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Epithelial-mesenchymal transition (EMT) is a developmental cell state transition co-opted by cancer to drive metastasis and resistance. Stable EMT intermediate states play a particularly important role in cell state plasticity and confer metastatic potential. To explore the dynamics of EMT and identify marker genes of highly metastatic intermediate cells, we analyzed EMT across multiple tumor types and stimuli via mathematical modeling with single-cell RNA-sequencing (scRNA-seq) data. We identified pan-cancer genes consistently expressed or upregulated in EMT intermediate states, most of which were not previously annotated as markers of EMT. Using Bayesian parameter inference, we fit a simple mathematical model to scRNA-seq data, revealing tumor-specific transition rates. This mathematical model offers a framework to quantify EMT progression. A consensus analysis of differential intermediate expression, regulation, and model-derived dynamics identified marker genes associated with persistence of the intermediate EMT state. SFN and NRG1 emerged as genes with the strongest evidence for their role influencing intermediate EMT dynamics. Through analysis of an independent cell line, we verified the role of SFN as a marker intermediate EMT transition. Modeling and inference of genes associated with EMT dynamics offer means to find biomarkers and to identify therapeutic approaches to harness or reverse tumor-promoting cell state transitions driven by EMT.
McDermott et al. (Fri,) studied this question.