Biology subjects

Levine, H.

Publications and source records attributed to Levine, H..

At least 37 records · Page 2Linked to original sources

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↗

bioRxiv2022

The Alternate Ligand Jagged Enhances the Robustness of Notch Signaling Patterns

The Notch pathway, an example of juxtacrine signaling, is an evolutionary conserved cell-cell communication mechanism. It governs emergent spatiotemporal patterning in tissues during development, wound healing and tumorigenesis. Communication occurs when Notch receptors of one cell bind to either of its ligands, Delta/Jagged of neighboring cell. In general, Delta-mediated signaling drives neighboring cells to have an opposite fate (lateral inhibition) whereas Jagged-mediated signaling drives cells to maintain similar fates (lateral induction). Here, By deriving and solving a reduced set of 12 coupled ordinary differential equations for Notch-Delta-Jagged system on a hexagonal grid of cells, we determine the allowed states across different parameter sets. We also show that Jagged (at low dose) acts synergistically with Delta to enable more robust pattern formation, despite of its lateral induction property; this effect is due to competition with Delta over binding with Notch, as experimentally observed in the case of chick inner ear development. Finally, we show that how Jagged can help to expand the bistable (both Uniform and Hexagon phases are stable) region, where a local perturbation can spread over time in a ordered manner to create a biologically relevant, defect-free lateral inhibition pattern.

biophysics↗

bioRxiv2022

Epigenetic memory acquired during long-term EMTinduction governs the recovery to the epithelial state

Epithelial-Mesenchymal Transition (EMT) and its reverse Mesenchymal-Epithelial Transition (MET) are critical during embryonic development, wound healing and cancer metastasis. While phenotypic changes during short-term EMT induction are reversible, long-term EMT induction has been often associated with irreversibility. Here, we show that phenotypic changes seen in MCF10A cells upon long-term EMT induction by TGF{beta} need not be irreversible, but have relatively longer timescales of reversibility than those seen in short-term induction. Next, using a phenomenological mathematical model incorporating the epigenetic silencing of miR-200 by ZEB, we highlight how the epigenetic memory gained during long-term EMT induction can slow the recovery to the epithelial state post-TGF{beta} withdrawal. Our results suggest that epigenetic modifiers can govern the extent and timescale of EMT reversibility, and advise caution against labelling phenotypic changes seen in long-term EMT induction as irreversible.

cancer biology↗

bioRxiv2022

Optimal Cancer Evasion in a Dynamic Immune Microenvironment

The failure of cancer treatments, including immunotherapy, continues to be a major obstacle in preventing durable remission. This failure often results from tumor evolution, both genotypic and phenotypic, away from sensitive cell states. Here, we propose a mathematical framework for studying the dynamics of adaptive immune evasion that tracks the number of tumor-associated antigens available for immune targeting. We solve for the unique optimal cancer evasion strategy using stochastic dynamic programming and demonstrate that this policy results in increased cancer evasion rates when compared to a passive, fixed strategy. Our foundational model relates the likelihood and temporal dynamics of cancer evasion to features of the immune microenvironment, where tumor immunogenicity reflects a balance between cancer adaptation and host recognition. In contrast with a passive strategy, optimally adaptive evaders navigating varying selective environments result in substantially heterogeneous post-escape tumor antigenicity, giving rise to immunogenically hot and cold tumors.

evolutionary biology↗

bioRxiv2022

Infiltration of Tumor Spheroids by Activated Immune Cells

Recent years have seen a tremendous growth of interest in understanding the role that the adaptive immune system could play in interdicting tumor progression. In this context, it has been shown that the density of adaptive immune cells inside a solid tumor serves as a favorable prognostic marker across different types of cancer. The exact mechanisms underlying the degree of immune cell infiltration is largely unknown. Here, we quantify the temporal dynamics of the density profile of activated immune cells around a solid tumor spheroid. We propose a computational model incorporating immune cells with active, persistent movement and a proliferation rate that depends on the presence of cancer cells, and show that the model able to reproduce quantitatively the experimentally measured infiltration profile. Studying the density distribution of immune cells inside a solid tumor can help us better understand immune trafficking in the tumor micro-environment, hopefully leading towards novel immunotherapeutic strategies.

cancer biology↗

bioRxiv2022

Minimal frustration underlies the usefulness of incomplete and inexact regulatory network models in biology

Regulatory networks as large and complex as those implicated in cell-fate choice are expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a macroscopically simple process. Additionally, regulatory network models are almost always incomplete and / or inexact, and do not incorporate all the regulators and interactions that may be involved in cellfate regulation. In spite of these issues, regulatory network models have proven to be incredibly effective tools for understanding cell-fate choice across contexts and for making useful predictions. Here, we show that minimal frustration--a feature of biological networks across contexts but not of random networks--can compel simple, low-dimensional steady-state behavior even in large and complex networks. Moreover, the steady-state behavior of minimally frustrated networks can be recapitulated by simpler networks such as those lacking many of the nodes and edges, and those that treat multiple regulators as one. The present study provides a theoretical explanation for the success of network models in biology and for the challenges in network inference.

systems biology↗

bioRxiv2021

Quantifying the patterns of metabolic plasticity and heterogeneity along the epithelial-hybrid-mesenchymal spectrum in cancer

Cancer metastasis is the leading cause of cancer-related mortality and the process of Epithelial to Mesenchymal Transition (EMT) is crucial for cancer metastasis. Either a partial or complete EMT have been reported to influence the metabolic plasticity of cancer cells in terms of switching among oxidative phosphorylation, fatty acid oxidation and glycolysis pathways. However, a comprehensive analysis of these major metabolic pathways their associations with EMT across different cancers is lacking. Here, we analyse more than 180 cancer cell datasets and show diverse associations of these metabolic pathways with the EMT status of cancer cells. Our bulk data analysis shows that EMT generally positively correlates with glycolysis but negatively with oxidative phosphorylation and fatty acid metabolism. These correlations are also consistent at the level of their molecular master regulators, namely AMPK and HIF1. Yet, these associations are shown to not be universal. Analysis of singlecell data of EMT induction shows dynamic changes along the different axes of metabolic pathways, consistent with general trends seen in bulk samples. Together, our results reveal underlying patterns of metabolic plasticity and heterogeneity as cancer cells traverse through the epithelial-hybrid-mesenchymal spectrum of states.

cancer biology↗

bioRxiv2021

NRF2-dependent epigenetic regulation can promote the hybrid epithelial/mesenchymal phenotype

The epithelial-mesenchymal transition (EMT) is a cellular process critical for wound healing, cancer metastasis and embryonic development. Recent efforts have identified the role of hybrid epithelial/mesenchymal states, having both epithelial and mesehncymal traits, in enabling cancer metastasis and resistance to various therapies. Also, previous work has suggested that NRF2 can act as phenotypic stability factor to help stablize such hybrid states. Here, we incorporate a phenomenological epigenetic feedback effect into our previous computational model for EMT signaling. We show that this type of feedback can stabilize the hybrid state as compared to the fully mesenchymal phenotype if NRF2 can influence SNAIL at an epigenetic level, as this link makes transitions out of hybrid state more difficult. However, epigenetic regulation on other NRF2-related links do not significantly change the EMT dynamics. Finally, we considered possible cell division effects in our epigenetic regulation model, and our results indicate that the degree of epigenetic inheritance does not appear to be a critical factor for the hybrid E/M state stabilizing behavior of NRF2.

systems biology↗

bioRxiv2021

Three-dimensional Cancer Cell Migration Directed by Dual Mechanochemical Guidance

Directed cell migration guided by external cues plays a central role in many physiological and pathophysiological processes. The microenvironment of cells often simultaneously contains various cues and the motility response of cells to multiplexed guidance is poorly understood. Here we combine experiments and mathematical models to study the three-dimensional migration of breast cancer cells in the presence of both contact guidance and a chemoattractant gradient. We find that the chemotaxis of cells is complicated by the presence of contact guidance as the microstructure of extracellular matrix (ECM) vary spatially. In the presence of dual guidance, the impact of ECM alignment is determined externally by the coherence of ECM fibers, and internally by cell mechanosensing Rho/Rock pathways. When contact guidance is parallel to the chemical gradient, coherent ECM fibers significantly increase the efficiency of chemotaxis. When contact guidance is perpendicular to the chemical gradient, cells exploit the ECM disorder to locate paths for chemotaxis. Our results underscores the importance of fully characterizing the cancer cell microenvironment in order to better understand invasion and metastasis.

biophysics↗

bioRxiv2021

Cerebral perfusion imaging: Hypoxia-induced deoxyhemoglobin or gadolinium?

Assessment of resting cerebrovascular perfusion measures (mean transit time, cerebral blood flow and cerebral blood volume) with magnetic resonance imaging currently requires the intravascular injection of the dynamic susceptibility contrast agent gadolinium. An initial comparison between hypoxia-induced deoxyhemoglobin and gadolinium was made for these measures in six healthy participants. A bolus of deoxyhemoglobin is generated in the lung via transient hypoxia induced by an available computer-controlled gas blender technology employing sequential gas delivery (RespirAct). We hypothesised and confirmed perfusion measures from both susceptibility contrast agents would yield similar spatial patterns of cerebrovascular perfusion measures. We conclude that hypoxia-induced deoxyhemoglobin, an endogenously, non-invasively generated, non-allergenic, non-toxic, recyclable, environmentally innocuous molecule, may be suitable to become the first new magnetic resonance imaging susceptibility contrast agent introduction since gadolinium.

neuroscience↗

bioRxiv2021

Transcriptomic-based quantification of the epithelial-hybrid-mesenchymal spectrum across biological contexts

Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics - each derived using a different gene list and algorithm - that quantify the EMP spectrum. Our results for 96 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.

bioinformatics↗

bioRxiv2021

Immunosuppressive traits of the hybrid epithelial/mesenchymal phenotype

Recent preclinical and clinical data suggests enhanced metastatic fitness of hybrid epithelial/ mesenchymal (E/M) phenotypes, but mechanistic details regarding their survival strategies during metastasis remain unclear. Here, we investigate immune-evasive strategies of hybrid E/M states. We construct and simulate the dynamics of a minimalistic regulatory network encompassing the known associations among regulators of EMT (epithelial-mesenchymal transition) and PD-L1, an established immune-suppressor. Our model simulations, integrated with single-cell and bulk RNA-seq data analysis, elucidate that hybrid E/M cells can have high levels of PD-L1, similar to those seen in cells with a full EMT phenotype, thus obviating the need for cancer cells to undergo a full EMT to be immune-evasive. Specifically, in breast cancer, we show the co-existence of hybrid E/M phenotypes, enhanced resistance to anti-estrogen therapy and increased PD-L1 levels. Our results underscore how the emergent dynamics of interconnected regulatory networks can coordinate different axes of cellular fitness during metastasis.

cancer biology↗

bioRxiv2021

Cluster Size Distribution of Cells Disseminating from a Primary Tumor

The first stage of the metastatic cascade often involves motile cells emerging from a primary tumor either as single cells or as clusters. These cells enter the circulation, transit to other parts of the body and finally are responsible for growth of secondary tumors in distant organs. The mode of dissemination is believed to depend on the EMT nature (epithelial, hybrid or mesenchymal) of the cells. Here, we calculate the cluster size distribution of these migrating cells, using a mechanistic computational model, in presence of different degree of EMT-ness of the cells; EMT is treated as given rise to changes in their active motile forces () and cell-medium surface tension ({Gamma}). We find that, for ( > min, {Gamma} > 1), when the cells are hybrid in nature, the mean cluster size, [Formula], where min increases with increase in {Gamma}. For {Gamma} [≤] 0, [Formula], the cells behave as completely mesenchymal. In presence of spectrum of hybrid states with different degree of EMT-ness (motility) in primary tumor, the cells which are relatively more mesenchymal (higher ) in nature, form larger clusters, whereas the smaller clusters are relatively more epithelial (lower ). Moreover, the heterogeneity in is comparatively higher for smaller clusters with respect to that for larger clusters. We also observe that more extended cell shapes promote the formation of smaller clusters. Overall, this study establishes a framework which connects the nature and size of migrating clusters disseminating from a primary tumor with the phenotypic composition of the tumor, and can lead to the better understanding of metastasis. Author summaryIn the process of metastasis, tumor cells disseminate from the primary tumor either as single cells or multicellular clusters. These clusters are potential contributor to the initiation of secondary tumor in distant organs. Our computational model captures the size distribution of migrating clusters depending on the adhesion and motility of the cells (which determine the degree of their EMT nature). Furthermore, we investigate the effect of heterogeneity of cell types in the primary tumor on the resultant heterogeneity of cell types in clusters of different sizes. We believe that the understanding the formation and nature of these clusters, dangerous actors in the deadly aspect of cancer progression, will be useful for improving prognostic methods and eventually better treatments.

cancer biology↗

bioRxiv2021

Nrf2 regulates collective cancer migration by modulating the hybrid epithelial/mesenchymal phenotype

Hybrid epithelial/mesenchymal cells (E/M) are key players in aggressive cancer metastasis. It remains a challenge to understand how these cell states, which are mostly non-existent in healthy tissue, become stable phenotypes participating in collective cancer migration. The transcription factor Nrf2, which is associated with tumor progression and resistance to therapy, appears to be central to this process. Here, using a combination of single cell biosensors, immunocytochemistry, and computational modeling, we show that Nrf2 functions as a phenotypic stability factor for hybrid E/M cells by inhibiting a complete epithelial-mesenchymal transition (EMT) during collective cancer migration. We also demonstrate that Nrf2 and EMT signaling are spatially coordinated near the migrating front. In particular, computational analysis of an Nrf2-EMT-Notch network and experimental modulation of Nrf2 by pharmacological treatment or CRISPR/Cas9 gene editing reveal that Nrf2 stabilizes a hybrid E/M phenotype which is maximally observed in the interior region immediately behind the leading edge. We further demonstrate that the Nrf2-EMT-Notch network enhances Dll4 and Jagged1 expression near the leading edge, which correlates with the formation of leader cells and protruding tips. Altogether, our results provide direct evidence that Nrf2 acts as a phenotypic stability factor in restricting complete EMT and plays an important role in coordinating collective cancer migration.

cancer biology↗

bioRxiv2021

Mechanical Interplay Between Transcription Elongation and DNA Supercoiling

Multiple RNA polymerases (RNAPs) transcribing a gene have been known to exhibit collective group behavior, causing the transcription elongation rate to increase with the rate of transcription initiation. Such behavior has long been believed to be driven by a physical interaction or "push" between closely spaced RNAPs. However, recent studies have posited that RNAPs separated by longer distances may cooperate via the DNA segment under transcription. Here, we present a theoretical model incorporating the mechanical coupling between RNAP translocation and the torsional response of supercoiled DNA. Using stochastic simulations, we demonstrate long-range cooperation between co-transcribing RNAPs mediated by DNA supercoiling. We find that inhibiting transcription initiation can slow down the already recruited RNAPs, in agreement with recent experimental observations, and predict that the average transcription elongation rate varies non-monotonically with the rate of transcription initiation. We further show that while RNAPs transcribing neighboring genes oriented in tandem can cooperate, those transcribing genes in divergent or convergent orientations can act antagonistically, and that such behavior holds over a large range of intergenic separations. Our model makes testable predictions, revealing how the mechanical interplay between RNAPs and the DNA they transcribe can govern a key cellular process.

biophysics↗

bioRxiv2021

A theoretical approach to coupling the epithelial-mesenchymal transition (EMT) to extracellular matrix (ECM) stiffness via LOXL2

The epithelial-mesenchymal transition (EMT) plays a critical role in cancer progression, being responsible in many cases for the onset of the metastatic cascade and being integral in the ability of cells to resist drug treatment. Most studies of EMT focus on its induction via chemical signals such as TGF-{beta} or Notch ligands, but it has become increasingly clear that biomechanical features of the microenvironment such as ECM (extracellular matrix) stiffness can be equally important. Here, we introduce a coupled feedback loop connecting stiffness to the EMT transcription factor ZEB1, which acts via increasing the secretion of LOXL2 that leads to increased cross-linking of collagen fibers in the ECM. This increased cross-linking can effectively increase ECM stiffness and increase ZEB1 levels, thus setting a positive feedback loop between ZEB1 and ECM stiffness. To investigate the impact of this non-cell-autonomous effect, we introduce a computational approach capable of connecting LOXL2 concentration to increased stiffness and thereby to higher ZEB1 levels. Our results indicate that this positive feedback loop, once activated, can effectively lock the cells in a mesenchymal state.

cancer biology↗

bioRxiv2021

A Mechanistic Modeling Framework Reveals the Key Principles Underlying Tumor Metabolism

While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive heterogeneity with respect to the presentation of the Warburg effect. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. Next, we report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer. Author SummaryTumor cells exhibit heterogeneity and plasticity in their metabolic behavior, relying on distinct nutrients and metabolic pathways, and switching to reliance on different pathways when challenged by an environmental change or a drug. While multiple previous studies have focused on identifying metabolic signatures that can distinguish tumor cells from non-tumorigenic ones, frameworks to analyze the metabolic heterogeneity in tumors have been lacking. Here, we present a mechanistic mathematical model of some of the key metabolic pathways active in tumor cells and analyze the steady state behaviors the model can exhibit. We find that the rate of ATP use by tumor cells can be a key determinant of the metabolic pathway via which tumor cells utilize glucose. We further show that tumor cells can utilize different pathways for satisfying the same metabolic requirements, and explore the implications of such behavior for the response of tumor cells to drugs targeting tumor metabolism. At each step, we discuss how our model predictions fit within the context of experimental observations made across tumor types. The present modeling framework represents an important step towards reconciling the wide array of experimental observations concerning tumor metabolism, and towards a more methodical approach to targeting tumors metabolic vulnerabilities.

cancer biology↗

bioRxiv2020

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum

Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.

cancer biology↗