Bioinformatics Analysis Identifies a Novel Role of Gene in Colorectal Cancer.

Background: Colorectal cancer (CRC) is one of the most lethal malignancies and the incidence of CRC has been on the rise. Herein, we aimed to identify effective biomarkers for early diagnosis and treatment of colorectal cancer via bioinformatic tools.

Methods: To identify differentially expressed genes (DEGs) in CRC, we downloaded CRC gene expression data from GSE24514 and GSE110223 datasets in Gene Expression Omnibus (GEO) and employed R to analyze the data. We further performed functional enrichment analysis of the DEGs on the DAVID gene ontology analysis tool. STRING database and Cytoscape visualization tool were employed to construct a PPI (protein-protein interaction) network and establish intensive intervals in the network. Immunohistochemistry, qRT-PCR and Western blotting were performed to identify the expression level of in CRC. In vitro and in vivo experiments were performed to assess the impact of in the pathogenesis of CRC in terms of proliferation, migration and metastasis.

Results: Among the two datasets, 389 DEGs were identified and used to construct a PPI network. These genes were mainly involved in cell proliferation and cell cycle. Among them, 15 genes including were found to be strongly associated with the PPI network. We further performed immunohistochemistry, qRT-PCR and Western blotting to identify that expression was higher in CRC than in paired normal tissues. Moreover, in vitro and in vivo experiments demonstrated could promote the proliferation, invasion and migration of colorectal cancer cells.

Conclusions: could be considered as a potential biomarker for CRC patients.