An epithelial-mesenchymal transition-related prognostic model for colorectal cancer based on weighted gene co-expression network analysis.

ABSTRACT:

Objective

To identify susceptibility modules and genes for colorectal cancer (CRC) using weighted gene co-expression network analysis (WGCNA).

Methods

Four microarray datasets were downloaded from the Gene Expression Omnibus database. We divided the tumor samples into three subgroups based on consensus clustering of gene expression, and analyzed the correlations between the subgroups and clinical features. The genetic features of the subgroups were investigated by gene set enrichment analysis (GSEA). A gene expression network was constructed using WGCNA, and a protein-protein interaction (PPI) network was used to identify the key genes. Gene modules were annotated by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses.

Results

We divided the

SUBMITTER: Zhang L 

PROVIDER: S-EPMC9751178 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature