SARACATINIB SYNERGIZES WITH ENZALUTAMIDE IN CASTRATION-
RESISTANT PROSTATE CANCER 
A DISSERTATION 
 
SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL 
 
OF THE UNIVERSITY OF MINNESOTA 
 
BY 
RALPH EDWARD WHITE III 
 
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS 
 
FOR THE DEGREE OF 
DOCTOR OF PHILOSOPHY 
 
Advisor 
JUSTIN M. DRAKE, Ph.D. 
JUNE 2023 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
© Ralph White III 2023
i 
 
Acknowledgements 
First, I would like to acknowledge God for this journey, for the hills I have climbed, 
for the depths I have trekked to ultimately be brought here. Thank you for all the 
good and bad, for your mercy and grace alone have given me this opportunity. 
Second, I would like to acknowledge my lovely loving family. Thank you, my father 
for your relaxed composition, my mother for your constant reassurance, and my 
brother for your encouraging spirit. All this and much more held my heart in comfort 
in times of insecurity and in times of prosperity throughout this journey. And to my 
extended family, I thank you for reminding me whose I come from. 
Third, I would like to acknowledge my wonderful friends, those near and far. To 
those recent and those from the beginning. Thank you, for to have a friend like you 
is of the utmost importance to me as I, in my anxieties and depression moments, 
in my triumphs and in my victories, continue to grow as a scientist and person. 
Lastly, I would like to acknowledge Justin Drake and the Drake lab, and my thesis 
committee. To you Justin, I thank you for taking a chance on my potential to 
develop the scientist in me. In challenge and in agreeance with one another, I am 
appreciative of it all. To the lab, thank you for allowing me to learn from you. With 
the fun we had, I know it’ll be hard to forget these moments. And to you, Scott 
Dehm, Carol Lange, and Nicholas Levinson, I thank you for the sacrifice you gave 
to guide this black child from Stone Mountain, GA towards this milestone. 
 
 
 
ii 
 
Dedication 
Dedicated to you who have gone to glory. You may have left my sight along the 
way, but your presence and memory still remain in me. 
Aunt Dee Dee, GDaddy and Memaw, Jeana Thomas, Gardner Gay, and Dr. 
Hiroshi Hiasa.  
 
 
 
 
 
 
 
 
 
 
 
 
 
iii 
 
Abstract: Prostate cancer (PCa) remains the most diagnosed non-skin cancer amongst 
the American male population. Treatment for localized prostate cancer consists of 
androgen deprivation therapies (ADTs), which typically inhibit androgen production and 
the androgen receptor (AR). Though initially effective, a subset of patients will develop 
resistance to ADTs and the tumors will transition to castration-resistant prostate cancer 
(CRPC). Second generation hormonal therapies such as abiraterone acetate and 
particularly enzalutamide, which inhibits AR full-length (AR-FL), are typically given to men 
with CRPC. However, these treatments are not curative and typically prolong survival only 
by a few months. Several resistance mechanisms contribute to this lack of efficacy such 
as the emergence of AR mutations, AR amplification, lineage plasticity, AR splice variants 
(AR-Vs) and increased kinase signaling. Having identified SRC kinase as a key tyrosine 
kinase enriched in CRPC patient tumors from our previous work, we evaluated whether 
inhibition of SRC kinase synergizes with enzalutamide or chemotherapy in several 
prostate cancer cell lines expressing variable AR isoforms. We observed robust synergy 
between the SRC kinase inhibitor, saracatinib, and enzalutamide, in the AR-FL+/AR-V+ 
CRPC cell lines, LNCaP95 and 22Rv1. We also observed that saracatinib significantly 
decreased AR Y534 phosphorylation, a key SRC kinase substrate residue, on AR-FL and 
AR-Vs, along with the AR regulome, supporting key mechanisms of synergy with 
enzalutamide. Lastly, we also found that the saracatinib-enzalutamide combination 
reduced DNA replication compared to the saracatinib-docetaxel combination, resulting in 
marked increased apoptosis. By elucidating this combination strategy, we provide pre-
clinical data that suggests combining SRC kinase inhibitors with enzalutamide in select 
patients that express both AR-FL and AR-Vs. 
 
 
iv 
 
Table of Contents 
List of Tables-vi 
List of Figures-vii 
Chapter 1. An Overview of Prostate cancer, and the role of AR-1 
I-Clinical Relevance of Prostate Cancer and Associated Risk Factors- 1 
II-Development and Progression of Prostate Cancer- 2 
III-Genomic Characterization of Early and Late Stage Prostate Cancer-4 
IV-Role of AR-4 
V-Role of AR in PCa-7 
VII-Treatment Landscape of Prostate Cancer-9 
-Historical Perspective of Prostate Cancer-9 
-Leuprolide-12 
-Taxanes-12 
-Targeting AR-13 
 -Abiraterone Acetate and Enzalutamide-13 
 -Apalutamide and Darolutamide-15 
-Platinum Agents-16 
- Sipuleucel-T-17     
VIII-Conclusion and the Future-18 
Chapter 2. CRPC resistance mechanisms and the role of kinases. -20 
I-Introduction-20 
II-Expression of AR Variants-20 
III-Upregulation of Other Steroid Receptor Signaling-23 
IV-Lineage Plasticity and Neuroendocrine Differentiation-24 
V-Increased Kinase Activity-25 
 -PI3K/AKT/mTOR pathway-26 
 -MAPK-ERK pathway-27 
 -SRC Family Kinases-28 
Chapter 3. Saracatinib synergizes with enzalutamide in CRPC-31 
I-Introduction-31 
v 
 
II-Results-33 
 - Enzalutamide and saracatinib yields strong synergy in AR-FL+ cell lines-33 
 - Saracatinib decreases AR phosphorylation and AR-V protein expression via SRC 
kinase inhibition-40 
 - Saracatinib alters AR gene signature in CRPC-45 
- Saracatinib induces DNA damage and apoptosis via DNA replication stress-52 
III-Discussion-64 
IV-Methods-69 
Closing Remarks-76 
Bibliography-79 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
vi 
 
List of Tables 
Table 1: Genetic background of cell lines used in vitro studies with corresponding AR 
and SRC status-34 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
vii 
 
List of Figures 
Figure 1: Treatment Landscape for PCa progression-5 
Figure 2. Canonical AR signaling pathway-8 
Figure 3: AR splice variant (AR-V) signaling and exon structure-22 
Figure 4: SRC kinase interaction with AR-30 
Figure 5: Dose-response Curves of Enzalutamide, Saracatinib, and Docetaxel-35 
Figure 6: Synergy observed between Enzalutamide and SRC kinase inhibitor Saracatinib 
in AR+ Positive Cells (Bliss Independence)-37 
Figure 7: Synergy observed between Enzalutamide and SRC kinase inhibitor Saracatinib 
in AR+ Positive Cells. (Combination Index-Chou Talalay)-38 
Figure 8: Synergy observed between Enzalutamide and SRC kinase inhibitor Saracatinib 
in AR+ Positive Cells. (Dose Reduction Index)-39 
Figure 9: AR Y534 phosphorylation and AR-V protein expression ablated via SRC kinase 
inhibition in 22Rv1 cells-41 
Figure 10: Quantification of AR Y534 phosphorylation and AR-V protein expression 
ablated via SRC kinase inhibition in 22Rv1 cells-42 
Figure 11: AR Y534 phosphorylation and AR-V protein expression ablated via SRC kinase 
inhibition in LNCaP95 cells-43 
Figure 12: Quantification of AR Y534 phosphorylation and AR-V protein expression 
ablated via SRC kinase inhibition in LNCaP95 cells-44 
Figure 13: Saracatinib affects steroid receptor gene expression-46 
Figure 14: Saracatinib affects GR gene signature-48 
Figure 15: Saracatinib affects AR gene signature (Dehm)-49 
Figure 16: Saracatinib affects AR gene signatures (Western Blot)-50 
Figure 17: Saracatinib affects AR gene signature (Nelson)-51 
Figure 18: Saracatinib affects AR-V7 gene signature-53 
Figure 19: Saracatinib affects MYC gene signature-54 
Figure 20: Saracatinib affects cell cycle gene signature-55 
Figure 21: Saracatinib halts DNA synthesis and induces DNA Damage (Cell phase 
Identification)-57 
Figure 22: Saracatinib halts DNA synthesis and induces DNA Damage(Quantification)-
58 
viii 
 
Figure 23: Saracatinib halts DNA synthesis and induces DNA Damage.  Representative 
immunofluorescence images of γH2AX (Representative Images)-59 
Figure 24: Quantification of immunofluorescence in S-phase cells for EdU (marker of 
incorporation into DNA) and γH2AX (DNA Damage marker), for each drug group-60 
Figure 25: Quantification of immunofluorescence in G1 and G2 cells for EdU (marker of 
incorporation into DNA) and γH2AX (DNA Damage marker), for each drug group-61 
Figure 26: Saracatinib activates markers of apoptosis (Caspase 3/7 activation)-62 
Figure 27: Saracatinib activates markers of apoptosis (cleaved PARP)-63    
Figure 28: Saracatinib synergizes with Enzalutamide to cause greater prostate cancer 
cell death (Summary Figure)-67 
Figure 29: Synergy study plate layout (combination index via Chou-Talalay)-72 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1 
 
Chapter 1: 
An Overview of Prostate Cancer and the Role of AR 
Clinical Relevance between Prostate Cancer and Associated Risk Factors 
The American Cancer Society has predicted that in 2023, there will be 288,300 
new cases of prostate cancer (PCa) and 34,700 deaths, an uptick of 2-3% more 
from 2022(1). A number of factors contribute to these predictions, including 
increased screening approaches such as prostate specific antigen (PSA) testing. 
Risk factors (age, race, family history, lifestyle) are associated with prostate 
cancer(2).  Age is a major risk factor corresponding to majority of cancers. 
Currently, 1 out of 8 men will be diagnosed with prostate cancer in their life(3). With 
life expectancy steadily increasing over the course of decades, along with PSA 
testing, the occurrence of prostate cancer has increased alongside it. The current 
clinical parameters require men to be screened for PCa at aged 50 and older for 
prostate cancer, resulting in over half of the total cases of PCa being diagnosed in 
men who are 65 years of age or older(3,4). Racial health disparities present a 
glaring difference in incidence for cancer. For non-Hispanic Black men in 
comparison to their Caucasian counterparts, the risk of developing prostate cancer 
is nearly doubled, contributing to many of the cases and deaths of prostate cancer. 
In Asian populations, the risk is significantly lower(3), though, once environment 
and diet are interwoven due to migration to Western nations, there is increased 
risk. Family history also contributes toward the potential risk to developing cancer, 
including prostate cancer. Previous literature has shown that having those who are 
first-degree family members who have prostate cancer increases the risk of 
prostate cancer for the man up to 68%(5). Also, those first degree family members 
2 
 
who have breast cancer increases the risk of prostate cancer for the man up to 
21%. Moreover, those who have both amongst their family elevates the risk even 
higher. Factors such as environmental interactions and overall activity lifestyle 
contribute to the risk of prostate cancer. Tobacco smoke, along with exposure to 
aerosol chemicals, correlate to increased risk for benign prostate hyperplasia and 
PCa (6,7). Co-morbidities such as diabetes and obesity increase the risk of 
recurrence and lethal forms of prostate cancer. In addition, depending on where 
one lives, access to adequate healthcare and food supply for diet can shift the risk. 
While there are studies for environment and lifestyle contributions, more is needed 
to solidify the findings, due to other findings showing these risk factors having little 
to no effect on PCa development. There are some interplaying nuances to the 
interpretation of the risk factors. For instance, there is a trend to lower the 
screening age to target younger men aged 30-40, increasing the number of cases. 
Plus, clinicians are screening black men at ages 40 to 45 due to overarching health 
disparity in comparison to the normal screening age for other men(8). 
Development and Progression of Prostate Cancer 
The prostate is an organ located near the groin area and under the bladder, 
developed from steroidal signaling during the first 10 weeks of gestation. Its 
function is to supply seminal fluid and is regulated mainly by androgen receptor 
(AR) signaling. AR signaling is a part of the hypothalamic-pituitary-adrenal axis, 
where the central nervous system and endocrine system are tied together. First, 
the hypothalamus secretes gonadatropin-releasing hormone (GnRH) which travels 
to the anterior pituitary to bind to the GnRH receptors. Once bound, luteinizing 
3 
 
hormone (LH) and follicle-stimulating hormone (FSH) are released to the testes to 
initiate steroidogenesis and spermatogenesis(7,9). When the HPA axis becomes 
dysregulated, the prostate has hyper-proliferation in the luminal epithelium and 
reduction in basal epithelium, which can be diagnosed as either benign prostatic 
hyperplasia or prostate cancer.  To screen for prostate cancer, PSA is measured 
via blood, along with MRI and PET scans of the organ to inform tumor activity and 
androgenic signaling (10,11). Needle biopsies are also done to determine the cell 
differentiation and morphology in prostate tissue via Gleason score. A number of 
markers can also be detected to establish the diagnosis as well, specifically, losses 
in basal markers p63, cytokeratin 4 and 5, along with gains in luminal markers 
TMPRSS2 and cytokeratin 8 and 18 (11). For localized PCa, patients undergo 
radical prostatectomy or radiotherapy along with androgen deprivation therapies 
(ADT) to disrupt the HPA axis activity (Leuprolide), which inhibits androgenic 
signaling (Figure 1). As a result, majority of patients are cured, with their PCa going 
into remission. While PSA drops significantly for nearly all men undergoing ADT 
treatment, unfortunately a subset of patients will have their PSA levels rise, 
concomitant with metastatic disease, and these patients will no longer respond to 
therapy. This treatment resistant phenotype of prostate cancer is known as 
castration resistant prostate cancer (CRPC), requiring clinicians to prescribe 
newer second-generation therapies (e.g. abiraterone acetate, enzalutamide, 
apalutamide, darolutamide). In response for some patients, PSA will decrease 
again for a variable number of months, but eventually these newer therapies will 
yield little benefit for these and de novo patients. Clinicians then prescribe 
4 
 
therapies that impact the prostate cancer broadly (taxanes, platinum drugs, radium 
223) until the death of the patient.  
Genomic Characterization of Early and Late Stage Prostate Cancer 
In its early stages, prostate cancer is characterized by copy number changes (gene 
gain or loss) and gene translocations however not many mutations on AR. 
Rearrangements in chromosomes 4, 6, and prominently 21 cause the truncation 
and subsequently, inactivation of tumor suppressor genes, for example, UNC5C 
and SNX9, as well as fusion events between genes(12). One key fusion event is 
ETS gene fusion with TMPRSS2 which lead to distinct malignancies (13). 
Deletions and mutations of tumor suppressor genes like PTEN and TP53 are also 
common in prostate cancer(14,15). MYC overexpression corresponds to 
dysregulated cell growth (16). DNA damage response genes BRCA1, BRCA2, and 
ATM are also mutated in select tumors, resulting in DNA damage and potential 
tumorigenesis(17). In the later stages of prostate cancer, major shifts occur in the 
genome of AR due to adaptations to treatment, causing AR gene amplification(18), 
overexpression, and overall increase in androgenic signaling. In addition, further 
loss of corepressors such as RB1, potentiates further dysregulation of cell 
growth(19). Additionally, in response to hormonal therapies, CRPC can shift 
towards different molecular phenotypes which include loss of AR signaling that can 
exacerbate tumor growth, metastatic disease and ultimately death of the patient. 
Role of AR 
AR, located on chromosome X (Xq11-12) is a 110 kDa, 919 amino acid, four 
domain protein, containing an N-terminal domain, DNA binding domain, hinge  
5 
 
Figure 1: Treatment Landscape for PCa progression. PCa in terms of time is considered 
a slow growing cancer, requiring surveillance and therapeutic intervention to maintain PSA 
levels over the course of the PCa patient’s life. 
 
 
 
 
 
 
 
 
 
 
6 
 
region, and ligand binding domain (20). The N-terminal domain, encoded in exon 
1, is in control of AR transactivation and the majority of its signaling. The DNA 
binding domain, encoded by exons 2-3, regulates AR binding to DNA that activates 
AR transcriptional activity. It also contains a minor part of the nucleus localization 
signal required for AR to move from the cytoplasm to the nucleus. The hinge 
region, encoded by exon 4, contains majority of the nucleus localization signal 
plays a role in the conformation of AR, impacting its activity. Lastly, the ligand 
binding domain, encoded by exons 5-8, mediates androgenic action and activation 
of AR. AR functions as a nuclear steroid receptor via androgenic signaling, like the 
estrogen (ER), mineralocorticoid (MR), glucocorticoid (GR), and progesterone 
receptors (PR) along with their respective ligands. AR also operates as a 
transcription factor regulating cell proliferation and differentiation in prostatic 
tissue. In normal conditions, AR species are dispersed throughout the cytoplasm 
and nucleus, with the majority being in the cytoplasm awaiting activation. Inactive 
AR is in complex with heat shock proteins 40, 70 and 90, as well as other cofactors, 
such as NCoR and SMRT, to prevent access to nuclear localization signal in AR’s 
amino acid sequence (Figure 2). Meanwhile, steroidogenesis and subsequently, 
testosterone synthesis is initiated for future binding to AR. Testosterone is then 
reduced to a more potent version of itself called dihydrotestosterone (DHT), which 
binds within the ligand-binding domain of AR. Heat shock proteins and cofactors 
dissociate from AR, allowing AR to translocate to the nucleus to function as a 
transcription factor. The DHT- bound androgen receptor dimerizes with another 
DHT-bound AR and align atop specific DNA sequences with coactivators to 
7 
 
activate the transcription of AR dependent genes. Normal AR engages in a variety 
of molecular activities in order to maintain the survival of the prostate epithelium 
and stroma, transcribing genes involved in protein trafficking, cell-cycle 
metabolism and regulation of transcription factors. Historically, the focus has been 
on genes KLK2/3, TMPRSS2, and NKX3.1. KLK2 and KLK3 encode for proteins 
that contribute to PSA activity in prostatic tissue, while TMPRSS2 and NKX3.1 are 
regulators of growth of prostatic epithelium(21,22,23).  
Role of AR in PCa 
Patients with AR positive castration-sensitive prostate cancer (CSPC), while 
dysregulated in function, respond well to ADT, however AR will have gains in 
oncogenic function such as gene amplification, mutations, and upregulation of 
androgen biosynthesis that bypasses therapeutic intervention to dampen therapy 
response. AR gene amplification occurs in 50% of CRPC patients that initially 
responded well to first-line therapy(24). In comparison to the castration-sensitive 
patients, AR expression and copy number increases from the amplification (25), 
bringing forth more opportunity for androgenic signaling in CRPC patients. Primary 
tumors with Gleason scores of 8 and above are correlated to have AR gene 
amplification. Approximately 10-30% of all CRPC patients contain mutations on 
AR in its different domains, with many of them gaining mutations through therapy. 
Mutations in each domain of AR can confer a number of changes in AR 
signaling(26), such as in the N-terminal domain, where two mutations, G142V and 
D221H, can lead to increased response to DHT through AR transactivation. In the 
DNA binding domain and hinge region, mutation T575A led to AR binding to  
8 
 
 
 
Figure 2. Canonical AR signaling pathway. Schematic showing the canonical signaling 
pathway of the Androgen Receptor (AR) in its dynamic nature. Testosterone (T), 
Dihydrotestosterone (DHT).   
 
 
 
 
 
 
9 
 
nonspecific promoters, increasing transcriptional activity. As for the ligand binding 
domain, mutations T877A and L701H leads to a loss of specific recognition of DHT, 
allowing ligands similar to DHT’s structure to bind and activate AR, including 
enzalutamide. These mutations also can reduce the interactions of antiandrogens, 
dampening activity. HSD3β1, CYP17A1, and AKR1C3, precursors to AR activity 
in testosterone synthesis are also overexpressed, leading to significant amounts 
of androgen being formed to activate AR transcriptional activity. Lastly, alongside 
AR gene amplification is AR coactivator gene amplification, where many of the 
coactivators form AR complexes on chromatin to increase transcription activity. 
For example, SRC-2/3, an AR coactivator is elevated in CRPC, leading to the 
activation of PI3K/AKT bypass signaling, inducing further cell proliferation and 
metastasis. Mutation and loss of co-regulators that degrade AR and coactivators 
(SPOP) via ubiquitination further increases AR transcriptional activity. SPOP 
mutations are found up to 30% of prostate cancer tumors. Overall, these structural 
changes along with genetic amplification alters the role of AR toward malignancy 
with little opportunity for intervention 
Treatment Landscape of Prostate Cancer  
Historical Therapeutic Perspective of Prostate Cancer 
Since the approval of oestrogen injection and prostatectomy in the 1940s, major 
therapies used to treat prostate cancer act to disrupt any potential for androgenic 
signaling, either through surgery or the pharmacological inhibition of testosterone 
synthesis or of AR. Therapy approval was based on a number of endpoints that 
exhibit some form of response to therapy, including 1) improvement on overall 
10 
 
survival (OS) or progression-free survival (PFS) of patients 2) PSA response rate 
(between 30% to 50%) and 3) limited grade i/ii adverse events.  
Preliminary studies in the late 19th to early 20th century had begun to establish 
androgen depletion as an approach to treating prostate cancer. In 1893, William 
White found atrophy in the prostate gland of dogs after castration, supporting 
androgen depletion(27). This finding was bolstered by similar experimentation on 
primates by Clyde Deming in 1935(28). In 1930 and 1940s, Charles Huggins found 
that using oestrogen administration produced a similar result to castration in dogs, 
leading to the Nobel prize winning discovery where he, along with Clarence 
Hodges, would treat prostate cancer patients with either castration or oestrogen 
administration and see improvements in their health (29). In 1960s, oral oestrogen 
was evaluated, and while there were decreases in serum testosterone levels and 
shrinkage in of enlarged prostates of many patients, setbacks such as 
cardiovascular health issues and resistance occurred, requiring further study into 
other approaches into treating this disease. 
While Huggins and Hodges were making their groundbreaking discovery, there 
were advancements in prostatectomy that focused on accessing the lymph nodes 
in pelvis and bleeding control, with the drawback being impotence. Also, alternative 
approaches were aimed to lower serum testosterone, leading to Andrew Schally’s 
discovery of the structure of luteinizing hormone-releasing hormone. With this 
structure, he synthesized agonists that take advantage of the feedback inhibition 
induced by surplus LH. Schally’s Nobel award winning discovery would go on to 
become standard treatments for prostate cancer such as Leuprolide (30,31). Side 
11 
 
effects from their administration included obstructive pain and lower libido, 
however, there were less cardiovascular health issues. From agonists being 
developed, there was assistance in the development of antagonists, such as 
cetrorelix, that also inhibits the synthesis of testosterone without the obstructive 
pain. During these studies, the interplay of the hypothalamus, the pituitary gland 
and the adrenal glands and how they influence androgenic signaling was 
established by Liao, Bruchsovsky, and Mainwaring(32,33,34). Steroidal anti-
androgens were created in order to treat PCa as well, the first being 
cyproterone(35). Cyproterone’s inhibition of AR occurred in cancer cells, but 
unfortunately occurs in normal cells that express AR in the hypothalamus and 
pituitary gland, leading to the induction of testosterone synthesis. To accommodate 
for this, an acetate group was added to cyproterone to prevent the induction of LH 
through binding to PR. Non-steroidal anti-androgens were developed such as 
flutamide and bicalutamide(36,37) to improve on side effects of lower libido and 
potency. Overall, these therapies set the framework for current therapies used to 
treat prostate cancer, such as abiraterone acetate and enzalutamide. Lastly, to 
assist proper therapeutic usage, an evaluation tool (Gleason Score) and screening 
tool (PSA) were developed for identifying prostate cancer and the different stages. 
From biopsies of the prostate, in 1960, Donald Gleason determined 5 different 
levels of aggressiveness of prostate cancer based on growth pattern and 
differentiation, with a scale from 1-5. Based on the two most prevalent subtypes 
shown in the biopsies, the score is determined, with a lower score representing 
12 
 
normal tissue architecture with well-shaped cells, and a higher score representing 
abnormal growth and cell shape. 
Leuprolide 
During the normal signaling of testes, the GnRH receptors release LH and FSH to 
be processed by the testes, specifically by Leydig cells and Sertoli cells. Once 
activated, Leydig cells initiate testosterone synthesis, and the Sertoli cells 
synthesize Inhibin B, which inhibit FSH release. Overproduction of testosterone 
causes a feedback inhibition to the production of GnRH by the HPA axis and 
subsequently, the anterior pituitary releasing LH, halting testosterone synthesis. 
GnRH agonists take advantage of this signaling cascade like Leuprolide through 
its mechanism of action stimulating testosterone synthesis towards saturation to 
cause inhibition. In a clinical trial that compared Leuprolide to the nonsteroidal ER 
inhibitor diethylstilbestrol, 86% of the patients either had complete to partial 
response or higher stabilization of disease with less of the side effects, mainly hot 
flashes (38). In 1985, FDA approved the use of Leuprolide for prostate cancer, 
which has become a standard first line ADT used in the clinic. 
Taxanes 
Docetaxel and Cabaxitaxel 
As a current standard of care for CRPC, taxanes have been used in chemotherapy 
for a variety of cancers. Taxanes bind the β subunits of tubulin in microtubules, 
preventing depolymerization in mitosis and causing cellular death.  AR when 
dimerized has the affinity to utilize the microtubules to onboard into the nucleus, 
showing AR’s transport as a vulnerability taken advantage of by docetaxel. In 
13 
 
phase III TAX 327 clinical trial that led to FDA approval in 2004, docetaxel was the 
first to show higher OS in metastatic CRPC (mCRPC) patients who were treated 
with prednisolone vs. mitoxantrone. Docetaxel also decreased PSA > 50% in 
patients(39). Side effects associated with this drug are nausea, vomiting, motor 
and sensory neuropathies, as well as cytopenias. In the phase III CHAARTED 
clinical trial, metastatic castration sensitive prostate cancer (mCSPC) received 
docetaxel in combination with ADT, resulting in longer OS at 57.6 months vs. 44.0 
months with ADT alone(40). In response to these agents, CRPC drives docetaxel 
resistance by modifying its binding and activation of survival pathways. In vitro, it’s 
been found that overexpression of drug efflux transporters, cytokines, along with 
less p53 phosphorylation contribute to resistance. To overcome resistance, 
cabaxitaxel was developed and tested in 2008 and approved in 2010. In the phase 
III TROPIC trial, cabaxitaxel had antitumor activity in docetaxel-resistant prostate 
cancer as well as being better tolerated, with similar side effects to 
docetaxel(41,42,43).   
Targeting AR 
Abiraterone Acetate and Enzalutamide 
Targeting AR has been the mainstay of treatment for CSPC and CRPC with newer 
hormonal therapies that impact androgen production and AR action. Abiraterone 
acetate was first to act indirectly against AR as a cytochrome p450 17A1 inhibitor, 
which reduced endogenous steroids from being converted into androgens, and 
subsequently, DHT available for AR action. In the STAMPEDE trial, where CSPC 
patients received abiraterone acetate plus ADT, there was higher probability of OS 
of years at 83% vs. 76% when ADT is given alone(44).  In the LATITUDE trail, 
14 
 
where mCSPC patients received ADT plus abiraterone acetate vs. placebo, at the 
3 year mark, there was higher OS at 66% for patients receiving abiraterone acetate 
vs 49% for patients receiving placebo, with longer radiographic PFS at 33 months 
vs. 14 months(45).  In the COU-AA-302 trial, where chemotherapy-naive patients 
received prednisone along with abiraterone acetate, rPFS was higher in the 
abiraterone group at 16.5 months vs. the placebo group’s 8.3 months. There was 
higher median OS   with the time point not being reached vs. the placebo’s 27.2 
months (46). In the AFFIRM trial, 26% of the mCRPC patients who received 
abiraterone acetate had a decrease in PSA greater than 30% (47). Side effects 
seen in the patients include hypertension, hypokalemia, fluid retention, and sexual 
dysfunction.  
Enzalutamide directly inhibits AR by competitively binding against DHT in the 
ligand binding domain of AR. By preventing this action, AR homodimerization, 
nuclear translocation, binding to DNA, and recruitment of co-activators cannot 
occur in the canonical fashion. In the AFFIRM trial, mCRPC patients that have 
already received chemotherapy were given enzalutamide, resulting in a higher OS 
of 18 months vs. 14 months to placebo, with 54% of patients having a PSA 
response to therapy (47). As for the PROSPER trial(48), non-mCRPC patients who 
were received ADT also received either enzalutamide or placebo, resulting in 
longer metastasis-free survival of 36.6 months vs. 14.7 month in the placebo 
group, leading to FDA approval in non-metastatic CRPC in 2018.  As for the 
PREVAIL trial, where chemotherapy-naïve mCRPC patients received 
enzalutamide, treatment duration lasted to 17 months vs. 5 months to placebo. In 
15 
 
addition, there was longer OS of 32.4 months vs. 25 months to placebo, while 
adverse events were the same (49). In the EnzaMET trial, in comparison to the 
mCSPC patients who received docetaxel, a similar pattern is seen as with 
abiraterone acetate, though lower OS at 63% vs. 71% to those who didn’t receive 
docetaxel, yet higher PFS 30% in the docetaxel arm vs. 17%(50). Side effects of 
enzalutamide include fatigue, GI issues, hot flashes, and sexual dysfunction. 
Apalutamide and Darolutamide 
Recent advancements in AR inhibition have been made since enzalutamide, with 
the goal of preventing metastasis progression and reducing the side effect profile 
for specific facets of prostate cancer. To address this, AR antagonists 
darolutamide and apalutamide were developed with unique chemical structure, 
improving upon molecular interaction and subsequently antiandrogenic activity 
with AR in its ligand binding domain. In the TITAN trial, mCSPC patients treated 
with ADT were given apalutamide, resulting in higher radiographic PFS at 68.2% 
compared to placebo at 47.5% with lower risk of death(51). PSA was found to be 
nearly undetectable (≤0.2ng/ml) in 68.4% of the patients treated with apalutamide 
to placebo at 28.7%. Safety-wise, the most common adverse event seen in these 
patients were rash, occurring in 27% of patients, along with hot flush and fatigue 
with lower occurrence were hypothyroidism and ischemic heart disease. In the 
SPARTAN trial, non-mCRPC patients who continued on ADT were given 
apalutamide, increasing the median time point of metastasis free survival to 40.2 
months for those treated with apalutamide versus ADT alone at 16.2 months (52). 
Time to PSA progression was extended beyond the scope of 44 months of study 
16 
 
versus placebo at 3.7 months. Adverse events that were seen in the apalutamide 
group were similar to the TITAN trial. In 2018 the FDA approved the use of 
apalutamide for non-mCRPC and in a year later approved apalutamide for 
mCSPC. Though an improvement from enzalutamide, both enzalutamide and 
apalutamide still face resistance mechanisms such as AR mutation F876L, located 
in the binding pocket of AR, which reduces these interactions with the inhibitors. 
To circumvent this, darolutamide was developed and in the ARAMIS trial, non-
mCRPC patients were given darolutamide along with ADT, leading to longer 
metastasis free survival of 40.4 months versus placebo 18.4 months, with lower 
risk of death(53). PFS was also higher at 36.8 months for darolutamide to 14.8 
months for placebo. Time to PSA progression was nearly five times longer 
compared to placebo, with 33.2 months to 7.3 months. Adverse events were 
similar to apalutamide and enzalutamide but at lower occurrence, showing 
improvement in tolerability of this antiandrogen. In the follow-up ARASENS trial, 
mCSPC patients were given darolutamide in combination with ADT and docetaxel. 
Lower amount of deaths occurred in the darolutamide arm and an increase in OS 
was observed at 62.7% vs. 50.4% for placebo(54). Time to CRPC development 
was beyond the timeline of the study with darolutamide vs 19.1 months for placebo. 
The safety profile was similar with no apparent increase, leading to the FDA 
approval of darolutamide for mCSPC in 2022.  
Platinum Agents 
In addition to androgenic signaling, AR functions as a regulator of DNA damage 
response, participating in repair via homologous recombination and non-
17 
 
homologous end-joining(55). In many prostate cancers, about 10% contain 
genomic instabilities that can contribute to tumorigenesis by repairing defected 
DNA. Within these aberrations are mutations in DNA response genes BRCA1, 
BRCA2, along with SPOP(56, 57, 58, 59). These gene mutations present 
therapeutic sensitivities that platinum therapies are able to take advantage of to 
treat CRPC. In a phase II trial where CRPC patients who have received docetaxel, 
cisplatin was given with prednisone, resulting in 20% of patients having a PSA 
response rate greater than 50% (60). Adverse effects were mainly neuropathy. In 
another monotherapy trial, carboplatin was given, with patients feeling less pain 
and having more disease stabilization. In addition, 28% of those patients had a 
PSA response rate greater than 50%. However, leukopenia, thrombocytopenia, 
and fatigue were cited in the study. These two drugs were also combined with 
taxanes in clinical trial, with the major benefit being an increase in the percentage 
of patients with PSA decline greater than 50%.  
Sipuleucel-T     
Sipuleucel-T functions as a vaccine that improves the white blood cells in PCa 
patients to trigger T-cell immune response in response to prostate antigen protein 
(PAP). In the IMPACT clinical trial, 512 mCRPC patients were administered three 
infusions of sipuleucel-T, resulting in a median OS of 25.8 months vs. placebo’s 
21.7 months, showing a slight improvement (61). However, many patients 
presented with increases in PSA, pain, and bone metastases in both treatment 
groups. Observable adverse events were fever and chills, likely associated with 
the immune response caused by the vaccine. 
18 
 
Conclusion and the Future 
With this knowledge spanning over 100 years of innovative medicine, prostate 
cancer now more than ever continues to have an impact on patient lives. 
Solidifying associated risk factors in prostate cancer has assisted in earlier 
screenings and drawn special attention to health disparities when it comes to non-
Caucasian men. Clinical trial design of the primary and secondary endpoints’ focus 
on survival and PSA decline has now shifted to understanding patient adverse 
event tolerability. Plus, setting the foundational science of our physiology in HPA 
axis involvement and AR signaling has led to multiple therapeutic targets being 
thoroughly studied in labs and in clinical trials. And yet, unfortunately, resistance 
to these newer therapies continues to take new forms to blunt their therapeutic 
benefits, prompting investigators to revisit therapies to further improve survival or 
to use them as preventative measures. Combination therapy is becoming an 
established approach due to the potential of improving the survival of PCa patients 
by combating resistance mechanisms, such as what was done in the STAMP and 
STRIDE clinical trials, which studied the OS and adverse events of mCRPC 
patients treated with enzalutamide or abiraterone acetate plus sipuleucel-T, 
though no benefits were seen(62,63). In addition, more clinical trials and FDA 
approvals are happening at earlier progression points of prostate cancer, as seen 
by the FDA approval of enzalutamide for metastatic castration-sensitive prostate 
cancer in 2019. Newer therapeutics such as PARP inhibitors have become popular 
by taking advantage of loss of function mutations in homologous recombination 
DNA repair found in many PCa patients, mainly through BRCA1/2. Through 
synthetic lethality of BRCA dysfunction and PARP inhibition, these inhibitors cause 
19 
 
lasting single strand breaks in DNA that remain, leading prostate cancer cells 
toward irreparable damage and subsequently, apoptosis (64). PARP signaling in 
repair is highly active in prostate cancer cells, and as it pertains to AR, it is 
somewhat regulated by androgenic signaling. PARP inhibitors also prove 
beneficial towards greater prostate cancer cell death. Based on the PROfound trial, 
PARP inhibitor, olaparib, was approved by the FDA for mCRPC(65). Additionally, 
studies on better biomarkers of PCa are also underway, due to PCa’s multiple 
phenotypes, such as neuroendocrine and double-negative prostate cancer, that 
do not involve PSA.  For neuroendocrine prostate cancer chromogranin A and 
synaptophysin are key biomarkers, both of which can correlate to poorer prognosis 
for prostate cancer. Other transcription factors expressed such as MYCN and 
FOXA1/2 are also considered in biopsy. The field has also continued to study 
PSMA, a cell surface protein expressed by PCa cells, to image the location of the 
disease and its metastasis, allowing us to increase detection further via PET scan. 
In addition, newer radioligand-based therapies that target PSMA have also been 
recently approved by the FDA. 
 
 
 
 
 
 
20 
 
Chapter 2: 
Resistance Mechanisms in CRPC and the role of kinases 
Introduction 
Unfortunately, a subset of PCa patients who continue to receive endocrine 
therapy/chemotherapy won’t respond after a number of months due to resistance, 
prompting investigators to better understand mechanisms of resistance involved 
in CRPC. Known resistance mechanisms can range from the expression of AR 
splice variants (AR-Vs) to increased steroidal activity outside of AR. In addition, 
PCa cells molecularly adapt to initiate bypass signaling resulting in varying 
phenotypes of PCa, including aggressive variant PCa (AVPC), neuroendocrine 
PCa (NEPC), and double negative PCa(DNPC). Secondary causes also can 
include germline mutations associated with PCa progression and other co-
morbidities, such as those seen with BRCA1/2 and HOXB13(57,66,67). 
Expression of AR Variants 
Though AR is inhibited with therapies such as abiraterone acetate and 
enzalutamide, resistance is acquired through the alternative splicing of AR mRNA, 
leading to truncated species of AR called AR splice variants (AR-Vs)(68). 
Alternative splicing is through the incorporation of cryptic exons and exon skipping 
events during translation of AR, resulting in the lack of ligand binding domain and 
hinge region, contributing to AR-V’s constitutive ligand-independent activity all 
while conserving the N-terminal domain and DNA binding domain (Figure 3). There 
are over 20 AR-Vs identified, but AR-V7, AR-V9, and AR-V567es are three major 
AR-Vs that have been investigated in detail and implicated in resistance to 
hormonal therapies. Roles include non-canonical mechanisms to maintain AR 
21 
 
activity, along with bypass signaling. For example, AR-V7, and AR-V567es, due to 
having the N-Terminal Domain, homodimerize and heterodimerize with other 
variants and AR-FL without the need of ligand, expanding the advantage taken by 
prostate cancer for abnormal AR signaling(69,70). AR-V1, though it remains in the 
cytosol, dimerizes with AR-FL independent of androgen. In addition, AR-Vs 
participate in transient DNA binding with other AR dependent co-activators(71).    
Clinically, AR-V7 can significantly reduce the PSA response rate to hormonal 
therapies in comparison to prostate cancer patients who lack AR-V7. In one 
retrospective analysis, 209 PCa patients had gone through ADT, finding the 
response in AR-V7+ patients was 41% vs. 82% in AR-V7-(72). In mCRPC cases, 
the response rate drops to near 0, ridding any possible efficacy. In addition, these 
patients are known to have a worse PFS at 3 months and OS at 8 months, with 
AR-V7 negative patients having PFS at 8 months and OS at 22 months. 
Interestingly, we also see that patients with AR-V7 also have a higher expression 
of AR-FL, corresponding to AR amplification. In regards to treatment, taxanes have 
greater efficacy with AR-V positive patients compared to hormonal therapies, 
though data has not been solidified. In one case, taxane administration had an OS 
of 9 months in AR-V7+ patients, yet still was lower compared to AR-V7- patients, 
with an OS of 20 months. AR-V9 has also contributed to disease progression. 
Biopsies in the PROMOTE study showed that high expression of AR-V9 in patients 
correlates to disease progression when treated with abiraterone acetate(73). 
Additionally, AR-V9 mRNA was co-expressed with AR-V7 mRNA in these samples  
 
22 
 
 
 
Figure 3: AR splice variant (AR-V) signaling and exon structure. Schematic 
showing AR splice variant (AR-V) signaling and exon layout of AR-full length (AR-
FL), AR splice variant 7 (AR-V7), and AR splice variant 567es (AR-V567es)  
 
 
 
 
 
 
 
 
 
23 
 
and PDX clinical samples LuCaP 35-CR and 147 of liver metastasis(74). AR-
V567es, while not always expressed in CRPC, has been confirmed in many 
metastasis and having a mitotic transcriptome, contributing to disease(75). Also, 
investigators have shown AR-V567es to be trafficked into the nucleus in response 
to taxane therapy due to retention of microtubule binding domains, however further 
study is needed(76).  
Upregulation of Other Steroid Receptor Signaling 
Though AR is a major driver of PCa progression, there are contributions to CRPC 
by nuclear receptors ERα/β, PR, GR, and MR that occur from prolonged ADT and 
hormonal therapy. By blocking androgenic activity, PCa tumors adapt by rewiring 
their activation to the respective ligands of these receptors through loss of AR. 
ERα and ERβ have differential actions and location to one another, with ERα being 
located in the basal and stromal cells as a tumor promoter, and ERβ being located 
in the prostate epithelium as a tumor suppressor(77).ERβ is expressed in CSPC 
and can slow tumor activity when stimulated. Loss of ERβ initiates the loss of tissue 
differentiation, expanding basal cells and hyper-activating ERα leading to 
aggressive phenotypes of PCa(78). Clinically, ERα is highly expressed in Gleason 
4 and 5 grade PCa tumors and is not as seen in lower grade, citing its relevance 
solely in CRPC. In tandem with ERα, estrogen-dependent nuclear steroid PR is 
heavily expressed in CRPC and bone metastases. GR is expressed both in the 
stroma and epithelium of normal prostate tissue, which decreases during PCa 
initiation. Over the course of PCa progression, GR expression is increased in 
metastatic tissue of PCa patients that have been subjected to long term 
24 
 
administration of ADT, hormonal therapy, and/or chemotherapy. Under 
glucocorticoid activation, PCa cancer cells activate cell survival and immune 
response pathways. Clinically, high GR expression corresponds to lower PFS in 
PCa relapsed patients(79). However, conflicting data has suggested another role 
of GR where it is anti-tumorigenic, where the addition of glucocorticoids reduces 
androgens in men which decreases AR activity. Yet molecularly, GR and AR are 
structurally similar and have major overlap in their transcription program, allowing 
for PCa progression to continue in the presence of therapy. Lastly, MR operates 
in an antagonistic role to AR, where stimulation of MR inhibits AR(80), and MR 
inhibition leads to PCa cell viability and AR activation. 
Lineage Plasticity and Neuroendocrine Differentiation 
CRPC is a heterogeneous disease, and there are cases where ADT and hormonal 
therapy drive some CRPC tumors to change their phenotype. Cells transition from 
being dependent on AR into a mixture of cellular states branching toward an 
epithelial-mesenchymal transition(EMT)-like state similar to stem cells(81,82), with 
the administration of androgen being able to reverse this state. In in vitro and 
clinical studies, neuroendocrine markers including CHGA and NSE are driven by 
EMT and stem cell regulators SOX (SOX2/11) in PCa(81,83). Kinase signaling in 
the Interleukin-6/STAT3 and WNT/β-catenin pathways also promote EMT and 
stem cell differentiation in PCa cells under therapy(84,85). In this adaptation 
towards EMT, neuronal transcription factors (e.g. NEUROD1, ASCL1, MYCN) are 
activated, AR and tumor suppressor RB1 are lost, TP53 is mutated, all of which 
allow for the development of neuroendocrine PCa (NEPC)(86,87). In comparison 
to adenocarcinoma, loss of RB1 and overexpression of MYCN occur in 50% of 
25 
 
NEPC tumors while overexpression of AURKA occurs in 40% (88). Some cell 
surface markers like CD44 correlate exclusively to specific neuroendocrine 
markers NSE and can upregulate NEPC invasiveness(89,90). Key features of 
NEPC include epigenetic changes that contribute to progression, such as 
epigenetic regulator EZH2, which methylates H3K27, impacting expression of cell 
cycle and DNA repair genes. EZH2 is overexpressed in many tumors including 
NEPC, and is associated with poor prognosis. In some studies, EZH2 interacts 
with MYCN causing inhibition of AR transcriptional program driving cells toward 
NEPC(91). In terms of rarity, some cells in certain instances can transition away 
from both AR and neuroendocrine programming, making it double negative 
prostate cancer (DNPC). Because of this rarity, there are no set markers for this 
phenotype aside from the lack of luminal and neuroendocrine markers. 
Therapeutic studies have shown there is immune system changes and FGF/MAPK 
kinase signaling that can be targeted due to their activity in DNPC(92). 
Increased Kinase Signaling 
There are approximately 500 kinases within our kinome, functioning in varying 
roles for maintaining a cell’s viability(93). In a kinase’s conserved nature, 
phosphorylation and other post-translational modifications contribute to cell 
maintenance. In many cancers, these actions are taken advantage of through 
genetic mutations of PCa that transform kinases from their conserved nature to 
having abnormal behavior. Common examples are the hyper-activation of kinase 
bypass signaling pathways which promote tumor growth and metastasis. In 
prostate cancer, genetic abnormalities in kinases are rare, concluding that it could 
be the overexpression of non-mutated kinases and their hyperactivity by an 
26 
 
abundance of stimulation of upstream ligand/receptor binding that play a big role 
in PCa vitality. Tyrosine kinase networks also enrich in major hallmarks of cancer 
that influence stemness, migration and invasiveness of cancer and recent work 
from our laboratory has also implicated RET kinase as hyperactive and a 
therapeutic target in NEPC(94,95). Within these tumor phenotypes, AR can shift 
from androgen dependent signaling to more androgen-independent signaling in 
castrate conditions by recruiting kinases to engage in phosphorylation and binding 
to activate AR signaling(96). AR phosphorylation influences AR transcription, 
stability, localization, and its export from the nucleus. Major phosphorylation sites 
that have been of focus are S81, S213, Y267, Y363, S515, Y534, S650, and T850, which 
are substrates of upstream kinases such as CDKs 1/5/7/9, AKT, PIM-1, ACK, 
MAPK, SRC, ETK, JNK, and p38. In a functional screen by Faltermeir(97), these 
and some other kinases were identified to promote metastasis, presenting kinases 
as a pivotal point of study in their involvement with prostate cancer. While the use 
of kinase inhibitors is not a new approach towards treatment in prostate cancer, 
many kinase inhibitors have been tested in clinical trials for primary prostate cancer 
and CRPC and failed in primary and secondary outcomes on improving survival.  
PI3K/AKT/mTOR pathway 
One major genetic adaption that occurs in PCa is the mutation and loss of tumor 
suppressor PTEN. PTEN’s course of action is as a tumor suppressor converting 
PIP3 to PIP2, which negatively regulates PI3K/AKT/mTOR. With PIP3 not being 
converted, there is constitutive activation of the pathway, promoting cell 
invasiveness and proliferation. Greater than 70% of PCa patients have this 
mutation or loss during CRPC progression(14,15). In addition, other aberrations 
27 
 
such as amplification of PI3K subunits is found up to 30% of CRPC patients. With 
PTEN loss and PI3K amplification, recruitment of AKT occurs to the cellular 
membrane, activating downstream targets. AKT activation has been found to 
correspond with higher Gleason score and while it is rare for AKT to be mutated, 
its regulators like FKBP5 (AR target protein) can be downregulated to supplement 
its signaling(98). As for mTOR, its components can be amplified by DEPTOR 
amplification, which corresponds to worse prognosis(99,100). DEPTOR 
amplification not only increases AKT signaling further, but also protein kinase C α, 
which plays roles in calcium signaling for cell survival and autophagy. 
Therapeutically, preclinical studies with mTOR and AKT inhibitors have shown 
promise, yet require further study, due to conflicting clinical trials results. For 
example, Ipatasertib (AKT inhibitor) in the phase III trial, IPATential150, were given 
to mCRPC patients in combination with abiraterone or placebo(101). rPFS 
improved for patients with negative PTEN status though the survival difference and 
safety profile was minimal for the intent to treat population, leading to failure of one 
primary endpoint.  
MAPK-ERK pathway 
Another critical kinase in CRPC treatment resistances is MAPK. MAPKs, are a 
group of serine-threonine kinases and three members of MAPK (JNK, p38 and 
ERK1) affect cellular damage and death, as well as drive PCa cells toward 
androgen independence. Normally, JNK and p38 act as stress activated protein 
kinases, but operate to initiate apoptosis when needed as cells come in contact 
with therapeutics. However, these kinases may be induced by therapy to operate 
in the opposite manner. JNK is able to protect cells from apoptosis and nutrient 
28 
 
deprivation, promoting abnormal malignancy(102,103). p38 has been shown to 
inhibit TNF-based apoptosis of LNCaP cells(104). In addition, these two kinases 
also interact with matrix metalloproteinases (MMPs), important for tissue modeling, 
to degrade the extracellular matrix of epithelium and allow these MMPs to promote 
metastasis(105). ERK1 has been well established in its role of being 
overexpressed and stimulated by a multitude of ligands that lead to cell 
proliferation.  In fact, in a transcriptome study of mCRPC patients, this MAPK was 
amplified in 32% of patients(106). Through mitogens and cytokines, ERK1, being 
in part of the Ras-Raf-MEK-ERK cascade, primarily interacts with nuclear proteins 
and factors such as CMYC and ETS1. Interestingly, in some studies, ERK1 is also 
anti-apoptotic(107) by phosphorylating caspase 9 and bcl2 proteins and has the 
capability to be. Overall, the roles of MAPKs and their signaling are able to shift 
the tide in PCa development and its treatability. Currently, trametinib, inhibitor of 
ERK1 downstream target MEK, is currently under phase II trial for mCRPC 
(NCT02881242).  
SRC Family Kinases 
SRC Family kinases are a group of non-receptor tyrosine kinases primarily 
involved in cell proliferation, cell differentiation, and cell metabolism. The members 
are YES, FGR, LYN, LCK, BLK, HCK, FYN, FRK, YRK, and SRC(108). These 
kinases have four domains that are involved in kinase activity. The unique domain, 
which has been shown to contribute to kinase location, linkage of downstream 
kinases, and apoptosis, all based on its phosphorylation and cleavage. The SH3 
and SH2 domains, which coordinate to activate or deactivate the kinase. Lastly, 
the kinase domain which houses the activation tyrosine residue Y416 and the 
29 
 
inhibition tyrosine Y527, via phosphorylation. In normal prostate development, 6 of 
the members expressed. When prostate cancer occurs, LYN and FYN are 
overexpressed and overall SFKs are hyper-activated.  Three members (SRC, 
FYN, LYN) contribute to prostate tumorigenesis in cell line models and prostatic 
mouse models via RTKs like EGFR, integrin α/β, and/or FAK. By interacting with 
FAK, SRC family kinases move to an open conformation to bind and phosphorylate 
other proteins involved in cellular growth (STAT3, PI3K, MEK-ERK)(109). SRC’s 
involvement with AR is two-fold through phosphorylation and binding (Figure 4). 
Phosphorylation-wise, there is a substrate on a AR for SRC phosphorylation on 
Y534. This residue has been known to contribute to AR nuclear translocation and 
overall AR transcription. SRC’s SH3 domain is able to bind to AR in a proline-rich 
motif located in the N-Terminal domain, leading to SRC having an open 
conformation that can lead to bypass signaling. Clinically, in a phase II/III trial, 
patients who have received docetaxel were administered dasatinib, which is a dual 
BCR-ABL and SRC multi-kinase inhibitor(110). Unfortunately, dasatinib failed to 
improve OS in mCRPC patients, with an improvement of only 0.3 months vs 
placebo. 
 
 
 
 
 
 
30 
 
 
Figure 4: SRC kinase interaction with AR. Schematic showing SRC kinase 
contributions to AR signaling via phosphorylation and binding. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
31 
 
Chapter 3:  
Saracatinib synergizes with enzalutamide in CRPC 
Introduction 
Prostate cancer remains the highest diagnosed non-skin cancer amongst the 
American male population and is second highest in deaths, next to lung cancer. 
When primary prostate cancer is diagnosed in patients, many clinicians will either 
prescribe surgery, radiotherapy, and/or androgen deprivation therapy (ADT) that 
interfere with androgen synthesis such as leuprolide (GnRH agonist)(111). While 
potentially curative in up to 70-80% of men, the remaining 20-30% of men will 
develop tumors that become resistant to ADT with a rising prostate specific antigen 
termed castration resistant prostate cancer (CRPC). Newer, second generation 
therapies such as enzalutamide (AR competitive antagonist)(112,113) and 
abiraterone acetate (CYP17A inhibitor)(114) have been developed to prolong 
survival in both hormone-naïve and hormone-resistant cancer. However, none of 
these agents are curative, prompting investigators to elucidate the major 
mechanisms of resistance in CRPC. 
Previous literature has implicated several major mechanisms of resistance in 
CRPC such as the amplification of the androgen receptor (AR), loss of PTEN, and 
TMPRSS-ERG fusions(115,116). One key mechanism is the emergence of 
androgen receptor splice variants (AR-Vs)(117). AR-Vs are constitutively-active 
truncated versions of AR that lack the C-terminal ligand binding domain and can 
function independently in the presence of androgen, leading to additional AR 
transcriptional activity. Clinically, AR-Vs (in particular AR-V7) increase in 
abundance and are implicated in resistance to prior hormonal therapies such as 
32 
 
abiraterone acetate and enzalutamide(118). Recent studies show chemotherapy, 
such as docetaxel, has a higher treatment efficacy in patient tumors expressing 
AR-V7(119). Yet, these therapies are toxic, leading to side effects that heavily 
impact quality of life for the patient. Chemotherapy also does not inhibit primary 
mechanisms of resistance involving AR, revealing the need for alternative 
approaches to treatment.  
Another mechanism of resistance is increased tyrosine kinase signaling(120). Our 
previous work evaluated the phosphoproteome of CRPC patients at autopsy. 
Using multi-omic integration, we took a kinase-centric approach to identify SRC 
kinase as a key activated kinase and signaling hub in CRPC(94). SRC kinase, also 
known as c-SRC, is a non-receptor tyrosine kinase that plays major roles in cancer 
cell proliferation, communication, and adhesion(121,122). Specifically to prostate 
cancer, SRC kinase phosphorylates AR at Y534(96) and directly interacts with the 
AR N-Terminal domain via hydrophobic interactions with SRC’s SH3 domain(123). 
Phosphorylation of AR by SRC kinase maintains AR stability and transcriptional 
activity(124,125) along with regulating other kinases that phosphorylate other 
residues of AR via growth factor stimulation and kinase crosstalk(126,127,128). 
While intriguing as a pre-clinical target, SRC kinase inhibition in clinical trials for 
treatment of CRPC has not been successful(129). Administration of a dual SRC 
kinase and BCR-ABL inhibitor, dasatinib, failed in late stage CRPC clinical trials 
as both a monotherapy and in combination with docetaxel(110). These clinical trial 
results dampened the excitement around SRC kinase as a viable target in CRPC. 
However, several explanations may exist as to why these trials were not 
33 
 
successful, such as lack of patient stratification and broadly targeted combinations 
that do not focus on AR inhibition. 
To resolve this, in this study, we provide pre-clinical data that supports SRC kinase 
inhibition with standard of care hormonal therapies such as enzalutamide for 
treating AR positive CRPC. We find that enzalutamide plus saracatinib was 
strongly synergistic in AR-full length positive (AR-FL+) cell lines, regardless of AR-
V positive (AR-V+) status. Meanwhile, docetaxel plus saracatinib was not as 
effective, especially in cell lines expressing AR-Vs, supporting the potential failure 
of dasatinib in the previously mentioned clinical trial with docetaxel. We also found 
that saracatinib ablated AR Y534 phosphorylation, AR-V protein expression, and 
altered AR specific gene signatures, suggesting that AR stability and 
transcriptional activity was perturbed through SRC kinase inhibition. Lastly, we 
also observed that saracatinib induced higher levels of γH2AX, DNA replication 
stress when in combination with enzalutamide, and markers of apoptosis in an AR-
FL+/AR-V+ cell line 22Rv1.  
Results 
Enzalutamide and saracatinib yields strong synergy in AR-FL+ cell lines 
To begin studying our drug combinations, we selected prostate cancer cell lines 
with different AR genetic backgrounds that also expressed SRC kinase (Table 1), 
expecting a myriad of responses that will allow us to evaluate synergy between 
our selected drugs. Using these cell lines, we generated dose-response curves to 
determine the IC50s of enzalutamide (enza), docetaxel (DTX), and the SRC 
34 
 
 
Table 1: Genetic background of cell lines used in vitro studies with corresponding AR 
and SRC status. All cell lines have SRC kinase. AD1, 22Rv1, and LNCaP95 have 
AR-FL. 22Rv1, LNCaP95, and R1-D567 have varying amounts of AR-Vs. DU145 is 
null of AR species. 
 
 
 
 
 
 
 
 
 
35 
 
 
 
 
Figure 5: Dose-response Curves of Enzalutamide, Saracatinib, and Docetaxel. 
Enzalutamide is a second-generation AR competitive inhibitor. Saracatinib is a SRC 
family kinase inhibitor with an affinity of c-SRC. Docetaxel is a microtubule 
destabilization agent. IC50’s for each drug ranges between nM-µM. 
-1 0 1 2 3
0
50
100
150
Enzalutamide Dose-Response
log[enzalutamide] (μM)
C
e
ll
 V
ia
b
il
it
y
 %
AD1
22Rv1
LNCaP95
R1D567
DU145
AD1 22Rv1 LNCaP95 R1D567 DU145
IC50 (µM) 86.21 90.23 32.49 59.92 35.62
-2 -1 0 1 2 3
0
50
100
150
Saracatinib Dose-Response
log[saracatinib] (μM)
C
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ia
b
il
it
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 %
AD1
22Rv1
LNCaP95
R1D567
DU145
AD1 22Rv1 LNCaP95 R1D567 DU145
IC50 (µM) 4.736 31.02 5.225 6.573 3.06
-2 -1 0 1 2
0
50
100
150
 Docetaxel Dose-Response
log [docetaxel] (nM)
C
e
ll
 V
ia
b
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it
y
 %
AD1
22Rv1
LNCaP95
R1D567
DU145
AD1 22Rv1 LNCaP95 R1D567 DU145
IC50 (nM) 0.7005 0.6415 0.8295 0.8229 0.4429
36 
 
kinase inhibitor saracatinib (sara) (Figure 5). Using the IC50 dosage, we 
administered serial dilutions of enza plus sara or DTX plus sara to our cell lines. 
Synergy was then calculated via Bliss Independence (BI) and the Combination 
Index (CI) equation via Chou-Talalay method through CompuSyn 1.1(130, 131). 
AR-FL+ only AD1 cells showed synergy in both enza plus sara and DTX plus sara 
combinations (Figure 6,7). Synergy was also observed in both AR-FL+ and AR-V+ 
22Rv1 and LNCaP95 cells (Figure 6,7) with the enza plus sara combination. 
Interestingly, synergy was observed in LNCaP95 cells with the DTX plus sara 
combination but not in 22Rv1 cells. AR-V+ R1D567 cells showed synergy in the 
enza plus sara combination via the BI model (Figure 6,7) and showed additivity via 
the CI model. There is a lack of synergy seen between DTX plus sara in R1D567 
using both models (Figure 6,7). Using CompuSyn 1.1, we were able to generate a 
dose reduction index (DRI), which determines the fold reduction of each drug when 
in combination with another drug. In our 22Rv1 and LNCaP95 cell lines, we see a 
reduction up to 5-fold for both enza and sara when in combination (Figure 8) We 
also observe a 3-fold reduction for DTX and a near zero fold reduction for sara 
when in combination, which suggests that the reduction of sara was more potent 
37 
 
   
  
Figure 6: Synergy observed between Enzalutamide and SRC kinase inhibitor 
Saracatinib in AR+ Positive Cells. Results were calculated with Bliss Independence 
equation (Fab=Fa x Fb). Fab is considered the line of additivity. Any result greater 
than Fab is considered synergistic and any result less than Fab is considered 
antagonistic. 
E
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R1D567 Drug Group Synergy
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Antagonistic
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Synergistic
Antagonistic
38 
 
 
 
 
 
Figure 7: Synergy observed between Enzalutamide and SRC kinase inhibitor 
Saracatinib in AR+ Positive Cells. Results were calculated with Combination Index 
(CI) equation (CI= D1/E1+ D2/E2). D is the dose of drug when in combination 
(calculated by CompuSyn based on dose response curve input) and E is the dose of 
drug when given alone. Dose used is IC50. 1 is considered the line of additivity. Any 
result less than 1 is considered synergistic and any result less than Fab is 
considered antagonistic. 
 
 
0.
25
0.
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0.
75
0.
90
0.
95
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Enzalutamide +Saracatinib
fraction affected (fa)
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R1D567
0.
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Docetaxel + Saracatinib
fraction affected (fa)
C
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 V
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AD1
22Rv1
LNCaP95
R1D567
39 
 
 
 
Figure 8: Synergy observed between Enzalutamide and SRC kinase inhibitor 
Saracatinib in AR+ Positive Cells. Dose Reduction Index (DRI) determines how 
many fold is the dose of drug reduced when in combination with another drug. Dose 
Reduction Index at 90% of each cell line affected with the enza plus sara 
combination and the DTX plus sara combination. 
 
 
 
 
 
 
0 5 10 15
R1D567
LNCaP95
22Rv1
AD1
DRI Enza+Sara @ fa90
Fold Reduction
C
e
ll
 L
in
e
Enzalutamide
Saracatinib
0 5 10 15
R1D567
LNCaP95
22Rv1
AD1
DRI DTX + Sara @ fa90
Fold Reduction
C
e
ll
 L
in
e
Docetaxel
Saracatinib
40 
 
in the presence of enza versus DTX. Lastly, we show no synergy, but rather 
antagonism, between enza plus sara and DTX plus sara in the AR negative DU145 
cells (Figure 6). We expected no synergy for enza plus sara in DU145 cells due to 
enza’s inability to enact its mechanism of action because of DU145’s lack of AR. 
Overall, these findings indicate there is substantial synergy between enza and sara 
in PCa cell lines and this synergy potentially coincides with the presence of AR-FL 
alone or in the presence of AR-V expression.  
Saracatinib decreases AR phosphorylation and AR-V protein expression via 
SRC kinase inhibition 
Previous literature has shown that certain kinases can regulate AR function, 
stability, and activity via phosphorylation on particular residues of AR. For 
example, CDK1, 5, and 9 phosphorylates AR S81, which is located within the N-
terminal domain of AR and regulates AR transactivation, transcription, and nuclear 
localization(132,133,134,135). SRC kinase phosphorylates AR on residue Y534, 
which is critical for AR stability and transcription(96, 128). To assess the role of 
SRC kinase inhibition on AR phosphorylation and how that may contribute to drug 
synergy in CRPC, we seeded the CRPC cell lines 22Rv1 and LNCaP95 overnight 
followed by a media change to charcoal stripped serum media for 3 days. We then 
administered individual and drug combinations for 24 hours at each drug’s IC50 
followed by stimulation with R1881, a synthetic androgen, and epidermal growth 
factor (EGF) for 5 minutes to induce maximal phosphorylation on AR. We found 
that sara ablated the phosphorylation of AR Y534 (both AR-FL and AR-Vs) in both 
22Rv1 and LNCaP-95 cells (Figure 9,10,11,12). This effect was sara dependent 
as enzalutamide and docetaxel were unable to decrease this phosphorylation 
41 
 
 
Figure 9: AR Y534 phosphorylation and AR-V protein expression ablated via SRC 
kinase inhibition in 22Rv1 cells. Cells were treated with Enzalutamide, Saracatinib, 
Docetaxel for 24 hours, then stimulated with R1881 (synthetic androgen) and 
epidermal growth factor (EGF).  
 
 
 
42 
 
   
 
Figure 10: Quantification of AR Y534 phosphorylation and AR-V protein expression 
ablated via SRC kinase inhibition in 22Rv1 cells. Cells were treated with 
Enzalutamide, Saracatinib, Docetaxel for 24 hours, then stimulated with R1881 
(synthetic androgen) and epidermal growth factor (EGF). *, P < 0.05; **, P < 0.01; 
***, P < 0.001; and ****, P < 0.0001.  
 
 
 
V
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+S
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+S
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AR-FL pY534
Drug Group
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Y
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/T
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Drug Group
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/T
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+S
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+S
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AR-V expression
Drug Group
fo
ld
 c
h
a
n
g
e
 t
o
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e
ta
-A
c
ti
n
✱
✱
43 
 
 
Figure 11: AR Y534 phosphorylation and AR-V protein expression ablated via SRC 
kinase inhibition in LNCaP95 cells. Cells were treated with Enzalutamide, 
Saracatinib, Docetaxel for 24 hours, then stimulated with R1881 (synthetic 
androgen) and epidermal growth factor (EGF). 
 
 
 
44 
 
   
Figure 12: Quantification of AR Y534 phosphorylation and AR-V protein expression 
ablated via SRC kinase inhibition in LNCaP95 cells. Cells were treated with 
Enzalutamide, Saracatinib, Docetaxel for 24 hours, then stimulated with R1881 
(synthetic androgen) and epidermal growth factor (EGF). *, P < 0.05; **, P < 0.01; 
***, P < 0.001; and ****, P < 0.0001. 
  
 
 
 
 
 
 
 
 
 
V
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F
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Drug Group
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Drug Group
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45 
 
site, while sara alone and in combination with enza or DTX all produced similar 
reduction of this phosphorylation residue. We also measured AR S81 
phosphorylation and found that its reduction coincided with the reduction of AR 
protein. Interestingly, we also found that total AR-V protein expression was 
decreased by sara, so we measured AR-V7 and found decreased expression in 
sara-treated samples. Overall, these findings indicate that pharmacological 
ablation of SRC kinase can heavily affect AR phosphorylation and AR protein 
expression. 
Saracatinib alters AR gene signature in CRPC 
Based on previous literature that stated phosphorylation on AR Y534 regulated AR 
transcriptional activity, we decided to perform RNA-Seq to evaluate the 
consequence of AR-specific gene signatures after sara-induced reduction of AR 
Y534. 22Rv1 cells were prepared as stated previously and administered drug 
groups (enza, sara, enza plus sara) were added. Cells were harvested after 48 
hours and RNA sequencing was performed. We initially focused on changes in 
steroid receptor mRNA expression as it had been reported that inhibition of AR 
can induce expression of another steroid receptor as a mechanism of resistance 
to AR targeted therapies, such as with the glucocorticoid receptor (NR3C1) and 
mineralocorticoid receptor (NR3C2)(135, 136) We also utilized gene signatures 
from select literature. We found that sara reduced AR mRNA expression (Figure 
13) and enza induced the expression of the glucocorticoid-GR (NR3C1) and 
mineralocorticoid-MR (NR3C2) receptors, similar to what was published 
previously. 
46 
 
 
   
Figure 13: Saracatinib affects steroid receptor gene expression. 22Rv1 cells were 
treated with drug plus stimulated with R1881+EGF for 48hrs then collected for RNA-seq. 
(Left) Heatmap describing nuclear steroid receptor mRNA expression (AR, ESR2-ER, 
NR3C1-GR, NR3C2-MR) (Right) Quantification of normalized counts of AR in each drug 
treatment. *, P < 0.05; **, P < 0.01; ***, P < 0.001; and ****, P < 0.0001. 
 
 
 
 
 
 
 
 
 
D
M
SO
E
nz
a
S
ar
a
E
+S
0
1000
2000
3000
4000
Total AR mRNA expression
Drug Group
N
o
rm
a
li
z
e
d
 C
o
u
n
ts
DMSO
Enza
Sara
E+S
✱✱
✱✱✱✱
✱✱✱✱
47 
 
We also found that the enza plus sara combination further reduced AR mRNA 
expression with little induction of NR3C1 and NR3C2 expression, hinting towards 
sara preventing this mechanism of resistance. To investigate this further, we used 
the Sawyers GR signature (135) and observed that enza and sara individually as 
well as in combination reduced the signature score (Figure 14). This suggests that 
enza and sara work together to prevent the transcription of genes involved in GR 
dependent mechanisms of resistance (e.g  BCL6, ZMIZ1, SGK1, MEAF6). We also 
observed that sara altered AR gene signature activity in both the Dehm(137) and 
Nelson(138) AR-regulated gene sets. In the Dehm gene set, which contains 19 
AR-regulated genes, we found that sara treatment alone reduced certain AR-
regulated genes (e.g. ABCC4, KLK3, ACSL3, and ELL2) and the combination of 
sara and enza dramatically reduced the expression of several AR-regulated genes 
that were less perturbed by either treatment alone, including ZBTB10, PMEPA1, 
CENPN, NKX3-1, and FKBP5 (Figure 15). Similar effects were also observed in 
the Nelson gene set with sara-dependent reduction identified unique AR-regulated 
genes when compared to the sara plus enza combination (Figure 16). We then 
evaluated the protein expression of AR targets FKBP5 and NKX 3.1 and found 
enza and sara individually and in combination reduces their protein expression 
(Figure 17). We also found that sara can reduce the AR-regulated gene signature 
scores in both the Dehm and Nelson gene sets similar to enza and that the 
combination of enza plus sara even further reduced the AR activity signatures 
scores in both datasets (Figure 15, 16). We also assessed AR-V7-specific, cell 
proliferation, and cell cycle gene signatures. 
48 
 
  
 
Figure 14: Saracatinib affects GR gene signature. Heatmap showing Sawyers 
glucocorticoid receptor gene signature (66 genes) with signature score 
0.00
0.25
0.50
0.75
1.00
GR Sawyers Signature Score
Drug Group
S
ig
n
a
tu
re
 S
c
o
re
DMSO
Enza
Sara
Enza+Sara
49 
 
  
Figure 15: Saracatinib affects AR gene signature. Using Dehm Gene signature, which 
is a 19 gene set corresponding to AR activity (Left) Heatmap describing AR target and 
AR dependent genes (Right) Quantification of signature score for Dehm gene signature 
in each drug treatment. 
 
 
 
 
0.00
0.25
0.50
0.75
1.00
AR Dehm Signature Score
Drug Group
S
ig
n
a
tu
re
 S
c
o
re
DMSO
Enza
Sara
Enza+Sara
50 
 
  
Figure 16: Saracatinib affects AR gene signature. Using Nelson Gene signature, which 
is 83 gene set corresponding to AR activity (Left) Heatmap describing AR target and 
AR dependent genes (Right) Quantification of signature score for Nelson gene signature 
in each drug treatment. 
 
 
 
 
 
0.00
0.25
0.50
0.75
1.00
AR Nelson Signature Score
Drug Group
S
ig
n
a
tu
re
 S
c
o
re
DMSO
Enza
Sara
Enza+Sara
51 
 
 
Figure 17: Saracatinib affects AR gene signatures. Western blot of FKBP5 and NKX 3.1 
under treatment 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
52 
 
We found that sara drastically altered the Sharp AR-V7 gene signature(139) more 
than enza, affecting pivotal regulatory genes of AR-V7, HOXB13 and FASN, with 
a reduction in the AR-V7 signature score (Figure 18). For the MYC signature, we 
observed a sara-specific changes in MYC-related genes opposite from DMSO 
control (Figure 19). Interestingly, this did not dramatically affect the MYC signature 
score but when added in combination with enza, we observed a significant drop in 
the MYC signature score suggesting the potency of this combination. Lastly, we 
observed sara and enza dramatically alter the G2M signature leading to a 
significant drop in its signature score (Figure 20). Overall, these findings indicate 
that SRC kinase ablation can heavily affect AR dependent gene expression and 
may work with enzalutamide to further inhibit AR-specific activity.  
Saracatinib induces DNA damage and apoptosis via DNA replication stress 
Since sara alone and in combination with enza significantly lowered AR activity 
signature scores, and that blocking AR function can induce cell death via apoptosis 
and suppression of cell growth(140,141,142), we sought to investigate if sara plus 
enza synergized in exerting their cytotoxic effects during the cell cycle and 
activating apoptotic pathways. First, to follow the cell cycle status of individual cells 
in asynchronous growing cell populations, we stained the chromatin-bound PCNA, 
a component of the DNA replication fork, and DNA in the 22Rv1 cell line using 
antibody and DAPI, respectively (Figure 21). We also pulse-labeled newly 
synthesized DNA with EdU, a modified thymidine nucleoside incorporated into the 
DNA of actively proliferating cells. Cells undergoing DNA replication displayed high 
levels of chromatin-bound PCNA and became EdU-positive after pulse-labeling. 
53 
 
  
Figure 18: Saracatinib affects AR-V7 gene signature. Using Sharp Gene signature, 
which is a 59 gene set corresponding to AR-V7 activity (Left) Heatmap describing AR 
target and AR dependent genes (Right) Quantification of signature score for Sharp gene 
signature in each drug treatment. 
0.00
0.25
0.50
0.75
1.00
ARv7 Sharp Signature Score
Drug Group
S
ig
n
a
tu
re
 S
c
o
re
DMSO
Enza
Sara
Enza+Sara
54 
 
  
Figure 19: Saracatinib affects MYC gene signature. Using MSigdb MYC Gene 
signature, which is a 200 gene set corresponding to MYC activity (Left) Heatmap 
describing AR target and AR dependent genes (Right) Quantification of signature score 
for MYC gene signature in each drug treatment. 
0.00
0.25
0.50
0.75
1.00
MSigdb MYC Signature Score
Drug Group
S
ig
n
a
tu
re
 S
c
o
re
DMSO
Enza
Sara
Enza+Sara
55 
 
  
Figure 20:Saracatinib affects cell cycle gene signature. Heatmap of MSigdb G2M gene 
signature (200 genes) corresponding to cell cycle with signature score 
0.00
0.25
0.50
0.75
1.00
G2M Signature Score
Drug Group
S
ig
n
a
tu
re
 S
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Enza
Sara
Enza+Sara
56 
 
We then established a cell cycle profile using quantitative image-based cytometry, 
comparing PCNA and DAPI in each drug group to identify G1, S, and G2 cell 
populations (Figure 22). Sara treatment alone or in combination with enza or DTX, 
caused a modest, but statistically significant, decrease in S phase cells (Figure 21, 
right). We then evaluated our drug combinations’ impact on DNA synthesis by 
measuring pulse-labeled EdU in PCNA-positive cells. In S phase cells (PCNA-
positive), enza and sara individually decreased EdU incorporation in comparison 
to DTX (Figure 23,24). We also saw enza plus sara decreases EdU incorporation 
to baseline in comparison to DTX plus sara, showing enza plus sara can greatly 
halt DNA synthesis. With DNA synthesis impacted, this may lead to DNA damage 
in S phase. We measured H2AX phosphorylation on residue S139, also known as 
γH2AX, a known marker for DNA damage. We found that the sara alone and in 
combination with enza or DTX significantly induced higher levels of γH2AX in S 
phase cells (Figure 23,24). Also, γH2AX expression was not specific to any one 
cell cycle population, as sara alone and in combination with enza or DTX caused 
greater amounts of γH2AX in G1 cells (Figure 25), while enza plus sara induced 
the highest amounts of γH2AX in G2 cells (Figure 25). Lastly, to understand 
activation of apoptotic pathways, we measured activated caspase 3/7 and cleaved 
PARP, early markers for apoptosis required for late stages in apoptosis. We 
detected higher levels of activated caspase 3/7 in the enza plus sara combination 
over each drug alone (Figure 26) as well as higher cleaved PARP expression 
(Figure 27). 
 
57 
 
 
Figure 21: Saracatinib halts DNA synthesis and induces DNA Damage.  (Above) 
Quantitative Image-based cytometry (QIBC) results comparing PCNA to DAPI to identify 
G1, S-phase, and G2 cells. (Below) Representative images of PCNA, EdU, DAPI, and 
merged  
 
 
 
 
 
58 
 
Figure 22: Saracatinib halts DNA synthesis and induces DNA Damage.  
Quantification of the distribution of G1, S-phase, and G2 cells from QIBC results.  
 
 
 
 
Figure 23: Saracatinib halts DNA synthesis and induces DNA Damage.  
Representative immunofluorescence images of γH2AX (DNA Damage marker, 
PCNA (DNA Synthesis marker), EdU(marker of incorporation into DNA) , and DAPI 
for each drug group.  
 
59 
 
  
 
Figure 24: Quantification of immunofluorescence in S-phase cells for EdU (marker of 
incorporation into DNA) and γH2AX (DNA Damage marker), for each drug group. S-
phase cells were determined by PCNA positivity. *, P < 0.05; **, P < 0.01; ***, P < 
0.001; and ****, P < 0.0001. 
 
 
 
 
 
 
 
60 
 
 
Figure 25: Quantification of immunofluorescence in G1 and G2 cells for EdU (marker 
of incorporation into DNA) and γH2AX (DNA Damage marker), for each drug group. 
S-phase cells were determined by PCNA positivity. *, P < 0.05; **, P < 0.01; ***, P < 
0.001; and ****, P < 0.0001 
 
 
 
 
 
 
61 
 
 
Figure 26: Saracatinib activates markers of apoptosis. (Left) Representative images 
of caspase 3/7 activation (via Cell Event) detected via immunofluorescence for each 
drug group. (Right) Quantification of immunofluorescence (RFU). *, P < 0.05; **, P < 
0.01; ***, P < 0.001; and ****, P < 0.0001. 
 
 
 
 
 
 
 
 
62 
 
 
Figure 27: Saracatinib activates markers of apoptosis. (Left) Western blot of cleaved 
PARP, Total PARP, with β actin as loading control for each drug group (Right) 
Quantification of immunofluorescence (RFU). *, P < 0.05; **, P < 0.01; ***, P < 0.001; 
and ****, P < 0.0001.  
 
 
 
 
 
 
 
 
 
 
 
63 
 
Overall, these findings indicate SRC kinase inhibition via sara causes DNA 
replication stress that is supplemented by enzalutamide vs. docetaxel, resulting 
in greater activation of apoptotic pathways. 
Discussion 
In this study, we found that enzalutamide plus saracatinib is synergistic in prostate 
cancer cell lines that express AR-FL, regardless of AR-V status. We also found 
that docetaxel plus saracatinib is synergistic to additive in cell lines that express 
AR-FL only. However, synergy is reduced between docetaxel and saracatinib in 
cell lines that express AR-Vs, highlighting its treatment potential in the correct 
context. Clinically, this is important for the patient as we can identify the 
appropriate combination strategy to have a greater impact on halting their disease 
progression and circumvent any unnecessary side effects. However, this study 
remains correlative and lacks genetic validity, requiring further study to understand 
how AR status can affect therapeutic efficacy in PCa cells. Under castrate 
conditions, AR can shift from its canonical ligand dependent signaling to non-
canonical ligand independent signaling(96, 143, 144). This adaptive signaling can 
lead to the expression of constitutively active AR-Vs and increased tyrosine kinase 
activity. SRC kinase phosphorylates AR and has been shown to bind to the N-
Terminal domain of AR, leading to a gain in cell proliferation and signaling(96). We 
found that saracatinib decreased AR Y534 on both AR-FL and AR-Vs and, 
interestingly, saracatinib also decreased AR-V protein expression, including AR-
V7. This points out that changes in phosphorylation on AR Y534 may affect AR-V 
64 
 
protein stability highlighting a possible route towards its ligand-independent 
function.  
Previous literature has shown that the phosphorylation of AR can activate and 
contribute to AR-dependent gene networks(143,133,134,135). In particular, Y534 
phosphorylation by SRC kinase contributes to AR transcriptional activity and 
nuclear localization(128). Therefore, we evaluated saracatinib’s effects on AR 
mRNA expression alongside other steroid receptors’ mRNA expression. We found 
that AR mRNA expression decreased in the presence of saracatinib and an 
increase in GR and MR mRNA expression when enzalutamide was given. The 
effect of enzalutamide is blunted when combined with saracatinib, suggesting that 
saracatinib affects AR-gene regulated specific mechanisms of resistance tied to 
enzalutamide. We also found that enzalutamide and saracatinib individually and in 
combination, negatively alters an GR gene signature. We then evaluated AR gene 
signatures to observe saracatinib’s effects on AR dependent genes and observed 
that saracatinib altered AR gene signature scores to a similar level as 
enzalutamide, which was quite surprising. We found many of the major AR target 
genes were impacted, such as TMPRSS2, KLK2/3, NKX3.1 and FKBP5. In 
addition, we evaluated AR-V7 specific, MYC, and G2M gene signatures and found 
saracatinib negatively altered AR-V7 and G2M gene signatures, while having an 
opposite effect to DMSO in the MYC signature. While this mechanism requires 
more investigation, we postulate that saracatinib impacts AR-V protein stability, 
resulting in reduced AR-V binding to DNA that in return lessens activation of ligand-
independent AR gene expression. AR inhibition has been shown cause DNA 
65 
 
damage on telomeres to prostate cancer cells in previous literature(140, 141), so 
we evaluated our drug combinations in DNA synthesis, DNA damage, and 
apoptosis. Using quantitative immunofluorescence cytometry, we identified G1, S 
phase, and G2 cell populations in each of our drug groups and found that 
saracatinib decreased the percentage of cells in S-phase. We also observed that 
enzalutamide and saracatinib, individually and together, halted EdU incorporation 
greater than docetaxel alone, indicating that cells undergo DNA replication stress 
when given this drug combination. We also found that saracatinib induced greater 
γH2AX expression vs. enzalutamide or docetaxel. Lastly, we found greater 
caspase 3/7 activity and cleaved PARP expression in cells administered 
enzalutamide and saracatinib.  
While the in vitro mechanisms combining sara plus enza are quite striking and 
point towards SRC kinase as a key therapeutic target in CRPC, clinical trial data 
has been not as positive. In the phase 3 clinical trial, READY, docetaxel plus the 
dual SRC kinase and BCR-ABL inhibitor, dasatinib, were given to metastatic 
CRPC patients who were naïve to chemotherapy(110). While the trial was unable 
to meet the specified primary endpoints and no benefit in OS, it should be noted 
that there was a lack of CRPC patient stratification by AR or SRC kinase status. 
It should also be pointed out that while docetaxel is a standard of care in 
CRPC(118), it does not directly affect AR function or activity. From a clinical 
perspective and our work presented here, the combination of enza plus sara 
would benefit a portion of CRPC patients who still retain AR activity, including 
AR-Vs, over docetaxel plus sara. Our study may also prompt investigators to 
66 
 
 
Figure 28: Saracatinib synergizes with Enzalutamide to cause greater prostate 
cancer cell death  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
67 
 
look deeper into select kinases that phosphorylate AR, such as CDK1/5/9, ACK1, 
SRC, MAPK(128), as inhibition of these kinases in AR+ prostate cancers may 
provide patient benefit in combination with AR-targeted agents. 
Evaluating combination therapy, in comparison to monotherapy, by using 
mathematical equations, such as Bliss Independence and Combination Index, can 
possibly bridge the clinical gap for testing(145). Both equations note trends of 
synergy and the interplay of the drugs’ mechanisms of actions based on the cell 
model(130, 131). Specifically, for our purposes, we focused on AR species as the 
variable of our models and saw different responses with enzalutamide and 
docetaxel when paired with saracatinib. While enzalutamide combinations were 
synergistic and resulted in greater prostate cancer cell death, it is still important to 
note that docetaxel combinations were synergistic to additive in some of our 
models, citing the importance of using docetaxel in the clinic in some cases, 
especially when AR-Vs are not expressed. 
Major topics of interest to build upon these findings involve the accessibility of AR 
and deciphering the mechanism of DNA damage caused by saracatinib. Since 
saracatinib alters AR transcriptional activity, SRC kinase inhibition could cause 
chromatin remodeling of AR as well as affect co-activator recruitment, as shown in 
previous literature with CDKs(133). Saracatinib’s induction of γH2AX is of key 
importance to determine if saracatinib causes DNA replication forks and how that 
impacts DNA repair pathways. Overall, we present SRC kinase inhibition as a 
therapeutic strategy to be combined with current AR therapies available for use to 
treat AR driven CRPC (Figure 28). Though we show this promising 
68 
 
pharmacological intervention, there are limitations. With SRC kinase inhibitors, like 
many kinase inhibitors, they are promiscuous which lead to off target effects. This 
prompts a need to develop better kinase inhibitors with specificity to the chosen 
kinase target. Also, while saracatinib is a potent SRC kinase inhibitor, it also 
inhibits other members of the SRC family kinases, including Lyn and Fgr, which 
are also expressed in prostatic tissue. This requires further investigation into each 
kinases’ activity and how their inhibition could impact prostate cancer cell death. 
Methods 
4.1 Cell Culture 
Human prostate cancer cell lines DU-145, 22Rv1, LNCaP95 were obtained from 
ATCC and cultured according to ATCC protocol in RPMI1640, supplemented with 
10% FBS and 1% penicillin-streptomycin and 1% Glutamax, a substitute for L-
glutamine (Corning). AD1 and R1D567 cells were obtained from Dr. Scott Dehm 
at the University of Minnesota Medical School and cultured as described 
previously(146). Cells were not used beyond 25 passages. All cells were grown 
and maintained in a humidified incubator at 37°C and 5% CO2 
4.2 Drug Dose Response (Cell Viability) 
Cells were seeded at the following densities: DU-145 (500 cells/0.1 mL), AD1 
(2,000 cells/0.1 mL), R1D567 (1,000 cells/0.1 mL), LNCaP95 (4,000 cells/0.1 mL), 
22Rv1 (2,000 cells/0.1 mL) in 96 well plates in RPMI media (Sigma-Aldrich) with 
10% FBS, 1% penicillin-streptomycin, and 1% Glutamax (Corning). After an 
overnight incubation at 37°C and 5% CO2, media in the wells was replaced with 
fresh RPMI media with 5% charcoal-stripped (CSS)-FBS, 1% penicillin-
69 
 
streptomycin, and 1% Glutamax (Corning). Cells were then grown in the media for 
3 days. One of the following three drug groups is then administered: enzalutamide, 
saracatinib, ranging from 0.39-100μM, and docetaxel 0.04-10nM. All drugs were 
obtained from Selleckchem. Treatment lasted for 6 days with replenishment of the 
media and drug after 3 days. Cell viability was measured using WST-1 at 1:10 
dilution with CSS-FBS media at absorbance of 450 nm (Tecan 1100 Plate Reader). 
IC50 dosage was calculated using GraphPad Prism. Each data point was 
conducted in technical and biological triplicate.  
4.3 Synergy Studies 
Cells were seeded at the densities grown as stated above. Drug combinations 
used included enzalutamide plus saracatinib and docetaxel plus Saracatinib at 
their respective IC50 dosages for each cell line. Therapy was given, beginning at 
2x the IC50 dose, then serial diluted by 2 till 9 dilution groups were established 
(Figure 29). Cell viability was measured using WST-1 at 1:10 dilution with CSS-
FBS media at absorbance of 450 nm (Tecan 1100 Plate Reader). Measured 
absorbance was converted in percentile and inputted in the Bliss Independence 
equation(130) as well as CompuSyn 1.1, a computer software that determines 
synergy via Combination Index(131) between drugs based on individual dose 
response. Bliss independence is calculated as Fab=Fa x Fb, where Fa/b is the 
fraction of cells affected by drug A/B and Fab is the product of the two fractions, 
representing the predicted additivity of the two drugs. Bliss independence value 
(represented in Figure 1C) is portrayed with Fab and the experimental values of 
each combination. Combinations with values greater than Fab are considered 
70 
 
synergistic, while combination with values less than Fab are considered 
antagonistic. Each data point was conducted in technical triplicate.  
4.4 Immunofluorescence Imaging and Quantitative Image-based Cytometry 
For cell-cycle analysis of 22Rv1 cells, a quantitative image-based cytometry 
method was used as described previously(147). Briefly, cells were labeled with 10 
μM EdU for 30 min and processed with the Click-IT EdU Alexa Fluor 488 Imaging 
Kit (Invitrogen, #C10337) according to the manufacturer’s instructions. Otherwise 
cells were extracted with 1x PBS containing 0.1% Triton-X100 for 10 min on ice 
prior to fixation with 3% paraformaldehyde/2% sucrose for 15 min at ambient 
temperature. Subsequently, cells were permeabilized with 100% methanol at -
20°C for 10 min, blocked in blocking buffer (1x TBS containing 5% BSA, 0.05% 
Tween-20) for 1 hour, and incubated in primary antibodies for PCNA (mouse, 
1:200, Calbiochem #PC10) and γH2AX (rabbit, 1:1000, CST #9718S) in blocking 
buffer overnight at 4°C.Next day, cells were washed 3 times with PBS-T before 
incubation with Cy5 anti-rabbit and Cy3 anti-mouse secondary antibodies for 1 
hour at ambient temperature. Cells were stained with DAPI before mounting 
coverslips on slides. Z-stack images were captured using a Leica DMi8 
microscope (Leica Microsystems). Image segmentation of nuclei and whole cells 
was performed using the cellpose algorithm implemented in Python. The cyto2 and 
nuclei models were further trained on the images in this study to achieve high-
quality segmentation. Nuclear and/or cellular masks were exported to ImageJ to 
measure total intensity, mean intensity, and pixel areas of defined regions, 
 
71 
 
 
Figure 29: Synergy study plate layout (combination index via Chou-Talalay). Based on 
the IC50 dosage of Drug 1 and Drug 2, serial dilutions are at concocted to evaluate cell 
viability, which are then processed through CompuSyn to determine the combination 
index (CI) value. 
 
 
 
 
 
 
 
 
 
 
within max-projected images.  
72 
 
4.5 Caspase 3/7 Activation 
To measure caspase 3/7 activation, Invitrogen CellEvent Caspase-3/7 green 
detection reagent (C10423, ThermoFisher) was used as stated in manufacturer’s 
protocol. 22Rv1 cells were seeded in 96 well plates at 4,000 cells/100 μL in FBS 
media overnight. Media in the wells was then replaced with CSS-FBS media and 
grown for 3 days. The following drug groups were then administered for 24 hours 
at IC50 dosage: DMSO Vehicle, enzalutamide, saracatinib, docetaxel, 
enzalutamide plus saracatinib, docetaxel plus saracatinib. After 24 hours, the 
caspase reagent, diluted to 4 μM was added to the cells for 1 hour. Fluorescence 
was observed using Spark Cyto Multimode Plate Reader. Excitation and emission 
settings were 488 and 590/50 nm respectively. The intensity of fluorescence was 
analyzed with Spark Cyto Imaging software. 
4.6 Immunoblot Analysis 
Cells were lysed with RIPA buffer supplemented with protease inhibitor tablets and 
phosphatase inhibitor cocktail. Protein concentration was quantified using Pierce 
BCA protein assay kit following manufacturer’s protocol. 40 micrograms of protein 
were loaded into GenScript SurePage 4%-12% polyacrylamide gel, transferred to 
both nitrocellulose and PVDF membranes, blocked in 5% BSA or 5% milk in 1x 
TBST for one hour, before incubating the membranes with primary antibodies 
overnight at 4°C in 1% BSA solution. Membranes were washed with 1x TBST 3 
three times before incubating the membranes in LI-COR IR-conjugated secondary 
antibodies (1:10,000-20,000) for 2 hours at room temperature. Membranes were 
washed three times with 1x TBST and imaged using the LI-COR Odyssey System. 
Membranes were adjusted and quantified with the LI-COR Image Studio Lite 
73 
 
software (v5.2). The following antibodies were used for Western Blot Analysis: At 
1:1000 Total AR (rabbit CST: #5153), Total SRC (rabbit CST: #2109), Total β-actin 
(mouse Santa Cruz: 4970S), ARpY534 (rabbit Invitrogen: #PA5-64643), SRCpY416 
(rabbit CST: #2101), FKBP5 (rabbit CST: #8245), NKX3.1 (rabbit CST: #83700) 
cleaved PARP (mouse CST: #32563), total PARP (rabbit CST: #9532). At 1:500, 
ARpS81 (rabbit Sigma-Aldrich: #07-1375), AR-V7 (rabbit CST: #19672). Blots are 
results in triplicate. 
4.7 RNA sequencing and Analysis 
Total RNA was isolated from 22Rv1 cells via RNeasy Mini Kit (QIAGEN, no. 
74106). Messenger RNA was purified from total RNA using poly-T oligo-attached 
magnetic beads. After fragmentation, the first strand cDNA was synthesized using 
hexamer primers followed by second strand cDNA synthesis. Library sequencing 
was conducted on Novaseq6000 S4 flowcell for PE150 sequencing (Novogene 
Corporation Inc., Sacramento, CA 95817). Transcriptome sequence data 
processing and analysis were performed using pipelines at the Minnesota 
Supercomputing Institute (MSI) and University of Minnesota Informatics Institute 
(UMII) at the University of Minnesota. Raw reads were trimmed, aligned to the 
GRCh38 human genome, and gene-level read counts were generated using the 
CHURP pipeline(148). All downstream gene expression analyses and 
visualizations were conducted using R (4.2.1), RStudio (2022.07.2+576)(149) and 
GraphPad Prism 9. Genes with less than ten total counts across all samples were 
filtered out. Count normalization was conducted using DESeq2’s median of ratios 
74 
 
method(150). Visualizations were generated using the R packages ggplot2(151) 
and ClassDiscovery(152), and Graphpad Prism 9. 
4.8 Gene Activity Scoring 
Relative AR activity scores were computed by summing the normalized counts of 
the set of genes defining each signature. Peter Nelson’s AR signature includes 83 
genes, all of which were present in the dataset(138). Scott Dehm’s signature 
includes 19 genes, 18 of which were present in the dataset(137). 
4.9 Statistics and Analysis 
The data were presented as the mean ± SD for the indicated number of 
independently performed experiments, except the immunofluorescence data, 
which was presented as the median. The statistical significance (p<0.05) was 
determined using GraphPad Prism 9 with the tests indicated in the figure legends. 
P < 0.05 was considered to indicate a statistically significant difference. P values 
were determined with significance indicated as follows: *, P < 0.05; **, P < 0.01; 
***, P < 0.001; and ****, P < 0.0001. Tukey's multiple comparisons test and Kruskal-
Wallis test were performed after one-way ANOVA. 
 
 
   
 
 
 
 
Closing Remarks 
75 
 
The overall aim of this dissertation was to highlight the importance of the biological 
and pharmacological contexts for the use of kinase inhibitors as treatment for 
prostate cancer. Non-genomic signaling of AR via kinase crosstalk shows promise 
as a therapeutic avenue based on these in vitro studies. Saracatinib inhibiting AR 
phosphorylation on residue Y534 and altering AR transcriptional activity gives 
reason to investigate the access to chromatin AR when cells are treated with 
saracatinib through chromatin immunoprecipitation sequencing (CHIP-seq). Using 
CHIP-seq, we would identify AR specific binding sites across the genome that are 
heavily impacted under drug treatment that could contribute to drug synergy. In 
addition, other experiments we could perform are genetic studies via 
siRNA/shRNA targeting SRC, along with SRC family kinase members FGR and 
LYN, to confirm that the molecular changes resulting from saracatinib are SRC 
dependent. Non-genomic signaling of AR-Vs also requires further study, as 
saracatinib reduced AR-V phosphorylation of Y534 and expression, a major 
mechanism of resistance in CRPC. It is unknown whether this reduction in AR-V 
expression is due to the decreased phosphorylation of Y534 or changes in signaling 
outside of AR. To rectify this, we could take a phosphoproteomic enrichment 
coupled to quantitative mass spectrometry approach to assess the changes in the 
kinome after SRC depletion.  
Currently, there are 20 active phase 2 clinical trials for kinase inhibitors that target 
tyrosine kinase receptors VEGFR (sunitinib, tivozanib), CDKs (palbociclib), MEK 
(trametinib), and even SRC (dasatinib). Interestingly, many of these clinical trials 
are in combination with androgen ablation and hormonal therapy, which shows a 
76 
 
shift from monotherapy studies on kinase inhibitors to combination therapy. The 
major premise for these studies is to circumvent drug-induced resistance 
mechanisms found in CRPC, such as changes in EMT and lineage plasticity. 
VEGFR in PCa upregulates angiogenesis pathways and induce metastasis. MEK 
and SRC hyperactivity in PCa cause cell proliferation and growth. CDKs 
(specifically CDK 4/6) in PCa dysregulate transitions in the cell cycle. By 
circumventing these signaling cascades with kinase inhibitors alongside AR 
hormonal therapy, we may possibly increase the efficacy of treatments currently 
available for PCa. 
In addition, BRCA and ATM status of PCa patients has been a focus in terms of 
therapeutic intervention due to the development of PARP inhibitors, olaparib and 
rucaparib. BRCA1/2 is typically mutated to deleted alongside RB1, contributing to 
the aggressiveness of CRPC. Clinical trials TRITON2, TOPARP-B and PROfound 
3 show that the use of olaparib and rucaparib is promising, as these PARP 
inhibitors cause a PSA response and better response overall for treating PCa 
tumors. Broadening outside of PCa, computational studies on synergy, additivity, 
and independent drug action are also being done to determine clinically beneficial 
combination therapies for individual patients with cancer, through using gene 
expression data and individual drug dose response data from cell lines and PDXs. 
Retrospective analysis to model independent drug action of different combination 
therapies in PDX tumors show in many cases, the best combination therapies are 
when the two drugs in question both yield a clinical response in monotherapy in 
the patient’s disease context(153,154). Overall, kinase inhibitors are returning as 
77 
 
viable treatment options for PCa in combination with other therapies to develop 
personalized medicine.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78 
 
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