Identification of clinically predictive metagenes that encode components of a network coupling cell shape to transcription by image-omics.

ABSTRACT: The associations between clinical phenotypes (tumor grade, survival) and cell phenotypes, such as shape, signaling activity, and gene expression, are the basis for cancer pathology, but the mechanisms explaining these relationships are not always clear. The generation of large data sets containing information regarding cell phenotypes and clinical data provides an opportunity to describe these mechanisms. Here, we develop an image-omics approach to integrate quantitative cell imaging data, gene expression, and protein-protein interaction data to systematically describe a "shape-gene network" that couples specific aspects of breast cancer cell shape to signaling and transcriptional events. The actions of this network converge on NF-κB, and support the idea that NF-κB is responsive to mechan

SUBMITTER: Sailem HZ 

PROVIDER: S-EPMC5287226 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature