Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis

• Main Authors: Zhaoxing Li, Zhao Liu, Zhiting Shao, Chuang Li, Yong Li, Qingwei Liu, Yifei Zhang, Bibo Tan, Yu Liu
• Format: Article
• Language: English
• Published: PeerJ Inc. 2020-05-01
• Series: PeerJ
• Subjects: Gastric cancer; Bioinformatics; Survival; Biomarker
• Online Access: https://peerj.com/articles/9123.pdf

Background Gastric cancer is one of the most common malignant cancers worldwide. Despite substantial developments in therapeutic strategies, the five-year survival rate remains low. Therefore, novel biomarkers and therapeutic targets involved in the progression of gastric tumors need to be identified. Methods We obtained the mRNA microarray datasets GSE65801, GSE54129 and GSE79973 from the Gene Expression Omnibus database to acquire differentially expressed genes (DEGs). We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to analyze DEG pathways and functions, and the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape to obtain the protein–protein interaction (PPI) network. Next, we validated the hub gene expression levels using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA), and conducted stage expression and survival analysis. Results From the three microarray datasets, we identified nine major hub genes: COL1A1, COL1A2, COL3A1, COL5A2, COL4A1, FN1, COL5A1, COL4A2, and COL6A3. Conclusion Our study identified COL1A1 and COL1A2 as potential gastric cancer prognostic biomarkers.