Sigma Aldrich, St. Louis,
Missouri, USA) with CCCP (Sigma Aldrich, St. Louis, Missouri, USA) as a positive control.
Stock solutions of 1 mM TMRE and CCCP were diluted in DMSO. Cells were seeded at 2 x 105 cells per well in 6-well plates and incubated for 48 h before treatment with an appropriate concentration of drugs for the allotted time period as indicated. Positive controls were incubated for 10 min at a final concentration of 10 µM CCCP at room temperature prior to analysis. A working concentration of 100 nM TMRE was added to DMEM or RPMI media as appropriate, and 1 mL of this solution was applied to each well and incubated for 30 min. Cells were harvested as previously described and stored on ice before analysis using the BD Fortessa.
Cytometric analysis was confirmed by fluorescent microscopy via an Olympus IX50 microscope.
Determination of Cellular ROS Levels Mitochondrial superoxide was measured using the MitoSOX red kit (Life Technologies,
California, USA). Cells were seeded at 2 x 105 in 6-well plates and incubated for 48 h. Cells were treated with NSAID as indicated and incubated for a further 2-6 h. Samples were harvested,
90 of 329 stored on ice before analysis with the BD Fortessa cell analyzer. For MitoSOX red, dihydroethidium (DHE) (Sigma Aldrich, St. Louis, Missouri, USA) or dichlorofluorescein
(DCF) (Sigma Aldrich, St. Louis, Missouri, USA) measurements in 96-well black wall plates,
105 cells/mL were seeded at 100 µl per well and incubated for 48 h before staining and drug addition (as indicated) before reading on a Flexstation 3 Multi-Mode Microplate Reader. For timed responses using MitoSOX, cell suspensions (106/mL) were prepared, stained for 10 min at
37°C at a concentration of 5 µM, with periodic gentle vortexing and then stored at 4°C before analysis. Immediately prior to analysis, cell samples were warmed to 37°C in a water bath for 60 s and baseline readings obtained before adding drug and continuously reading every 6 min.
Fluorescent and Confocal Microscopy All fluorescence and light field microscopy was performed using an Olympus IX53 microscope and CellSens software. For fluorescent imaging, exposure times and minima/maxima light fields were set to a standard based on the signals from untreated and negative vs. positive controls.
Sytox imaging was performed after 48 h drug treatment of cells cultured in 96 well black wall plates using the FITC channel. For MitoSOX red imaging, cells were plated at a density of 105 cells/mL in sterile 96 well black wall culture plates for 48 h before incubating with NSAID for
60 min. Confocal images were performed using a Leica SP-8 (Leica, Wetzlar, Germany) confocal microscope after seeding 4 x 104 cells on an 8-well u-Slide (Ibidi, Munich, Germany)
overnight, and staining with MitoSOX (5 µL) and nuclear counterstaining with Hoescht33342
(Sigma Aldrich, St. Louis, Missouri, USA) (1 µg/mL) for 10 min. The 8-well slide was then washed twice gently with pre-warmed PBS. Following this HBSS containing 1% FCS was added to each of the wells and the cells were stored at room temperature before analysis using a Leica
SP-8 confocal microscope. A baseline was determined before addition of 100 µM of celecoxib to
91 of 329 the experimental wells and the increase in MitoSOX signal observed with treated vs untreated wells imaged after 1 h.
Confocal Microscopy and Cytometry using MitoSOX and MitoSpy Confocal images over time were performed using an Olympus FV-3000 confocal microscope
(Olympus, Tokyo, Japan) after seeding 105 cells on an 8-well u-Slide overnight and staining with
MitoSOX and nuclear counterstaining with Hoescht 33342 for 10 min before celecoxib (100μM) addition. Experiments using MitoSpy (BioLegend, California, USA) were performed using 200 nM for 10 mins. Stock concentrations were achieved by diluting MitoSpy in 74 μL of DMSO with dilutions, staining and incubation performed with HBSS. For imaging using MitoSpy, 105 cells seeded on glass bottomed petri dishes (Ibidi, Munich, Germany) and incubated overnight.
Following staining, cells were washed in HBSS before imaging using an Olympus FV3000 confocal, or Olympus IX53 fluorescent microscopes. For FACS analysis comparing ROS inducing abilities of celecoxib vs DMC, the protocol follows that previously described except that the concentration of celecoxib was 100 μM and DMC was 50 μM and the incubation period was only 1 h.
Acridine Orange Staining Cells were seeded in 96-well black wall plates at a density of 2 x 104 cells per well in 100 µl of media and incubated under standard conditions for 24 h. Cells were incubated for 3 h in 100 µM celecoxib. Acridine Orange (Sigma Aldrich, St. Louis, Missouri, USA) was diluted into warm
HBBS at a concentration of 2 μg/mL. Wells were then washed twice in prewarmed PBS.
Acridine Orange staining was performed in triplicate after adding 100 µl of the working solution to each experimental well, except for the unstained control, and incubated in standard culture conditions in the dark for 15 min. Wells were then washed once with warm PBS before the
92 of 329 addition of warm HBSS. Imaging was performed on an Olympus IX53 microscope utilizing the
FITC and CY3 filters as compared to untreated and unstained wells. Images were overlaid with the CellSens software from Olympus.
Caspase-Glo® 3/7 Assay For caspase 3/7 activation the Caspase-Glo 3/7® reagent (Promega, Wisconsin, USA) was used following the manufacturer’s protocol after incubation with celecoxib (100μM) or alpha
Tocopheryl succinate (Sigma Aldrich, St. Louis, Missouri, USA) (αTS) (200μM) for 4 h or 18 h as shown. Cells were plated at 2 x 104 cells per well in black wall plates and incubated for 24 h.
The Caspase-Glo 3/7® buffer and substrate were equilibrated to room temperature for 30 mins before adding buffer to substrate and mixing with a vortex. The mixed reagent was then added as 100 μL to each well and incubated for 30 min before reading on a Flexstation 3 spectrophotometer with an integration time of 500 ms. Note that longer incubation times (60 min) or longer integration times (1000 ms) did not alter the results.
MnTMPyP Antioxidant Treatment The antioxidant MnTMPyP (Abcam, Cambridge, UK) was made fresh for use and solubilised in
HBSS to a stock concentration of 1 mM. Cells were incubated for either 10 mins or 1 h at concentrations of either 10 μM or 50 μM, depending on the experiment, after the staining protocol with MitoSOX or DHE had been performed. Cells were then challenged with either celecoxib, (tert-butyl hydroperoxide (TBHP) (Sigma Aldrich, St. Louis, Missouri, USA) or αTS and read on either a Flexstation 3 or TECAN (TECAN, Männedorf, Switzerland) M200 Pro spectrophotometer at either 2, 3 or 4 h as shown. Images were performed following the same
93 of 329 procedure with images taken using an Olympus IX53 microscope after 2 h with minima/maxima light field and acquisition time based on the positive control.
Seahorse XFp Cell Mito Stress Test Celecoxib’s effect on the metabolism were analyzed using the Seahorse XFp Flux Analyzer
(Agilent, California, USA) coupled with the Mito Stress test kit and following the manufactures protocol. Briefly, both B16F10 and 4T1 cell lines were titrated and it was determined that 104 cells incubated overnight was the optimal range for both cell types. Cells were then plated at this density and incubated overnight following standard tissue culture method described. The flux cartridges were hydrated with calibrant and incubated in a non-CO2 incubator for the same period. Each assay was designed to have two media and reagent blanks, three untreated internal controls and three treatment groups for celecoxib. On the day of the assay, pyruvate, glutamine and glucose were added to the XF base medium and pH adjusted with the addition of NaOH.
Cells were washed in assay media and new media is added. The reagent tubes were allowed to calibrate to room temperature for a period of 15 mins. The test reagents are then diluted in test media following the modified assay injection, in which test compound (celecoxib) occupies the first port, with oligomycin, FCCP and rotenone/antimycin A occupying the remaining ports in that order of injection. A baseline is then established after incubation with test compound for a period of 20 min before testing ATP production, maximal respiration and spare respiratory capacity.
Animal Study Animal work was carried out in accordance with animal ethics permit MSC/05/15/AEC. Female
C57Bl6 mice at 8 weeks of age were distributed into family groups of three individuals. Animals were allowed access to food and water ad libitum. B16F10 wild-type cells were injected into the
94 of 329 tail-vein using a 25g needle and syringe. Animals were segregated into control and treatment groups, with the treatment group receiving 150 µg of celecoxib every 48 h through i.p. injection.
Once signs of ill health were observed, animals were culled and autopsied to observed metastatic colonies on the lungs.
Statistical Analysis Experiments were repeated at least twice unless otherwise indicated. Certain other experiments such as, cytotoxicity, ROS, mitochondrial membrane potential and hypoxia inducing Oct4 were also conducted by other independent researchers the laboratory. However, the data shown here is only the candidate’s work. Each experiment was conducted with a minimum of 3 replicates, to determine mean values ± Standard Deviation (SD) or Standard Error of the Mean (SEM) as indicated. N.D. = not determined. Statistical analysis was performed using Graphpad Prism
(version 6.1) software and statistical significance was determined using one-way ANOVA by comparing the means of the groups to the control group (Dunnett’s multiple comparisons) for most of the data sets dealing with multiple drug treatment. One notable exception is in the use of one-way ANOVA in using Tukey’s test to analyse the weights of the mice in the groups to each other (Figure 13). For the comparison of two groups, the unpaired two-tailed Student’s t-test was employed to determine any significant differences. Comparison of survival was used for the waterfall plot with no significant difference in the curves (Mantel-Cox test). For drug treatment curves, dotted lines indicate the confidence interval (CI 95%) following fitting the curves using the quadratic equation.
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Chapter Three
Results: Hypoxia and Cancer Stem Cells
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Hypoxia and Cancer Stem-cells
Introduction Hypoxia has been demonstrated to contribute to a malignant phenotype through regulation of certain stem-like and pro-migratory factors (Table 3). While a lot of research has been conducted surrounding the role of intratumoural hypoxia and hypoxia-inducible factors in reprogramming tumour cell metabolism and promoting cancer stem-like cells, more promising strategies are required to eradicate these populations in order to promote patient survival. The stem cell factor
Oct4 is upregulated by HIFs during hypoxia and promotes dedifferentiation and EMT. The purpose of the work carried out in this section was to determine if the stemness factor Oct4 could be induced through either hypoxia or cycling hypoxic conditions. Once a stably Oct4 expressing cell line could be generated, this would provide the basis of testing for increased sensitivity to
NSAIDs that form the next chapter.
Note that the B16F10 cell line, as well as the human metastatic melanoma cell lines Skmel-28 and A375, were cycled in hypoxia and sorted as part of the Master’s thesis. The B16F10 cell line was chosen to continue this work in order to suit transplantation in vivo. All of the data presented here was produced during the PhD candidature. Some information from the Master’s thesis has been included as Appendix I for clarity.
Aims The aims of this section build upon work that was performed during the Master’s degree in which B16F10 cells were transfected with an Oct4 promoter containing plasmid conjugated to
EGFP. These cells were selected in G-418 and subjected to cycling hypoxic and normoxic
97 of 329 incubation. Observation was made via flow cytometry of an increase in Oct4 expression. Cells were then sorted using FACS to derive a stable Oct4 expressing cell line (2VB5) that was thought to represent a more “stem-like” cell line. However, this was unable to generate a 100%
Oct4 expressing line for unknown reasons, with the “stable” expression seen to be less that than cells removed from hypoxia, and still with ~15% of cells not expressing Oct4 (Appendix I).
The aims of this section were therefore to:
1. Further monitor the stability of the Oct4 expression in the cell line.
2. Test whether the pseudohypoxia inducing CoCl2 could increase the Oct4 expression in
both hypoxic and normoxic cells.
3. Determine if a cell line derived from a monoclonal population would express Oct4 in a
uniform fashion as opposed to a heterogeneous population from either of the hypoxic
2VB5 or normoxic transfected cells.
4. Determine if isolated cell spheroids that are generated during hypoxia show an increase
in Oct4 expression and are a more “stem-like” population.
5. Identify if the hypoxic cells are more migratory or metastatic than the “wild-type”
population.
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Stable Expression of EGFP in the B16F10 Cell Line 2VB5 In the previous year, the B16F10 cell line was transfected with a plasmid that is conjugated to
EGFP and contains the entire promoted region for the Oct4 gene. The aim of this was to generate, through hypoxia and based on the regulation of Oct4 by HIF, a subset of cells that had higher Oct4 expression and were therefore more stem-like. Following transfection of the cells, selection of the plasmid retaining population was conducted with neomycin to ensure that there was a pure plasmid containing population. The transfected population B16F10-Oct4 was then analyzed for basal Oct4 expression before being subjected to a variety of different hypoxic incubations to determine if the expression of Oct4 could be increased through hypoxia as hypothesised. The expression of Oct4 in the B16F10 cells was seen to increase the most in a cycle of 3 days hypoxic and 1-day normoxic culture as witnessed by cytometry and microscopy measuring the EGFP conjugated Oct4. Marked differences in cellular morphology were also observed. After hypoxic cycling and FACS based on EGFP expression, the B16F10 cells were sorted into five different peaks. This process was repeated twice in order to generate the stably
Oct4 expressing 2nd sort Very Bight isolate 5 (2VB5) B16F10 cell phenotype that stably expressed Oct4-EGFP in ~85% of its population. This was then hypothesised to be a more
“stem-like” cell population that could be utilised for further experimentation. Figure 6 shows the final cytometry data of B16F10wt, B16F10Oct4 transfected (non-hypoxic), 2VB5 cells stably expressing Oct4 and the 2VB5 cell line further subjected to 48 h of hypoxia. Further subjecting the 2VB5 line to hypoxia is sufficient to increase Oct4 expression. However, repeated testing of this demonstrated that this decreased back to the profile seen with the 2VB5 line that remains stable in normoxia.
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1)A)
B)1 1)
Normoxic Hypoxic
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Figure 6: B16F10wt, Oct4 Normoxic, 2VB5 Hypoxic and 2VB5 Hypoxic + 48 h Hypoxia Oct4EGFP Expression Profiles A) Comparison between B16F10wt (red) and two different 2VB5 lines (orange, blue) maintained in normoxia, as compared with the same 2VB5 line that has just been subjected to a further 48 h of hypoxic (1%) incubation (green). Note that the increase in brightness witnessed after hypoxic culture was repeatedly observed to reduce to the levels seen in the lines maintained in normoxia (orange, blue), but maintains that expression stably even measured after months. B) 2VB5 cells subjected to a further 48 h hypoxia (blue) with cells after passaging and a further 48 h of normoxic culture (red). Images show the difference in transfected normoxic cells vs hypoxic selected 2VB5 cells in Oct4 EGFP expression via fluorescent microscopy in the FITC range. Scale is 200 µm.
Oct4EGFP is Inducible via Pseudo Hypoxia To further test the response of B16F10 and 2VB5 cells to hypoxic stress, and to determine if
Oct4 expression could be increased, both phenotypes were assayed using a range of concentrations of CoCl2, a known inducer of HIFs and pseudo hypoxia through replacement of the central ferric compound of PHDs with cobalt causing a conformational inactivation of the enzyme [149, 150]. Both B16F10 phenotypes were tested over a range of 25-500 μM for 24 hours before cytometry. Note that the higher concentrations (250-500 μM) of CoCl2 were toxic to both phenotypes with both visual and scatter patterns from FSC and SSC indicating apoptotic cell populations and were seen to greatly reduce the expression of EGFP. Figure 7 shows a dose dependent increase in EGFP in the normoxic cells with both 50 μM and 100 μM concentrations being significant over the untreated population. This was replicated in the 2VB5 hypoxically cycled population with all of the values being significant. Interestingly, this does not appear to be a dose dependent response. Figure 8 shows the histogram plots from the assay showing a uniform increase in the cell population. Histograms of the hypoxically cycled cells were only seen to increase their fluorescence in the non-expressing population with no obvious increase in the expressing population (indicated by red arrow).
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B16F10 Oct4 Normoxic CoCl2 Treated
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Figure 7: B16F10 Oct4 Normoxic and 2VB5 Hypoxic Oct4EGFP Expression Profiles in Response to CoCl2 Treatment
Normoxic or hypoxic cells subjected to pseudohypoxia via CoCl2 concentrations as indicated for a period of 24 h before analysis of Oct4 expression via cytometry. Note the higher concentrations and longer incubation time were tested with an obvious impact on cell health. Results are presented as means±SD (N=1, n=3), with * indicating a difference from Z (P<0.05) for untreated vs treated cells.
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B16F10 Hypoxic UT
Normoxic Hypoxic UT 50 µM
Normoxic Hypoxic 100 µM 100 µM
Figure 8: Cytometry Profiles of Normoxic and 2VB5 Cells after CoCl2 Treatment
Cytometry profiles witnessed post treatment with CoCl2. Normoxic profiles are increased uniformly with increasing concentrations up to 100 µM, Normoxic profiles are only seen to shift cells that do not express Oct4 with no obvious increase in the brightness of cells that already express Oct.
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Hypoxic Spheroids Highly Express Oct4 EGFP and are Heterogeneous It was noticed that spheroids that developed after hypoxically cycling B16F10 cells highly expressed the Oct4EGFP. To determine if isolating theses spheroids would result in a phenotype with a total Oct4 expression, or increased brightness, multiple spheroids were grown from the media of hypoxic cultures or isolated and grown in 96-well plates (Figure 9). Suitable individual spheroids were identified by microscopy and grown to confluence before being transferred to 6- well plates for further growth before being analyzed by flow cytometry. At the end of the assay three suitable populations of individual spheroids were analyzed. Figure 10 shows the expression profile for each of the three spheroids. Interestingly, they are all different in the way that the population formed out of the isolated spheroid. Spheroid C7 expressed EGFP in 92.6% of its population and has three distinctive peaks, indicative of high Oct4 expression in a small subset of cells, Oct4 expression in the main group and a subset of non-expressing cells. Spheroid C6 expresses Oct4 in 56.8% of the population with two distinct peaks and a large group of non- expressing cells. Spheroid C4 had the highest Oct4 expression with 95.4% of the population expressing Oct4, but still contains a small population of non-expressing cells.
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Figure 9: Isolated Spheroids and Spheroids Maintain their Morphology after Passaging TOP: Isolated spheroid with high Oct4 expression and a monolayer of cells spreading from the spheroid with lower and non-Oct4 expressing cells. BOTTOM: Spheroids derived from the media of 2VB5 hypoxic culture when passaged and seeded into a new culture retain their spheroid morphology and derive the typical monolayer culture of B16F10 cells. Red arrows highlight the individual cell spheroids with a monolayer spreading from each. Images were captured using an Olympus IX53 fluorescent microscope using bright-field and FITC channels. Scale is 100 µM and 200 µM.
Isolated Clones Largely Reform their Parent Population To determine if a single cell could be isolated from either phenotype that expressed high levels of Oct4 in its entire population and would therefore be more representative of a “stem-like” cell regardless of hypoxic cycling, both B16F10 Oct4 normoxic and 2VB5 hypoxic phenotypes were
105 of 329 isolated into single cells in 96-well plates and allowed to grow to confluence before transfer in 6- well plates (Figure 11). Individual cells and EGFP expression were confirmed with light or fluorescent microscopy. Once sufficient numbers were generated populations were harvested and analyzed by cytometry. Single cell isolation generated 4 individual clones of each phenotype.
Figure 10 shows representative histograms of Oct4 normoxic phenotypes all of which have
EGFP expression in <1% of their population, less than that of their parent (6.8%) and were deemed to be non-expressing cells. Of the 4 2VB5 phenotypes isolated the expression pattern was observed to vary markedly, yet still resembled a variety of peaks of expression that had been witnessed in several other experiments. Clone 11E has expression in 70.5% of its population with peaks representing the parent population of non-expressing and weakly expressing cells.
Clone 10F has expression in 81.4% of its population but has the majority of cells in the highly expressing peak with an increase in median fluorescence (10F med = 119.0 afu vs 2VB5 med =
39.6 afu) with a peak more indicative of that of cells analyzed post-hypoxia, yet still containing a non-expressing population. Clone 10D expresses Oct4 in 91.0% of the population again similar to the parent population in both EFGP% and fluorescence intensity (med = 36.2 afu). Most interesting was clone 10B that appeared to have both highly expressing (53.3%) and a large population of non-expressing cells with no population of weakly expressing cells as an intermediate.
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A) B)
C) D)
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Figure 10: B16F10 Oct4 Normoxic and 2VB5 Hypoxic Single Cell Clone Isolates EGFP Expression Profile. B16F10 2VB5 Hypoxic Spheroid Isolates EGFP Expression Profile A) Comparison between B16F10 phenotypes. B16F10wt (red) as a baseline control for Oct4EGFP expression. B16F10Oct4 normoxic transfected cells showing baseline Oct4 expression before being subjected to hypoxia (blue). B16F10 2VB5 hypoxic cells post sorting and with stable expression being maintained in normoxia (orange). 2VB5 cells subjected to 48 h hypoxia (1%) showing a shift in the short term to higher Oct4 expression (green). B) Transfected B16F10 normoxic monoclonal populations with no Oct4 expression 4B (red), 4F (blue), 5B (orange) and 5E (green). C) Isolated spheroids from 2VB5 hypoxic culture with various Oct4 expression and several varying levels of expression, C4 (red), C6 (blue) and C7 (orange). D) Isolated monoclonal population from the 2VB5 hypoxic population with various Oct4 expression, 10B (red), 10D (blue), 10F (orange) and 11E (green). All assays were conducted on a BD Fortessa flow cytometer using the FITC channel.
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Figure 11: Isolated Single B16F10 2VB5 Cells Isolated B16F10 transfected normoxic and hypoxic 2VB5 cells in both bright-field (LEFT) and Fluorescent FITC (RIGHT) channels. TOP: Isolated B16F10 transfected normoxic cell isolated into monoculture showing no EGFP expression. MIDDLE: Hypoxic 2VB5 cell showing high Oct4 expression that appears to be in late telophase of cell division. BOTTOM: Another of the 2VB5 monoclonal cells at the beginning of metaphase cell division. Images were captured using an Olympus IX53 fluorescent microscope using bright-field and FITC channels. Scale is 50 µM.
The B16F10 2VB5 Phenotype does not Demonstrate Increased Migration over the Oct4EGFP Containing Phenotype. Hypoxia is commonly known to increase cell migration through a variety of cellular pathways.
Upregulation of “stemness” markers such as Oct4 and SOX2 have been demonstrated to contribute to EMT in a variety of cancers [151, 152]. To test this, a scratch assay was employed with multiple time points to track cell migration. Figure 12 shows both B16F10Oct4 normoxic cells compared with the 2VB5 phenotype and documents their migration pattern tested at both 6 h and 24 h. Image panel figure 12 demonstrates the same assay as a representation of images that were measured to track the front of migration. These data were supported using the JuLi BR system that is capable of both measuring cell confluence and wound healing assays. Figure 12 shows the results of the comparison using both methods, with a slight increase in the amount of time to reach confluence for the 2VB5 phenotype. However, after repeat measures of migration from each phenotype, this result was found to be non-significant.
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. A) B)
Hypoxic
Normoxic
Figure 12: B16F10 Oct4 Normoxic vs 2VB5 Hypoxic Migration Figure depicts migration of normoxic or hypoxically cycled cells. A) No significant difference in normoxic vs hypoxic cells in a migration assay when measured over 6 h and 24 h. Results are presented as means±SD (N=3, n=9), with * indicating a difference from Z (P<0.05), for Oct4 normoxic vs 2VB5 hypoxic cells at both 6 h and 24 h. B) Migration over-time with the JuLi cell monitoring system giving the same result. Image panel shows the scratch assay imaged at 0, 6
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Neither B16F10wt nor 2VB5 Phenotypes Metastasise from a Primary s.c. Injection Site To determine if there was an increase in the metastatic potential of the 2VB5 hypoxically cycled
B16F10 phenotype, the indicated concentration of either B16F10wt or 2VB5 cells were injected s.c. into the LHS flank of C57Bl6 mice and observed for both primary tumour growth and number of metastasis. Figure 13 shows the growth rate of the primary tumours with both B16F10 in the 105 and 104 cell injection density forming primary tumours as expected with a difference in initial growth time that is reflective of the cells doubling time. Once initial tumour are begun, the time until the tumour met the allowable size as dictated by the animal ethics permit was practically identical. The hypoxically cycled 2VB5 cells took far longer to form primary tumours. Once the tumours were observed, the amount of time until the allowable tumour size before culling of the animal was the same as for the wild-type population. To ensure that the
2VB5 Oct4 expressing cells were indeed able to form a primary tumour as opposed to the non- expressing population for this phenotype (which may have accounted for the delay in growth times, the non-expressing population only comprising ~15% of these cells), A tumour section was taken and grown back to confluence. Image panel 13 shows 2VB5 cells in culture expressing
EGFP as well as tumour section that was removed from the mouse with EGFP expression apparent.
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Figure 13: B16F10wt vs 2VB5 Hypoxic Primary Tumour Formation and Survival Time from first Observed Tumour Measurement Figure shows amount of time in days for primary tumour growth after s.c injection into the LHS flank of C57Bl6 mice at the concentrations of cells as indicated. The amount of growth time once a tumour was established was practically identical among the different amounts and phenotypes used. Results are presented as means±SD (N=1, n=4), with * indicating a difference from Z (P<0.05) for comparison among the 3 different phenotypes and numbers of cells tested. Images show the 2VB5 cell line (TOP) and a cell line derived from a primary tumour (BOTTOM) showing EGFP expression indicating that the plasmid was retained and 2VB5 cells were capable of forming tumours. Note that the B16F10 cell line is not recognised as a primary metastatic tumour model. Schematic shows how other groups have demonstrated metastasis from a primary tumour with the primary tumour resected once it becomes too large to meet with animal ethics requirements.
Discussion
Summary This chapter has expanded upon the hypoxic work performed previously and provides stable
Oct4 expressing cells for use in drug cytotoxicity assays performed in the next chapter. The validity of the Oct4 plasmid was tested using CoCl2 as a form of pseudohypoxia to test whether
Oct4 expression was increased. Note that other data from our laboratory confirmed that Oct4
114 of 329 levels were increased in parallel with EGFP expression after hypoxic cycling by testing with
Western blot using F9 stem cell lysate as a control. Isolated single cells and spheroids from hypoxic incubation were also tested for their Oct4 expression and demonstrate that single cells largely reform the same Oct4 expression profile as the parent population and that spheroids are a heterogeneous mix of Oct4 expressing cells. It was also observed that these spheroids, when isolated and grown back in normoxic culture, reform a monolayer culture while retaining the original spheroid morphology. Testing of the hypoxically cycled B16F10 cells in animal models yielded several strange results and there was no obvious increase in their metastatic potential from a primary tumour site when using s.c. injections.
B16F10 Cells Stably Express Oct4EGFP after Several Rounds of Hypoxic and Normoxic Incubation The B16F10 cells that were transfected with Oct4EGFP and hypoxically cycled and sorted
(2VB5) maintain an expression profile of ~85% when kept in normoxic culturing conditions for extended periods. This expression can be increased in the short term with further exposure to hypoxia. However, performing this several times and monitoring the results consistently saw that the stable level of EGFP expression was ~85%. The theory surrounding dedifferentiation of metastatic melanoma is in part linked to HIF becoming constitutively active causing dedifferentiation through upregulation of Oct4, as well as several other stem cell factors [47,
153]. However, the levels of HIF found in these cells using various methods is typically quite low and it would seem as though these cells behave more as having “stem-like” characteristics, rather than those of an actual stem cell as they are currently described. Interestingly, even after rounds of hypoxic and normoxic incubation followed by rounds of sorting selecting on the top
5% of EGFP expressing cells was still unable to produce a 100% Oct4EGFP expressing cell phenotype. Further culturing of these high EGFP expressing cells is able to increase the
115 of 329 expression of Oct4 in the short term. However, they always revert to the same EGFP expression.
It is thought that these stem-like cells either revert back to a lower or non-EGFP expressing state, or that their progeny are more differentiated similar to the model of transit amplification.
Pseudo Hypoxic Stress using CoCl2 Increased Oct4EGFP Expression in both Hypoxic and Normoxic B16F10 Cells Testing both B16F10 Oct4EGFP normoxic and 2VB5 hypoxic phenotypes with various concentrations of CoCl2, a known inducer of HIF and pseudo hypoxic stress, was able to increase
EGFP expression. Note that CoCl2 is toxic to cells and higher concentrations and longer durations that were tested showed obvious signs of poor cell health and a decrease in the amount of EGFP in the high expressing cells, with a marked increase in “sick” or apoptotic cells as witnessed by their cytometry profiles [149, 154]. Most interestingly, while the normoxic type seems to increase uniformly and in a concentration dependent manner, the 2VB5 hypoxic population only seemed to shift in the non-EGFP expressing group. It would appear as though these cells are able to shift phenotype between Oct4 expression in response to hypoxic (or at least pseudo hypoxic) stimuli, although the mechanism for this remains elusive. This in some way supports the previous data regarding dedifferentiation of these cells. It would seem as though a certain subset of these cells are not locked in to the stem-like state through hypoxia alone. The theory surrounding this is that cells remain in the stem-like state through upregulation of stemness factors through constitutive HIF acquired through the hypoxic process. However, data from other groups [155] has shown that this “constitutive” activation of HIFs through hypoxic cycling is far less than the amount that is activated by hypoxia. This may then explain why these cells can switch between the phenotypes, these cells not being firmly locked into the
HIF regulated high Oct4 expressing phenotype [156, 157]
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Hypoxic incubation quite rapidly gives rise to numerous cell spheroids upon reoxygenation of the culture. These cell spheres are proven to be viable cells through the use of trypan blue.
Several other groups have witnessed these spheroids and they are commonly associated with hypoxic incubation [158-160]. Interestingly, these cell spheroids were shown to highly express
Oct4EGFP. However, it is noted that the center of these spheres would most likely contain regions of depleted oxygen supply, similar to what would be witnessed within a tumour proliferating in vivo. When these spheroids are isolated and grown in normoxic culture, a monolayer of culture was seen to spread out from the spheroid that represents the normal layer that would be observed. Other groups have shown that upon exposure to normoxic culture conditions with non-stem cell media and lysine treated flasks demonstrate that these cell spheroids tend to disperse and form a standard monolayer [161, 162]. This was not observed with the B16F10 cells line after repeated observations – the original cell spheroid always remained, and highly expressed Oct4EGFP. This may in some way be explained by constitutive
HIF levels in these cells, not allowing for the reversal of cell-cell adhesion bonds that are a result of HIF regulation in melanoma cell lines as compared to other cell lines.
It was believed that isolating single cells would produce a more uniform cell population if cells were locked into their phenotypic state. The clones gave a range of Oct4EGFP expression which provides further evidence that they are able to switch their phenotype. The profiles do range a bit in the intensity of their expression and amount of Oct4 expressing cells. However, they largely appear to resemble the original expression – a certain number of cells in the non-expressing region, regardless if the population was generated from a single clone or not [163]. This is further observed in isolated spheroids [164]. Of the three that were successfully isolated, all
117 of 329 appear to contain at least three separate phenotypes representing non-expressing, low expressing and high Oct4 EGFP expressing cells [165, 166].
Isolating Oct4 expressing cells from the normoxic line would have been helpful in further characterizing the heterogeneous profile of these cells. Unfortunately, of the four clones that were isolated, none of them were Oct4 expressing. This is not surprising given the frequency of these cells in the population (typically 1-5%). Due to the time required to isolate and grow these clones back into populations that could be assayed, this was not investigated further.
Interestingly, of the four clones isolated, none of them have any Oct4 expression at all. It would be interesting to subject these cells to hypoxia to see if the Oct4 expression could be increased.
These cells still retain the Oct4EGFP plasmid as they are neomycin resistant as expected.
Scratch Assay The scratch assay is a commonly employed measure of cell migration [167, 168]. While this technique is commonly used, cheap and easy to perform, it is not without its inaccuracy [169].
The data shown in figure 11 indicates that there may be a slight increase in the migratory capacity of the B16F10 2VB5 hypoxic cells over the B16F10 Oct4 normoxic cells. However, following repeated measures of the migration front of the cells assayed, it was determined that there was no increase in the migration of the B16F10 2VB5 hypoxic cells when compared to the
B16F10 Oct4 normoxic cells that were used as a control for this experiment (Figure 11). Subtle differences in the width of the scratch may make it appear as though the “scratch” has closed more slowly/quickly than those of the control. However, this did not stand to repeated testing when measuring migration distances. It was also believed that cells that more highly express
Oct4 would be more likely to migrate than low Oct4 expressing or the wild-type population due to HIF upregulating promigratory factors. However, monitoring these cells in the scratch assay
118 of 329 format saw no obvious increase in the migration of high expressing cells vs lower or non- expressing populations.
Animal Work Testing of the propensity of the B16F10 wild-type and high Oct4 expressing (2VB5) cells to migrate from primary tumours through s.c injection into C57Bl6 mice was not successful. None of the primary tumours were shown to migrate and no colonies were observed on the lungs at the completion of this work. There are several explanations for this [170]. The B16F10 cell line represents more of a t.v.i lung metastatic model and is not commonly associated with a primary tumour migration model [171, 172]. It was believed that after rounds of cycling hypoxia, this would make the cell line more metastatic from primary tumour, however this was not observed in this experiment. It would have been more beneficial to examine the effect of 4T1 migration from ectopic models [173]. However, as these cells and the 4T1.2 counterpart were never subjected to the hypoxic cycling as were the B16F10 cells, this was less valid in these experimental settings. From this preliminary experiment, it would appear as though the hypoxically cycled 2VB5 cells are not more metastatic than the wild-type population. There may be an issue with the maximum allowable size for primary tumours as allowable by the ethics permit (10 mm in any direction). This may not allow for enough time for tumour cells to migrate from the primary or does not allow for them to grow large enough to be observable on the lungs at the time of autopsy. Other groups have documented a model whereby primary tumours are excised in order to allow metastatic tumours to grow. However, given the amount of surgery that would be required on the animals, the amount of time required to apply for ethics approval for this, the amount of training that would have been involved to perform animal surgeries such as this, the large amounts of time involved in the procedure itself, and the fact that after all of this,
119 of 329 there still may be no appreciable increase in metastatic lesions in this model, this was not tested further.
One of the most interesting facets of this experiment is the amount of time taken for the Oct4 high 2VB5 cells to form primary tumours. The dilutions of wild-type B16F10 cells formed tumours extremely uniformly. Given the doubling rate for B16F10 cells stated at 17.2 h [174,
175] (measured at 19 h in my own assays). It would be expected that cells at ten-fold dilution lower would reach the same tumour volume after a couple of days, and this was witnessed with the B16F10 wild-type population. However, the 2VB5 cells took 44 days to form tumours, 33 days longer than the wild-type population. The reasons for this are unclear. It is possible that these stem-like cells are more dormant when placed in vivo. However, this is not the case when measuring in vitro, the migration rates and doubling times being virtually identical. It is possible that the addition of the Oct4EGFP plasmid or hypoxic cycling itself makes the cells more easily recognizable to the innate immune system, thereby leading to the destruction of a greater number of cells when the tumour is generating [176]. Regarding hypoxic incubation, this could be related to the expression of inflammatory markers. Although unlikely, it may be that more of these cells migrate from the primary inoculation site, therefore leaving less to form the primary tumour bulk. However, given the difficulty witnessed from others and better models existing, this was not explored further.
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Chapter Four
Results: NSAIDs as a Cancer Therapy
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NSAIDs as a Cancer Therapy
This section contains results from the publication: [177] Pritchard, R., et al., Celecoxib inhibits mitochondrial O2 consumption, promoting ROS dependent death of murine and human metastatic cancer cells via the apoptotic signalling pathway. Biochem Pharmacol, 2018. 154: p. 318-334
Introduction Non-steroidal anti-inflammatory drugs (NSAIDs) as the name implies, are a class of non- steroidal drugs that mediate pain and inflammation chiefly through inhibition of E2 prostaglandin synthases and downstream effects on cyclooxygenase 1, 2 or both. They are widely used with many varieties being common over the counter medications. Interest has arisen over the use of NSAIDs as anticancer drugs following epidemiological data that demonstrates cancer patients taking NSAIDs longitudinally have markedly lower incidences of cancer recurrence. The proposed mechanism for this reduction is typically centered on COX inhibition through its effects on inflammation, anti-angiogenesis properties and certain effects on migration and the cell cycle. The ability of NSAIDs to inhibit either COX-1 or COX-2 varies markedly, yet typically falls into one of three categories:
1. Competitive reversible binding of COX-1 and COX-2 (examples include: piroxicam, mefenamic acid and ibuprofen)
2. Rapid low affinity reversible binding followed by time-dependent, higher affinity, slowly reversible binding of COX-1 and COX-2 (examples include diclofenac, indomethacin and flurbiprofen)
3. Rapid reversible binding follows by covalent modification of COX-1 and COX-2
(example: aspirin)
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However, a gathering body of evidence has suggested that other mechanistic aspects are at play.
We therefore set out to test five widely used and commonly prescribed NSAIDs in order to test their efficacy to eliminate metastatic cancer cell lines originating from murine metastatic melanoma and breast cancer, B16F10 and 4T1 respectively. Celecoxib (marketed as Celebrex), is a COX-2 specific NSAID of the Coxib family that is typically prescribed for the treatment of rheumatoid arthritis (RA) and is currently FDA approved for the treatment of familial adenomatous polyposis (FAP). Celecoxib is a slow competitive binder of COX-2 and in high concentrations binds irreversibly. Diclofenac (Voltaren) is used as a general NSAID commonly focusing on RA, osteoarthritis and gout. The COX-2 selective nature of diclofenac is quite similar to that of celecoxib yet is seen to have more far-ranging side effects. Nimesulide (various generic names) is commonly prescribed in the treatment of acute pain and osteoarthritis.
Nimesulide is weak competitive inhibitor of COX-1, but a potent time-dependent inhibitor of
COX-2. Sulindac (Clinoril) is a prodrug used to treat acute and chronic inflammatory conditions.
It is less COX-2 selective than celecoxib (5-fold selective vs up to 50-fold for celecoxib) and is seen to have comparable gastrointestinal side effects. Salicylate (Aspirin) is commonly used to treat pain, fever and inflammation and has other physiological benefits due to its anti-platelet function in reducing the risk of thrombotic events. It is non-COX selective and displays a range of adverse effects chiefly gastrointestinal in nature or related to excessive bleeding. The NSAIDs chosen for this study therefor represent a range of the NSAIDs and a variety of differing COX-1 and COX-2 selectivity and affinity.
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Aims Given the information presented in the literature review and above, as well as the evidence from multiple research outputs, including; in vitro, in vivo, clinical trials and epidemiological studies,
NSAIDs obviously warranted further investigation. With respect to the differing efficacy and mechanisms tested, we set out to:
1. Test a variety of NSAIDs for their cytotoxicity against, particularly, metastatic cancers
2. Select a variety of NSAIDs that from the literature have shown to be promising anti-
cancer drugs
3. Test the NSAIDs against the B16F10 2VB5 (hypoxic) cell line that is hypothesised to
represent a more stem-like population, and the 4T1.2 cell line that is shown to be more
metastatic than the parent populations
4. Ensure that, of the NSAID drugs selected, there was a reasonable mix of COX selection,
as well as platelet inhibition, that are stated as the main mechanisms of anti-cancer action
prescribed to the NSAIDs
5. Demonstrate that the non-COX-2 inhibitory DMC still exhibits anti-cancer or cytotoxic
actions against cancer cell lines
6. Present a viable mechanism for the anti-cancer actions of the NSAIDs tested that is not
COX related
The five NSAIDs were assayed to determine their cytotoxic and growth restricting capabilities using Sytox green nuclear dye, a DNA binding and membrane impermeable dye. Cell health and growth restriction was measured both with the use of a spectrometer and fluorescent microscopy.
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Further assays were undertaken to identify if the NSAIDs tested induced apoptosis. Further to this, a host of basic mechanistic assays were undertaken to identify whether the NSAIDs.
Figure 14: Structure of the NSAIDS used in this Study
Molecular structures of the NSAIDs used in this project. Note the difference in COX active celecoxib vs non-COX-2 inhibitory DMC with the addition of a second methylated head group on one of the aromatic rings.
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Solubility Study The NSAIDs celecoxib, DMC, nimesulide and sulindac, and the vitamin-E analogue αTS that was used as a control for ROS production are markedly insoluble in water, alcohols and DMSO
(Table 7 - Methods section). Testing was then performed on three different types of cyclodextrins (α-cyclodextrin, 2-hydroxypropyl-β-cyclodextrin (HBCD) and γ-cyclodextrin) for their ability to solubilise in ddH2O. HBCD was the most soluble after 24 h and was chosen as the solubilising agent for the remainder of the study (Figure 15). Preliminary attempts to solubilise the NSAID in the concentrations required to produce cytotoxic effects were met with unacceptable levels of toxicity from the vehicle controls (Figure 15). The NSAIDs still remained largely insoluble until the addition of 100uL/mL 1M NaOH and heating to 60 oC for 10 min, at which point a clear solution without precipitates was achieved. HBCD was then tested in culture vs equal volumes of other common solvents without any significant effects on cell cultures over
72 h (Figure 16). Following this, the HBCD + NaOH vehicle was tested on all of the cell lines and phenotypes used in the study for a period of 72 h and included as internal controls for the experiments with no significant impact on cell health (Figure 16).
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Figure 15: Different Forms and Structure of Cyclodextrins that were Tested for Drug Dilutions The Taurus-like structure of the cyclodextrins used to solubilise various hydrophobic drugs in these assays. Theory suggests that solubilization occurs due to hydrophobic molecules being incorporated into the inner ring of the structure with water molecules binding to the outer hydrophilic layer. After testing multiple cyclodextrins, 2-hydroxypropyl-β-cyclodextrin (HBCD) was determined to be the best.
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Optimization of Cytotoxicity Assays To determine whether there would be significant interference from the EGFP transfected cells, these cells were tested for fluorescence against an equal number of cells expressing Sytox.
Figure 16 shows that the signal from 104 cells incubated overnight expressing EGFP is approximately an order of magnitude lower than those stained with Sytox. The background signal from all cell lines and phenotypes was deducted from the final cytotoxicity plots. Initial testing of NSAIDs was completed on the B16F10 cell line using EtOH and ddH2O vehicles as appropriate. Initial testing comprised a range of 5-fold dilutions from 500 μM down to 160 nM to obtain an approximate range for further investigation. Even at these relatively high doses, the
NSAIDs nimesulide, sulindac and salicylate were not particularly effective in inducing death in the B16F10 cell line. Due to the relatively high amount of vehicle (4%) that was required due to the solubility and concentrations of NSAIDs required, it was noted that the EtOH vehicle alone was having a significant effect on the outcome of the cytotoxicity assay. Several other vehicles were then tested. Figure 15 demonstrates the outcome of testing a variety of vehicles on B16F10 cells in culture. Once a stable solution for the NSAIDs had been found (see Solubility Study above), the assay was retested utilising a concentration range that encompassed the NSAIDs tested 800-50 µM for a period of 96 h (Figure 15). However, further investigation into the availability of NSAIDs to the tissues in vivo based on standard dosing (Table 8) shows that these levels are impractical and are highly unlikely to be achievable. Also, due to Sytox dye measuring only cell death as opposed to viability, the results of the preliminary study are not a measure of cell viability. A method of measuring GI50 was then employed based on total number of cells and utilised throughout the remainder of the study.
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Figure 16: Optimization of the Sytox Cytotoxicity Assay and Cyclodextrin Cytotoxicity after Repeated Testing Figure shows initial prescreening of NSAIDs using a 5-fold dilution series to determine a concentration range using EtOH vehicle presented as means±SD (N = 1, n = 3). NSAIDs were then tested in a narrower range over 96 h to observe cytotoxicity presented as means±SD (N = 1, n = 3). Ethanol and other alcohol vehicles were shown to have a dramatic impact on cell heath when tested at the concentrations used presented as means±SD (N = 1, n = 3). Cyclodextrin vehicles were then employed after being shown to have negligible effects and solubilised the hydrophobic NSAIDs well. Sytox signal was measured against transfected EGFP expressing cells to ensure sound measurement could be made and background signal subtracted presented as means±SD (N = 1, n = 3). Statistics N.D. for optimisiation assays. All cells and phenotypes used in this study tested against HBCD vehicles included as internal control for the experiments show no significant alteration in cell health Results are presented as means±SD (N=2, n=6), with no significant difference from Z (P<0.05) observed in untreated vs vehicle treated cells . All assays were measured on a Molecular Devices Flex Station 3 plate reader measuring Sytox Green fluorescence Ex: 485, Em: 525
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Table 8: Recommended Daily Dosing of NSAIDs vs Cmax at Tissues
Note that this table was adapted from the publication in Appendix V and the references in this table are part of that document.
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IC50 and GI50 NSAIDs
Further testing of GI50 values was carried out on both cell lines and phenotypes to determine the effects of NSIADs. Figure 17 demonstrates the response of the B16F10 and hypoxic 2VB5 cell line, and 4T1 and the more metastatic variant 4T1.2 [178] cell lines to NSAID treatment over 72 h. For all of the cell lines and phenotypes tested, DMC and celecoxib are by far the most potent, with diclofenac and nimesulide having moderate effects at the higher concentrations, and sulindac and salicylate being relatively ineffective (one exception is sulindac for the 4T1 cell line). When the NSAIDs are examined for their potential to affect different cell phenotypes
(Figure 18 & 19), there is no obvious difference when analyzing the B16F10 and hypoxic variant
2VB5. In fact, it would appear that there is a slight measure of resistance in the 2VB5 phenotype when treating with both celecoxib and DMC. All of the other curves for the other NSAIDs treated on both B16F10 phenotypes are practically identical. However, when comparing the 4T1 and 4T1.2 phenotypes, the response to celecoxib, DMC and sulindac is markedly improved, with the diclofenac, nimesulide and salicylate curves being practically identical.
The plate reader data was supported with the use of fluorescent microscopy. Both B16F10 and
4T1 cells were imaged in 96-well plates post 48 h of NSAID treatment. Image panels figure 20
& 21 show B16F10 and 4T1 respectively. Vehicle control shows healthy populations with minimal Sytox uptake. Celecoxib and DMC wells show almost 100% cell death at these concentrations (100 μM celecoxib and 50 μM for DMC). Diclofenac and Nimesulide treated wells show distinct morphological changes and a reduction in cell growth at 200 μM. However, the amount of Sytox positive cells is far fewer than that witnessed with celecoxib and DMC treatment, even at these higher concentrations. Sulindac and salicylate show almost no visible reduction of cell growth or increase in cell death at this concentration 200 μM as expected.
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B16F10 - NSAIDs 2VB5 - NSAIDs 120 120 Celecoxib Celecoxib
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Figure 17: B16F10wt and 2VB5 Hypoxic, 4T1wt and 4T1.2 Cell Lines and Phenotypes Response to NSAID Treatment Comparison of all cell lines and phenotypes tested vs concentrations of NSAIDs as indicated. In every instance celecoxib and DMC are the most cytotoxic. Results were measured on a Molecular Devices Flex Station 3 plate reader measuring Sytox Green. Results are presented as means±SD (N=2, n=6), with dotted likes indicating the confidence interval (95%) for each as compared to vehicle treated populations represented as 100%. Image panel is a representative sample showing an increase in Sytox uptake by dead cells post 72 h treatment with increasing concentrations of celecoxib, A) vehicle (HBCD) treated, B) 50 µM, C) 100 µM, D) 150 µM. Images were captured using an Olympus IX53 fluorescent microscope using bright-field and FITC channels.
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B16F10/2VB5 - Celecoxib B16F10/2VB5 - DMC
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Figure 18: Comparison between B1610 and 2VB5 Hypoxic Phenotypes in Response to NSAID Treatment Comparison between all of the NSAIDs tested between the two B16F10wt and hypoxic 2VB5 phenotypes. No obvious increase was witnessed for any of the NSAIDs when tested against the hypoxic phenotype vs the wild-type cells. In fact, it appears as though the 2VB5 phenotype is at least mildly resistant to the effects of both celecoxib and DMC. Results were measured on a Molecular Devices Flex Station 3 plate reader measuring Sytox Green. Results are presented as means±SD (N=2, n=6), with dotted likes indicating the confidence interval (95%) for each as compared to vehicle treated populations represented as 100%.
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4T1/4T1.2 - Celecoxib 4T1/4T1.2 - DMC
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Figure 19: Comparison between 4T1 and 4T1.2 Phenotypes in Response to NSAID Treatment Comparison between all of the NSAIDs tested between the 4T1 and the metastatic 4T1.2 phenotypes. There is an obvious increase in cytotoxicity of celecoxib, DMC and sulindac with a shift of the curve for 4T1.2 vs the wild-type 4T1. Demonstrating that at least in this instance, these NSAIDs appear to be more effective against more metastatic cell phenotypes. Results were measured on a Molecular Devices Flex Station 3 plate reader measuring Sytox Green. Results are presented as means±SD (N=2, n=6), with dotted likes indicating the confidence interval (95%) for each as compared to vehicle treated populations represented as 100%.
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Figure 20: Bright-Field and Fluorescent Images of B16F10wt Cells in Response to NSAID Treatment at 200 µM post 48 h Images show B16F10wt cells after treatment with NSAIDs for 48 h using both bright-field (LEFT), fluorescence in the FITC channel (MIDDLE) and overlaid (RIGHT). 1) Vehicle treated (HBCD) cells with normal morphology and very few dead cells. 2) Celecoxib treated (100 µM) with mostly dead cells as evidenced with Sytox uptake (green). 3) DMC treated cells (50 µM) with mostly dead cells similar to celecoxib treated above at half the concentration. 4) Diclofenac treated (200 µM) cells with little cell death but a reduction in growth and marked changes in cell morphology. 5) Nimesulide treated (200 µM) cells with no cell death but a reduction in cell
139 of 329 number and changes to cell morphology. 6) Sulindac treated (200 µM) cells with little effect on cell health, number or morphology at this concentration. 7) Sulindac treated (200 µM) cells with little effect on cell health, number or morphology at this concentration.
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Figure 21: Bright-Field and Fluorescent Images of 4T1wt Cells in Response to NSAID Treatment at 200 µM post 48 h Images show 4T1wt cells after treatment with NSAIDs for 48 h using both bright-field (LEFT), fluorescence in the FITC channel (MIDDLE) and overlaid (RIGHT). 1) Vehicle treated (HBCD) cells with normal morphology and very few dead cells. 2) Celecoxib treated (100 µM) with mostly dead cells as evidenced with Sytox uptake (green). 3) DMC treated cells (50 µM) with mostly2) dead cells similar to celecoxib treated above at half the concentration. 4) Diclofenac
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treated (200 µM) cells with little cell death but a reduction in growth and marked changes in cell morphology. 5) Nimesulide treated (200 µM) cells with no cell death but a reduction in cell number and changes to cell morphology. 6) Sulindac treated (200 µM) cells with little effect on cell health, number or morphology at this concentration. 7) Sulindac treated (200 µM) cells with little effect on cell health, number or morphology at this concentration.
Apoptosis in Response to NSAID Treatment The ability of the NSAIDs to induce apoptosis over time was determined with the B16F10 cell line. Testing was performed over 24 h increments after treatment with IC50/72 h. Figure 22 shows all NSAIDs displaying a significant increase in annexin-V staining after 24 h with these values increasing over the 48 h and 72 h time points. The exception here was with salicylate that was assayed at the maximum value of 800 μM and failed to increase annexin-V staining significantly after 72 h of treatment. Based on these results both B16F10 and 4T1 cells were exposed to each NSAID using its IC50/72 h concentration and apoptosis levels assayed after 24 h
(Figure 22). All of the NSAIDs increased the levels of apoptosis over the control (apart from salicylate that was assayed at the maximum concentration of 800 μM). The five NSAIDs were then compared using a fixed concentration of 50 μM for 48 h (Figure 22). Again, celecoxib proved the most potent, causing extensive apoptosis by 48 h in both B16F10 and 4T1 cell lines
(mean 63% and 67% apoptosis respectively).
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Figure 22: Apoptosis induced by NSAIDs using IC50 Values or 50 µM at Multiple Timepoints A) Overtime observation of apoptosis at 24 h timepoints in the B16F19 cell line (N = 1, n = 3). B) Testing of both B16F10 and 4T1 cell lines after 24 h (N = 2, n = 6). C) Testing of both B16F10 and 4T1 cell lines using a fixed dose of NSAID (50 µM) for 48 h (N = 2, n = 6). All assays used annexin-V and PI staining and were analyzed using a BD Fortessa flow cytometer using FITC and PE channels. Results are presented as means±SEM with * indicating a difference from Z (P<0.05) in comparison to untreated controls.
Observation of ROS levels after NSAID Treatment To further investigate the mechanisms for the NSAID-mediated toxicity on the metastatic
B16F10 and 4T1 cancer cells, the ability of the NSAIDs to promote cellular ROS production was analyzed. Exposing these two cell lines to 50 μM of each NSAID did not significantly change the endogenous levels of cytosolic ROS detected by DCFDA in either cell line over 2 or 24 h of treatment (Figure 23), interestingly with the exception of a salicylate-induced increase detected at 24h in the B16F10 line. Slightly increased cytosolic ROS was obtained with 50 μM tert-butyl hydroperoxide (TBHP) added as a positive control for producing ROS inside the cells. Hence, the present data indicate that cytosolic levels of ROS were not greatly affected by the NSAIDs.
These results were confirmed with the use of the CellROX reagent coupled with FACS
(Appendix II) showing that in the B16F10 cell line only salicylate and nimesulide display a significant increase in cytosolic superoxide after 2 h, with levels after 24 h largely returning to normal (nimesulide still having a significant increase at this time point)
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Figure 23: Cytosolic ROS induced by NSAID Treatment at both 2 h and 24 h in both B16F10wt and 4T1wt Cell Lines
Cytosolic ROS was measured using DCF in both cell lines at both 2 h and 24 h. No obvious increase was witnessed at either time-point with the exception of salicylate. NAC and peroxide saw decreases and increases as negative and positive controls, respectively. Results are presented as means±SD (N=2, n=6), with * indicating a difference from Z (P<0.05) in comparison to untreated controls.
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Next, both cell lines were exposed to each individual NSAID fixed at 50 μM and the superoxide production levels assayed at regular 2 h intervals for up to 6 h. Alpha-tocopherol succinate (α-
TOS), a known potent inducer of mitochondrial superoxide [179], was included as a positive control for enhancing mitochondrial ROS production. Celecoxib was the only NSAID that induced greater levels of mitochondrial superoxide production by 2 h (39% increase over control; Figure 24). However, by 4 h, the celecoxib treated B16F10 cells showed substantially greater mitochondrial superoxide (137% increase above control cells; Figure 24), with diclofenac then displaying a non-significant increase. By 6 h, all five of the NSAID-treated B16F10 samples started to show increased mitochondrial superoxide production, with both diclofenac and nimesulide induced levels then becoming significant (Figure 23, 103% and 118% increase respectively). By 6 h, the celecoxib induced levels of ROS production started decreasing, consistent with a transient oxidative burst of mitochondrial superoxide taking place.
Interestingly, these results were not observed when testing the 4T1 cell line in the same format.
Only celecoxib showed a significant increase in superoxide and only at 2 h. The only other significant increase in superoxide came from the use of the control αTS and only after 6 h.
Further investigation demonstrated that higher concentrations of αTS were required to induce superoxide in this cell line, and that the superoxide burst was occurring more rapidly in these cells – perhaps explaining why there was only a significant increase with the use of celecoxib after 2 h, the superoxide burst dissipating at this point. This is supported with testing concentration ranges of NSAIDs with MitoSOX (Table 9)
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Figure 24: Mitochondrial Superoxide Produced in both B16F10wt and 4T1wt cells at 2- 6 h post Treatment using 50 µM of NSAIDs Figure shows the measurement of superoxide using the MitoSOX reagent analysed by cytometry at 2, 4 and 6-hour timepoints post treatment with 50 µM of NSAIDS as indicated. Cytometry histograms are unstained, αTS, celecoxib, nimesulide, sulindac and salicylate after 4 h in the B16F10 cell line as an example. Results are presented as means±SEM (N=2, n=6), with * indicating a difference from Z (P<0.05) in comparison to untreated controls.
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Table 9: Dose Depended Increase in Superoxide Production in Response to NSAID Treatment
Concentration (μM) Drug/Cell Line
αTS 100 200 400
B16F10 3.6±0.7 4.8±1.4 4.5±0.8
4T1 6±2.3 6.3±2.9 6.1±1.6
Celecoxib 25 50 100
B16F10 1.2±0.2 2.7±0.5 4.7±1.2
4T1 1.4±0.1 2.8±0.06 13.8±0.9
Diclofenac 100 200 400
B16F10 1.2±0.2 1.3±0.3 1.5±0.4
4T1 1.7±0.3 1.5±0.3 1.5±0.2
Nimesulide 100 200 400
B16F10 1.3±0.3 1.9±0.3 3.9±1.1
4T1 1.1±0.06 1.3±0.05 6.6±1.9
Sulindac 200 400 800
B16F10 1.7±0.1 3.6±1 1.8±0.6
4T1 1.5±0.7 4.7±3. 4.9±0.9
Salicylate 200 400 800
B16F10 0.6±0.1 0.4±0.1 0.5±0.1
4T1 1.2±0.06 1.4±0.2 1.5±0.4
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To examine the NSAID induced mitochondrial superoxide production more closely, treated cell samples were assayed by flow cytometry at regular 6 min intervals for up to 84 min (Figure 25).
Celecoxib induced significant mitochondrial superoxide production in both the B16F10 and 4T1 metastatic cells, detected as early as 12 min after drug addition, becoming strongly significant in both cell lines by 84 min, when compared to untreated controls. Nimesulide was the only other
NSAID that increased the levels of mitochondrial superoxide production over this time course, and only in the B16F10 cells (Figure 25). These findings indicated that celecoxib at this concentration (50 μM) was able to rapidly induce mitochondrial superoxide production over short time periods, whereas the other NSAIDs have a more delayed mechanism of action or are active only at much higher concentrations.
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Figure 25: Superoxide Production over Time in Response to 50 µM NSAID Treatment Early detection of MitoSOX signal in whole cells and confocal imaging. Changes in MitoSOX red signals assayed at 6 min intervals when treating B16F10 or 4T1 cells respectively with each NSAID (50 μM) analysed by flow cytometry.
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To investigate this further, ROS production was again analyzed using the fluorescent indicator dye MitoSOX red to detect mitochondrial superoxide [180]. Table 9 summarises the data for each of the NSAIDs, tested at different concentrations (as indicated) reflecting their IC50 values for their abilities over the first hour after adding drug to promote mitochondrial ROS production.
Of the NSAIDs, celecoxib was markedly more active at inducing significantly increased mitochondrial ROS production, even with low concentrations of added drug. These results were confirmed both by spectrophotometry and fluorescence microscopy (Figure 26) with celecoxib tested for 1 h over the range of 50-200 μM. Of the five NSAIDs, only celecoxib displayed such a markedly increased mitochondrial ROS signal above that of the control or vehicle alone treated cells.
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AI AII III IV
B16 V VI VII VIII
AI AII III IV
4T1 V VI VII VIII
Figure 26: Fluorescent Microscopy of Superoxide Induction in Response to NSAID Treatment
TOP: untreated (I), vehicle treated (II), positive control (III) (αTS, 200 μM), celecoxib (IV) (100 μM). BOTTOM: diclofenac (V) (200 μM), nimesulide (VI) (200 μM), sulindac (VII) (200 μM), and salicylate (VIII) (200 μM) treated cells after staining with MitoSOX and treatment with NSAID as indicated. Imaging was performed in triplicate and imaged on an Olympus IX53 microscope using a TX Red filter.
Effects of NSAID Treatment on Mitochondrial Membrane Potential To determine if treatment with NSAIDs was affecting the mitochondrial membrane potential as
one possible aspect of their induction of mitochondrial superoxide, both of the B16F10 and 4T1
151 of 329 cell lines were treated with NSAID for the indicated time point and their membrane potentials assayed via FACS after staining with TMRE. Only the 4T1 cell line displayed a significant decrease in membrane potential after the 2 h period after treatment with 50 μM of celecoxib
(Figure 27). However, data from collaborators shown in the publication [177] demonstrate that the effects on the mitochondrial membrane potential occur in the short term in response to
NSAID treatment, and it is likely that at the 2 h time point tested here the membrane potential has largely recovered in the short term, before the ensuing apoptotic cascade. A basic analysis regarding the difference in mitochondrial density between the two B16F10 and 4T1 cell lines shows a nearly 3-fold difference in the amount of signal for the B16F10 line. Further testing of the effects of NSAID treatment on the B16F10 using the dye Mitopotential (Appendix II) show a marked and significant increase in the number of depolarised cells in response to NSAID treatment at IC50 values for 24 h and 72 h the effects appears to be dose dependent. However, this is most likely a result of the apoptotic process and was not explored further.
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Figure 27: Mitochondrial Membrane Potential in Response to NSAID Treatment 50 µM after 2 h. Relative Difference in Mitochondrial Membrane Potential between the B16F10 and 4T1 cell lines The response of mitochondrial membrane potential to NSAIDs was measured using TMRE with CCCP as a control. Assays were analyzed using flow cytometry using a BD Fortessa flow cytometer using the PE filter. Untreated and vehicle (HBCD) treated populations were included as controls. Results are presented as means±SD (N=2, n=6), with * indicating a difference from Z (P<0.05) in comparison to vehicle treated controls. A comparison between the cell lines was made using the cytometer settings for B16F10 compared to 4T1 with CCCP added to reveal a difference in potential. Results are presented as means±SD (N=1, n=3), with * indicating a difference from Z (P<0.05) for comparison between the cell lines and CCCP treated cells.
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Discussion
Summary This chapter provided a screening of 6 NSAID compound to document their effects on highly metastatic cancer cell lines from murine melanoma and breast cancer. Also tested were the hypoxically cycled and Oct4 expressing 2VB5 cells and the perceived more metastatic variant
4T1.2 that was generated by [181]. The aims of the chapter were successful in that one compound stood out above the others and provided a promising candidate for further inquiry provide in the last experimental chapter, and due to its current role in many clinical trials throughout the world. Also demonstrated was the increase in cytotoxic potential from the celecoxib derivative DMC, providing evidence for the novel mechanism that cytotoxic cancer cell death is not from COX inhibition. Also provided in this chapter is an analysis of the potential of the NSAIDs to produce either cytosolic or mitochondrial ROS production, providing a novel plausible mechanism action.
Comparison between Metastatic and Hypoxic Phenotypes Interestingly, when treating the hypoxically cycled B16F10 2VB5 cell line in the same assays as its parent, the response to NSAID treatment does not appear to be significantly different. In fact, it appears as though the 2VB5 phenotype is somewhat resistant to the effects of celecoxib and
DMC. When looking at the 4T1 and 4T1.2 cells, the more metastatic 4T1.2 population is more sensitive to both celecoxib and DMC. The trend for the rest of the NSAIDs is much the same as that witnessed in the B16F10 cell line, with the exception of sulindac, which again appears to be more effective on the 4T1.2 phenotype. Note that this trend is also observed with collaborator data when testing against MDA-MB-231, MDA-MB-486 vs MCF-7 and 3T3 cells. It would appear then that at least in this study that more metastatic cancer cells are more sensitive to
154 of 329 celecoxib’s effects and that perhaps more “stem-like” Oct4 expressing population may have some mechanism of resistance. However, further testing with more cell lines placed under the same hypoxic stress would be required to prove this. It may also be possible that because the cells are maintained in normoxic conditions after the hypoxic selection process that they are not being forced to respire in a way that would make them more sensitive to NSAIDs. Further testing under hypoxic conditions would elucidate these factors.
NSAIDs Cytotoxic Effects on Cancer Cells Given the frequently observed decreased incidence of cancer from longitudinal studies of patients using low doses of NSAIDs for analgesic purposes, including preventing metastasis, much interest has arisen concerning the use of NSAIDs as potential anticancer therapies. In fact, recent results from a Phase II study have exemplified the clinical potential of celecoxib as a drug which greatly enhances survival and complete responses in patients with advanced Stage IV metastatic colorectal cancers when celecoxib was used as a treatment in combination with the chemotherapy, Capecitabine [182]. The five NSAIDs examined showed marked variation in their
IC50 values, although with the exception of salicylate, the other NSAIDs either decreased cell growth and/or increased cell death in a dose- and time-dependent fashion. Celecoxib and DMC were by far the most potent NSAIDs for inducing cell death in the range of metastatic cell lines tested here, including against human triple negative breast cancer cells, where it was active even at the low micromolar concentration. Diclofenac also induced cell death, although it required four-fold higher concentrations than celecoxib. Nimesulide restricted cell growth when at concentrations above 100 μM but was not a significant inducer of cell death compared to either celecoxib or diclofenac. Both sulindac and salicylate only induced cell death at very high μM to low mM concentrations making these unlikely to be achievable or useful as a therapy in vivo. In
155 of 329 the present study, celecoxib showed marked activity against the human triple negative breast cancer cell lines, decreasing proliferation within 24 h when using low levels (GI50 at 24 h was
∼6 μM for MDAMB468; and ∼20 μM for MDA-MB231). In these studies, the metastatic cancer cells were only exposed to a single dose of drug added at the start of the assays, with monitoring over periods of 24–72 h. Repeated daily doses of low (1–10 μM) celecoxib levels administered to the metastatic cancer cells could sustain much higher accumulative drug actions and effects in vitro, with a greater net cytotoxic activity and further decrease IC50 and GI50 values in a system more closely mimicking an in vivo dosing regimen [183]. In this regard, low and physiologically relevant levels (1–10 μM) of celecoxib have been reported to chemo sensitize cancer cells to subsequent treatment with common cytotoxic chemotherapeutic drugs such as doxorubicin [184,
185] and greatly enhances chemotherapeutic anti-metastatic cancer cell efficacy in vitro and in vivo [186], as well as in clinical trials of metastatic colorectal cancer patients [187]. Celecoxib induces mitochondrial ROS production required for triggering cancer cell death by apoptosis.
Our novel findings reported here clearly highlight previously unrecognized effects of the
NSAIDs such as celecoxib on mitochondrial respiration and function. The data presented here establish that celecoxib is a potent anticancer agent which can directly and rapidly affect mitochondrial O2 uptake by causing excessive mitochondrial superoxide production. These findings of excessive mitochondrial ROS production explain the previously reported celecoxib mediated mechanism of action inside cancer cells shown to proceed via the mitochondrial apoptosis signaling pathway [87]. Results from other studies are entirely consistent with our own findings presented here that celecoxib is cytotoxic for cancer cells independent of its effects on
COX-2 [90, 188], particularly for the closely related, COX-2 non-inhibitory analogue, dimethyl celecoxib, which shows even greater anticancer activity [70, 189]. Our results establish that
156 of 329 celecoxib increases mitochondrial ROS levels to trigger the ensuing cytotoxic actions of the drug, activating the intrinsic apoptotic pathway in metastatic cancer cells by disrupting mitochondrial metabolism and induces excessive ROS production directly from the mitochondria as an essential part of this death signaling process.
Clinical Relevance of Celecoxib’s Anti-Cancer Activity to Drug Pharmacokinetics in Humans We have included a table of recommended NSAID dosage per day, resulting peak serum concentrations, calculated maximum available concentrations (μM values) and source references
(Table 7), particularly relating to celecoxib in humans. It is important to note these concentrations as any effects witnessed with NSAID needs to be relative to a clinical basis. The ration between the IC50 values at concentrations available to the tissues of celecoxib are far closer than any of the other NSAIDs tested. Note that due to the relatively high Cmax of salicylate, preliminary testing was performed with 5mM of salicylate (10x its Cmax values) and show that while initially slowing the growth of B16F10 cells, it did not induce cell death
(Appendix II) Other NSAIDs have been ruled out due to their much higher (clinically irrelevant)
IC50 values and inability to increase mitochondrial ROS at achievable levels. Furthermore, levels of celecoxib can be achieved in the 10–20 μM range which are sufficient and capable of effectively killing cancer cells in vivo. Analysis of peak plasma concentrations for celecoxib from patients taking daily doses (400 mg) for rheumatoid arthritis (RA) and (800 mg, as a 400 mg dose taken twice-daily) for familial adenomatous polyposis (FAP) after 3–4 h reached ∼4
μM and ∼8 μM respectively [190]. Peak levels depend on patient CYP2A9 versus CYP2C8 polymorphisms of the cytochrome P450 oxidases which metabolize celecoxib [191].
Interestingly, patients given 200-mg celecoxib+200-mg ketoconazole daily for 7 days to inhibit
CYP enzymes showed the highest Cmax 12 μM, with no side effects [190]. More recent
157 of 329 advances in drug delivery based around mixtures of polyvinylpyrrolidone (PVP)/d-α-Tocopherol polyethylene glycol 1000 succinate (TPGS) as solid dispersion nanoparticles [192] or supersaturating self-emulsifying drug delivery systems (S-SEDDS) [193] have significantly increased the dissolution and orally administered bioavailability of celecoxib. The area under the concentration-time curve (AUC 0→24 h) and peak plasma concentration (Cmax) was increased several fold using celecoxib-PVP-TPGS formulations [192] or S-SEDDS with the highest Cmax reaching 8 μg/ml (or 20 μM) in rat plasma after 3–4 h [8, 194]. The human equivalent dose
(HED) based on the FDA guidelines for body area would be 16 mg/kg or 800 mg/day for a 50 kg person. Recently, a liquid formulation of celecoxib (aka DFN-15) was developed which gave improved median time to peak concentration (Tmax) within 1 h whereas 2.5 h was required for the oral capsules [195]. The pharmacokinetics of DFN-15 was dose proportional over the range tested (120–240 mg) and the Cmax after administering DFN-15 at 120, 180, and 240 mg (1062–
1933 ng/ml; 2.7–5 μM) were much higher than for the 400 mg oral capsules (611 ng/ml) [60]
[195]. However, 400 mg oral capsules provided higher sustained levels over 72 h with AUC (8
μg h/ml). Given the IC50 for celecoxib obtained in the present study of 25–30 μM after 96 h, reaching the range of physiologically relevant plasma concentrations should be achievable and tolerable over one to two weeks of treatment. In addition, considering that the present study was based on the use of only a single dose with monitoring over 72–96 h, it is probable that a treatment regime using repeated daily dosing over several days of up to 800 mg would bring the concentration of celecoxib to within the 10–20 μM range, in line with clinically relevant values.
Furthermore, with celecoxib demonstrating a significant killing of both cell lines at ∼10 μM from a single dose, then such a repeated daily dosing scheme (400 mg capsule twice-daily) should provide levels sufficient for killing in vivo. In this regard, it should be noted that many
158 of 329 studies have reported use of celecoxib doses at these levels as an adjunct therapy in combination with common chemotherapeutic drugs (such as doxorubicin or 5-flurouracil). Several trials have demonstrated synergism with either a marked decrease in the levels of chemotherapy required to be effective or enhanced anticancer efficacy when given as combination therapy for advanced stage metastatic cancers [145, 184, 196, 197].
Efficiency of the Sytox Assay As the stain Sytox does not measure cell viability but is rather only an agent for measuring cell death. It is believed that the data represented here for the IC50 values is artificially high. This is supported through observation and fluorescent microscopy. In figures 20 & 21 the image panels show that treatment with celecoxib (100 μM) or DMC (50 μM) was inducing 100% cell death after 48 h of treatment. However, analysis of the plate reader data, particularly when looking at the 4T1 cell line demonstrates cell viability up to 200 μM and an IC50 value of approximately
100 μM after 72 h. Further testing with more sensitive viability reagents (Figure 31) further supports this notion. The fact that Sytox dye only binds on cell death may artificially skew any cytotoxicity data as by its nature will not include subtle effects on cell growth and metabolism.
For example, an entire culture could be rendered senescent through drug treatments and would not give any signal in a Sytox assay above background. This was somewhat combated by using
Sytox to provide a total cell number at the completion of the assay and comparing that to vehicle and untreated controls.
Mitochondrial Membrane Potential The effects on mitochondrial membrane represented here are interesting. At the timepoint measured (2 h) there does not appear to be much of an effect with the exception of celecoxib on the 4T1 cell line. Information from the publication [177] shows that celecoxib rapidly affects the
159 of 329 membrane of isolated mitochondrial. Investigation into this with the B16F10 and 4T1 cell lines were inconclusive. It may be that measurement at this timepoint represents cells that have largely recovered from the initial cytotoxic affront that was initiated through the introduction of
NSAIDS. This may also be a quirk of the cell lines that were tested. Note also that the assays used to measure membrane potential were vastly different, and the results observed may simply be a difference in observation and measurement.
Further observed was the stark difference between membrane potential between the B16F10 and
4T1 cell lines. When measured at the same settings, B16F10 cell demonstrate a ~4-fold increase over the 4T1 cell line, with the same difference revealed after reducing the potential with CCCP.
It was believed that the cell line with the highest membrane potential would be the most sensitive to an increase in ROS due to proton leak, an inefficiency in converting ETC substrates and a greater potential for the disruption to the mitochondria, leading to cell death. It would also be sound to believe that cells with a greater mitochondrial mass would be more susceptible to
NSAIDs or pro-oxidant treatment, due to the higher number of mitochondria available to produce ROS. However, the 4T1 cells were more sensitive to the effects of NSAIDs across the board and also produce more ROS faster than the B16F10 cell line. Further testing with both a mitochondrial dye (such as MitoSPY) combined with TMRE may give more clear results to the mitochondrial mass and potential in these cell line. However, the result witnessed is intriguing.
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Chapter Five
Results: Celecoxib as a Cancer Therapy
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Celecoxib as a Cancer Therapy
This section contains results from the publication: [177] Pritchard, R., et al., Celecoxib inhibits mitochondrial O2 consumption, promoting ROS dependent death of murine and human metastatic cancer cells via the apoptotic signalling pathway. Biochem Pharmacol, 2018. 154: p. 318-334
Introduction From data provided in the previous section, it was apparent that celecoxib was:
1. The most cytotoxic drug at lower concentrations than its counterparts.
2. That the levels of celecoxib or DMC required to inhibit in vitro metastatic cell growth were either within or approaching physiologically attainable levels (See Table 7) based upon only a single dose over 72 h.
3. That celecoxib was inducing apoptosis in both B16F10 and 4T1 cells
4. That the ROS generation witnessed from celecoxib was mitochondrial and not emanating from the cytosol.
5. That the generation of ROS appeared to be instantaneous from the point of addition.
This, along with numerous clinical trials and current literature surrounding the use of celecoxib as an anti-cancer drug, lead to the selection of celecoxib as the NSAID of focus for the remaining chapter. This chapter elucidates further on how celecoxib affects cancerous cells and mitochondria. More work is undertaken to identify that DMC is even more potent at increasing mitochondrial ROS than celecoxib. Note that other NSAIDs assayed in the previous chapter may still be effective anticancer agents (particularly nimesulide and diclofenac) given further testing.
However, based on the in vitro data acquired and the physiologically relevant concentrations that are achievable, celecoxib certainly seemed to be the most promising candidate out of those
162 of 329 tested. Furthermore, as celecoxib is already approved for the treatment of FAP, and several groups have already reported success with combination treatment in vivo, further understanding its mechanism was deemed most important.
Aims The aims of this chapter were to therefore delve more thoroughly into the mechanism(s) of anti- cancer action attributed to celecoxib and its derivative dimethyl celecoxib, that were seen to be the most effective NSAIDs at inducing cell death and ROS in both cell lines previously tested.
1. Demonstrate further celecoxib and DMC action of cytotoxicity.
2. Show that the proposed mechanism of ROS related killing could be blocked or at least
abrogated with the use of antioxidants.
3. To look further into the effects of celecoxib and DMC on mitochondria.
4. That cells treated with celecoxib are sensitive at levels approaching those that are valid in
vivo.
5. Demonstrate that DMC is a more potent cytotoxic and ROS inducing agent than
celecoxib.
6. Elucidate further the effects of celecoxib on mitochondria and cell metabolism
Celecoxib’s Effects on Apoptotic Pathway To further demonstrate celecoxib’s effect on cells by causing apoptosis, imaging of celecoxib treated cells were stained with Sytox and imaged to observe nuclear condensation and blebbing.
Figure 28 Image Panel shows celecoxib treated (50 μM) cells after 24 h in various stages of
163 of 329 nuclear degradation with characteristic ring structures and fragmentation of DNA. The ability of celecoxib to also induce apoptosis in a dose dependent fashion was explored. Figure 29 shows
B16F10 cells treated with either vehicle or celecoxib 50 μM or 100 μM after 48 h and stained with annexin-V or PI. Cells treated with 50 μM of celecoxib show a marked increase in annexin-
V staining (green) with membrane blebbing, a reduction in total cell number and increased cell death indicated with PI (red) uptake to the nucleus. Cells treated with 100 μM of celecoxib show a marked increase in the amount of PI staining with cells and cell fragments also expressing annexin-V staining indicating that cells were expressing phosphatidylserine, a known marked of apoptosis, prior to membrane permeabilization an uptake of PI indicating late stage apoptosis.
Celecoxib was then tested for caspase 3/7 activation as a short-term indicator for the induction of mitochondrially triggered apoptosis. Figure 28 shows B16F10 cells treated at 4 h and 18 h with
100 μM of celecoxib. Caspase 3/7 is markedly increased at 4 h relative to untreated and control
(αTS 200 μM) treated cells. Interestingly, when measured at 18 h at this concentration, the levels of caspase 3/7 are not increased, showing that apoptosis is rapidly induced when compared to the
αTS control that then demonstrates much higher levels. Repeated observation of celecoxib treated cells demonstrated a marked build-up of intracellular vesicles. To observe these phenomena more closely, both B16F10 and 4T1 cells were stained with acridine orange. Figure
29 shows cells after 3 h when treated with 100 μM of celecoxib showing marked strand breaks in
DNA coupled with lysosome formation that may be indicative of mito/autophagy. This further supports celecoxib’s triggering of mitochondrially derived apoptosis and mitochondrial ROS being the trigger with cells attempting to degrade or remove the afflicted mitochondria to minimise oxidative stress.
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Cells stained with Sytox without (I) or with (II) celecoxib treatment showing characteristic apoptotic morphology, nuclear condensation, blebbing, ring structure and fragmentation as an indication of apoptosis. Images were performed in triplicate using an Olympus IX53 microscope using the FITC channel. Caspase activity measured using the Caspase-Glo® 3/7 reagent and a Molecular Devices Flex Station 3 plate reader using luminescence channels with αTS as a positive control for mitochondrial apoptosis. Results are presented as means±SD (N=2, n=12), with * indicating a difference from Z (P<0.05) for untreated vs drug treated cells.
