Identification of phenotype-specific networks from paired gene expression-cell shape imaging data.

ABSTRACT: The morphology of breast cancer cells is often used as an indicator of tumor severity and prognosis. Additionally, morphology can be used to identify more fine-grained, molecular developments within a cancer cell, such as transcriptomic changes and signaling pathway activity. Delineating the interface between morphology and signaling is important to understand the mechanical cues that a cell processes in order to undergo epithelial-to-mesenchymal transition and consequently metastasize. However, the exact regulatory systems that define these changes remain poorly characterized. In this study, we used a network-systems approach to integrate imaging data and RNA-seq expression data. Our workflow allowed the discovery of unbiased and context-specific gene expression signatures and cell signal

SUBMITTER: Barker CG 

PROVIDER: S-EPMC8997347 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature