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. Understanding EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing (scRNA-seq) 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 com

SUBMITTER: Najafi A 

PROVIDER: S-EPMC10329148 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature