Comparative Study of Transcriptomics-Based Scoring Metrics for the Epithelial-Hybrid-Mesenchymal Spectrum.
ABSTRACT: 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 the immune system. Recent in silico, in vitro, and in vivo evidence indicates that EMT is not an all-or-none process; instead, cells can stably acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes which often can be more aggressive than purely E or M 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 can 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 E and 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.
Project description:Epithelial-to-mesenchymal transition (EMT) is a key process associated with tumor progression and metastasis. To define molecular features associated with EMT states, we undertook an integrative approach combining mRNA, miRNA, DNA methylation, and proteomic profiles of 38 cell populations representative of the genomic heterogeneity in lung adenocarcinoma. The resulting data were integrated with functional profiles consisting of cell invasiveness, adhesion, and motility. A subset of cell lines that were readily defined as epithelial or mesenchymal based on their morphology and E-cadherin and vimentin expression elicited distinctive molecular signatures. Other cell populations displayed intermediate/hybrid states of EMT, with mixed epithelial and mesenchymal characteristics. A dominant proteomic feature of aggressive hybrid cell lines was upregulation of cytoskeletal and actin-binding proteins, a signature shared with mesenchymal cell lines. Cytoskeletal reorganization preceded loss of E-cadherin in epithelial cells in which EMT was induced by TGF?. A set of transcripts corresponding to the mesenchymal protein signature enriched in cytoskeletal proteins was found to be predictive of survival in independent datasets of lung adenocarcinomas. Our findings point to an association between cytoskeletal and actin-binding proteins, a mesenchymal or hybrid EMT phenotype and invasive properties of lung adenocarcinomas.
Project description:According to the sequential metastasis model, aggressive mesenchymal (M) metastasis-initiating cells (MICs) are generated by an epithelial-mesenchymal transition (EMT) which eventually is reversed by a mesenchymal-epithelial transition (MET) and outgrowth of life-threatening epithelial (E) macrometastases. Paradoxically, in breast cancer M signatures are linked with more favorable outcomes than E signatures, and M cells are often dispensable for metastasis in mouse models. Here we present evidence at the cellular and patient level for the cooperation metastasis model, according to which E cells are MICs, while M cells merely support E cell persistence through cooperation. We tracked the fates of co-cultured E and M clones and of fluorescent CDH1-promoter-driven cell lines reporting the E state derived from basal breast cancer HMLER cells. Cells were placed in suspension state and allowed to reattach and select an EMT cell fate. Flow cytometry, single cell and bulk gene expression analyses revealed that only pre-existing E cells generated E cells, mixed E/M populations, or stem-like hybrid E/M cells after suspension and that complete EMT manifest in M clones and CDH1-negative reporter cells resulted in loss of cell plasticity, suggesting full transdifferentiation. Mechanistically, E-M coculture experiments supported the persistence of pre-existing E cells where M cells inhibited EMT of E cells in a mutual cooperation via direct cell-cell contact. Consistently, M signatures were associated with more favorable patient outcomes compared to E signatures in breast cancer, specifically in basal breast cancer patients. These findings suggest a potential benefit of complete EMT for basal breast cancer patients.
Project description:<h4>Background</h4>The epithelial-mesenchymal transition (EMT) enables dissociation of tumour cells from the primary tumour mass, invasion through the extracellular matrix, intravasation into blood vessels and colonisation of distant organs. Cells that revert to the epithelial state via the mesenchymal-epithelial transition cause metastases, the primary cause of death in cancer patients. EMT also empowers cancer cells with stem-cell properties and induces resistance to chemotherapeutic drugs. Understanding the driving factors of EMT is critical for the development of effective therapeutic interventions.<h4>Methods</h4>This manuscript describes the generation of a database containing EMT gene signatures derived from cell lines, patient-derived xenografts and patient studies across cancer types and multiomics data and the creation of a web-based portal to provide a comprehensive analysis resource.<h4>Results</h4>EMTome incorporates (i) EMT gene signatures; (ii) EMT-related genes with multiomics features across different cancer types; (iii) interactomes of EMT-related genes (miRNAs, transcription factors, and proteins); (iv) immune profiles identified from The Cancer Genome Atlas (TCGA) cohorts by exploring transcriptomics, epigenomics, and proteomics, and drug sensitivity and (iv) clinical outcomes of cancer cohorts linked to EMT gene signatures.<h4>Conclusion</h4>The web-based EMTome portal is a resource for primary and metastatic tumour research publicly available at www.emtome.org .
