Biology subjects

Jolly, M. K.

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

At least 145 records · Page 8Linked to original sources

bioRxiv2020

NFATc acts as a non-canonical phenotypic stability factor for a hybrid epithelial/mesenchymal phenotype

Metastasis remains the cause of over 90% of cancer-related deaths. Cells undergoing metastasis use phenotypic plasticity to adapt to their changing environmental conditions and avoid therapy and immune response. Reversible transitions between epithelial and mesenchymal phenotypes - Epithelial-Mesenchymal Transition (EMT) and its reverse Mesenchymal-Epithelial Transition (MET) - form a key axis of phenotypic plasticity during metastasis and therapy resistance. Recent studies have shown that the cells undergoing EMT/MET can attain one or more hybrid epithelial/mesenchymal (E/M) phenotypes, the process of which is termed as partial EMT/MET. Cells in hybrid E/M phenotype(s) can be more aggressive than those in either epithelial or mesenchymal state. Thus, it is crucial to identify the factors and regulatory networks enabling such hybrid E/M phenotypes. Here, employing an integrated computational-experimental approach, we show that the transcription factor NFATc can inhibit the process of complete EMT, thus stabilizing the hybrid E/M phenotype. It increases the range of parameters enabling the existence of a hybrid E/M phenotype, thus behaving as a phenotypic stability factor (PSF). However, unlike previously identified PSFs, it does not increase the mean residence time of the cells in hybrid E/M phenotypes, as shown by stochastic simulations; rather it enables the co-existence of epithelial, mesenchymal and hybrid E/M phenotypes and transitions among them. Clinical data suggests the effect of NFATc on patient survival in a tissue-specific or context-dependent manner. Together, our results indicate that NFATc behaves as a non-canonical phenotypic stability factor for a hybrid E/M phenotype.

cancer biology↗

bioRxiv2020

Interactive dynamics of reaction-diffusion and adhesion predict diverse invasion strategies of cancer cells in matrix-like microenvironments

The metastasis of malignant epithelial tumors begins with the egress of transformed cells from the confines of their basement membrane to their surrounding collagenous stroma. Invasion can be morphologically diverse, ranging from dispersed mesenchymal cells to multicellular collectives. When breast cancer cells are cultured within basement membrane-like matrix (BM), or Type 1 collagen, or a combination of both, they exhibit collective-, dispersed mesenchymal-, and hybrid collective-dispersed (multiscale) invasion, respectively. In this paper, we asked how distinct these invasive modes are with respect to the cellular and microenvironmental cues that drive them. A rigorous computational exploration of invasion was performed within an experimentally motivated Cellular Potts-based modeling environment. The model comprises of adhesive interactions between cancer cells, BM- and collagen-like extracellular matrix (ECM), and reaction-diffusion-based remodeling of ECM. The model outputs were parameters cognate to dispersed- and collective- invasion. Input sweeps gave rise to a spatial output distribution that consisted of dispersed-, collective- and multiscale- invasion. K-means clustering of the output distribution followed by silhouette analysis revealed three optimal clusters: one signifying indolent invasion and two representing multiscale invasions, which we call collective-multiscale (CMI), and dispersed multiscale invasion (DMI), respectively. Constructing input-output mapped phenotypic spaces suggested that adhesion to BM- and collagen- matrix specify CMI and DMI respectively. Parameter perturbations confirmed these associations and revealed how the cellular phenotype may transition between the three states. Our systems-level analysis provides quantitative insights into how the diversity in matrix microenvironments may steer invasion into distinct phenotypic modes during metastasis.

cancer biology↗

bioRxiv2020

Phenotypic switching and adaptive strategies of cancer cells in response to stress: insights from live cell imaging and mathematical modeling

A major challenge in cancer therapy is drug resistance, which is typically attributed to acquired mutations and tumor heterogeneity. However, emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance, although, the details of such mechanisms are poorly understood. Here, by combining real time cellular growth data with mathematical modeling, we showed that the cisplatin-sensitive and tolerant lung cancer cells when co-cultured in cisplatin-free and cisplatin-treated environments, exhibit drastically different group strategies in response to environmental changes. While tolerant cells exhibited a persister-like behaviour and were attenuated by sensitive cells, sensitive cells learned to evade chemotherapy from tolerant cells when co-cultured. Further, tolerant cells could switch phenotypes to become sensitive, although high cisplatin concentrations suppressed this switching. Finally, switching cisplatin administration from continuous to intermittent suppressed the emergence of tolerant cells, suggesting that intermittent rather than continuous chemotherapy may result in better outcomes in lung cancer.

cancer biology↗

bioRxiv2020

Emergent properties of the HNF4α-PPARγ may drive consequent phenotypic plasticity in NAFLD

Non-Alcoholic Fatty Liver Disease (NAFLD) is the most common form of chronic liver disease in adults and children. It is characterized by excessive accumulation of lipids in the hepatocytes of patients without any excess alcohol intake. With a global presence of 24% and limited therapeutic options, the disease burden of NAFLD is increasing. Thus, it becomes imperative to attempt to understand the dynamics of disease progression at a systems-level. Here, we decode the emergent dynamics of underlying gene regulatory networks that have been identified to drive the initiation and progression of NAFLD. We have developed a mathematical model to elucidate the dynamics of the HNF4-PPAR{gamma} gene regulatory network. Our simulations reveal that this network can enable multiple co-existing phenotypes under certain biological conditions: an adipocyte, a hepatocyte, and a "hybrid" adipocyte-like state of the hepatocyte. These phenotypes may also switch among each other, thus enabling phenotypic plasticity and consequently leading to simultaneous deregulation of the levels of molecules that maintain a hepatic identity and/or facilitate a partial or complete acquisition of adipocytic traits. These predicted trends are supported by the analysis of clinical data, further substantiating the putative role of phenotypic plasticity in driving NAFLD. Our results unravel how the emergent dynamics of underlying regulatory networks can promote phenotypic plasticity, thereby propelling the clinically observed changes in gene expression often associated with NAFLD.

systems biology↗

bioRxiv2020

Comparative study of transcriptomics-based scoring metrics for the epithelial-hybrid-mesenchymal spectrum

The Epithelial-mesenchymal transition (EMT) is a cellular process implicated in embryonic development, wound healing, and pathological conditions such as cancer metastasis and fibrosis. Cancer cells undergoing EMT exhibit enhanced aggressive behavior characterized by drug resistance, tumor-initiation potential, and the ability to evade immune system. Recent in silico, in vitro, and in vivo evidence indicates that EMT is not an all-or-none process; instead, cells stably acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes which often can be more aggressive than purely epithelial or mesenchymal cell populations. Thus, the EMT status of cancer cells can prove to be a critical estimate of patient prognosis. Recent attempts have employed different transcriptomics signatures to quantify EMT status in cell lines and patient tumors. However, a comprehensive comparison of these methods, including their accuracy in identifying cells in the hybrid E/M phenotype(s), is lacking. Here, we compare three distinct metrics that score EMT on a continuum, based on the transcriptomics signature of individual samples. Our results demonstrate that these methods exhibit good concordance among themselves in quantifying the extent of EMT in a given sample. Moreover, scoring EMT using any of the three methods discerned that cells undergo varying extents of EMT across tumor types. Separately, our analysis also identified tumor types with maximum variability in terms of EMT and associated an enrichment of hybrid E/M signatures in these samples. Moreover, we also found that the multinomial logistic regression (MLR) based metric was capable of distinguishing between pure individual hybrid E/M vs. mixtures of epithelial (E) and mesenchymal (M) cells. Our results, thus, suggest that while any of the three methods can indicate a generic trend in the EMT status of a given cell, the MLR method has two additional advantages: a) it uses a small number of predictors to calculate the EMT score, and b) it can predict from the transcriptomic signature of a population whether it is comprised of pure hybrid E/M cells at the single-cell level or is instead an ensemble of E and M cell subpopulations.

cancer biology↗

bioRxiv2019

Integrative analysis and machine learning based characterization of single circulating tumor cells

We collated publicly available single-cell expression profiles of circulating tumor cells (CTCs) and showed that CTCs across cancers lie on a near-perfect continuum of epithelial to mesenchymal (EMT) transition. Integrative analysis of CTC transcriptomes also highlighted the inverse gene expression pattern between PD-L1 and MHC, which is implicated in cancer immunotherapy. We used the CTCs expression profiles in tandem with publicly available peripheral blood mononuclear cell (PBMC) transcriptomes to train a classifier that accurately recognizes CTCs of diverse phenotype. Further, we used this classifier to validate circulating breast tumor cells captured using a newly developed microfluidic systems for label-free enrichment of CTCs.

genomics↗

bioRxiv2019

Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology based approach

Metastasis is the cause of over 90% of cancer-related deaths. Cancer cells undergoing metastasis can switch dynamically between different phenotypes, enabling them to adapt to harsh challenges such as overcoming anoikis and evading immune response. This ability, known as phenotypic plasticity, is crucial for the survival of cancer cells during metastasis, as well as acquiring therapy resistance. Various biochemical networks have been identified to contribute to phenotypic plasticity, but how plasticity emerges from the dynamics of these networks remains elusive. Here, we investigated the dynamics of various regulatory networks implicated in Epithelial-Mesenchymal Plasticity (EMP) - an important arm of phenotypic plasticity - through two different mathematical modelling frameworks: a discrete, parameter-independent framework (Boolean) and a continuous, parameter-agnostic modelling framework (RACIPE). Results from either framework in terms of phenotypic distributions obtained from a given EMP network are qualitatively similar and suggest that these networks are multi-stable and can give rise to phenotypic plasticity. Neither method requires specific kinetic parameters, thus our results emphasize that EMP can emerge through these networks over a wide range of parameter sets, elucidating the importance of network topology in enabling phenotypic plasticity. Furthermore, we show that the ability to exhibit phenotypic plasticity correlates positively with the number of positive feedback loops in a given network. These results pave a way towards an unorthodox network topology-based approach to identify crucial links in a given EMP network that can reduce phenotypic plasticity and possibly inhibit metastasis - by reducing the number of positive feedback loops.

systems biology↗

bioRxiv2019

A Non-genetic Mechanism for Chemoresistance in Lung Cancer: The Role of Integrin β4/Paxillin Axis

Tumor heterogeneity and cisplatin resistance are a major cause of tumor relapse and poor survival. Here we show that in lung adenocarcinoma (LUAD), paxillin (PXN) and integrin beta 4 (ITGB4) are associated with tumor progression, and cisplatin resistance. Silencing PXN and ITGB4 render cisplatin tolerant cells sensitive, and immunologically neutralizing ITGB4 improves sensitivity. The N-terminal half of PXN is intrinsically disordered and interacts with ITGB4 to regulate expression of USP1 and VDAC1 which are required for maintaining genomic stability and mitochondrial function in LUAD. By virtual screening an FDA-approved compound library, we identified compounds that interact with PXN in silico and attenuate cisplatin resistance in LUAD cells. RNAseq analysis identified a double negative feedback loop between ITGB4 and microRNA miR-1-3p, suggesting that bistability could lead to stochastic switching between cisplatin-sensitive and resistant states in these cells. The data highlight an alternate, non-genetic, mechanism underlying chemoresistance in lung cancer.

cancer biology↗

bioRxiv2019

Targeting the Id1-Kif11-Aurka axis in triple negative breast cancer using combination therapy