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Figure 29: Apoptosis after Celecoxib Treatment Cells were treated with annexin-V (green) and PI (red) and imaged in triplicate after 48 h celecoxib treatment at either 50 µM or 100 µM of celecoxib TOP: untreated B16F10 cells with little apoptosis or cell death. MIDDLE: celecoxib treated 50 µM cells showing marked reduction in cell number, altered morphology, increase in phosphatidylserine expression and PI indicating early and late stage apoptosis. BOTTOM: cells treated with 100 µM celecoxib showing further reduction in cell health and a marked increase in PI positive cells.
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Figure 30: Single Strand DNA Breaks and Lysosome Formation post Celecoxib Treatment
TOP: B16F10 untreated (I) or treated (II) with 100 µM celecoxib after 3 h. BOTTOM: 4T1 untreated (III) or treated (IV) with 100 µM celecoxib after 3 h. Assays were performed in triplicate and images captured with an Olympus IX53 microscope using FITC and Cy3 filters. Images show a marked increase in single-strand DNA breaks and lysosome formation indicative of auto/mitophagy.
Celecoxib and Dimethyl Celecoxib have Dose Dependent Effects on Cell Viability at Short Time Points Previous data had shown that celecoxib and DMC were the most potent NSAIDs when measured at 24 h time points with cytotoxicity. However, this was measured using a dye that indicates cell
167 of 329 death only and is not a measure of cell viability in the short term and lacks sensitivity. A cell viability assay was therefore employed to determine more accurately the effects of celecoxib and dimethyl celecoxib at early time points in a dose dependent fashion. Figure 31 shows the results of the RealTime-Glo® assay that is extremely sensitive for measuring cell viability. Note that the increase in the wells containing no cells is used as the control for background signal. Therefore, once any of the other curves cross this line, it is reasonable to assume that there are no remaining viable cells. The higher concentration (200 µM) of celecoxib is shown to be particularly lethal with no viability remaining in the B16F10 cells after 10 h. Interestingly, the remainder of the concentrations used show a distribution as would be expected. However, there is an obvious decrease in cell viability at concentrations as low as 25 µM, lower than that previously witnessed. All of the concentrations seem to dip at the same time point of ~12 h. Keeping with observations witnessed in previous experiments that DMC was approximately twice as potent as celecoxib at killing the cancerous cells, the dilutions of DMC began at a concentration half that of celecoxib. The results are quite similar with a reduction in cell viability beginning at the ~12 h stage. The highest concentration of DMC used (100 µM) required ~24 h to completely remove any viability on these cells. The remaining concentrations of DMC used were also seen to be dose dependent but more separated, with a reduction in viability measured using the lowest (12.5
µM) concentration, that is also approaching amount achievable in vivo from only a single dose administered once in 24 h. Untreated and vehicle treated populations remained stable as expected.
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Figure 31: Reduction in Cell Viability Measured with MT-Glo Reagent over 24 Hours vs Celecoxib & DMC
B16F10 cells treated with a variety of celecoxib or DMC concentrations as indicated. Results demonstrate a dramatic reduction in cell viability in a dose dependent fashion far lower than that witnessed with the use of the Sytox assay. Note that DMC is potent at levels half that of celecoxib demonstrating a mechanism alternate to that induced via COX inhibition. Note also that this demonstrated effectiveness at levels approaching those achievable in vivo and in patient models. Results were measured on a Molecular Devices Flex Station 3 plate reader using luminescence channels and the MT-Glo reagent from Promega. Results are presented as means±SD (N=1, n=3) over time and at the concentrations indicated.
The SOD Mimetic MnTMPyP Significantly Reduces the Amount of ROS Induced by Celecoxib and Increases Cell Viability Post Celecoxib Treatment. To determine if the ROS induced through celecoxib treatment could be reduced with the use anti-oxidants, the MnSOD mimetic MnTMPyP was used [198]. Both B16F10 and 4T1 cells were first tested with DHE to determine increase in fluorescent signal. Figure 32 shows a dose dependent increase in both cell lines. Figure 33 shows both B16F10 and 4T1 cells after both 2 h and 4 h treatment with 50 μM celecoxib following a 10 min incubation with 10 μM of
MnTMPyP. Figures demonstrated a reduction in DHE signal in all three untreated, TBHP control and celecoxib treated samples (except for B16F10 untreated at 2 h) indicating that the
MnTMPyP treatment was successful in reducing the intrinsic amount of ROS found in these metastatic cell lines, regardless of drug treatment. These data were supported with the use of fluorescent microscopy. Figure 34 shows B16F10 cells with or without MnTMPyP treatment showing marked oxidation of DHE and binding to the nucleus in the untreated sample, this was completely abrogated in the MnTMPyP pre-treated sample with no visible binding of DHE to the nucleus. Figure 34 shows 4T1 cells both with and without MnTMPyP and/or celecoxib treatment showing highly increased DHE signal when microscope controls fixed in order to indicate a difference in fluorescent signal (see also Appendix III for full well images).
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Figure 32: Dose Dependent Increase in Superoxide Measured with DHE after 1 Hour Change in superoxide levels detected by DHE after treating cells for 1 h with increasing concentrations of celecoxib for B16F10 and 4T1 cells. Measured using a Molecular Devices Flex Station 3 plate reader with TBHP (50 µM) as a positive control. Results are presented as means±SD (N=2, n=6), with * indicating a difference from Z (P<0.05) as compared to untreated controls.
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Figure 33: MnSOD Mimetic MnTMPyP Significantly Abrogates the Superoxide Increase Caused by Celecoxib at 2 h and 4 h
Celecoxib induced superoxide production in whole cells is abrogated by pre-treating with MnTMPyP. A and B) MnTMPyP [10 μM] pre-treatment for 10 min significantly abrogates the celecoxib (50 μM) induced superoxide production in both B16F10 and 4T1 cells at 2 h and 4 h. T-BHP (200 μM) was used as a positive control for ROS induction, as determined with DHE staining and spectrofluorometry. Results are presented as means±SD (N=2, n=12), with * indicating a difference from Z (P<0.05) for each sample compared to MnTMPyP treatment.
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Figure 34: DHE Staining after Celecoxib and MnTMPyP Treatment Decreased DHE nuclear fluorescence signal assessed by microscopy after pre-treating cells with 10 μM MnTMPyP for 10 min: (I) untreated 4T1 cells; (II) untreated 4 T1 cells with MnTMPyP (10 μM); (III) celecoxib treated (50 μM); and (IV) celecoxib treated (50 μM) with MnTMPyP (10 μM) after two hours. Scale represents 30 μM.
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To ensure that the ROS being blocked when cells were treated with MnTMPyP was emanating from the mitochondria, B16F10 cells were treated with αTS in the same assay format. Figure 35 shows cells pre-treated with 10 μM with DHE fluorescence measured after 3 h of treatment using
200 μM of αTS. Results demonstrate a significant reduction in DHE oxidation and DHE fluorescence. Image panel shows the same assay with either untreated or treated with 200 μM
αTS and with or without MnTMPyP. Results show a complete lack of DHE oxidation and accumulation in the nucleus indicative of a marked reduction in mitochondrial superoxide. To determine if MnTMPyP treatment was sufficient to preserve cell viability after celecoxib treatment, B16F10 cells pre-treated with 50 μM of MnTMPyP for 1 h was sufficient to increase cell numbers by ~20% after treatment with 50 μM celecoxib and saw a slight ~5% increase in the
100 μM treated samples.
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A)
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Figure 35: MnSOD Mimetic MnTMPyP Significantly Abrogates the Superoxide Increase Caused by αTS at 3 h and Preserves B16F10 cell Health after 48 h Pre-treating cells with MnTMPyP inhibits ROS induced by α-TOS and partially reverses celecoxib induced cell death. A. Right side panel: 50 μM MnTMPyP (Mn) pre-treatment for 1 h before addition of α-TOS (αTS) [200 μM] significantly abrogates the superoxide signal detected as DHE nuclear staining in B16F10 cells detected at 3 h. Results are presented as means±SD (N=2, n=6), with * indicating a difference from Z (P<0.05) for αTS (200 µM) vs αTS (200 µM) plus MnTMPyP treated cells. Left side panel: Representative fluorescence micrograph of DHE nuclear staining in B16F10 cells. I: untreated cells, II: Mn/vehicle alone treated cells, III: α-TOS alone treated, IV: Mn pre-treated+α-TOS. Scale bar 30 μM. B. Percent live B16F10 cells after 48 h treatment with Mn/vehicle alone or pre-treated with Mn for 1 h before addition of celecoxib at the concentration shown compared to untreated control cells. Results are presented as means±SD
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(N=2, n=6), with * indicating a difference from Z (P<0.05) for drug vs MnTMPyP plus drug treated samples at the concentrations indicated.
It is interesting to note that treatment using only MnTMPyP was sufficient to kill the cancerous cells. This was observed in both the B16F10 and 4T1 cell lines when treated with both
MnTMPyP and MnTBAP (another SOD mimetic). Treatment of cells in a range of 100 - 6.25
μM saw dose dependent cell death in all treated wells after a period of 7 days (data not shown).
These findings are consistent with [199] who demonstrate the same effects in breast cancer cells.
However, based on evidence reviewed in [147], this treatment of metastatic cancers through
ROS abrogation as opposed to induction was abandoned.
DMC is a More Potent Inducer of Mitochondrial Superoxide than Celecoxib As shown in the previous chapter when determining if the cytotoxic effects of celecoxib were attributed solely to COX-2 inhibition, the non-COX-2 inhibitory celecoxib analogue DMC was used in cytotoxicity assays and proved to be even more potent than celecoxib. B16F10 and 4T1 cells were assayed using MitoSOX red and MitoSpy green staining and treated with either 100
μM of celecoxib or 50 μM of DMC. Figure 36 shows ~4-fold increase in both celecoxib and
DMC treated samples in both cell lines, demonstrating that DMC is as potent at inducing mitochondrial superoxide as celecoxib when treating at half of the dosage. Note also that cell death witnessed in the cytotoxicity assays (Figures 20 & 21) reflect the same dosages for cytotoxicity after 48 h, total cytotoxicity witnessed with the concentration of celecoxib 100 μM and 50 DMC after 48 h of treatment. Figure 36 Image Panel shows MitoSOX and MitoSpy stained cells demonstrating fluorescence signal from the mitochondria.
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Figure 36: DMC is more Potent at Inducing Superoxide than Celecoxib
Cells stained with MitoSPY (green) and MitoSOX (red) and treated with celecoxib or DMC at the concentrations indicated. DMC is as potent at inducing superoxide as celecoxib at half of the dose. Results were captured using a BD Fortessa flow cytometer using the FITC and Texas Red channels and compared to untreated cells. Results are presented as means±SD (N=2, n=4), with * indicating a difference from Z (P<0.05) for untreated vs drug treated samples.
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MitoSOX Signal is of Mitochondrial Origin with Little Translocation to the Nucleus Due the similarity of MitoSOX with DHE, MitoSOX having the addition of a charged triphenolphosphonium side-chain in order for it to locate to the mitochondria, some reports have stipulated care in its use as nuclear binding may result in false positives. To test this 4T1 cells were imaged using high resolution confocal microscopy. Figure 37 Image panel shows cells stained with both MitoSOX and Hoechst 33342 without or with Celecoxib treatment at 100 μM showing a large amount of increase in fluorescent signal after 1 h of treatment that largely emanates from the mitochondria. Figure 37 Image panel demonstrates the same assay and time point with a high magnification showing some low-level binding of MitoSOX to the nucleoli.
Note also that clumping or fusion of the mitochondria is evident in this image consistent with acridine orange staining. To study this phenomenon more closely, B16F10 cells were stained with MitoSOX red and MitoSpy green and observed for condensation of the mitochondria in response to celecoxib 100 μM treatment. Figure 38 Image Panel shows the results of mitochondria clumping after 40 mins.
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Figure 37: Superoxide Produced by Celecoxib is Specific to the Mitochondria, with Little Nuclear Translocation
Confocal micrographs of B16F10 cells untreated (B, I-III) or treated (C, I-III) with celecoxib (100 μM) for 1 h. Scale bar represents 30 μM. D) Magnified images of celecoxib treated B16F10 cells (100 μM) with Hoechst 33342 (I), MitoSOX (II) or combined superimposed (III) images. Cell nuclei were counter stained with Hoechst 33342 for 10 min and images obtained with a Leica SP-8 confocal microscope. Scale represents 30 μM.
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I II
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Figure 38: Increase in MitoSOX Signal and Mitochondrial Fusion via Confocal Microscopy TOP: Confocal images of B16F10 cells stained with both MitoSPY (I, green) and MitoSOX (II, red). BOTTOM: combined channels showing MitoSOX bound to the mitochondria (III). BOTTOM RIGHT: The same combined imaged after 40 mins 100 µM celecoxib treatment (IV) showing clumping or packaging of the mitochondria into green dots and increase in the red signal indicting an increase in ROS production. Note the dispersion of red signal into the cytosol that may be a sign of mitochondrial membrane potential dropping and releasing the charged MitoSOX. Scale is 20 µM
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Celecoxib Strongly Affects Mitochondria in Whole Cells when Measured over Short Time Points We have previously shown celecoxib’s effects on isolated mitochondria [177]. To more closely study this in whole cells, the Seahorse flux analyzer was utilised coupled with the Mitostress assay. When treating both B16F10 and 4T1 cells with 100 µM of celecoxib, a large variety of mitochondrial functions were compromised. Most interesting and obvious to note is the complete abrogation of spare respiratory capacity (Figure 39 & 40). However, significant results were observed across all parameters, increased proton leak, a reduction in ATP production, a marked decrease in maximal respiration and reduced coupling efficiency. These data are supported with non-significant effects on parameters that should go unaffected, basal respiration before celecoxib addition and non-mitochondrial oxygen consumption (Figure 39 & 40).
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Proton Leak ATP Production 45.0 120.0
40.0 100.0 35.0
30.0 80.0
25.0
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OCR (pmol/min) OCR 20.0
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Maximal Respiration Spare Respiratory Capacity 300.0 (%) 300.0%
250.0 250.0%
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Coupling Efficiency (%) Acute Response 45.0% 18.0
40.0% 16.0 14.0 35.0% 12.0 30.0% 10.0
25.0% 8.0
OCR (pmol/min) OCR OCR (pmol/min) OCR 20.0% 6.0 4.0 15.0% 2.0 10.0% 0.0
5.0% -2.0
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Non-mitochondrial Oxygen Basal Consumption 120.0 40.0 100.0 35.0
30.0 80.0 25.0
60.0 OCR (pmol/min) OCR 20.0 (pmol/min) OCR
15.0 40.0 10.0 20.0 5.0
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Figure 39: Seahorse Mitostress Test on B16F10 Cells after Celecoxib 100 µM Treatment B16F10 cells were analyzed for metabolic activity using the Seahorse XFp analyzer. Cells were treated with celecoxib and an acute response monitored for three cycles before following the standard procedure outlined. Effects were witnessed across all of the parameters measured, most notably in the acute response and spare respiratory capacity. Figures demonstrate that celecoxib treatment rapidly affects mitochondria in whole cells. Vehicle treated and wells with no cells were used as controls and baseline. Results are presented as means±SD (N=2, n=6) for control and drug treated samples.
