Identification of the MRTFA/SRF pathway as a critical regulator of quiescence and chemotherapy resistance in cancer

Abstract

Chemoresistance is a major cause of cancer deaths. One understudied mechanism of chemoresistance is quiescence. We used single-cell culture to identify and isolate patient-derived proliferating and quiescent ovarian cancer cells (qOvCa). RNA-seq analysis indicated that hundreds of genes that are differentially expressed in qOvCa cells are transcriptional targets of the Myocardin-Related Transcription Factor-A/Serum Response Factor (MRTFA/SRF) pathway, and both genetic disruption and pharmacologic inhibition of MRTFA/SRF interaction (with the inhibitor CCG257081) induced quiescence across multiple cancer types. MRTFA/SRF inhibition-mediated quiescence is p27/Kip1 dependent and associated with a downregulation of cell cycle regulators, NCL, MYH9, and alterations in the proteasome. We show that the MRTFA/SRF axis plays a dual role in chemotherapy resistance, with both pathway inhibition and activation contributing to chemotherapy resistance in vitro and in patient samples. CCG081 treatment results in a proteasome-dependent downregulation of the stem-cell marker CD133. Suggesting a critical role for the proteasome in quiescent cells, CCG081 therapy sensitized OvCa cells to proteasome inhibitors. In vivo, we found that CCG257081 therapy could be used to induce tumor growth-arrest and delay disease growth to improve overall survival. Moreover, we found that dual therapy with CCG081 and proteasome inhibition further improved outcomes, leading to undetectable tumors in ~20% of mice. Together, these data suggest that the MRTFA/SRF pathway is a critical regulator of quiescence in cancer and a potential therapeutic target.

Introduction

While targeted therapeutics and immunotherapy have had a significant impact in many tumor types, for many patients, chemotherapy remains the mainstay of treatment. Unfortunately, for many cancers, such as lung and ovarian, despite an initial response to chemotherapy, relapse is common, typically occurring within 2 years of completing therapy (1). This suggests an inherent mechanism of chemoresistance. A better understanding of mechanisms promoting chemotherapy resistance is critical to inform therapy development and improve patient outcomes.

One poorly studied mechanism of chemotherapy resistance is quiescence. Functionally, quiescent cells have alterations in chromatin structure, RNA content and processing, protein translation, and proteasome activity (2,3).Quiescent cells reversibly exit the cell cycle and are thus refractory to standard chemotherapies, which preferentially target rapidly proliferating cells (4). Quiescent cancer cells, often a subset of cancer stem-like cells (CSCs), exhibit resilience to therapy (5,6): slow-cycling pancreatic CSCs demonstrate enhanced chemotherapeutic resistance and tumor initiation capacity (7,8), quiescent leukemia stem cells (9,10), SOX2⁺ medulloblastoma stem cells (11), and colon cancer stem cells (12) have all been associated with therapeutic resistance and tumor recurrence.

Ovarian cancer (OvCa) is a disease in which chemotherapy resistance is particularly problematic. Chemotherapy remains the standard adjuvant therapy for patients with OvCa, and despite an almost complete clinical response with surgery and chemotherapy, approximately 60-70% will relapse and ultimately succumb to chemoresistant disease (1).. Quiescence is emerging as a critical driver of chemotherapy resistance in ovarian cancer. Gao et. al. identified a population of slow-cycling, chemotherapy-resistant OvCa CSCs that drive cancer recurrence in primary human tumors (13). Similarly, studies with OvCa patient samples and PDX models indicate that residual OvCa cells are enriched for Ki67(−) CSCs (14,15). Furthermore, when OvCa cells are grown in suspension, commonly seen with OvCa-associated ascites, they assume a reversible quiescent stem-like state and are chemotherapy resistant (16).

We recently demonstrated that the transcription factor Nuclear Factor of Activated T-cells-C4 (NFATC4) drives OvCa cell quiescence and chemotherapy resistance (17). This is analogous to the role of NFATc1 in promoting hair follicle stem cell quiescence (18,19). In addition, we found that inherently resistant quiescent OvCa (qOvCa) cells secrete factors, such as follistatin, to increase chemotherapy resistance in neighboring non-quiescent cells (20). Validating quiescence as a therapeutic target in ovarian cancer, we found that loss of follistatin activity could improve response to chemotherapy and increase cure rates in animal models (20).

To further increase our understanding of drivers of quiescence and identify putative quiescent cell therapeutic targets/pathways, we used single-cell microfluidic culture of primary ovarian cancer cells to identify and perform single-cell RNA sequencing on qOvCa. We identified numerous cellular changes consistent with quiescence. We found that the Myocardin-Related Transcription Factor-A (MRTFA)/Serum Response Factor (SRF) pathway is a master regulator of many qOvCa expressed genes, mediates chemotherapy resistance in vitro and in vivo, and represents an important therapeutic target.

Materials and Methods

Cell Culture

OVSAHO cells were donated by Dr. Deborah Marsh of the University of Sydney. PT412, provided by Dr. Geeta Mehta, was derived from an abdominal metastasis from a patient with platinum-sensitive high-grade serous ovarian cancer, as previously described (21). PT340 was used in our previous paper, with mutations as described (20). Other cell lines were purchased from ATCC or Sigma. All cell culture media were supplemented with 10% FBS and 1% penicillin/streptomycin and cultured at 37° C and 5% CO₂. All cell lines were tested bimonthly for the presence of mycoplasma. Cell counts were performed using the Moxi Z system (Orflo Technologies)and via hemocytometer using trypan blue.

Drugs

CCG257081 was synthesized and provided by Vahlteich Medicinal Chemistry Core at the University of Michigan for use in all our experiments. Carfilzomib (MedchemExpress) was used at 15μM doses unless otherwise specified. PLK1 inhibitor (onvasertib 100-300 nM), AURKA inhibitor (alisertib 30nM), or AXL inhibitor (Bencentinib, 120nM), blebbistatin (3-10uM) and oridonin (1 and 3μM) purchased from Selleckchem.

SiRNA knockdown of genes of interest

siRNA duplicates of Universal Negative Control (MISSION sigma cat# sic001), NCL (siRNA ID# SASI_Hs01_00116210 and SASI_Hs01_00116211), MYH9 (siRNA ID# SASI_Hs01_00197338 and SASI_Hs01_00197339) and EIF4G1 (siRNA ID# SASI_Hs01_00222596 and SASI_Hs01_00222597) were transfected into cell lines with Mission Transfection Reagent (Sigma #S1452) as per manufacturer’s protocol. MRTF-A siRNA (Santa Cruz, sc-43944) and MRTF-B siRNA (Santa Cruz, sc-61074) were transfected, at 10 nM concentration, with Lipofectamine RNAiMAX (Thermo Fisher, 13778100). Transfected cells were plated, in triplicate, in 2D cell culture assay and lysates harvested at 72h post-transfection. Experiments were done in triplicate.

Live cell imaging and analysis

Live cell imaging was performed using the IncuCyte; ~3000 cells were seeded into a 96-well plate and imaged every 4h for the duration of the experiment. Cell confluency was measured following training optimization experiments.

Flow Cytometry Analysis

Cells were fixed in 70% ethanol and incubated at −20°C for 20 minutes before being treated with RNase A and propidium iodide (PI) for 20 minutes and run on the CytoFlex flow cytometer (Beckman Coulter); at least 10,000 events were recorded and analyzed using FlowJo v10.6.2. For apoptosis detection, cells were stained with the Annexin-V FITC apoptosis kit (BD Biosciences) according to the manufacturer’s instructions at least 10,000 events were analyzed via CytoFlex. HEY1 cells expressing the p27-mVenus and CDT1-mCherry FUCCI cell cycle reporter (22) similarly analyzed on the CytoFlex

Quantitative PCR

RNA was extracted using RNeasy Mini Kit (Qiagen), and cDNA was made using SuperScript III Reverse Transcription Kit (Thermo Fisher). qPCR was performed with SYBR Green PCR Master Mix (Applied Biosystems), using standard cycling conditions and indicated primers (Sup Table 2).

Microfluidics cell capture

CD133⁺/ALDH⁺ cells were FACS isolated as previously described (23) and 10,000 cells were loaded onto single-cell-capture microfluidic devices, using gravity flow. Microfluidic devices were imaged at Day 0 and every 24h for 5 days. On Day 5, cells were stained with a viability stain, and single cells, whether they had divided or not, were collected via laser detachment retrieval. Single cells were snap frozen in Eppendorf tubes containing RT master mix and shipped to NYU genomic core for single-cell RNA sequencing, as previously described (24).

Bulk RNA sequencing

Ovarian cancer cell lines (OVSAHO, PT340, PT412) were treated for 72h with XXX MRTFA inhibitor CCG257081, and RNA was extracted using the miRNeasy Mini Kit (Qiagen, 217004). Bulk RNA sequencing was performed as previously described (20). Briefly, RNA quality was determined using Bioanalyzer, and sequencing was performed on the NextSeq platform (Illumina) using the 150-bp paired-ends protocol by Novogene Bioinformatics Technology (Beijing, China); 20 million reads were sequenced per sample, and sequencing data analysis was performed by Novogene aligned to hg19. Differential gene expression was performed by the R/Bioconductor package DESeq2. Gene ontology analysis was conducted using the R/Bioconductor package clusterProfiler.

Motif activity analysis

To infer transcription factor binding motif (TFBM) activities from cell line RNA-seq data, we used the Integrated System for Motif Activity Response Analysis (ISMARA). Differential motif activity between treatment groups was evaluated using two-sample t-tests, followed by multiple-hypothesis correction using the Benjamini–Hochberg false discovery rate (FDR) procedure to identify transcription factors whose inferred activities were significantly associated with treatment.

Western Blotting

Western blotting was performed as described (25). Membranes were incubated overnight with 1:1000 anti-CDKN1B (Abcam, ab32034) or 1:5000 anti-GAPDH (Proteintech cat# 60004-1-1g) antibodies in 5% skim milk. Membranes were washed in TBST, then incubated for 1h with 1:10,000 anti-mouse or anti-rabbit HRP (Cell Signaling) and rewashed with TBST. Visualization was performed with ECL Plus Western Blotting Substrate (Pierce). Densitometry and quantification were subsequently performed with ImageJ.

Chromatin Immunoprecipitation quantitative Polymerase Chain Reaction (ChIP-qPCR)

Approximately 5x10⁶ PT340 cells were seeded in a 15-cm tissue culture plate, allowed to attach for 24h, and treated with 1% DMSO (control) or 15μM CCG257081 for 24h. Cells were then washed and lysed for immunoprecipitation using SimpleChIP Plus Enzymatic Chromatin IP Kit (Cell Signaling, 9005S) according to the manufacturer’s instructions. qPCR was performed using SimpleChIP Universal qPCR Master Mix (Cell Signaling, 88989) with primers (Sup Table 3) targeting promoter regions with published SRF binding affinity (UCSC Genome Browser). The primers used for this study are available in supplemental material.

Proteasome activity assay

Proteasome activity was measured by monitoring the liberation of 7-amino-4-methylcoumarin from the Suc-LLVY-AMC(26). Cells were lysed via sonication in ice-cold 50mM Tris-HCl pH 7.5, 1mM DTT, 0.25M sucrose, 5mM MgCl2, 0.5mM EDTA, and 2mM ATP. The lysate was mixed with 50μM N-SUC-LEU-LEU-VAL-TYR-7-Amido-4-methylcoumarin (Sigma S6510) in 20mM Tris-HCl pH 7.5, 1mM ATP, 2mM MgCl₂, 0.2% bovine serum albumin and treated with DMSO (control), 10μM MG-132 (used to confirm the specificity of proteasome activity), or 15μM CCG257081. The AMC fluorescence was measured every 60 minutes in a Cytation 5 plate reader (BioTek) at an excitation wavelength of 340nm and emission wavelength of 420nm for up to 4h, with peak activity reported.

In vivo model

. All experimental procedures were conducted with the guidelines set by the Institute for Laboratory Animal Research of the National Academy of Sciences. 300,000 PT340 cells were xenografted into the subcutaneous space of six-week-old female NSG (NOD.Cg-Prkdc^scid) mice (Jackson Laboratory) When tumors were ~100mm³, mice were treated with DMSO, 20mg/kg oridonin, or 2mg/kg blebbistatin daily. This study was repeated and mice were treated with DMSO or CCG257081 20mg/kg daily for 3 weeks. A parallel survival study was done with tumors injected intraperitoneally (IP). One week after tumor injection, the animals were treated with CCG257081 Criteria for euthanasia were as previously published (20,27) including (i) an increase of 1cm of abdominal perimeter and/or (ii) changes in physiology and behavior (body weight, external pH, or physical appearance); (iii) lower response to stimulation (inability to reach food and water, lethargy or decreased mental awareness, labored breathing, or inability to remain upright). For dual therapy studies, mice were injected as above and treated with DMSO, carfilzomib (2 mg/kg), CCG257081 or combination CCG/carfilzomib daily.

Immunohistochemistry

Formalin embedded tumors were processed as previously described (20,28). Primary anti-rabbit Ki67 (1:500, Abcam #ab15580) was incubated overnight at 4° C. Subsequently, slides were incubated with a ready-to-use peroxidase-labeled anti-mouse HRP or anti-rabbit AP (Cell Signaling). Signal was visualized with DAB staining solution according to the manufacturer’s instructions and counterstained using hematoxylin. Ki67 was performed on six to eight independent sections of three independent PT340 cell-derived tumors. Images were captured on an Olympus BX41 fluorescent microscope with a 12-MB digital camera at 16-bit depth/300 dpi. Total stain area/low power field (100) was defined by pixel area (X:Y 1:1).

Immunofluorescence

For proliferation detection by EdU staining, cells were cultured with 10μM EdU for 24h and then fixed with 2% paraformaldehyde at 4°C for 30 minutes. Staining was performed using the Click-iT PLUS EdU Alexa Fluor 488 Imaging Kit (Life Technologies) and detected according to the manufacturer’s protocol. Coverslips were mounted onto slides and imaged using a Nikon A1 microscope. Human peritoneal cavity OvCa cells were obtained as part of an IRB-approved protocol as previously described (21). Briefly, cells with an intraperitoneal port underwent abdominal wash and fluid collection immediately prior to treatment with cisplatin and 24h after treatment. Collected fluid was centrifuged and live cells collected and frozen as live-cell suspensions.

Statistical analysis

Statistical analysis was conducted using GraphPad Prism (10.1.0). For scRNA-seq analysis, MNNCorrect and ComBat were used to confirm the absence of a batch effect. Afterward, paired t-tests were performed to compare quiescent vs. non-quiescent genes. Data was analyzed through two-tailed Student’s t-tests or one-way ANOVA. A p value of less than 0.05 was considered to be statistically significant. For in vitro studies (cell counts, viability, siRNA knockdown) a minimum of three replicate experiments were used for statistical analysis.

Data availability statement

The data analyzed in this study were obtained from Gene Expression Omnibus. RNA Sequencing data are processed by GEO, Submission entry MvWV4Omg. Other data generated in this study are available upon request from the corresponding author.

Results

RNA signature of quiescent ovarian cancer stem-like cells

To identify genes differentially expressed in proliferative vs. qOvCa, we used a microfluidic single-cell-culture device with laser retrieval capacity (29). FACs-isolated ALDH⁺/CD133⁺ OvCa cells were loaded, via gravity flow, into a 10,000-microwell device. Automated imaging was used to ensure capture of a single cell in each microwell. Microwells were imaged daily to monitor division. After 5 days in culture, cells were stained with a viability dye. While >95% of cells underwent cellular division during the 5-day period, ~5% of the viable cells did not proliferate, remaining as single cells (Fig 1A). We used laser retrieval to isolate ~200 dividing cells and ~100 quiescent cells from two primary ovarian cancer patient cell lines, PT340 and PT412. Isolated cells were then profiled using the CellSeq2 single-cell RNA-sequencing method (24).

Figure 1. Identifying and single-cell-RNA-seq profiling quiescent ovarian cancer stem cells identifies key quiescence genes and pathways.

A. Single-cell microfluidic images of live-cell-stain cells after 5 days in culture, identifying (left) a single non-dividing/quiescent cell and (right) a well with multiple cells that are derived from a single proliferating cell. B. GO analysis of the top downregulated molecular pathways. C. STRING analysis to the significantly enriched downregulated genes. D Normalized cell counts and quantification of PT412 cells G0/G1 status, following treatment with EIF4G1, MYH9, NCL or scrambled siRNA. E Representative flow cytometry and G0 quantification of HEY1 cells expressing the FUCCI cell cycle reporters, treated with EIF4G1, MYH9, NCL or scrambled siRNA. F. Normalized cell counts and viability of PT340 cells treated with oridonin or blebbistatin for 72h. Three μM cisplatin was used as a cell death viability control. G Tumor growth curve and tumor weights of PT340 tumor xenografts (n=10/treatment group). Black bars indicate treatment with 20mg/Kg oridonin, 2mg/Kg blebbistatin, or DMSO control daily. H Representative images and quantification of Ki67 staining. In vitro assays were replicated at least three times (n ≥ 3). Results were compared with Student’s T-test. Tumor Ki67 was analyzed for 6 to 8 independent sections of 3 independent tumors for each treatment group. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

Despite the limited depth of sequencing using the manual CellSeq2 amplification approach, we identified hundreds of genes which were significantly differentially expressed between the proliferating and quiescent cells (Sup Fig 1A). Gene-Ontology (GO) analysis of downregulated genes demonstrated significant downregulation of pathways associated with cellular metabolism, protein translation, RNA processing and metabolism, and chromatin binding (Fig 1B), while the major upregulated pathways were NADH/NADPH activity, transmembrane transport, and RNA binding (Sup Fig 1B). Due to the abundance of upregulated genes, we decided to investigate the function of the more modest number of significantly downregulated genes (Sup Table 1). STRING (Search Tool for the Retrieval of Interacting Genes/Protein) analysis of the downregulated genes identified EIF4G1, MYH9, and NCL as key signaling factors (Fig 1C) (30).

To determine whether downregulation of EIF4G1, MYH9, or NCL promotes a quiescent phenotype, we reduced their expression, using two siRNAs (Sup Fig 2) in the PT340 and PT412 OvCa cell lines (20). Compared to scrambled siRNA control, siRNA downregulation of all target genes resulted in a significant decrease in cell number (Fig 1D, PT412 p<0.001, Sup Fig 3A PT340 p<0.01), without impacting cell viability (Sup Fig 3B). Cell cycle analysis showed that, for all three genes, siRNA downregulation resulted in a significant increase in cells in the G0/G1 phase of cell cycle (Fig 1D, p<0.01). We next evaluated the impact of CCG257081 on the cell cycle, using the G0/G1 p27KIP1-mVenus/CDT1-mCherry Fucci reporter vectors (22). Similarly, FUCCI cell cycle reporter analysis demonstrated that downregulation of each gene significantly increased p27KIP1, which has been strongly linked with quiescence (Fig 1E, Sup Fig 3C p<0.01). MYH9 and NCL knockdown, but not EIF4G1 knockdown, increased the p27/CDT1⁺ G0 cells. Both MYH9 and NCL knockdown increased G0 population (Fig 1E, p<0.05-p<0.0001).

We next tested the impact of MYH9 and NCL inhibitors, blebbistatin and oridonin, respectively, on ovarian cancer cells (31). Both drugs significantly reduced cell number, without affecting cell viability (Fig 1F, p<0.0001). To determine whether these drugs, by inducing quiescence, could delay cancer growth in vivo, we tested them in a PT340 xenograft model. Both drugs significantly delayed tumor growth, with the NCL inhibitor oridonin having the greatest effect (Fig 1G, p<0.0001). Ki67 immunohistochemical staining in control and treated tumors confirmed a significant reduction in Ki67⁺ cells in both treatment groups (blebbistatin, p<0.01 and oridonin, p<0.001), with percent reduction in Ki67 staining mirroring percent reduction in tumor growth (Fig 1G-H).

Linking the MRTFA/SRF pathway and quiescence

While drugs targeting both MYH9 and NCL restricted tumor growth, neither had a profound effect. We speculated that resistance is more likely to develop when targeting a single downstream mediator of quiescence and therefore sought to identify a more global mediator. Mining the Harmonizome 3.0 gene and protein database revealed that numerous genes identified in qOvCa, including EIF4G1, MYH9, and NCL, were transcriptional targets of the MRTFA/SRF pathway (32). Strikingly, 61% of qOvCa differentially expressed genes are ChIP-seq-validated SRF targets (Fig 2A) (33-37).

Figure 2. Identifying the MRTFA/SRF pathway as a critical regulator of quiescence.

A. Venn diagram showing overlap of differentially expressed genes of scRNA-seq of primary quiescent cells and previously reported SRF targets (33). B. Normalized viable cell counts of PT340 cells treated with the indicated SiRNAs. C FUCCI cell cycle analysis and quantification of p27-mVenus expression in HEY1 cells treated with scrambled control, MRTFA, SRF, or MRTFA⁺SRF siRNA. D. Relative cell growth of doxycycline-induced MDA-MB-231 cells expressing control, wild-type (WT) MRTFA, or MRTF-A with a deletion of the SRF binding domain (ΔSRF). E. Summary of percent of cells in G0/G1 as measured by PI staining in PT340 cells transfected with WT MRTF-A, or MRTF-A-ΔSRF. F. IncuCyte real time imaging analysis of cellular confluence and viability analysis of control and CCG257081 (15μM every 48 h for 4 days) treated Pt412 cells. G. Representative flow cytometry and quantification of p27⁺ cell percentages of FUCCI cell cycle reporter (p27KIP1 mVenus/CDT1mCherry) analysis of control and CCG257081-treated HEY1 cells. H. Relative cellular proliferation in control and CCG257081 (CCG) treated cells with doxycycline induction of WT MRTFA or MRTF-ΔSRF. I. Western blot (left) and qRT-PCR assessment (right) of p27KIP1 (p27) protein and CDKN1B (gene that encodes p27) mRNA expression in control and CCG257081-treated cells PT340 cells. J. Cell counts of PT340 cells treated with the indicated siRNA alone or in combination with 15 μM of CCG257081. In all experiments, CCG257081 treatment was every 48h for 3 days. K. Relative mRNA expression for the indicated genes as assessed by qRT-PCR in PT412 cells treated with DMSO (control) or CCG257081 for 72h. All assays were replicated, in triplicate, at least three times and compared with an ANOVA, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

To determine whether knockdown of the MRTFA/SRF pathway could induce quiescence, we used siRNA to knock down MRTFA and SRF, individually or in combination (PT340 Fig 2B; PT412 Sup Fig 4A). Knockdown of either MRTFA, SRF, or both did not significantly impact cell viability (Sup Fig 3D). However, SRF knockdown resulted in a modest decrease in cell number, MRTFA knockdown reduced proliferation further, and dual knockdown had the greatest effect (Fig 2B). The FUCCI reporter system demonstrated that both MRTFA and dual MRTFA/SRF knockdown significantly increased the number of p27⁺ cells (Fig 2C, p<0.0001). To evaluate the impact of genetic loss of function of MRTFA-SRF signaling on quiescence, we used the previously established human breast cancer cell line MDA-MB-231, expressing doxycycline-inducible wild-type MRTFA, or MRTFA with a deleted SRF binding domain (MRTF-ΔSRF which prevent MRTFA:SRF interactions). Compared to parental controls, cells expressing wild-type MRTFA demonstrated a modest increase in proliferation (Fig 2D, p<0.01). In contrast, consistent with disruption of the MRTFA-SRF interaction driving a quiescent state, cells expressing MRTF-ΔSRF demonstrated a significant restriction in proliferation (Fig 2D, p<0.001). Furthermore, MRTF-ΔSRF-expressing cells demonstrated an increase in number of cells in G0/G1 in propidium iodide-based cell cycle analysis (Fig 2E, p<0.0001).

To further interrogate the role of the MRTFA/SRF axis in quiescence, we treated the ovarian (PT340, PT412 OVSAHO) and breast (T47D) cancer cell lines with CCG257081, a high-affinity small-molecule inhibitor which induces MRTFA nuclear-to-cytoplasmic localization and inhibits SRF transcriptional activity (38,39). Suggesting induction of quiescence, (i) real-time live-cell imaging (Fig 2F), (ii) total cell counts and viability assays (Fig 2F and Sup Fig 5A, B), and (iii) cell cycle analysis (Sup Fig 6) indicated CCG257081 treatment restricted cell numbers/proliferation without inducing cell death. Furthermore, supporting induction of quiescence, after 48h of CCG257081 treatment, drug washout allowed cells to rapidly resume proliferation (Supp Fig 7). FUCCI reporter analysis of CCG257081-treated cells demonstrates a strong induction of p27 expression (Fig 2G), similar to that seen with MRTFA/SRF dual knockdown (2C). This normalized with drug washout (Supp Fig 7). Further linking CCG257081 activity to the MRTFA/SRF pathway, over-expression of wild-type MRTFA in MDA-MB-231 cells induced partial resistance to CCG257081, while over-expression MRTF-ΔSRF protein resulted in further reductions in cell growth (Fig 2H).

To determine whether endogenous p27KIP1 (p27) levels are increased with CCG257081 treatment, we performed Western blotting and qRT-PCR on CCG257081-treated cells. We observed a dose-dependent increase in endogenous p27 protein levels with CCG257081 treatment and an increased expression of p27 mRNA (encoded by CDKN1B) at the mRNA level (Fig 2I). Indicating p27 is necessary for the growth-restricting effect of CCG257081, CDKN1B (gene which encodes p27) knockdown with siRNA protected the cells against CCG257081-mediated quiescence, while SRF knockdown enhanced CCG257081’s effects (Fig 2J, p<0.01). Linking the pathway to the original qOvCa RNA-seq signature, qRT-PCR of treated cells indicated CCG257081 significantly repressed mRNA expression of EIF4G1, MYH9, and NCL (Fig 2K, Supp. Fig 5C, p<0.05). These data indicate that inhibition of the MRTFA/SRF pathway, via induction of p27, results in a quiescent state in cancer cells.

CCG257081 induces quiescence broadly across cancer types

We next CCG257081-treated cancer cell lines from multiple cancers, including colon (SW480, HT-29), breast (MCF7, MDA-MB-231, T47D), lung (H522, H2170), and pancreatic (PATU). We found that CCG257081 restricted cell growth in all cancer cell lines tested (Fig 3A), suggesting induction of a quiescent state. Further supporting the induction of quiescence, treatment of RFP-labeled MDA-MB-231 cells (triple-negative breast cancer cell line) with CCG257081 eliminated EdU uptake, suggesting an arrest of proliferation (Fig 3B).

Figure 3. Characterization of MRTFA/SRF inhibition effects across tumor cell types and RNA-seq analysis.

A. Normalized cell counts of the indicated colon, breast, lung, and pancreatic cancer cell lines, treated with DMSO or CCG257081. B. Summary and representative IF image of EdU staining in control and CCG257081-treated RFP-MDA-MB-231 breast cancer cells. C. RNA-seq Volcano plots of differential gene expression between control and CCG257081-treated cells (left). Gene Ontology (GO) analysis of the top pathways downregulated by CCG257081 treatment (middle). Volcano plot of top 100 transcription factor pathways differentially regulated in the RNA-seq of CCG257087 vs control treated ovarian cancer cells (right). D. Representative flow cytometry plots and summary of HEY1 p27⁺ cells expressing the FUCCI cell cycle reporters and treated with either AXL (bemcetinib), Aurora Kinase-A (AURKA, alisertib), or polio-like kinase 1 (PLK1, onvansertib) inhibitors. E. Normalized cell counts, and percent live cells following treatment with the indicated inhibitors. F. ChIP-qPCR comparing relatively promoter binding with IgG control and SRF immunoprecipitation in DMSO (control) and CCG257081 treated PT340 cells. In vitro assays were replicated in triplicate at least three times and compared with an ANOVA, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

Identifying other quiescent cancer cell therapeutic targets

To identify additional genes being regulated by CCG257081, we performed RNA sequencing on CCG257081-treated cells from three independent ovarian cancer cell lines. Principle component analysis demonstrated a clear treatment effect (Supp. Fig 8). Volcano plot using a Log2 fold change of at least one and an adjusted p value<0.05 revealed that, like the single-cell quiescence signature, more genes were upregulated (994) than downregulated (352) across the three cell lines (Fig 3C). Downregulated genes included numerous cell cycle and DNA damage response-linked factors and growth factors, including: PLK1, CCNA2, CDC25A, E2F8, AURKA, EGR3, and HB-EGF. Gene ontology pathway analysis of downregulated genes identified changes in pathways related to telomere binding, mitotic and meiotic DNA replication, and DNA repair (Fig 3C). Upregulated genes include AXL, SEMA3B, TGFb1L1, and FBXO2. GO pathway analysis of upregulated genes identified changes in pathways related to peptide catabolism, cell adhesion, lipid and fatty acid metabolism, and several biosynthetic processes (Supp Fig 9A). We next performed transcription factor motif analysis (40) on the RNA-seq data. As expected, SRF activity was significantly downregulated (Fig 3C). Top downregulated transcription factor pathways included important proliferation-driving factors, including E2F factors and MYC signaling. The top upregulated pathways included the ER stress-linked transcriptional regulators XBP1 and ATF6 (Fig 3C).

Several of the genes downregulated in our dataset, such as PLK1 (polio-like kinase 1) and AURKA (aurora kinase-A) have been proposed as cancer therapeutic targets (41,42). AXL, another therapeutic target, was upregulated. To determine whether inhibition of these targets restricts cancer growth by impacting quiescence (as opposed to inducing cell death), we treated ovarian cancer cells with ~IC50 doses of PLK1 inhibitor (onvasertib), AURKA inhibitor (alisertib), or AXL inhibitor (Bemcentinib). Consistent with induction of quiescence, Fucci reporter analysis indicated a strong upregulation of p27KIP1⁺/CDT1⁺ cells in G0 with the AURKA and PLK1 inhibitors (Fig 3D, p<0.0001). In contrast, the AXL inhibitor reduced the percentage of cells in GO. Confirming that AURKA and PLK1 inhibitors induce quiescence while the AXL inhibitor induced cell death, the AURKA and PLK1 inhibitors reduced cell numbers without affecting cellular viability (Fig 3E, p<0.0001).

To directly link expression of the CCG257081 quiescenc-associated genes MYH9, NCL, E2F8, CCNA2, CDC25A, and PLK1 to SRF transcriptional activity, we performed ChIP-PCR with antibodies reacting to SRF in control (DMSO) and CCG257081-treated cells. All six genes showed significant enrichment of promoter DNA binding with anti-SRF antibodies vs. control IgG, and indicating CCG257081 inhibits SRF activity, CCG257081 treatment reduced SRF DNA binding to control levels (Fig 3F).

MRTFA/SRF inhibition results in proteasome-dependent downregulation of CD133 and synergizes with proteasome inhibitors

Given quiescence is commonly a feature of CSC, we evaluated the impact of CCG257081 on the expression of ovarian cancer stem cell markers ALDH (as measured by Aldefluor activity) and CD133 using flow cytometry. To ensure significant CD133 expression, we enriched it, using CD133 magnetic beads isolated in three OvCa cell lines. Cells were then treated with CCG257081 for 24h and evaluated for CD133 expression via flow cytometry. We observed a decrease in CD133 expression with CCG257081 treatment (Fig 4A, p<0.01-p<0.001). Indicating this was a true reduction of protein and not a loss of surface expression of CD133, Western blotting after 48h of CCG257081 treatment confirmed a strong reduction in CD133 protein expression (Fig 4B). Surprisingly, qRT-PCR for PROM1 (gene that encodes CD133) in control and CCG257081 treated cells did not show significant differences, suggesting CD133 downregulation was not occurring via mRNA downregulation (Sup Fig 8B).

Figure 4. CCG257081 Treatment results in proteasome dependent downregulation of CD133 and synergizes with proteasome inhibitor therapy.

A Representative CD133 flow cytometry plots and quantification of % positive CD133 cells with the indicated treatments. B. CD133 Western blot in the indicated cell lines treated with DMSO control or CCG257081 (CCG081). C Representative Annexin-V/Propidium Iodide flow cytometry plots and quantification of % dead cells in PT340 cells treated with the indicated compounds. D. Summary of apoptotic cell percentages with the indicated colon and lung cancer cell lines. E. Loewe synergy heat map for CGG257081 (CCG081) and Carfilzomib. F. Proteasomal activity, measured via 7-amino-4-methylcoumarin release assay, in the indicated populations of PT340 cells. In vitro assays were replicated in triplicate at least three times and compared with an ANOVA, * p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

To determine if CD133 downregulation is dependent on the proteasome, we repeated flow cytometry assays with CCG257081 treatment in the presence or absence of the proteasome inhibitor MG132. Suggesting a role of the proteasome in CD133 degradation, MG132 treatment partially rescued CD133 expression at 24h in all three cell lines tested (Fig 4A). We next extended therapy with both CCG257081 and MG132 for 72h. Strikingly, while neither drug alone induced significant cell death, both drugs together resulted in profound cell death (Fig 4C, p<0.001). Induction of cell death was similarly seen with the clinically approved proteasome inhibitor carfilzomib (Fig 4C right). The synergy between these two drugs was not specific to ovarian cancer but seen also in other cancer cell lines tested, including SW480 (colon) and HT2170 (lung) (Fig 4D, p<0.001). Loewe Synergy calculations confirmed strong synergistic interaction between CCG257081 and carfilzomib (Fig 4E, p<0.001).

Given the observed synergy between CCG257081 and proteasome inhibition, we evaluated the proteasomal activity of (i) bulk ovarian cancer cells, (ii/iii) proliferating ovarian cancer quiescent/slowly dividing cells (as determined by vital dye retention after 7 days in culture), (iv) cells treated with the proteasome inhibitor tool compound MG132 and (v) cells treated with CCG257081. Proteasome activity was measured by monitoring the release of 7-amino-4-methylcoumarin from the synthetic proteasome substrate Suc-LLVY-AMC (26). We observed that slowly dividing cells demonstrated more proteasomal activity than bulk cells and rapidly dividing cells (Fig 4F). Consistent with RNA-seq data indicating suppression of proteasome-related pathways, CCG257081 treatment significantly reduced proteasome activity to a degree comparable to MG132 (Fig 4F).

Quiescence and chemotherapy resistance

Quiescence has been linked to chemotherapy resistance (17,43). To determine if the inhibition of MRTFA/SRF function could increase therapeutic resistance, we treated ovarian cancer cell lines with CCG257081 for 48h and then initiated treatment with cisplatin or radiation therapy. Consistent with the role of quiescence and therapeutic resistance, we found that cells treated with CCG257081 were more resistant to both cisplatin (Fig 5A) and radiation therapy (Fig 5 B, Supp Fig 10).

Figure 5. MRTFA/SRF pathway and chemotherapy resistance.

A. Cisplatin chemotherapy response curves for the indicated cell lines +/− CCG0257081 pretreatment. B. Radiation response curves for the OVSAHO cells +/− CCG0257081 pretreatment. C. MRTFA immunofluorescence in PT340 cells prior to, 24h and 72h after cisplatin treatment. D. MTRFA/CK7 immunofluorescence (left) and quantification (right) of patient tumor abdominal fluid collected before (untreated) and 24h (treated) intraperitoneal chemotherapy treatment. E. Cell viability curves for control, doxycycline inducible MRTFΔSRF expressing, and doxycycline inducible MRTFA expressing MDA-MB-231 cells. Each cell line is normalized to its total cell number prior to treatment with each data point in triplicate in replicate experiments. F. Correlation of MRTFA and SRF expression with chemotherapy response using the TCGA dataset. Survival curves are representative of replicate experiments with at least triplicate evaluations at each time point. Curves are compared using ANOVA, bar graphs are compared with students t-test. *p<0.05, **p<0.01, ***p<0.001.

MRFTA transcriptional activity is regulated by nuclear (active)/cytoplasmic (inactive) shuttling. To assess whether the MRTFA/SRF pathway could be inactivated in response to chemotherapy we evaluated MRTFA cellular localization in ovarian cancer cells exposed to chemotherapy. In non-treated cells, MRTFA was expressed diffusely in the cell, detectable throughout the cytoplasm and nucleus (Fig 5C). Conversely, 24h after cisplatin exposure, MRTFA was primarily detected in the cytoplasm, and expression was excluded from the nucleus. Seventy-two hours after cisplatin treatment, localization began to normalize (Fig 5C). To demonstrate the in vivo relevance, we repeated this study using OvCa patient specimens (n=9) collected from the intraperitoneal cavity immediately prior to and 24h after cisplatin treatment. We then used immunofluorescence to evaluate MRTFA cellular localization. CK7 positivity was used to distinguish cancer cells. CK7⁺ cancer cells demonstrated diffuse cytoplasmic and nuclear MRTFA expression prior to chemotherapy, while 24h after chemotherapy treatment, there was ~60% reduction in nuclear MRTFA expression (Fig 5D).

