Objective  To screen biomarkers for the clinical diagnosis and prognosis of gastric cancer.

Methods  Download the clinical information and mRNA expression data of gastirc cancer from the TCGA database and screen differentially expressed genes by R software and Bioconductor sofware. Using GO analysis, KEGG enrichment analysis and protein interaction network analysis to further determine the core dif-ferential genes. Analyze the survival analysis of core genes in gastric cancer and their role in survival time and clinical staging. Volcano map and heat map further determine the degree of COL1A1, COMP's influence on the transcriptome.

Results  It is found that the suivival prognosis of gastic cancer patients with low expression of COL1A1 and COMP gene was significantly better than that of the high expression group. In a subgroup analysis based on the staging of gastric cancer, although the transcript levels of COL1A1 and COMP were not significantly different in stages 1 and 2, the transcript levels of COL1A1 in stage 3 and 4 GC patients were higher than that in healthy people. Fur-thermore, the main enrichment of volcano plots and heat map suggested positive as-sociation with COL1A1 and COMP genes is in terms of cell aggregation function. Conclu-sion  This research reveals that the expression and potential regulatory network of COL1A1 and COMP in gastric cancer lays the foundation for further research on the role of COL1A1 and COMP in the process of carcinogenesis. The expression of COL1A1, COMP is expected to be a potential diagnostic index for gastric cancer.

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