A 65‑gene signature for prognostic prediction in colon adenocarcinoma.

ABSTRACT: The aim of the present study was to examine the molecular factors associated with the prognosis of colon cancer. Gene expression datasets were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases to screen differentially expressed genes (DEGs) between colon cancer samples and normal samples. Survival‑related genes were selected from the DEGs using the Cox regression method. A co‑expression network of survival‑related genes was then constructed, and functional clusters were extracted from this network. The significantly enriched functions and pathways of the genes in the network were identified. Using Bayesian discriminant analysis, a prognostic prediction system was established to distinguish the positive from negative prognostic samples. The discrimination

SUBMITTER: Jiang H 

PROVIDER: S-EPMC5810222 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature