Biology subjects

Jolly, M. K.

Publications and source records attributed to Jolly, M. K..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Multi-modal transcriptomic analysis unravels enrichment of hybrid epithelial/mesenchymal state and enhanced phenotypic heterogeneity in basal breast cancer

Intra-tumoral phenotypic heterogeneity promotes tumor relapse and therapeutic resistance and remains an unsolved clinical challenge. It manifests along multiple phenotypic axes and decoding the interconnections among these different axes is crucial to understand its molecular origins and to develop novel therapeutic strategies to control it. Here, we use multi-modal transcriptomic data analysis - bulk, single-cell and spatial transcriptomics - from breast cancer cell lines and primary tumor samples, to identify associations between epithelial-mesenchymal transition (EMT) and luminal-basal plasticity - two key processes that enable heterogeneity. We show that luminal breast cancer strongly associates with an epithelial cell state, but basal breast cancer is associated with hybrid epithelial/mesenchymal phenotype(s) and higher phenotypic heterogeneity. These patterns were inherent in methylation profiles, suggesting an epigenetic crosstalk between EMT and lineage plasticity in breast cancer. Mathematical modelling of core underlying gene regulatory networks representative of the crosstalk between the luminal-basal and epithelial-mesenchymal axes recapitulate and thus elucidate mechanistic underpinnings of the observed associations from transcriptomic data. Our systems-based approach integrating multi-modal data analysis with mechanism-based modeling offers a predictive framework to characterize intra-tumor heterogeneity and to identify possible interventions to restrict it.

systems biology↗

bioRxiv2023

Reconstruction of single cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition

Exploring the complexity of the epithelial-to-mesenchymal transition (EMT) unveils a diversity of potential cell fates; however, the exact timing and intricate mechanisms by which early cell states diverge into distinct EMT trajectories remain unclear. Studying these EMT trajectories through single cell RNA sequencing is challenging due to the necessity of sacrificing cells for each measurement. In this study, we employed optimal-transport (OT) analysis to reconstruct the past trajectories of different cell fates during TGF-beta-induced EMT in the MCF10A cell line. Our analysis revealed three distinct trajectories leading to low EMT, partial EMT, and high EMT states. Cells along partial EMT trajectory showed substantial variations in the EMT signature and exhibited pronounced stemness. Throughout this EMT trajectory, we observed a consistent downregulation of the EED and EZH2 genes. This finding was validated by recent inhibitor screens of EMT regulators and CRISPR screen studies. Moreover, we applied our analysis of early-phase differential gene expression to gene sets associated with stemness and proliferation, pinpointing ITGB4, LAMA3, and LAMB3 as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that CENPF, CKS1B, and MKI67 showed significant upregulation in the high EMT trajectory. While the first group of genes aligns with findings from previous studies, our work uniquely pinpoints the precise timing of these upregulations. Finally, the latter group of genes represents newly identified regulators, shedding light on potential targets for modulating EMT trajectories. Significance StatementIn our study, we investigated cellular trajectories during EMT using a time-series scRNAseq dataset. OT analysis was used to infer cell-to-cell connections from scRNAseq data, allowing us to predict cell linkages and overcome limitations of sequencing such as the need to sacrifice cells for each measurement. This approach allowed us to identify diverse EMT responses under uniform treatment, a significant advancement over previous studies limited by the static nature of scRNAseq data. Our analysis identified a broad set of genes involved in the EMT process, uncovering novel insights such as the upregulation of cell cycle genes in cells predisposed to a high EMT state and the enhancement of cell adhesion marker genes in cells veering towards a partial EMT state. This work enriches our understanding of the dynamic processes of EMT, showcasing the varied cellular fates within the same experimental setup.

systems biology↗

bioRxiv2023

Mutually exclusive teams-like patterns characterize phenotypic heterogeneity along the noradrenergic-mesenchymal axis in neuroblastoma

Neuroblastoma is the most frequent extracranial pediatric tumor and leads to 15% of all cancer-related deaths in children. Tumor relapse and therapy resistance in neuroblastoma are driven by phenotypic plasticity and heterogeneity between noradrenergic (NOR) and mesenchymal (MES) cell states. Despite the importance of this phenotypic plasticity, however, the dynamics and molecular patterns associated with these bidirectional cell-state transitions remain relatively poorly understood. Here, we analyze multiple RNA-seq datasets at both bulk and single-cell resolution, to understand the association between NOR- and MES-specific factors. We observed that NOR-specific and MES-specific expression patterns are largely mutually exclusive, exhibiting a "teams-like" behavior among the genes involved, reminiscent of our earlier observations in lung cancer and melanoma. This antagonism was noticed also in the association of NOR and MES phenotypes with metabolic reprogramming and with immunotherapy targets PD-L1 and GD2, and in experimental perturbations driving the NOR-MES and/or MES-NOR transition. Further, this "teams-like" patterns was seen only among the NOR- and MES-specific genes, but not in housekeeping genes, possibly highlighting a hallmark of network topology enabling cancer cell plasticity.

cancer biology↗

bioRxiv2023

Characterizing heterogeneity along EMT and metabolic axes in colorectal cancer reveals underlying consensus molecular subtype-specific trends

Colorectal cancer (CRC) is highly heterogenous with variable survival outcomes and therapeutic vulnerabilities. A commonly used classification system in CRC is the Consensus Molecular Subtypes (CMS) based on gene expression patterns. However, how these CMS categories connect to axes of phenotypic plasticity and heterogeneity remains unclear. Here, we analyze 101 bulk transcriptomic datasets, along with patient tumor samples from TCGA and single-cell RNA sequencing data, to evaluate the extent of variation among CMS subtypes across metabolic plasticity and EMT axes. Our results show that CMS2 and CMS3 samples were relatively more epithelial as compared to CMS1 and CMS4. Single-cell RNA-seq analysis of CMS1 revealed two subpopulations: one close to CMS4 (more mesenchymal) and the other closer to CMS2 or CMS3 (more epithelial), indicating a partial EMT-like behavior. Further, in our meta-analysis and in TCGA data, epithelial phenotype score was positively correlated with scores of glycolysis, OXPHOS and FAO pathways, while mesenchymal scores showed CMS subtype-specific associations with metabolic axes. PD-L1 activity scores, however, consistently correlated positively with mesenchymal signature ones and negatively with epithelial signature ones, across the four CMS categories. Together, our results quantify the patterns of two interconnected axes of phenotypic heterogeneity - EMT and metabolic reprogramming - at a CMS subtype level in CRC.

cancer biology↗

bioRxiv2023

p53 amyloid pathology with cancer grades and p53 mutations

p53 mutation and amyloid formation are implicated with cancer pathogenesis, but the direct demonstration of the link between p53 amyloid load and cancer progression is lacking. Using multi-disciplinary techniques and a cohort of 59 tumor tissues (53 from Indian cancer patients and six normal tissues) of oral and stomach cancer types, we showed that p53 amyloid load and cancer grades are highly correlated. Further, next-generation sequencing (NGS) data suggest that not only mutant p53 (e.g., SNVs, deletions, and insertions) but wild-type p53 also formed amyloids either in the nucleus (50%) and/or in the cytoplasm in most cancer tissues. Interestingly, in all these cancer tissues, p53 displays a loss of DNA binding and transcriptional activities, which is highly aggravated with the amyloid load and cancer grades. The p53 amyloids also sequester higher amounts of p63/p73 isoforms in higher-grade of tumor tissues. The data suggest p53 misfolding/aggregation and subsequent amyloid formation lead to loss and gain of p53 tumorigenic function, aggravation of which might determine the cancers grades.

cancer biology↗

bioRxiv2023

A systems-level analysis of the mutually antagonistic roles of RKIP and BACH1 in dynamics of cancer cell plasticity

Phenotypic plasticity is a hallmark of cancer metastasis. Epithelial-mesenchymal transition (EMT) is an important axis of phenotypic plasticity. Raf kinase-B inhibitor protein (RKIP) and BTB and CNC homology 1 (BACH1) are two proteins reported to influence EMT. In breast cancer, they act antagonistically, but the exact nature of their roles in mediating EMT and associated other axes of plasticity remains unclear. Here, analysing transcriptomic data, we reveal their antagonistic trends in a pan-cancer manner, in terms of association with EMT, metabolic reprogramming and immune evasion via PD-L1. Next, we developed and simulated a mechanism-based gene regulatory network that captures how RKIP and BACH1 engage in feedback loops with drivers of EMT and stemness. We found that RKIP and BACH1 belong to two separate "teams" of players - while BACH1 belonged to the one that drove pro-EMT, stem-like and therapy-resistant cell-states, RKIP is a member of a team that enables pro-epithelial, less stem-like and therapy-sensitive phenotypes. Finally, we observed that low RKIP levels and concomitant upregulated BACH1 levels associated with worse clinical outcomes in many cancer types. Together, our systems-level analysis indicates that the emergent dynamics of underlying regulatory network underlie the antagonistic patterns of RKIP and BACH1 with various axes of cancer cell plasticity, as well as with patient survival data.

systems biology↗

bioRxiv2023

Synthetic gene circuits combining CRISPR interference and CRISPR activation in E. coli: importance of equal guide RNA binding affinities to avoid context-dependent effects

Gene expression control based on CRISPR has emerged as a powerful approach for constructing synthetic gene circuits. While the use of CRISPR interference (CRISPRi) is already well-established in prokaryotic circuits, CRISPR activation (CRISPRa) is less mature and combination of the two in the same circuits is only just emerging. Here, we report that combining CRISPRi with SoxS-based CRISPRa in Escherichia coli can lead to context-dependent effects due to different affinities in the formation of CRISPRa and CRISPRi complexes, resulting in loss of predictable behaviour. We show that this effect can be avoided by using the same scaffold guide RNA structure for both complexes.

synthetic biology↗

bioRxiv2023

GPX4-VIM equates a proliferating DTP state in TNBC subtypes with converged vulnerabilities to autophagy and glutathione inhibition.

Frequent metastatic relapses in Triple-Negative Breast Cancer (TNBC) patients with residual disease is a clinical challenge, largely due to tumor heterogeneity and absence of strategies that target proliferating chemo-tolerant cells. Here, we longitudinally modeled cellular state transitions from dormant drug-tolerant persister (DTP) into proliferating drug-tolerant persister (PDTP) in cells representing all TNBC subtypes. Combining subcellular imaging with phenotypic and biochemical assays, we identified distinct and converged spectrums of alterations in TNBC-PDTPs. We show that PDTPs retain acquired resistance with increased invasion potential. Moreover, Basal-Like DTPs enter into a non-reversible mesenchymal state while luminal androgen receptor-positive gain partial-Epithelial-to-Mesenchymal Transition (EMT) with vimentin upregulation. PDTP state dwells on high autophagy with reduced glutathione and GPX4 levels, rendering it vulnerable to autophagy suppression and ferroptosis. Interestingly, we find that GPX4 negatively regulates EMT and autophagy in TNBC, and an inverse correlation of GPX4-VIM expression along with autophagy genes predicts survival in TNBC patients undergoing chemotherapy.

cancer biology↗

bioRxiv2023

Melanocytes Exhibit Distinct Cell States Governed by A Gene Regulatory Network Under Stochastic Influence

Melanocytes serve as a protector of the skin against external stressors such as ultraviolet radiations. While melanocytes remain functional for nearly the entire lifespan of an individual, how they respond efficiently and survive such insults remain elusive. Here, we show the co-existence of multiple distinct states of normal human epidermal melanocytes (NHEMs). Using a progressive pigmentation model, we show that stochasticity in gene expression can lead to the co-existence of multiple melanocyte states. Using active enhancers and gene expression footprint, we identified state-specific transcription factors and constructed a gene regulatory network (GRN). The GRN couples pigmentation and cell cycle regulators and explains the co-existence and transitions of the melanocyte states. Finally, we show that NHEMs respond to external cues by altering the cell state dynamics. These results demonstrate that stochasticity in gene expression followed by epigenetic modification leads to the co-existence of multiple melanocyte states enabling an efficient response to environmental cues.

cell biology↗

bioRxiv2023

Cell-autonomous BMP signalling plays a key role in the maintenance of tumour cell EMT and migration programs in human ovarian carcinoma

Epithelial-mesenchymal transition (EMT) plays a key role in tumour initiation, metastasis and resistance to therapy. Cells undergoing EMT, assume multiple semi-stable transitional states along the epithelial-mesenchymal axis that necessitates tight regulatory cascades. Although more is known about pathways involved in the initial induction of EMT, cascades that mediate/maintain the transitional states and/or the final mesenchymal phenotype are yet to be elucidated. In this study, we have assessed the role of bone morphogenic protein (BMP) signalling pathway in the regulation of cancer cell EMT and migration. Mining existing data from ovarian carcinomas, we defined the BMP pathway among the key pathways enriched in tumours with elevated EMT signatures, with a significant correlation in the expression of EMT markers with BMP ligands and downstream targets of the BMP pathway. Functional inhibition of the BMP pathway in ovarian cancer cells by a small molecule inhibitor, DMH1, resulted in impaired migration and depressed EMT signatures in both in vitro and in vivo models. Finally, ectopic induction of EMT in ovarian cancer cells through activation of an independent pathway, TNF, resulted in the selective induction of Smad-mediated BMP pathway suggesting a role in maintenance of EMT, secondary to EMT induction.

cancer biology↗

bioRxiv2023

Dual role of CASP8AP2/FLASH in regulating epithelial-to-mesenchymal (EMT) plasticity

Metastasis consists of sequential steps initiated by cancer cells invading from the primary tumor site into neighboring tissues, followed by entry into the circulatory system and completed by extravasation and growth in distal organs where secondary tumors are formed. Circulating tumor cells, thus, encounter and adapt to multiple environmental changes during their transition from the primary to the secondary tumor sites. Epithelial-to-mesenchymal transition (EMT) is a developmental program that consists of loss of epithelial features concomitant with acquisition of mesenchymal features. Activation of EMT in cancer facilitates acquisition of aggressive traits and cancer invasion. EMT plasticity (EMP), the dynamic transition between multiple hybrid states in which cancer cells display both epithelial and mesenchymal phenotypes, confers survival advantages for cancer cells in the constantly changing environment. Therefore, understanding the molecular mechanisms regulating intermediate phenotypic states along the E-M spectrum is critical. Core EMT transcription factors (EMT-TFs), ZEB, SNAI and TWIST families, play an important role in EMT and its plasticity. In the present study we characterize FLASH as a regulator of EMP and multiple EMT-TFs. We demonstrate that loss of FLASH gives rise to a hybrid E/M phenotype with high epithelial scores even in the presence of TGF{beta}, as determined by computational methods using expression of predetermined sets of epithelial and mesenchymal genes. We demonstrate that FLASH is regulating expression of multiple cell junction proteins with an established role in cancer progression and that its role in EMT is independent of its histone biogenesis role. Further, we show that FLASH expression in cancer lines is inversely correlated with the epithelial score, consistent with its function as a repressor of the epithelial phenotype. Nonetheless, activation of a distinct set of mesenchymal markers concomitant with epithelial markers reveals the complex role of FLASH in EMT and indicates that intermediate E/M states could arise from opposing control by FLASH on different families of EMT-TFs.

cancer biology↗

bioRxiv2023

Androgen Receptor driven gene score identifies tumors with Epithelial to Mesenchymal Transition features in triple negative breast cancer

BackgroundAndrogen receptor (AR) is considered marker associated with better prognosis within hormone receptor positive tumors. Its role in triple negative tumors however is controversial showing both better and worse prognosis and different methods are used for identification of AR driven tumors. Conflicting results could be due to intrinsic molecular differences or scoring method for AR positivity. We attempted to develop an AR driven gene score and examined its utility in subtypes of breast cancer (BC). MethodsA bioinformatic pipeline was constructed and applied on publicly available microarray data sets obtained from AR positive BC cell lines treated with dihydrotestosterone (DHT). Expression levels of genes identified through the pipeline along with set of epithelial mesenchymal transition (EMT) markers, proliferation associated genes and enzymes involved in intracrinal androgen metabolism was evaluated in a cohort of Indian Breast cancer patients. Tumors were divided into AR high and low based on the gene score and association with clinical parameters, circulating androgens, disease free survival, proliferation and EMT markers were examined, all results were further validated in external public datasets. ResultsAR driven gene score was calculated as average expression of the 6 genes selected through bioinformatic analysis. 53% (133/249) tumors were classified as AR high by the gene score and had significantly better clinical parameters such as higher age, smaller tumor size, lower grade and lower proliferation. Tumors with high AR driven gene score had significantly better disease-free survival (mean survival time of 86.13 vs 72.69 months, log rank p=0.032) when compared to the AR low tumors. A subset analysis within TNBC (N=66) showed 36% (24/66) were AR high and had significantly higher expression of EMT markers (p=0.024). Though circulating levels of total testosterone was not different between the groups, intratumoral levels of 5 alfa reductase (SRD5A1) was significantly high in tumors with high AR driven score. ConclusionRole of AR in breast cancer is debatable and difficult to decipher with protein detection alone. Our results support the context dependent function of AR in driving better prognosis, while identifying its role in driving EMT within TNBC tumors.

cancer biology↗

bioRxiv2023

Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks

Biological networks driving cell-fate decisions involve complex interactions, but they often give rise to only a few phenotypes, thus exhibiting low-dimensional dynamics. The network design principles that govern such cell-fate canalization remain unclear. Here, we investigate networks across diverse biological contexts- Epithelial-Mesenchymal Transition, Small Cell Lung Cancer, and Gonadal cell-fate determination - to reveal that the presence of two mutually antagonistic, well-coordinated teams of nodes leads to low-dimensional phenotypic space such that the first principal component (PC1) axis can capture most of the variance. Further analysis of artificial team-based networks and random counterparts of biological networks reveals that the principal component decomposition is determined by the team strength within these networks, demonstrating how the underlying network structure governs PC1 variance. The presence of low dimensionality in corresponding transcriptomic data confirms the applicability of our observations. We propose that team-based topology in biological networks are critical for generating a cell-fate canalization landscape.

systems biology↗

bioRxiv2023

Collective heterogeneity of mitochondrial potential in contact inhibition of proliferation

In the epithelium, cell density and cell proliferation are closely connected to each other through contact inhibition of proliferation (CIP). Depending on cell density, CIP proceeds through three distinct stages, namely the free-growing stage at low density, the pre-epithelial transition stage at medium density, and the post-epithelial transition stage at high density. Previous studies have elucidated how cell morphology, motion, and mechanics vary in these stages. However, it remains unknown whether cellular metabolism also has a density-dependent behavior. By measuring the mitochondrial membrane potential at different cell densities, here we reveal a heterogeneous landscape of metabolism in the epithelium, which appears qualitatively distinct in three stages of CIP. Moreover, it did not follow the trend of other CIP-associated parameters, which increase or decrease monotonically with increasing cell density. Importantly, epithelial cells established a collective heterogeneity in mitochondrial potential exclusively in the pre-epithelial transition stage, where the multicellular clusters of high and low-potential cells emerged. However, in the post-epithelial transition stage, the potential field became relatively homogeneous. The collective metabolic heterogeneity in the pre-epithelial transition stage was independent of the mitochondrial content and spatially correlated with the local cell density. Next, to study the underlying dynamics, we constructed a system-biological model, which predicted the role of cell proliferation in metabolic potential towards establishing collective heterogeneity. Further experiments revealed that the metabolic pattern indeed spatially correlated with the proliferative capacity of cells, as measured by the nuclear localization of a pro-proliferation protein, YAP. Finally, experiments perturbing the actomyosin contractility revealed that while metabolic heterogeneity was maintained in absence of actomyosin contractility, its ab initio emergence depended on the latter. Taken together, our results revealed a density-dependent collective heterogeneity in the metabolic field of a pre-epitheli al transition stage epithelial monolayer, which may have significant implications for epithelial form and function. STATEMENT OF SIGNIFICANCEEpithelial contact inhibition of proliferation (CIP) plays a key role in tissue homeostasis, morphogenesis, and development. The biochemical changes in cells during different stages of CIP are not as well-documented as the biophysical changes. We unveil a heterogeneous landscape of metabolism which appears distinct in different stages of CIP. Importantly, in the pre-epithelial transition stage, the epithelial cells establish a collective metabolic heterogeneity wherein multicellular clusters of high and low-potential cells emerge, despite the uniform genetic and nutrient conditions for the cells. The collective heterogeneity is correlated to the local fluctuations in geometrical parameters and the proliferative capacity of cells. Finally, we demonstrate the role of cell mechanics in the establishment of collective heterogeneity.

biophysics↗

bioRxiv2023

Population Dynamics of EMT Elucidates the Timing and Distribution of Phenotypic Intra-tumoral Heterogeneity

The Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of cancer metastasis and morbidity. EMT is a non-binary process, and cells can be stably arrested en route to EMT in an intermediate hybrid state associated with enhanced tumor aggressiveness and worse patient outcomes. Understanding EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing data that enable in-depth analyses of EMT at the single-cell resolution, current inferential approaches are limited to bulk microarray data. There is thus a great need for computational frameworks to systematically infer and predict the timing and distribution of EMT-related states at single-cell resolution. Here, we develop a computational framework for reliable inference and prediction of EMT-related trajectories from single-cell RNA sequencing data. Our model can be utilized across a variety of applications to predict the timing and distribution of EMT from single-cell sequencing data. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/523978v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@1c56970org.highwire.dtl.DTLVardef@18d7371org.highwire.dtl.DTLVardef@19612f9org.highwire.dtl.DTLVardef@1b7cf96_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA fully stochastic model elucidates the population dynamics of EMT C_LIO_LIA data-driven pipeline is introduced to track EMT trajectories from single-cell RNA sequencing C_LIO_LICell cycle scoring reveals cell line-dependent patterns of EMT Induction C_LI

bioengineering↗

bioRxiv2023

Dynamical modelling of proliferative-invasive plasticity and IFN-gamma signaling in melanoma reveals mechanisms of PD-L1 expression heterogeneity

Phenotypic heterogeneity of melanoma cells contributes to drug tolerance, increased metastasis, and immune evasion in patients with progressive disease. Diverse mechanisms have been individually reported to shape extensive intra- and inter-tumoral phenotypic heterogeneity, such as IFN{gamma} signaling and proliferative to invasive transition, but how their crosstalk impacts tumor progression remains largely elusive. Here, we integrate dynamical systems modeling with transcriptomic data analysis at bulk and single-cell levels to investigate underlying mechanisms behind phenotypic heterogeneity in melanoma and its impact on adaptation to targeted therapy and immune checkpoint inhibitors. We construct a minimal core regulatory network involving transcription factors implicated in this process and identify the multiple "attractors" in the phenotypic landscape enabled by this network. Our model predictions about synergistic control of PD-L1 by IFN{gamma} signaling and proliferative to invasive transition were validated experimentally in three melanoma cell lines - MALME3, SK-MEL-5 and A375. We demonstrate that the emergent dynamics of our regulatory network comprising MITF, SOX10, SOX9, JUN and ZEB1 can recapitulate experimental observations about the co-existence of diverse phenotypes (proliferative, neural crest-like, invasive) and reversible cell-state transitions among them, including in response to targeted therapy and immune checkpoint inhibitors. These phenotypes have varied levels of PD-L1, driving heterogeneity in immune-suppression. This heterogeneity in PD-L1 can be aggravated by combinatorial dynamics of these regulators with IFN{gamma} signaling. Our model predictions about changes in proliferative to invasive transition and PD-L1 levels as melanoma cells evade targeted therapy and immune checkpoint inhibitors were validated in multiple data sets from in vitro and in vivo experiments. Our calibrated dynamical model offers a platform to test combinatorial therapies and provide rational avenues for the treatment of metastatic melanoma. This improved understanding of crosstalk among PD-L1 expression, proliferative to invasive transition and IFN{gamma} signaling can be leveraged to improve the clinical management of therapy-resistant and metastatic melanoma.

cancer biology↗

bioRxiv2022

Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer

Advanced prostate cancer patients initially respond to hormone therapy, be it in the form of androgen deprivation therapy or second-generation hormone therapies, such as abiraterone acetate or enzalutamide. However, most men with prostate cancer eventually develop hormone therapy resistance. This resistance emerges in several ways, such as through genetic mutations, epigenetic mechanisms, or through non-genetic pathways, such as lineage plasticity along epithelial-mesenchymal or neuroendocrine-like axes. These mechanisms of hormone therapy resistance often co-exist within a single patients tumor and can overlap within a single cell. There exists a growing need to better understand how phenotypic heterogeneity and plasticity results from emergent dynamics of the regulatory networks governing androgen independence. Here, we investigated the dynamics of a regulatory network connecting the drivers of androgen receptor (AR) splice variant-mediated androgen independence and those of epithelial-mesenchymal transition. Model simulations for this network revealed four possible phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR) and mesenchymal-sensitive (MS), with the latter phenotype occurring rarely. We observed that well-coordinated "teams" of regulators working antagonistically within the network enable these phenotypes. These model predictions are supported by multiple transcriptomic datasets both at single-cell and bulk levels, including in vitro EMT induction models and clinical samples. Further, our simulations reveal spontaneous stochastic switching between the ES and MR states. Addition of the immune checkpoint molecule, PD-L1, to the network was able to capture the interactions between AR, PD-L1, and the mesenchymal marker SNAIL, which was also confirmed through quantitative experiments. This systems-level understanding of the driver of androgen independence and EMT could aid in understanding non-genetic transitions and progression of such cancers and help in identifying novel therapeutic strategies or targets.

cancer biology↗

bioRxiv2022

A synthetic lethal screen for Snail-induced enzalutamide resistance identifies JAK/STAT signaling as a therapeutic vulnerability in prostate cancer

Despite substantial improvements in the treatment landscape of prostate cancer, the evolution of hormone therapy-resistant and metastatic prostate cancer remains a major cause of cancer-related death globally. The mainstay of treatment for advanced prostate cancer is targeting of androgen receptor signaling, including androgen deprivation therapy plus second-generation androgen receptor blockade (e.g., enzalutamide, apalutamide, darolutamide), and/or androgen synthesis inhibition (abiraterone). While these agents have significantly prolonged the lives of patients with advanced prostate cancer, the evolution of resistance to these treatments in nearly universal. This therapy resistance is mediated by diverse mechanisms, including both androgen receptor-dependent mechanisms, such as androgen receptor mutations, amplifications, alternatively spliced isoforms, and structural rearrangements, as well as non-androgen receptor-mediated mechanisms, such as lineage plasticity toward neuroendocrine-like or epithelial-mesenchymal transition (EMT)-like lineages. Our prior work identified the EMT transcriptional regulator Snail as critical to hormonal therapy resistance and commonly detected in human metastatic prostate cancer. In the current study, we sought to interrogate the actionable landscape of EMT-mediated hormone therapy-resistant prostate cancer to identify synthetic lethality and collateral sensitivity approaches to treating this aggressive disease state. Using a combination of high-throughput drug screens and multi-parameter phenotyping by confluence imaging, ATP production, and phenotypic plasticity reporters of EMT, we identified candidate synthetic lethalities to Snail-mediated EMT in prostate cancer. These analyses identified multiple actionable targets, such as XPO1, PI3K/mTOR, aurora kinases, c-MET, polo-like kinases, and JAK/STAT as synthetic lethalities in Snail+ prostate cancer. We validated these targets in a subsequent validation screen in an LNCaP-derived model of resistance to sequential androgen deprivation and enzalutamide. This follow-up screen provided validation of inhibitors of JAK/STAT and PI3K/mTOR as therapeutic vulnerabilities for Snail+ and enzalutamide-resistant prostate cancer.

cancer biology↗