Gene expression analysis of colorectal cancer by bioinformatics strategy.

Objective: We used bioinformatics technology to analyze gene expression profiles involved in colorectal cancer tissue samples and healthy controls.

Methods: In this paper, we downloaded the gene expression profile GSE4107 from Gene Expression Omnibus (GEO) database, in which a total of 22 chips were available, including normal colonic mucosa tissue from normal healthy donors (n=10), colorectal cancer tissue samples from colorectal patients (n=33). To further understand the biological functions of the screened DGEs, the KEGG pathway enrichment analysis were conducted. Then we built a transcriptome network to study differentially co-expressed links.

Results: A total of 3151 DEGs of CRC were selected. Besides, total 164 DCGs (Differentially Coexpressed Gene, DCG) and 29279 DCLs (Differentially Co-expressed Link, DCL) were obtained. Furthermore, the significantly enriched KEGG pathways were Endocytosis, Calcium signaling pathway, Vascular smooth muscle contraction, Linoleic acid metabolism, Arginine and proline metabolism, Inositol phosphate metabolism and MAPK signaling pathway.

Conclusions: Our results show that the generation of CRC involves multiple genes, TFs and pathways. Several signal and immune pathways are linked to CRC and give us more clues in the process of CRC. Hence, our work would pave ways for novel diagnosis of CRC, and provided theoretical guidance into cancer therapy.