Project description:Cancer cells undergoing epithelial-mesenchymal transition (EMT) acquire stem cell-like phenotype associated with malignant behaviour, chemoresistance, and relapse. Current two-dimensional (2D) in-vitro culture models of tumorigenesis are inadequate to replicate the complexity of in-vivo microenvironment. Therefore, the generation of functional three-dimensional (3D) constructs is a fundamental prerequisite to form multi-cellular tumour spheroids for studying basic pathological mechanisms. In this study, we focused on two major points (i) designing and fabrication of 3D hybrid scaffolds comprising electrospun fibers with cancer cells embedded within hydrogels, and (ii) determining the potential roles of 3D hybrid scaffolds associated with EMT in cancer progression and metastasis. Our findings revealed that 3D hybrid scaffold enhances cell proliferation and induces cancer cells to undergo EMT, as demonstrated by significant up-regulation of EMT associated transcriptional factors including Snail1, Zeb1, and Twist2; and mesenchymal markers whereas epithelial marker, E-Cadherin was downregulated. Remarkably, this induction is independent of cancer cell-type as similar results were obtained for breast cancer cells, MDA-MB-231 and gastric cancer cells, MKN74. Moreover, the hybrid scaffolds enrich aggressive cancer cells with stem cell properties. We showed that our 3D scaffolds could trigger EMT of cancer cells which could provide a useful model for studying anticancer therapeutics against metastasis.
Project description:Systemic inflammation may increase risk for prostate cancer progression, but the role it plays in prostate cancer susceptibility is unknown. From a cohort of over 10,000 men who had either a prostate biopsy or transurethral resection that yielded a benign finding, we analyzed 517 incident prostate cancer cases identified during follow-up and 373 controls with one or more white blood cell tests during a follow-up period between one and 18 years. Multilevel, multivariable longitudinal models were fit to two measures of systemic inflammation, neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR), to determine NLR and MLR trajectories associated with increased risk for prostate cancer. For both measures, we found no significant differences in the trajectories by case/control status, however in modeling NLR trajectories there was a significant interaction between race (white or Black and case-control status. In race specific models, NLR and MLR values were consistently higher over time among white controls than white cases while case-control differences in NLR and MLR trajectories were not apparent among Black men. When cases were classified as aggressive as compared to non-aggressive, the case-control differences in NLR and MLR values over time among white men were most apparent for non-aggressive cases. For NLR among white men, significant case-control differences were observed for the entire duration of observation for men who had inflammation in their initial prostate specimen. It is possible that, among white men, monitoring of NLR and MLR trajectories after an initial negative biopsy may be useful in monitoring prostate cancer risk.
Project description:Epithelial-to-Mesenchymal Transition (EMT) and its reverse - Mesenchymal to Epithelial Transition (MET) - are hallmarks of cellular plasticity during embryonic development and cancer metastasis. During EMT, epithelial cells lose cell-cell adhesion and gain migratory and invasive traits either partially or completely, leading to a hybrid epithelial/mesenchymal (hybrid E/M) or a mesenchymal phenotype respectively. Mesenchymal cells move individually, but hybrid E/M cells migrate collectively as observed during gastrulation, wound healing, and the formation of tumor clusters detected as Circulating Tumor Cells (CTCs). Typically, the hybrid E/M phenotype has largely been tacitly assumed to be transient and 'metastable'. Here, we identify certain 'phenotypic stability factors' (PSFs) such as GRHL2 that couple to the core EMT decision-making circuit (miR-200/ZEB) and stabilize hybrid E/M phenotype. Further, we show that H1975 lung cancer cells can display a stable hybrid E/M phenotype and migrate collectively, a behavior that is impaired by knockdown of GRHL2 and another previously identified PSF - OVOL. In addition, our computational model predicts that GRHL2 can also associate hybrid E/M phenotype with high tumor-initiating potential, a prediction strengthened by the observation that the higher levels of these PSFs may be predictive of poor patient outcome. Finally, based on these specific examples, we deduce certain network motifs that can stabilize the hybrid E/M phenotype. Our results suggest that partial EMT, i.e. a hybrid E/M phenotype, need not be 'metastable', and strengthen the emerging notion that partial EMT, but not necessarily a complete EMT, is associated with aggressive tumor progression.
Project description:Epithelial-mesenchymal transition (EMT), the conversion between rigid epithelial cells and motile mesenchymal cells, is a reversible cellular process involved in tumorigenesis, metastasis, and chemoresistance. Numerous studies have found that several types of tumor cells show a high degree of cell-to-cell heterogeneity in terms of their gene expression signatures and cellular phenotypes related to EMT. Recently, the prevalence and importance of partial or intermediate EMT states have been reported. It is unclear, however, whether there is a general pattern of cancer cell distribution in terms of the overall expression of epithelial-related genes and mesenchymal-related genes, and how this distribution is related to EMT process in normal cells. In this study, we performed integrative transcriptomic analysis that combines cancer cell transcriptomes, time course data of EMT in non-tumorigenic epithelial cells, and epithelial cells with perturbations of key EMT factors. Our statistical analysis shows that cancer cells are widely distributed in the EMT spectrum, and the majority of these cells can be described by an EMT path that connects the epithelial and the mesenchymal states via a hybrid expression region in which both epithelial genes and mesenchymal genes are highly expressed overall. We found that key patterns of this EMT path are observed in EMT progression in non-tumorigenic cells and that transcription factor ZEB1 plays a key role in defining this EMT path via diverse gene regulatory circuits connecting to epithelial genes. We performed Gene Set Variation Analysis to show that the cancer cells at hybrid EMT states also possess hybrid cellular phenotypes with both high migratory and high proliferative potentials. Our results reveal critical patterns of cancer cells in the EMT spectrum and their relationship to the EMT process in normal cells, and provide insights into the mechanistic basis of cancer cell heterogeneity and plasticity.
Project description:Epithelial-mesenchymal transition (EMT) and cancer stem cell (CSCs) formation are two fundamental and well-studied processes contributing to cancer metastasis and tumor relapse. Cells can undergo a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype or a complete EMT to attain a mesenchymal one. Similarly, cells can reversibly gain or lose 'stemness'. This plasticity in cell states is modulated by signaling pathways such as Notch. However, the interconnections among the cell states enabled by EMT, CSCs and Notch signaling remain elusive. Here, we devise a computational model to investigate the coupling among the core decision-making circuits for EMT, CSCs and Notch. Our model predicts that hybrid E/M cells are most likely to associate with stem-like traits and enhanced Notch-Jagged signaling - a pathway implicated in therapeutic resistance. Further, we show that the position of the 'stemness window' on the 'EMT axis' is varied by altering the coupling strength between EMT and CSC circuits, and/or modulating Notch signaling. Finally, we analyze the gene expression profile of CSCs from several cancer types and observe a heterogeneous distribution along the 'EMT axis', suggesting that different subsets of CSCs may exist with varying phenotypes along the epithelial-mesenchymal axis. We further investigate therapeutic perturbations such as treatment with metformin, a drug associated with decreased cancer incidence and increased lifespan of patients. Our mechanism-based model explains how metformin can both inhibit EMT and blunt the aggressive potential of CSCs simultaneously, by driving the cells out of a hybrid E/M stem-like state with enhanced Notch-Jagged signaling.
Project description:Circulating tumour cells (CTCs) can provide valuable prognostic information in a number of epithelial cancers. However, their detection is hampered due to their molecular heterogeneity, which can be induced by the epithelial-mesenchymal transition (EMT) process. Therefore, current knowledge about CTCs from clinical samples is often limited due to an inability to isolate wide spectrum of CTCs phenotypes. In the current work, we aimed at isolation and molecular characterization of CTCs with different EMT status in order to establish their clinical significance in early breast cancer patients. We have obtained CTCs-enriched blood fraction from 83 breast cancer patients in which we have tested the expression of epithelial, mesenchymal and general breast cancer CTCs markers (<i>MGB1/HER2/CK19/CDH1/CDH2/VIM/PLS3</i>), cancer stem cell markers (<i>CD44</i>, <i>NANOG</i>, <i>ALDH1</i>, <i>OCT-4</i>, <i>CD133</i>) and cluster formation gene (plakoglobin). We have shown that in the CTCs-positive patients, epithelial, epithelial-mesenchymal and mesenchymal CTCs markers were detected at a similar rate (in 28%, 24% and 24%, respectively). Mesenchymal CTCs were characterized by the most aggressive phenotype (significantly higher expression of <i>CXCR4</i>, <i>uPAR</i>, <i>CD44</i>, <i>NANOG</i>, <i>p</i> < 0.05 for all), presence of lymph node metastases (<i>p</i> = <i>0.043</i>), larger tumour size (<i>p = 0.023</i>) and 7.33 higher risk of death in the multivariate analysis (95% CI 1.06?50.41, <i>p = 0.04</i>). Epithelial-mesenchymal subtype, believed to correspond to highly plastic and aggressive state, did not show significant impact on survival. Gene expression profile of samples with epithelial-mesenchymal CTCs group resembled pure epithelial or pure mesenchymal phenotypes, possibly underlining degree of EMT activation in particular patient's sample. Molecular profiling of CTCs EMT phenotype provides more detailed and clinically informative results, proving the role of EMT in malignant cancer progression in early breast cancer.
Project description: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 also show how 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.