We next tested the impact of chemotherapy response and recovery on control and doxycycline (dox)-induced MRTF-ΔSRF-expressing (pathway inactivating) or MRTFA-overexpressing MDA-MB-231 cells. Cell numbers were normalized to dox non-treated matched controls. In line with pathway inactivation inducing a quiescent/chemoresistant state, MRTF-ΔSRF-expressing cells demonstrated slowed growth and immediate chemoresistance early in the time course (Fig 5E). In contrast, compared to controls, MRTFA-overexpressing cells demonstrated a similar nadir in response to chemotherapy (Fig 5E) but, MRTFA-overexpressing cells recovered proliferation after chemotherapy more rapidly than controls such that cell numbers were significantly higher at the later stages of the time course (Fig 5E, p<0.001). Confirming the relevance of the MRTFA/SRF pathway in chemoresistance, evaluation of MRTFA and SRF expression in platinum-sensitive and platinum-resistant tumors from TCGA (44) demonstrated that. MRTFA expression was significantly enriched in platinum-resistant tumors (p=0.035), while SRF demonstrated a trend for enrichment (p=0.11) (Fig 5F).

Pharmacologically enforced quiescence as a therapeutic strategy and target

To evaluate the therapeutic potential of MRTFA/SRF pathway inhibition, we treated two triple-negative breast cancer organoids with CCG257081. Treatment resulted in (i) a reduced number (Fig 6A, p<0.0001) and (ii) size of organoids (Fig 6B), and (iii) organoids with a significantly lower percentage of Ki67-positive cells (Fig 6B, p<0.05). Linking this to the MRTFA/SRF pathway, we had previously noted that tumor initiation by MDA-MB-231 cells expressing MRTF-ΔSRF demonstrated a dramatic reduction in tumor initiation (45). MRTF-ΔSRF tumors that were evaluable showed a significant reduction in Ki67 cells (Fig 6C, p<0.01).

Figure 6. CCG257081 growth arrest in tumor models.

(A) Normalized cell counts, (B) representative Ki67 IHC and quantification from two triple negative breast cancer cell (TNBC) organoid cultures treated with DMSO (control) or 10 uM CCG257081. C. Quantification of Ki67 stain from tumor MDA-MB-231 cells expressing the indicated MRTF-A constructs. D. Tumor growth curves for PT340 xenografts treated with 20 mg/Kg CCG257081 or vehicle (DMSO) control daily (black bars indicate treatment window). E. qRT-PCR expression for the indicated genes in control and CCG257081-treated tumors. F. Representative images and quantification of Ki67 staining in control and CCG257081 treated tumors, 6 to 8 independent sections of 3 independent tumors for each treatment group. G. Kaplan-Meier overall survival curves for PT340 tumor cells injected intraperitoneally and treated with vehicle (DMSO), carfilzomib (2 mg/kg), CCG257081 (20 mg/Kg) or combination CCG/carfilzomib daily (black bars indicate treatment window). H. Normalized cell viability in response to cisplatin chemotherapy in control and CCG257081 resistant ovarian cancer cells. *P<0.05, **P<0.01, ***P<0.001. High Power Field (HPF).

To determine how CCG257081 performed in an in vivo, we treated PT340 ovarian cancer xenografts with CCG257081. CCG257081 treatment was associated with a prolonged restriction in tumor growth (Fig. 6D, p<0.0001). Evaluation of treated tumors showed CCG257081 treatment was associated with a strong reduction in NCL expression and a decreasing trend in EIF4G1 expression (Fig 6E, p<0.05). CCG257081-treated xenografts also had a significant reduction in Ki67 (~ 4-fold) compared to control (Fig 6F p<0.01).

Given we observed proteasome inhibition could induce cell death in CCG-257081 treated cells, we performed an overall survival tumor study with CCG257081 alone and in combination with the proteasome inhibitor carfilzomib. While single-agent carfilzomib had no impact on survival, single-agent CCG257081 led to a significant increase in survival compared with controls (Fig 6G, p<.001). Addition of carfilzomib to CCG257081 further increased survival, with two animals without evidence of disease at 100 days (Fig 6G, p<0.001).

These findings suggest that MRTFA/SRF-targeted therapies—analogous to clinically used cell cycle–modulating agents such as CDK4/6 inhibitors (46,47), may function as effective maintenance strategies to delay disease recurrence. However, it is important that such therapies do not permanently induce chemotherapy resistance following drug discontinuation. To evaluate this, we treated three ovarian cancer cell lines with CCG257081 daily to generate resistance such that cells demonstrated the ability to proliferate on therapy. We then compared the chemotherapy response in the parental and CCG257081-resistant cells. Notably, there was no difference in chemotherapy response (Fig 6H).

Discussion

In this study, we used a single-cell microfluidic approach to characterize the expression profile of qOvCa cells. Supporting the validity of the results, the RNA signature of qOvCa cells mirrors that seen in normal adult quiescent cells such as hematopoietic stem cells and neuronal stem cells (48). Like adult quiescent stem cells, qOvCa cells demonstrated significant changes that would impact protein homeostasis, including a downregulation of pathways related to mRNA processing/splicing, translation initiation, and protein/nitrogen metabolism. Interestingly, we also observed that many genes—many related to cellular metabolism—were upregulated in qOvCa. This suggests that the state of quiescence is not simply an arrested or hibernating state, but a distinct state with altered activities.

MYH9 and nucleolin as key quiescent genes

MYH9 is expressed in a wide range of tissues and is a member of the Myosin II motor protein superfamily, where it has normal physiological roles in cell migration/adhesion, cytokinesis, signal transduction and cell-structure maintenance. MYH9 has been widely reported to promote tumor progression, metastasis, and recurrence in a wide range of cancers (49) . Interestingly, MYH9 is a target of MRTFA (50) that can regulate CSC populations via mTOR signaling and upregulation of stem cell genes (CD44, SOX2, Nanog, CD133, and OCT4) (51,52). In OvCa, high expression of MYH9 in patient samples correlates with poor progression-free and overall survival and more advanced staging (53). Corroborating our findings, a recent study demonstrated a decrease in ovarian cancer proliferation, migration, invasion, and metastasis, both in vivo and in vitro, following downregulation of MYH9 with microRNA (54).

Nucleolin is a protein that is present in all growing eukaryotic cells, participating in ribosomal transcription, cell proliferation, and growth. Nucleolin has been found to be implicated in multiple aspects of both DNA and RNA as well as protein metabolism and angiogenesis (55). Nucleolin upregulation plays a critical role in molecular regulation of quiescence in hematopoiesis when it interacts with G0S2-associated proteins (56). In addition to MYH9 and nucleolin, we observed a strong induction of p27/dependency for p27 in CCG257081-triggered quiescence. This is consistent with a well-established role for p27 in quiescence (57).

The MRTFA/SRF pathway as a master regulator of quiescence

Serum is an important driver of cell proliferation, and its withdrawal can induce quiescence (58). This proliferative response is driven by ERK-regulated ternary complex factors in conjunction with SRF (59). SRF also works with the transcription co-activator MRTF-A, regulating cytoskeleton and contractility (60,61). Increasing data also positions MRTFA/SRF as a critical player in cancer (62). Rho kinases and the MRTFA/SRF pathway are linked with cancer “stemness” and epithelial-mesenchymal transition, cell migration, and metastasis in multiple cancers (63-66).

Our work suggests that activation/inhibition of the MRTFA/SRF transcription factor complex can mediate the balance of quiescence vs. proliferation in cancer cells. Specifically, when MRTFA and SRF cooperate in the nucleus to activate transcription, they activate proliferation (59). However, disruption of this interaction, with subsequent localization of MRTFA to the cytoplasm, stops proliferation and contributes to quiescence. As such, this axis represents a potential therapeutic target. While transcription factors have been notoriously difficult to target therapeutically, CCG257081 successfully blocks activation of the serum response element driving transcriptional activity, at least in part, by the blockade of MRTFA cytoplasmic-to-nuclear localization, mirroring other clinically relevant drugs, such as tacrolimus, which blocks NFAT transcriptional activity by inhibiting cytoplasmic-to-nuclear localization (38). RNA-seq indicates that CCG257081-mediated MRTFA/SRF inhibition leads to broad downstream transcriptional changes with differential expression of thousands of genes. Transcription factor motif analysis suggests downregulation of other important proliferation-promoting transcription factor pathways, including E2F factors and MYC-MAX.

Quiescence and the proteasome:

These studies support a critical role for the proteasome in quiescent cells. This is consistent with work of others (67,68). Furthermore, targeting the proteasome in conjunction with quiescence factor eIF2a has been reported to lead to the elimination of quiescent cells in multiple myeloma (69). Our work indicates that the role of the proteasome in quiescence will be complex. We observed that CCG257081 has a differential impact on proteasomal activity. It suppresses overall proteasomal activity; however, we see CCG-257081 mediation increases proteasome-dependent CD133 degradation. This is in line with literature indicating CD133 degradation via the proteasome/lysomal system (70,71) and a link for CD133 downregulation and suppression of the cell cycle (72,73). We have been unable to identify the specific driver of CCG257081-mediated CD133 degradation. Future studies will be needed to better define the role of the proteasome and its potential as a therapeutic target in quiescent cells.

Quiescence as a therapeutic strategy and target:

Our data indicates that both driving cells into a quiescent state and targeting quiescent cells may be viable therapeutic approaches. Forced quiescence will not increase cure rates. However, forced quiescence in diseases, such as ovarian or lung cancer, with a high and rapid relapse rate, could significantly improve relapse-free survival. Importantly, our studies indicate that targeting a single component of quiescence, such as MYH9 or NCL, may be insufficient to force prolonged quiescence, as resistance develops relatively rapidly. Targeting master regulators, such as MRTFA/SRF, can have a much more profound effect.

Ultimately, killing quiescent cells may increase cancer cure rates. Agents such as CCG257081 could be used to force cancer cells into a quiescent state AND sensitize these cells to drugs, such as carfilzomib, to synergistically kill otherwise therapeutically resistant cancer cells. Given the induction of ER stress-associated transcription factors, ER stress-targeting drugs may be additional targets to consider. We have also found that autophagy is an important target in quiescent cells. Timing of the use of quiescence-inducing agents will be critical. Indeed, use of a quiescence-inducing agent before chemotherapy could induce therapeutic resistance; these drugs should only be used after completion of chemotherapy, either as maintenance therapy to delay relapse or, ideally, in combination therapy, as consolidation, to kill residual cancer cells. Unlike drugs such as PARP inhibitors which target the DNA damage/repair pathway and can increase chemotherapy resistance after maintenance therapy, our study suggests that the development of resistance to CCG-257081/MRFT/SRF pathway inhibition does not increase chemoresistance upon drug discontinuation.

Quiescence inducers in the clinic:

While most oncology drugs were developed to induce cell death, more recently, drugs are being developed that induce cell cycle arrest without necessarily inducing cell death. CDK4/6 inhibitors are now widely used for the treatment of patients with breast cancer. These drugs do not increase cure rates but can increase patient survival. In vitro studies have reported that these drugs can induce senescence in breast cancer cells. We have found that, at least in ovarian cancer, CDK4/6 inhibitors induce reversible cell cycle arrest, more consistent with quiescence. Aurora A kinase inhibitors are also being developed for various cancer therapies. These drugs induce G2/M cell cycle arrest. Our studies suggest that these, too, induce quiescence. CCG257081 is currently only a tool compound and has not been tested in the clinic. However, it has characteristics of a potential drug: CCG-257081 has excellent bioavailability and pharmacokinetics and has not shown significant toxicities in animal studies, even with daily treatment up to 100 mg/kg (we treat at 20mg/kg) (74). Consistent with this, we found no abnormalities in blood counts or liver function in mice treated with CCG257081 daily for 30 days.

Significance:

The balance between quiescence and proliferation impacts chemotherapy response and recovery. We find the MRTFA/SRF pathway regulates cancer cell quiescence/proliferation, impacting chemotherapy response and tumor outgrowth, and representing an important therapeutic target.

Conclusion

We have characterized qOvCa cells and identified the MRTFA/SRF pathway as a critical regulatory switch of proliferation vs. quiescence. As such, inhibition of MRTFA/SRF signaling appears to drive a quiescent state in multiple cancer types. Our data implicate MRTFA/SRF as a novel therapeutic target to enforce a quiescent cancer cell state, resulting in delayed tumor growth, and in combination with proteasome inhibitors, can be used to eradicate quiescent cells and potentially increase cancer cure rates.

Highlights.

• Primary patient-derived quiescent ovarian cancer cells (qOvCa) have a distinct expression profile

• The MRTFA/SRF transcription factors dictate expression of qOvCa cell genes

• MRTFA inhibitors drive a quiescent state in cancer cells

• Chemotherapy exposure in patients drives MRTFA inhibition and MRTFA expression is correlated with early relapse

• MRTFA driven quiescence sensitizes cancer cells to proteasome inhibition, increasing cure rates in animal models