Biology subjects

Levine, H.

Publications and source records attributed to Levine, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2020

Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT

Epithelial-mesenchymal transition (EMT) and its reverse process mesenchymal-epithelial transition (MET) are central to metastatic aggressiveness and therapy resistance in solid tumors. While molecular determinants of both processes have been extensively characterized, the heterogeneity in the response of tumor cells to EMT and MET inducers has come into focus recently, and has been implicated in the failure of anti-cancer therapies. Recent experimental studies have shown that some cells can undergo an irreversible EMT depending on the duration of exposure to EMT-inducing signals. While the irreversibility of MET, or equivalently, resistance to EMT, has not been studied in as much detail, evidence supporting such behavior is slowly emerging. Here, we identify two possible mechanisms that can underlie resistance of cells to undergo EMT: epigenetic feedback in ZEB1/GRHL2 feedback loop and stochastic partitioning of biomolecules during cell division. Identifying the ZEB1/GRHL2 axis as a key determinant of epithelial-mesenchymal plasticity across many cancer types, we use mechanistic mathematical models to show how GRHL2 can be involved in both the abovementioned processes, thus driving an irreversible MET. Our study highlights how an isogenic population may contain subpopulation with varying degrees of susceptibility or resistance to EMT, and proposes a next set of questions for detailed experimental studies characterizing the irreversibility of MET/resistance to EMT.

cancer biology↗

bioRxiv2020

Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire

Accurate assessment of TCR-antigen specificity at the whole immune repertoire level lies at the heart of improved cancer immunotherapy, but predictive models capable of high-throughput assessment of TCR-peptide pairs are lacking. Recent advances in deep sequencing and crystallography have enriched the data available for studying TCR-p-MHC systems. Here, we introduce a pairwise energy model, RACER, for rapid assessment of TCR-peptide affinity at the immune repertoire level. RACER applies supervised machine learning to efficiently and accurately resolve strong TCR-peptide binding pairs from weak ones. The trained parameters further enable a physical interpretation of interacting patterns encoded in each specific TCR-p-MHC system. When applied to simulate thymic selection of an MHC-restricted T-cell repertoire, RACER accurately estimates recognition rates for tumor-associated neoantigens and foreign peptides, thus demonstrating its utility in helping address the large computational challenge of reliably identifying the properties of tumor antigen-specific T-cells at the level of an individual patients immune repertoire.

biophysics↗

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

Calpain-2 regulates hypoxia/HIF-induced amoeboid reprogramming and metastasis

Hypoxia, through hypoxia inducible factor (HIF), drives cancer cell invasion and metastatic progression in various cancer types, leading to poor prognosis. In epithelial cancer, hypoxia further induces the transition to amoeboid cancer cell dissemination, yet the molecular mechanisms, relevance for metastasis, and effective interventions to combat hypoxia-induced amoeboid reprogramming remain unclear. Here, we identify calpain-2 as key regulator and anti-metastasis target of hypoxia-induced transition from collective to amoeboid dissemination of breast and head and neck (HN) carcinoma cells. Hypoxia-induced amoeboid dissemination occurred through low ECM-adhesive, bleb-based amoeboid movement, which effectively invaded into 3D collagen with low-oxidative and -glycolytic energy metabolism, revealing an microenvironmentally-induced, energy-conserving dissemination route in epithelial cancers. Hypoxia-induced calpain-2 mediated amoeboid conversion by de-activating beta1 integrins, through enzymatic cleavage of the focal adhesion adaptor protein talin-1. Consequently, targeted downregulation of calpain-2 or pharmacological intervention restored talin-1 integrity, beta1 integrin engagement and reverted blebbing-amoeboid to elongated phenotypes under hypoxia. Calpain-2 activity was required for hypoxia-induced blebbing-amoeboid conversion in the orthotopic mouse dermis, and upregulated in invasive HN tumor xenografts in vivo, and attenuation of calpain activity prevented hypoxia-induced metastasis to the lungs. This identifies the calpain-2/talin-1/beta1 integrin axis as mechanosignaling program and promising intervention target of plasticity of cancer cell invasion and metastasis formation in epithelial cancers under hypoxia.

cancer 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

Drug-tolerant idling melanoma cells exhibit theory-predicted metabolic low-low phenotype

Cancer cells adjust their metabolic profiles to evade treatment. Metabolic adaptation is complex and hence better understood by an integrated theoretical-experimental approach. Using a minimal kinetic model, we predicted a previously undescribed Low/Low (L/L) phenotype, characterized by low oxidative phosphorylation (OXPHOS) and low glycolysis. Here, we report that L/L metabolism is observed in BRAF-mutated melanoma cells that enter a drug-tolerant "idling state" upon long-term MAPK inhibition (MAPKi). Consistently, using publicly available RNA-sequencing data of both cell lines and patient samples, we show that melanoma cells decrease their glycolysis and/or OXPHOS activity upon MAPKi and converge toward the L/L phenotype. L/L metabolism is unfavorable for tumor growth, yet supports successful cell division at ~50% rate. Thus, L/L drug-tolerant idling cells are a reservoir for accumulating mutations responsible for relapse, and it should be considered as a target subpopulation for improving MAPKi outcomes in melanoma treatment.

systems 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

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

Sustained Co-evolution in a Stochastic Model of the Cancer-Immune Interaction

The dynamical interaction between a growing cancer population and the adaptive immune system generates diverse evolutionary trajectories which ultimately result in tumor clearance or immune escape. Here, we create a simple mathematical model coupling T-cell recognition with an evolving cancer population which may randomly produce evasive subclones, imparting transient protection against the effector T-cells. We demonstrate that T-cell turnover declines and evasion rates together explain differential probabilities in early incidence data for almost all cancer types. Fitting the model to TRACERx evolutionary data argues in favor of substantial and sustained immune pressure exerted on a developing tumor, suggesting that measured incidence is a small proportion of all cancer initiation events. Most generally, dynamical models promise to increase our quantitative understanding of many immune escape contexts, with applications to cancer and intracellular pathogenic infections.

evolutionary biology↗

bioRxiv2019

Fractal dimension, occupancy and hotspot analyses of B cell spatial distribution predict clinical outcome in breast cancer

While the density of tumor-infiltrating lymphocytes (TILs) is now well known to correlate with clinical outcome, the clinical significance of spatial distribution of TILs is not well characterized. We have developed novel statistical techniques (including fractal dimension differences, a hotspot analysis, a box counting method that we call occupancy and a way to normalize cell density that we call thinning) to analyze the spatial distribution (at different length scales) of various types of TILs in triple negative breast tumors. Consistent with prior reports, the density of CD20+ B cells within tumors is not correlated with clinical outcome. However, we found that their spatial distribution differs significantly between good clinical outcome (no recurrence within at least 5 years of diagnosis) and poor clinical outcome (recurrence with 3 years of diagnosis). Furthermore, CD20+ B cells are more spatially dispersed in good outcome tumors and are more likely to infiltrate into cancer cell islands. Lastly, we found significant correlation between the spatial distributions of CD20+ B cells and CD8+ (cytotoxic) T cells (as well as CD3+ T cells), regardless of outcome. These results highlight the significance of the spatial distribution of TILs, especially B cells, within tumors.\n\nSignificance StatementImmune cells can fight cancer. For example, a patient has a good prognosis when a high density of killer T cells, a type of immune cell that can kill cancer cells, infiltrates into a tumor. However, there is no clear association between prognosis and the density of B cells, another type of immune cell, in a tumor. We developed several statistical techniques to go beyond cell density and look at the spatial distribution, i.e., the pattern or arrangement of immune cells, in tumors that have been removed from patients with triple negative breast cancer. We find that B cells and killer T cells tend to be more spread out in the tumors of patients whose cancer did not recur.

cancer 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↗

bioRxiv2019

Ordered Hexagonal Patterns via Notch-Delta Signaling

Many developmental processes in biology utilize Notch-Delta signaling to construct an ordered pattern of cellular differentiation. This signaling modality is based on nearest-neighbor contact, as opposed to the more familiar mechanism driven by the release of diffusible ligands. Here, we show that this "juxtracrine" property allows for an exact treatment of the pattern formation problem via a system of nine coupled ordinary differential equations. Furthermore, we show that the possible patterns that are realized can be analyzed by considering a co-dimension 2 pitchfork bifurcation of this system. This analysis explains the observed prevalence of hexagonal patterns with high Delta at their center, as opposed to those with central high Notch levels. Also, our theory suggests a simple strategy for producing defect-free patterns.

biophysics↗

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

Infiltration of CD8+ T cells into tumor-cell clusters in Triple Negative Breast Cancer

Infiltration of CD8+ T lymphocytes into solid tumors is associated with good prognosis in various types of cancer, including Triple Negative Breast Cancers (TNBC). However, the mechanisms underlying different infiltration-levels are largely unknown. Here, we have characterized the spatial profile of CD8+ T cells around tumorcell clusters in the core and margin regions in TNBC. Combining mathematical modeling and data analysis, we propose that there exists a possible chemo-repellent inside tumor-cell clusters, which prevents CD8+ T cells from infiltrating into tumor-cell clusters. Furthermore, investigation into the properties of collagen fibers suggests that variations in desmoplastic elements does not limit infiltration of CD8+ T lymphocytes into tumor-cell clusters. This is consistent with the prediction of our mathematical modeling analysis whereby CD8+ T cells are predicted to infiltrate the fibrotic barrier and their infiltration into tumor clusters is governed by other mechanisms involving a local repellent.

cancer biology↗

bioRxiv2018

Presynaptic Endoplasmic Reticulum Contributes Crucially to Short-term Plasticity in Small Hippocampal Synapses

Short-term plasticity (STP) of the presynaptic terminal maintains a brief history of activity experienced by the synapse that may otherwise remain unseen by the postsynaptic neuron. These synaptic changes are primarily regulated by calcium dynamics in the presynaptic terminal. A rapid increase in intracellular calcium is initiated by the opening of voltage-dependent calcium channels in response to depolarization, the main source of calcium required for vesicle fusion. Separately, electron-microscopic studies of hippocampal CA3-CA1 synapses reveal the strong presence of endoplasmic reticulum (ER) in all presynaptic terminals. However, the precise role of the ER in modifying STP at the presynaptic terminal remains unexplored. To investigate the contribution of ER in modulating calcium dynamics in small hippocampal boutons, we performed in silico experiments in a physiologically-realistic canonical synaptic geometry based on reconstructions of CA3-CA1 Schaffer collaterals in the rat hippocampus. The model predicts that presynaptic calcium stores are critical in generating the observed paired-pulse ratio (PPR) of normal CA3-CA1 synapses. In control synapses with intact ER, SERCA pumps act as additional calcium buffers, lowering the intrinsic release probability of vesicle release and increasing PPR. In addition, the presence of ER allows ongoing activity to trigger calcium influx from the presynaptic ER via ryanodine receptors (RyRs) and inositol trisphosphate receptors (IP3Rs). Intracellular stores and their associated machinery also allows a synapse with a low release probability to operate more reliably due to attenuation of calcium fluctuations. Finally, blocking ER activity in the presynaptic terminal mimics the pathological state of a low facilitating synapse characterized in animal models of Alzheimers disease, and underscores the critical role played by presynaptic stores in normal function.

neuroscience↗