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Colon cancer is one of the most commonly diagnosed malignancies and is a leading cause of cancer‑associated mortality. The aim of the present study was to investigate the molecular mechanisms underlying colon cancer and identify potentially significant genes associated with the disease using weighted gene co‑expression network analysis (WGCNA). The test datasets used were downloaded from The Cancer Genome Atlas (TCGA) database. WGCNA was applied to analyze microarray data obtained from colon adenocarcinoma samples to identify significant modules and highly associated genes. A gene co‑expression network was constructed and different gene modules were selected. Functional and pathway enrichment analyses were performed to investigate the molecular mechanisms of colon cancer. In addition, highly connected hub genes associated with the most significant module were selected for further analysis. Nine specific modules associated with colon cancer were identified, of which the turquoise module was observed to exhibit the greatest association with the disease. Pathway enrichment analysis of the turquoise module suggested that genes in the turquoise module were associated with 'RNA polymerase' and 'purine metabolism'. Furthermore, gene ontology enrichment analysis revealed the top 30 hub genes with a higher degree in the turquoise module, such as σ‑non‑opioid intracellular receptor 1, transmembrane protein 147  TMEM147) and carbamoyl‑phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase, were predominantly enriched in the biological processes 'translation' and 'gene expression'. Experimental verification demonstrated that the expression of TMEM147 in colon cancer was significantly increased compared with the control. Therefore, the results suggested that genes associated with RNA polymerase and the purine metabolic pathways may be substantially involved in the pathogenesis of colon cancer. Furthermore, TMEM147 may represent a biomarker for colon cancer.

Identification of specific modules and significant genes associated with colon cancer by weighted gene co‑expression network analysis