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Fall 12-18-2020
Melatonin-Tamoxifen Drug Conjugates as Breast Cancer Drugs: Pharmacological Evaluation in Phenotypically Diverse Breast Cancer Models and Pharmacokinetic Assessment in Liver Microsome and Female Mouse Models
Mahmud Hasan
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Recommended Citation Hasan, M. (2020). Melatonin-Tamoxifen Drug Conjugates as Breast Cancer Drugs: Pharmacological Evaluation in Phenotypically Diverse Breast Cancer Models and Pharmacokinetic Assessment in Liver Microsome and Female Mouse Models (Doctoral dissertation, Duquesne University). Retrieved from https://dsc.duq.edu/etd/1935
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MELATONIN-TAMOXIFEN DRUG CONJUGATES AS BREAST CANCER DRUGS:
PHARMACOLOGICAL EVALUATION IN PHENOTYPICALLY DIVERSE BREAST
CANCER MODELS AND PHARMACOKINETIC ASSESSMENT IN LIVER MICROSOME
AND FEMALE MOUSE MODELS
A Dissertation
Submitted to the Graduate School of Pharmaceutical, Administrative, and Social Sciences
Duquesne University
In partial fulfillment of the requirements for
the degree of Doctor of Philosophy
By
Mahmud Hasan
December 2020
Copyright by
Mahmud Hasan
2020 MELATONIN-TAMOXIFEN DRUG CONJUGATES AS BREAST CANCER
DRUGS: PHARMACOLOGICAL EVALUATION IN PHENOTYPICALLY
DIVERSE BREAST CANCER MODELS AND PHARMACOKINETIC
ASSESSMENT IN LIVER MICROSOME AND FEMALE MOUSE MODELS By
Mahmud Hasan
Approved September 4th, 2020
______Paula A. Witt-Enderby, Ph.D. David A. Johnson, Ph.D. Chair and Professor of Pharmacology Committee member and Associate Professor of School of Pharmacy and Graduate School of Pharmacology Pharmaceutical, Administrative, and Social School of Pharmacy and Graduate School of Sciences Pharmaceutical, Administrative, and Social Sciences
______Jane E. Cavanaugh, Ph.D. Lauren A. O’Donnell, Ph.D. Committee member and Associate Professor of Committee member and Associate Professor of Pharmacology Pharmacology School of Pharmacy and Graduate School of School of Pharmacy and Graduate School of Pharmaceutical, Administrative, and Social Pharmaceutical, Administrative, and Social Sciences Sciences
______Robert E. Stratford, Ph.D. Carl A. Anderson, Ph.D. Committee member and Associate Professor Representative and Associate Professor Division of Clinical Pharmacology School of Pharmacy and Graduate School of Indiana University School of Medicine Pharmaceutical, Administrative, and Social Sciences
______James K. Drennen III, Ph.D. Dean School of Pharmacy and Graduate School of Pharmaceutical, Administrative, and Social Sciences
iii ABSTRACT
MELATONIN-TAMOXIFEN DRUG CONJUGATES AS BREAST CANCER DRUGS:
PHARMACOLOGICAL EVALUATION IN PHENOTYPICALLY DIVERSE BREAST
CANCER MODELS AND PHARMACOKINETIC ASSESSMENT IN LIVER MICROSOME
AND FEMALE MOUSE MODELS
By
Mahmud Hasan
December 2020
Dissertation supervised by Paula A. Witt-Enderby
Tamoxifen is a first-generation selective estrogen receptor modulator, which reduces the risk of both invasive and non-invasive breast cancer (BC) as well as tumor recurrence in several clinical trials. However, chronic use of tamoxifen can increase uterine cancer risk and induce tamoxifen resistance. In past studies, melatonin alone reversed tamoxifen resistance induced by light exposure at night in rodents. This study demonstrates that melatonin or melatonin-based ligands (e.g., melatonin-tamoxifen drug conjugates) may be novel BC therapies that are efficacious and free of side effects. To investigate this further, five melatonin-tamoxifen drug conjugates with different linker sizes were synthesized and screened for their anti-cancer actions in a variety of BC cells that included: MCF-7 (ER+), tamoxifen-resistant MCF-7 (TamR), MMC (HER2+), MDA-
MB-231 (triple-negative), and BT-549 (triple-negative). Specifically, their actions against cell viability and migration and binding affinity to MT1 melatonin receptor (MT1Rs) and estrogen
iv receptor 1 (ESR1) were assessed. The melatonin-tamoxifen drug conjugate linked with four (C4) or five (C5) carbons demonstrated the most favorable pharmacological characteristics with respect to potency and efficacy to inhibit BC cell viability and migration. C4 and C5 also exhibited unique binding profiles (affinity for ESR1 and MT1R) compared to the other conjugates. C4 and C5 were further assessed for their actions against tamoxifen-resistant (TamR) MCF-7 cells and patient- derived xenograft triple-negative BC cells (TU-BcX-4IC) as well as for potential mechanisms of action using selective MEK1/2, MEK5, and PI3K inhibitors. C4 and C5 inhibited TamR MCF-7 cells with equal potency and efficacy and both C4 and C5 inhibited TU-BcX-4IC cell viability.
Even though both compounds demonstrated similar inhibitory actions against BC cell viability and migration, how this occurred, at a mechanistic level, was quite different between C4 and C5 in the cell lines. The underlying mechanisms of C4 and C5 in BC cell lines were context-specific and involved ERK1/2, ERK5, PI3 kinase, and NF-κB. They also exhibited unique pharmacokinetic profiles, where C4 had higher relative oral bioavailability than C5. These melatonin-tamoxifen drug conjugates show promise as novel anti-BC drugs.
v DEDICATION
To my mother, Rowshan Ara Khanam
vi ACKNOWLEDGEMENT
With a mixed feeling of happiness and sorrow, I am ending my journey at Duquesne
University. I am glad for the successful completion of my dissertation while I cannot express in
words how deeply I will miss Duquesne. Like all other journeys in our lives, I have to say goodbye
to my Duquesne family and move forward. Nevertheless, Duquesne became a part of my family
as they will be missed but not forgotten. I want to cherish the moments I spend at Duquesne till
my death. I want to express my gratitude to all the people at Duquesne University and to the people
I have met in Pittsburgh.
I am thankful to my committee members. They were very helpful since the beginning of
my journey at Duquesne University; even before being on my committee. They gave me priceless feedback. Without their help, my Ph.D. would be impossible to finish.
Besides their roles as committee members, I do not doubt that they are one of the most influential teachers in my life. Dr. David Johnson taught me drug mechanisms, receptors, pharmacological methods. Dr. Jane Cavanaugh, I learned rigorous scientific writing from her. Dr.
Lauren O’Donnell, I learned immunology, gene editing, and pharmacological methods from her.
Dr. Robert Stratford, taught me everything I know about pharmacokinetics today.
And, Dr. Rehana Leak, showed me the path of critical thinking. Her teachings will be a valuable asset in my scientific career. I am thankful to Dr. Christopher Surratt for teaching me transfection and PCR in the Methods class.
My heartfelt thanks to my collaborators. Dr. Darius Zlotos, Dr. Ulrike Holzgrabe, and
Mohamed Akmal Marzouk for their help in synthesis. Dr. Robert Stratford, Dr. Chandrali
Bhattacharya, and Saugat Adhikari for their help in the pharmacokinetic study. Dr. Matthew
vii Burow, Dr. Bridgette Collins-Burow, Madlin Alzoubi, Maryl Wright, Steven Elliott, and
Margarite Matossian for their help PDX study.
The labs at the GSPS were always very helpful and supportive to me. Specially I want to thank Dr. Cavanaugh's lab (Dr. Thomas Wright and Akshita Bhatt) and Dr. O’Donnell’s lab
(Manisha Chandwani and Yashika Kamte) for their help in my research.
My lab mates, Dr. Sifat Maria, Dr. Michael Wasko, and Fahima Munmun, I am forever in debt to them for their help in my research and their support in my time of need.
And last but not the least, my advisor, my mentor, Dr. Paula Witt-Enderby. She taught me everything I needed for my Ph.D. Critical thinking, pharmacology, receptor biology, cancer, endocrine, inhibitors mechanism, whatnot. She was never reluctant from giving me feedbacks.
Without Dr. Witt-Enderby, my Ph.D. would be impossible. And I am saying this not only because of her help as an advisor but also for the support in my life. She encouraged me, motivated me.
When I was depressed, when I failed. She always tells me, “like everything else, this shall pass too. Your mom wants to see you get the doctorate. You have to do it for your mom. You have to do it for your family.” I came to Pittsburgh, alone, leaving my family 10,000 miles away. I was homesick, but not alone. It’s because of Dr. Witt-Enderby and the people at Duquesne.
I am thankful to my wife, Tartela Tabassum, for her support. I am also thankful to my son,
Mikaeel Tasallee, who brought happiness to my life. Who showed me the meaning of life, and the true nature of unconditional love.
Finally, I want to thank everyone at Duquesne University for the unbelievable help and support. It was beyond my imagination and I could not ask more. I am thankful to God for having wonderful people in my life.
viii TABLE OF CONTENTS
Page
Abstract………………………………………………………………………………………….. iv
Dedication……………………………………………………………………………………….. vi
Acknowledgment……………………………………………………………………………….. vii
List of Tables……………………………………………………………………...…………… xiv
List of Figures………………………………………………………………………………….. xvi
List of Abbreviations…………………………………………………………………...…….. xviii
Chapter 1: Review on breast cancer…………………………………………………………... 1
1.1. Prevalence and Risk Factors……………………………………………………………….. 1
1.2. Classifications…………………………………………………………………………….... 1
1.2.1. Luminal A and B………………………………………………………………………... 2
1.2.2. Basal…………………………………………………………………………………….. 2
1.2.3. HER2-positive…………………………………………………………………………... 2
1.2.4. Claudin-low……………………………………………………………………………... 3
1.3. Therapies and limitations…………………………………………………………………... 3
1.3.1. Surgery………………………………………………………………………………….. 4
1.3.2. Radiotherapy……………………………………………………………………………. 4
1.3.3. Chemotherapy…………………………………………………………...…………….... 5
1.3.4. Endocrine therapy………………………………………………………………………. 6
1.3.4.1. Tamoxifen and its clinical actions…………………………………………………... 7
1.3.4.2. Tamoxifen and its molecular actions………………………………………………... 8
1.3.5. Targeted therapy………………………………………………………………………. 10
ix Page
1.3.5.1. Immunotherapy………………………………………………………..…………… 10
1.3.6. Antibody drug conjugates (ADCs) ………………………………………………….... 11
1.4. Estrogen receptors (ERs) and ER-mediated signaling pathways…………………………. 12
1.4.1. ER physiology, pharmacology, and signaling……………………………………….... 12
1.4.2. ERs and their role in BC…………………………………………………………….... 15
1.4.3. Heterologous modulation of ERs and ER-mediated signaling………………………... 19
1.5. Melatonin receptors, physiology, pharmacology, and signaling…………………………. 20
1.5.1. Melatonin’s role in physiological processes…………………………………………... 20
1.5.2. Melatonin’s role in BC………………………………………………………………... 21
1.5.2.1 Melatonin’s direct role in BC…………………………………………………….... 22
1.5.2.2 Melatonin’s role as an adjuvant in BC……………………………………………... 22
1.5.3. Melatonin receptor-dependent and -independent actions, associated signaling cascades and their role in BC……………………………………………………………………………... 23
1.5.3.1 Melatonin’s receptor-independent and anti-cancer actions………………………... 23
1.5.3.2 Melatonin, melatonin receptors, and their anti-cancer actions…………………….. 24
1.6. Mechanism of drug resistance and treatment……………………………………………... 27
1.6.1. Anti-HER2 resistance…………………………………………………………………. 28
1.6.2. Immune resistance…………………………………………………………………….. 28
1.6.3. ADC resistance……...... 29
1.6.4. Tamoxifen resistance……...... 29
1.7. Rationale for the Development of Drug conjugates for the Treatment of BC...... 31
1.7.1. Types of drug conjugates...... 32
x Page
1.7.1.1. Antibody-drug conjugates...... 32
1.7.1.2. Radionuclide conjugates...... 33
1.7.1.3. Drug-delivery system conjugates...... 33
1.7.1.4. Drug-drug conjugates...... 33
1.7.2. Pharmacology of drug conjugates...... 33
1.7.3. Pharmacokinetics of drug conjugates...... 34
1.7.4. Models for drug conjugates studies...... 34
1.7.4.1. In vitro...... 35
1.7.4.2. In vivo...... 35
Chapter 2: Research hypothesis and aims…………………………………………………… 37
2.1. Rationale………………………………………………………………………………..… 37
2.2. Hypothesis………………………………………………………………………………… 39
2.3. Specific Aims……………………………………………………………………………... 40
Chapter 3: Materials and methods………………………………………………………….... 41
3.1. Synthesis of melatonin-tamoxifen drug conjugates………………………………………. 41
3.2. Competition binding for melatonin and estrogen receptors………………………………. 42
3.3. Total binding assay……………………………………………………………………….. 43
3.4. Cell culture………………….…………………………………………………………….. 43
3.5. Development and characterization of TamR MCF-7 cells……………………………….. 43
3.6. Ex vivo treatment of PDX tumors…………………………………………………….….. 44
3.7. In vitro treatment of PDX-derived cells for western blot………………………………… 45
3.8. Cell viability……………………………………………………………….……………… 45
xi Page
3.9. Cell Migration……………………………………………………………….……….…… 46
3.10. Western blot………………………………………………………..…….……………… 47
3.11. Microsomal incubation method………………………………………….……………… 48
3.12. Pharmacokinetic analysis of C4 and C5………………………...……….……………… 49
3.13. LC-MS/MS method for quantification of tamoxifen, C4, and C5 in mouse plasma……. 50
3.14. Statistical analysis………………………...……….……………………..……………… 54
Chapter 4: Results……………………………………………………………………………... 55
4.1. Effects of C2, C4, C5, C9, and C15 conjugates on MCF-7 (ER+/PR+) cells……………. 55
4.2. Effects of C2, C4, C5, C9, and C15 conjugates on MMC (HER2+) cells………………... 58
4.3. Effect of C2, C4, C5, C9, and C15 conjugates on MDA-MB-231 (ER-/PR-/HER-) cells.. 62
4.4. Effects of C2, C4, C5, C9, and C15 conjugates on BT-549 cells……………………….... 64
4.5. Binding affinities of C2, C4, C5, C9, and C15 conjugates to ERs and MT1Rs………...… 68
4.6. Binding affinities of C4, C5, and G1 to ERs……………………………………………... 69
4.7. Effects of C4 and C5 conjugates on TamR MCF-7 cells…………………………………. 73
4.8. Effects of C4 and C5 conjugates on TU-BcX-4IC cells and TU-BcX-4QAN tumor tissue 76
4.9. Role of MEK1/2, MEK5 and PI3 kinases in mediating C4 and C5 effects on BC cell viability and migration………………………………………………………………………….. 81
4.10. Effect of C4 and C5 melatonin-tamoxifen drug conjugates on pERK5, pERK1/2, pAKT,
NF-кB, RUNX2, and β1-INTEGRIN protein levels…………………………………………… 89
4.11. Assessment of C4 and C5 drug conjugates metabolism both in vitro and in vivo……... 102
4.11.1. Microsomal incubation of tamoxifen, C4, and C5………………………………...... 102
4.11.2. Pharmacokinetics of tamoxifen, C4 and C5 in mice………………………………... 103
xii Page
Chapter 5: Discussion………………………………………………………………………... 105
Chapter 6: Strengths and Limitations…………………………………………………….... 116
Chapter 7: Conclusion and future directions………………………………………………. 119
Chapter 8: References……………………………………………………………………….. 123
Chapter 9: Appendices………………………………………………………………………. 141
9.1. Copyright statements………………………………………………………………….… 141
9.2. ER/ERE activation by estrogen in wildtype and TamR MCF-7 cells…………………... 141
9.2.1. Methods………………………………………………………...………………….… 141
9.2.1.1. ER-ERE Activation Analysis……..…………………………………………….… 141
9.2.1.2. Schild Plot analysis………….………………………………………………….… 142
9.2.2. Results………………………………….………………………………………….… 142
9.2.3. Summary and Conclusion……………………………………...………………….… 144
xiii LIST OF TABLES
Page
Table 1: Mass Spectrometry Collision Parameters…………………………………………….. 53
Table 2: Mass Spectrometry Acquisition and Source Parameters………………….………….. 53
Table 3: Matrix Effect and Extraction Recovery………………………...…………………….. 54
Table 4: Comparison of potencies between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell viability and migration……………………………………………………………………... 60
Table 5: Comparison of efficacies between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell viability and migration……………………………………………………………………... 64
Table 6: Comparison of potencies between C2, C4, C5, C9, and C15 conjugates and controls to inhibit BC cell viability and migration…………………………………………………………. 66
Table 7: Comparison of efficacies of C2, C4, C5, C9, and C15 conjugates and controls to inhibit
BC cell viability and migration. ………………………………………………………………... 67
Table 8: The effect of MEK1/2 (PD98059), MEK5 (Bix02189), and PI3K (pictilisib) on C4/C5- mediated effects on pERK1/2, pERK5, pAKT, NF-κB, RUNX2, β1-INTEGRIN levels in MCF-
7, MMC, MDA-MB-231, and BT-549 cell lines……………………………………………….. 90
Table 9: The effect of MEK1/2 (PD98059) and MEK5 (Bix02189) on C4-mediated effects on pERK1/2, pERK5, NF-κB, RUNX2, β1-INTEGRIN levels in MCF-7, MMC, MDA-MB-231, and BT-549 cell lines………………………………………………………………………….... 97
Table 10: The effect of MEK1/2 (PD98059) and MEK5 (Bix02189) on C5-mediated effects on pERK1/2, pERK5, NF-κB, RUNX2, and β1-INTEGRIN levels in MCF-7, MMC, MDA-MB-
231, and BT-549 cell lines……………………………………………………………………… 98
xiv Page
Table 11: The effect of PI3K (pictilisib) on C4-mediated effects on pERK1/2, pERK5, NF-κB,
RUNX2, β1-INTEGRIN, and pAKT levels in MCF-7, MMC, MDA-MB-231, and BT-549 cell lines……………………………………………………………………………………………... 99
Table 12: The effect of PI3K (pictilisib) on C5-mediated effects on pERK1/2, pERK5, NF-κB,
RUNX2, β 1-INTEGRIN, and pAKT levels in MCF-7, MMC, MDA-MB-231, and BT-549 cell lines……………………………………………………………………………………………. 100
Table 13: In vitro metabolism and in vivo pharmacokinetic parameters of tamoxifen, C4, or C5 by mouse (MLM)/human (HLM) liver microsomal incubation and by subcutaneous (SC)/oral
(PO) administration in female C57BL/6J mice, respectively…………………………………. 104
xv LIST OF FIGURES
Page
Figure 1: Molecular action of tamoxifen in breast cancer……………………………….…….... 9
Figure 2: Mechanism of ER of genes transcription through ER-ERE complex……………….. 14
Figure 3: Signaling pathways driving ERK activation, effectors, and cellular processes regulated by this kinase…………………………………………………………….... 18
Figure 4: Mechanism of melatonin’s anti-breast cancer action……………………………...… 26
Figure 5: Synthesis of the melatonin-tamoxifen drug conjugates……………………………... 41
Figure 6: Comparison of potency and efficacy between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell viability…………………………………………………………………………. 57
Figure 7: Comparison of potency and efficacy between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell migration……………………………………………………………………….. 61
Figure 8: Competition of C2, C4, C5, C9, or C15 for [3H]-or [125I]-estradiol binding to ERs expressed in mouse uterus or MCF-7 cells……………………………………………………... 70
125 Figure 9: Competition of C2, C4, C5, C9, or C15 for 2-[ I]-iodomelatonin binding to MT1Rs expressed in CHO cells…………………..……………………………………………………... 72
Figure 10: Saturation of [3H]-estradiol binding to ERs expressed in WT (A) and TamR (B)
MCF-7 cells……………………………...……………………………………………………... 74
Figure 11: Basal levels of pERK5 (A), pERK1/2 (B), ERα (C), NF-κB (D), and pAKT (E) in
TamR MCF-7 and MCF-7 cells………….……………………………………………………... 75
Figure 12: Effect of C4, C5, melatonin, tamoxifen, 4-OH-tamoxifen, and unlinked melatonin+tamoxifen on TamR MCF-7 cell viability and cell migration…………………….... 76
xvi Page
Figure 13: Effect of C4, C5, melatonin, tamoxifen, 4-OH-tamoxifen, and unlinked
melatonin+tamoxifen on TU-BCx-4IC cell viability and cell migration and TU-BcX-4QAN
tumor tissue…………………………………………………………………………………...… 80
Figure 14: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of C4 or
C5 in MCF-7 cells………………………………………………………………………………. 82
Figure 15: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of C4 or
C5 in MMC cells……………………………………………………………………………...… 84
Figure 16: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of C4 or
C5 in MDA-MB-231 cells……………………………………………………………………… 86
Figure 17: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of C4 or
C5 in BT-549 cells……………………………………………………………………………… 88
Figure 18: Summary of mechanisms of action underlying C4 or C5 in breast cancer cells…… 96
Figure 19: Basal levels of pERK5, pERK1/2, NF-κB, RUNX2, β1-INTEGRIN, and pAKT in
MCF-7, MMC, MDA-MB-231, and BT-549 BC cells……………………………………...… 102
Figure 20: Proposed mechanism of action for HER2, MTR, ER, and GPR30 in BC cells…... 109
Figure 21: Abridged mechanism of C4 and C5 on different BC cell lines…………………… 112
Figure 22: Binding of melatonin-tamoxifen conjugates to the receptors…………………….. 120
Figure 23: Proposed mechanism(s) of action of C4 or C5 melatonin-tamoxifen conjugate for
MCF-7 and TamR MCF-7, MDA-MB-231, BT-549, and MMC cells………………………... 121
xvii LIST OF ABBREVIATIONS
AC – Adenylyl cyclase
ADC – Antibody drug conjugate
AIB1 – Amplified in breast cancer-1
AKT – Protein kinase B (PKB)
APC – Antigen Presenting Cell
ATPase – Adenosinetriphosphatase
BC – Breast Cancer
Bix02189 – MEK5 inhibitor
C2 – 3-[[4-[4-[(1Z)-1,2-diphenyl-1-buten-1-yl]phenoxy]ethylmethylamino]-N-[2-(5-methoxy-
1H-indole-3-yl)ethyl]propionamide
C4 – 5-[[4-[4-[(1Z)-1,2-diphenyl-1-buten-1-yl]phenoxy]ethylmethylamino]-N-[2-(5-methoxy-
1H-indole-3-yl)ethyl]pentanamide
C5 – 6-[[4-[4-[(1Z)-1,2-diphenyl-1-buten-1-yl]phenoxy]ethylmethylamino]-N-[2-(5-methoxy-
1H-indole-3-yl)ethyl]hexanamide
C9 – 10-[[4-[4-[(1Z)-1,2-diphenyl-1-buten-1-yl]phenoxy]ethylmethylamino]-N-[2-(5-methoxy-
1H-indole-3-yl)ethyl]decanamide
C15 – 16-[[4-[4-[(1Z)-1,2-diphenyl-1-buten-1-yl]phenoxy]-ethylmethylamino]-N-[2-(5- methoxy-1H-indole-3-yl)ethyl]hexadecanamide
CDK – Cyclin-dependent Kinase
CREB – CREB-binding protein
CTLA-4 – Cytotoxic T lymphocyte-associated antigen 4
xviii DMEM – Dulbecco’s modified Eagle’s medium
DMSO – Dimethyl sulfoxide
DNMT – DNA-methyl transferase
ER – Estrogen Receptor
ERE – Estrogen response element
ERK – Extracellular-signal-regulated kinase
ESR1 – Estrogen receptor 1
ESR2 – Estrogen receptor 2
FBS – fetal bovine serum
GPR30 – G protein-coupled receptor for estrogen/ GPER-1
HAT – Histone acetyltransferase
HDAC – Histone deacetylase
HER2 – Human epidermal growth factor receptor 2
HPLC – High-performance liquid chromatography
IFN – Interferon
IRF-1 – Interferon Regulatory Factor 1
JNK – c-Jun N-terminal kinase
KRAS – Kirsten rat sarcoma viral oncogene homolog
LC – Liquid chromatography
LCMS – Liquid chromatography with mass spectrometry detection
LLQ – Lower Limit of Quantification
MAPK – Mitogen-activated protein kinase
MEK – Mitogen-activated protein kinase kinase
xix MHC – Major histocompatibility complex
MMC – Mouse mammary carcinoma
MMP – Matrix Metalloproteinases
MnSOD – manganese superoxide dismutase
MS – Mass spectrometry
MR – Melatonin receptor
MT1R – Melatonin receptor 1
MT2R – Melatonin receptor 2
MTT - 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide
NF-kB – Nuclear factor-kB
NO – Nitric oxide
PARP – Poly (ADP-ribose) polymerase
PD-1 – Programmed cell death 1
PD98059 – MEK1/2 inhibitor
PI3K – Phosphoinositide 3-kinase
Pictilisib – PI3 kinase inhibitor
PO – Per Os
PR – Progesterone receptor
PTEN – Phosphatase and tensin homolog
QC – Quality control
Runx2 – Runt-related transcription factor 2
SC – Subcutaneous
SERD – Selective estrogen receptor downregulator
xx SERM – Selective estrogen receptor modulator
SRC-1 – Steroid receptor co-activator-1
TAM – Tamoxifen
TAM-d5 – Deuterated tamoxifen
TamR – Tamoxifen resistant
TIMP1 – Tissue Inhibitor of Metalloproteinases-1
TNBC – Triple-negative breast cancer
WT – Wild type
xxi Chapter 1: Review on Breast Cancer
Cancer is a major health problem worldwide and the second leading cause of death in the
United States (Heron, 2019). Breast cancer (BC) is the most common cancer for women regardless of ethnicity and the leading cause of cancer-related death in women (G. N. Sharma et al., 2010).
The treatment options for BC depends on the type and stage of cancer (G. N. Sharma et al., 2010).
However, treatment failure can occur at any stage because of various factors such as patient compliance or resistance (Tang et al., 2016). Although significant improvements occurred in BC treatment and outcomes, further research is still required for safe, effective therapeutic options.
1.1. Prevalence and Risk Factors
According to the World Health Organization, BC affects about 2.1 million women worldwide each year, where BC deaths were estimated at 627,000 in 2018, which is 15% of all cancer-related deaths (2019). It is estimated that 41,760 BC patients will die because of BC in
2019, which is 6.9% of all cancer-related deaths (N et al., 2018). About 1 in 8 women have a risk of developing BC during their lifetime (Bunker et al., 1998). Several risk factors such as age, genetic mutations, reproduction, family history, and hormone replacement therapy can predispose
BC risk (Singletary, 2003). Lifestyle factors (i.e. physical activity, smoking, alcohol, hormone therapy, certain medications) can also play a crucial role in BC development (Singletary, 2003).
1.2. Classifications
BC can be classified based on different factors such as size, metastasis, receptor expression, and grade. Based on the receptor expression profiling, five molecular subtypes exist.
1 1.2.1. Luminal A and B
Luminal A BC expresses estrogen receptors (ERs), progesterone receptors (PRs), and have
low Ki67 expression. They are usually responsive to hormonal therapy or chemotherapy. MCF-7,
T47D, and SUM185 are cell lines that have these characteristics in that they are low in Ki67 and
responsive to endocrine therapy (Holliday & Speirs, 2011). Luminal B BC express ER, PR, HER2,
and high Ki67. They are usually responsive to hormone therapy, chemotherapy, and HER2
therapy. BT-474 and ZR-75 are cell lines that have these characteristics and are referred to as
triple-positive BC cells. Fallahpour et al. reported that luminal A type accounts for 59% of total
cases and showed a lower death rate of 2.2%; whereas luminal B accounts for 13.5% of total cases
and a death rate of 11.8% (Fallahpour et al., 2017).
1.2.2. Basal
Basal type BC cells are negative for ER, PR, or HER2 and are referred to as triple-negative
breast cancer (TNBC). They are not responsive to hormone therapy, but responsive to
chemotherapy. Examples of this type of cancer are the MDA-MB-468 and SUM190 cell lines.
Basal subtypes represent approximately 15% of total BC cases and demonstrate high mortality and
high rates of recurrence (Milioli et al., 2017).
1.2.3. HER2-positive
This BC overexpresses HER2 and is responsive to therapies targeting the HER2 receptor-
like trastuzumab as well as chemotherapy. The human BC lines, SKBR3 and MDA-MB-453, and mouse mammary carcinoma cells (MMCs) have these characteristics. HER2-positive BC accounts for 5.7% of total cases and 5.9% of total deaths (Fallahpour et al., 2017).
2 1.2.4. Claudin-low
Claudin-low BC does not express ER, PR, or HER2. In addition, Ki67, E-cadherin, claudin-
3, claudin-4, and claudin-7 expression are low. This type of BC is responsive to chemotherapy.
MDA-MB-231 and BT-549 are BC cells with these characteristics and they are referred to as
TNBC and claudin-low cell lines. MDA-MB-231 cells also harbor a KRAS/BRAF mutation while
BT-549 cells have a PTEN mutation, which will be an important consideration when identifying
the molecular mechanisms underlying some of the melatonin-tamoxifen drug conjugates’ actions
in these cell lines. Approximately 7-14% of invasive BC are claudin-low (Dias et al., 2017).
Claudin-low is considered a complex additional phenotype that can be divided into various
intrinsic subtypes (Fougner et al., 2020). Claudin-low subtypes can be found in 14.6% of all basal-
like tumors (Fougner et al., 2020). Claudin-low tumors show a lower proliferation rate compared to basal-like tumors (Fougner et al., 2020).
1.3. Therapies and limitations
There are many options regarding BC management, which includes surgery, radiotherapy,
chemotherapy, endocrine therapy, immunotherapy, targeted therapy, and conjugate therapy
(Hasan et al., 2018; X. Wang et al., 2019). The treatment choice varies depending on different
factors such as type, stage, invasiveness, and cost. Breast-conserving surgery and radiation therapy
are usually preferred for stage I and II BC, whereas chemotherapy alone or chemotherapy followed
by mastectomy is used for stage III BC patients (Maughan et al., 2010). A retrospective analysis
reported that there was a significant increase in treatment costs for advanced stage (stage III) BC
patients compared to the early-stage (stage I or II) patients (Blumen et al., 2016). For example, the
average cost per patient allowed by the insurance company increased by 58% between stage I or
3 II ($82,121) BC and stage III BC ($129,387), which was mostly due to the cost of chemotherapy
(Blumen et al., 2016).
1.3.1. Surgery
Tumors contained locally within the breast can be removed by surgery (Urruticoechea et al., 2010). Surgical options have been changed over the past two decades (Becker, 2015). For example, breast-conserving surgeries are being promoted along with radiation instead of radical mastectomy (Becker, 2015). Breast-conserving surgery (mastectomy) is often performed based on the reconstruction requirement where only the malignant tumor is removed to conserve normal tissues (Becker, 2015). While other therapies can only kill a fraction of cancer cells, complete removal of BC cells is possible by mastectomy (Urruticoechea et al., 2010). Tumor relapse post- surgery depends on the type of operation, post-operative therapy, receptor status, and lymph node status. For example, 5-year local recurrence after lumpectomy was found to be 2.1% (Arvold et al., 2011), while the 5-year local recurrence after mastectomy was found to be 6% when axillary nodes were devoid of cancer (RW, 2014).
1.3.2. Radiotherapy
Since the 1940s, radiotherapy has been used to reduce relapse after surgery (Ragaz et al.,
1997). While radiation therapy can cure 40% of cancer, it is limited to certain types of cancer
(Urruticoechea et al., 2010). Data from 36 randomized trials conducted in 17,273 women demonstrated that local recurrence was three times lower for patients receiving radiotherapy after surgery compared to patients receiving surgery alone ("Effects of Radiotherapy and Surgery in
Early Breast Cancer — An Overview of the Randomized Trials," 1995). After 15 years of follow- up, a randomized trial conducted in 318 premenopausal women with node-positive BC concluded that combined radiotherapy and chemotherapy reduced the recurrence rate by 33% and mortality
4 rate by 29% compared to chemotherapy alone (Ragaz et al., 1997). Radiotherapy can be used as
an effective adjuvant with other therapies such as tamoxifen, doxorubicin, methotrexate,
fluorouracil, and cyclophosphamide (Gröhn et al., 1984; Overgaard et al., 1999; Recht et al., 1996).
For example, radiotherapy plus tamoxifen exhibited a 36% disease-free survival compared to the
tamoxifen alone (24% disease-free survival) (Overgaard et al., 1999). Radiotherapy although
effective against BC produces adverse effects in the body like inducing secondary cancers or heart disease (Taylor et al., 2017). A systemic review and meta-analysis of 762,468 BC patients exhibited an increased risk of secondary cancer such as lung, esophagus, and sarcoma (Grantzau
& Overgaard, 2015). Regarding heart disease, a population-based, case-control study conducted in 2168 women who received radiotherapy demonstrated that patients showed an increased rate of ischemic heart disease due to ionizing radiation exposure to the heart (Darby et al., 2013).
1.3.3. Chemotherapy
Chemotherapy was first introduced in the 1950s for nonsolid tumors, which showed a higher rate of success for solid tumors (Becker, 2015). Over the years, several chemotherapies such as cyclophosphamide, methotrexate, 5-fluorouracil, paclitaxel, docetaxel, capecitabine, vincristine, gemcitabine, and eribulin have been developed—each targeting different signaling pathways (Becker, 2015). Chemotherapy usually produces adverse effects in those tissues that have a faster rate of growth like skin, nails, and bone marrow. The failure rate for chemotherapy varies between 5% to 50%, which is dependent upon the type of drug used, tumor size, metastasis, lymph node status, hormone receptor status, and HER2 receptor status/grading (Becker, 2015).
Chemotherapy is usually effective against TNBC, drug-resistant cancer, or non-responsive cancer because of its non-receptor-mediated actions and downstream targeting (Wahba & El-Hadaad,
2015). Treatment of TNBC remains complicated compared to the hormone-positive and HER2-
5 positive BC because of its aggressiveness and metastatic potential but also difficult to treat due to
a lack of targeted therapies (Anders & Carey, 2008). Since TNBC does not respond to endocrine
therapy or HER2-targeting agents (Anders & Carey, 2008), chemotherapy is the only option for
TNBC or basal-like BC (Cancer Genome Atlas, 2012).
1.3.4. Endocrine therapy
Anti-estrogen therapies comprise a broad class of drugs that include aromatase inhibitors,
selective estrogen receptor modulators (SERMs), and selective estrogen receptor downregulators
(SERDs). This form of therapy is commonly used to treat estrogen-dependent and estrogen
receptor (ER)-positive BC (Ali et al., 2016).
Aromatase inhibitors, which act by reducing estrogen levels, can bind covalently
(formestane and exemestane) with aromatase or non-covalently bind with the heme moiety
(fadrozole, vorozole, rogletimide, letrozole, and anastrozole) (Chumsri et al., 2011). Aromatase inhibitors are well-tolerated with some common side effects such as hot flashes, vaginal dryness, and headache (Chumsri et al., 2011). Unlike tamoxifen, aromatase inhibitors do not increase the risk of endometrial cancer and thromboembolism because of their lack of estrogenic effects
(Chumsri et al., 2011). Clinically aromatase inhibitors exhibit similar or superior efficacy compared to tamoxifen. For example, in one study comparing anastrozole to tamoxifen, a delay in disease progression from 23 weeks to 42 weeks was observed with aromatase inhibitors vs
tamoxifen. However, in the TARGET trial comparing anastrozole to tamoxifen, no distinction in disease progression (8.2 months vs. 8.3 months) was observed (Chumsri et al., 2011).
SERMs such as tamoxifen, raloxifene, and toremifene are a class of compounds that
agonize or antagonize ERs in a tissue-dependent manner. Tamoxifen, which will be the focus of
6 this dissertation, antagonizes ERs to inhibit BC but acts as an agonist in the endometrium and bone
(Johnston, 2001). Raloxifene came to the market in 1997 first as an anti-osteoporotic drug and then it was approved for use as a BC drug for ER+ BC in 2007 (Waters et al., 2012). Similar to tamoxifen, raloxifene antagonizes ERs in breast cells, whereas it differs from tamoxifen in that does not activate uterine ERs and stimulate the growth of uterine epithelium (Rey et al., 2009).
Both tamoxifen and raloxifene, however, exhibit estrogenic actions in bone and serum cholesterol in ovariectomized rats (Sato et al., 1994).
SERDs such as fulvestrant work differently than SERMs because they prevent ER dimerization from occurring making the ER monomers susceptible to proteolysis and degradation; this results in a loss of ER expression or down-regulation (Nathan & Schmid, 2017) (C. K. Osborne et al., 2004). Selective estrogen receptor downregulators can also inhibit AF1- and AF2-related transcriptional activity (Movérare-Skrtic et al., 2014).
1.3.4.1. Tamoxifen and its clinical actions
The first-generation SERM, tamoxifen, was developed in 1966 and is widely used for ER+
BC. It is approved by the FDA for both the prevention and treatment of ER+ BC in pre- and post- menopausal women (Jaiyesimi et al., 1995; Minsun, 2012; Ring & Dowsett, 2004; Wapnir et al.,
2011). Several studies demonstrate significant tamoxifen efficacy against invasive and non- invasive BC (Wapnir et al., 2011). Even though 20-30% of patients on tamoxifen therapy become resistant to it over time, it is the first drug of choice for ER+ BC because of its ability to reduce the mortality rate and relapse by 31% and 50%, respectively (Ali et al., 2016). Despite having the clinical benefit for treating BC, long-term use of tamoxifen can result in relapse (Ring & Dowsett,
2004) and increase the risk of uterine cancer (Assikis & Jordan, 1997; Bernstein et al., 1999; Jones et al., 2012; van Leeuwen et al., 1994). Regarding the mechanisms underlying tamoxifen’s actions
7 on the uterus, it is through its estrogenic actions at ERs expressed in the endometrium possibly through recruitment of co-activators such as steroid receptor co-activator-1 (SRC-1), amplified in breast cancer-1 (AIB1), and CREB-binding protein (CBP) (Hu et al., 2015). Tamoxifen’s mechanisms of resistance will be discussed further in Section 1.6.4.
1.3.4.2. Tamoxifen and its molecular actions
Tamoxifen is a prodrug, which gets metabolized into 4-hydroxytamoxifen and endoxifen by liver cytochrome P450 enzymes (CYP26 and CYP3A4 isoforms) (Ali et al., 2016). Both 4- hydroxytamoxifen and endoxifen have up to 100 times higher affinity for the ER compared to tamoxifen (Felker et al., 2016). A schematic of tamoxifen’s molecular action in BC has been described in Figure 1. Tamoxifen, following binding to ERs, recruit co-repressor proteins including NCoR, SMRT, and histone deacetylases (HDACs) reducing estrogen/ER-mediated gene expression. Tamoxifen, by antagonizing mitochondrial ER-β, can increase reactive oxygen species possibly through downregulation of manganese superoxide dismutase (Razandi et al., 2013).
Besides having ER-dependent actions, tamoxifen can also inhibit BC in an ER-independent manner. For example, tamoxifen can induce apoptosis in cells independent of ERs (Bogush et al.,
2012) and promote apoptosis in C6 glioma cells by inhibiting PI3K/AKT and JNK while sustaining
ERK1/2 activation (Feng et al., 2010). Tamoxifen can also induce mitochondrial stress by increasing intramitochondrial calcium levels through a NO-dependent pathway to enhance apoptosis; tamoxifen-mediated stimulation of NO synthase causes reduced cytochrome C release and suppression of mitochondrial respiration (Bogush et al., 2012). The finding that tamoxifen can stimulate ATPase suggests that tamoxifen may promote proton permeability due to a loss of mitochondrial inner membrane structural integrity (Cardoso et al., 2001). Tamoxifen can also modulate matrix metalloproteinases, which may or may not be favorable to breast cancer
8 protection. For example, tamoxifen can up-regulate matrix metalloproteinase 1, an enzyme involved in BC angiogenesis and invasiveness, and tissue inhibitor of metalloproteinases-1, a protein that promotes BC cell proliferation and anti-apoptosis. However, tamoxifen can also downregulate metalloproteinase 9, a protein involved in tumor vascularization and also known to be involved in metastases in MCF-7 cells, which would prevent BC (Cheng et al., 2016; Eck et al.,
2009; Mehner et al., 2014; Nilsson et al., 2007).
Figure 1: Molecular action of tamoxifen in BC. Tamoxifen demonstrated a multitude of actions in BC cells. It can inhibit nuclear ER while activating membrane-bound ER. It can block
JNK and PI3K pathway while sustaining ERK1/2 activation. Tamoxifen can also modulate BC angiogenesis, invasiveness, vascularization, metastasis, apoptosis, and proliferation by regulating
MMPs and TIMP1. Furthermore, tamoxifen can produce mitochondrial stress and apoptosis through the regulation of ER- β, calcium level, NO synthase, and ATPase. MMP = Matrix
Metalloproteinases, TIMP1 = Tissue Inhibitor of Metalloproteinases-1, MnSOD = manganese superoxide dismutase.
9 1.3.5. Targeted therapy
Targeted therapy usually regulates a target receptor or specific signaling protein in cancer cells by the use of monoclonal antibodies or small molecule inhibitors. For example, monoclonal antibodies that inhibit HER2 (e.g., trastuzumab and pertuzumab b) have been approved by the
FDA to treat HER2-positive BC (Appert-Collin et al., 2015) while signaling proteins, CDK4/6,
PARP, and PI3K, involved in cell proliferation, cell survival, cell growth, and DNA repair, are targeted using small molecule inhibitors (Breast Cancer Facts & Figures 2019-2020, 2019; Nur
Husna et al., 2018). In this dissertation, immunotherapy is discussed under the section on targeted therapy. However, some immunotherapies such as interleukins and interferons, might not be considered “targeted” when the therapy affects non-cancerous cells (Monjazeb et al., 2012).
1.3.5.1. Immunotherapy
The immune system actively works in recognizing and destroying cancer cells where T- cells are activated by the cancer neoantigen signaling through Antigen Presenting Cells (APCs)
(García-Aranda & Redondo, 2019). Activated CD8+ T-cells are considered the main effectors in killing aberrant cells. CD8+ T-cells can enhance CD4 T-helper cell activity and increase B cell antibody production (Pross & Lefkowitz, 2007). However, different types of immune cells can act differently on the tumor. Innate immune cells play a role in tumor proliferation, tumor elimination, promote metastasis, and inhibition of tumor cell transformation (Gonzalez et al., 2018). For example, T cell infiltration exhibits a good prognosis on solid tumors, whereas macrophage infiltration demonstrates poor prognosis (Gonzalez et al., 2018).
After the engagement of major histocompatibility complexes (MHCs) with T cell receptors
(TCRs), CD28 binds to CD80/86 for further T cell activation (Abril-Rodriguez & Ribas, 2017).
Binding of CD28 to CD80/86 can be inhibited by cytotoxic T lymphocyte-associated antigen 4
10 (CTLA-4) in the early stage of T cell activation in the lymph nodes (Abril-Rodriguez & Ribas,
2017). Cancer cells can further prevent the action of T cells by blocking programmed cell death 1
(PD-1) receptor by expressing PD-L1 or PD-L2 ligands (Abril-Rodriguez & Ribas, 2017).
Monoclonal antibodies targeting CTLA-4, PD-1, PD-L1, and immune checkpoint proteins,
have been approved by the FDA to treat different cancers such as melanoma, lung cancer,
Hodgkin’s lymphoma, renal carcinoma, Merkel cell carcinoma, urothelial carcinoma, bladder
cancer, head and neck cancer (Abril-Rodriguez & Ribas, 2017); clinical trials on immune checkpoint inhibitors are ongoing for BC patients (Cesar & Rita, 2018). An anti-PD-1 antibody, pembrolizumab, demonstrates an 18.5% to 23% response rate in TNBC patients (Adams et al.,
2017; Nanda et al., 2016) and a 12% response rate in ER+/HER2- advanced breast cancer patients
(Basu et al., 2019). Although well-tolerated, these immune checkpoint inhibitors are unable to
prevent relapse and metastasis (Basu et al., 2019). The CTLA 4 blocker, tremelimumab, plus
exemestane exhibit stable disease conditions in 42% of metastatic ER+ patients (Vonderheide et
al., 2017). In a pilot study, a preoperative single dose of ipilimumab (anti-CTLA4) and
cryoablation exhibit intratumoral and systemic immunologic effects (McArthur et al., 2016).
1.3.6. Antibody drug conjugates
Antibody drug conjugates (ADCs) are immunoconjugates where an antibody is usually
attached to a cytotoxic drug. Although ADCs are one of the fastest growing classes of cancer
therapeutics and several ADCs are under investigation, only Kadcyla® (Trastuzumab emtansine
conjugate) has been approved by the FDA for HER2-positive metastatic BC patients and other
HER2 targeting drug conjugates are also on clinical trials (Hasan et al., 2018; Lambert & Chari,
2014). Details of ADCs are discussed further in section 1.7.1.1.
11 1.4. Estrogen receptors (ERs) and ER-mediated signaling pathways
Numerous receptors (ER, HER2, and ErbB) and/or signaling pathways (i.e., MAPK, Wnt,
Hedgehog, PI3K, mTOR, JAK/STAT, TGF, and Notch) play critical roles in tumor progression,
cell growth, apoptosis, and drug resistance (McCubrey et al., 2016). Because of their important
role in BC pathogenesis, they are targets of myriad cancer drugs including tamoxifen.
1.4.1. ER physiology, pharmacology, and signaling
Estrogens play critical roles in both female and male reproduction, including mammary
development in females (Molina et al., 2017) and sperm maturation in males (Molina et al., 2017).
Estrogens also are important in cardiovascular, skeletal, and nervous system functions (Molina et
al., 2017). Endogenous estrogens such as estrone (E1), estradiol (E2), and estriol (E3) bind to and
activate nuclear ERs through passive diffusion due to their hydrophobic nature (Molina et al.,
2017). Estrogens can also bind to and activate membrane-bound ERs, GPR 30, and activate
downstream proteins (Figure 2).
ERs are classified as non-genomic (membrane-bound G-protein coupled receptor) or
genomic (ERα and ERβ) (Saha Roy & Vadlamudi, 2012a). The ERα-expressing gene, which
encodes for a 595 amino acid protein, is located on chromosome 6 whereas the ERβ-expressing
gene, which encodes for a 530 amino acid protein, is located on chromosome 14 (Jameera Begam
et al., 2017) making them unique gene products and not splice variants. ERα, which has a
molecular weight of 66 kDa is larger than ERβ, which has a molecular weight of 54 kDa (Jameera
Begam et al., 2017). The genomic ERs modulate intracellular responses via estrogen response
elements (EREs), which is a 28-nucleotide sequence consisting of 5′-GATCTCGAGTCAGGT-
CACAGTGACCTGA-3′ that lay upstream of various genes and promoter sequences.
12 Estrogen modulates ER-dependent gene transcription by the following sequence described
in Figure 2. In brief, estrogen, following binding to ERs, promotes ER dimerization and
translocation to EREs located on genes. Gene transcription occurs following the activation of
histone acetyltransferase (HAT) proteins, which acetylates lysine residues on histone binding
proteins releasing their binding to DNA. ER-ERE mediated gene transcription can be enhanced by co-activators (e.g., SRC1, NCoA2, NCoA3, and CREB-binding protein) and can be suppressed by co-repressors (e.g., NCoR1 and NCoR2) (Ring & Dowsett, 2004). Moreover, other receptors (e.g.,
IGFR, EGFR, and HER2), cytokines, and stress can phosphorylate ERs through the activation of
AKT, ERK1/2, and p38 pathways (Ring & Dowsett, 2004).
ERα can activate Src kinase, mitogen-activated protein kinase (MAPK), phosphatidylinositol 3-kinase (PI3K), and protein kinase C pathways (Saha Roy & Vadlamudi,
2012b). A detailed mechanism of the MAPK pathway is described in Figure 3.
The PI3K-AKT-mTOR pathway plays an important role in cell survival; and dysregulation of this pathway may induce endocrine resistance (Mohamed et al., 2013). Mutation in the PI3KCA gene is the most frequent genetic abnormality in ER+ BC, whereas a somatic mutation in TP53,
PIK3CA, and GATA3 occurs in more than 10% of all BC (Xiang et al., 2012). Cytosolic activation of ERK and AKT can induce cell migration (Saha Roy & Vadlamudi, 2012b). ERs can also interact with kinases in the cytoplasm and membrane via a non-genomic pathway (Ring & Dowsett, 2004).
The estrogen-mediated actions on ERK1/2 occur in human HER2 (SKBR-3) BC cells that are ERα and ERβ negative demonstrating that these estrogen-mediated actions on ERK1/2 probably are occurring through the non-nuclear estrogen receptor, GPR30 (Molina et al., 2017).
GPR30 (also known as GPER-1) is a seven-transmembrane G-protein coupled receptor that
13 contains 375 amino acids with a molecular weight of 41 kDa (Hsu et al., 2019; Molina et al., 2017).
Estrogen-induced signaling through GPR30 is considered a non-classical pathway. GPR30 can increase cAMP formation and intracellular IP3, which can transactivate EGFR or activate
PI3K/AKT or ERK1/2 pathways (Molina et al., 2017). For example, inhibition of GPR30 downregulates PI3K and p-AKT expression and blocks SKBR-3 BC cell proliferation (Shi et al.,
2020). GPR 30 activates transcription factors such as Fos/Jun activating protein-1 by binding with co-activators (Ring & Dowsett, 2004). See Figure 2 for the detailed schematic.
Figure 2: Mechanism of ER of genes transcription through ER-ERE complex. This schematic is taken from (Egeland et al., 2015), licensed under CC BY 4.0
14 (https://creativecommons.org/licenses/by/4.0/). ER is activated by estrogen (E) that dimerize and
translocate to the nucleus. The dimer binds with ERE or serum response element (SRE). ER-ERE
complex recruits co-activators such as HATs to induce gene transcription, whereas ER-SRE
complex also recruits transcription factors such as AP-1 and AP-2. In the non-classical pathway,
E can bind with GPR30, RTKs, or other receptors. Depending on the type of receptor, E can
activate secondary messenger (SM) or PI3K-AKT pathway. ER can stimulate ERK or transactivate
RTKs in a ligand-independent manner. RTKs further phosphorylate genomic ER. PI3K/AKT pathway and ERK activation can further activate transcription factors bound to the response
element.
1.4.2. ERs and their role in BC
Estrogen, directly or through its cognate receptors, can cause BC. Even though estrogen,
specifically through its quinone metabolites, can induce mammary cancer through DNA damage
(Yue et al., 2013), most of the estrogen’s cancer-promoting actions occur through ERs. Most
(70%) of total BC cases are ER-positive (Mohibi et al., 2011). The mechanisms by which ERs
play a role in BC are diverse and include estrogen/ER-mediated actions as well as non-estrogen-
mediated actions. For example, in the absence of estrogen, ERα can attach to an Hsp90 multi-
chaperone complex in the cytosol (Renoir et al., 2013). After ligand-activation, Hsp90 is released
from the ER and active ERs dimerize and translocate to the nucleus (Renoir, Marsaud, & Lazennec,
2013). After translocation, the ER dimer binds to the ERE and recruits co-activators such as SRC1,
AIB1, and CBP, which have histone acetyltransferase activity, to induce ER/ERE-regulated genes
(Saha Roy & Vadlamudi, 2012a). Moreover, studies demonstrate that chronic estradiol exposure
results in ER/ERE-mediated downregulation of transcriptional repressors that regulate anti-
15 proliferative and pro-apoptotic genes (Frasor et al., 2003) and upregulate tumor promoters like
AF-1 and AF-2 (Ring & Dowsett, 2004).
ERα and ERβ can exhibit different actions in normal mammary epithelial cells. For
example, the ERα-ERE complex can induce several gene transcripts such as the cyclins and c-
myc, which are related to cell proliferation, migration, differentiation, invasion, metastasis (Renoir et al., 2013). ERβ inhibits cell proliferation by arresting cells in G2 of the cell cycle, by inhibiting c-myc, cyclin D1, and cyclin A (Paruthiyil et al., 2004). Coactivators can be differentially expressed and their functions can be altered in tumors (Saha Roy & Vadlamudi, 2012b). Histone acetyltransferases (HATs), DNA-methyl transferases (DNMTs), and histone deacetylases
(HDACs) can regulate gene transcription by altering chromatin structure (Mohamed et al., 2013).
Histone modulators can act as coactivators/corepressors for several nuclear receptors such as ER.
Studies demonstrate that methylation within the ERα gene promoter decreases ERα gene transcription (Yoshida et al., 2000). Cell proliferation markers such as Ki67 and cyclin A are related to ERβ expression in BC (Jameera Begam et al., 2017). An interaction between ERs and the cyclin-dependent kinases, CDK4/6, can lead to endocrine resistance by persistent cyclin D1 expression and retinoblastoma (Rb) phosphorylation (Mohamed et al., 2013). CDK4/6 kinases regulate G1-to-S1 phase transition by interacting with cyclin D while phosphorylated Rb releases
E2F transcription factors and genes that are responsible for cell division (Mohamed et al., 2013).
GPR30, the membrane-bound ER, plays an important role in BC pathogenesis as it is expressed in about 50-60% of all BC. The mechanisms underlying GPR30 action in BC is through
EGFR, cAMP, and ERK pathways to modulate cell proliferation and migration. Evidence for this comes from studies in cells whereby knock-down of GPR30 in TNBC cells results in an inhibition
16 of cell proliferation and estrogen-mediated EGFR activation (Girgert et al., 2012). In ER-negative
BC cells, activation of GPR30 results in cAMP-mediated inhibition of EGFR/ERK (Filardo et al.,
2002). Finally, in inflammatory BC cells, GPR30 activation by GPR30-selective agonists increases migration and invasiveness through cyclin E, CXC receptor-1, and the notch pathway (Lappano et al., 2014).
GPR30 may be involved in tamoxifen resistance. For example, tamoxifen-resistant BC cells exhibit GPR30 upregulation due to estrogenic stimulation. A GPR30 agonist, G-15, improves tamoxifen sensitivity in tamoxifen-resistant MCF-7 cells possibly due to increases in GPR30 expression (Lappano et al., 2014). In a cohort study conducted in 103 patients, it was found that
GPR30 negatively correlates with relapse-free survival in tamoxifen-treated patients (Ignatov et al., 2011). However, studies demonstrate that GRP30 acts as a pro-apoptotic and tumor suppressor protein (Hsu et al., 2019). GPR30 mRNA expression is downregulated in both ER-positive and
ER-negative BC tissues compared to the normal tissues, suggesting a correlation between low
GPR30 and metastasis to the lymph node (Poola et al., 2008). These mixed effects of GPR30 action on BC may be due, in part, to the type of BC because in some BC cells (e.g., SKBR-3-HER2),
GPR30 stimulates cell growth while in others (e.g., MCF-7-ER+), GPR30 inhibits cell growth
(Ariazi et al., 2010).
17
Figure 3: Signaling pathways driving ERK activation, effectors, and cellular processes
regulated by this kinase. This schematic is taken from (Olea-Flores et al., 2019), licensed under
CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). MEK1/2 can be activated by B-RAF
RTKs, GPCRs, extracellular matrix, and Ca2+ ions. ERK1/2 can be phosphorylated by p-MEK1/2
and translocate to the nucleus, where it activates transcription factors such as Elk1, Ets1/2, and c-
Myc. ERK1/2 and/or MEK5 can phosphorylate ERK5. Translocated ERK5 activates transcription factors such as MEF2, Ets1/2, and c-Myc. ERKs-mediated gene transcriptions play a role in cell division, survival, differentiation, motility, and epithelial-mesenchymal transition.
18 1.4.3. Heterologous modulation of ERs and ER-mediated signaling
ErbB receptor. Erythroblastosis oncogene-B (ErbB) or human epidermal growth factor receptor
(HER) is a receptor family classified as receptor tyrosine kinase (Appert-Collin et al., 2015), The
ErbB family has four receptors: ErbB1 (EGFR/HER1), ErbB2 (HER2/Neu), ErbB3 (HER3), and
ErbB4 (HER4) (Appert-Collin et al., 2015). ErbB receptors can regulate cell proliferation,
migration, and differentiation (Appert-Collin et al., 2015). ErbB2 receptor has no known ligand
and so it dimerizes with other ErbB proteins for transactivation. It is overexpressed in almost 20%
of BC (Moreno-Layseca et al., 2017). ErbB2 can modulate ductal elongation and branching in
mammary epithelium and can induce cell proliferation (Moreno-Layseca et al., 2017).
A relationship exists between ERs (including GPR30) and ErbB where each can modulate
the other; this may occur through common intracellular signaling proteins like AKT and MAPK
or through direct modulation of receptor activity and/or levels. For example, in HER2
overexpressed cells, AKT and MAPK demonstrate reduced ER expression (Giuliano et al., 2013).
However, in ER+ BC, AKT and MAPK can phosphorylate ER and its coactivators to increase ER
activity; this has been proposed to be a potential mechanism underlying endocrine therapy
resistance in ER+ BC (Giuliano et al., 2013). Co-modulation between ERs and HER2 has also
been demonstrated in studies that result in altered receptor function; this may be due, in part, to phosphorylation processes. For example, heregulin, a HER2 agonist, can rapidly phosphorylate
ERs (Bender & Nahta, 2008) while GPR30 can activate HER2 (Giuliano et al., 2013). ER+ BC
cells that were originally sensitive to both estrogen and tamoxifen become resistant to each when
these cells are transfected (or overexpressed) with HER2 (Bender & Nahta, 2008). In tamoxifen-
resistant BC, increases in ERK1/2 and HER2 phosphorylation is observed (Bender & Nahta,
2008). These findings suggest that both HER2/ErbB2 and ER bidirectionally modulate one another
19 to impact their activity possibly through phosphorylation processes directed at the receptors and/or downstream signaling proteins.
Melatonin receptor. Melatonin, which is discussed in detail below, can inhibit ER signaling. This primarily occurs through inhibition of ER binding to EREs to decrease the transcriptional activity of ERα and/or coactivator phosphorylation. These actions of melatonin appear to be specific for
ERa as no effect was observed on ERb (Hill et al., 2015).
1.5. Melatonin receptors, physiology, pharmacology, and signaling
1.5.1. Melatonin’s role in physiological processes
Melatonin is an ancient molecule estimated to be billions of years old (Manchester et al.,
2015). It is hypothesized that melatonin evolved from purple-containing bacteria. Because primitive eukaryotes engulfed bacteria during the early phases of evolution, all species can synthesize melatonin in the mitochondria and/or chloroplast; it was during these early stages of evolution whereby melatonin primarily functioned as an antioxidant (D. Zhao et al., 2019).
In humans, melatonin synthesis occurs in the pineal gland, retina, gastrointestinal tract, skin, bone marrow, and lymphocytes (Hill et al., 2015). However, the pineal gland is the main organ that synthesizes melatonin in the absence of light perception (Maria & Witt-Enderby, 2014;
P. A. Witt-Enderby et al., 2006). In the classical pathway, melatonin is synthesized from tryptophan precursor (D. X. Tan et al., 2016b). Aromatic amino acid decarboxylase (AADC) converts 5-hydroxytryptophan into 5-hydroxytryptamine (serotonin). Serotonin then gets acetylated to N-acetylserotonin by arylalkylamine N-acetyltransferase (AANAT), which then is methylated to melatonin by N-acetylserotonin O-methyltransferase (ASMT) (D. X. Tan et al.,
2016b).
20 The rhythm and secretion of melatonin are under the control of an endogenous (near 24 hr) oscillator generated spontaneously through nuclei that reside in the suprachiasmatic nucleus (SCN) of the hypothalamus. The eyes, specifically melanopsin in retinal ganglion cells, which are cells distinct from rods and cones, can also regulate the SCN endogenous clock through the retinohypothalamic tract. Melanopsin has an absorption spectrum distinct from that of rods and cones with a wavelength of approximately 480nm (blue light range). So, although melatonin synthesis and secretion are generated by the endogenous clock, the eyes entrain these rhythms to the light/dark cycle (Lockley et al., 2007). For the most part, the physiological concentration of
melatonin in the body is regulated by the pineal gland’s response to light and the organ most
responsible for its metabolism—the liver (Kelleher et al., 2014).
Although melatonin modulates numerous physiological functions in the body through
myriad signaling cascades, the focus of this dissertation will be on its anti-BC actions and
associated signaling pathways.
1.5.2. Melatonin’s role in BC
Epidemiological evidence demonstrates that decreased melatonin levels due to aging, light
exposure at night, and shift work is associated with BC risk (David E. Blask et al., 2005b; S. Davis
et al., 2001; Grant et al., 2009; Schernhammer et al., 2001; P. A. Witt-Enderby et al., 2006). Also,
a lower level of melatonin induced by a 1 hr light exposure at night increases tumor growth in
rodents (David E. Blask et al., 2005b; S. Davis et al., 2001; Grant et al., 2009; Schernhammer et
al., 2001). Hence, the data suggest that decreased levels of melatonin due to aging and light
exposure at night are associated with increases in tumor growth.
21 1.5.2.1. Melatonin’s direct role in BC
The observation that levels of melatonin are higher in neoplastic breast tissues compared
to serum suggest that melatonin has a direct action on BC (P. A. Witt-Enderby et al., 2006). In
support of this, physiological concentrations of melatonin (1nM to 100nM) significantly inhibit
MCF-7 cell proliferation; the morphological characteristics of these cells also demonstrate reduced
surface microvilli, nuclear swelling, cytoplasmic and ribosomal shedding, and increased
autophagic vacuoles (Hill & Blask, 1988). Melatonin also reduces aromatase activity, the enzyme
responsible for estrogen production, and increases p53 and p21WAF21 expression in MCF-7 cells
(Cos et al., 2005; Mediavilla et al., 1999). In a variety of rodent models, melatonin supplementation or optimum nocturnal melatonin levels demonstrate BC protection (David E. Blask et al., 2005b;
Robert T. Dauchy et al., 2014b; V. Davis et al., 2011a; Grant et al., 2009; Hill et al., 2015).
1.5.2.2 Melatonin’s role as an adjuvant in BC
Melatonin can regulate apoptosis, angiogenesis, metabolism, and cell migration, and it
possesses antioxidant activity (Favero et al., 2018). However, because of its other unique
properties—free radical scavenger and anti-oxidant—melatonin has also been shown to be an
effective adjuvant to enhance the efficacy of cancer therapies as well as reduce the adverse effects
and toxicities associated with them (V. L. Davis et al., 2011b; Grant et al., 2009; P. Lissoni et al.,
1996; Sabzichi et al., 2016; P. A. Witt-Enderby et al., 2006). For example, a combination of
melatonin with anti-estrogen therapies (i.e., tamoxifen or anastrozole) improves the survival and
quality of life in metastatic BC patients (P. Lissoni et al., 1995; Paolo Lissoni et al., 2009; P.
Lissoni et al., 1996). Melatonin has also been shown to increase the efficacy of tamoxifen in
tamoxifen-unresponsive metastatic BC patients (P. Lissoni et al., 1995) while other studies suggest that tamoxifen can comodulate melatonin receptor activity in breast and ovarian cancer cells
22 enhancing melatonin’s anti-cancer actions (Treeck et al., 2006). These findings suggest that tamoxifen and melatonin can cross-modulate ERs and MTRs, respectively, to enhance tamoxifen’s actions at ERs and melatonin’s action at MTRs.
This benefit of melatonin on tamoxifen resistance also extends to tamoxifen-resistant models in rodents and cells. For example, melatonin increases the efficacy of tamoxifen in MCF-
7 cells (Sabzichi et al., 2016). Moreover, melatonin can reverse tamoxifen resistance due to light exposure at night and depletion of nocturnal melatonin levels (D. E. Blask et al., 2005a; R. T.
Dauchy et al., 2014a; Grant et al., 2009). The mechanisms underlying this reversal in tamoxifen resistance may be through the downregulation of ERK1/2, AKT, SRC, NF-κB, STAT3, and
CREB, which can mediate tamoxifen resistance in BC (R. T. Dauchy et al., 2014a). Melatonin can suppress estrogen-mediated ERα transcriptional activity through Gαi protein (Hill et al., 2009).
1.5.3. Melatonin receptor-dependent and -independent actions, associated signaling cascades
and their role in BC
1.5.3.1. Melatonin’s receptor-independent and anti-cancer actions
Melatonin can work as a paracoid, autocoid, antioxidant, and free radical scavenger in a
receptor-independent manner (Reiter et al., 2007). Melatonin’s lipophilic properties enable it to
cross the plasma membrane to reach cytosolic, mitochondrial, and nuclear proteins (Hill et al.,
2015). Melatonin can decrease adenylyl cyclase (AC) activity and cAMP production by binding
with calmodulin directly, which can enhance cellular differentiation and suppress cell proliferation
(Hill et al., 2015; P. A. Witt-Enderby et al., 2006). Furthermore, antioxidant enzymes such as
superoxide dismutase, glutathione peroxidase, and glutathione reductase can be activated by
melatonin, which can reduce free hydroxy radical formation (Reiter et al., 2007). Melatonin can
also detoxify free radicals directly by donating one or more electrons and while detoxifying
23 melatonin produces metabolites that are equally or better free radical scavengers compared to the
melatonin (Reiter et al., 2007). In vitro, melatonin synergizes with vitamins C and E to enhance
their activity (Reiter et al., 2007). In terms of potency to inhibit lipid peroxidation, melatonin,
vitamin C, vitamin E, and glutathione demonstrate IC50 values of 426, 4325, 4, and 2290 µM,
respectively (Gitto et al., 2001). However, melatonin exhibits better efficacy in inhibiting free-
radical–based molecular destruction compared to vitamin C, vitamin E, and β-carotene (Korkmaz
et al., 2009).
1.5.3.2. Melatonin, melatonin receptors, and their anti-cancer actions
Regarding its receptors, three subtypes of melatonin receptors exist initially named Mel1a,
Mel1b, and Mel1c. However, based on IUPHAR nomenclature, these receptors were renamed from Mel1a and Mel1b to MT1R and MT2R, respectively, because of their expression in
mammalian cells (Dufourny et al., 2008). Mel1c is found only in Xenopus species and chicken
(Dufourny et al., 2008). GPR50, an orphan receptor found only in eutherial mammals, is considered an ortholog of Mel1c which heterodimerizes with MT1R and MT2R, has been
demonstrated to modulate MT1R affinity for melatonin (Dufourny et al., 2008). All three subtypes,
except for GPR50 where no binding was observed, have a high affinity (MT1R, Kd=0.1 nM;
MT2R, Kd=0.1 nM; Mel1c, Ki=1 nM) for endogenous melatonin (Clement et al., 2017; Liu et al.,
2019). A detailed mechanism of melatonin’s action is described in Figure 4. The human melatonin
receptors, MT1 and MT2, are G-protein coupled receptors located at the plasma membrane and for the MT1 receptor, also in the mitochondria (Cecon et al., 2018; Suofu et al., 2017). The
mitochondrial MT1 receptor can inhibit stress-mediated cytochrome c release and caspase
activation to provide neuroprotection in the brain (Suofu et al., 2017).
24 Melatonin, through activation of melatonin receptors, MT1 and MT2, can exhibit anti-
cancer activity through several mechanisms. Melatonin receptors through Gαi/o proteins inhibit adenylyl cyclase and cAMP, which reduces linoleic acid uptake (Molina et al., 2017). Melatonin decreases telomerase activity in MCF-7 xenografts of nude mice, which is essential for telomere elongation (Leon-Blanco et al., 2003). Melatonin can down-regulate angiogenesis-associated genes such as EPAS1, NDRG1, and EFNA1 to prevent tumor metastasis through MT1R (Hill et al., 2015). Melatonin through MT1 melatonin receptors suppresses transactivation of other nuclear
receptors such ER, glucocorticoid receptor, RORα in BC cells and can potentiate the
transactivation of RARα, RXRα, vitamin D receptor, and PPARγ (Hill et al., 2015). Melatonin
activity on ER has already been described in section 1.4.3. Few studies suggested that melatonin
can also bind to the retinoid orphan nuclear receptors (Cos et al., 2005).
Recently, melatonin receptors have been identified in the mitochondria. The mitochondria
are important cellular organelles because of their importance in energy (ATP) production. The
- mitochondria can produce free radicals such as superoxide anion (O2ꞏ ) during ATP production
via the electron transport system, whereas, excessive production of free radicals may cause
oxidative stress and cell death (D.-X. Tan et al., 2016a). Excessive free radicals can induce
hydrogen peroxide production and/or cellular death (D.-X. Tan et al., 2016a).
Besides expressing melatonin receptors, the mitochondria also contain high concentrations of melatonin against the concentration gradient (D.-X. Tan et al., 2016a). This finding and that
AANAT, one of the enzymes involved in melatonin synthesis, and melatonin metabolites are found in the mitochondria indicate that the mitochondria may be able to synthesize and metabolize melatonin (D.-X. Tan et al., 2016a). Melatonin is a potent free radical scavenger and
25 mitochondrial-targeted antioxidant (D.-X. Tan et al., 2016a) and so its presence in the
mitochondria is not unexpected. Suofu et al. showed that the mitochondria can synthesize
melatonin and that mitochondrial MT1R can inhibit cytochrome c release and caspase activation through GPCR signaling (Suofu et al., 2017). Melatonin can stimulate complex I and complex IV
of the electron transport system to improve mitochondrial respiration, which can trigger
mitochondrial transition pore and apoptosis (Leon et al., 2005). Melatonin accumulation
transported by peptide transporter 1/2 has been shown to induce mitochondrial apoptosis in
prostate cancer (PC3) and glioblastoma (U118) cells (Huo et al., 2017). Melatonin can stimulate mitochondrial differentiation and mitochondrial apoptosis through modulation of the
mitochondrial respiratory chain that may enhance drug-induced apoptosis (Proietti et al., 2017).
Figure 4: Mechanism of melatonin’s anti-breast cancer action. This schematic is taken from
(Sardo et al., 2017), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), and
26 further modified (all modifications are expressed in red texts or arrows). Melatonin can work
through MT1R, MT2R (MT1/2), or receptor-independently. Activated MT1R can activate Gαi, which can inhibit several signaling cascades such as Ras, ERK1/2, AKT, PKCα, and AC/cAMP.
Downstream of those signaling cascades modulates receptors (i.e., RXRα and ERα) and transcription factors (i.e., Myc and NF-κB), which are responsible for cell proliferation, cell survival, and metastasis.
1.6. Mechanism of drug resistance and treatment
Almost half of the cancer patients develop drug resistance during their lifetime (X. Wang
et al., 2019). Cancer drug resistance can be classified into two broad categories, intrinsic and
acquired resistance (X. Wang et al., 2019). Intrinsically-resistant patients show resistance to
certain drug(s) before therapy, whereas, in the latter, the patient acquires the resistance against a
drug after the treatment with that drug (X. Wang et al., 2019). Genetic modification helps BC cells
to evade therapeutic action (Gonzalez-Angulo et al., 2007). Several mechanisms such as tumor
mutation, upregulation of receptor activity, constitutive activation of the receptor, downregulation
of the receptor, receptor internalization, increased efflux can play role in drug resistance
(Gonzalez-Angulo et al., 2007). For example, multidrug resistance can occur through modulation
of P-glycoproteins (Gonzalez-Angulo et al., 2007). Several multidrug resistance proteins such as
MRP1, MRP2, and MRP3 can cause efflux detoxification of cancer drugs (Gonzalez-Angulo et
al., 2007). BC cells can also express free radical scavenging enzymes to neutralize drugs, which
work by forming free radicals (Sinha, 1989). Furthermore, BC cells can regulate apoptotic
pathways such as MAPK, PI3K, p53 to evade cellular death signals (Gonzalez-Angulo et al.,
2007).
27 1.6.1. Anti-HER2 resistance. Several mechanisms have been proposed for trastuzumab resistance
in HER2+ BC patients. For example, a lack of an extracellular domain in the receptor or steric
hindrance in receptor binding can cause trastuzumab resistance (Mohamed et al., 2013). Other
mechanisms include crosstalk with IGF-R1, activation of other HER receptors, PTEN deficiency,
AKT mutation, and Rac1 upregulation (Mohamed et al., 2013). Lapatinib added with trastuzumab appears to be effective in trastuzumab-resistant patients. In a phase 3 trial, lapatinib and trastuzumab combination demonstrate improved progression-free survival with a 26% reduction
in risk of death (Blackwell et al., 2010).
1.6.2. Immune resistance. Interferons play a great role in cancer immune resistance. Three main
types of interferons (IFN-α and IFN-β, IFN-γ, and IFN-λ) can activate JAKs and STATs through their respective receptors (Abril-Rodriguez & Ribas, 2017). Activation of STAT1 and STAT3 can induce PD-L1 expression and induce adaptive immune resistance (Abril-Rodriguez & Ribas,
2017). Furthermore, tumors can acquire resistance through mutation of epigenetic modulation of the IFN- γ pathway. Loss of IFN- γ pathway sensitivity can lead to the reduction of IRF-1
(Interferon Regulatory Factor 1) expression, apoptosis, and/or chemokines (Abril-Rodriguez &
Ribas, 2017). Some BC exhibit de novo or acquired resistance against some antibodies (Mohamed
et al., 2013). Many BC either is resistant or become resistant to drug therapies, which is thought
to occur, in part, through de novo resistance, acquired resistance, or through immune escape. For
example, many BCs keep T cell infiltration low as a defense mechanism termed as
“immunologically cold” proposed to occur through an immunosuppressive response of nascent T
cell response (Vonderheide et al., 2017). If this is the case, then only drugs targeted to release the
immunosuppression, for example, drugs targeted to immunosuppressive pathways such as IDO,
CD73, TIGIT, VISTA may be most effective in killing BC using this defense pathway.
28 (Vonderheide et al., 2017). Also, some oncogenic genes can alter chemokine production or increase PD-L1 production to induce immunosuppression (Vonderheide et al., 2017) and so understanding, specifically, the molecular mechanisms that govern the BC’s actions in the body is critical for effective drug therapy response in the host.
1.6.3. Antibody Drug Conjugate resistance. Tumors can become resistant against the antibody portion of the antibody drug conjugate (ADC) (Collins et al., 2019). Downregulation of target antigen or upregulation of efflux transporter could be the possible mechanism (Collins et al., 2019).
For example, tumors can become resistant against trastuzumab-emtansine drug conjugate by
HER2 downregulation, increasing efflux transporter, STAT3 activation, PTEN/PI3K activation,
and/or altered internalization (Collins et al., 2019).
1.6.4. Tamoxifen resistance: Estrogen receptors can undergo a variety of compensatory and
modulatory events that can impact tamoxifen’s actions against ERs (Ring & Dowsett, 2004). These
changes can impact how ERs signal especially through its interactions with other proteins like
IGFR, HER2, and EGFR and their downstream signaling proteins like MAPKs. For example, ERα
can activate IGFR and its downstream ERK1/2 pathway (Kahlert et al., 2000). However, increases
in ERK activity can induce endocrine resistance through ERK1/2-mediated phosphorylation of ER
(Ring & Dowsett, 2004). Moreover, tamoxifen-resistant MCF-7 cells exhibit reduced ERK5 and pERK5 nuclear localization compared to the tamoxifen-sensitive MCF-7 cells (Wrobel et al.,
2016). HER2-transfected MCF-7 cells became tamoxifen-resistant probably through MAPK and by reducing co-repressors such as NCoR, SMRT (Kurokawa & Arteaga, 2001; Pietras et al., 1995).
Loss of ER expression is the dominant mechanism of tamoxifen resistance (Ring &
Dowsett, 2004). HDAC inhibitors prevent ER stabilization and transcribe pro-apoptotic genes and
29 thus apoptosis (Munster et al., 2011). In a phase 2 clinical trial, a combination of the HDAC
inhibitor (vorinostat) and tamoxifen exhibit promising activity in reversing hormone resistance
(Mohamed et al., 2013). S6 kinase 1 mTOR substrate induces ligand-independent ER activation
by phosphorylating the activation function domain, which may cause anti-estrogen therapy
resistance (Baselga et al., 2012).
Modulation of co-activators and co-repressors responsible for ER signaling is another way to induce tamoxifen resistance. Tamoxifen resistance is shown to occur, in part, through attenuation of co-repressor recruitment (e.g., NCoR and SMRT) (Ali et al., 2016; Wong et al.,
2014). AIB1 (Amplified In Breast Cancer 1) co-activator expression is inversely related to disease- free survival in tamoxifen-treated patients (C. Kent Osborne et al., 2003). Experiments show that
SRC-1 overexpression increases the transcription of estrogen-stimulated target genes and 4- hydroxytamoxifen agonism (Smith et al., 1997; Tzukerman et al., 1994). By contrast, the NCoR co-repressor exhibits low expression in tamoxifen-resistant tumors compared to the tamoxifen- sensitive tumors in MCF-7 PDX mice (Ring & Dowsett, 2004).
Increases in tamoxifen efflux or metabolism are other potential mechanisms for acquired resistance to tamoxifen. Significantly lower intra-tumor tamoxifen concentration is observed in acquired resistance patients, whereas the phenomenon is absent in de novo resistant patients (Ring
& Dowsett, 2004). Women with the CYP2D6 allele variant have low plasma concentration of tamoxifen metabolites (Stearns et al., 2003), which indicates that increased metabolism of tamoxifen to ER-activating metabolites could induce resistance in BC patients (C. K. Osborne et al., 1991).
30 Drug therapies have also demonstrated efficacy to overcome tamoxifen resistance. For
example, treatment with a selective CDK4/6 inhibitor (PD0332991) in TamR MCF-7 cells
increases tamoxifen sensitivity and overcomes tamoxifen resistance (Finn et al., 2009). Also, in an
MCF-7 tumor xenograft model, melatonin given during the hours of darkness is shown to reverse
the tamoxifen resistance induced by light exposure at night (R. T. Dauchy et al., 2014a). A similar
study demonstrates that circadian disruption at night (which reduces nocturnal melatonin levels)
causes doxorubicin insensitivity in an MCF-7-PDX tumor, where replenishment with melatonin
reestablishes the tumor’s sensitivity to doxorubicin (Xiang et al., 2015).
1.7. Rationale for the development of drug conjugates for the treatment of BC
The average cost to market for a new drug is approximately $2.5 billion (Hasan et al., 2018).
Nonspecific target action and poor bioavailability are often the reasons for the failure of clinical
trials in drug development (Hasan et al., 2018). Some adverse effects of anti-breast cancer drugs include toxicity related to bone marrow, gastrointestinal tract, nervous system, liver, urinary tract, heart, and lungs (Hasan et al., 2018). Moreover, breast cancer can easily develop resistance by dysregulating the balance of prosurvival and proapoptotic genes through mutations described previously (Hasan et al., 2018). Drug conjugates can be an alternative to single or combination therapy. It could be another viable option to treat breast cancer effectively. Drug conjugates are a hybrid of multiple molecules linked together either cleavable or non-cleavable linkers (Hasan et al., 2018). Cleavable linkers are usually stable in the circulation and break down when the conjugates become internalized inside the cancer cells (Hasan et al., 2018). The cleaving of the linker depends on the structure and target site. Chemically cleavable linkers break down under certain biochemical environment. For example, a hydrazine linker breaks down in the tumor acidic
31 environment (Ducry & Stump, 2010). Enzymatically cleavable linkers release the drugs in the
presence of certain enzymes. For example, the valine-citrulline linker is degraded by cathepsin B enzyme and tends to be more stable than a hydrazine linker (Doronina et al., 2003). Drug conjugates can be designed to achieve the following actions (one or more) (Hasan et al., 2018):
1. Target selectivity
2. Reduce the bystander effect
3. Increase cytotoxicity
4. Increase potency
5. Overcome drug resistance
1.7.1. Types of drug conjugates
At present, one antibody drug conjugate (Kadcyla®) and one nanoparticle-based drug
conjugate (Abraxane®) has been approved for advanced metastatic breast cancer patients (Hasan
et al., 2018). Several drug conjugates have been under investigation using different models such
as in vitro, in-vivo, and clinical.
1.7.1.1. Antibody-drug conjugates (ADCs)
Most ADCs are conjugates of an antibody and a cytotoxic drug (Hasan et al., 2018).
MylotargTM (gemtuzumab ozogamicin) was approved by the FDA in 2001 for acute myeloid
leukemia. The trastuzumab-emtansine drug conjugate (Kadcyla®) has been approved for HER2-
positive metastatic BC, which demonstrates improved survival rate compared to the lapatinib plus
capecitabine (Hasan et al., 2018). ADCs are usually stable in the circulation and break down at the
target site (Rinnerthaler et al., 2019). ADCs can also show a bystander effect due to the antibody
(Rinnerthaler et al., 2019). However, ADCs can also become resistant against BC which has been
discussed in section 1.5.
32 1.7.1.2. Radionuclide conjugates
A targeted drug delivery system is used to deliver a cytotoxic radionuclide to the tumor.
The chelation method can be used to conjugate a radionuclide to a monoclonal antibody (Hasan et
al., 2018). For example, 89Zr-trastuzumab-monomethyl auristatin E immunoconjugate demonstrates more than 90% tumor volume reduction after 20 days of treatment in a HER2- positive murine model (Adumeau et al., 2018).
1.7.1.3. Drug-delivery system conjugates
Similar to radionuclide conjugates, a drug delivery system can be used to deliver cytotoxic drugs to the tumor. The drug delivery system is selected based on the status of the target tissue.
For example, the FDA approved Abraxane (Paclitaxel conjugated with albumin-bound nanoparticles) can be categorized into this group (Hasan et al., 2018).
1.7.1.4. Drug-drug conjugates
Several drug-drug conjugates are being tested in BC cells and patient-derived xenograft
(PDX) models (Hasan et al., 2018). Multiple drugs can be used to make conjugates. For example, platinum-, acridine-, endoxifen-containing drug conjugates exhibit higher toxicity compared to a cisplatin and tamoxifen combination therapy (Ding et al., 2013).
1.7.2. Pharmacology of drug conjugates
Two or more drug moieties can be linked with a cleavable or non-cleavable linker. The pharmacological property of a drug conjugate depends on both drug moieties and linkers. Drug conjugates can demonstrate higher potency or cytotoxicity compared to the individual component.
For example, ribociclib-vorinostat conjugate exhibit higher potency (IC50 = 1.86 µmol/L)
compared to vorinostat (IC50 = 2.56 µmol/L) and ribociclib (IC50 > 10 µmol/L) in MDA-MB-231
33 TNBC cell line (Li et al., 2018). Moreover, tamoxifen-vorinostat conjugates exhibit higher toxicity
in MCF-7 and MDA-MB-231 compared to the tamoxifen or vorinostat alone (Gryder et al., 2013).
1.7.3. Pharmacokinetics of drug conjugates
Pharmacokinetic data can help in understanding the deconjugation process, as well as the
metabolism of the conjugate. Pharmacokinetic parameters (i.e. clearance, half-life, and
distribution) of ADCs depend on the drug components and/or linkers (Kamath & Iyer, 2015).
Clearance may depend on the stability of the linkers. For example, the disulfide linker
demonstrates faster clearance compared to the nonreducible MCC linker in female beige nude
mice (Lewis Phillips et al., 2008). A drug conjugate can alter the half-life and tumor tissue
distribution. For example, paclitaxel linked with poly-L-glutamic acid demonstrates a half-life of
100 hours and a low volume of distribution (Bumbaca et al., 2019). Abraxane® (albumin-bound
paclitaxel nanoparticle) exhibits higher paclitaxel plasma concentration compared to the solvent-
based paclitaxel (Bumbaca et al., 2019).
1.7.4. Models for drug conjugates studies
Choosing the right model for studying drug conjugates depends on several factors like the
types of conjugate being assessed, the conjugate’s target, and the expected outcomes. Therefore,
it is critical to choose the appropriate model for analysis, which may be through the use of in vitro
cell culture models, in vivo rodent models and, if possible, clinical models. For this dissertation,
in vitro breast cancer cell models were chosen because all, except for the mouse mammary carcinoma cells (MMCs), were derived from human tumors. A brief discussion on different BC models is described below. A more detailed description of the cell models used in this study can
be found under Section 2.1.
34 1.7.4.1. In vitro
Due to the complexity and heterogeneity of BC, several BC cell lines have been developed for drug development research. One way to classify the cell lines is based on receptor expression.
The ER+/PR+ cell line, MCF-7, is the most widely used BC cell line to study endocrine or anti-
estrogen therapy (Holliday & Speirs, 2011). MCF-7 cells were derived from the pleural effusion
of a metastatic BC patient (Levenson & Jordan, 1997). The mouse mammary carcinoma (MMC)
cell line (ER–/PR–/HER2+) was obtained from a spontaneous tumor harvested from the neu-
transgenic mice. It is similar to human BC in that its hormonal profile mimics that of
premenopausal BC in humans (Dodda et al., 2019). TNBC cell lines although devoid of ER, PR,
and HER2 receptors are not the same but, rather, heterogeneous in nature (Foulkes et al., 2010).
TNBCs can arise due to different mutations (i.e., BRCA, PTEN, and p53) or different levels of
receptor expression (i.e., TGF and EGFR) (Foulkes et al., 2010). This is important to know
especially when deducing the molecular mechanisms underlying novel BC drugs like the
melatonin-tamoxifen drug conjugates described in this dissertation. Some widely used TNBC cell
lines include: MDA-MB-231, MDA-MB-468, BT-20, and BT-549 (Chavez et al., 2010).
1.7.4.2. In vivo
In vivo or preclinical models are vital to drug development because of the ethical
considerations for testing candidate drugs in humans. Animal testing can give information about
the efficacy, toxicity, and pharmacokinetic profiles of candidate drugs (Mak et al., 2014). Also,
the FDA mandates the completion of a preclinical trial for a new drug molecule before it can move
into the clinical phase (Mak et al., 2014). Since there are different ways to study the anti-cancer
actions of drugs using animal models, the first concern is to determine the suitability of the in vivo
model.
35 1. Xenograft: These models are popular in that they are tumors or cells obtained from
BC patients or commercially purchased. These tumors or cells are implanted in
animals (mostly rodents) either orthotopically or in different organs other than the
mammary tissue. Patient-derived xenograft (PDX) models are a suitable model to
study tumor heterogeneity since the patient’s characteristics can be maintained in the
tumor (Whittle et al., 2015). However, one limitation to using this type of model is
that the animal needs to be immunocompromised to prevent tumor rejection, which
does not mimic the patient’s immune system (Whittle et al., 2015).
2. Carcinogen induced: In this model, radiation or chemicals (i.e. 7,12-
dimethylbenz[a]-anthracene, methylcholanthrene, and urethane) are used to induce
BC in rodents (Imaoka et al., 2009). This type of model is not as widely used since
most human cancer occurs from spontaneous mutations.
3. Genetically- induced: Transposon based, transgenic, knock-in, knockout, and
inducible mutation animals have been widely used for genetic research and to induce
BC (Swiatnicki & Andrechek, 2019). There are about 100 oncogenes that have been
targeted to induce carcinogenesis (Allred & Medina, 2008). Overexpression of
oncogenes such as c-myc, ras, and HER2 can induce mammary cell proliferation and
form tumors (Swiatnicki & Andrechek, 2019). These types of models are commonly
used in BC research.
36 Chapter 2: Research Objectives
2.1. Rationale
Drug conjugates show promise as novel anti-cancer agents as reviewed (Hasan et al.,
2018). It is thought that the conjugated form of multiple drugs may exhibit beneficial effects based on diverse targets such as receptors or intracellular signaling proteins (Hasan et al., 2018). In keeping with this idea, melatonin-tamoxifen drug conjugates were developed with varying CH2- spacer lengths as novel BC drugs since both melatonin and tamoxifen alone or in combination but unlinked are effective anti-cancer agents (Hasan et al., 2018). A melatonin-tamoxifen drug conjugate with a spacer length of five CH2-groups (C5) was reported as a promising new class of drugs for the prevention and treatment of BC without uterotropic effects (P.A. Witt-Enderby et al.,
2014), US Patent 8,785,501). To further assess the influence of this class of drugs, melatonin-
tamoxifen drug conjugates with varying spacer lengths were synthesized and consist of C2
(contains two CH2 spacer groups; shortest spacer), C4 (contains four CH2 spacer groups), C5
(contains five CH2 spacer groups), C9 (contains nine CH2 spacer groups) and C15 (contains fifteen
CH2 spacer groups; longest spacers) (Figure 5). In this study, these five melatonin and tamoxifen drug conjugates (C2, C4, C5, C9, and C15) were tested against BC cells that are ER-positive
(MCF-7), ER-positive but tamoxifen-resistant MCF-7 (TamR MCF-7), HER2 positive (MMC), triple-negative (MDA-MB-231 and BT-549), and patient-derived xenograft cells and tissue. These cell lines and models were chosen because melatonin, tamoxifen, and melatonin plus tamoxifen have demonstrated anti-cancer actions against these types of breast cancers (Hasan et al., 2019).
The MCF-7 cell line was derived from a metastatic pleural effusion from a 69-year old
Caucasian female with an adenoma of the breast classified as epithelial and adherent.
37 The MMC (ER-/PR-/HER2+) cell line was derived from the breast tumor tissue of Neu mice expressing Neu proto-oncogene. Neu-transgenic mice [strain name, FVB/N-TgN
(MMTVneu)-202Mul] were obtained from Charles River Laboratory (Bar Harbor, ME). These mice harbor a nonmutated, nonactivated rat neu under the control of the mouse mammary tumor virus (MMTV) promoter. This model is parallel to human HER2/neu-overexpressing cancer in a number of ways. First, the expression of neu under the mouse mammary tumor virus promoter results in an amplified expression in the breast epithelium. This is analogous to gene amplification in humans that results in overexpression of the nonmutated HER-2/neu with a significant proportion of cases expressing medium to high levels of the protein.
Based on our proposed mechanism of action, we have selected two TNBC cell lines expressing different mutations. The MDA-MB-231 cell line was derived from the metastatic pleural effusion of a 51-year old Caucasian female with an adenocarcinoma of the breast, classified as basal B/claudin-low (Chavez et al., 2010). It contains a p53 mutation, KRAS mutation, and wild type BRCA 1 (Chavez et al., 2010). These cells are epithelial, adherent, and display a triple- negative hormonal profile. Capable of forming tumors in both nude and ALS-treated BALB/c mice, the MDA-MB-231 cells are hypotriploid with a modal chromosome number of 65. The BT-
549 cell line was derived from a metastatic primary tumor of a 72-year old Caucasian female classified as basal B/claudin-low (Chavez et al., 2010). It contains PTEN homo deletion, p53 mutation, and wild type BRCA1 (Chavez et al., 2010). These cells are triple-negative, polymorphic, adherent, and epithelial in nature. BT-549 cells are multinucleated giant cells with a modal number of 78.
C4 and C5 were also tested in patient-derived xenograft cells and tumors. PDX cells and
PDX mice tissues were derived from chemo-naive and chemoresistant triple-negative BC patients.
38 TU-BcX-4IC cells, which were chemonaive, were derived from a mastectomy specimen of a
Caucasian female. The TU-BcX-4IC tumor was a metaplastic breast carcinoma that had a TNBC
PAM50 subtype. TU-BcX-4QAN PDX tumor was established from a mastectomy specimen of an
African American woman and represents a drug-resistant TNBC tumor. The PDX tumor was propagated and maintained in SCID/Beige immunodeficient mice (CB17.cg-PrkdcscidLystbg/Crl)
obtained from Charles River (Wilmington, MA, USA).
MEK1/2, MEK5, and PI3K were chosen due to their role in BC pathogenesis and
MT1R/ESR1-mediated BC signaling (Driggers & Segars, 2002; Lobenhofer et al., 2000). Estrogen,
through ERs, can produce MCF-7 cell mitogenesis via MAPK and PI3K (Driggers & Segars, 2002;
Lobenhofer et al., 2000). Melatonin works through MEK1/2 to promote differentiation processes
that may be protective against BC (Radio et al., 2006; Sethi et al., 2010a). Mutations in the
PI3K/Akt signaling pathway correlate with ER+ or ER+/PR+ BC where ~30% of ER+ BC patients
have the PI3KCA mutation while the AKT1 mutation was found exclusively in ER+/PR+ BC
(Araki & Miyoshi, 2018). Also, melatonin has been shown to inhibit cell survival, proliferation by suppressing phosphorylation of the PI3K/Akt pathway (J. Wang et al., 2012).
2.2. Hypothesis
Melatonin-tamoxifen drug conjugates will exhibit anti-cancer effects (reduced cell
viability and migration) in phenotypically diverse BC by modulating MEK1/2, MEK5, or PI3
kinases.
39 2.3. Specific Aims
The study was designed to test all melatonin-tamoxifen drug conjugates (C2, C4, C5, C9, C15) on MCF-7, MMC, MDA-MB-231, BT-549 BC cell lines in terms of cell viability, cell migration,
and binding affinities to ERs and MT1Rs. Based on the outcomes, two drug conjugates were
selected for further evaluation in TamR MCF-7 cells and patient-derived xenograft cells (chemo-
naïve) and tumors (chemo-resistant). Next, different pharmacokinetic parameters (i.e., clearance,
half-life, and bioavailability) were assessed using the female mice model. The research was
conducted based on the following specific aims:
i. To assess the anti-cancer actions (inhibition of cell viability and cell migration) of
melatonin-tamoxifen drug conjugates (C2, C4, C5, C9, C15) on MCF-7, MMC, MDA-
MB-231, and BT-549 cell lines.
ii. To assess the binding affinities of melatonin-tamoxifen drug conjugates (C2, C4, C5, C9,
C15) to ERs and MT1Rs.
iii. To assess the role of melatonin-tamoxifen drug conjugates (C4, C5) on TamR MCF-7
cells and in patient-derived TNBC (chemonaive or chemoresistant) xenografts.
iv. To assess the role of MEK1/2, MEK5, and PI3 kinases in mediating C4 and C5
melatonin-tamoxifen drug conjugates’ anti-cancer actions (i.e., viability and migration)
in MCF-7, MMC and TNBC cells.
v. To assess the effect of C4 and C5 melatonin-tamoxifen drug conjugates on pERK5,
pERK1/2, pAKT, NF-κB, RUNX2, and β1-INTEGRIN protein levels.
vi. To assess the metabolism of C4 and C5 melatonin-tamoxifen drug conjugates both in
vitro and in vivo.
40 Chapter 3: Materials and Methods
3.1. Synthesis of melatonin-tamoxifen drug conjugates
All of the synthesis studies were conducted by Dr. Zlotos and his research lab. For a
complete description and analysis of these compounds, please refer to (Hasan et al. Mol Pharm
Paper). (Hasan et al., 2018). In brief, melatonin-tamoxifen drug conjugates were developed with
varying CH2-spacer lengths: C2, which contains two CH2 spacer groups, is the shortest spacer; C4
contains four CH2 spacer groups; C5 contains five CH2 spacer groups; C9 contains nine CH2 spacer groups; and C15, contains fifteen CH2 spacer groups, contains the longest spacer (Figure 5).
H C O MeO C(CH )n O 3 N 2 2 N H 1. NaH, DMF CH3
CH3 CH3 2. MeO2C(CH2)nBr
N-desmethyltamoxifen
1. LiOH, THF, H2O 2. HCl n = 2, 4, 5, 9, 15 3. EDCI HCl, CH2Cl2 4. NH MeO 2
N H O N MeO H (CH2)n O N N CH H 3
CH3 n
C2 2 C4 4 C5 5 C9 9 C15 15
Figure 5: Synthesis of the melatonin-tamoxifen drug conjugates (C2, C4, C5, C9, and C15).
41 3.2. Competition binding for melatonin and estrogen receptors
Binding affinities of each of the drug conjugates (C2, C4, C5, C9, and C15) or melatonin,
tamoxifen, 4-OH-tamoxifen alone were measured using 2-[125I]-iodomelatonin, [125I]-estradiol and
[3H]-estradiol respectively, as described previously with modification (Kirker et al., 2013; P. A.
Witt-Enderby & Dubocovich, 1996). In brief, the experiments were conducted on mouse uterus
((P.A. Witt-Enderby et al., 2014); US Patent 8,785,501) and in whole-cell lysates prepared from
human MT1 CHO cells or MCF-7 breast cancer cells grown to confluence on 10cm plates. Cell lysates were prepared by first washing cells with 5 mL of PBS and then lifting them into the buffer
(10 mM KPO4, 1 mM EDTA, pH 7.4). Cells were then pelleted by centrifugation (277 x g for 5
min) and then resuspended in Tris-HCl buffer (50 mM, pH 7.4). Next, cells were added to tubes
containing 115 pM of 2-[125I]-iodomelatonin (Perkin-Elmer, 2200 Ci/mmole) in the presence of
melatonin (1 pM-100 µM) or drug conjugate (1 pM-100 µM) or the absence of melatonin or drug
conjugated (total binding). For 4-OH-tamoxifen or drug conjugate binding in MCF-7 cells, 2 nM
of [3H]-estradiol was used in the presence of 4-OH-tamoxifen (1 pM-100 µM) or drug conjugate
(1 pM-100 µM). The incubation volume was 260 µL. Next, cells were incubated for one hr at room
temperature and then terminated by the addition of ice-cold 50 mM Tris-HCl solution and rapid
filtration over glass-fiber filters (0.22 μm; Schleicher & Schuell, Keene, NH) presoaked in 0.5%
polyethyleneimine solution (v/v) (Sigma Aldrich, St. Louis, MO). Each filter was washed twice
with 5 mL of cold buffer. Radioactivity of [125I]-iodomelatonin and [3H]-estradiol were determined
in a gamma counter and scintillation counter respectively.
42 3.3. Total binding assay
G-protein coupled estrogen receptor (GPR30) total binding to C4 and C5 in MCF-7 cells was assessed using [3H]-estradiol as described with modification (Kirker et al., 2013) on MCF-7 cell lysates. Briefly, 200 μL of cell lysate was added to tubes containing 3 nM of [3H]-estradiol
(Perkin Elmer, Waltham, MA, USA) in the absence (total binding) or presence of 10 μM 4-OH- tamoxifen, 1 μM C4, 1 μM C5 and/or 1 μM G1 GPR30 agonist (Cayman Chemical Company, Ann
Arbor, MI). The whole incubation volume was 260 µL. Binding data, initially expressed as moles/mg protein, were repeated three times and subjected to one-way ANOVA.
3.4. Cell culture
MCF-7, MMC, MDA-MB-231, and BT-549 cells were obtained from American Type
Culture Collection (ATCC, Manassas, VA), were cultured in DMEM:F12 containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin at 37° C in a humidified atmosphere with 5%
CO2. BT-549 cells were cultured in the same condition (10% FBS and 1% penicillin/streptomycin at 37° C in a humidified atmosphere with 5% CO2) using RPMI-1640 medium.
3.5. Development and characterization of TamR MCF-7 cells
The characterization of TamR MCF-7 cells is described in Figure 12. In brief, MCF-7 cells, obtained from ATCC, were cultured at 37° C in a humidified atmosphere with 5% CO2 for 6 months in DMEM (phenol red-free):F-12 containing 10% charcoal-stripped FBS and 1% penicillin/streptomycin and 100 nM 4-OH-tamoxifen; 6 mo was the amount of time required for
MCF-7 cells to become resistant to tamoxifen. For growth assays, WT (wild type) and TamR
MCF-7 cells were counted using trypan blue exclusion assay following exposure to 100 nM 4-
43 OH-tamoxifen for 1-7 days. For immunocytochemistry images, MCF-7 and TamR cells were
treated with either vehicle or 100 nM 4-Hydroxytamoxifen for 24 hr. After treatment, cells were
fixed in 4% Paraformaldehyde for 15 min. Cells were then permeabilized with 0.3% Triton-X
followed by the addition of rabbit Ki-67 (1:1000, CAT# 9129S, Cell Signaling Technology,
Danvers, MA) and mouse ∝-Tubulin (1:1000, CAT# 3873S, Cell Signaling Technology, Danvers,
MA) primary antibodies. Goat anti-mouse Alexa Fluor 488 nm (1:1000, CAT# A-11001, Life
Technologies, Carlsbad, CA) and goat anti-Rabbit Alexa Fluor 555 nm (1:1000, CAT# A-21429,
Life Technologies, Carlsbad, CA) were used as secondary antibodies. A Hoechst (Fisher) stain
was used to visualize the nucleus. Images were obtained with the EVOS fluorescent inverted
microscope (Life Technologies, Carlsbad, CA) under 20x objective. Scale bar = 200 microns.
Basal expression of pERK5, pERK1/2, ER-α, NF-κB, and pAKT in TamR MCF-7 and MCF-7 cells were measured by western blot. Bands were quantified using Image Studio™ Lite Software
(LI-COR Biosciences, Lincoln, NE) and normalized against β-actin (see western blot methods section for further detail).
3.6. Ex vivo treatment of PDX tumors
TU-BcX-4QAN PDX tumor was established from a mastectomy specimen of an African
American woman and represents a drug-resistant TNBC tumor. The PDX tumor was propagated and maintained in SCID/Beige immunodeficient mice (CB17.cg-PrkdcscidLystbg/Crl) obtained from Charles River (Wilmington, MA, USA). After two serial transplantation passages in mice, the tumor was removed, and small tumor pieces were dissected (approximately 3 x 3 mm2). The
tumor pieces were kept intact and placed in individual wells of a 24-well plate. Drug solutions of
DMSO/PBS vehicle control, melatonin (10 µM), tamoxifen (10 µM), melatonin + tamoxifen (10
44 µM of each), C4 (10 µM), and C5 (10 µM) were made and added to the intact tumor pieces (1 mL
per well) in triplicate. After 24 hr of incubation at 37° C in 5% CO2, tumor pieces were removed
and placed in 1.5 mL centrifuge tubes and stored at -20° C.
3.7. In vitro treatment of PDX-derived cells for western blot
TU-BcX-4IC cells were derived from a mastectomy specimen of a Caucasian female. The
TU-BcX-4IC tumor was a metaplastic breast carcinoma that had a TNBC PAM50 subtype. The
cells were maintained in DMEM supplemented with 10% FBS, insulin, non-essential amino acids,
minimal essential amino acids, antibiotic-antimycotic, and sodium pyruvate at 37° C in 5% CO2.
TU-BcX-4IC cells were plated in T-25 flasks and exposed to serum-free media for 24 hr before treatment. DMSO/PBS vehicle control, melatonin (10 µM), tamoxifen (10 µM), melatonin + tamoxifen (10 µM of each), C4 (10 µM), and C5 (10 µM) were added to the cells in triplicate.
After 36 hr, of incubation at 37° C in 5% CO2, images were obtained using brightfield microscopy
(40x magnification) and cells were harvested. Adherent cells were harvested from the DMSO and
melatonin treatments. Detached cells were harvested in the media from the tamoxifen, melatonin+tamoxifen, C4, and C5 treatments.
3.8. Cell viability
The MTT assay method was used to determine cellular viability following exposure to each of the drug conjugates (C2, C4, C5, C9, C15. Sub-confluent monolayer cell lines grown on 10 cm culture plates were trypsinized and plated equally into each well of a 48-well plate. The next day, cells were exposed to each of the drug conjugates (1 pM, 1 nM, 1 µM, 10 µM, and, 100 µM) alone or in combination with the inhibitors for 24 hr. For the inhibitor studies assessing the involvement
45 of MEK1/2, MEK5 or PI3 kinase, PD98059 (Santa Cruz Biotechnology, Dallas, TX), Bix02189
(Santa Cruz Biotechnology, Dallas, TX) and pictilisib (PI3 kinase inhibitor, SellerChem, Houston,
TX, USA) were all added at a final concentration of 10 µM. Melatonin (1 pM, 1 nM, 1 µM, 10
µM, and, 100 µM; Millipore Sigma, Burlington, MA, USA), tamoxifen alone or in combination
with melatonin (1 pM, 1 nM, 1 µM, 10 µM, and, 100 µM; Millipore Sigma, Burlington, MA,
USA), 4-OH-tamoxifen alone or in combination with melatonin (1 pM, 1 nM, 1 µM, 10 µM, and,
100 µM; Millipore Sigma, Burlington, MA, USA) were used as control groups. After 24 hr, 25 µL
MTT (Sigma-Aldrich, St. Louis, MO) (dissolved in sterile water) (5mg/mL) was added to each
well (0.5 mg/mL final concentration), and the plates were placed in the incubator for 3 hr (5% CO2 and 37º C). Next, the plates were centrifuged at 50 x g (37º C for 5 min). The entire medium was aspirated, and 250 µL DMSO (Fisher Scientific, Pittsburgh, PA) was added to each well to stop the reaction. The plate was wrapped in aluminum foil and incubated at room temperature for 15 min to dissolve the MTT-formazan crystals. The absorbance was measured at 570 nm (VICTOR3
1420 multilabel counter, Perkin Elmer).
3.9. Cell Migration
Wound/scratch assays were performed in 24-well cell plates to determine the invasiveness
of the cells following exposure to each of the drug conjugates (C2, C4, C5, C9, and C15). Cells
were plated and allowed to settle for 24 hr. After 24 hr, a border was created using a 200 μL pipette
tip that was dragged across the bottom of each well to make a visible and uniform space between
the cells. The floating cells were aspirated, and the cells were refed fresh media containing the
various drug treatments described for the MTT assays above. The border width was measured at
baseline (time 0 hr) and then 24 hr following exposure to the treatments (time 24 hr) added alone
46 or in combination with the inhibitors (where indicated) using an EVOS digital inverted
fluorescence microscope. Any width changes were expressed as percentages. For the inhibitor
studies assessing the involvement of MEK1/2, MEK5 or PI3 kinase, PD98059, Bix02189 and pictilisib were all added at a final concentration of 10 µM. Border widths were calculated as (24
hr-0 hr) / 0 hr x 100; where a more positive number indicates inhibition of migration while a more
negative number indicates stimulation of migration. For calculating the max inhibition of TamR
MCF-7 cell migration, percent change in border width was normalized against minimum inhibition
of migration, whereas minimum inhibition of migration was considered as 0% and no border
change was considered as 100%.
3.10. Western blot
To identify potential intracellular targets, C4- or C5-mediated effects on pERK1/2, pERK5,
p-AKT, NF-ĸB, Runx2, and β1-integrin proteins were analyzed by western blot analysis. BC cells were treated with each drug conjugate (1 nM and 10 µM) in the absence or presence of 10 µM of
PD98059, BIX02189 or pictilisib 0 min (baseline) or 15 min after which the cells were scraped
into Laemmli sample buffer containing β-mercaptoethanol, heated for 5 min at 95o C, cooled and
then stored at -20o C until use. Western blot analysis was conducted using the Odyssey® Western
Blotting Kit IV RD (CAT# 926-31084, LI-COR Bioscience, USA). Equal amounts of each sample
(20 µL) and 5 µL of molecular weight marker (Precision Plus ProteinTM, CAT# 161-0373, BioRad,
USA) were loaded onto 10% gels. Proteins, separated by SDS-PAGE, were transferred to
nitrocellulose membranes. Membranes were then incubated in blocking buffer (LI-COR
Biosciences, Lincoln, NE) for 30 min and then incubated with each respective primary antibody
[(rabbit anti-pERK1/2 and anti-pERK5 (T218/Y220; CAT# 3371, 1:1000 dilution, Cell Signaling,
47 Danvers, MA), rabbit anti-phospho-AKT (CAT# 9271, 1:750 dilution; Cell Signaling, Danvers,
MA), rabbit anti-NF-ĸB (p52, CAT# sc-298; 1:1000 dilution; Santa Cruz, Dallas, TX), rabbit anti-
Runx2 (CAT# sc-10758; 1:1000 dilution; Santa Cruz, Dallas, TX), rat ER-α (CAT# sc-53493;
1:750 dilution; Santa Cruz, Dallas, TX) and rabbit anti-β1-integrin (M-106; CAT# sc-8978; 1:1000 dilution; Santa Cruz, Dallas, TX)] along with mouse anti-β-actin (CAT# 926-42212, LI-COR
Biosciences, USA) overnight at 4° C. Next, the blots were washed with PBS containing Tween-
20 and then incubated with secondary antibodies [goat anti-rabbit (IRDye 800CW, CAT# 925-
32211, 1:20,000 dilution; LI-COR Biosciences) and goat anti-mouse (IRDye 680RD, CAT# 925-
68070, 1:20,000 dilution; LI-COR Biosciences)] for 30min at room temperature. For ER-α primary antibody, goat anti-rat (IRDye 800CW, CAT# 925-32219, 1:20,000 dilution; LI-COR
Biosciences) was used for 30 min at room temperature. Bands were quantified using Image
Studio™ Lite (LI-COR Biosciences, Lincoln, NE, USA) software and normalized against β-actin
to control for differences in protein loading between treatment groups.
3.11. Microsomal incubation method
Human liver microsomes (UltrapoolTM HLM 150, Cat#452117, Corning, Woburn, MA,
USA) and mouse liver microsomes (pooled female MLM, Cat#452702, Corning, Woburn, MA,
USA) were used to assess susceptibility to hepatic metabolism of C4 and C5. Specifically,
microsomes were incubated with 5 µM of either C4, C5, or tamoxifen in the presence of an
NADPH regenerating system (0.5 mM NADPH, 1 unit/mL glucose-6-phosphate dehydrogenase, and 10 mM glucose 6-phosphate) at 37° C for 0, 5, and 10 min in mouse, and 0, 10, and 20 min in
human microsomes. A longer incubation time was required for human microsomes compared to
mouse microsomes because of slow metabolism. Reactions were stopped and precipitated using
48 50% acetonitrile. Reaction vials were centrifuged at 9500 x g (4º C for 15 min) The rate of drug
loss was measured by HPLC-UV detection. Following optimization of the HPLC conditions
[column pre-wash 2 min with 70% solvent A (10% methanol in phosphate buffer) and 30% solvent
B (100% methanol) for 2 min; sample runs = 25 min at a gradient flow rate of 0.4mL/min where
solvent B was changed from 30% to 90%], retention times for C4 (retention time = 20.46 min) and
C5 (retention time = 20.93 min) were similar to that of tamoxifen (retention time = 20.46 min).
Peak absorbance of each sample was normalized against the internal standard, celecoxib.
Celecoxib was used as an internal standard for this study because it gave a retention time (RT =
11.51 min) distinguishable from the retention times for tamoxifen, C4, and C5 melatonin-
tamoxifen drug conjugates.
3.12. Pharmacokinetic analysis of C4 and C5
All original studies using animals have been carried out in accordance with the Guide for
the Care and Use of Laboratory Animals as adopted and promulgated by the U.S. National
Institutes of Health, and were approved by the Institution’s Animal Care and Use Committee or
local equivalent (IACUC approval number: 1607-07M1). C57BL/6J female mice (2 months) were
used to assess the pharmacokinetic properties of C4 and C5. The drugs were initially dissolved in
ethanol (5% v/v) and then added to hydroxypropyl methylcellulose (5 mg/mL in ddH20) to obtain
a final concentration of 0.5% (w/v). The C4 and C5, each was administered separately by two routes of administration—subcutaneous and oral. The outcomes were compared to the subcutaneous administration of tamoxifen, which served as the control group. One group of mice
(n=8) received a subcutaneous dose of 1 mg/kg body weight while another group received an oral
dose of 10 mg/kg body weight. Different doses for the two routes were given to achieve similar
49 exposures for the two routes based on experience with tamoxifen (Reid et al., 2014). For both routes of administration, blood was collected at similar time points (0, 30, 60, 120, 180, 360, 480, and 1440 min) except that one earlier time of 15min was also taken for the subcutaneous route.
One C56BL/6J female mouse age of 2 months was used for each time point. The blood was collected in a K2-EDTA coated tube by decapitation after CO2 euthanasia. After that, blood was
centrifuged at 1166 x g (4º C for 5 min) to separate the plasma. The plasma was then stored at -
80º C until performing the LC-MS.
3.13. LC-MS/MS method for quantification of tamoxifen, C4, and C5 in mouse
plasma
Deuterated tamoxifen (TAM -d5) was purchased from Toronto Research Chemicals,
Canada. Mouse plasma in Li- Heparin was purchased from Lampire biological laboratories, USA.
Acetonitrile (HPLC grade), isopropanol, hexane, and formic acid (MS Grade) were purchased from Fisher Chemicals, USA. Individual stock solutions (20 µg/mL) of tamoxifen, C4, and C5 were prepared in methanol and stored at -20 C until use. The standards for the calibration curve were prepared by serial dilution of working stock solutions (64 ng/mL) of tamoxifen, C4, and C5 in methanol and then dividing them into 125 µL aliquots. Deuterated tamoxifen (TAM-d5) was used as the internal standard. Working stock solutions (50 ng/mL) of TAM-d5 were prepared in methanol, divided into 20 µL aliquots, and stored at -20 C until use.
Calibration standards (0.25, 0.5, 1, 2, 4, 8, 16, and, 32 ng/mL) of tamoxifen, C4 or C5 were prepared in 115 µL of mouse plasma and then spiked with TAM-d5 (2 ng/mL final concentration) to quantify all the compounds during the extraction process. Quality control (QC) samples of 0.1 ng/mL (Lower Limit of Quantification, LLQ), 2 ng/mL (QC-Low), and 32 ng/mL (QC- high) were
50 run in parallel and in triplicate for each experimental run of tamoxifen, C4, and C5. Before the extraction process, 10 µL of 1 M NaOH was added to 200 µL of each sample followed by vortexing for 30 s. Next, 1000 µL of extraction solvent [hexane:isopropanol (95:5, v/v)] was added to each tube and then placed on a rotary shaker for 5 min. Samples were then centrifuged for 5 min at 9500 x g to separate the aqueous phase (bottom layer) from the organic phase (top layer). Next, 900 µL of the supernatant was transferred to a clean test tube. The remaining aqueous layer in the original tube was subjected to the same extraction process by adding another 1000 µL of extraction solvent.
The total transferred supernatant (organic phase) was air dried under N2 flux. The dry residue was dissolved in 200 µL of methanol and subjected to liquid chromatography with mass spectrometry detection (LC-MS).
HPLC followed by tandem mass spectrometry was conducted using a system model 1200 and triple quadrupole mass spectrometer (model 6460) with a jet stream electrospray ion (ESI) source (Agilent Technologies, Santa Clara, CA). Data acquisition and chromatographic peak integration were performed using Agilent MassHunter software (versions B02.01 and B02.00). All analyses were performed in positive ion mode and chromatograms were recorded in multiple reaction monitoring (MRM) scan mode. Mass spectrometry collision parameters for tamoxifen,
TAM-d5, C4, and C5 are shown in Table 1, while mass spectrometry acquisition and source parameters for the instrument are summarized in Table 2.
Chromatographic separation was achieved with a Thermo scientific Hypersil GOLDTM;
ThermoScientific, Waltham, MA) reverse phase C18 column (50 x 4.6 mm, 3 µm packing) thermostated at T = 25 C. Deionized water and acetonitrile, both acidified with 0.1% formic acid, were used as mobile phase A and B, respectively, at the flow rate of 0.5 mL/min. A linear gradient separation was used where mobile phase B was initially set at 20% for 1min, then increased to
51 80% over 5 min, and then further increased to 95% over 0.1 min where it remained for 1.9 min.
Next, mobile phase B was decreased to initial conditions over 0.1 min, and the system was re- equilibrated for 3.9 min before the following injection. The total run time was 12 min with an injection volume of 40 µL. The injection needle was washed in between analyses using a wash solution of acetonitrile containing 0.1% formic acid (v/v) for 20 s. The needle draw and ejection speed was set to 100 µL/min.
Calibration samples and quality control samples (described above and performed in triplicate) were used for the determination of linearity, accuracy, and precision. Calibration curves were plotted by correlating the peak area ratio of each compound (relative to TAM-d5 as the internal standard) as a function of the concentration of spiked standard solutions with a weight factor of 1/y2 or 1/relative response2. The concentration range (0.25 ng/mL-32 ng/mL with LLQ
of 0.1 ng/mL) for the calibration standards was chosen based on the level of concentration expected
in the unknown samples. The concentration of the quality control samples was set to 0.1 ng/mL
(LLQ), 2 ng/mL (QC-low), and 32 ng/mL (QC-high) for tamoxifen, C4, and C5 based on the range
of calibration concentrations for each compound.
Middle concentrations of the calibration curve were used to determine matrix effects and
extraction recovery. The matrix effect was determined by comparing the peak area in post-
extracted spiked samples versus the peak area in a standard methanol solution. At least six
independent plasma samples with different concentrations were tested for the matrix effect for
each compound. The extraction recovery was calculated by comparing the peak area of each
extracted sample (spiked standard in the blank matrix) with the post-extracted spiked sample at
the same concentration; this represented 100% recovery. Recovery was calculated for at least 4
52 independent plasma samples with different concentrations for each compound. Matrix effects and extraction recoveries for tamoxifen, C4, and C5 are shown in Table 3.
Table 1: Mass Spectrometry Collision Parameters Compounds Parent (m/z) Daughter (m/z) Collision Energy (V)
Tamoxifen (TAM) 372.2 72.1 21
TAM-d5 377.2 72.1 21
C4 630.4 174.1 45
C5 644.4 174.1 45
Table 2: Mass Spectrometry Acquisition and Source Parameters Source parameters Conditions Acquisition parameters Conditions
Gas Temperature 320 C Dwell time 200 ms
Gas Flow 10 l/min Fragmentor Voltage 135 V
Nebulizer 45 psi Cell Accelerator Voltage 7 V
Sheath gas Temp 370 C Polarity positive
Sheath gas Flow 11 l/min
Capillary Voltage 3500 V
Nozzle Voltage 500
53 Table 3: Matrix Effect and Extraction Recovery (a n = 7, b n = 6, c n = 4) Compounds Matrix effect (%) Extraction Recovery (%)
Mean SD Mean SD
Tamoxifen 10.75 7.76 a 94.34 14.41 a
C4 8.47 8.64 a 96.9 29.92 a
C5 11.32 6.85 b 105.27 6.18 c
3.14. Statistical analysis
All statistical analyses were performed using GraphPad Prism™ (version 6; GraphPad
Software, La Jolla, CA) and determined in advance. Data represent the mean ± SD unless
mentioned otherwise. Data points that were determined to be outliers by Grubbs’ test were excluded. The mean IC50 values of cell viability and cell migration were obtained by nonlinear
regression analysis (log (inhibitor) vs. response (three parameters) and fit by the least sum of
squares. For the saturation binding analyses, Bmax values comparing wildtype MCF-7 cells to tamoxifen-resistant (TamR) MCF-7 cells using unpaired Student’s t-test. For all biphasic curves, two sites – Fit Ki Nonlinear Regression model in GraphPad Prism has been used. Total cell number obtained via the MTT analysis comparing wildtype vs. TamR MCF-7 cells was analyzed by two- way ANOVA followed by Bonferroni’s post hoc test. For other statistical comparisons, one-way
ANOVA followed by Newman-Keuls multiple comparisons test was performed. Mean differences between treatment groups were considered significant at p<0.05.
54 Chapter 4: Results
4.1. Effects of C2, C4, C5, C9, and C15 conjugates on MCF-7 (ER+/PR+) cells
Viability: Cells were exposed to varying concentrations of C2, C4, C5, C9, and C15 and
their effect on cell viability was assessed. As controls, MCF-7 cells were exposed to vehicle,
melatonin, tamoxifen, 4-OH-tamoxifen, and combinations of melatonin plus tamoxifen or 4-OH- tamoxifen. With respect to viability, C4 trended towards being the most potent (IC50=4 nM) vs.
C2 (IC50=69 mM), C5 (IC50=440 mM), C9 (IC50=107 mM) and C15 (IC50= 34 µM) (Figure 6A;
Table 4). Tamoxifen is a prodrug that gets converted into 4-OH-tamoxifen by CYP2D6 (Goetz et
al., 2008). This metabolite of tamoxifen, 4-OH-tamoxifen, has 30 to 100 fold higher binding
affinity to ERs compared to tamoxifen (Goetz et al., 2008). Because it is expected that melatonin-
tamoxifen conjugates will be converted into melatonin-4-OH-tamoxifen conjugates in vivo, 4-OH-
tamoxifen and melatonin+4-OH-tamoxifen were also run as controls. With respect to efficacy,
although all five drug conjugates inhibited MCF-7 cell viability compared to vehicle, C4 and C5
were most efficacious at inhibiting viability by 70-90% compared to vehicle (Figure 6B; Table 5).
To determine if the drug conjugates displayed equal or superior potency and/or efficacy against
the controls with respect to effects on MCF-7 cell viability, each drug conjugate was compared
against melatonin alone, tamoxifen alone, 4-OH-tamoxifen alone, melatonin plus tamoxifen
(unlinked), and melatonin plus 4-OH-tamoxifen (unlinked) by one-way ANOVA. The potency of
C2, C4, C5, and C15 were similar to all of the controls except for C9, which was least potent
(Figure 6C; Table 6). Regarding efficacy, C5 displayed the greatest efficacy (~90% compared to
vehicle), which was not significantly different from the other controls except for melatonin, which
only inhibited viability by ~10% compared to the vehicle (Figure 6D; Table 7).
55 Migration: With respect to migration and when compared to each other, C5 (IC50=4 µM),
and C15 (IC50=1 µM) trended towards being most potent to inhibit MCF-7 cell migration while
the C2 (IC50=100 µM), C4 (IC50=9 mM), and C9 (IC50=218 mM) were least potent (Figure 7A;
Table 4). Regarding efficacy, all drug conjugates, except for C15 (-13% of baseline), inhibited
MCF-7 cell migration equally (+2% to +20% of baseline) compared to the vehicle (Figure 7B;
Table 5). All drug conjugates, except for C9, were more potent than melatonin plus 4-OH-
tamoxifen to inhibit MCF-7 cell migration but similar to melatonin, tamoxifen, 4-OH-tamoxifen,
and melatonin plus tamoxifen controls (Figure 7C; Table 6). Regarding efficacy, C2, C4, C5, and
C9 displayed similar efficacies to inhibit MCF-7 cell migration compared to all controls (+0% to
+39% of baseline). Both melatonin (-14% of baseline) and C15 were without effect on MCF-7 cell
migration (Figure 7D; Table 7).
56
Figure 6: Comparison of potency and efficacy between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell viability. The potency (IC50) (A) or efficacy (B) of C2, C4, C5, C9, and C15 on cell viability in MCF-7, MMCs, MDA-MB-231, and BT-549. Similarly, C and D represent the potency (IC50) (C) or efficacy (D) of melatonin, tamoxifen, 4-OH-tamoxifen, and unlinked melatonin+tamoxifen and unlinked melatonin+4-OH-tamoxifen on cell viability in MCF-7,
MMCs, MDA-MB-231, and BT-549. Each bar represents the mean ± SD of 3 independent experiments for each compound and n=9 for the vehicle since it was run with each experiment
57 conducted. Data were analyzed by one-way ANOVA followed by Newman-Keuls post-hoc t-test
where significance was defined as p<0.05.
4.2. Effects of C2, C4, C5, C9, and C15 conjugates on MMC (HER2+) cells
Viability: Cells were exposed to varying concentrations of C2, C4, C5, C9, and C15 and
their effect on cell viability was assessed. C4 trended towards being most potent (IC50=243 nM)
followed by C2 (IC50=13 µM), C5 (IC50=6 µM), C9 (IC50=6 µM), and then C15, which was least
potent (IC50=333 mM) (Figure 6A; Table 4). Concerning efficacy, C2, C4, C5, and C9 inhibited
MMC cell viability to a similar extent (~20-50% inhibition compared to vehicle). C15 produced a minimal non-significant effect (3% inhibition compared to vehicle) (Figure 6B; Table 5). All conjugates, except C2, had similar potency to the controls except for C4, which was more potent than melatonin plus 4-OH-tamoxifen (Figure 6C; Table 6). Regarding efficacy, all drug conjugates, except for C15, inhibited MMC cell viability to a similar extent, which was similar
(~40% inhibition compared to vehicle) to controls (tamoxifen ± melatonin; 4-OH-tamoxifen ± melatonin) except for melatonin (9% inhibition compared to vehicle), which did not inhibit MMC viability (Figure 6D; Table 7).
Migration: The potencies of C4, C5, C9, and C15 to inhibit MMC cell migration, though variable, were not significantly different from one another; however, they were significantly more potent than that of C2, which had a potency of (IC50=221 mM; Figure 7A; Table 4). Regarding
efficacy to inhibit MMC cell migration, all drug conjugates, except for C15 (-32% of baseline),
inhibited MMC cell migration equally (+1% to +44% of baseline) compared to vehicle (Figure
7B; Table 5). C2 and C9 were the least potent of all drug conjugates when compared to the controls
(melatonin alone; tamoxifen alone; 4-OH-tamoxifen alone; melatonin + tamoxifen unlinked;
58 Figure 7C; Table 6). C4, C5, and C15 were similar to all controls except C5, which was more potent than melatonin plus 4-OH-tamoxifen to inhibit MMC cell migration (Figure 7C; Table 6).
Regarding efficacy, C2 and C9 displayed the greatest efficacy (~+40% of baseline) to inhibit MMC cell migration when compared to all controls. C4 and C5 were similar to all controls (between
+1% to 7% of baseline) except melatonin, which was without effect vs. vehicle. The C15 was without effect on MMC cell migration compared to the vehicle (Figure 7D; Table 7).
59 Table 4: Comparison of potencies between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell viability and migration. Each value represents the average ± SD of potency (IC50) values generated from 3-9 individual curves fit by non-linear regression analysis. Data were analyzed by one-way ANOVA followed by Newman-Keuls post-hoc t-test where significance was defined as p<0.05. Letters denote significance between groups where a = p<0.05 vs. C2; b = p<0.05 vs. C4; c = p<0.05 vs. C5; d = p<0.05 vs. C9.
C2 (n=1) C4 (n=3) C5 (n=4) C9 (n=8) C15 (n=14) 69 mM±81 4 nM±4.31 440 107 34 µM±15 Viability mM±331 mM±17 MCF-7 100 9 mM±11 4 µM±3.3 218 1 µM ±2 Migration µM±156 mM±48 d abc 13 µM±8 243 6 µM ±1.6 6 µM±2.8 333 mM±333 Viability nM±331 MMC 221 5 mM±8 227 206 110 nM±149 Migration mM±65 A nM±200 µM±25.7 a a a 246 37 nM±34 12 µM±11 145 477 pM±674 Viability µM±178 mM±70 d MDA- abc MB-231 559 11 3 µM±3 269 173 mM±157 Migration mM±131 mM±19 a µM±119 abcd A a Viability 24 µM±8 6 µM±2 24 µM±31 34 µM±34 2 µM±3 BT-549 579 9 µM±9 51 µM±62 328 18 nM±23 Migration mM±308 mM±340
60
Figure 7: Comparison of potency and efficacy between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell migration. The potency (IC50) (A) and efficacy (B) of C2, C4, C5, C9, and C15
on cell migration in MCF-7, MMCs, MDA-MB-231, and BT-549. Similarly, C and D represent the potency (IC50) (C) or efficacy (D) of melatonin, tamoxifen, 4-OH-tamoxifen, unlinked
melatonin+tamoxifen, and unlinked melatonin+4-OH-tamoxifen on cell migration in MCF-7,
MMC, MDA-MB-231, and BT-549. Each bar represents the mean ± SD of 3 independent
experiments for each compound and n=9 for the vehicle since it was run with each experiment
61 conducted. Data were analyzed by one-way ANOVA followed by Newman-Keuls post-hoc t-test where significance was defined as p<0.05.
4.3. Effect of C2, C4, C5, C9, and C15 conjugates on MDA-MB-231 (ER-/PR-
/HER-) cells
Viability: Cells were exposed to varying concentrations of C2, C4, C5, C9, and C15 and their effect on cell viability was assessed. C9 was the least potent (IC50=145 mM) while the C15 was most potent (IC50=477 pM) vs C2 (IC50=246 µM), C4 (IC50=37 nM), and C5 (IC50=12 µM)
(Figure 6A; Table 4). Regarding efficacy, C2, C5, and C9 inhibited cell viability to a similar extent
(25-37% inhibition compared to vehicle) while the C4 and C15 were without effect and similar to the vehicle (Figure 6B; Table 5). The potencies, although variable, were not significantly different from one another except for C5, which was more potent than combination melatonin plus tamoxifen (Figure 6C; Table 6). Regarding efficacy, C2, C5, and C9 displayed significant inhibition (25-37%) when compared to the vehicle while C4 and C15 were without effect; C2 and
C9 were also significantly different than melatonin alone; and C2, C5, and C9 were also more efficacious at inhibiting MDA-MB-231 cell viability vs. 4-OH-tamoxifen alone (Figure 6D; Table
7).
Migration: Melatonin-tamoxifen drug conjugate potency and efficacy to inhibit MDA-
MB-231 cell migration revealed no significant differences in potency between C4, C5, and C9; however, they were significantly higher compared to C2 and C15, which displayed mM potency
(Figure 7A; Table 4). Regarding efficacy, all drug conjugates, except for C15, inhibited MDA-
MB-231 cell migration equally (+10% to +35% of baseline) compared to the vehicle; C15 worsened migration of the cells (Figure 7B; Table 5). When compared to the controls [i.e.,
62 melatonin alone, tamoxifen alone, 4-OH-tamoxifen alone, melatonin plus tamoxifen (unlinked),
and melatonin plus 4-OH-tamoxifen (unlinked)], C2 was the least potent of all drug conjugates to
inhibit MDA-MB-231 cell migration (IC50=559 mM). C4, C5, C9, and C15 were similar to all
controls with C5 displaying greater potency (IC50=3 µM) than combination melatonin plus
tamoxifen (IC50=229 mM; Figure 7C; Table 6). Regarding efficacy, all drug conjugates inhibited
MDA-MB-231 cell migration compared to vehicle and melatonin; however, C9 had the highest efficacy (+35% of baseline) and inhibited cell migration greater than melatonin plus tamoxifen
(+0% of baseline) and melatonin plus 4-OH-tamoxifen (+2% of baseline). C15 was least efficacious (-43% of baseline) while melatonin was without effect (Figure 7D; Table 7).
63 Table 5: Comparison of efficacies between C2, C4, C5, C9, and C15 conjugates to inhibit BC cell viability and migration. Each value represents the average ± SD of the maximum inhibitory effect of each drug conjugate represented as % of the vehicle for viability and % of baseline for migration assays. Values were derived from 3-9 individual curves fit by non-linear regression analysis. Data were analyzed by one-way ANOVA followed by Newman-Keuls post-hoc t-test where significance was defined as p<0.05. Letters denote significance between groups where a = p<0.05 vs. vehicle; b = p<0.05 vs. C2; c = p<0.05 vs. C4; d = p<0.05 vs. C5; e = p<0.05 vs. C9.
C2 C4 C5 C9 C15 66±2 29±7 10±0.3 65±2 86±2.4 Viability A ab abc acd abcde MCF-7 20±11 10±15 2±2 19±11 -13±5 Migration Ab Abf af Ab df 79±6 57±22 65±7 79±9 97±11 Viability A ab a ac bcde MMC 44±34 7±40 1±2.3 39±39 -32±5 Migration abcdef A a Abe 63±1.4 98±22 75±1.7 68±2 104±6.7 Viability MDA-MB- A b ac ac bde 231 33±13 30±36 10±7 35±10 -43±27 Migration Ab Ab Ab abcdef Acdef 80±16 66±4 67±6 88±27 93±7 Viability a a BT-549 42±12 20±4 0±0 56±29 -61±14 Migration abcd A abcde Abcdef
4.4. Effects of C2, C4, C5, C9, and C15 conjugates on BT-549 cells
Viability: Another triple-negative BC line, BT-549, was screened to assess the potency
and efficacy of the drug conjugates on viability and migration. With respect to viability, all drug
conjugates had similar potency to inhibit BT-549 cell viability with potency in the low µM range
(IC50=2-34 µM; Figure 6A; Table 4). Concerning efficacy, only C4 and C5 inhibited BT-549 cell
viability (~35% inhibition compared to vehicle); C2, C9, and C15 were without effect and similar
to the vehicle (Figure 6B; Table 5). All drug conjugates had a similar potency to the controls
(melatonin, 4-OH-tamoxifen, melatonin plus tamoxifen, and melatonin plus 4-OH-tamoxifen) except for tamoxifen, which was least potent (IC50=781 mM; Figure 6C; Table 6). Regarding
efficacy, C2, C4, and C5 inhibited BT-549 cell viability (~20-35% inhibition compared to vehicle)
64 and melatonin with C15 being least efficacious (~10% inhibition compared to vehicle) (Figure 6D;
Table 7).
Migration: Exposure of BT-549 cells to C2, C4, C5, C9, and C15 did not result in
significant differences in potencies between drug conjugates to inhibit their migration (Figure 7A;
Table 4). With respect to migration, all drug conjugates had similar potency. Regarding efficacy,
C2, C4, C5, and C9 inhibited BT-549 cell migration (+0% to +56% of baseline) when compared to the vehicle. C15 increased BT-549 cell migration (-61% of baseline) vs. vehicle (Figure 7B;
Table 5). With respect to control potencies, which ranged between 3-116 µM, no significant
differences in potencies occurred for any of the drug conjugates except for C2, which had low potency (IC50=579 mM; Figure 7C; Table 6). Regarding efficacy, C9 inhibited BT-549 cell
migration when compared to the vehicle; C2 and C9 also inhibited cell migration to a greater extent
than melatonin, tamoxifen, or 4-OH-tamoxifen—all of which were without effect on BT-549 cell
migration. Furthermore, C9 was more efficacious compared to combination melatonin plus tamoxifen (+15% of baseline) and combination melatonin plus 4-OH-tamoxifen (+32% of
baseline). C15 made the BT-549 cells more aggressive (-61% of baseline) when compared to all
controls (Figure 7D; Table 7).
65 e b 34 34 18 18 110 110 477 477 333 333 173 173 nM±23 nM±23 µM±15 2 µM±3 2 µM±3 nM±149 pM±674 1 µM ±2 ±2 1 µM mM±333 mM±157
b 107 107 206 206 145 218 218 269 269 328 328 abce abce abcde abcde abcde abcde mM±17 mM±70 mM±48 µM±119 mM±340 µM±25.7 6 µM±2.8 6 µM±2.8 34 µM±34 µM±34 34 individual curves fit by e d 4 b E 12 12 24 24 51 51 440 440 227 227 ±1.6 ±1.6 6 µM 6 µM µM±11 µM±31 µM±62 µM±3.3 3 µM±3 3 µM±3 nM±200 mM±331 controls to inhibit BC cell viability BC cell viability controls to inhibit e e 4 9 d b 37 37 11 11 Newman-Keuls post-hoc t-test where post-hoc t-test where Newman-Keuls 243 243 nM±34 nM±34 mM±11 mM±19 6 µM±2 6 µM±2 9 µM±9 9 µM±9 nM±331 5 mM±8 5 mM±8 nM±4.31 nM±4.31 e b 69 69 C2 C4 C5 C15 C9 246 246 100 100 559 559 221 221 579 579 abcde abcde abcde abcde abcde abcde abcde abcde mM±81 mM±65 µM±178 µM±156 mM±131 mM±308 24 µM±8 µM±8 24 13 µM±8 µM±8 13 ) values generated from 3-9 ) values generated from 50 a a 7 ac 17 17 69 69 24 24 68 68 abc abc 131 131 116 116 Mel+4- µM±11 µM±33 µM±93 mM±29 mM±18 5 µM±3 5 µM±3 µM±2.3 OH-tam OH-tam nM±106 e = p<0.05 vs. Mel+4-OH-Tam. e = p<0.05 vs. Mel+4-OH-Tam. cance between groups where a = p<0.05 vs. Mel; b ; a 11 11 11 11 31 31 328 328 419 419 229 229 µM±40 nM±0.1 nM±0.1 mM±19 3 µM±2 3 µM±2 µM±222 mM±354 mM±232 Mel+Tam a 4 3 34 34 26 26 13 13 91 91 30 30 tam C2, C4, C5, C9 and C15 conjugates 4-OH- µM±30 µM±84 mM±41 mM±13 µM±0.9 µM±1.5 µM±3.6 3 µM±3 3 µM±3 µM±7 24 average ± SD of potency (IC average re analyzed by one-way ANOVA followed 3 12 12 58 58 30 30 21 21 11 11 138 138 781 781 mM±7 µM±23 µM±18 mM±20 mM±67 mM±35 µM±3.1 µM±117 18 18 52 52 309 309 123 123 231 231 504 504 427 427 nM±18 nM±18 nM±89 nM±89 nM±0.1 nM±0.1 4 µM±6 4 µM±6 nM±164 nM±392 nM±479 µM±239 Each value represents the Each value represents Viability Viability Viability Viability Migration Migration Migration Migration (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) (n=3/group) (n=3/group) (n=4/group) (n=4/group) (n=4/group) (n=4/group) Mel Tam Mel 231 MB- MMC MDA- MCF-7 BT-549
Table 6: Comparison of potencies between and migration. non-linear regression analysis. Data we significance was defined as p<0.05. Letters denote signifi d = p<0.05 vs. Mel+Tam c = p<0.05 vs. 4-OH-Tam; Tam;
66
df df cef cdef 93±7 93±7 acdef acdef acdef -13±5 -13±5 -32±5 97±11 97±11 abcdef abcdef 86±2.4 86±2.4 -43±27 -61±14 104±6.7 a ab abe abe abd cdef 68±2 68±2 65±2 65±2 79±9 79±9 abcde abcde 35±10 35±10 88±27 88±27 19±11 19±11 39±39 39±39 abcdef abcdef abcdef abcdef a af ad ab ab ab ab 2±2 2±2 0±0 56±29 56±29 0±0 10±7 10±7 67±6 67±6 65±7 65±7 1±2.3 1±2.3 75±1.7 75±1.7 10±0.3 10±0.3 denote significance between and controls to inhibit BC cell a A ce ab ab ab abf 29±7 29±7 7±40 66±4 66±4 20±4 20±4 98±22 98±22 30±36 30±36 10±15 10±15 57±22 57±22 abcdef abcdef a it. Data were analyzed by one-way ANOVA ab ab C2 C4 C5 C9 C15 C9 C5 C2 C4 abd abcd 66±2 66±2 79±6 79±6 abcef 33±13 33±13 20±11 20±11 44±34 44±34 80±16 80±16 42±12 42±12 abcdef abcdef abcdef abcdef 63±1.4 63±1.4 ximum inhibitory effect of each drug conjugate ximum baseline for migration assays. Values were derived baseline for migration a ab ab ab ab abd abd 2±2 2±2 abce abce 78±3 78±3 65±3 65±3 66±7 66±7 0.7±9 0.7±9 39±12 39±12 32±16 32±16 12±1.2 12±1.2 Mel+4- OH-tam OH-tam was defined as p<0.05. Letters c = p<0.05 vs. Tam; d = p<0.05 vs. 4-OH-Tam; e = p<0.05 vs. a a a ab ab ab abd abd 0±0 0±0 0±0 0±0 64±5 64±5 65±8 65±8 11±0.5 11±0.5 -12±14 Mel+Tam c a ab ab ab ab of C2, C4, C5, C9 and C15 conjugates tam 3±3 3±3 72±6 72±6 0.5±1 0.5±1 20±10 20±10 65±13 65±13 4-OH- 14±2.2 14±2.2 107±40 70±5 tested) for viability and % of regression analysis and least squares f a a a a ab ab ab 13±1.2 13±1.2 0.05±0.01 0.05±0.01 a a Each value represents the average ± SD of ma 87±8 87±8 91±2 66±6 66±6 91±2 92±5 76±2 76±2 92±5 -64±2 9±11 -14±6 6±1.6 6±1.6 -14±6 -15±9 0±0 0±0 -15±9 0±0 15±5 -23±7 -23±7 91±17 65±12 65±12 91±17 Viability Viability Viability Viability Migration Migration Migration Migration (n=4/group) (n=4/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) (n=3/group) Table 7: Comparison of efficacies Table 7: Comparison of efficacies
Mel Tam Mel MMC MDA- MCF-7 BT-549 MB-231
viability and migration. viability and represented as % of vehicle (n=9/cell line as % of vehicle (n=9/cell line represented individual curves fit by non-linear from followed by Newman-Keuls post-hoc t-test where significance followed by Newman-Keuls groups, where a = p<0.05 vs. Vehicle; b Mel; f = p<0.05 vs. Mel+4-OH-Tam. Mel+Tam;
67 4.5. Binding affinities of C2, C4, C5, C9, and C15 conjugates to ERs and
MT1Rs
Competition binding analysis was performed to identify potential mechanisms of action
for the anti-cancer actions of the drug conjugates. Specifically, competition of tamoxifen, 4-OH-
tamoxifen and each of the drug conjugates (C2, C4, C5, C9, and C15) for [3H]-estradiol or [125I]- estradiol binding to ERs or competition of melatonin and each of the drug conjugates for 2-[125I]- iodomelatonin binding to MT1 melatonin receptor binding assays were conducted. ER binding affinity assays were conducted in both mouse uterus ((P.A. Witt-Enderby et al., 2014); US Patent
8,785,501) and MCF-7 cell lines (Figure 8). Tamoxifen and 4-OH-tamoxifen were used as controls for mouse uterus and MCF-7 cells, respectively. As previously published ((P.A. Witt-Enderby et al., 2014); US Patent 8,785,501), the affinity of tamoxifen (Kihigh=3 pM and Kilow=6 nM) for ERs
expressed in mouse uterus displayed a biphasic curve (Figure 8A). In MCF-7 cells, the affinity of
4-OH-tamoxifen for ERs displayed a monophasic curve with an affinity Ki=46 nM (Figure 8C).
For C2, C9 and C15, no concentration-dependent inhibition of [3H]-estradiol binding occurred
(Figures 8E, 8F, 8G) whereas C4 had a binding affinity (Ki=41 nM) similar to 4-OH-tamoxifen
(Ki=46 nM) between concentrations of 1 pM-10 µM (Figure 8D). As already reported, C5 showed
a similar binding affinity (Ki=2 nM) as tamoxifen ((P.A. Witt-Enderby et al., 2014); US Patent
8,785,501) between concentrations 1 pM-1 µM (Figure 8B). Interestingly, all drug conjugates
displayed an increase in total ER binding sites (~225-800% of control) at higher (10-100 µM)
concentrations.
68 4.6. Binding affinities of C4, C5, and G1 to ERs
Total binding assays were conducted on MCF-7 cells using [3H]-estradiol to elucidate the role of C4 and C5 on the membrane-bound G-protein coupled estrogen receptor (GPR30). As shown in Figure 8H, all treatments, except for G1, decreased [3H]-estradiol binding compared to vehicle whereas G1 increased [3H]-estradiol binding. Combination of C5 with G1 demonstrated the lowest [3H]-estradiol binding compared to all groups, including C5 alone (Figure 8H).
69
Figure 8: Competition of C2, C4, C5, C9, or C15
for [3H]-or [125I]-estradiol binding to ERs
expressed in mouse uterus or MCF-7 cells.
Binding of [3H]-or [125I]-estradiol to ERs expressed
in mouse uterus (A and B) and MCF-7 cells by
competition binding using tamoxifen (A), 4-OH- tamoxifen (C) or conjugates C2, C4, C5, C9 or C15) (C-G) and G1 effects on total [3H]-estradiol
70 binding to ERs expressed in MCF-7 cells (H). Data represent the mean ± SD of 3 independent experiments performed in duplicate. Figures A and B were taken from (P.A. Witt-Enderby et al.,
2014), US Patent 8,785,501. Data in Figure H were analyzed by one-way ANOVA followed by
Newman-Keuls post hoc t-test where significance a = p<0.05 vs vehicle; b = p<0.05 vs tamoxifen and c = p<0.05 vs G1; d = p< 0.05 vs C4; e = p<0.05 vs C5.
For human MT1 receptors (MT1Rs), all drug conjugates demonstrated concentration- dependent inhibition of 2-[125I]-melatonin binding with binding affinity (Ki: C2=35 nM; C4=12
µM; C5= Kihigh=6 pM and Kilow=9 nM; C9=111 nM; C15=56 nM) similar to that of melatonin (Ki
= 2 nM) (Figure 9). Unlike the increases in ER binding sites observed for all drug conjugates at concentrations greater than 10 µM, no drug conjugates except for C5, produced an increase in 2-
[125I]-melatonin binding sites (~90% of control) at 100 µM (Figure 9D).
71
Figure 9: Competition of C2, C4, C5, C9, or C15 for 2-[125I]-iodomelatonin binding to
125 MT1Rs expressed in CHO cells. Competition of 2-[ I]-iodomelatonin for binding to MT1Rs expressed in CHO cells in the presence of melatonin (A and B) or conjugates C2, C4, C5, C9 or
C15) (Figures C-G). Data represent the mean ± SD of 3 independent experiments performed in duplicate. Figures B and D were taken from ((P.A. Witt-Enderby et al., 2014); US Patent
8,785,501).
72 4.7. Effects of C4 and C5 conjugates on TamR MCF-7 cells
Characterization of TamR cells revealed that the binding affinity and density of [3H]- estradiol did not change in TamR MCF-7 cells (KD=1.1 nM, Bmax=21.4 pmol/mg protein) versus
WT MCF-7 cells (KD=2.2 nM, Bmax=4.8 pmol/mg protein) even though ER expression was
decreased in TamR cells vs. WT cells (Figures 10A, 10B and 10C). Further characterization of
TamR MCF-7 by Schild plot analysis (Chapter 9: Appendix) revealed that the TamR MCF-7 cells
displayed tight ER/ERE complexation. Analysis of growth patterns of TamR cells revealed that
over 7 days, TamR cells grew at a faster rate and to a greater extent than WT MCF-7 cells in the
presence of 4-OH-tamoxifen (Figure 10C) and this was accompanied by a mesenchymal
phenotype (Figures 10D and 10E) perhaps due to an increase in pERK5 and a decrease in pERK1/2
(Figures 10A and 10B). These TamR MCF-7 cells are consistent with literature demonstrating low
ERα, high ERK5, and low ERK1/2 vs wildtype (Barbara A. Drew et al., 2012c; Mendes-Pereira
et al., 2012; Julie A. Vendrell et al., 2008a; Zhu et al., 2018).
C4 and C5 were then further tested for their anti-cancer actions in TamR MCF-7 cells.
Regarding viability, both C4 (IC50=4.27 µM; max inhibition = 83% of vehicle) and C5 (IC50=6.03
µM; max inhibition = 81% of vehicle) displayed similar potency and efficacy to inhibit TamR cell
viability (Figure 12A) while the controls were without effect except for tamoxifen which
demonstrated 27% inhibition of TamR cell viability compared to vehicle (Figure 12A). Regarding
migration (Figure 12B), both C4 (IC50=4.53 µM; max inhibition = 126%) and C5 (IC50=5.07 µM; max inhibition = 137%) exhibited similar potency and efficacy to inhibit TamR cell migration similar to melatonin (IC50=1.85 µM; max inhibition = 15%), tamoxifen (IC50=153.4 mM; max inhibition = 129%), or melatonin plus tamoxifen (IC50=12.19 mM; max inhibition = 161%); 4-
OH-tamoxifen was least potent and efficacious (IC50=19.11 µM; max inhibition = 50%).
73 Maximum inhibition greater than 100% indicates that the cells were detached from the plate or the
border width after 24 hr was wider than the 0 hr border width (Figure 12B).
Figure 10: Saturation of [3H]-estradiol binding to ERs expressed in WT (A) and TamR (B)
MCF-7 cells. Cell counting of WT and TamR MCF-7 cell lines treated with 100 nM of 4-OH-
tamoxifen (C). Each bar represents the total cell number (in ten thousand) expressed as mean ±
SD. ** P<0.001 day 7th WT MCF-7 cell number vs. day 1st WT MCF-7 cell number by one-way
ANOVA. *** P<0.001 day 3rd and day 7th TamR MCF-7 cell number vs. day 1st TamR MCF-7 cell number by one-way ANOVA. ## P<0.01 day 3rd TamR MCF-7 cell number vs. day 3rd WT
74 MCF-7 cell number by 2-way ANOVA with Bonferroni post hoc analysis. ### P<0.01 day 7th
TamR MCF-7 cell number vs. day 7th WT MCF-7 cell number by two-way ANOVA with
Bonferroni post hoc test. Immunocytochemistry images of WT MCF-7 (D) and TamR MCF-7 (E)
cells.
Figure 11: Basal levels of pERK5 (A), pERK1/2 (B), ERα (C), NF-κB (D), and pAKT (E) in
TamR MCF-7 and MCF-7 cells. Bands were quantified using Image Studio™ Lite Software (LI-
COR Biosciences, Lincoln, NE) and normalized against β-actin. Each bar represents the mean ±
SD of 3 independent experiments. Data were analyzed by a two-tailed t-test where a=p<0.05 vs.
TamR MCF-7. Representative blot images were included in each figure. The upper band indicates
the protein of interest and the lower band indicates the β-actin band.
75
Figure 12: Effect of C4, C5, melatonin, tamoxifen, 4-OH-tamoxifen, and unlinked melatonin+tamoxifen on TamR MCF-7 cell viability and cell migration. Data in (A) demonstrate the effect of C4, C5, melatonin, tamoxifen, 4-OH-tamoxifen, or unlinked melatonin+tamoxifen on TamR MCF-7 cell viability and cell migration (B). Data represent the mean ± SD of 3 independent experiments performed in duplicate.
4.8. Effects of C4 and C5 conjugates on TU-BcX-4IC cells and TU-BcX-4QAN tumor tissue
C4 and C5 were then tested for their anti-cancer actions in TU-BCx-4IC cells. Regarding viability, both C4 (IC50=181.5 mM; max inhibition=78% of vehicle) and C5 (IC50=304.2 mM; max
76 inhibition =65% of vehicle) displayed similar potency and efficacy to inhibit cell viability while
melatonin was without effect; and melatonin plus tamoxifen demonstrated 80% inhibition of cell
viability compared to the vehicle (Figure 13A). Regarding migration (Figure 13B), both C4
(IC50=211.1 µM; max inhibition = 145%) and C5 (IC50=80.38 µM; max inhibition =145%)
exhibited similar and greater potency and efficacy compared to melatonin (IC50=168.6 mM; max
inhibition=21%), tamoxifen (IC50=514.9 mM; max inhibition=159%), or melatonin plus tamoxifen (IC50=116.8 mM; max inhibition=155%). Maximum inhibition greater than 100%
indicates that the cells were detached from the plate or the border width after 24 hr was wider than
the 0 hr border width. In TU-BcX-4IC cells, western blot analysis data demonstrated that C4 and
C5 decreased pERK1/2 levels, and C5 increased NF-ᴋB with trends towards an increase occurring
with C4 (Figure 13C) similar to what occurred in the other triple-negative cells, MDA-MB-231
and BT-549 (Table 8). However, C4 and C5 had no significant effects on pERK5 levels in TU-
BcX-4IC cells (Figure 13C). Both conjugates did not change pERK1/2, pERK5, and NF-ᴋB levels
in PDX tumor tissue, although C4 and C5 trended towards a reduction in pERK5 levels (Figure
13C). Further characterization of the TU-BCx-4IC cells for melatonin binding sites or estrogen
binding sites revealed total specific binding of 2-[125I]-iodomelatonin (7.6 ± 3.9 fmol/mg protein) or [3H]-estradiol (117 ± 56 fmol/mg protein; Figure 13D).
77 Vehicle
A 150
100 *
(% Vehicle) 50 * * * Relative Abs. at 570nm at Abs. Relative 0 in in n n n n 4 4 4 4 5 5 5 en en e e e C C on if if if ifen C5 tonin ton xife xif xifen xifen M M C M C M C M C M a a lat latonin o o o ox ox o nM e e m m m m 1pM C1nM C41 0 0 1pM C51 1 am am a 1 10 Mel Mel M M T T TamoxTamoxTa Tamoxif 10 100 M M MelatoninM M +Ta nM M M M M n in+ 1p 1 1 1pM 1n 1 0 ni 10 10 o on tonin+T 100 10 la elat elatonin+Ta e M M Melat M M Melatonin+TamoxifenM M pM 1 1nM 1 10 00 1
78
79
Figure 13: Effect of C4, C5, melatonin, tamoxifen, 4-OH-tamoxifen, and unlinked
melatonin+tamoxifen on TU-BCx-4IC cell viability and cell migration and TU-BcX-4QAN
tumor tissue. Data demonstrate the effect of C4, C5, melatonin, tamoxifen, or unlinked
melatonin+tamoxifen on TU-BCx-4IC cell viability (A) and cell migration (B). Expression of
pERK1/2, pERK5, and NF-ᴋB were analyzed in TU-BcX-4QAN tumor tissue and TU-BCx-4IC
cells (C), and total specific binding of 2-[125I]-iodomelatonin or [3H]-estradiol was measured in
TU-BCx-4IC cells (D). Data represent the mean ± SD of 3 independent experiments performed in duplicate. Significance was defined as p<0.05. In A, B, (*) indicates significance from all
treatments except 100µM treatments for all groups. In (C), “a” indicates significance compared to vehicle and “b” indicates significance compared to 10µM melatonin. Images of cells in (A) and
(B) were exposed to vehicle or 100µM of treatment listed within each series of graphs.
80 4.9. Role of MEK1/2, MEK5 and PI3 kinases in mediating C4 and C5 effects
on BC cell viability and migration
MCF-7: MEK1/2, MEK5, and PI3K were chosen due to their role in BC cell viability and
migration. For example, inhibition of MAPK by MEK inhibitors demonstrated anti-invasive
properties in breast carcinoma cell lines (Katagiri et al., 2010). PD98059-mediated inhibition of
MEK1/2 decreased proliferation and promoted migration in MCF-7 and MDA-MB-231 cells via
dose- and time-dependent manner (Y. Zhao et al., 2017). The pro-survival protein, MEK5, was
found to be overexpressed in drug-resistant MCF-7 cells; and MEK5 was responsible for
chemoresistance and inhibition of apoptosis (Weldon et al., 2002). Furthermore, ERK5 was found
to be overexpressed in 25% of BC patients and in 84 tumor tissues examined, ERK5 was inversely
correlated with disease-free survival (Barbara A. Drew et al., 2012b). Several studies have shown
that PIK3CA mutation, an activating mutation, was found in 18-40% of BC patients (Isakoff et al.,
2005). This mutation was found to be a good predictor of the overall survival of HER2+ BC
patients (Vasan et al., 2019). Furthermore, the FDA approved alpelisib, a PI3K inhibitor in
combination with fulvestrant to treat advanced or metastatic breast cancer patients containing the
PIK3CA gene mutation ("First PI3K Inhibitor for Breast Cancer," 2019; Verret et al., 2019).
All inhibitors (PD98059, Bix02189, and pictilisib) attenuated MCF-7 (ER+) cell viability
on their own and when combined with C4 or C5, only pictilisib (PI3 kinase inhibitor) enhanced
C4- and C5-mediated MCF-7 cell viability while PD98059 and Bix02189 produced subtle (if any)
inhibitory effects (Figures 14A-14D, 18A). Regarding migration and when added alone, PD98059
and Bix02189 were without effect and pictilisib inhibited MCF-7 cell migration vs. vehicle. When
combined with C4, all inhibitors (PD98059, Bix02189, pictilisib) enhanced C4-mediated
inhibition of MCF-7 cell migration (Figures 14E, 14G) (See Figure 18B for schematic). For C5,
81 co-administration with PD98059 was without effect; co-administration with pictilisib enhanced the inhibitory effect of C5; and co-administration with Bix02189 blocked C5’s effects (Figures
14F, 14H; 18C).
Figure 14: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of
C4 or C5 in MCF-7 cells. Cell viability (A-D) and migration (E-H) of C4 or C5 in the absence or presence of PD98059, Bix02189, or pictilisib in MCF-7 cells Each point represents the mean ± SD
82 of 3 independent experiments. Data were analyzed by one-way ANOVA followed by Newman-
Keuls post-hoc t-test where significance was defined as p<0.05.
MMC: Bix02189 and PD98059 alone were without effect while pictilisib alone inhibited
MMC viability (Figure 15). Combination of Bix02189 (Figure 15A) or pictilisib (Figure 15C) with
C4 enhanced MMC viability. PD98059 added in combination with C4, blocked C4-mediated
MMC viability at C4 concentrations (1 pM-1 µM). C5 inhibited MMC viability, which was enhanced in the presence of Bix02189 (Figure 15B) or pictilisib (Figure 15D), but not PD98059
(Figure 15B). Regarding MMC migration, PD98059, Bix02189 (Figure 15E), or pictilisib (Figure
15G) each alone inhibited MMC migration; however, when combined with C4 only PD98059 and pictilisib enhanced C4’s inhibitory actions (Figure 18F). For C5, PD98059 and Bix02189 enhanced C5’s inhibitory actions on MMC migration at C5 concentrations ranging from 1 pM-1
µM where then no further enhancement occurred at higher (>1 µM) concentration of C5 (Figure
15F). Pictilisib enhanced C5-mediated MMC migration at all concentrations tested except the highest concentration of 100 µM (Figures 15H; 18G).
83
Figure 15: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of
C4 or C5 in MMC cells. Cell viability (A-D) and migration (E-H) of C4 or C5 in the absence or presence of PD98059, Bix02189, or pictilisib in MMC cells. Each point represents the mean ± SD
of 3 independent experiments. Data were analyzed by one-way ANOVA followed by Newman-
Keuls post-hoc t-test where significance was defined as p<0.05.
84 MDA-MB-231: No effect of the inhibitors occurred either alone or in combination with
C4 and C5 except for pictilisib, which inhibited MDA-MB-231 cell viability when added alone and when compared to vehicle (Figure 16). Only at one concentration (1 nM C5) did pictilisib block its effect (Figures 16C and 16D; 18H and 18I). Regarding migration, PD98059 and
Bix02189 alone were without effect while pictilisib inhibited cell migration vs. vehicle. When combined with C4, all inhibitors enhanced C4-mediated inhibition of cell migration (Figures 16E and 16G). For C5, pictilisib, added in combination with C5, enhanced cell migration while
PD98059 and Bix02189 blocked C5’s inhibitory effects (Figures 16F and 16H).
85
Figure 16: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of
C4 or C5 in MDA-MB-231 cells. Cell viability (A-D) and migration (E-H) of C4 or C5 in the
absence or presence of PD98059, Bix02189, or pictilisib in MDA-MB-231 cells. Each point represents the mean ± SD of 3 independent experiments. Data were analyzed by one-way ANOVA followed by Newman-Keuls post-hoc t-test where significance was defined as p<0.05.
86 BT-549: PD98059 or Bix02189 alone was without effect on BT-549 cell viability while
pictilisib alone produced some inhibitory effects. When added in combination with C4, all inhibitors slightly, albeit significantly, inhibited C4-mediated inhibition of BT-549 viability at C4 concentrations higher than 1 µM and for C5, the same occurred in the presence of Bix02189 or pictilisib but not PD98059 (Figures 17A-17D and 18J). For migration, PD98059 and Bix02189 alone were without effect while pictilisib inhibited BT-549 cell migration (vs. vehicle). When co- administered with Bix02189 or pictilisib but not PD98059, C4-mediated effects on BT-549 cell migration was enhanced (Figures 17E-17H and 18K). Pictilisib, added in combination with C4 or
C5, enhanced their inhibitory effects on BT-549 cell migration while PD98059 was without effect
(Figures 17G and 17H). The same findings occurred for C5 except that Bix02189 blocked—not enhanced—the inhibitory effect of C5 on BT-549 cell migration (Figures 17E and 17F).
87
Figure 17: Effect of MEK1/2, MEK5, or PI3K inhibitors on cell viability and migration of
C4 or C5 in BT-549 cells. Cell viability (A-D) and migration (E-H) of C4 or C5 in the absence or presence of PD98059, Bix02189, or pictilisib in BT-549 cells. Each point represents the mean ±
SD of 3 independent experiments. Data were analyzed by one-way ANOVA followed by
Newman-Keuls post-hoc t-test where significance was defined as p<0.05.
88 4.10. Effect of C4 and C5 melatonin-tamoxifen drug conjugates on pERK5,
pERK1/2, pAKT, NF-κB, RUNX2, and β1-INTEGRIN protein levels
To identify the signaling proteins/cascades involved in C4- or C5-mediated inhibition of breast cancer, western blot analysis was performed in each cell line under basal (unstimulated) conditions; or following 15 min exposure to each conjugate (C4 or C5) alone or in combination
with PD98059 (MEK1/2 inhibitor), Bix02189 (MEK5 inhibitor) or pictilisib (PI3 kinase inhibitor).
Treatment effects on pERK1/2, pERK5, pAKT, RUNX2, NF-ĸB, and β1-INTEGRIN were
analyzed. Due to the enormity and complexity of the analyses, all data are presented in Tables 9-
15 and schematics are shown in Figure 18 (indicated in blue) for clarity, whereas significant
changes in protein levels were mentioned in Table 8.
89
ailed t-tests Data represent a, b, c, etc.) indicate a, b, c, etc.) indicate protein of interest and and of interest protein ayed in Table 8 and Table ayed in s on s on pERK1/2, pERK5, pAKT, Bands were quantified using Image Studio™ Studio™ Image using quantified were Bands e each table where lower-case letters (e.g., lower-case letters where each table e The data were then normalized against -actin. against -actin. normalized then data were The tilisib) on C4/C5-mediated effect t-test. The upper-case letters (e.g., A, B, C) indicate two-t C) upper-caseA, B, t-test. The letters (e.g., Tables 9-12. (NS indicates not significant). Upper band indicates band Upper significant). not indicates (NS 9-12. Tables MCF-7, MMC, MDA-MB-231, and BT-549 cell lines. ments. The lettering scheme is shown abov lettering scheme ments. The NE), where relative OD values were obtained. obtained. were values OD relative where NE), -actin band. band. -actin β 1-INTEGRIN levels in β The The effect of MEK1/2 (PD98059), MEK5 (Bix02189) and PI3K (pic
B, RUNX2, ĸ Lite (LI-COR Biosciences, Lincoln, Lite (LI-COR Table 8: the mean ± SD of three independent experi ± SD of three independent the mean hoc post Newman-Keuls by followed ANOVA one-way by done analysis displ are values Significant p<0.05. as defined was significance where t-tests, one-tailed indicate $) *, (#, symbols the while datacomplete presented sets alongwith theirare analyses in the band indicates lower NF-
90 91 92
93 In general, the major findings of the western blot analyses for MCF-7 cells demonstrate
that all three pathways (MEK1/2, MEK5, PI3 kinase), when inhibited by PD98059, Bix02189, or pictilisib, respectively, enhance the inhibitory effects of C4 on MCF-7 viability and migration and
cross-talk (mainly inhibitory actions) between MEK/pERK1/2 and MEK5/pERK5 occurs. This
cross-talk between MAPK members has been demonstrated in other reports too (B. A. Drew et al.,
2012a; Lochhead et al., 2016). For C5, although both MEK1/2 and PI3 kinase pathways lay parallel
to and enhance the inhibitory effects of C5 when inhibited by PD98059 and pictilisib, respectively,
it was MEK5 that was critical in mediating C5’s actions on MCF-7 viability and migration.
RUNX2 expression was inhibited in the presence of C4 and C4 plus pictilisib. β1-INTEGRIN
expression levels were not significantly changed in the presence of C4 or C5 (Tables 9-12; Figures
19A-19C).
For MMC (HER2+) breast cancer cells, the western blot analysis revealed that the
MEK1/2/pERK1/2 pathway appeared to play a more central role possibly through co-modulation
of NF-ĸB, pERK5, and β1-INTEGRIN. Western blot analyses revealed that C5 activated (1 nM)
or inhibited (10 µM) NF-ĸB or β1-INTEGRIN levels that were concentration-dependent (see blue
dotted lines; Figures 18E, 18G). For C5, the inhibitor analysis revealed that crosstalk between
MEK1/2/pERK1/2 and MEK5/pERK5 occurred and that inhibition of pERK5 may be through a
MEK1/2/pERK1/2-mediated inhibition of MEK5 (Figure 18G). No effect of C4 or C5 on RUNX2
expression was observed (Tables 9-12).
For the triple-negative breast cancer line, MDA-MB-231 cells, relationships between PI3
kinase/pERK1/2 and MEK5/pERK5 on NF-ĸB expression were observed where pictilisib
inhibited pERK1/2 levels and Bix02189 increased NF-ĸB expression (Figure 18H). C5 increased
NF-ĸB and β1-INTEGRIN levels, whereas MEK1/2-mediated crosstalk with MEK5/pERK5
94 occurred and PI3 kinase-mediated modulation of NF-ĸB, RUNX2, and β1-integrin was observed
(Figure 18I).
For BT-549 triple-negative breast cancer cells, the MEK5/pERK5 and PI3 kinase signaling pathways lay parallel to and facilitated the inhibitory actions of C4 in the presence of Bix02189 and pictilisib, respectively, possibly by modulating pERK1/2 as revealed through western blot analysis (Table 8; Figure 18K); PD98059 alone inhibited BT-549 cell migration and these effects may be mediated through NF-ĸB (Figure 18K). For C5, western blot analysis revealed that C5 modulates NF-ĸB; however how NF-ĸB fits into these signaling cascades remains unclear and needs further study (Figure 18L). MEK/1/2 inhibition by PD98059 inhibited BT-549 migration and these effects are likely mediated through inhibition of pERK1/2 revealed by western blot analysis. No effect of C4 or C5 on β1-integrin or RUNX2 expression occurred in these cells
(Tables 9-12; Figure 18L).
95
Figure 18: Summary of mechanisms of action underlying C4 or C5 in breast cancer cells.
Depicted is a summary of the mechanisms of action underlying C4 (A, B, D, F, H, J, K) or C5 (C,
E, G, I, J, L) in MCF-7 (A-C), MMC (D-G), MDA-MB-231 (H, I) or BT-549 (J-L) BC cells. The lines connecting the proteins indicated in black were the relationships deduced from the viability and migration assays and the lines indicated in blue derived from the western blot analyses.
96 1 nM C5+10 µM PD98059 0.0021±0.0 01 ($C) 5 3 0.0077±0.0 11 0.012±0.00 9 ($C) 1 nM C5+PD 0.013±0.00 6 4 0.0018±0.0 03 0.16±0.041 0.16±0.041 0.0008±0.0 005 1 nM C5+PD 0.00098±0. 0008 1 nM C5+PD 0.011±0.01 8 0.017±0.00 7 1-INTEGRIN levels in MCF- 1-INTEGRIN β 1 nM C4+10 1 nM C4+10 µM PD98059 0.0012±0.00 1 0.031±0.00 0.016±0.022 0.078±0.03 0.067±0.022 0.0067±0.00 7 0.014±0.005 (#B) C4+PD 0.014±0.001 (#B) 0.058±0.03 0.07±0.008 0.0085±0.01 0 (#B) 0.093±0.037 (#) 0.13±0.046 0.00073±0.0 002 C4+PD 0.00046±0.0 001 C4+PD t-test. The A, letters (e.g., upper-case lettering scheme is shown above each lettering scheme is shown B, RUNX2, 0.05. 0.05. ĸ 10 µM PD98059 0.00039±0. 0005 (*A) 8 3 0.0066±0.0 04 2 10 µM PD 1 nM 0.0082±0.0 03 (*) 0.011±0.00 7 (*) 0.085±0.01 9 0.00074±0. 0003 10 µM PD 1 nM 0.00072±0. 0005 10 µM PD 1 nM 0.0094±0.0 09 0.013±0.015 9 0.054±0.023 0.03±0.028 0.03±0.028 0.047±0.01 9 0.054±0.023 0.016±0.00 5 0.014±0.007 Biosciences, Lincoln, NE), where relative OD values were OD values relative where NE), Lincoln, Biosciences, 0.078 0.12±0.036 0.14±0.016 0.12±0.036 0.078 1nM C5+10 µM Bix02189 1 ($C) 9 1 nM C5+BIX 0.0044±0.00 6 ($C) 0.06±0.035 0.078±0.015 004 0.0013±0.00 1 1 nM C5+BIX 1 nM C5+BIX of three independent experiments. The experiments. The of three independent 1 nM C4+10 1 nM C4+10 µM Bix02189 0.0018±0.001 0.0022±0.00 0.0018±0.001 0.038±0.0012 0.055±0.022 0.035±0.02 0.055±0.022 0.038±0.0012 0.085±0.02 0.099±0.052 0.09±0.032 0.0081±0.00 0.0078±0.009 C4+BIX 0.015±0.007 0.018±0.007 0.015±0.007 0.093±0.008 (#) 0.0014±0.001 0.00084±0.0 0.0014±0.001 0.00048±0.00 04 C4+BIX 0.027±0.01 0.049±0.011 0.038±0.005 C4+BIX ANOVA followed by Newman-Keuls post hoc post hoc Newman-Keuls by ANOVA followed 10 µM Bix02189 0.004±0.00 2 (*A) 0.044±0.03 8 0.091±0.05 3 0.0088±0.0 09 10 µM BIX 1 nM 0.0087±0.0 08 0.0042±0.007 0.0076±0.0 05 0.071±0.05 9 0.2±0.220 0.13±0.067 0.1± 0.062±0.04 7 (*) 0.035±0.003 0.06±0.005 0.00081±0. 0001 0.00065±0. 0004 0±0 0±0 0.000063± 0.0001 10 µM BIX 1 nM 0.039±0.01 5 10 µM BIX 1 nM 0.023±0.007 0.042±0.02 1 0.033±0.006 3 0.091±0.016 0.065±0.005 0.065±0.005 0.079±0.01 3 0.091±0.016 7 0.018±0.006 0.014±0.001 0.014±0.001 0.016±0.00 7 0.018±0.006 on C4-mediated effects on pERK1/2, pERK5, NF- on on C4-mediated effects 1 nM C5 ($C) 0.0093±0. 003 (*A) 0.051±0.0 27 0.14±0.07 4 (*A) 0.010±0.0 11 1 nM C5 ($C) 0.0091±0. 005 0.005±0.0 01 0.079±0.0 53 8 0.043±0.0 12 0.00079±0 .0003 0.00062±0 .0002 1 nM C5 ($C) 0.063±0.0 21 1 nM C5 ($C) 0.033±0.0 012 0.076±0.0 13 0.016±0.0 02 -actin. Data represent the mean ± SD the mean Data represent -actin. Bands were quantified using Image Studio™ Lite (LI-COR Lite (LI-COR Studio™ using Image quantified Bands were β indicate analysis done by one-way C4(#B) 0.018±0.0 24 0.31±0.42 1 0.085±0.0 56 0.043±0.0 69 C4(#B) 0.0029±0. 002 0.0054±0. 001 0.05±0.01 8 0.12±0.03 0.1±0.010 0.032±0.0 18 0.00049±0 .0005 0.00073±0 .0003 C4(#B) 0.051±0.0 18 C4(#B) 0.029±0.0 12 0.07±0.01 1 0.013±0.0 008 .g., a, b, c, etc.) etc.) .g., a, b, c, Veh (*A) 1 nM .001 .001 2 30 005 Veh (*A) 1 nM 006 0.0092±0. 004 27 1 21 .0002 .0002 .0003 Veh (*A) 1 nM 17 Veh (*A) 1 nM 0±0 .0006 0±0 14 19 11 231 549 BT- MB- MMC MDA- MCF-7 B 0.045±0.0 B 0.12±0.05 B 0.022±0.0 B 0.058±0.0 κ κ κ κ The effect of MEK1/2 (PD98059) and MEK5 (Bix02189) and MEK5 (Bix02189) (PD98059) MEK1/2 of The effect
pERK1/2 0.00092±0 pERK5 0.02±0.02 NF- RUNX2 0.0048±0. pERK5 0.0028±0. pERK1/2 pERK5 0.041±0.0 NF- NF- RUNX2 0.00041±0 RUNX2 0.00049±0 pERK5 0.018±0.0 pERK1/2 0.038±0.0 pERK1/2 0.00033±0 NF- RUNX2 0.013±0.0 B, C) indicate two-tailed t-tests while the symbols (#, *, $) indicate one-tailed t-tests, where significance was defined as p< was defined significance where t-tests, one-tailed $) indicate *, (#, symbols the while t-tests two-tailed indicate B, C) table where lower-case letters (e lower-case table where Table 9: 7, MMC, MDA-MB-231, and BT-549 cell lines. 7, MMC, MDA-MB-231, and BT-549 against normalized then The data were obtained.
97 1 03 02 ($C) 10 µM 10 µM 10 µM C5+PD C5+PD C5+PD 0.014±0.003 0.014±0.004 0.014±0.004 µM PD98059 0.00048±0.00 0.00075±0.00 0.0021±0.002 0.0021±0.002 0.00079±0.00 10 µM C5+10 1-INTEGRIN levels in 1-INTEGRIN levels β 2 3 oln, NE), where relative OD values 0±0 0±0 ($) 0±0 (#B) ($C) e lettering scheme is shown above each each above shown is scheme e lettering t-test. The upper-case letters (e.g., A, B, (e.g., letters The upper-case t-test. 0.096±0.019 0.072±0.005 0.072±0.005 0.096±0.019 0.032±0.028 0.023±0.020 0.023±0.020 0.032±0.028 0.032±0.011 0.032±0.011 0.11±0.033 0.096±0.023 0.014±0.004 0.0061±0.002 0.0061±0.002 0.014±0.004 0.019±0.007 0.014±0.010 0.014±0.010 0.019±0.007 0.018±0.001 0.018±0.006 µM PD98059 0.0064±0.004 0.0052±0.007 0.0052±0.007 0.0064±0.004 0.001±0.0003 0.001±0.0003 10 µM C4+10 0.00059±0.000 0.00023±0.000 B, RUNX2 and ĸ 5. 035 0.043±0.042 0.043±0.042 035 0.067±0.009 8 2 7 9 5 04 09 03 0005 0005 0003 3 (*A) 9 (*A) 10 µM PD98059 10 µM PD 10 µM C4+PD 10 µM PD 10 µM C4+PD 10 µM PD 10 µM C4+PD 0.00039±0. 0.085±0.02 0.035±0.02 0.0066±0.0 0.027±0.01 0.011±0.00 0.0094±0.0 0.085±0.01 0.00072±0. 0.047±0.01 0.12±0.036 0.14±0.026 0.14±0.026 0.12±0.036 0.13±0.026 0.00074±0. 0.0082±0.0 0.016±0.00 1 7 2 3 001 006 10 µM 10 µM 10 µM 10 µM ree independent experiments. ree independent Th C5+BIX C5+BIX C5+BIX Bix02189 C5+10 µM 0.0028±0.00 0.0072±0.00 0.013±0.010 0.013±0.010 0.00074±0.0 0.00069±0.0 0.0052±0.00 0.0097±0.00 udio™ Lite (LI-COR Biosciences, Linc Biosciences, (LI-COR Lite udio™ 1 7 3 2 001 005 0±0 0±0 0±0 0±0 0±0 0±0 10 µM 10 µM 10 µM 10 µM ANOVA followed by Newman-Keuls post hoc post hoc Newman-Keuls by ANOVA followed C4+BIX C4+BIX C4+BIX where significance was defined as p<0.0 defined was where significance Bix02189 C4+10 µM 0.12±0.028 0.11±0.011 0.11±0.011 0.12±0.028 0.08±0.015 0.065±0.016 0.065±0.016 0.08±0.015 0.0039±0.00 0.043±0.032 0.035±0.038 0.035±0.038 0.043±0.032 0.0085±0.00 0.032±0.017 0.037±0.011 0.037±0.011 0.032±0.017 0.0091±0.00 0.083±0.008 0.072±0.038 0.072±0.038 0.083±0.008 0.00095±0.0 0.043±0.022 0.075±0.063 0.06±0. 0.075±0.063 0.043±0.022 0.00063±0.0 0.0045±0.00 0.026±0.002 0.026±0.002 0.029±0.008 0.03±0.015 0.03±0.015 0.029±0.008 on C5-mediated effects on pERK1/2, pERK5, NF- on on C5-mediated effects 2 3 8 5 7 3 9 1 7 09 08 05 (*A) 0004 0001 .0001 .0001 represent the mean ± SD of th of ± SD mean the represent 10 µM Bix02189 0.004±0.00 0.091±0.05 0.044±0.03 0.0088±0.0 0.039±0.01 0.0087±0.0 0.062±0.04 0.00065±0. 0.079±0.01 0.13±0.067 0.071±0.076 0.097±0.026 0.097±0.026 0.071±0.076 0.13±0.067 0.071±0.05 0.00081±0. 0.0076±0.0 0.042±0.02 0.016±0.00 10 µM BIX 10 µM BIX 10 µM BIX 0.000063±0 Bands were quantified using Image St Bands were quantified 7 9 5 3 43 06 17 31 22 (*) 003 004 004 ($C) ($C) ($C) ($C) .0003 .0003 .0003 .0003 8 (*A) 0.0047±0. 0.01±0.00 0.13±0.06 0.032±0.0 0.033±0.0 0.0071±0. 0.054±0.0 0.08±0.03 0.16±0.14 0.023±0.0 0.0053±0. 0.026±0.0 0.02±0.00 10 µM C5 10 µM C5 10 µM C5 10 µM C5 0.00047±0 0.00073±0 indicate analysis done by one-way 5 09 64 26 03 37 64 11 03 004 007 0±0 mbols (#, *, $) indicate one-tailed t-tests, one-tailed indicate $) *, (#, mbols (#B) (#B) (#B) (#B) (*A) .0004 .0004 .0002 .0002 55 (*) 55 (*) 5 (*A) 0.0042±0. 0.012±0.0 0.16±0.08 0.072±0.0 0.026±0.0 0.004±0.0 0.043±0.0 0.091±0.0 0.15±0.11 0.067±0.0 0.0084±0. 0.021±0.0 0.019±0.0 10 µM C4 10 µM C4 10 µM C4 10 µM C4 0.00049±0 0.00075±0 .g., a, b, c, etc.) etc.) .g., a, b, c, 2 1 30 17 21 19 27 14 11 005 006 004 .0006 .0006 .0003 .0003 .0002 .0002 .0006 .0006 Veh (*A) Veh (*A) Veh (*A) Veh (*A) 0.0048±0. 0.045±0.0 0.02±0.02 0.038±0.0 0.0028±0. 0.022±0.0 0.058±0.0 0.12±0.05 0.041±0.0 0.0092±0. 0.018±0.0 0.013±0.0 0.00092±0 0.00049±0 0.00041±0 0.00033±0 7 549 231 BT- MB- MCF- MMC MDA- The effect of MEK1/2 (PD98059) and MEK5 (Bix02189) MEK5 (Bix02189) (PD98059) and of MEK1/2 The effect
B B B B κ κ κ κ
2 2 2 2 NF- NF- NF- NF- pERK5 pERK5 pERK5 pERK5 pERK1/ pERK1/ pERK1/ pERK1/ RUNX2 RUNX2 RUNX2 RUNX2 C) indicate two-tailed t-tests while the sy the while t-tests two-tailed C) indicate MCF-7, MMC, MDA-MB-231, and BT-549 cell lines. MDA-MB-231, MCF-7, MMC, Table 10: were obtained. The data were then normalized against -actin. Data -actin. against normalized then were data The were obtained. table where lower-case letters (e lower-case table where
98 data er-case er-case each table where low where table each letters (e.g., A, B, C) indicate two-tailed t- two-tailed indicate C) B, A, (e.g., letters 0.029 0.12±0.034 0.015 0.23±0.056 0.17 0.50±0.15 heme is shown above heme 0.0014±0.0011 ($C) 0.0014±0.0011 ($C) 0.0029±0.00076 0.00056±0.00098 0.00054±0.00059 0.00054±0.00059 0.00056±0.00098 0.00063±0.0005 ($) 0.00085±0.0012 0.12±0.04 0.15±0.04 0.0033±0.0020 0.0033±0.0020 0.0038±0.0008 0.004±0.0004 0.004±0.0004 0.0046±0.0003 0.0033±0.0018 0.0033±0.0018 0.0033±0.0030 0.00023±0.00041 0.00023±0.00041 0.0040±0.0047 1-INTEGRIN and pAKT levels in MCF-7, MMC, MDA- MMC, MCF-7, 1-INTEGRIN and in pAKT levels β 00019 0.0020±0.00052 0.0020±0.00052 00019 0.00092±0.00018 37±0.085 (*A) 37±0.085 (*A) 0.33±0.095 0.39±0.12 0.089±0.033 0.11±0.030 0.11±0.030 0.089±0.033 0.08±0.032 10 µM C4 ($C) 10 µM C4 ($C) 10 µM C4+pictilisib pictilisib 10 µM C4 ($C) 10 µM C4+pictilisib 0.00018±0.00024 pictilisib 0.00058±0.0005 6 0.00028±0.00031 10 µM C4 ($C) 10 µM C4 ($C) 10 µM C4+pictilisib pictilisib 0.19±0.06 0.24±0.09 0.22±0.01 2 10 µM C4 ($C) 10 µM C4 ($C) 10 µM C4+pictilisib pictilisib 0.59±0.43 0.46±0.049 0.46±0.049 0.59±0.43 0.75±0.45 B, RUNX2, к 0.17±0.075 0.16± 0.17±0.075 0.19±0.03 0.22± 0.34±0.21 0.34± 0003 0.00084±0.001 0.0015±0.001 0.0015±0.001 0.00084±0.001 0003 0.0021±0.001 0013 0.0038±0.0025 0.0019±0.0009 0.0019±0.0009 0.0038±0.0025 0013 0.0014±0.0007 013 0.030±0.019 0.035±0.022 0.035±0.022 0.030±0.019 013 0.015±0.020 01 0.072±0.02 0.079±0.03 0.079±0.03 0.072±0.02 01 0.083±0.05 048 0.26±0.077 (*) 0.23±0.030 0.23±0.030 0.24±0.095 (*) 0.26±0.077 048 11 0.43±0.30 0.36±0.069 0.36±0.069 0.43±0.30 11 0.57±0.34 Lite (LI-COR Biosciences, Lincoln, NE), where relative OD values were obtained. The The were obtained. OD values relative where NE), Lincoln, Biosciences, (LI-COR Lite C4+pictlisib C4+pictlisib C4+pictlisib C4+pictlisib C4+pictlisib 0.00030±0.0003 0.00060±0.00052 (#B) 0.0036±0.0052 0.0023±0.0021 0±0 0.0023±0.0021 C4+pictlisib 0.0021±0.0003 (#B) 0.0036±0.0052 ree independent experiments. The lettering sc lettering The experiments. independent ree 0.0022±0.0012 0.0025±0.0012 0.0025±0.0012 0.0022±0.0012 significance was defined as p<0.05. as p<0.05. defined significance was 0020 0.0032±0.0018 0.0039±0.0022 0.0032±0.0018 0020 0.0023±0.00095 0.0025±0.0018 0018 0027 0.0065±0.0019 0.0055±0.0008 0.0065±0.0019 0027 0025 0.0043±0.0024 0.0050±0.0035 0.0043±0.0024 0025 0016 0.0014±0.0020 0.0013±0.0022 0.0014±0.0020 0016 0.19±0.02 0.15±0.02 (*A) 0.15±0.02 0.19±0.02 0.0013±0.00015 0.0020±0.0001 0.0016±0. 0.0020±0.0001 0.0013±0.00015 0.000029±0.00005 1 C4-mediated effects on pERK1/2, pERK5, NF- on pERK1/2, effects C4-mediated Veh (*A) 1 nM C4 (#B) 1 nM 0.00030±0.00022 6 12 0.00077±0.0012 Veh (*A) 1 nM C4 (#B) 1 nM Veh (*A) 1 nM C4 (#B) 1 nM 5 Veh (*A) 1 nM C4 (#B) 1 nM 0.00087±0.0015 0.00018±0.00032 0.00018±0.00032 0.00087±0.0015 Bands were quantified using Image Studio™ Studio™ using Image quantified Bands were indicate one-tailed t-tests, where t-tests, indicate one-tailed -actin. Data represent the mean ± SD of th the mean ± SD Data represent -actin. β 231 MB- MMC MDA- MCF-7 BT-549 B 0.093±0.03 0.085±0.026 0.10±0.042 0.10±0.042 0.085±0.026 B 0.093±0.03 B 0. 0.35±0.12 0.34±0.043 0.36±0.11 B 0.19±0.11 0.36±0.12 0.29±0.10 0.29±0.10 0.36±0.12 B 0.19±0.11 B 0.54±0.25 0.83±0.53 0.50±0.091 0.50±0.091 0.83±0.53 B 0.54±0.25 κ κ κ κ 1-INTEGRIN 0.022±0.009 0.025±0.020 0.036±0. 0.025±0.020 1-INTEGRIN 0.022±0.009 1-INTEGRIN 0.25±0.085 0.23±0.028 0.23±0. 0.23±0.028 1-INTEGRIN 0.25±0.085 1-INTEGRIN 0.13±0.05 0.14±0.10 0.094±0. 0.14±0.10 1-INTEGRIN 0.13±0.05 1-INTEGRIN 0.38±0.21 0.58±0.48 0.35±0. 0.58±0.48 1-INTEGRIN 0.38±0.21
RUNX2 0.16±0.055 0.11±0.002 0.12±0.019 0.11±0.002 RUNX2 0.16±0.055 β pERK1/2 0.0017±0.0009 0.0010±0.0003 0.0010±0. 0.0010±0.0003 0.0023±0. pERK1/2 0.0017±0.0009 pERK5 0.0038±0.0021 0.0021±0. pERK1/2 0.0024±0.0017 pERK5 0.00092±0.0007 p-AKT 0.000049±0.000 NF- RUNX2 0.22±0.039 0.20±0.041 0.21±0.005 0.20±0.041 RUNX2 0.22±0.039 β
pERK1/2 0.0039±0.0031 0.0021±0.0021 0.0018±0. 0.0021±0.0021 0.0082±0. pERK1/2 0.0039±0.0031 0.17±0.04 pERK5 0.0054±0.0025 RUNX2 0.19±0.04 β p-AKT 0.00018±0.0004 NF- pERK5 0.0051±0.0026 0.0067±0. pERK1/2 pERK5 0.0051±0.0026 p-AKT 0.00094±0.0008 0.0030±0.0011 p-AKT 0.00094±0.0008 NF- β p-AKT 0.00089±0.0013 0.0020±0. 0.27±0.077 0.45±0.30 p-AKT 0.00089±0.0013 RUNX2 0.31±0.10 NF- MB-231, and BT-549 cell lines. MB-231, and BT-549 against normalized were then The upper-case t-test. hoc post Newman-Keuls followed by one-way ANOVA by done analysis indicate etc.) c, b, a, (e.g., letters $) *, (#, symbols the tests while Table 11: The effect of PI3K (pictilisib) on of PI3K (pictilisib) Table 11: The effect
99 data er-case er-case pictilisib (d) (d) pictilisib pictilisib (d) (d) pictilisib pictilisib (d) (d) pictilisib pictilisib (d) (d) pictilisib each table where low where table each 0.034 0.23±0.056 0.17 0.50±0.15 0.10 0.15±0.04 C5+pictilisib C5+pictilisib C5+pictilisib C5+pictilisib 0.000073±0.00007 5 0.00018±0.00024 C5+pictilisib C5+pictilisib C5+pictilisib C5+pictilisib letters (e.g., A, B, C) indicate two-tailed t- two-tailed indicate C) B, A, (e.g., letters 0.00063±0.0010 0.0040±0.0047 0.0040±0.0047 0.00063±0.0010 0.0013±0.0006 0.00085±0.0012 0.00085±0.0012 0.0013±0.0006 0.0022±0.00038 0.00092±0.00018 0.00092±0.00018 0.0022±0.00038 0.0039±0.0010 0.0038±0.0008 0.0038±0.0008 0.00054±0.00059 0.0039±0.0010 0.00071±0.00096 0.0094±0.0050 0.0046±0.0003 0.0046±0.0003 0.0094±0.0050 heme is shown above heme 1-INTEGRIN and pAKT levels in MCF-7, MMC, MDA- MMC, MCF-7, 1-INTEGRIN and in pAKT levels β 0.58±0.46 0.57±0.39 0.75±0.45 0.75±0.45 0.57±0.39 0.58±0.46 0.27±0.16 0.65±0.43 0.22±0.01 0.22±0.01 0.65±0.43 0.27±0.16 B, RUNX2, bd) 0.14±0.028 0.14±0.028 bd) 0.16±0.060 0.08±0.032 (#B) 0.061±0.010 (*) (*) 0.073±0.037 0.015±0.020 0.15±0.069 (#) 0.061±0.010 (#B) 0.17±0.077 0.12±0.034 к 0.22±0.066 0.20± 0015 0015 0.0029±0.00076 0.0029±0.0015 0.0021±0.00082 0027 0.0022±0.0010 0.0013±0.0006 0.0021±0.0010 0.0021±0.0010 0.0013±0.0006 0.0022±0.0010 0027 0049 0.0062±0.0061 0.0057±0.0061 0.0033±0.0030 0.0033±0.0030 0.0057±0.0061 0.0062±0.0061 0049 0018 0.0026±0.0013 0.0031±0.0015 0.0014±0.0007 0.0014±0.0007 0.0031±0.0015 0.0026±0.0013 0018 0.34±0.12 0.36±0.072 0.39±0.12 0.39±0.12 0.36±0.072 0.34±0.12 0.36±0.22 0.38± 0.16±0.05 0.21± 0.0014 0.00055±0.0009 0.00063±0.0011 0±0 0.00063±0.0011 0.00055±0.0009 0.0014 03 0.082±0.01 0.22±0.17 0.083±0.05 0.083±0.05 0.22±0.17 0.082±0.01 03 42 0.43±0.33 0.40±0.30 0.57±0.34 0.57±0.34 0.40±0.30 0.43±0.33 42 0.13 0.22±0.088 0.24±0.043 0.24±0.095 0.24±0.095 0.24±0.043 0.22±0.088 0.13 0.00019±0.00033 0.00025±0.00041 0.00025±0.00041 0.00019±0.00033 Lite (LI-COR Biosciences, Lincoln, NE), where relative OD values were obtained. The The were obtained. OD values relative where NE), Lincoln, Biosciences, (LI-COR Lite ree independent experiments. The lettering sc lettering The experiments. independent ree 00038 0.0015±0.0026 0.0015±0.0026 00038 0.00071±0.0012 00080 0.0047±0.0021 0.0020±0.0012 0.0047±0.0021 00080 0004 0.0037±0.0026 0.0034±0.0007 0.0037±0.0026 0004 0.0013±0.0019 0.0017±0.0022 0011 0049 0.0090±0.0040 0.0090±0.0048 0.0090±0.0040 0049 0.00040±0.0006 0.00068±0.0007 0018 significance was defined as p<0.05. as p<0.05. defined significance was ediated effects on pERK1/2, pERK5, NF- on pERK1/2, ediated effects Veh (*A) 1 nM C5 (#B) 1 nM C5+pictlisib 10 µM C5 ($C) 10 µM Veh (*A) 1nM C5 (#B) 1 nM C5+pictlisib 10 µM C5 ($C) 10 µM 0.000049±0.00012 0.00037±0.00035 0.00037±0.00035 0.000049±0.00012 Veh (*A) 1 nM C5 (#B) 1 nM C5+pictlisib 10 µM C5 ($C) 10 µM Veh (*A) 1 nM C5 (#B) 1 nM C5+pictlisib 10 µM C5 ($C) 10 µM Bands were quantified using Image Studio™ Studio™ using Image quantified Bands were indicate one-tailed t-tests, where t-tests, indicate one-tailed -actin. Data represent the mean ± SD of th the mean ± SD Data represent -actin. β MMC MDA- MCF-7 BT-549 MB-231 The effect of PI3K (pictilisib) on C5-m of PI3K (pictilisib) The effect
B 0.093±0.030 0.19±0.072 (a) 0.27±0.063 ( B 0.36±0.11 0.46±0.045 (*A) 0.38±0.16 (*A) 0.46±0.045 B 0.36±0.11 B 0.54±0.25 0.51±0.22 0.59±0.65 0.59±0.65 0.51±0.22 B 0.54±0.25 B 0.19±0.11 0.27±0.14 0.38±0.25 0.38±0.25 0.27±0.14 B 0.19±0.11 κ κ κ κ 1-INTEGRIN 0.022±0.009 0.037±0.021 0.11±0.011 0.037±0.021 1-INTEGRIN 0.022±0.009 1-INTEGRIN 0.25±0.085 0.33±0.07 (*) 0.29± (*) 0.33±0.07 1-INTEGRIN 0.25±0.085 1-INTEGRIN 0.38±0.21 0.40±0.18 0.41±0. 0.40±0.18 1-INTEGRIN 0.38±0.21 1-INTEGRIN 0.069±0. 0.070±0.05 0.13±0.05 RUNX2 0.16±0.055 0.19±0.025 0.22±0.042 0.19±0.025 RUNX2 0.16±0.055 β pERK1/2 0.00087±0.0015 0.00097±0.0014 0.00099± 0.00097±0.0014 pERK1/2 0.00087±0.0015
p-AKT NF- pERK5 0.00092±0.00076 0.0020±0. pERK1/2 pERK5 0.00092±0.00076 0.0013±0. 0.0022±0.00038 0.0024±0.0017 β RUNX2 0.22±0.039 0.23±0.02 0.20±0.061 0.23±0.02 RUNX2 0.22±0.039 β RUNX2 0.31±0.10 0.24±0.024 0.29±0.25 p-AKT 0.00018±0.00045 0.0012±0. p-AKT 0.00018±0.00045 NF- pERK1/2 0.0017±0.0009 0.0020±0.0004 0.0029±0. 0.0020±0.0004 0.0042±0. pERK1/2 0.0017±0.0009 pERK5 0.0038±0.0021 NF- pERK5 0.0051±0.0026 0.0026±0.0017 (*A) 0.0040±0. (*A) 0.0026±0.0017 pERK5 0.0051±0.0026 p-AKT 0.00089±0.0013 0.00027±0. p-AKT 0.00089±0.0013 β RUNX2 0.19±0.04 0.16±0.07 0.18±0.09 0.16±0.07 RUNX2 0.19±0.04
p-AKT 0.00094±0.0008 0.0022±0. p-AKT 0.00094±0.0008 NF- pERK1/2 0.0039±0.0031 0.0019±0.0018 0.0031±0. 0.0019±0.0018 0.0084±0. pERK1/2 0.0039±0.0031 pERK5 0.0054±0.0025 Table 12: MB-231, and BT-549 cell lines. MB-231, and BT-549 against normalized were then The upper-case t-test. hoc post Newman-Keuls followed by one-way ANOVA by done analysis indicate etc.) c, b, a, (e.g., letters $) *, (#, symbols the tests while
100 As shown in Figure 19, basal expression of all proteins was assessed between cell lines and significant differences in some of these proteins existed between the triple-negative BC lines,
MDA-MB-231 and BT-549, and the ER+-expressing BC line, MCF-7. Specifically, pERK1/2 levels were highest in MDA-MB-231 cells compared to MCF-7 and BT-549 cells; and in BT-549 cells, levels of NF-ĸB were greatest when compared to MCF-7 cells and β1-INTEGRIN levels were highest when compared to MCF-7 or MDA-MB-231 cells (Figure 19).
B
MCF-7 MMC BT-549 MDA-MB-231 pERK5
pERK1/2
NF-кB
RUNX2
β-actin
101 MCF-7 MMC MDA-MB-231 BT-549
β1-integrin
pAKT
β-actin
Figure 19: A. Basal levels of pERK5, pERK1/2, NF-ĸB, RUNX2, β1-INTEGRIN, and pAKT in
MCF-7, MMC, MDA-MB-231, and BT-549 BC cells. Bands were quantified using Image
Studio™ Lite (LI-COR Biosciences, Lincoln, NE) and normalized against β-actin. Each bar
represents the mean ± SD of 3 independent experiments. Data were analyzed by one-way ANOVA
followed by Newman-Keuls post-hoc t-test where a=p<0.05 vs MCF-7; b=p<0.05 vs MMC;
c=p<0.05 vs MDA-MB-231. B. Representative blot images were included below the figure.
4.11. Assessment of C4 and C5 drug conjugates metabolism both in vitro and in vivo
4.11.1. Microsomal incubation of tamoxifen, C4, and C5
Tamoxifen was incubated for up to 20 min in the absence of microsomes, and levels
assessed by HPLC-UV. No change in drug levels occurred suggesting that it was stable over time
during the incubation period (data not shown). To assess tamoxifen oxidative metabolism by liver
microsomes, incubations were conducted in the presence of NADPH for either 10 or 20 min in
mouse or human microsomes, respectively. As shown in Table 13, there was approximately a 40%
loss in 10 min in mouse microsomes and in 20 min in human microsomes. The observed loss in
the human experiment is consistent with the preponderance of CYP-mediated metabolism of
102 tamoxifen (Dahmane et al., 2014). The same assay in both species was conducted as described for
tamoxifen to assess the susceptibility of C4 and C5 conjugates to liver microsomal metabolism.
Loss of either compound was similar to that observed for tamoxifen in the respective species
(Table 13).
4.11.2. Pharmacokinetics of tamoxifen, C4 and C5 in mice
Tamoxifen was administrated by the SC route; whereas, C4 and C5 were administered
through SC and PO routes. As summarized in Table 13, exposure to C5 following PO
administration was substantially lower compared to C4. In contrast, exposure parameters (Cmax and AUC0-24) were similar for the two compounds following SC administration, and they were
similar to those calculated following the same dose of tamoxifen by this route (Table 13). Based
on the differences between C4 and C5 following oral dosing relative to the similar exposures
obtained following SC dosing, the oral bioavailability relative to SC administration of C4 was
much higher than C5.
103 Relative Relative bioavailability
where significance 0-24 AUC (hr*ng/mL) (hr*ng/mL) Half- life (hr)
metabolism in female C57BL/6J mice mice C57BL/6J female metabolism in -Keuls post-hoc t-test of remaining at each timepoint was at each timepoint of remaining ous route, or a 10 mg/kg dose by the oral ous route, or a 10 mg/kg max were incubated with mouse or human liver or human were incubated with mouse C (ng/mL) (ng/mL) In vivo
6 27.5 27.5 6 4.6 259.4 6 40.9 40.9 6 6.8 289.1 6 31.0 31.0 6 5.3 229.1 max 24 8.9 8.9 24 6.9 1.6 0.11% 0.5 102.6 102.6 0.5 3.6 143.7 4.52% (hr) (hr) T SC SC SC PO PO PO PO ubcutaneous (SC)/oral (PO) administration in female ubcutaneous (SC)/oral (PO) administration ± SD percent drug conjugate remaining from microsomal microsomal from ± SD percent drug conjugate remaining
58.35 65.78 61.72 (±8.76) (±8.76) (±4.96) (±4.96) (±24.55) 60.36 65.55 80.03 69.45 79.22 75.32 (±3.79) (±3.79) (±8.43) (±8.43) (±5.47) (±5.47) pharmacokinetic parameters of tamoxifen, C4 or C5 by mouse (±11.59) (±14.60) (±14.23) e and 20 min for human) and the amount for human) and the amount e and 20 min
in vivo administered a 1 mg/kg dose by the subcutane a 1 mg/kg administered 74.79 88.36 85.39 (±10.13) (±11.92) (±12.22) Tamoxifen, C4 or C5 drug conjugates (10 µM) analyzed by one-way ANOVA followed Newman metabolism in microsomes metabolism in microsomes 97.16 95.20 95.82 0 min 0 min 5 min min 10 min 20 100.67 100.67 107.81 107.81 112.11 112.11 (±9.44) (±9.44) (±7.84) (±7.84) In vitro (±16.14) (±20.19) (±16.02) (±10.62) metabolism and HLM HLM HLM MLM MLM MLM MLM MLM MLM In vitro In
C4 C4 C5 C5 Tamoxifen Table 13: measured by HPLC-UV detection. Data represent the mean represent the mean by HPLC-UV detection. Data measured incubations (n=3). Data were (MLM)/human (HLM) liver microsomal incubation and by s incubation microsomal liver (HLM) (MLM)/human respectively. C57BL/6J mice, for mous (10 min over time microsomes was defined as p<0.05. Mice were route (conjugates only).
104 Chapter 5: Discussion
In US Patent 8,785,501, C5 was used to screen for ESR1 and MT1R receptor binding and test the uterus growth in mice (P.A. Witt-Enderby et al., 2014). Similar approaches were taken to screen different hybrid drug conjugates for anti-breast cancer activity both in-vitro and in-vivo
(Hasan et al., 2018). In this study, we have synthesized five melatonin-tamoxifen drug conjugates linked with different alkane chains. Two conjugates (C2 and C4) have shorter linker length than
C5, and two conjugates (C9 and C15) have longer linker length than C5. These five drug conjugates were screened for cell viability, cell migration, ESR1/MT1R receptor binding for anti- breast cancer activity.
Although, statistically, no drug conjugates demonstrated significant potency differences when compared between each other (i.e., C2 vs C4 vs C5 vs C9 vs C15), efficacy differences were observed for C4 and C5, which demonstrated the greatest efficacy to inhibit cell viability compared to the other conjugates in MCF-7 and MMC cells. Because the C4 and C5 conjugates inhibited both viability and migration in MCF-7 and MMC cells, the decreases in migration could be due to an attenuation in proliferation. However, for the TNBC cells, MDA-MB-231 and BT-549 cells, differences between C4 and C5 on proliferation and migration were observed indicating that the conjugates were inhibiting cellular migration beyond that of a reduction in cellular viability and using different signaling pathways dependent on the type of TNBC. For example, C5 inhibited cell viability in MDA-MB-231 and both C4 and C5 inhibited cell viability in BT-549 cells. The different actions between MDA-MB-231 and BT-549 could be due to the mutations that result in their TNBC phenotype—in MDA-MB-231 cells, a constitutively activating KRAS/BRAF mutation occurs increasing MAPK signaling pathways in these cells while in BT-549 cells, a
PTEN mutation occurs preventing PI3K/Akt signaling inactivation in these cells (Torbett et al.,
105 2008). The western blot analyses performed on these cells also supports this idea. For example,
in MDA-MB-231 cells, C5 modulated MEK1/2 and 5, which lay downstream from the
KRAS/BRAF pathway and C4 and C5 both modulated MEK1/2/5 and PI3K kinases in BT-549
cells. Also, BT-549 cells express a higher level of the ER-β2 isoform compared to MCF-7 cells, which promotes cell proliferation and invasion (Bialesova et al., 2017). This may explain why
BT549 cells have a much greater proliferative and invasive phenotype than MCF-7 cells and why differences were observed for C4- and C5-mediated inhibitory actins on viability and migration between these cell lines.
For the control groups, both tamoxifen and 4-OH-tamoxifen exhibited similar effects to
inhibit cell viability and migration, where tamoxifen or 4-OH-tamoxifen inhibited viability up to
87% compared to the vehicle in ER+/PR+ (MCF-7) cells and the inhibition was about 45% in
HER2+ (MMC) and TNBC (MDA-MB-231 and BT-549) cells. This was unexpected since
tamoxifen is a prodrug, which shows less binding affinity compared to the metabolized form, 4-
OH-tamoxifen. Perhaps, in TNBC cell lines, tamoxifen is working through GPR30, and/or non-
receptor-mediated action targeted to the mitochondria (Figure 21) to continue to promote its anti-
cancer actions as a prodrug (Nazarewicz et al., 2007). The findings that melatonin alone was
without effect to inhibit cellular migration demonstrates the essentiality of tamoxifen as a component of the melatonin-tamoxifen drug conjugates, C4 and C5, to promote their anti-cancer actions in TNBC.
The uniqueness of C4 and C5 may also be due to their binding to their respective receptors, especially ERs. For example, higher concentrations of C4 and C5 increased [3H]-estradiol binding
to ERs suggesting that the melatonin component of the melatonin-tamoxifen conjugates is
influencing the number of [3H]-estradiol binding sites, which was not observed with tamoxifen or
106 4-OH-tamoxifen alone. Perhaps one of the mechanisms underlying the anti-cancer actions of C4
and C5 is due to an increase in ERs enhancing the efficacy of tamoxifen to inhibit cell proliferation
and migration. For melatonin receptor binding, C5 but not C4 increased the binding of [125I]-
125 iodomelatonin to the MT1R. Because melatonin alone and C4 alone did not increase [ I]- iodomelatonin to the MT1R suggest that the tamoxifen component of the melatonin-tamoxifen drug conjugate of C5 and the linker length may be important determinants as to how C4 and C5 inhibit BC uniquely from each other.
Our data demonstrate that C4 and C5 drug conjugates have the greatest potential as novel
BC drugs compared to the C2, C9, and C15 drug conjugates supported by their efficacy to inhibit an array of diverse BC cells and their binding profiles at ERs and MT1Rs. C4 and C5 demonstrated
low nM or µM potency to inhibit BC cell viability (65-80% inhibition compared to vehicle) making
them attractive anti-cancer drug candidates in ER+, HER2+, and triple-negative BCs that include
PDX-TNBC.
Hence, C4 and C5 were selected for further evaluation in BC cells including TamR and
PDX-TNBC cells. TamR MCF-7 cells have a mesenchymal morphology, indicating that the cells
have undergone an epithelial to mesenchymal transition and they also display an accelerated
growth rate in the presence of 4-OH-tamoxifen compared to the WT MCF-7 cells perhaps due to
increased pERK5 (prosurvival kinase) activity and lower pERK1/2 (kinase involved in
differentiation and anti-proliferative when located in the cytoplasm) activity (Eapen et al., 2011;
Mebratu & Tesfaigzi, 2009; Sethi et al., 2010b). The findings that [3H]-estradiol binding
characteristics (affinity and Bmax) were not different between TamR and WT MCF-7 cells suggest that other ERs (i.e., non-genomic ERs like GPR30) may be playing more of a role in C4- and C5- mediated anti-cancer actions. However, ER-α expression was found to be lower in TamR MCF-7
107 cells compared to WT MCF-7 cells, whereas, low ER-α is associated with poor prognosis in
patients with tamoxifen failure (J. A. Vendrell et al., 2008b). This idea is supported by the findings
that tamoxifen could activate GPR30 in endometrial (Ishikawa) cells (Lin et al. 2009). The detection of [3H]-estradiol binding sites in TU-BCx-4IC (PDX-TNBC) cells also supports this
idea. C4 and C5 inhibited cell viability and migration in TamR MCF-7 cells with high efficacy
and potency making these compounds potentially useful for treating recurrent or TamR BC.
Enhanced inhibition of cell viability compared to the controls (melatonin, tamoxifen, 4-
OH-tamoxifen, melatonin+tamoxifen, and melatonin+4-OH-tamoxifen) indicate that conjugation
between melatonin and tamoxifen is required to be effective in the tamoxifen-resistant BC model.
Perhaps melatonin, when conjugated, potentiates tamoxifen activity by inhibiting ER-ERE
binding. Furthermore, migration data suggest that compared to the controls, conjugates can
demonstrate a greater extent of anti-migratory effect from low concentration to a high
concentration. The findings were validated using PDX models that represent clinically aggressive
TNBC tumors, TU-BcX-4IC, and TU-BcX-4QAN. Although melatonin receptors were found in
the PDX-TNBC cells, melatonin alone did not produce any effect. At 100uM concentration,
tamoxifen, 4-OH-tamoxifen, melatonin+tamoxifen, C4, and C5 inhibited viability as well as
detached the cells from the plate. Hence, the data suggest that the conjugates can exhibit anti-
cancer action in patient-derived BC cells possibly by regulating MEK1/2 and NF-кB pathways.
Future studies should explore downstream effectors like ERK1/2, ERK5, or PI3K pathways.
The involvement of MEK1/2, MEK5, and PI3 kinases in C4- or C5-mediated anti-cancer
actions was chosen because of their involvement in MT1R/ESR1-mediated BC signaling (Figure
20) (Araki & Miyoshi, 2018; Kastrati et al., 2017; Kumar et al., 2018; Martinelli et al., 2017;
Simoes et al., 2016; Temraz et al., 2015).
108
Figure 20: Molecular targets for melatonin, tamoxifen and the kinase inhibitors against MEK1/2
(PD98059), MEK5 (Bix02189) and PI3K (pictilisib) in MCF-7 (ER+), MMC (ER-/PR-/HER2+)
and TNBC (ER-/PR-/HER2-) cell lines HER2, MTR, ER, and GPR30 in BC cells.
C4 and C5 inhibited MCF-7 cell viability in parallel with MEK1/2, MEK5, and PI3 kinase
but not through these pathways (Figure 21). For cellular migration, the inhibitory effects were
shown to be mediated through MEK5 for C5 and not through MEK1/2 while the PI3 kinase pathway (when inhibited) worked in parallel with C5 to enhance its inhibitory action. However,
when MCF-7 cells were treated short-term (15 min) with C5, there was no change in
MEK5/pERK5, which suggests that chronic treatment of C5 modulates MEK5 through other signaling pathways. These data suggest that C4 and C5 work similarly with respect to viability but not migration and that the number of carbons linking melatonin with tamoxifen influenced the
109 outcome with respect to MCF-7 cell migration and the signaling cascade to which the drug
conjugate modulated.
For MMCs, the findings suggest that lower concentrations of C4 may be working through the MEK1/2 pathway to influence MMC viability and that C5-mediated inhibition of MMC viability works in concert with but not through PI3 kinase and possibly MEK5 but not MEK1/2
(Figure 21). For migration, the PI3K and MEK1/2 pathways enhanced C4’s inhibitory action while the combination of PD98059, Bix02189 and pictilisib with C5 enhanced its inhibitory actions.
However, C4 and C5 modulated NF-кB and β1-integrin suggesting that the conjugates may regulate other signaling proteins to induce their action.
For MDA-MB-231 cells, the data suggest that the MEK1/2, MEK5, and PI3K pathways
(when inhibited) work in concert with C4 to inhibit MDA-MB-231 migration and for viability, only the PI3 kinase pathway cooperated with C4 to inhibit MDA-MB-231 (Figure 21). Pictilisib enhanced C5-mediated inhibition of viability and migration like C4; however, C5 inhibited MDA-
MB-231 cell migration through MEK1/2 and MEK5. Similar to the NF-кB modulation by C5 in
PDX-TNBC cells, C4 stimulated NF-кB and C5 stimulated NF-кB and β1-integrin levels.
Although NF-кB is a pro-proliferative and pro-survival protein, other studies have demonstrated that inhibition of NF-кB can promote ras-mediated invasive epidermal cell growth (Xia et al.,
2018). These findings suggest that the C4- and C5-mediated stimulation of NF-кB may be attenuating ras-mediated invasive properties of the TNBCs.
For BT-49 cells, C4-mediated inhibition of viability occurred through MEK1/2, MEK5, and PI3 kinase signaling pathways while C5 inhibited viability through MEK5 and PI3 kinase and not MEK1/2 (Figure 21). For C4, the MEK5 and PI3 kinase pathways (when inhibited) worked in
110 concert with C4 to enhance its inhibitory actions on BT-549 migration. For C5, Bix02189 blocked
C5’s inhibitory effects on BT-549 cell migration suggesting the C5-mediated inhibition of BT-549
cell migration occurs through MEK5; however, the PI3 kinase pathway worked in concert with C5
to enhance its anti-migratory effects but only when PI3 kinase was inhibited by pictilisib. These
data demonstrate that unique pharmacophores are being produced in the presence of C4 or C5 that explain, in part, their anti-cancer actions and their uterine-protective actions not observed with the
co-administered but unlinked controls (i.e., melatonin + tamoxifen or melatonin +4-OH-
tamoxifen).
The data demonstrate enhanced efficacy of C4 and C5 compared to the unlinked controls
likely due to unique ER/MT1R and/or intracellular protein interactions (Figure 21). For example,
in MCF-7 (ER+) BC cells, pERK1/2, pERK5 and NF-ĸB were the proteins significantly modulated
by C4 or C5. For MMC (HER2+) BC cells, pERK1/2 appeared to play a more central role possibly
through co-modulation of NF-ĸB, pERK5, and β1-INTEGRIN. For the triple-negative BC line,
MDA-MB-231, pERK1/2 and pERK5-mediated inhibition of NF-ĸB were modulated by C4 while
C5 effects on NF-ĸB and β1-INTEGRIN expression levels; or pERK1/2 cross-modulation of pERK5 and NF-ĸB; or PI3K-dependent inhibition of NF-ĸB, RUNX2, and β1-INTEGRIN may
underlie its anti-cancer effects in MDA-MB-231 cells. For BT-549 triple-negative BC cells, C4-
and C5-mediated effects on NF-ĸB or PI3K-dependent regulation of pERK1/2 may underlie its
anti-cancer actions in this triple-negative BC line.
111
Figure 21: Abridged mechanism of C4 and C5 effects in MCF-7, MMC and TNBC cell lines. The red arrow indicates that kinase has been modulated for drug conjugates-mediated change in viability in a certain cell line. The green arrow indicates that kinases have been modulated for change in migration mediated by drug conjugates in certain cell lines. The dotted line indicates kinases worked parallel with the drug conjugates for cell viability and cell migration in the specific cell line. The blue box indicates the proteins were changed by the conjugate treatments, where the data was obtained from western blot method.
112 These inhibitor studies demonstrate that C4 and C5 are not acting “typically” at ERs and
MT1Rs and suggest that novel pharmacophores are being created in a cancer cell-specific manner
to produce their diverse anti-cancer actions. These unique pharmacophores created by C4 and C5
may be attributed to the type of linker connecting melatonin to tamoxifen (i.e., cleavable or non- cleavable) to influence the pharmacological characteristics of anti-cancer drugs as shown in Fig.
22 and as reviewed (Hasan et al., 2018).
This idea is supported by the findings that (1) C4 and C5 inhibited BC lines devoid of estrogen receptors (MMC, MDA-MB-231, BT-549); (2) that C4 and C5 displayed unique binding characteristics at ERs and MT1Rs and (3) uterine-protection occurred for C5, which was not
observed when melatonin and tamoxifen were co-administered but unlinked. Regarding (3), it was
demonstrated that a 3-day administration of the C5 prevented uterine stimulation compared to
17 -estradiol (E2) alone, tamoxifen alone, and melatonin plus tamoxifen co-administered but
unlinked in FVB/n OVX mice ((P.A. Witt-Enderby et al., 2014); US Patent 8,785,501). This
observation suggests that the melatonin component of the C4 or C5 drug conjugates may be
opposing tamoxifen’s uterine-enhancing actions by inhibiting ER binding to EREs thus decreasing
ERE-mediated gene transcription in the uterus as shown (Hu et al., 2015; Rato et al., 1999). Even
though the uterotropic effects of tamoxifen were lessened in the presence of melatonin in an
unlinked manner, the findings that the melatonin-tamoxifen drug conjugates demonstrated an
enhance inhibiting action on the uterus suggests that some unique interaction between melatonin
receptors and estrogen receptors (genomic and non-genomic) is occurring in the uterus (See blue
and orange boxes in Figure 22).
Basal expression of pERK1/2, NF-ĸB, and β1-INTEGRIN could also account for the
differential actions of C4 and C5 on BC cell viability, migration, and modulation of signaling
113 cascades in MCF-7 cells, MMCs, MDA-MB-231, and BT-549 cells. Phospho- ERK1/2 levels were highest in MDA-MB-231 cells versus MCF-7 and BT-549 cells; NF-ĸB levels were highest in BT-
549 cells vs. MCF-7 cells; and β1-INTEGRIN levels were highest in BT-549 cells when compared to MCF-7 or MDA-MB-231 cells. The preference of C4 and C5 for the MEK1/2 pathway in MDA-
MB-231 cells may be attributed, in part, to its high basal levels of pERK1/2 and the strong PI3 kinase inhibitory effect in BT-549 cells when combined with C4 or C5 may be attributed to its high NF-ĸB and β1-integrin levels. All of these proteins analyzed have been shown to either lay downstream of MEK1/2, MEK5, and/or PI3 kinase and play significant roles in BC development, growth, and progression (Kumar et al., 2018; Simoes et al., 2016; Kastrati et al. 2017; Temraz et al. 2015; Martinelli et al., 2017; Araki and Miyoshi, 2017). Their inhibition by C4 or C5 alone or in combination with the MEK1/2, MEK5, or PI3 kinase inhibitors opens a novel and rich area for
BC drug development.
Using a mouse and human microsomal system, C4 and C5 followed similar metabolic loss as tamoxifen, demonstrating oxidative, presumably cytochrome P450-dependent metabolism. In- vivo pharmacokinetic analysis in mice demonstrated that both C4 and C5 had exposures similar to tamoxifen following subcutaneous administration, suggesting similar pharmacokinetic characteristics to tamoxifen. Following oral administration to mice, rats, and humans, tamoxifen is extensively metabolized (Fromson et al., 1973; Kisanga et al., 2004). In mice, the oral bioavailability of tamoxifen compared to the subcutaneous route was < 10% following doses of either 4 or 10 mg/kg doses for each route (Reid et al., 2014). A similar estimate of oral relative to subcutaneous bioavailability was observed for the C4 conjugate (Table 6). The lower bioavailability of C5 compared to C4 following oral administration suggests higher first-pass elimination of C5 and that other route of delivery should be considered for C5, like subcutaneous
114 delivery. This idea is supported in Witt-Enderby (US Patent 8,785,501) where C5, given subcutaneously at a dose of 200µg/kg body weight, was sufficient to produce uterine protection and modulate estrogen/ER-dependent progesterone receptor mRNA expression in the mammary gland ((P.A. Witt-Enderby et al., 2014); US Patent 8,785,501). These data suggest that C5 is bioavailable and has the potential to protect against the adverse effects associated with chronic tamoxifen usage on the uterus.
115 Chapter 6: Strengths and Limitations
Melatonin-tamoxifen drug conjugates demonstrated context-specific activities, which depend on the receptor status, drug concentration, treatment duration, and/or linker length. However, several research questions still need to be answered and further experiments are required.
i. The effect of drug conjugates, C4 and C5, on tumor growth and metastases needs to be
studied in vivo using a PDX mouse model. Utilizing PDX models in drug discovery
research incorporates a translational approach to evaluate drug effects in the laboratory
setting (Whittle et al., 2015; Byrne et al., 2017). While established cell line-based research
provides important insights into drug effects on cancer cells and basic mechanisms of
action, treating patient tumors in vivo facilitates the translation of these findings to clinical
observation. Hence, future studies will be examining the in vivo actions of C4 and C5 in
PDXs of TamR and TNBC in mice.
ii. The pharmacokinetic analyses conducted for this dissertation were preliminary where the
experiment was conducted for 24 hr and a single mouse was used for each time point.
Therefore, further pharmacokinetic assessments are required for dosing calculations.
Similar to the pharmacokinetic analysis conducted in this study, more mice will be
included with longer time points in future studies. Since the observed plasma
concentrations were very close to the limit of quantification, a higher dosage of C4, C5,
and tamoxifen will also be tested in future studies.
iii. More elaborate time-courses on C4 and C5 need to be conducted to assess the effect of
chronic exposure on BC cell viability and migration. All the cell viability and cell
migration assays were conducted over 24 hr. Hence, 48 and 72 hr of treatment duration
will be used for cell viability assay (R. I. Sharma et al., 2011). Furthermore, Boyden
116 chamber assays will be used for a better assessment of C4- and C5-mediated actions on
BC cell invasion and treatments will occur over longer periods of time (i.e., 24 and 48 hr)
to confirm the outcomes of scratch/wound healing assay observed in this study. iv. Further analysis of the downstream targets modulated by C4 and C5 need to be assessed.
Due to the limitation of the western blot method, regulation of 6 proteins (pERK1/2,
pERK5, pAKT, NF-кB, RUNX2, and β1-INTEGRIN) by C4 and C5 were analyzed in
this dissertation. RNA sequencing, which demonstrates a broad quantification of
transcriptomes compared to western blot method (Brueffer et al., 2018) has been
conducted on TU-BcX-4QAN TNBC tumor tissue exposed to C4 and C5 to identify as
yet unknown downstream molecular targets modulated by these drug conjugates.
v. Tamoxifen is a pro-drug that cannot be converted into the active form (4-OH-tamoxifen)
in vitro. Hence, it is postulated that melatonin-4-OH-tamoxifen drug conjugates will
demonstrate a better effect to inhibit BC cell viability and migration. Currently, novel
melatonin-4-OH-tamoxifen drug conjugates have been developed and are being tested on
BC cells for assessment of their anti-cancer actions on cell viability and migration. vi. Radioligand binding data indicated that GPR30 may play a role in C5-mediated action.
Studies suggest that GPR30 plays a crucial role in BC pathogenesis and drug resistance
induction (Molina et al., 2017). Hence, further experiments need to be conducted to
ascertain its role in melatonin-tamoxifen drug conjugates’ action. vii. One important question that needs to be answered is the role of the receptors in C4- or
C5-mediated anti-BC action. Studies using melatonin receptor antagonists and/or ER
receptor agonists will help to determine the role of melatonin and estrogen receptors in
mediating these anti-BC actions of C4 and C5. In the future, C4 and C5 conjugates will
117 be tested in the presence or absence of luzindole/estrogen for the viability and migration
assays. viii. Another important question is how the linked melatonin-tamoxifen conjugates are
working as a pharmacophore and modulating two different receptors at the same time. Co-
immunofluorescence may help to answer that question in future studies. Colocalization of
MTR and ER will suggest dimerization or coactivation of the receptors and can be used
for further characterization of the receptors (Porzionato et al., 2018).
118 Chapter 7: Conclusion
It was observed that the anti-cancer actions of C4 and C5 were “context-specific”
dependent upon the BC phenotype (i.e., ER+, HER2+ or triple-negative), the linkers connecting melatonin to tamoxifen, the endpoints measured (i.e., viability or migration), and the inhibitors used in the analysis (i.e., PD98059, Bix02189, or pictilisib). Based on the study outcomes, it is proposed that melatonin-tamoxifen drug conjugates are targeting a novel pharmacophore between melatonin receptors located at the plasma membrane or mitochondrial membrane and estrogen receptors located in the plasma membrane or in the nucleus; and this pharmacophore formed between the melatonin and estrogen receptors causes a unique interaction with downstream signaling proteins to inhibit pro-survival and pro-proliferation pathways as shown (Figures 22 and
23).
119
Figure 22: Molecular targets for C4 and C5 and the kinase inhibitors at melatonin and estrogen receptors, MEK1/2, MEK5, and PI3K in MCF-7 (ER+), MMC (ER-/PR-/HER2+) and TNBC (ER-/PR-/HER2-) cell lines. The drug conjugates can bind to MT1R and genomic
(ERs) or non-genomic (GPR30) to regulate MAPK and PI3K. MT1R and ER can regulate MAPK while GPR30 and HER2 receptors can regulate the PI3K pathway.
The C4 and C5 conjugates may be working differently in the BC cells based on the expression of different melatonin or estrogen receptors (i.e., plasma membrane melatonin receptors vs mitochondrial melatonin receptors or nuclear estrogen receptors vs plasma membrane estrogen receptors, GPR30) in the various BC cells. Also, the fact that the melatonin-tamoxifen drug conjugates are linked suggests that the simultaneous activation of estrogen receptors
(genomic or non-genomic) or melatonin receptors (plasma membrane or mitochondrial) also may
120 explain the pharmacological differences observed between the melatonin-tamoxifen conjugates
(linked) and melatonin plus tamoxifen combination (unlinked).
Figure 23: Overall and composite mechanisms of action proposed for C4 and C5 effects in
MCF-7, MMC and TNBC cell lines. The arrow indicates a positive feed into the signaling
cascade while a perpendicular line indicates a negative (inhibitory) feed into the signaling cascade.
The line indicates the linkage between melatonin and tamoxifen drug conjugate. The blue boxes indicate the proposed sequence of events that would occur following the binding of C4 or C5 to melatonin receptors at the plasma membrane and with genomic ERs. The orange boxes indicate the proposed interactions of melatonin to melatonin receptors at plasma membranes with tamoxifen to GPR30 receptors at the plasma membrane; melatonin at melatonin receptors expressed on the mitochondria and tamoxifen with GPR30 receptors at the plasma membrane or at the mitochondria (Suofu et al., 2017).
121 In conclusion, melatonin-tamoxifen drug conjugates exhibited anti-cancer actions against
BC, including triple-negative and TamR. In the future, more comprehensive experiments including both in-vitro and in-vivo to overcome the limitations and to implement clinical testing.
122 Chapter 8: References
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140 Chapter 9: Appendices
9.1. Copyright statements
This dissertation contains verbatim language from the paper, Hasan et al., 2019 (M Hasan,
MA Marzouk, S Adhikari, TD Wright, BP Miller, MD Matossian, S Elliott, M Wright, M Alzoubi,
BM Collins-Burow, ME Burow, U Holzgrabe, DP Zlotos, RE Stratford, and PA Witt-Enderby
(2019) Pharmacological, Mechanistic, and Pharmacokinetic Assessment of Novel Melatonin-
Tamoxifen Drug Conjugates as Breast Cancer Drugs, Molecular Pharmacol, 96(2): 272-296;
DOI:https://doi.org/10.1124/mol.119.116202), which is reprinted with permission of the
American Society for Pharmacology and Experimental Therapeutics. All rights reserved.
Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.
This dissertation contains language from the paper, Hasan et al., 2018 (Hasan M, Leak RK,
Stratford RE, Zlotos DP, Witt-Enderby PA. Drug conjugates—an emerging approach to treat
breast cancer. Pharmacol Res Perspect. 2018;e00417. https://doi.org/10.1002/prp2.417), which is
an open-access article under the terms of the Creative Commons Attribution License, which
permits use, distribution, and reproduction in any medium, provided the original work is properly
cited.
9.2. ER/ERE activation by estrogen in wildtype and TamR MCF-7 cells
9.2.1. Methods
9.2.1.1. ER-ERE Activation Analysis. ER transcription factor ELISA (TransAMTM; Catalog:
41996; Active Motif, Carlsbad, CA) followed by Schild Plot analysis were conducted to assess the
functional change of ERs expressed in wildtype (WT) and TamR MCF-7 cells. This was conducted
141 to identify a potential mechanism underlying the tamoxifen resistance in TamR MCF-7 cells. This
ELISA measures the colorimetric values in response to ER/ERE complex activation in the nuclear extract of the cells.
9.2.1.2. Schild Plot analysis: The antagonistic potency of ERs expressed in WT and TamR MCF-
7 cells was measured by Schild regression developed by Heinz Otto Schild. Log EC50 ratios were calculated from the EC50 values obtained from ELISA assay using the following formula,
EC50 of estrogen with 4 OH tamoxifen log EC50 of estrogen only 1
Log EC50 ratios were calculated for all 4-OH-tamoxifen concentrations and plotted against the log
estrogen concentrations. A linear regression line was drawn from the values and the anti-log of X-
intercept (pA2 and Kb) values were calculated as described (Tallarida RJ, Raffa RB, McGonigle
P (eds) (1988) Chapter 9: Radioligand Binding. In: Principles in general pharmacology, vol 9.
Springer, New York.).
In the ELISA experiment and for the Schild plot analysis, concentration-response curves for
estrogen (10 fM-10 mM) were conducted in the presence of increasing concentrations of 4-OH-
tamoxifen (1 pM, 1 nM, 10 nM, and 100 nM) and assessed for their effects on ER-mediated
activation of ERE in both WT MCF-7 and TamR MCF-7 cells.
9.2.2. Results
The EC50 values in the presence or absence of 4-OH-tamoxifen are reported in Table A.
The potency (EC50 = 12 nM) of estrogen to activate ERE in TamR MCF-7 cells was similar to the potency (EC50 = 18.4 nM) in wildtype (WT) MCF-7 cells. However, the ability of the competitive
142 antagonist of ER, 4-OH-tamoxifen, to antagonize the effects of estrogen is different between WT
MCF-7 cells compared to TamR MCF-7 cells (Figure A).
Table A: EC50 values for estrogen-mediated ER/ERE complex activation Potency (EC50) of estrogen Wt MCF-7 TamR MCF-7 Estrogen only 18.4 nM 12 nM Estrogen + 1 pM 4-OH-tamoxifen 51 nM 5 nM Estrogen + 1 nM 4-OH-tamoxifen 94 nM 2.6 nM Estrogen + 10 nM 4-OH-tamoxifen 0.15 nM 2.2 nM Estrogen + 100 nM 4-OH-tamoxifen 5.18 nM 59 nM
Figure A: Estrogen mediated ER/ERE complex activation in the presence or absence of
different concentrations of 4-OH-tamoxifen in WT (A) and TamR (B) MCF-7 cell lines. The
highest response was considered as a maximum response. Other values were normalized by the
maximum response. Each value represents the average value of duplicates.
For the Schild Plot analysis, EC50 values were calculated for each curve run with estrogen alone
or in combination with the different concentrations of 4-OH-tamoxifen. The data demonstrate that
no convergence in the Schild plot analysis occurred for TamR MCF-7 cells, whereas KB and pA2 value for wild type MCF-7 cells were able to be calculated and determined to be KB of 11.28 fM
and a pA2 value of 13.9 (Figure B).
143 0.7
0.6
0.5 Wild type 0.4 TamR 0.3 y = 0.1232x + 1.7192 0.2 pKB (x-intercept) = -13.9497
log concentration ratio log concentration KB (anti-log of pKB) = 11.28 fM 0.1
0 ‐15 ‐14 ‐13 ‐12 ‐11 ‐10 ‐9 ‐8 ‐7 ‐6 ‐5 ‐0.1 log [4-OH-tamoxifen] (M)
Figure B: Schild plot analysis of estrogen-mediated ER/ERE complex activation in Wt and
TamR MCF-7 cells. Y-axis represents logarithmic values of the EC50 ratio between estrogen with
4-OH-tamoxifen and estrogen alone subtracted by 1.
9.2.3. Summary and Conclusion
The potency (EC50) values for estrogen to activate ER/ERE complexes in WT and TamR
MCF-7 cells were similar indicating that estrogen’s ability to activate ERs was not different
between the cells and so the TamR observed was not due to receptor desensitization. However,
when Schild Plot analysis was conducted using 4-OH-tamoxifen as the competitive antagonist,
differences between cell lines were observed. Specifically, in WT MCF-7 cells, a KB value of
11.28fM was obtained while no KB value could be calculated because no antagonism or rightward
shift in estrogen-mediated ERE activation occurred in TamR MCF-7 cells. These findings may
indicate that the ER/ERE complex is so tightly coupled in TamR MCF-7 cells resulting in
constitutive activation of the ER/ERE complex in TamR MCF-7 cells that could not be turned off
by an ER antagonist, 4-OH-tamoxifen. This, perhaps, may explain the greater rates of growth in
TamR cells vs wildtype MCF-7 cells.
144