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Temporal and spatial characterization of cisplatin treatment and emerging acute resistance in bladder cancer cells

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Temporal and spatial characterization of cisplatin treatment and emerging acute resistance in bladder cancer cells

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Temporal and Spatial Characterization of Cisplatin Treatment
and Emerging Acute Resistance in Bladder Cancer Cells

By
Lisa M. Swartz

A Thesis Presented to the
FACULTY OF THE USC KECK SCHOOL OF MEDICINE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOCHEMISTRY AND MOLECULAR MEDICINE)
December 2023
ii
ACKNOWLEDGEMENTS
First and foremost, I must extend my most sincere gratitude towards Dr. Amir Goldkorn,
my exceptional mentor and committee chair. Throughout the past two years, you have provided
me with constant guidance and encouragement in my development as both a researcher and
individual, and I am very grateful to have the opportunity to continue into my Ph.D. in your lab.
I would also like to express my gratitude to the other esteemed members of my thesis
committee and advisors, namely Professor Scott Fraser, Professor Marc Vermulst, and Professor
Pinchas Cohen for their encouragement, insightful comments, and thought-provoking questions.
I am sincerely appreciative of the time they dedicated from their busy schedules to attend my
committee and dissertation meetings as their presence and contributions greatly enriched my
research and overall learning experience.
Additionally, I would like to thank Dr. Jason Junge, the director of the Translational
Imaging Center at USC, and Dr. Seth Ruffins, the director of the Optical Imaging Facility at
USC, for their invaluable wisdom and expertise in the field of microscopy. I am deeply grateful
for their willingness to share their knowledge and answer my never-ending list of questions. I
would also like to thank Professor Judd Rice, the director of the Biochemistry and Molecular
Medicine master’s program, for helping to provide an excellent academic and work environment.
I must also thank my fellow lab members and friends, Tong Xu, Emmanuelle Hodara,
Benjamin Weekley, Smruthi Maganti, Daniel Bsteh, Maheen Iqbal, Aubree Mades, Betty Yu,
Nimisha Mazumdar, Aakriti Singh, and Valerie Narumi for being the best lab and school mates I
could have asked for, and creating the environment that made this work possible. Thank you all
for being my family away from home.
Finally, I have to acknowledge my parents for always providing me with unwavering
support, words cannot express my gratitude.

iii
TABLE OF CONTENTS
Acknowledgements………………………………………………………………………………..ii
List of Tables....................………………………………………………………………....……..iv
List of Figures...................………………………………………………………………....……...v
Abbreviations……………………………………………………………………...…………..….vi
Abstract……...………………………………………………………………..……….....………vii
Chapter 1: Introduction……………………………………………………..…...…………..…….1
1.1 Chemotherapy Resistance in Bladder Cancer……………………......……………...…..1
1.2 Metabolic Reprogramming…………………......………………...………….....….…...3
1.3 N6-methyladenosine RNA modifications…………………........…………...…..…...…7
Chapter 2: Materials and Methods………………………………………..……………..……….10
Cell culture…………………………………………………………..………...................10
Treatment with Pharmacological Agents……………………………….…....…..…….….10
Immunofluorescence and Fluorescence Microscopy……………………...………….........11
Western Blot………………………………………..……….........………………..…......12
RNA Isolation………………………………………………………..……..……….........14
RT-qPCR…………………………………………………..………...……..……….........14
Statistical Analysis………………………………………..……….………………...........14
Chapter 3: Results……………………………………………………....…………..……………15
TR-Cis observed in BC cells 2 hours after initial cisplatin treatment…………...………….15
Temporal & spatial pattern of TFAM expression after short-term cisplatin treatments.........18
Temporal & spatial pattern of SLC7A11 expression after short-term cisplatin treatments....25
Chapter 4: Discussion……………………………………………..………..…………..………..32
References…………………………………………………………………..…………..………..39
iv
LIST OF TABLES
Table 1. Immunofluorescence Antibodies.………………………………………………...….....12
Table 2. Western Blot Antibodies…………………………………………………......................13
Table 3. Primer information…………………………………………………...............................14

v
LIST OF FIGURES
Figure 1.1 Plasticity of cancer stem-like subpopulations in bladder cancer cell lines…….……...2
Figure 1.2 Gene expression in SP cells is enriched for OxPhos pathway………………….….….4
Figure 1.3 Single-cell analysis of metabolic states………………………………………………..5
Figure 2. TR-Cis observed in BC cells 2 hours after initial cisplatin treatment.................….......16
Figure 3. Short-term effect of cisplatin on TFAM mRNA expression in bladder cancer cells.....18
Figure 4. Short-term effects of cisplatin on TFAM protein levels in bladder cancer cells............19
Figure 5. Characterization of TFAM localization and mitochondrial morphology in response to
short-term cisplatin treatment.............……………………………………........…….......21
Figure 6. Comparing BC cisplatin-resistant vs. cisplatin-sensitive TFAM and mitochondrial
phenotypic differences.............……… …………………………….................................22
Figure 7. Short-term effect of cisplatin on SLC7A11 mRNA expression in bladder cancer
cells............…………………………………………..................………......…...….........25
Figure 8. Short-term effect of cisplatin on SLC7A11 protein levels in bladder cancer cells........26
Figure 9. Characterization of SLC7A11 abundance and localization in response to short-term
cisplatin treatment............…………………....………………………..............................28
Figure 10. Comparing cisplatin-resistant vs. cisplatin-sensitive phenotypic differences in
SLC7A11............……………………………………………………...............................30

vi
LIST OF ABBREVIATIONS
BC Bladder Cancer
FACS Fluorescence activated cell sorting
FLIM Fluorescence lifetime microscopy
GFP Green fluorescent protein
IF Immunofluorescence microscopy
MeRIP-Seq Methylated RNA immunoprecipitation sequencing
mtDNA Mitochondrial DNA
OxPhos Oxidative phosphorylation
PTMs Post-translational modifications
RNA-seq RNA sequencing
RT-qPCR Quantitative reverse transcription polymerase chain reaction
siRNA Small (or short) interfering RNA
SLC7A11, xCT Solute carrier family 7 member 11
TCGA The Cancer Genome Atlas
TFAM Mitochondrial transcription factor A
TOMM20 Translocase of Outer Mitochondrial Membrane 20
TR-Cis Texas Red-Cisplatin
DSB Double-stranded DNA breaks

vii
ABSTRACT
Background: Management of cancer has greatly advanced in recent decades; however, efficacy
of treatment is limited by the emergence of chemo-resistant tumor cell populations.
Chemotherapy resistance is recognized to occur not only through selection of pre-existing
genetically resistant clones, but also through rapid phenotypic plasticity mechanisms. We
previously reported that bladder cancer cells can rapidly transition to and from a chemo-resistant
phenotype through epigenetic and transcriptional reprogramming. Using our previously
published model of bladder cancer (BC) plasticity, we FACS-sorted highly aggressive, cisplatin-
resistant side population (SP) from cisplatin-sensitive non-side pollution (NSP) and found that
the more aggressive cells were associated with a metabolic shift towards mitochondrial oxidative
phosphorylation (OxPhos). Consistent with this, the lab identified Mitochondrial Transcription
Factor A (TFAM) as a key upstream driver of the phenotypic transition between the two cell
states. A second mechanism that contributes to phenotypic plasticity and cisplatin-resistance in
bladder cancer is N6-methyladenosine(m6A), a reversible RNA modification shown to
dynamically regulate mRNA processing, differentiation, and cell fate. Using methyl-RNA-
immunoprecipitation followed by sequencing (MeRIP-seq) and RNA-seq, we found that
methylation controls the levels of SLC7A11, a mediator of cisplatin resistance. In the current
work, we aimed to characterize the timing and cellular distribution of these two newly identified
protein mediators of acute cisplatin resistance.
Methods: T24 and UM-UC-3 BC cell lines were treated with cisplatin for 2, 8, 16, 24, and 48
hours and evaluated for early changes in mRNA levels of TFAM and SLC7A11 using RT-qPCR.
Additionally, western blot and confocal microscopy were used to detect and visualize changes in
viii
protein expression of TFAM and SLC7A11 after 16, 24, 48 and/or 72 hours, as well as the
mitochondrial co-localization of TFAM using TOMM20 stain.
Results: Following cisplatin treatment, TFAM was upregulated at the mRNA (24 hrs) and
protein (16 hrs) level, and IF microscopy showed that cisplatin-treated cells and cisplatin-
resistant cells exhibit expanded mitochondrial networks. Following cisplatin treatment,
SLC7A11 was upregulated at the mRNA level (T24:16hrs, UM-UC-3: 24hrs), with a trend
towards increase at the protein level (48 hrs). IF microscopy showed that SLC7A11 signal
intensity increased after 16 hours of cisplatin treatment, and cisplatin-resistant cells had
increased SLC7A11, especially at the cellular membrane, compared to cisplatin-sensitive cells.
Conclusions: Our findings indicate that there are early, adaptive increases in these proteins,
which can be attributed to a combination of increased expression and altered post-translational
regulation. These results highlight the early significance of non-genetic factors, such as TFAM
and SLC7A11, in driving the development of acute cisplatin resistance in BC, presenting
potential therapeutic targets to avert drug-resistance in BC.

1
Chapter 1
INTRODUCTION
1.1 Chemotherapy Resistance in Bladder Cancer
Bladder cancer (BC) is one of the top ten most prevalent cancers worldwide, with an
estimated 600,000 new diagnoses each year. While the management of BC has greatly advanced
in recent decades, the emergence of drug-resistant cells poses a major obstacle to achieving
lasting cures in patients. Thus, a better understanding of the mechanisms underlying the
development of drug-resistance in patients is necessary to further improving patient care.
Traditionally, resistance to chemotherapy has been thought to occur progressively through the
acquisition of genetic mutations that provide a selective advantage (1). However, recent studies
now suggest that resistance can also arise through rapid, non-genetic mechanisms, and it is now
recognized that many cancers are heterogeneous, consisting of cellular subpopulations that
demonstrate both heritable and non-heritable phenotypic differences. A significant body of work
by our lab and others has established that BC cells can reacquire drug-resistant, stem-like
properties, and that this phenotypic reprogramming does not necessitate the emergence of new
DNA mutations (2-7). Using Hoechst-stained and FACS-fractionated drug-resistant and drug-
sensitive subpopulations of cells, we previously observed phenotypic plasticity in BC, wherein
cancer cells spontaneously and reversibly convert between a drug-resistant and drug-sensitive
state (Figure 1) (2). Xu et al. postulated this phenomenon to be an adaptive response, a “bet-
hedging” of phenotypes to increase the likelihood of some cells surviving chemotherapy.

2

Figure 1.1 Plasticity of cancer stem-like subpopulations in bladder cancer cell lines.
(a) Two cancer cell states coexist: Hoechst staining and flow cytometry differentiates Side
Population (SP: high tumorigenicity, drug resistance, and high pluripotency gene expression)
from nonside population (NSP: low tumorigenicity, no drug resistance, and low pluripotency
gene expression). (b) Dynamic equilibrium: Cancer stem-like side population (SP) fluctuates in
size spontaneously and cyclically over serial passages. (c) Phenotypic plasticity: cancer stem-like
side population cells differentiate into nonside population cells, and nonside population cells
convert back into side population cells. Figure taken from Xu et al. (2020) (2).

3
1.2 Metabolic Reprogramming
Cisplatin, or cis-diamminedichloroplatinum(II), has acted as the primary treatment for
BC since the FDA initially approved it in the treatment of testicular and bladder cancer in 1978
(8). However, despite frequent initial treatment response, resistance to cisplatin is common.
While there has been extensive research into improving the response to treatment, the molecular
mechanisms underlying adaptive cellular stress responses to cisplatin are still poorly understood.
Tumor cell metabolism is recognized as a hallmark of cancer, and metabolic
reprogramming has recently emerged as a potential molecular mechanism of cisplatin resistance
(9). Early studies on the energy metabolism of cancer cells found that they display increased
glucose uptake and fermentation of glucose to lactate, a phenomenon dubbed as the “Warburg
effect” (10,11). However, since then considerable evidence has indicated that the purely
“glycolytic” cancer cell cannot be indiscriminately applied to all tumors and cell types (12).
Studies in some hepatoma, glioma, and breast cancer cell lines have demonstrated that cells not
only retain functional mitochondria, but also predominantly generate ATP through oxidative
metabolism (13-16). Furthermore, others have shown that cancer cells are capable of undergoing
reversible metabolic transitions between fermentation and oxidative phosphorylation, depending
on their environmental conditions (17-19). These and other findings have emphasized the role of
metabolic plasticity in many aspects of tumor behavior, including drug resistance.
Indeed, the Goldkorn lab has previously shown that the spontaneous transition to a drug-
resistant phenotype in BC cells involves an upregulation of mitochondrial gene expression and a
resulting metabolic shift favoring oxidative phosphorylation (OxPhos) (6). Using the BC model
of nongenetic plasticity, Xu et al. conducted integrative analysis of DNA methylation,
nucleosome accessibility, and gene expression which identified both methylation and
4
accessibility differences between the drug-resistant and drug-sensitive cells at thousands of loci
(2-5). Furthermore, differential gene expression and metabolic profiling revealed that cells
shifted to the drug-resistant phenotype had significantly increased mitochondrial OxPhos, and
metabolomic and functional metabolic assays confirmed that the drug-resistant cells had
significantly higher OxPhos relative to the drug-sensitive cells (Fig. 1.2) (6).

Figure 1.2 Gene expression in SP cells is enriched for OxPhos pathway
(a) Oxidative phosphorylation pathway was the most highly enriched in the KEGG metabolic pathways.
(b) GSEA analysis demonstrated that the OxPhos gene set was significantly enriched in SP (normalized
enrichment score (NES) 3.97, nominal p-value < 0.0002, FDR q-value < 0.0002). (c) Volcano plot of
differential gene expression between SP and NSP cells. OxPhos genes (red) were predominantly
overexpressed in SP as compared with the entire transcriptome (black). (d) Heatmap (Transcripts Per
Million, TPM) of all significantly differentially expressed genes demonstrating OxPhos gene
overexpression in SP. Figure taken from Xu et al. (2022) (6).

Using fluorescence lifetime microscopy (FLIM) analysis on the sorted drug-resistant and
drug-sensitive subpopulations, the lab found that drug-resistant cells exhibited a discrete OxPhos
FLIM signature that was readily distinguishable from the more Glycolytic signature of the drug-
5
sensitive cells. When this FLIM profile was applied to unsorted cells growing in culture, OxPhos
and Glycolytic cells were identified and then observed converting from one metabolic state to the
over the course of hours. Furthermore, after cisplatin administration, these drug-resistant OxPhos
cells were found to maintain their OxPhos metabolic FLIM signature, whereas more drug-
sensitive Glycolytic cells transitioned in greater numbers towards a more OxPhos state or died
from the treatment (Fig. 1.3) (6). Additionally, the lab found that treatment with cisplatin
increased mitochondrial DNA (mtDNA) expression and levels in BC cells, whereas
pharmacological inhibition of OxPhos increased the cisplatin-sensitivity of cells.

Figure 1.3 Single-cell analysis of metabolic states.
(a-b) J82 cells were sorted into SP and NSP cultures by FACS and analyzed in FLIM phasors. SP cells (a)
have a phasor distribution that describes more OxPhos metabolic states whereas NSP cells (b) have a
phasor distribution that describes more Glycolytic metabolism. The dashed line in the phasor panels of a
and b represents an identifiable boundary between NSP and SP FLIM signals, and the color scale bar
applies to the cell images of a and b. (c) In unsorted J82 cell culture, we tracked the metabolism of 35
cells for 48 hours after seeding and plotted the real component for centers of mass for 9 cells
demonstrating shifts in metabolic states from OxPhos to Glycolytic states (3 cells), from Glycolytic to
6
OxPhos (4 cells) and no change (2 cells). (d) In J82 cells treated with cisplatin at IC50, we tracked a cell
that shifted quickly from Glycolytic (top cyan cell) to an OxPhos state (same cell, yellow and orange)
whereas a neighboring cell remained Glycolytic (lower cyan cell). Cell colors reflect real metabolic states
determined by phasor position relative to the color scale bar in a and b. (e) When analyzed in total from
initial treatment to 22.5 hours post treatment, the percentage of cells that are OxPhos rises to 42% (red
data points) compared with 5% for untreated cells (black data points). (f-g) J82 cells were cultured in the
absence (f) or presence of phenformin (g) and analyzed in FLIM phasors, demonstrating a clear shift
away from OxPhos (f) and toward glycolytic (g) metabolism. (h) Co-treatment with cisplatin and
phenformin produced synergistic reduction in cell count (CDI 0.69, p=0.048). *p <0.01, calculated using
t-test. Figure taken from Xu et al. (2022) (6).

In recent years, there has been increasing interest in the role of the mitochondria as a
potential target of cisplatin that may play a role in phenotypic plasticity and adaptive drug
resistance. It is well-known that mitochondrial fidelity is essential for overall cellular
homeostasis as they perform crucial functions in the cell which must be tightly regulated and
maintained (20). Moreover, mitochondrial dysfunction alters cellular metabolism which can
provide tumors with a survival advantage, and thus has been found in many cancers (21). So, in
order to identify possible signaling candidates driving the observed OxPhos upregulation in
drug-resistant BC cells, the Goldkorn lab analyzed RNA-seq data from the drug-resistant and
drug-sensitive BC cells, which revealed a potential role for Mitochondrial Transcription Factor A
(TFAM). TFAM is recognized as a key nuclear regulator of mtDNA replication that plays an
essential role in regulating mtDNA metabolism (22). TFAM has been reported to bind mtDNA
in both a sequence-specific and nonspecific manner, through which it influences both mtDNA
transcription and copy number (23-25). Sequence-specific binding of TFAM is required for
initiating mitochondrial gene transcription, whereas sequence-independent binding of TFAM to
mtDNA is necessary for compacting the genome. Furthermore, TFAM has a direct connection
with mtDNA copy number, as genetic overexpression of TFAM has been reported to
7
proportionally increases mtDNA abundance, further implicating TFAM as a major nuclear
coordinator of mitochondrial biogenesis (26,27).
Given its role in mtDNA replication and transcription, along with the RNAseq analysis, our
group tested whether the rapid mitochondrial metabolic response to cisplatin involved TFAM,
and found TFAM depletion decreased mtDNA expression, oxygen consumption rates, and
reduced survival of cisplatin-treated cells (Ongoing work). Interestingly, mtDNA damage –
induced by low-dose ethidium bromide– also resulted in TFAM upregulation, suggesting the
presence of an adaptive stress signal involving TFAM overexpression that promotes drug
resistance and cell survival. These findings not only implicate the mitochondria as an important
target for cisplatin, but also TFAM upregulation as a potential contributor in regulating
mechanisms that lead to resistance. Thus, understanding the effects of cisplatin on TFAM
expression and spatial localization is critical to better understanding drug-resistance in bladder
cancer.

1.3 N6-methyladenosine RNA modifications

Another mechanism that has been shown to contribute to phenotypic plasticity and cisplatin-
resistance in bladder cancer involves the methylation of adenosine at the N
6
position in RNA
(m
6
A). N
6
-methyladenosine is an abundant modification in messenger RNA (mRNA) and non-
coding RNAs (ncRNAs) and has been identified as the most prevalent mRNA internal
modification in most eukaryotic species (28). Importantly, m
6
A has been shown to dynamically
and reversibly regulate mRNA processing, differentiation, and cell fate (29,30).
The modulation of m
6
A is controlled by three different classes of molecules depicted as
writers, erasers, and readers. m
6
A RNA methylation is executed through the activity of a core
writer complex that consists of the highly conserved METTL3 (methyltransferase-like 3), along
8
with METTL14, and WTAP (Wilms’ Tumor1-Associating Protein) (31-34). Two m
6
A
demethylases, ALKBH5 and FTO, serve as erasers and have been reported to remove m
6
A from
RNA, while the m
6
A readers, YTHDF1-3, are involved in mediating the downstream effects of
m
6
A modifications through recognition and selective binding (35-37). The balance between
deposition and removal of m
6
A is extremely dynamic and is essential for maintaining basic
cellular functions and contributing to tissue-specific gene expression (38). Moreover, m
6
A
modifications are believed to be master regulators of specific signaling pathways that induce
major effects on mRNA stability as well as nuclear processes such as splicing and epigenetic
regulation (39,40).
The broad effects of m
6
A on gene expression emphasize the necessity for its proper
regulation, as global abundance of m
6
A and the expression levels of its regulatory proteins
(writers, erasers, readers) are often found to be deregulated in various cancer types. Notably, an
analysis of The Cancer Genome Atlas (TCGA) database showed that 80% of bladder cancer
samples were altered in one or more m
6
A effectors (41). Given the dynamic nature of m
6
A and
its role in cell fate, the lab had hypothesized that m
6
A modifications regulate the expression of
genes that promote cisplatin-resistance in bladder cancer (BC). To identify those genes, the lab
used methyl-RNA-immunoprecipitation followed by sequencing (MeRIP-seq) and RNA-seq,
finding 130 genes to be both differentially expressed and differentially methylated. Once these
candidates were narrowed down based on Extreme log fold changes, Bladder cancer relevance
(Pubmed), TCGA/ORIEN: Stage, Grade and Survival, CARIS CodeAI: Drug Response and
Survival, and COSMIC mutations corresponding to m
6
A sites, each gene was confirmed with
PCR and finally, functionally validated with siRNA knockdown (42).
9
This analysis led to the identification of the cystine/glutamate antiporter solute carrier
family 7 member 11 (SLC7A11, xCT) as a driver of m
6
A-regulated cisplatin resistance in
bladder cancer. SLC7A11 mediates cystine import for glutathione biosynthesis and plays a vital
role in providing antioxidant defense and preventing ferroptotic cell death (43). Ferroptosis is an
iron-dependent form of regulated cell death induced by the accumulation of lipid peroxides (44).
SLC7A11 works to suppress ferroptosis and maintain redox homeostasis by supplying cysteine
for biosynthesis of glutathione, a key cofactor for the activation of antioxidant enzymes (45,46).
Recent studies have indicated SLC7A11 as an important oncogenic protein involved in several
cancer types through various mechanisms, and SLC7A11 overexpression or upregulation is
frequently found in cancer cells, especially in tumors resistant to therapeutic treatments (47).
Moreover, SLC7A11 has been linked to cisplatin resistance in ovarian cancer where an increase
of cystine transport activity mediated by SLC7A11 was found in cisplatin-resistant cells (48). In
bladder cancer, two recent studies found an association between SLC7A11 overexpression and
poor clinical outcomes (49,50). SLC7A11 overexpression is hypothesized to confer therapeutic
resistance in cancers by alleviating oxidative stress and thereby preventing cell death by
ferroptosis (51).
All together, these findings indicate that overexpression of TFAM and/or SLC7A11
promotes acute cisplatin resistance, however, the dynamics of these increases in resistance
proteins have not yet been defined. Thus, the current study aims to determine the early cisplatin-
induced temporal and spatial shifts of TFAM and SLC7A11 in BC cells.

10
Chapter 2
MATERIALS AND METHODS
Cell culture
Human bladder cancer cell lines, T24 and UM-UC-3, were purchased from ATCC (Manassas,
VA) and maintained in the lab in RPMI 1640 (Corning, Cat#10-040-CV) and DMEM (Corning,
Cat# 10-013-CV), respectively, supplemented with 10% heat-inactivated fetal bovine serum
(Omega) and 1% penicillin/streptomycin (100 units/mL, Invitrogen) at 37°C, 5% CO2. Prior to
conducting experiments, cell lines were authenticated using 9-marker short tandem repeat (STR)
profiling and tested for interspecies and mycoplasma contamination (CellCheck 9 Plus, IDEXX
BioAnalytics, Columbia, MO). The T24R2 cell line was generated through serial desensitization
with cisplatin and were generously gifted by Dr. Seok-Soo Byun from the Byun Lab (Seoul
National University Bundang Hospital, South Korea) and maintained at 37°C, 5% CO2 in RPMI
1640 media with 6.6 µM cisplatin (Catalog # NSC 119872, SelleckChem, Houston, TX).

Treatment with Pharmacological Agents
Cells were seeded 24-48 hours prior to cisplatin treatment. Cell death was induced using 10 µM
cisplatin concentration (IC-50) dissolved in 1X PBS, and cell conditions were maintained at
37°C, 5% CO2 for the duration of treatment. Texas Red-Cisplatin (TR-Cis) was obtained from
Ursa BioScience LLC (Abingdon, MA, USA). In experiments using TR-Cis, serial dilutions with
PBS were performed so while the total cisplatin concentration was 10 µM, the Texas Red-
Cisplatin only comprised a 1 µM concentration (1 µM TR-Cis:10 µM cisplatin). An equivalent
volume of PBS was added to untreated vehicle controls.

11

Immunofluorescence and Fluorescence Microscopy
150K cells were seeded per well in 12-well plates over 18mm #1.5 thick precision coverslips
(Neuvitro, #NCO768385). After treatment, cells were fixed with pre-warmed 10% formalin for
15 min at 37°C, permeabilized in 0.1% Triton X-100 in 1X PBS at room temperature for 15
minutes and blocked in 2% Bovine Serum Albumin for 1 hour at room temperature. Primary
antibody incubations were performed overnight with appropriate antibodies at 4°C. The primary
antibodies used in this study were: mouse anti-TOMM20 (ThermoFisher, 1D6F5, Cat# 66777-1-
IG, 1:1000), rabbit anti-TOMM20 (ThermoFisher, Cat# PA5-78300, 1:400), rabbit anti-TFAM
(Cell Signaling, #7495, 1:500), rabbit anti-SLC7A11 polyclonal antibody (Invitrogen, PA1-
16893, 1:1000), and rabbit anti-Texas Red (ThermoFisher, A-6399, 1:100). Samples were then
washed 3 times with 1X PBS and incubated with secondary antibodies for 45 minutes at room
temperature before being washed 3 more times with 1X PBS. Coverslips were mounted on
microscopy slides (VWR, Catalog #16004-368) using VectaShield Antifade Mounting Medium
containing DAPI (Catalog #H-1200-10 Vector Laboratories, Burlingame, CA, USA) and sealed
with clear nail polish. Antibody-amplified staining for TR-Cis was done with the VectaFluor
Excel Amplified anti-Rabbit IgG, DyLight 594 antibody kit (Vector Laboratories, DK-1594)
according to manufacturer’s instructions. After primary antibody incubation, samples were
washed 3X with PBS followed by a 15 minute incubation with VectaFluor amplifier antibody.
Following washing, samples were incubated for 45 minutes at room temperature with the
DyLight 594 tertiary antibody, then subsequently washed and incubated with the TOMM20
secondary antibody, Horse Anti-Mouse IgG Antibody (H+L), DyLight 488 (Vector Laboratories,
DI-2488-1.5) for 45 minutes at room temperature. Representative cells were selected and imaged
12
on a Zeiss 800 Axio Imager.Z2 upright laser scanning confocal microscope (USC Stem Cell
Optical Imaging Facility), using an EC Plan-Neofluar 40x/1.30 Oil lens. 1024 x 1024 pixel
images were acquired using GaAsP-PMT detectors. For z-stack imaging, slices were acquired
with 1μm intervals. Image analysis was then performed uniformly using ImageJ. Antibodies used
in immunofluorescence experiments are listed in Table 1.
Table 1. Immunofluorescence Antibodies
Protein Target Dilution Company Catalog#
TOMM20 mAb
(Mouse)
1:400 ThermoFisher
Scientific
1D6F5
#66777-1-IG
TFAM pAb
(Rabbit)
1:1000 Cell Signaling
Technologies
#7495
SLC7A11 pAb for IF
(Rabbit)
1:500
1:1000
Invitrogen PA1-16893
Texas Red pAb
(Rabbit)
1:100 ThermoFisher
Scientific
A-6399
Goat anti-Rabbit
Alexa Fluor 488
1:500 ThermoFisher
Scientific
A-11001
Goat anti-Rabbit
Alexa Fluor 568
1:1000 Invitrogen A-11004
Horse anti-Mouse
DyLight 488
1:1000 Vector Laboratories DI-2488-1.5
VectaFluor Excel
Amplified anti-
Rabbit DyLight 594
Antibody Kit
- Vector Laboratories DK-1594

Western Blot
Whole cell lysates were extracted from BC cells using RIPA lysis buffer (Sigma-Aldrich, Cat#
R0278). Total protein concentration was determined by Lowry Assay using the BCA Protein
Assay Kit (Bio-Rad, Hercules, CA, USA). 30 µg protein lysate samples were boiled in loading
buffer for 10 minutes before running on 4-20% Tris-Glycine gradient gels (Invitrogen, Cat#
13
EC6021BOX) with PageRuler Prestained Protein Ladder (10-180 kDa) (ThermoFisher,
Catalog#26616). Western blot transfer was performed using the iBlot Dry Blotting System
(ThermoFisher Scientific) and PVDF iBlot Transfer Stack (Invitrogen, Catalog #IB401031).
Membranes were then blocked in Odyssey blocking buffer (LI-COR, Lincoln, NE, USA) and
incubated with primary antibodies overnight at 4°C. Membranes were then washed 3 times in 1X
TBST + 0.10% Tween20 Buffer, and then incubated in respective secondary anti-mouse (goat
anti-mouse IRDye 680RD, 1:1000, LI-COR, Cat# 926-68070) and secondary anti-rabbit (goat
anti-rabbit IRDye 800CW, 1:10,000, LI-COR, Cat# 926-68070) for 45 minutes at room
temperature. After 3 more washes in 1X TBST + 0.10% Tween20 Buffer, membranes were
visualized using an Odyssey DLx Imaging System (LI-COR). Images were digitally processed
and analyzed using ImageStudio Version 5.0 software (LI-COR) and ImageJ was used to
quantify protein expression. Primary and secondary antibodies used in western blots can be
found in Table 2.
Table 2. Western Blot Antibodies
Protein Target Size (kDa) Dilution Company Catalog#
β-ACTIN
(Mouse)
45 1:5000 Cell Signaling
Technologies
8H10D10
#3700S
α-TUBULIN
(Mouse)
55 1:4000 Invitrogen 62204
TFAM pAb
(Rabbit)
24 1:1000 Cell Signaling
Technologies
#7495
SLC7A11 mAb
for WB (Rabbit)
35 1:1000 Cell Signaling
Technologies
D2M7A #12691
Goat anti-Rabbit
IRDye 800CW
- 1:10,000 LI-COR 926-32211
Goat anti-Mouse
IRDye 680RD
- 1:10,000 LI-COR 926-68070

14
RNA Isolation
Total RNA was extracted from BC cell lines using Trizol reagent and Direct-zol RNA Microprep
extraction kit (Zymo Research, R2060). The concentration of total RNA was measured via
nanodrop.
RT-qPCR
cDNA synthesis was performed using qScript cDNA SuperMix (QuantaBio, Catalog #95408-
100, Beverly, MA). Real Time PCR was performed using PerfeCTa SYBER Green FastMix
(QuantaBio, Catalog #95408-500, Beverly, MA) using a BioRad CFX96 Real Time PCR
Detection System. The relative gene expression of target genes was calculated using GAPDH as
a housekeeping gene: relative expression = 2^(Ct of GAPDH – Ct of target gene). Primer
sequences can be found in Table 3. All experiments were performed in biological triplicates, and
additional technical triplicates were used for all RT-qPCR experiments.
Table 3. Primer information
RT-qPCR Primers FWD REV
GAPDH TCA AGG CTG AGA ACG
GGA AG
GGA CTC CAC GAC GTA
CTC AG
TFAM AGC TCA GAA CCC AGA
TGC AA
TCA GGA AGT TCC CTC
CAA CG
SLC7A11 GCG TGG GCA TGT CTC
TGA C
GCT GGT AAT GGA CCA
AAG ACT TC

Statistical Analysis
P-values were calculated using Student’s t-test between two groups. Data are presented as means
+/- SEMs from at least three independent experiments. Significant codes: ‘***’: p< 0.001, ‘**’:
p<0.01, ‘*’: p <0.05. GraphPad Prism version 9 or Excel version 16.68 were used for statistical
analysis.
15
Chapter 3
RESULTS
TR-Cis observed in BC cells 2 hours after initial cisplatin treatment
Since we were interested in determining the rapid temporal and spatial effects on TFAM
and SLC7A11 expression in BC cells treated with cisplatin, we first aimed to establish the
earliest time at which BC cells begin cisplatin uptake following administration. To visualize
cisplatin uptake in cells, T24 and UM-UC-3 bladder cancer cells were fixed at early timepoints
following treatment with 10 µM cisplatin (IC-50) that consisted of 1 µM Texas Red-Cisplatin
(TR-Cis) (1 µM TR-Cis: 10 µM cisplatin).
Following fixation, cells were antibody-stained for Texas Red to amplify the TR-Cis
signal and Translocase of Outer Mitochondrial Membrane 20 (TOMM20), to simultaneously
visualize the mitochondria, before being imaged. After 2 hours of treatment, most cells were TR-
Cis positive, whereas no TR-Cis signal was observed in the untreated samples (Fig. 2A-B). UM-
UC-3 cells were also treated for 48 hours with TR-Cis as a positive control, and these cells
displayed even more intense TR-Cis signal than in the 2 hour samples (Fig. 2B). In treated cells,
TR-Cis fluorescence appears diffused or in puncta, and is fairly evenly distributed throughout the
cell, with the most signal appearing in the nuclear regions.
16

17
Figure 2. TR-Cis observed in BC cells 2 hours after initial cisplatin treatment.
Representative immunofluorescence images of cisplatin (TR-Cis; red), nuclei (DAPI; blue) and mitochondria
(TOMM20; green) in BC cells treated with 1 µM TR-Cis: 10 µM cisplatin or untreated control. Intracellular
Texas Red-Cisplatin was visualized by performing α-Texas Red staining with DyLight 594 (Red) conjugated
tertiary antibody. (A) T24 cells treated with TR-Cis for 2 hours. (B) UM-UC-3 cells treated with TR-Cis for 2
hours or 48 hours. Red cisplatin molecules can be observed as puncta, or dots, in the 2hr and 48hr treatment
time points. Confocal images were taken at 40x magnification. Scale bar, 50 µm.

18
Temporal & spatial pattern of TFAM expression after short-term cisplatin
treatments
Since cellular uptake of cisplatin was visualized 2 hours following initial exposure, we
performed RT-qPCR for TFAM in T24 and UM-UC-3 BC cells beginning as early as 2 hours
after administration to explore how rapidly cisplatin would affect TFAM expression in BC cells.
mRNA expression of TFAM was also determined after 8, 16, 24, and 48 hours of cisplatin
exposure to characterize the temporal pattern of TFAM expression over the first two days of
cisplatin treatment. We found that cisplatin did not significantly upregulate TFAM expression in
either cell line until 24 hours of cisplatin treatment, and this upregulation was even greater after
48 hours of cisplatin treatment (Fig. 3).

Figure 3. Short-term effect of cisplatin on TFAM mRNA expression in bladder cancer cells.
TFAM expression levels by RT-qPCR in T24 (A) or UM-UC-3 (B) BC cells treated with 10 µM cisplatin
for 2hr, 8hr, 16hr, 24hr, or 48hr. No significant upregulation in TFAM was found until 24 hours after
cisplatin treatment. TFAM copy number was normalized to the housekeeping gene GAPDH. Graph
displays mean ± SEM values in n=6 replicates; p values comparing treated cells to respective untreated
A B
T24
Cisplatin Ctrl
UM-UC-3
16h 24h 48h Ctrl 16h 24h 48h
TFAM
β-actin
25
35
55
40
A
B C
Unt
2hr cis
8hr cis
16hr cis
24hr cis
48hr cis
0
2
4
6
Fold change normalized by GAPDH T24 Expression levels of TFAM
normalized by GAPDH
***
***
Unt
2hr cis
8hr cis
16hr cis
24hr cis
48hr cis
0
1
2
3
Fold change normalized by GAPDH
UMUC3 Expression levels of TFAM
normalized by GAPDH
**
***
19
cells ‘***’: p< 0.001, ‘**’: p<0.01. Statistical differences in TFAM expression were conducted using
student’s t-test.
We then tested whether this trend of TFAM upregulation beginning at 24 hours could be
observed at the protein level through western blots. In both cell lines we found a trend of
increasing TFAM as the exposure time to cisplatin increased (Fig. 4). In the T24 cell line, there
was significant upregulation of TFAM at all treatment timepoints, whereas UM-UC-3 cells
exhibited more subtle increases in TFAM levels along the cisplatin treatment timepoints.
Surprisingly, in both cell lines, TFAM upregulation was observed after only 16 hours of
treatment, suggesting another mechanism besides mRNA upregulation may also be influencing
TFAM protein levels.

20
Figure 4. Short-term effects of cisplatin on TFAM protein levels in bladder cancer cells.
(A) Western blot analysis of TFAM expression in T24 and UM-UC-3 cells treated with 10 µM cisplatin
for 16hr, 24hr, or 48hr. (B,C) Quantified fold change of TFAM in T24 (B) and UM-UC-3 (C) cells based
on densitometry graphs generated using Image J; normalized to ß-Actin loading control. ‘**’: p<0.01
Having established that TFAM mRNA and protein levels were increased as early as 24
hours, and possibly 16 hours, after initial cisplatin treatment we were next interested in
determining the spatial effects of cisplatin on TFAM localization at these early time points. We
also hypothesized that since TFAM is a key regulator of mitochondrial gene expression, any
changes in TFAM expression or localization may also affect mitochondrial morphology. Thus,
we co-stained cells for both TFAM and TOMM20 following 16, 24, or 48 hours of cisplatin
treatment to visualize both TFAM localization and mitochondrial morphology in BC cells. We
found that as the exposure time to cisplatin increased, cells exhibited a more expanded
mitochondrial distribution phenotype that colocalized with the TFAM signal (Fig. 5). Untreated
BC cells appeared to have mitochondrial networks positioned close to the nuclei that did not take
up a relatively large surface area, whereas the mitochondrial network of treated cells expanded
into interconnected structures that were more spread out. Furthermore, both the overall and
nuclear sizes of cells also appeared to increase correspondingly with prolonged cisplatin
exposure.
21

22
Figure 5. Characterization of TFAM localization and mitochondrial morphology in
response to short-term cisplatin treatment.
Representative immunofluorescence images of nuclei (DAPI; blue), TFAM (red) and mitochondria
(TOMM20; green) in T24 (A-B) or UM-UC-3 (C-D) BC cells exposed to 10 µM cisplatin for 16hr, 24hr,
48hr, or untreated control. (B,D) Zoomed-in images of representative T24 or UM-UC-3 cells,
respectively. Confocal images were taken at 40x magnification. Scale bar, 50 µm (A,C) or 15 µm (B,D).
After observing the effects of short-term cisplatin treatment on TFAM and mitochondrial
morphology in BC cell lines, we were interested in determining if an established cisplatin-
resistant cell line exhibited similar morphological characteristics. We used the cisplatin-resistant
cell line, T24R2, to visualize TFAM and TOMM20 by fixing and staining the cells in an
identical manner as previously described. We found that the resistant cell line also exhibited
TFAM and TOMM20 colocalization and an expanded mitochondrial network morphology,
suggesting this phenotype as a characteristic of cisplatin resistance (Fig. 6).

23

24
Figure 6. Comparing BC cisplatin-resistant vs. cisplatin-sensitive TFAM and
mitochondrial phenotypic differences.
(A) Representative immunofluorescence images of nuclei (DAPI; blue), TFAM (red) and mitochondria
(TOMM20; green) in untreated T24 vs. cisplatin-resistant T24R2 cells. (B) Higher magnification images
of representative T24 untreated or T24R2 cells. (C) Higher magnification images of representative T24
24hr cisplatin treated or T24R2 cells. Confocal images were taken at 40x magnification. Scale bar, 50 µm
(A) or 15 µm (B,C).

25
Temporal & spatial pattern of SLC7A11 expression after short-term cisplatin
treatments
As we previously found an association between SLC7A11 overexpression and cisplatin-
resistance in bladder cancer, we were interested in determining the rapid effects of cisplatin
treatment on SLC7A11. Again, since we found that cisplatin uptake in BC cells appears
substantial only after 2 hours of treatment, we first examined SLC7A11 mRNA expression in
T24 and UM-UC-3 BC cells after 2, 8, 16, and 24 hours of cisplatin treatment. We found that
SLC7A11 expression was not significantly upregulated in either T24 or UM-UC-3 cells until
after 24 hours of cisplatin treatment (Fig. 7).

Figure 7. Short-term effect of cisplatin on SLC7A11 mRNA expression in bladder cancer
cells.
SLC7A11 expression levels by RT-qPCR in T24 (A) or UM-UC-3 (B) BC cells treated with 10 µM
cisplatin for 2hr, 8hr, 16hr, or 24hr. (A) T24 cells exhibited SLC7A11 upregulation after 16 and 24hrs of
treatment. (B) UM-UC-3 cells did not exhibit significant SLC7A11 upregulation until 24hr after
treatment. SLC7A11 copy number was normalized to the housekeeping gene GAPDH. Graph displays
26
mean ± SEM values in n=4 replicates; p values comparing treated cells to respective untreated cells ‘**’:
p< 0.01, ‘*’: p<0.05. Statistical differences in SLC7A11 expression were conducted using student’s t-test.
We then evaluated SLC7A11 protein levels after 16, 24, or 48 hours of cisplatin
treatment in both T24 and UM-UC-3 cells using western blots and found that cisplatin treatment
caused a trend towards increased SLC7A11 protein after 48 hours of treatment (Fig. 8). A
significant increase in SLC7A11 was found after 48 hours in T24 cells, however no significant
increase was found in the UM-UC-3 cell line.

Figure 8. Short-term effect of cisplatin on SLC7A11 protein levels in bladder cancer cells.
(A) Western blot analysis of SLC7A11 expression in T24 and UM-UC-3 cells treated with 10 µM
cisplatin for 16hr, 24hr, or 48hr. (B,C) Quantified fold change of SLC7A11 in T24 (B) and UM-UC-3 (C)
27
cells based on densitometry graphs generated using Image J; normalized to α-Tubulin loading control.
‘**’: p<0.01.
As the SLC7A11 antiporter is reported as a membrane protein, we were interested in how
its localization may be affected by cisplatin exposure. Interestingly, in the T24 cell line,
SLC7A11 signal appeared mostly nuclear, however localization expanded into cytoplasmic
regions with prolonged cisplatin exposure (Fig. 9 A-B). After 48 hours of cisplatin treatment,
T24 cells were enlarged and SLC7A11 signal appeared both brighter and more widespread in the
nucleus and cytoplasm of all treated cells. In the UM-UC-3 cell line, the SLC7A11 signal
appeared to be more evenly diffused throughout the nuclear and cytoplasmic regions of untreated
cells, and the signal intensity greatly increased in all cellular regions with increasing temporal
exposure to cisplatin (Fig. 9 C-D). Notably, in both cell lines, we found that the nuclei and
overall cell size also appeared to increase with prolonged exposure to cisplatin.

28

Figure 9. Characterization of SLC7A11 abundance and localization in response to short-
term cisplatin treatment.
Representative immunofluorescence images of SLC7A11 (green) and nuclei (DAPI; blue) in T24 (A-B)
or UM-UC-3 (C-D) BC cells exposed to 10 µM cisplatin for 16hr, 48hr (T24) or 72hr (UM-UC-3), or
untreated control. (B,D) Zoomed-in images of representative T24 or UM-UC-3 cells, respectively.
Confocal images were taken at 40x magnification. Scale bar, 50 µm (A,C) or 15 µm (B,D).

29
Next, we were interested in determining how the levels and localization of SLC7A11
differed between cisplatin-resistant (T24R2) and cisplatin-sensitive (T24) BC cell lines. We
found that the T24R2 cisplatin-resistant cells displayed a dramatic increase in SLC7A11 signal
relative to the T24 cisplatin-sensitive cell line, and the resistant cells also had distinct,
concentrated SLC7A11 signal in the outer cellular membranes (Fig. 10).
30

31
Figure 10. Comparing cisplatin-resistant vs. cisplatin-sensitive phenotypic differences in
SLC7A11.
(A) Representative immunofluorescence images of nuclei (DAPI; blue) and SLC7A11 (green) in
untreated T24 vs. cisplatin-resistant T24R2 cells. (B) Zoomed-in images of representative T24 or T24R2
cells. Confocal images were taken at 40x magnification. Scale bar, 50 µm (A) or 15 µm (B).