Evidence points to breast cancer following a hierarchical model, with Cancer Stem Cells (CSCs) driving critical phenotypes of the bulk tumor. Chemoresistant CSCs are not an abstract concept but have clinical consequences as they drive relapse and ultimately lead to mortality in patients, making it imperative to understand how these subpopulations of cells survive. Our previous work (1-2) has demonstrated that the bHLH transcription factor, Inhibitor of Differentiation 1 (Id1) and its closely related family member Id3, have an important role in maintaining the CSC phenotype in the Triple Negative breast cancer (TNBC) subtype. A genetic screen conducted to further elucidate the molecular mechanism underlying the Id (Id1/3) mediated CSC phenotypes in TNBC revealed critical cell cycle genes such as Kif11 and Aurka as putative Id targets. We take this work forward by investigating how alteration in Kif11 and Aurka via Id proteins promotes the CSC phenotype in TNBC. Cells lacking Id are poised in a state of G0/G1 arrest from which they can re-enter the cell cycle. Intriguingly, depletion of Kif11 and Aurka independently did not phenocopy the G0/G1 arrest observed in Id knockdown (Id KD) cells. We have further explored the hypothesis that we can deplete the chemo resistant Id expressing CSC population by combining chemotherapy with targeted therapy using existing small molecule inhibitors (against Id target Kif11) to more effectively debulk the entire tumor. This work opens up exciting new possibilities of targeting Id targets like Kif11, in the TNBC subtype which is currently refractory to chemotherapy.

cancer biology↗

bioRxiv2019

Phenotypic Switching of Naïve T cells to Immune-suppressive Treg-like Cells by Mutant KRAS

Oncogenic (mutant) Ras protein Kirsten rat sarcoma viral oncogene homolog (KRAS) promotes uncontrolled proliferation, altered metabolism, and loss of genome integrity in a cell-intrinsic manner. Here, we demonstrate that CD4+ T cells when incubated with tumor-derived exosomes from mutant (MT) KRAS non-small cell lung cancer (NSCLC) cells, patient sera, or a mouse xenograft model, induce phenotypic conversion to FOXP3+ Treg-like cells that are immune-suppressive. Furthermore, transfecting T cells with MT KRAS cDNA alone induced phenotypic switching and mathematical modeling supported this conclusion. Single-cell sequencing identified the interferon pathway as the mechanism underlying the phenotypic switch. These observations highlight a novel cytokine-independent, cell-extrinsic role for KRAS in T cell phenotypic switching. Thus, targeting this new class of Tregs represents a unique therapeutic approach for NSCLC. Since KRAS is the most frequently mutated oncogene in a wide variety of cancers, the findings of this investigation are likely to be of broad interest and have a large scientific impact.

cancer biology↗

bioRxiv2019

Feedback loops involving AMPK, ERK and TFEB in matrix detachment leads to non-genetic heterogeneity

Cancer cells metastasize by evading apoptosis induced due to the detachment from the extracellular matrix. Deciphering the adaptive strategies employed by cancer cells in matrix-deprived condition can help design novel therapeutic strategies to tackle metastasis. Here, we provide evidence for non-genetic heterogeneity in matrix-detached cells enabled by feedback loop among AMPK, ERK and TFEB that determines autophagy maturation and cell survival. The subpopulation of matrix-detached cells with pAMPKlow/pERKhigh/TFEBlow state show autophagy maturation arrest and elevated cell death. Conversely, pAMPKhigh/pERKlow/ TFEBhigh cells show high autophagy maturation and better cell survival. We show that AMPK inhibits ERK activity in suspension; ERK negatively regulates TFEB which promotes autophagy maturation and re-enforces AMPK. Inhibition of ERK promotes autophagy maturation, cell survival and metastasis in vivo, while AMPK inhibition (and TFEB depletion) renders the population homogeneous by depleting the pAMPKhigh/pERKlow/TFEBhigh subpopulation, driving detachment-induced death. Such non-genetic heterogeneity is further deciphered by mathematical modelling and RNA-sequencing data of circulating tumor cells (CTCs) isolated from breast cancer patients. Altogether, our work unravels a contextual feedback loop involving two kinases and a transcription factor that helps a subpopulation to evade cell death in matrix-deprived condition. Disrupting such feedback loops may offer improved therapeutic efficacy and a novel approach to constrain metastasis. Significance of the StudyAttachment to the extracellular matrix is pivotal for the growth and survival of normal epithelial cells. In contrast, cancer cells acquest the ability to survive matrix-deprivation and cause cancer spread, or metastasis, which is a leading cause of cancer-related deaths. Non-genetic heterogeneity within cancer cell populations is increasingly being recognized as a major cause of treatment failure. However, the implications of such heterogeneity in the survival of matrix-detached cancer cells remain poorly understood. In this study, we demonstrate feedback loops involving kinases and transcription factor to maintain non-genetic heterogeneous population, where population harbouring pAMPKhigh/pERKlow/TFEBhigh status shows survival advantage. Targeting such feedback loops that generate non-genetic heterogeneity can open newer therapeutic means to restrict cancer spread.

cancer biology↗

bioRxiv2019

Anticipating critical transitions in epithelial-hybrid-mesenchymal cell-fate determination

In the vicinity of a tipping point, critical transitions occur when small changes in an input condition causes sudden, large and often irreversible changes in the state of a system. Many natural systems ranging from ecosystems to molecular biosystems are known to exhibit critical transitions in their response to stochastic perturbations. In diseases, an early prediction of upcoming critical transitions from a healthy to a disease state by using early warning signals is of prime interest due to potential application in forecasting disease onset. Here, we analyze cell-fate transitions between different phenotypes (epithelial, hybrid epithelial/mesenchymal (E/M) and mesenchymal states) that are implicated in cancer metastasis and chemoresistance. These transitions are mediated by a mutually inhibitory feedback loop microRNA-200/ZEB driven by the levels of transcription factor SNAIL. We find that the proximity to tipping points enabling these transitions among different phenotypes can be captured by critical slowing down based early warning signals, calculated from the trajectory of ZEB mRNA level. Further, the basin stability analysis reveals the unexpectedly large basin of attraction for a hybrid E/M phenotype. Finally, we identified mechanisms that can potentially elude the transition to a hybrid E/M phenotype. Overall, our results unravel the early warning signals that can be used to anticipate upcoming epithelial-hybrid-mesenchymal transitions. With the emerging evidence about the hybrid E/M phenotype being a key driver of metastasis, drug resistance, and tumor relapse; our results suggest ways to potentially evade these transitions, reducing the fitness of cancer cells and restricting tumor aggressiveness.\n\nSignificance StatementEpithelial-hybrid-mesenchymal transitions play critical roles in cancer metastasis, drug resistance, and tumor relapse. Recent studies have proposed that cells in a hybrid epithelial/mesenchymal phenotype may be more aggressive than those on either end of the spectrum. However, no biomarker to predict upcoming transitions has been identified. Here, we show that critical slowing down based early warning signals can detect sudden transitions among epithelial, hybrid E/M, and mesenchymal phenotypes. Importantly, our results highlight how stable a hybrid E/M phenotype can be, and how can a transition to this state be avoided. Thus, our study provides valuable insights into restricting cellular plasticity en route metastasis.

systems biology↗

bioRxiv2019

A possible role for epigenetic feedback regulation in the dynamics of the Epithelial-Mesenchymal Transition (EMT)

The epithelial-mesenchymal transition (EMT) often plays a critical role in cancer metastasis and chemoresistance, and decoding its dynamics is crucial to design effective therapeutics. EMT is regulated at multiple levels transcriptional, translational, protein stability, and epigenetics; the mechanisms by which epigenetic regulation can alter the dynamics of EMT remain elusive. Here, to identify the possible effects of epigenetic regulation in EMT, we incorporate a feedback term in our previously proposed model of EMT regulation of the miR 200/ZEB/miR 34/SNAIL circuit. This epigenetic feedback that stabilizes long-term transcriptional activity can alter the relative stability and distribution of states in a given cell population, particularly when incorporated in the inhibitory effect on miR 200 from ZEB. This feedback can stabilize the mesenchymal state, thus making transitions out of that state difficult. Conversely, epigenetic regulation of the self activation of ZEB has only minor effects. Our model predicts that this effect could be seen in experiments, when epithelial cells are treated with an external EMT inducing signal for a sufficiently long period of time and then allowed to recover. Our preliminary experimental data indeed shows that a prolonged TGF beta; exposure gives rise to increasing difficult reversion back to the epithelial state. Thus, this integrated theoretical experimental approach yields insights into how an epigenetic feedback may alter the dynamics of EMT.

biophysics↗

bioRxiv2019

Pericytes enable effective angiogenesis in the presence of pro inflammatory signals

Angiogenesis frequently occurs in the context of acute or persistent inflammation. The complex interplay of pro-inflammatory and pro-angiogenic cues is only partially understood. Using a new experimental model permitting exposure of developing blood vessel sprouts to multiple combinations of diverse biochemical stimuli and juxtacrine cell interactions, we present evidence that a pro-inflammatory cytokine, tumor necrosis factor (TNF), can have both pro- and anti-angiogenic effects, depending on the dose and the presence of pericytes. In particular, we find that pericytes can rescue and enhance angiogenesis in the presence of otherwise inhibitory high TNF doses. This sharp switch from pro- to anti-angiogenic effect of TNF observed with an escalating dose of this cytokine, as well as the effect of pericytes are explained by a mathematical model trained on the biochemical data. Furthermore, this model was predictive of the effects of diverse combinations of pro-and anti-inflammatory cues, and variable pericyte coverage. The mechanism supports the effect of TNF and pericytes as modulating signaling networks impinging in Notch signaling and specification of the Tip and Stalk phenotypes. This integrative analysis elucidates the plasticity of the angiogenic morphogenesis in the presence of diverse and potentially conflicting cues, with immediate implications for many physiological and pathological settings.

developmental biology↗

bioRxiv2019

A Mechanism for Epithelial-Mesenchymal Heterogeneity in a Population of Cancer Cells

Epithelial-mesenchymal heterogeneity, wherein cells within the same tumor can exhibit an epithelial, a mesenchymal, or one or more hybrid epithelial-mesenchymal phenotype(s), has been observed across cancer types and implicated in metastatic aggressiveness. Here, we have used computational modeling to show that this heterogeneity can emerge from the noise in the partitioning of RNAs and proteins among the daughter cells during cancer cell division. Our model captures the population-level behavior of murine prostate cancer cells, the hysteresis in the dynamics of epithelial-mesenchymal plasticity, and how hybrid phenotype-promoting factors alter the phenotypic composition of a population. We further used the model to describe the implications of heterogeneity for therapeutics. By linking the dynamics of an intracellular regulatory circuit to the phenotypic composition of a population, the study contributes towards understanding how non-genetic heterogeneity can be generated and propagated from a small, homogeneous population, and towards therapeutic targeting of cancer cell heterogeneity.

cancer biology↗

bioRxiv2018

Testing the Gene Expression Classification of the EMT Spectrum

The epithelial-mesenchymal transition (EMT) plays a central role in cancer metastasis and drug resistance - two persistent clinical challenges. Epithelial cells can undergo a partial or full EMT, attaining either a hybrid epithelial/mesenchymal (E/M) or mesenchymal phenotype, respectively. Recent studies have emphasized that hybrid E/M cells may be more aggressive than their mesenchymal counterparts. However, mechanisms driving hybrid E/M phenotypes remain largely elusive. Here, to better characterize the hybrid E/M phenotype(s) and tumor aggressiveness, we integrate two computational methods - (a) RACIPE - to identify the robust gene expression patterns emerging from the dynamics of a given gene regulatory network, and (b) EMT scoring metric - to calculate the probability that a given gene expression profile displays a hybrid E/M phenotype. We apply the EMT scoring metric to RACIPE-generated gene expression data generated from a core EMT regulatory network and classify the gene expression profiles into relevant categories (epithelial, hybrid E/M, mesenchymal). This categorization is broadly consistent with hierarchical clustering readouts of RACIPE-generated gene expression data. We show that the EMT scoring metric can be used to distinguish between samples composed of exclusively hybrid E/M cells and those containing mixtures of epithelial and mesenchymal subpopulations using the RACIPE-generated gene expression data.

systems biology↗

bioRxiv2018

Computational modeling of the crosstalk between macrophage polarization and tumor cell plasticity in the tumor microenvironment

Tumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both cancer cells and different immune cells can display phenotypic plasticity in response to these communicating signals, thereby leading to complex spatiotemporal patterns that can impact therapeutic response. Here, we investigate the crosstalk between cancer cells and macrophages in a tumor microenvironment through in silico (computational) co-culture models. In particular, we investigate how macrophages of different polarization (M1 vs. M2) can interact with epithelial-mesenchymal plasticity of cancer cells, and conversely, how cancer cells exhibiting different phenotypes (epithelial vs. mesenchymal) can influence the polarization of macrophages. Based on interactions documented in the literature, an interaction network of cancer cells and macrophages is constructed. The steady states of the network are then analyzed. Various interactions were removed or added into the constructed-network to test the functions of those interactions. Also, parameters in the mathematical models were varied to explore their effects on the steady states of the network. In general, the interactions between cancer cells and macrophages can give rise to multiple stable steady-states for a given set of parameters and each steady state is stable against perturbations. Importantly, we show that the system can often reach one type of stable steady states where cancer cells go extinct. Our results may help inform efficient therapeutic strategies.

systems biology↗

bioRxiv2018

Towards understanding cancer stem cell heterogeneity in the tumor microenvironment

The Epithelial-Mesenchymal Transition (EMT) and Cancer Stem Cell (CSC) formation are two paramount processes driving tumor progression, therapy resistance and cancer metastasis. Some recent experiments show that cells with varying EMT and CSC phenotypes are spatially segregated in the primary tumor. The underlying mechanisms generating such spatiotemporal dynamics and heterogeneity in the tumor micro-environment, however, remain largely unexplored. Here, we show through a mechanism-based dynamical model that the diffusion of EMT-inducing signals such as TGF-{beta} in a tumor tissue, together with non-cell autonomous control of EMT and CSC decision-making via juxtacrine signaling mediated via the Notch signaling pathway, can explain experimentally observed disparate localization of subsets of CSCs with varying EMT states in the tumor. Our simulations show that the more mesenchymal CSCs lie at the invasive edge, while the hybrid epithelial/mesenchymal (E/M) CSCs reside in the tumor interior. Further, motivated by the role of Notch-Jagged signaling in mediating EMT and stemness, we investigated the microenvironmental factors that promote Notch-Jagged signaling. We show that many inflammatory cytokines that can promote Notch-Jagged signaling such as IL-6 can (a) stabilize a hybrid E/M phenotype, (b) increase the likelihood of spatial proximity of hybrid E/M cells, and (c) expand the fraction of CSCs. To validate the predicted connection between Notch-Jagged signaling and stemness, we knocked down JAG1 in hybrid E/M SUM149 human breast cancer cells in vitro. JAG1 knockdown significantly restricted organoid formation, confirming the key role that Notch-Jagged signaling can play in tumor progression. Together, our integrated computational-experimental framework reveals the underlying principles of spatiotemporal dynamics of EMT and CSCs in the tumor microenvironment.\n\nSignificance statementThe presence of heterogeneous subsets of cancer stem cells (CSCs) remains a clinical challenge. These subsets often occupy different regions in the primary tumor and have varied epithelial-mesenchymal phenotypes. Here, we device a theoretical framework to investigate how the tumor microenvironment (TME) modulates this spatial patterning. We find that a spatial gradient of EMT-inducing signal, coupled with juxtacrine Notch-JAG1 signaling triggered by inflammatory cytokines in TME, explains this spatial heterogeneity. Finally, in vitro JAG1 knockdown experiments in triple negative breast cancer cells severely restricts the growth of tumor organoid, hence validating the association between JAG1 and CSC fraction. Our results offer insights into principles of spatiotemporal patterning in TME, and identifies a relevant target to alleviate multiple CSC subsets - JAG1.

cancer biology↗