COL1A2 is a Novel Biomarker to Improve Clinical Prediction in Human Gastric Cancer: Integrating Bioinformatics and Meta-Analysis

Abstract

Gastric cancer is the third most common cause of cancer-related death in worldwide. It is crucial to target the key genes controlling pathogenesis in the early stage of gastric cancer. This study describes an integrated bioinformatics to identify molecular biomarkers for gastric cancer in patients' cancer tissues. We reports differently expression genes in large gastric cancer cohorts from Gene Expression Ominus (GEO). Our findings revealed that 433 genes were significantly different expressed in human gastric cancer. Differently expression gene profile in gastric cancer was further validated by bioinformatic analyses, co-expression network construction. Based on the co-expression network and top-ranked genes, we identified collagen type I alpha 2 (COL1A2) which encodes the pro-alpha2 chain of type I collagen whose triple helix comprises two alpha1 chains and one alpha2 chain, was the key gene in a 37-gene network that modulates cell motility by interacting with the cytoskeleton. Furthermore, the prognostic role of COL1A2 was determined by use of immunohistochemistry on human gastric cancer tissue. COL1A2 was highly expressed in human gastric cancer as compared with normal gastric tissues. Statistical analysis showed COL1A2 expression level was significantly associated with histological type and lymph node status. However, there were no correlations between COL1A2 expression and age, lymph node numbers, tumor size, or clinical stage. In conclusion, the novel bioinformatics used in this study has led to identification of improving diagnostic biomarkers for human gastric cancer and could benefit further analyses of the key alteration during its progression.

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