32
Chapter 4
DISCUSSION
The emergence of drug-resistant cell populations is a major obstacle in the treatment of
cancer. Therefore, a better understanding of the proteins and mechanisms involved in the early
cellular response to cisplatin is necessary to improving cancer therapies. In this study, we first
characterized the rate of cisplatin uptake in bladder cancer cells to determine the earliest time at
which cisplatin has the ability to affect our proposed factors of acute cisplatin resistance. We
observed cisplatin uptake in BC cells as early as 2 hours following treatment, indicating BC cells
rapidly take in cisplatin molecules within the first few hours following administration (Fig. 2).
We also noted that cisplatin did not appear to have strong colocalization with the mitochondria,
but instead had more intense signal in the nuclear regions of cells.
Despite there often being initial success following cisplatin treatment, a substantial
fraction of tumors eventually develops resistance (52). The Goldkorn lab has reported that a
spontaneous transition to a drug-resistant phenotype in BC cells involves an upregulation of
mitochondrial gene expression and a resulting metabolic shift favoring OxPhos (2-7). Cancer cell
metabolism is considered a possible target for therapy, and thus understanding the mechanisms
governing adaptive metabolic shifts is crucial to properly combating resistance in a clinical
setting. Ongoing work in our lab has demonstrated that several days of cisplatin treatment
induces TFAM expression which drives a rapid shift towards a drug-resistant phenotype, and that
TFAM is overexpressed in drug-resistant BC cells. These findings indicate TFAM may play an
important role in non-mutation-mediated metabolic plasticity, enabling specific subsets of BC
cells to endure the effects of cisplatin exposure, and therefore further analysis of TFAM and its
33
functions may potentially elucidate new therapeutic targets to delay or avert drug resistance in
BC.
So, with our established timeline of cellular cisplatin uptake, I aimed to define the
temporal and spatial aspects of TFAM expression in relationship to short-term cisplatin treatment
in BC cells. We found that TFAM mRNA expression was significantly upregulated in both cell
lines after 24 hours of treatment with 10 µM cisplatin (IC-50) (Fig. 3). By 48 hours, a more
dramatic overexpression of TFAM was observed in the T24 and UM-UC-3 cells. This rapid
increase in TFAM mRNA that was observed after only 24 hours of cisplatin treatment may be
due to cisplatin inducing an upregulation in TFAM expression. However, as the IC-50
concentration of cisplatin was utilized, we expect only about 50% of cells to have survived after
24 hours, and even less cells to remain after 48 hours of treatment. Since RT-qPCR experiments
examine cells at a population level, and TFAM mRNA increase was not significantly observed
until 24 hours, these results may also be due to the cisplatin treatment having selected for cells
that already exhibited higher TFAM levels, rather than inducing TFAM upregulation itself.
Although a significant increase in TFAM mRNA was not observed until 24 hours post-
treatment, we found that TFAM protein levels appeared to increase as early as 16 hours
following cisplatin administration (Fig. 4). The discrepancy in the timeline of TFAM mRNA vs.
protein level increase raises the question of how mechanisms other than mRNA overexpression,
such as TFAM turnover and stability, are affecting intracellular TFAM levels in BC cells treated
with cisplatin. For instance, the mitochondrial matrix protease, Lon, has been reported to
selectively degrade TFAM protein (53). Furthermore, the cAMP-dependent protein kinase A
(PKA) has also been implicated in regulating TFAM turnover by phosphorylating TFAM at
specific sites which in turn impairs ability to bind DNA, inducing TFAM release and promoting
34
increased degradation by Lon. TFAM has also been reported as a direct substrate of extracellular
signal-regulated protein kinases (ERK1/2), where phosphorylation of TFAM by ERK reduces
promoter binding and transcription, and therefore contributes to the suppression of mitochondrial
biogenesis (54). Differential regulation of TFAM through post-translational modifications
(PTMs), such as those mentioned, may be responsible for the apparent increase in TFAM protein
after only 16 hours of cisplatin treatment that was not observed at the mRNA level, and poses an
interesting avenue for future research.
Numerous reports have demonstrated a direct connection between TFAM and mtDNA
levels, as TFAM is required for mitochondrial biogenesis (55). Genetic overexpression of TFAM
in mice has been demonstrated to induce a proportional increase in mtDNA abundance, and it
has been reported that heterozygous mutation of TFAM results in mtDNA depletion and
increased oxidative mtDNA damage in vivo (27, 56-57). Interestingly, our lab found there was a
significant increase in mtDNA levels in BC cells treated with cisplatin for 24 hours, and that
T24R2 cisplatin-resistant cells also had increased mtDNA content relative to cisplatin-sensitive
cells (Ongoing work). Thus, I sought to visually examine the spatial pattern of both TFAM and
mitochondria in BC cells after short-term cisplatin treatments. Immunofluorescent imaging of
TFAM and TOMM20 at early cisplatin treatment times revealed that the mitochondrial networks
of cells sustained rapid morphological changes over cisplatin treatment (Fig. 5). Even at 16 hours
after initial treatment, the mitochondrial distribution appears more spread out relative to
untreated cells, and in both cell lines there is an even more dramatic expansion of the
mitochondria after 24 and 48 hours of cisplatin treatment. It is important to note that the overall
size of cells and their nuclei also increased as the exposure time to cisplatin was extended.
35
Furthermore, specific amplification of the TFAM signal intensity itself was not observed in cells
treated for longer times with cisplatin. Instead, TFAM appeared to spread outward and remain
colocalized with the expanded mitochondrial network of treated cells. Strikingly, this phenotype
of an expanded mitochondrial distribution was also observed in T24R2 cisplatin-resistant cells,
where the mitochondrial network appeared more widespread, but still interconnected, relative to
T24 cisplatin-sensitive cells (Fig. 6A-B). Rather, the distribution of both TFAM and TOMM20
in T24R2 cells was more similar to what was observed in T24 cells that had been treated with
cisplatin for 24 or 48 hours (Fig. 6C). These results suggest that the biochemical mechanisms
responsible for causing this expansion of interconnected mitochondria could potentially play a
role in aiding the development of non-genetic resistance against cisplatin treatment.
Solute carrier family 7 member 11 (SLC7A11, xCT) has also been implicated in playing
an important role in cancer progression and resistance by providing antioxidant defense and
suppressing ferroptosis. In cancer patients, SLC7A11 overexpression is linked to poorer clinical
outcomes, and artificial overexpression of SLC7A11 in ovarian cancer cells was found to
increase resistance to cisplatin treatment (48). In BC, a previous study reported that resistant BC
cell lines were resensitized to cisplatin treatment through SLC7A11 inhibition (49). In addition,
work in our lab found that SLC7A11 siRNA knockdown sensitizes cells to cisplatin treatment in
three BC cell lines (42). Thus, I aimed to characterize the role of SLC7A11 in acute BC cisplatin
resistance by determining early changes in the spatial and temporal patterns of SLC7A11 in BC
cells. SLC7A11 mRNA expression was found to be significantly upregulated in both cell lines
after 24 hours of treatment with 10 µM cisplatin (IC-50), and in T24 cells, a significant increase
in SLC7A11 expression observed as early as 16 hours after treatment (Fig. 7). This early
36
increase in SLC7A11 mRNA could be the result of a cisplatin induction or selection but may
also occur through other mechanisms involving PTMs or cell cycle dependence.
SLC7A11 protein levels detected by western blots found that cisplatin treatment causes a
trend towards increased SLC7A11 protein over the course of the first 48 hours after initial
treatment (Fig. 8). In the western blots, a significant increase in SLC7A11 protein was only
found in T24 cells at the 48-hour cisplatin treatment timepoint. Interestingly, an increase in
SLC7A11 was observable after 16 hours of cisplatin treatment via immunofluorescence, and BC
cells treated for longer timepoints showed even more dramatic increases in SLC7A11 signal in
both nuclear and cytoplasmic regions of cells (Fig. 9). As it has been established that cancer cells
exhibit heterogeneous responses to toxic agents such as cisplatin, the western blot results may
not have shown SLC7A11 protein increases until later timepoints due to its method of analyzing
the cells at a population level, whereas single cells with clear SLC7A11 elevation could be
observed via immunofluorescence. Moreover, T24R2 cisplatin-resistant cells showed
considerably increased SLC7A11 protein levels relative to T24 cisplatin-sensitive cells, with
notable SLC7A11 localization at outer cellular membranes (Fig. 10). These results demonstrate
that SLC7A11 mRNA and protein rapidly increase following cisplatin treatment, suggesting
early changes in SLC7A11 levels and the mechanisms that induce SLC7A11 upregulation may
promote the transition to cisplatin resistance in bladder cancer.
Further investigation into the mechanisms controlling the early cisplatin-driven
expression and spatial changes in TFAM and SLC7A11 is necessary for better understanding the
role of these non-genetic factors in promoting cisplatin resistance in BC cells. For instance, DNA
damage, such as double-stranded DNA breaks (DSBs), has been reported to be sensed by a
signaling cascade involving ATM that may also play a role in regulating TFAM levels and
37
consequently, mitochondrial biogenesis, and future work investigating these early responses to
short-term cisplatin treatments could provide more insight into the development of resistance in
BC cells (58). In addition, the mechanisms responsible for eliciting SLC7A11 upregulation in
response to cisplatin may involve differential expression of m6A writers and/or erasers, as they
are often found dysregulated in cancers, and more research into these factors could provide a
biochemical mechanism behind the observed rapid increases in SLC7A11 levels. Furthermore,
relating the shifts in TFAM or SLC7A11 levels to cisplatin treatment could be better understood
in the context of heterogeneous cellular responses to cisplatin administration. Cancer cells have
the ability to switch phenotypes in response to their environmental conditions, a phenomenon
known as phenotypic plasticity, that can confer a survival advantage to tumors when under stress
from a chemotherapy such as cisplatin (59). Thus, it is important to consider other attributes of
cells when considering how TFAM and/or SLC7A11 dynamics affect cisplatin-resistance. For
example, it could potentially be considered in the context of proliferative rates for specific
cellular phenotypes when under stress from cisplatin, through co-staining cells with the
proliferative marker Ki67 and TFAM or SLC7A11. In addition, my results in this study further
validate TFAM and SLC7A11 overexpression as a characteristic of cisplatin-resistance in BC.
As such, more investigation would be warranted in order to determine if the downstream effects
of TFAM and SLC7A11 upregulation could be abrogated to better combat the development of
drug-resistance. This could be accomplished through siRNA knockdown of TFAM or SLC7A11,
or with the use of specific inhibitors that prevent either the upregulation or downstream actions
of TFAM and SLC7A11 to observe how this impacts cell survival and the development of
resistance. In addition, to better understand whether cisplatin is inducing or selecting for the
upregulation of these factors, next steps could involve sorting for cells with high or low
38
expression and then determining their viability in the face of cisplatin treatment. The single-cell
transcriptional dynamics of sorted BC cells could also be investigated to further specify cellular
phenotypes and define patterns of TFAM or SLC7A11 expression, and other potentially relevant
genes, in cells responding to cisplatin treatment. Live cell imaging could also be utilized in order
to track the fates of individuals cells while visualizing their levels of TFAM or SLC7A11 over
the course of cisplatin treatment. This could be performed in conjunction with Perceval, a fusion
protein that consists of a bacterial regulatory protein and modified green fluorescent protein
(GFP) which has been developed as a sensor of cellular ATP:ADP ratio (60). If live imaging of
TFAM or SLC7A11 was performed and combined with Perceval technology, the metabolic
states of cells could be examined at the same time, providing a more wholistic depiction of the
cellular mechanisms involved in phenotypic plasticity.
Collectively, these results confirm TFAM and SLC7A11 overexpression as a
characteristic of cisplatin-resistant BC cells and indicate that cisplatin treatment rapidly brings
about upregulation of TFAM or SLC7A11. These findings highlight the importance of TFAM
and SLC7A11 in driving acute cisplatin resistance in BC and offer more insight into how cells
can evade death by cisplatin, presenting potential therapeutic targets to avert drug-resistance in
BC.

39
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Abstract (if available)

Abstract Background: Management of cancer has greatly advanced in recent decades; however, efficacy of treatment is limited by the emergence of chemo-resistant tumor cell populations. Chemotherapy resistance is recognized to occur not only through selection of pre-existing genetically resistant clones, but also through rapid phenotypic plasticity mechanisms. We previously reported that bladder cancer cells can rapidly transition to and from a chemo-resistant phenotype through epigenetic and transcriptional reprogramming. Using our previously published model of bladder cancer (BC) plasticity, we FACS-sorted highly aggressive, cisplatin-resistant side population (SP) from cisplatin-sensitive non-side pollution (NSP) and found that the more aggressive cells were associated with a metabolic shift towards mitochondrial oxidative phosphorylation (OxPhos). Consistent with this, the lab identified Mitochondrial Transcription Factor A (TFAM) as a key upstream driver of the phenotypic transition between the two cell states. A second mechanism that contributes to phenotypic plasticity and cisplatin-resistance in bladder cancer is N6-methyladenosine(m6A), a reversible RNA modification shown to dynamically regulate mRNA processing, differentiation, and cell fate. Using methyl-RNA-immunoprecipitation followed by sequencing (MeRIP-seq) and RNA-seq, we found that methylation controls the levels of SLC7A11, a mediator of cisplatin resistance. In the current work, we aimed to characterize the timing and cellular distribution of these two newly identified protein mediators of acute cisplatin resistance.

Methods: T24 and UM-UC-3 BC cell lines were treated with cisplatin for 2, 8, 16, 24, and 48 hours and evaluated for early changes in mRNA levels of TFAM and SLC7A11 using RT-qPCR. Additionally, western blot and confocal microscopy were used to detect and visualize changes in protein expression of TFAM and SLC7A11 after 16, 24, 48 and/or 72 hours, as well as the mitochondrial co-localization of TFAM using TOMM20 stain.

Results: Following cisplatin treatment, TFAM was upregulated at the mRNA (24 hrs) and protein (16 hrs) level, and IF microscopy showed that cisplatin-treated cells and cisplatin-resistant cells exhibit expanded mitochondrial networks. Following cisplatin treatment, SLC7A11 was upregulated at the mRNA level (T24:16hrs, UM-UC-3: 24hrs), with a trend towards increase at the protein level (48 hrs). IF microscopy showed that SLC7A11 signal intensity increased after 16 hours of cisplatin treatment, and cisplatin-resistant cells had increased SLC7A11, especially at the cellular membrane, compared to cisplatin-sensitive cells.

Conclusions: Our findings indicate that there are early, adaptive increases in these proteins, which can be attributed to a combination of increased expression and altered post-translational regulation. These results highlight the early significance of non-genetic factors, such as TFAM and SLC7A11, in driving the development of acute cisplatin resistance in BC, presenting potential therapeutic targets to avert drug-resistance in BC.

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Creator Swartz, Lisa Michelle (author)

Core Title Temporal and spatial characterization of cisplatin treatment and emerging acute resistance in bladder cancer cells

School Keck School of Medicine

Degree Master of Science

Degree Program Biochemistry and Molecular Medicine

Degree Conferral Date 2023-12

Publication Date 09/06/2023

Defense Date 06/27/2023

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag bladder cancer,cisplatin,drug resistance,mitochondria,OAI-PMH Harvest,oxidative phosphorylation,phenotypic plasticity,SLC7A11,TFAM

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Language English

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Advisor Goldkorn, Amir (committee chair), Fraser, Scott (committee member), Vermulst, Marc (committee member)

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