Survival Outcomes in Cancer Patients Predicted by a Partial EMT Gene Expression Scoring Metric

Abstract

Metastasis is a significant contributor to morbidity and mortality for many cancer patients and remains a major obstacle for effective treatment. In many tissue types, metastasis is fueled by the epithelial-to-mesenchymal transition (EMT) - a dynamic process characterized by phenotypic and morphologic changes concomitant with increased migratory and invasive potential. Recent experimental and theoretical evidence suggests that cells can be stably halted en route to EMT in a hybrid E/M phenotype. Cells in this phenotype tend to move collectively, forming clusters of circulating-tumor-cells that are key tumor-initiating agents. Here, we developed an inferential model built on the gene expression of multiple cancer subtypes to devise an EMT metric that characterizes the degree to which a given cell line exhibits hybrid E/M features. Our model identified drivers and fine-tuners of epithelial-mesenchymal plasticity and recapitulated the behavior observed in multiple in vitro experiments across cancer types. We also predicted and experimentally validated the hybrid E/M status of certain cancer cell lines, including DU145 and A549. Lastly, we demonstrated the relevance of predicted EMT scores to patient survival and observed that the role of the hybrid E/M phenotype in characterizing tumor aggressiveness is tissue- and subtype-specific. Our algorithm is a promising tool to quantify the EMT spectrum, to investigate the correlation of EMT score with cancer treatment response and survival, and to provide an important metric for systematic clinical risk stratification and treatment.

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

“…6B-D), when these samples are divided by median. We further calculated the 'EMT score' for all these patients' gene expression profiles using an inferential parameter developed by George et al [24] based on the expression level of several key EMT regulators. These scores are calculated on a scale of 0 (highly epithelial) to 2 (highly mesenchymal), with the following categorization: epithelial (0<score<0.5), hybrid E/M (0.5<score<1.5) or mesenchymal (1.5<score<2).…”

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

“…It consequently calculates the probability that given sample belongs to epithelial, mesenchymal, or hybrid E/M categories. An EMT score is assigned based on those probabilities; the higher the score, the more mesenchymal the sample is (George et al, 2017). A comparative analysis of these methods in terms of similarities, differences, strengths, and limitations, remains to be done.…”

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

“…7). Thus, counterintuitive to the long-standing paradigm, mechanisms that inhibit a complete EMT and instead stabilize hybrid E/M state(s) might bear a higher metastatic potential (27,28,59). Future investigations should therefore focus on identifying the molecular mechanisms that drive a progression to a mesenchymal state or maintain a partial EMT instead.…”