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Mitochondrial Respiration 140.0
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0.0 0 20 40 60 80 100 Time (min)
Proton Leak ATP Production 30.0 45.0
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Maximal Respiration Spare Respiratory 140.0 Capacity (%) 250.0% 120.0
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OCR (pmol/min) OCR OCR (pmol/min) OCR 60.0 100.0%
40.0
50.0% 20.0
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Coupling Efficiency (%) Acute Response 90.0% 7.0
80.0% 6.0
5.0 70.0% 4.0 60.0% 3.0
50.0% OCR (pmol/min) OCR OCR (pmol/min) OCR 2.0 40.0% 1.0 30.0% 0.0 20.0% -1.0
10.0% -2.0
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Non-mitochondrial Basal Oxygen Consumption 70.0 25.0 60.0
20.0 50.0
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OCR (pmol/min) OCR OCR (pmol/min) OCR 30.0 10.0 20.0
5.0 10.0
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Figure 40: Seahorse Mitostress Test on 4T1 Cells after Celecoxib 100 µM Treatment 4T1 cells were analyzed for metabolic activity using the Seahorse XFp analyzer. Cells were treated with celecoxib and an acute response monitored for three cycles before following the standard procedure outlined. Effects were witnessed across all of the parameters measured, most notably in the acute response and spare respiratory capacity. Figures demonstrate that celecoxib treatment rapidly affects mitochondria in whole cells. Vehicle treated and wells with no cells were used as controls and baseline. Results are presented as means±SD (N=2, n=6), for control and drug treated samples.
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Preliminary Animal Work In order to test the efficacy of celecoxib as a standalone treatment for the reduction of metastatic lesions in vivo, C57Bl6 mice were inoculated with B16F10 cells and treated with 150 µg of celecoxib via i.p. injection. Figure 41 shows the number of lung metastasis observed at the time of death. While there is a slight reduction in the mean number of tumours observed, this number is not significant. Figure 41 shows that there was also no meaningful increase in the survival times between the untreated and celecoxib groups. Figure 41 shows the weight of the animals upon being culled, indicating that treatment using celecoxib is well tolerated by the treatment groups. No adverse events were reported after observing animals for a period of 20 min post administration of celecoxib.
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Figure 41: In Vivo Celecoxib Dosing after B16F10 Inoculation via Tail-Vein Injection Celecoxib treated (150 µg) vs untreated C57Bl6 mice lung metastasis post B16F10wt t.v.i and counting of colonies on the lung demonstrates no significant reduction in metastatic burden results presented as means+SD (N = 1, n = 6) with no significant difference from Z (P<0.05) for colonies on the lung of untreated vs celecoxib treated mice. Waterfall plots for the survival of the mice post t.v.i are practically identical. Weight of the mice following i.p. injections of celecoxib are not significantly different indicating that the treatment is well tolerated. Results are presented as means±SD (N=1, n=3), with no significant difference from Z (P<0.05) for untreated vs celecoxib treated C57Bl6 mice.
Discussion
Summary This chapter highlights several of the mechanistic aspect of celecoxib treatment in vitro.
More data is shown celecoxib’s effects on apoptosis and demonstrates that caspase 3/7 activity is increased in the short-term as part of the mitochondrial pathway of apoptosis. Imaging of celecoxib treated cells demonstrates apoptotic nuclei in various stages of degradation as further indication of the apoptotic process. The induction of apoptosis following celecoxib treatment
190 of 329 was also shown to be dose dependent to support previous data. Acridine staining was able to show a large build-up of lysosome formation as an indication of auto/mitophagy as well as single strand breaks in the DNA supporting mitochondrial damage and apoptosis as the proposed action of call death. Studies into blocking the ROS inducing effects of celecoxib treatment were successful in both reducing the levels of ROS and preserving cell health. It was noted that DMC was more potent at inducing cytotoxicity than celecoxib, and confirmed in this chapter that DMC is an event more potent inducer of ROS species than celecoxib. This also works to confirm that the mechanism of action is not solely related to COX inhibition. Imaging of mitochondria in a variety of confocal microscope assays was able to confirm that the ROS was of mitochondrial origin, and supports other data that mitochondria are heavily affected by treatment with celecoxib. Celecoxib was both shown to have marked effects on cancer cell mitochondria.
Preliminary animal work undertaken has demonstrated no significant reduction of tumour burden or increase in survival times when treating with celecoxib at the concentrations used, yet also that treatment was highly tolerated.
Celecoxib’s Effects on Apoptotic Pathway This chapter and previous sections have shown that celecoxib is a potent inducer of apoptosis via the intrinsic apoptotic pathway. The work presented here using celecoxib builds on the apoptosis data from the previous chapter showing that celecoxib treatment induces apoptosis in a dose dependent manner, and that the higher doses used (100 µM) are still inducing cell death in this fashion. Imaging also captured cells in the various stages of apoptosis, showing shrinking of the cells, blebbing of the membrane, nuclear condensation and fragmentation of the DNA including the characteristic ring structure, and finally, smaller packages apoptotic bodies. Further to this, apoptosis was linked to the intrinsic cascade as opposed to death receptor mediated with the use
191 of 329 of caspase 3/7. This showed a high increase in the levels of caspase activity in the short term as compared to both the control treatment and the untreated populations, with the levels reducing to background after 18 h, as would be expected of cells in a late apoptotic phase. The induction of apoptosis was further witnessed with the image from the acridine orange assay. The images
(Figure 30) show marked single strand breaks in the DNA and is further indicative of apoptosis, auto and mitophagy.
The SOD Mimetic MnTMPyP Significantly Reduces the Amount of ROS Induced by Celecoxib and Increased Cell Viability Post Celecoxib Treatment. The SOD mimetic MnTMPyP was shown to be a powerful antioxidant in both of the cell lines tested, completely abrogating the effects of celecoxib over the 2 h and 4 h time points measured.
MnTMPyP was also able to reduce the amount of ROS measured in the untreated population of these cells. When testing MnTMPyP antioxidant capability using DHE as an indicator of superoxide production and nuclear binding, it was shown that there was a complete lack of oxidised DHE in the nucleus of these cells. These data were also confirmed when using αTS in the same assay format to ensure that the ROS was mitochondrial in origin. The same reduction of oxidised DHE was observed and the imaging revealed no buildup of oxidised DHE in the nucleus of these cells. Further to this, pretreating cells with higher levels of MnTMPyP for greater periods was sufficient to preserve the health of these cells at least somewhat. This demonstrated that in the short term MnTMPyP is able to completely mitigate the ROS inducing effects of celecoxib and several different controls and was also able to preserve cell viability at increase doses and longer incubation times. This assay was initially attempted with the use of
MitoTEMPO that is a mitochondrially target antioxidant. However, this did not reveal any significant results. As MitoTEMPO is a ROS scavenger (based on the piperidine molecule) as opposed to a SOD mimetic it is believed that the amount of superoxide produced by celecoxib is
192 of 329 too high to be significantly reduced by using MitoTEMPO in the manufacturer’s recommended doses. Note also that treatment with antioxidants is another strategy in the treatment of cancer.
Tests of MnTMPyP on the B16F10 cell line was sufficient to see a reduction in cell viability in a dose dependent manner after 7 days of treatment. The timing of the protective qualities of
MnTMPyP against ROS inducing agents is therefore limited.
An important point to note is that the standard versions of the culture media used throughout this study do not contain ascorbate. Ascorbate is known to break down rapidly and oxidises in aqueous media and is therefore typically left out of both DMEM and RPMI. Ascorbate provides several antioxidant functions to cells in vivo including protection of fatty acids from peroxidation and the regeneration of membrane bound alpha-tocopherol that has been oxidised by lipid peroxyl radicals [200]. It is therefore possible that performing assays centered on ROS initiation and abrogation may be skewed by a lack of ascorbate in the culture media. However, within the parameters described in the assay and the comparison between untreated vs treated cells, there is an obvious increase in the production of superoxide, with this production decreased with the use of MnTMPyP. Furthermore, testing with the other ROS scavenger MitoTEMPO failed to yield any significant results. However, the difference between ascorbate deficient media and experimentation in vivo should be considered.
DMC is a More Potent Inducer of Mitochondrial Superoxide than Celecoxib This the first reported instance of DMC being an even more potent inducer of
ROS that celecoxib. The results presented here are entirely consistent with the data gathered in the previous chapter that DMC is more potent at killing the metastatic cancer cells, and that the intrinsic mitochondrial apoptotic cascade in initiated through an excessive burst of mitochondrial
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ROS. These results strengthen further one of the novel aspects of the thesis that states that the reduction in cancer occurrence observed with the use of NSAIDs, and particularly celecoxib, are not solely attributed to the inhibition of COX. Interesting also is the fact that when treating at a dose half that of celecoxib (50 µM) the amount of ROS generated was practically identical. This then matched the increased cytotoxicity of DMC over celecoxib that was shown in the previous chapter (Figures 20 & 21). With 50 µM of DMC sufficient to kill the entire cell population in 48 h compared to 100 µM of celecoxib required. This also served to reinforce the notion that the anticancer action of celecoxib is not only attributed to its COX-2 inhibiting function, but that inducing mitochondrial ROS plays a significant role.
MitoSOX Signal is of Mitochondrial Origin with Little Translocation to the Nucleus Other reports have documented caution with the use of MitoSOX (and most other ROS measuring reagents) due to false positive signals that may occur. However, the DHE that forms the indicator of the MitoSOX dye still needs to be oxidised by the superoxide radical in order to emit red fluorescence and bind to the nucleus. Furthermore, any drug treatment that induces apoptosis will see a reduction in the amount of charge that is generated by the mitochondrial membrane potential as this marks one of the first stages of the intrinsic apoptotic cascade. This will therefore reduce the affinity of the charge TPP side chain that targets the mitochondria and will cause a buildup in the cytosol and/or nucleus. This can be witnessed in figures 37 & 38.
However, in the short term, it is still obvious that the majority of the signal witnessed is from the mitochondria, and that this signal visibly increases over time.
Celecoxib has Rapid Effects on Mitochondrial Morphology It was across several assays that celecoxib treated cells showed a quite distinctive alteration to their intracellular morphology. It was believed that this was attributed to either autophagy,
194 of 329 mitophagy or some other cellular mechanism, such as lysosome formation, that was acting to protect the cells from the damaged mitochondria. It seems as though once celecoxib effects the mitochondria with the ensuing build-up of ROS the cells attempt to isolate or package these mitochondria in vesicles in order to mitigate the cytotoxic stress. This action was also seen to be quite fast and can be observed after just a few hours when treating with higher (100 µM) doses of celecoxib, with lower (50 µM) doses witnessing the same phenomena the next day. The data shown in the acridine orange imaging seem to support the notion that it is lysosomes that are being formed to get rid of or break down the damaged mitochondria. The data supplied by use of confocal microscopy was equally interesting. When stained with MitoSPY, a mitochondrial binding dye that is not dependent on the mitochondrial membrane potential, this “clumping” or perhaps fusing of the mitochondria was observed very rapidly and lead to very distinctive green dots on the image (Figure 38). Also of note in this image is the lack of the distinctive yellow/orange tinge that indicate that the green and red signals are overlapping. It also seems that the MitoSOX dye is not solely attached to the mitochondria and is present in regions of the cytosol where there are no mitochondria. To explain this, mitochondria that are subjected to high doses of celecoxib increase the amount of ROS that they are producing almost instantly. This causes a drop in the mitochondrial membrane potential that cause the charged MitoSOX to not be attached to the mitochondria anymore and releases to permeate the cytosol. These damaged mitochondria then either clump together or are packaged inside a vesicle to limit the damage to the rest of the cell. The staining on these cells in the vesicles is therefor only seen to be green. It is also possible that the signal from the MitoSOX cannot permeate through the vesicle in the same way that the MitoSPY signal can for some reason. It would be useful to further explore some of these mechanism with the use of mitophagy indicators. Note also that mitophagy has
195 of 329 recently been implicated in supporting cancer cell resistance to drug treatments and may be a negative facet to the use of celecoxib as a cancer therapy.
Celecoxib Strongly Affects Mitochondria in Whole Cells when Measured over Short Time Points The use of the Seahorse XFp analyzer coupled with the Mito Stress assay kit enabled the understanding of celecoxib’s impact on several key factors of the mitochondria and ETC.
Through the use of compounds that inhibit different complexes of the ETC, it is possible to reveal several of the effects of celecoxib on mitochondrial function. The assay was set to first inject celecoxib and to monitor the effects for 3 x 6-minute cycles to see the effects on the acute response and basal respiration. Following this, oligomycin, FCCP and rotenone/antimycin A were added in the typical cycle recommended by the manufacturer. In both cell lines there was a marked increase in the OCR due to the acute response to celecoxib addition. As previously suggested the coupling efficiency of the cells is reduced in the short term through the addition of celecoxib. Linked with this is the increase in proton leak and reduction in ATP production as is expected. The addition of FCCP as an uncoupler reveals quite marked effects on the spare respiratory capacity of the cells, practically negating it altogether and saw a reduction in the maximum respiration. From these data it appears as though celecoxib has a significant effect on the ability of the cell to respire and indicates that at these early timepoints, celecoxib has far ranging effects on the ETC. However, what is not clear is how celecoxib is having these effects.
It is possible that celecoxib binds to either complex I or III and producing effects similar to treatment with rotenone and antimycin, effectively blocking the passage of protons.
Note that when following the manufacturer’s protocol, the test compound needs to be added to the port at a concentration 10-fold higher than the final concentration in the well. This is somewhat difficult to achieve with celecoxib as it is so hydrophobic and tends to precipitate at
196 of 329 concentrations above 200 µM if it is placed directly into a salty buffer such as the assay media for the Seahorse. The celecoxib was therefore diluted into the cyclodextrin mixture as previously described instead of the recommended assay media.
Preliminary Animal Work Preliminary results when testing celecoxib alone as an anti-cancer therapy were met with non- significant results. However, this preliminary study used only 150 µg of celecoxib via i.p. injection every 48 h for the period of the study. The dosage was determined by factoring the 400 mg amount allowed as a single dosage for an average 70 kg patient in comparison to an average
25g mouse, resulting in 6mg/Kg. However, the standard dose for patients may be taken b.i.d and in higher doses than the average recommended dose for short periods. It was determined the b.i.d i.p. injections would be too distressing for the animals involved. It may then have been a more sound strategy to increase the individual dosing to 300 µg or more daily, to more closely mimic treatment that would be received by patients. This may have seen a significant result in the reduction of metastasis and increase the survival times. One positive aspect of the study was that the treatment of celecoxib in this manner appeared to be well tolerated as witness by the comparable weight between the control and treatment groups. There were also no adverse results recorded during this trial. Celecoxib treatment may work best in combination with other therapeutics as opposed to a standalone therapy. Several other reports support this notion when celecoxib is combined with commonly prescribed cancer drugs such as doxorubicin or capecitabine. Note that this was only a preliminary study using three animals in each of the groups. While the results are practically inseparable, further testing with higher numbers of animals may see a significant reduction the number of metastatic tumours observed or an
197 of 329 increase in survival times. However, it is likely that to see positive results in animal studies, it is best to combine celecoxib as an adjuvant therapy as opposed to administering it on its own.
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Chapter Six
Conclusion
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Summary The work presented here represents several important factors to the treatment of cancer. Stem- like cancer cell populations and particularly metastatic cancers provide a particular challenge to clinicians and researchers to combat these cancers that are the most lethal. Experiments were undertaken to elicit further the effects that hypoxia has on the stem-cell factor Oct4, that has been demonstrated to be the most important factor for pluripotent cell maintenance and dedifferentiation of cancer cells to maintain phenotypic diversity. Assays were undertaken to determine that it is cycling hypoxia as opposed to hypoxia itself that leads to an increase in Oct4 levels as an indication of “stemness”, with cycling hypoxia being far more effective at inducing
Oct4 expression. However, the cell line generated through rounds of hypoxic incubation and sorting still contain non-expressing cells that seem to occupy every culture that was generated.
The expression of Oct4 is obviously increased upon exposure to hypoxia. However, when maintained in normoxic culture post-hypoxia, the cultures retain Oct4 expression at less fluorescence intensity than is seen immediately after being withdrawn from hypoxia yet remains stable at that level shown for weeks or months in standard culture conditions. These Oct4 expressing hypoxic cells also had the same growth rates and migratory capability as the parental line, which was surprising as differences were expected. When placed in animal models, these cells took markedly longer to grow, yet were not more invasive or metastatic than the wild-type cells with no cells in either phenotype seen to migrate from the primary tumour before the allowable maximum volume was reached.
When tested against NSAIDs, there was no obvious increase in the effectiveness of treatment for the hypoxic cell (2VB5) over the parental B16F10 line. As these cells are maintained in normoxic culture after cycling hypoxic conditions and sorting, it is possible that some reversion
200 of 329 or differentiation of the cells occurs and that they more closely match the parental line. However, they still express levels of Oct4 far higher than the parent phenotype and should therefore be more “stem-like”. It is possible that as the B16F10 cell line and advanced melanoma in general are so heterogeneous, pro-migratory, metastatic and often are HIF constitutive anyway, that hypoxic incubation does little to increase their stemness and therefore little difference is witnessed. In this regard, it would have been far more beneficial to begin with a more primary tumour cell line and select it through hypoxia. It is also possible that the particular NSAIDs used in this study are not effective against stem-like cell populations, or that the assays used were simply not sensitive enough to detect any difference. It would also be interesting to test cells under hypoxia, cultures just removed from hypoxia, or hypoxically generated spheroids for the effects of NSAID treatment and it is believed that this would represent a more sound model of stem-like, hypoxic or 3-D culture than the methods used here. Note that this work is currently being carried out by our collaborators using mamosphere assays in conjunction with celecoxib and is showing positive results.
Two of the NSAIDs (celecoxib and sulindac) were clearly more effective against more metastatic cell lines, represented here with the two 4T1 and 4T1.2 phenotypes, and also in the data supplied from the collaborators in [177] (Appendix V) with the difference between the
MDA-231 and MDA-486 cells when compared to MCF-7 and 3T3 cell lines. However, the concentration of sulindac required to produce these results is far in excess of the values that can be produced biologically without severe side-effects. Sulindac may still represent a valid anti- cancer therapy, particularly if used in combination with other therapeutics. However, as only celecoxib and DMC appeared to be active at biologically attainable levels, celecoxib and its derivative DMC remained the focus of the final chapter. The fact that these two NSAIDs, and
201 of 329 especially celecoxib, are more effective against metastatic cancer populations over a variety of cell lines provides promise and justification for further experimentation.
With the data generated across two experimental chapters that focus on the use of NSAIDs it is possible to generate a timeline that demonstrates the proposed mechanisms of action of celecoxib on cells treated in vitro (Figure 42). Reactive oxygen species, particularly mitochondrially derived superoxide, are detected almost instantly in both whole cells and isolated mitochondria and is associated with a drop in mitochondrial membrane potential. ROS continues to increase, and metabolic effects are witnessed at early time points. Early effects on mitochondrial fusion and degradation can be observed after about 1 h with higher doses of celecoxib. Marked lysosome formation, single-strand DNA breaks and mitophagy was observed at 3 h showing destruction or removal of the damaged mitochondria and as an early indicator of the apoptotic process. Caspase 3/7 was shown to be increased at 4 h, with the mitochondrial ROS “burst” decreasing. This process appears to be even more rapid in the 4T1 cells, with the ROS increasing more dramatically at the early stages, shown with marked increases when measuring after an hour, still being significantly increased above control after 2 h, but then not detectable above control at the 4 h and 6 h time points. Cell viability was shown to begin declining after ~12 h.
After 18 h, caspase 3/7 was shown to be decreased as these cells are then in later stages of apoptosis, cell viability is now declining rapidly. At 24 h some cells are already dead as indicated by PI staining, with most others expressing phosphatidylserine on the cell membrane, obvious blebbing and nuclear condensation. By 48 h, most of the treated cells and in advanced stages of apoptosis with characteristic degradation of the DNA. Cell death continues to roughly the 72 h mark depending on the concentration used.
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Figure 42: Timeline of Proposed Effect of Celecoxib in Vitro
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Current and Future Directions The work here covers murine melanoma and breast cancer cell lines and coupled with work that was performed with the collaborators covers human breast cancer cell lines also. There are currently experiments being conducted in our laboratory that are reproducing this work in the human metastatic melanoma cell lines A375 and Skmel-28, as well as in colorectal cancer lines such as SW480. This will provide a sound basis as to the use of celecoxib in a variety of cancer cell lines demonstrating its effectiveness across the board. Preliminary work was also conducted with the drugs doxorubicin and 5-fluorouracil in combination with celecoxib to determine if there is an additive or a synergistic effect to combination treatment. This work is also currently being performed. Further experimentation is being performed on 3D spheroids in response to celecoxib as a sounder model for stem-like cells.
Given that the mechanism of action of cytotoxicity that is presented in this work is novel, it would be interesting to narrow down more on what precisely causes the excessive burst of ROS that is witnessed and what exactly about the celecoxib and DMC molecule causes this to happen.
If the specific interaction was identified, it may be possible to engineer another molecule that had even greater anti-cancer activity that is more specified and produces fewer side-effects. Research groups have adopted this idea and several different analogue compounds to celecoxib have been produced – this is in fact how DMC was initially derived. Swiss Doc [201] modelling of the celecoxib compounds interactions produces interesting results with many strong binding interactions. Based on this, work is currently being undertaken to determine if one of the protein interactions observed provides the target, and if blocking the pore channel with celecoxib increases ROS in this fashion. However, many drugs exist that are used routinely for various
204 of 329 treatments without the mechanism of action being fully understood and learning the minutia of the drugs interactions may not be required. Furthermore, especially with drugs such as NSAIDs, that are known and proposed to have such wide-ranging effects on a number of targets, it is most likely that several of these interactions work in concert to reduce cancer recurrence when administered to patients.
The preliminary animal work conducted with celecoxib did not see a reduction in the amount of lung metastasis. It is possible that the administered amount or that the frequency of the application was not sufficient to see a positive benefit. However, as it is believed that celecoxib would work best as a combination treatment, it would be best to proceed with this strategy as opposed to administering celecoxib alone. Once the dosing and combination of treatments was determined from the experimentation using DOX or 5-FU in conjunction with celecoxib, this mixture could then be used in a metastatic cancer model and may yield better results. This strategy could then be expanded to other cell lines and models of different cancer origin. Due to the increased effect of DMC over celecoxib, it would also be interesting to test these models with
DMC also to see if this increase in effect is translated in vivo. However, as DMC is not currently an FDA approved drug and not currently used as a cancer drug as is the parent compound celecoxib, even if there were more positive benefits to using DMC, the costs and time incurred in clinical testing to have DMC approved may make the use of DMC unfeasible as a cancer drug in a clinical setting.
Upon completion of a study using small animal models that elucidated on several of the aspects of combining celecoxib with other therapies that provided the basis for the concentrations and timing of the administration, it would then be feasible to extend the treatment to larger animal
205 of 329 models. This would determine if the treatment combination is well translated on a larger scale and without negative side-effects, while still retaining the positive anti-cancer benefits of treatment. The ultimate goal would then be to administer the treatment in a phase I clinical trial using the information derived to provide the best possible benefit.
Aspects of the trial that are either reviewed or elucidated from this work that may contribute to the success of a clinical trial are as follows:
1. Treatment with the use of celecoxib is more beneficial to more advanced and metastatic
cancers.
2. It is possible that celecoxib is efficient at eradicating the tumour stem-like cell
population, although this was not the case in the model used in this work.
3. The combination of treatments should be complimentary to each other. In this case it is
believed that a therapeutic that provided “off target” effects to those produced by
celecoxib would be the best e.g. DNA damaging, or receptor targeted. Agents that act as
an anti-oxidant or target mitochondria are not advisable.
4. The timing of the administration may be critical so as to derive the best benefit possible.
Due to the effects of celecoxib over time, it may be best to stagger the treatment or use
celecoxib as a sensitizing agent before using the combination treatment.
5. The anti-inflammatory effects of celecoxib should be considered if it was to be
combined with an immunotherapy as this could abrogate the immune response.
However, this may actually be beneficial as it would assist with chronic inflammation
and help to retrain the immune system.
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6. Treatment using celecoxib may contribute to a reduction of pain or other side-effects that
are present when using other therapeutics, as, if there were a synergistic response to the
combination treatment, it would be possible to reduce the dosage but receive the same
benefits.
7. The patient’s overall health profile would need to be monitored. Therapy with celecoxib
would not be advisable for patient with a history of hepatic or cardiovascular
abnormality due to the negative side-effects celecoxib has on these systems.
8. It is likely that to retain any positive benefit from the use of celecoxib for cancer
treatment that the patient will have to continue to take celecoxib daily for extended
periods of time.
Conclusion NSAIDs have attracted attention in a novel role as anti-cancer medications following longitudinal studies demonstrating a reduction in cancer recurrence. Cancer patients from almost all cancer types taking NSAIDs in the long term for pain management show a decrease in the recurrence of their disease. Several of the NSAIDs show promise for a variety of reasons, given their differing effects on COX-1/2 inhibition, as anti-angiogenic or antipyretic drugs, having the ability to regulate or reprogram the immune system, anti-platelet activity, or other novel mechanisms that were the focus of this work are currently the focus for many researchers around the world. An added benefit to the use of NSAIDs is in their primary function as pain relieving medications, their well-established toxicity and pharmacological profiles, common usage and low cost. Several of the other NSAIDs tested here besides celecoxib may be beneficial as anti- cancer therapies. However, a word of caution based on the concentrations required to observe
207 of 329 effects in cells in this work as well as the work of others is that the concentrations required to see these effects are far in excess of those that are attainable and do not therefore represent a realistic approach to treatment.
It is most likely that NSAIDs and celecoxib would function more effectively as a combination or adjuvant therapy, and this reasoning is borne out by several other groups that have demonstrated additive or synergistic effects, or a reduction in negative side-effects with combination NSAIDs treatment. While there is a lot of interest in the use of NSAIDs and particularly celecoxib in clinical trials, several groups have reported failures in their studies. It is important to understand that the action of NSAIDs will be more effective in targeting metastatic as opposed to primary populations and that these data should not be analyzed concurrently as this will skew any positive results that could be witnessed. Therapy should also be tailored so as to enhance the efficacy of both therapeutics used, and information as to a drugs mechanism(s) of action, such as those proposed here assists in this strategy.
The work presented here supplies a novel mechanism of anti-cancer action for the NSAIDs that is not COX related as evidenced by even stronger cytotoxic effects from the non-COX-2 inhibitory derivative dimethyl celecoxib. Of the group of NSAIDs that was screened, celecoxib was identified as the most promising candidate, and this is supported in the literature and in the high volume of clinical trials that are currently being conducted. The representative timeline that was established could assist with treatment strategies as the timing of the effects of celecoxib – at least in vitro and on the cell lines tested – is well established. Combining this with other therapeutics may therefore assist in treating particularly metastatic cancers more effectively.
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Figure 43: Proposed Method of Utilizing Celecoxib as an Adjuvant Therapy with Chemo/radio Therapies Model for application of celecoxib as a chemo sensitizing agent by inducing mitochondrial superoxide production (ROS) if combined with current commonly used chemo/radiotherapy-based treatments to promote enhanced cancer cell death.
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Appendix I
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Figure 44: Oct4EGFP Plasmid Transfection, Hypoxic Cycling and Antibiotic Selection of the B16F10 Oct4EGFP Cell Phenotype B16F10 cells were transfected and selected using G-418. Image shows a cell 24 h post transfection using a Cell-M fluorescent microscope using the FITC channel. The transfected cells
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Figure 45: Overgrowth, Sorting and Stable Oct4EGFP Expression in the B16F10 2VB5 Hypoxic Cell Phenotype B16F10 cells were overgrown in normoxic culture for 35 days post hypoxic cycling. Hypoxic spheroids were frequently observed in these cultures and highly expressed Oct4. Cells were sorted based on Oct4 expression with a new highly Oct4 expressing population witnessed post hypoxia. Final result of normoxic vs hypoxic selected cells with Oct4 expression.
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Appendix II
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Figure 46: Increase in Sytox Signal over Time in the B16F10 Cell Line in Response to Celecoxib and Diclofenac Response to different concentrations of NSAIDs measured every 24 h for 72 h. Increase in fluorescence is measured with the Sytox reagent in the FITC channel with a molecular devices flex station plate reader. Untreated and vehicle treated (HBCD) served as controls. Results are presented as means±SD (N=2, n=6). Statistics N.D.
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Figure 47: Increase in Sytox Signal over Time in the B16F10 Cell Line in Response to Nimesulide and Sulindac Response to different concentrations of NSAIDs measured every 24 h for 72 h. Increase in fluorescence is measured with the Sytox reagent in the FITC channel with a molecular devices flex station plate reader. Untreated and vehicle treated (HBCD) served as controls. Results are presented as means±SD (N=2, n=6). Statistics N.D.
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Figure 48: Increase in Sytox Signal over Time in the B16F10 Cell Line in Response to Salicylate Response to different concentrations of NSAIDs measured every 24 h for 72 h. Increase in fluorescence is measured with the Sytox reagent in the FITC channel with a molecular devices flex station plate reader. Untreated and vehicle treated (HBCD) served as controls. Results are presented as means±SD (N=2, n=6). Statistics N.D.
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Figure 49: Increase in Sytox Signal over Time in the 4T1 Cell Line in Response to Celecoxib and Diclofenac Response to different concentrations of NSAIDs measured every 24 h for 72 h. Increase in fluorescence is measured with the Sytox reagent in the FITC channel with a molecular devices flex station plate reader. Untreated and vehicle treated (HBCD) served as controls. Results are presented as means±SD (N=2, n=6). Statistics N.D.
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Figure 50: Increase in Sytox Signal over Time in the 4T1 Cell Line in Response to Nimesulide and Sulindac Response to different concentrations of NSAIDs measured every 24 h for 72 h. Increase in fluorescence is measured with the Sytox reagent in the FITC channel with a molecular devices flex station plate reader. Untreated and vehicle treated (HBCD) served as controls. Results are presented as means±SD (N=2, n=6). Statistics N.D.
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Figure 51: Increase in Sytox Signal over Time in the 4T1 Cell Line in Response to Salicylate Response to different concentrations of NSAIDs measured every 24 h for 72 h. Increase in fluorescence is measured with the Sytox reagent in the FITC channel with a molecular devices flex station plate reader. Untreated and vehicle treated (HBCD) served as controls. Results are presented as means±SD (N=2, n=6). Statistics N.D.
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Figure 52: Cytosolic ROS Measured using CellROX is Similar to that Produced Using DCF. Mitochondrial Membrane Potential in Response to NSAID Testing at 24 h and 72 h B16F10 cells were analyzed for cytosolic ROS production using the CellROX reagent at both 2 h and 24 h via cytometry using a BD Fortessa in the FITC channel. NSAIDs were assayed at 50 µM with αTS as a control. Results are presented as means±SD (N=1, n=3), with * indicating a difference from Z (P<0.05) for control vs drug treated samples. Membrane potential was measured using the Mitopotential reagent from Merck and analyzed using a Muse cytometer at the timepoints indicated. Results are presented as means±SD (N=1, n=3), with * indicating a difference from Z (P<0.05) for control vs drug treated samples.
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Figure 53: Salicylate Tested at 5 mM slows Growth Rates but Does Not Induce Cell Death in the B16F10 Cell Line B16F10 cells were analyzed for growth rates using a JuLiBR cell monitoring system with concentrations of diclofenac or salicylate as shown. Images show the growth of salicylate treated cultures, even after treatment at 5mM, untreated cells, and diclofenac treated cells at 500 µM with complete cell death.
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Appendix III
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Figure 54: Full Well Imaging of Acridine Orange Assay Full well images of the Acridine Orange assay as described in Figure 30
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Figure 55: Full Well Imaging of MnTMPyP DHE Assay Full well images of the DHE assay as described in Figure 34
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Appendix V
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Appendix VI
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