Biology subjects

Onuchic, J. N.

Publications and source records attributed to Onuchic, J. N..

At least 37 records · Page 2Linked to original sources

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

Evolutionary differences in the ACE2 reveals the molecular origins of COVID-19 susceptibility

We explore the energetic frustration patterns associated with the binding between the SARS-CoV-2 spike protein and the ACE2 receptor protein in a broad selection of animals. Using energy landscape theory and the concept of energy frustration--theoretical tools originally developed to study protein folding--we are able to identify interactions among residues of the spike protein and ACE2 that result in COVID-19 resistance. This allows us to identify whether or not a particular animal is susceptible to COVID-19 from the protein sequence of ACE2 alone. Our analysis predicts a number of experimental observations regarding COVID-19 susceptibility, demonstrating that this feature can be explained, at least partially, on the basis of theoretical means.

biophysics↗

bioRxiv2021

Design and proof-of-concept for targeted phage-based COVID-19 vaccination strategies with a streamlined cold-free supply chain

Development of effective vaccines against Coronavirus Disease 2019 (COVID-19) is a global imperative. Rapid immunization of the world human population against a widespread, continually evolving, and highly pathogenic virus is an unprecedented challenge, and many different vaccine approaches are being pursued to meet this task. Engineered filamentous bacteriophage (phage) have unique potential in vaccine development due to their inherent immunogenicity, genetic plasticity, stability, cost-effectiveness for large-scale production, and proven safety profile in humans. Herein we report the design, development, and initial evaluation of targeted phage-based vaccination approaches against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) by using dual ligand peptide-targeted phage and adeno-associated virus/phage (AAVP) particles. Towards a unique phage- and AAVP-based dual-display candidate approach, we first performed structure-guided antigen design to select six solvent-exposed epitopes of the SARS-CoV-2 spike (S) protein for display on the recombinant major capsid coat protein pVIII. Targeted phage particles carrying one of these epitopes induced a strong and specific humoral response. In an initial experimental approach, when these targeted phage particles were further genetically engineered to simultaneously display a ligand peptide (CAKSMGDIVC) on the minor capsid protein pIII, which enables receptor-mediated transport of phage particles from the lung epithelium into the systemic circulation (termed "dual-display"), they enhanced a systemic and specific spike (S) protein-specific antibody response upon aerosolization into the lungs of mice. In a second line of investigation, we engineered targeted AAVP particles to deliver the entire S protein gene under the control of a constitutive cytomegalovirus (CMV) promoter, which induced tissue-specific transgene expression stimulating a systemic S protein-specific antibody response. As proof-of-concept preclinical experiments, we show that targeted phage- and AAVP-based particles serve as robust yet versatile enabling platforms for ligand-directed immunization and promptly yield COVID-19 vaccine prototypes for further translational development. SignificanceThe ongoing COVID-19 global pandemic has accounted for over 2.5 million deaths and an unprecedented impact on the health of mankind worldwide. Over the past several months, while a few COVID-19 vaccines have received Emergency Use Authorization and are currently being administered to the entire human population, the demand for prompt global immunization has created enormous logistical challenges--including but not limited to supply, access, and distribution--that justify and reinforce the research for additional strategic alternatives. Phage are viruses that only infect bacteria and have been safely administered to humans as antibiotics for decades. As experimental proof-of-concept, we demonstrated that aerosol pulmonary vaccination with lung-targeted phage particles that display short epitopes of the S protein on the capsid as well as preclinical vaccination with targeted AAVP particles carrying the S protein gene elicit a systemic and specific immune response against SARS-CoV-2 in immunocompetent mice. Given that targeted phage- and AAVP-based viral particles are sturdy yet simple to genetically engineer, cost-effective for rapid large-scale production in clinical grade, and relatively stable at room temperature, such unique attributes might perhaps become additional tools towards COVID-19 vaccine design and development for immediate and future unmet needs.

microbiology↗

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

Exploring Energy Landscapes of Intrinsically Disordered Proteins: Insights into Functional Mechanisms

Intrinsically disordered proteins (IDPs) lack a rigid 3D structure and populate a polymorphic ensemble of conformations. Because of the lack of a reference conformation, their energy landscape representation in terms of reaction coordinates presents a daunting challenge. Here, our newly developed Energy Landscape Visualization Method (ELViM), a reaction coordinate-free approach, shows its prime application to explore frustrated energy landscapes of an intrinsically disordered protein, Prostate-Associated Gene 4 (PAGE4). PAGE4 is a transcriptional coactivator that potentiates the oncogene c-Jun. Two kinases, namely HIPK1 and CLK2, phosphorylate PAGE4 generating variants phosphorylated at different serine/threonine residues (HIPK1-PAGE4 and CLK2-PAGE4, respectively) with opposing functions. While HIPK1-PAGE4 predominantly phosphorylates Thr51 and potentiates c-Jun, CLK2-PAGE4 hyper-phosphorylates PAGE4 and attenuates transactivation. To understand the underlying mechanisms of conformational diversity among different phosphoforms, we have analyzed their atomistic trajectories simulated using AWSEM forcefield and the energy landscapes were elucidated using ELViM. This method allows us to identify and compare the population distributions of different conformational ensembles of PAGE4 phosphoforms using the same effective phase space. The results reveal a predominant conformational ensemble with an extended C-terminal segment of WT PAGE4, which exposes a functional residue Thr51, implying its potential of undertaking a fly-casting mechanism while binding to its cognate partner. In contrast, for HIPK1-PAGE4, a compact conformational ensemble enhances its population sequestering phosphorylated-Thr51. This clearly explains the experimentally observed weaker affinity of HIPK1-PAGE4 for c-Jun. ELViM appears as a powerful tool especially to analyze the highly-frustrated energy landscape representation of IDPs where appropriate reaction coordinates are hard to apprehend.

biophysics↗

bioRxiv2021

Sterically-Confined Rearrangements of SARS-CoV-2 Spike Protein Control Cell Invasion

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly contagious, and transmission involves a series of processes that may be targeted by vaccines and therapeutics. During transmission, host cell invasion is controlled by a large-scale conformational change of the Spike protein. This conformational rearrangement leads to membrane fusion, which creates transmembrane pores through which the viral genome is passed to the host. During Spike-protein-mediated fusion, the fusion peptides must be released from the core of the protein and associate with the host membrane. Interestingly, the Spike protein possesses many post-translational modifications, in the form of branched glycans that flank the surface of the assembly. Despite the large number of glycosylation sites, until now, the specific role of glycans during cell invasion has been unclear. Here, we propose that glycosylation is needed to provide sufficient time for the fusion peptides to reach the host membrane, otherwise the viral particle would fail to enter the host. To understand this process, an all-atom model with simplified energetics was used to perform thousands of simulations in which the protein transitions between the prefusion and postfusion conformations. These simulations indicate that the steric composition of the glycans induces a pause during the Spike protein conformational change. We additionally show that this glycan-induced delay provides a critical opportunity for the fusion peptides to capture the host cell. This previously-unrecognized role of glycans reveals how the glycosylation state can regulate infectivity of this pervasive pathogen.

biophysics↗

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

Exploring Chromosomal Structural Heterogeneity AcrossMultiple Cell Lines

We study the structural ensembles of human chromosomes across different cell types. Using computer simulations, we generate cell-specific 3D chromosomal structures and compare them to recently published chromatin structures obtained through microscopy. We demonstrate using a combination of machine learning and polymer physics simulations that epigenetic information can be used to predict the structural ensembles of multiple human cell lines. The chromosomal structures obtained in silico are quantitatively consistent with those obtained through microscopy as well as DNA-DNA proximity ligation assays. Theory predicts that chromosome structures are fluid and can only be described by an ensemble, which is consistent with the observation that chromosomes exhibit no unique fold. Nevertheless, our analysis of both structures from simulation and microscopy reveals that short segments of chromatin make transitions between a closed conformation and an open dumbbell conformation. This conformational transition appears to be consistent with a two-state process with an effective free energy cost of about four times the effective information theoretic temperature. Finally, we study the conformational changes associated with the switching of genomic compartments observed in human cell lines. Genetically identical but epigenetically distinct cell types appear to rearrange their respective structural ensembles to expose segments of transcriptionally active chromatin, belonging to the A genomic compartment, towards the surface of the chromosome, while inactive segments, belonging to the B compartment, move to the interior. The formation of genomic compartments resembles hydrophobic collapse in protein folding, with the aggregation of denser and predominantly inactive chromatin driving the positioning of active chromatin toward the surface of individual chromosomal territories.

biophysics↗

bioRxiv2019

Enhancing Intracellular Concentration and Target Engagement of PROTACs with Reversible Covalent Chemistry

Current efforts in the proteolysis targeting chimera (PROTAC) field mostly focus on choosing an appropriate E3 ligase for the target protein, improving the binding affinities towards the target protein and the E3 ligase, and optimizing the PROTAC linker. However, due to the large molecular weights of PROTACs, their cellular uptake remains an issue. Through comparing how different warhead chemistry, reversible noncovalent (RNC), reversible covalent (RC), and irreversible covalent (IRC) binders, affects the degradation of Brutons Tyrosine Kinase (BTK), we serendipitously discover that cyano-acrylamide-based reversible covalent chemistry can significantly enhance the intracellular accumulation and target engagement of PROTACs and develop RC-1 as a reversible covalent BTK PROTAC with a high target occupancy as its corresponding kinase inhibitor and effectiveness as a dual functional inhibitor and degrader, a different mechanism-of-action for PROTACs. Importantly, this reversible covalent strategy is generalizable to improve other PROTACs, opening a path to enhance PROTAC efficacy.

pharmacology and toxicology↗

bioRxiv2019

The Nucleome Data Bank: Web-based Resources to Simulate and Analyze the Three-Dimensional Genome

We introduce the Nucleome Data Bank, a web-based platform to simulate and analyze the three-dimensional organization of genomes. The Nucleome Data Bank enables physics-based simulation of chromosomal structural dynamics through the MEGABASE + MiChroM computational pipeline. The input of the pipeline consists of epigenetic information sourced from the Encode database; the output consists of the trajectories of chromosomal motions that accurately predict Hi-C and FISH data, as well as multiple observations of chromosomal dynamics in vivo. As an intermediate step, users can also generate chromosomal sub-compartment annotations directly from the same epigenetic input, without the use of any DNA-DNA proximity ligation data. Additionally, the Nucleome Data Bank freely hosts both experimental and computational structural genomics data. Besides being able to perform their own genome simulations and download the hosted data, users can also analyze and visualize the same data through custom-designed web-based tools. In particular, the one-dimensional genetic and epigenetic data can be overlaid onto accurate three-dimensional structures of chromosomes, to study the spatial distribution of genetic and epigenetic features. The Nucleome Data Bank aims to be a shared resource to biologists, biophysicists, and all genome scientists. The Nucleome Data Bank (NDB) is available at https://ndb.rice.edu.

bioinformatics↗

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

Modeling Mayaro and Chikungunya Control Strategies in Rio de Janeiro Outbreaks

Mosquito-borne diseases have become a significant health issue in many regions around the world. For tropical countries, diseases such as Dengue, Zika, and Chikungunya, became epidemic in the last decades. Health surveillance reports during this period were crucial in providing scientific-based information to guide decision making and resources allocation to control outbreaks. In this work, we perform data analysis of last Chikungunya epidemics in the city of Rio de Janeiro by applying a compartmental mathematical model. We estimate the \"basic reproduction number\" for those outbreaks and predict the potential epidemic outbreak of Mayaro virus. We also simulated several scenarios with different public interventions to decrease the number of infected people. Such scenarios should provide insights about possible strategies to control future outbreaks.

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 biophysical model of Epithelial-Mesenchymal Transition uncovers the frequency and size distribution of Circulating Tumor Cell clusters across cancer types

The gain of cellular motility via the epithelial-mesenchymal transition (EMT) is considered crucial in the metastatic cascade. Cells undergoing EMT to varying extents are launched into the bloodstream as single circulating tumor cells (CTCs) or multi-cellular clusters. The frequency and size distributions of these multi-cellular clusters has been recently measured, but the underlying mechanisms enabling these different modes of migration remain poorly understood. We present a biophysical model that couples the epithelial-mesenchymal phenotypic transition and cell migration to explain these different modes of cancer cell migration. With this reduced physical model, we identify a transition from individual migration to clustered cell migration that is regulated by the rate of EMT and the degree of cooperativity between cells during migration. This single cell to clustered migration transition can robustly recapitulate cluster size distributions observed experimentally across several cancer types, thus suggesting the existence of common features in the mechanisms of cell migration during metastasis. Furthermore, we identify three main mechanisms that can facilitate the formation and dissemination of large clusters: first, mechanisms that prevent a complete EMT and instead increase the population of hybrid Epithelial/Mesenchymal (E/M) cells; second, multiple intermediate E/M states that give rise to heterogeneous clusters formed by cells with different epithelial-mesenchymal traits; and third, non-cell-autonomous induction of EMT via cell-to-cell signaling that gives rise to spatial correlations among cells in a tissue. Overall, this biophysical model represents a first step toward bridging the gap between the molecular and biophysical understanding of EMT and various modes of cancer cell migration, and highlights that a complete EMT might not be required for metastasis. Popular summaryThe Epithelial-Mesenchymal Transition (EMT) has been identified as the first step that enables cancer metastases; through this process, cancer cells gain the motility necessary to migrate and invade. Cancer cells that undergo EMT can enter the circulatory system both as single cells or as multi-cellular clusters. While single cells are generally more frequent in human cancers, clusters are more prevalent in aggressive cancers that metastasize more. Although the molecular mechanisms of EMT are relatively conserved across cancers, how different cancers exhibit such tremendous variability in terms of cell migration remains unclear. We develop a biophysical model to investigate how EMT regulation at a single cell level can give rise to single cell and clustered cell migration. This model quantitatively reproduces size distributions of circulating tumor cell clusters reported in human circulation and mouse models, therefore identifying a unifying set of principles governing cell migration across different cancer types. Moreover, a model where cells only undergo a partial EMT to a hybrid epithelial/mesenchymal state can recapitulate different features observed in collective cancer cell migration, including the frequency of large clusters and flat distributions that cannot be captured by a model of complete EMT. Besides partial EMT, we propose additional mechanisms that can facilitate the formation of large tumor cell clusters, including multiple hybrid epithelial/mesenchymal cell states and signaling between cells that enables noncell autonomous EMT induction. Therefore, our general picture suggests universal traits in the migration of cancer cells and challenges the necessity of a complete EMT for cancer metastasis.

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

Towards Decoding the Metabolic Plasticity in Cancer: Coupling of Gene Regulation and Metabolic Pathways

Metabolic plasticity enables cancer cells to switch their metabolism phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) during tumorigenesis and metastasis. However, it is still largely unknown how cancer cells orchestrate gene regulation to balance their glycolysis and OXPHOS activities for better survival. Here, we establish a theoretical framework to model the coupling of gene regulation and metabolic pathways in cancer. Our modeling results demonstrate a direct association between the activities of AMPK and HIF-1, master regulators of OXPHOS and glycolysis respectively, with the activities of three metabolic pathways: glucose oxidation, glycolysis and fatty acid oxidation (FAO). Guided by the model, we develop metabolic pathway signatures to quantify the activities of glycolysis, FAO and the citric acid cycle of tumor samples by evaluating the expression levels of enzymes involved in corresponding processes. The association of AMPK/HIF-1 activity with metabolic pathway activity, predicted by the model and verified by analyzing the gene expression and metabolite abundance data of patient samples, is further validated by in vitro studies of aggressive triple negative breast cancer cell lines.

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↗

bioRxiv2018

NRF2 activates a partial Epithelial-Mesenchymal Transition and is maximally present in a hybrid Epithelial/Mesenchymal phenotype

The Epithelial-Mesenchymal Transition (EMT) is a key process implicated in cancer metastasis and therapy resistance. Recent studies have emphasized that cells can undergo partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype - a cornerstone of tumour aggressiveness and poor prognosis. These cells can have enhanced tumour-initiation potential as compared to purely epithelial or mesenchymal ones, and can integrate the properties of cell-cell adhesion and motility that facilitates collective cell migration leading to clusters of Circulating Tumour Cells (CTCs) - the prevalent mode of metastasis. Thus, identifying the molecular players that can enable cells to maintain a hybrid E/M phenotype is crucial to curb the metastatic load. Here, using an integrated computational-experimental approach, we show that the transcription factor NRF2 can prevent a complete EMT and instead stabilize a hybrid E/M phenotype. Knockdown of NRF2 in hybrid E/M non-small cell lung cancer cells H1975 drove progression to a completely mesenchymal phenotype at molecular and morphological levels. Notably, overexpression of NRF2 enriched for a hybrid E/M phenotype by simultaneously upregulating both E-cadherin and ZEB in RT4 bladder cancer cells. Further, we predict that NRF2 is maximally expressed in hybrid E/M phenotype(s) and demonstrate that this biphasic dynamic arises from the interconnections among NRF2 and the EMT regulatory circuit. Finally, clinical data from multiple datasets suggests a correlation between a hybrid E/M phenotype, high levels of NRF2 and its targets and poor survival, further strengthening the emerging notion that hybrid E/M phenotype(s) may occupy the metastatic sweet spot.

cancer biology↗