Population Dynamics of EMT Elucidates the Timing and Distribution of Phenotypic Intra-tumoral Heterogeneity

Abstract

The Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of cancer metastasis and morbidity. EMT is a non-binary process, and cells can be stably arrested en route to EMT in an intermediate hybrid state associated with enhanced tumor aggressiveness and worse patient outcomes. Understand- ing EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing data that enable in-depth analyses of EMT at the single-cell resolution, current inferential approaches are limited to bulk microarray data. There is thus a great need for computational frameworks to systematically infer and predict the timing and distribution of EMT-related states at single-cell resolution. Here, we develop a computational framework for reliable inference and prediction of EMT-related trajectories from single-cell RNA sequencing data. Our model can be utilized across a variety of applications to predict the timing and distribution of EMT from single-cell sequencing data.

Cell-state transitions and frequency-dependent interactions among subpopulations together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity in breast cancer

“…Nonetheless, with limited experimental data and different assays, we were able to narrow down to mechanisms that could explain E-M population dynamics observed in PMC42-LA and HCC38 cells, and establish the necessity of cell-state transition in determining these dynamics. Future longitudinal experimental data using more than one surface or molecular marker to classify phenotypic heterogeneity (for instance, E-cadherin and Vimentin) will facilitate characterizing and isolating the more plastic hybrid E/M phenotypes and their contribution to population dynamics 5,13,[44][45][46][47][48] .…”

Molecular mechanism underlying epithelial‐mesenchymal transformation and cisplatin resistance in esophageal squamous cell carcinoma

“…However, attempts to identify recurrent mutations in the metastatic cell genome have failed. These failures are experienced at a time when genome sequencing and bioinformatic techniques have become extremely powerful, suggesting that multiple steps in the invasion‐metastasis cascade can be largely driven by nongenetic processes, especially EMT programs in the case of the cancer 19 . Nevertheless, there is little clear experimental evidence on the role of EMT programs in transfer formation.…”