Comparative gene co-expression network analysis of epithelial to mesenchymal transition reveals lung cancer progression stages.

ABSTRACT:

Background

The epithelial to mesenchymal transition (EMT) plays a key role in lung cancer progression and drug resistance. The dynamics and stability of gene expression patterns as cancer cells transition from E to M at a systems level and relevance to patient outcomes are unknown.

Methods

Using comparative network and clustering analysis, we systematically analyzed time-series gene expression data from lung cancer cell lines H358 and A549 that were induced to undergo EMT. We also predicted the putative regulatory networks controlling EMT expression dynamics, especially for the EMT-dynamic genes and related these patterns to patient outcomes using data from TCGA. Example EMT hub regulatory genes were validated using RNAi.

Results

We identified several novel genes dist

SUBMITTER: Wang D 

PROVIDER: S-EPMC5719936 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature