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Archive > Volume 27 Issue 8 > 2020,27(8):903-910. DOI:10.3872/j.issn.1007-385X.2020.08.011 Prev Next
Clinical Research
Screening of molecular markers in gastric cancer based on GEO database
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Abstract:
Objective: Bioinformatics combined with Gene Expression Omnibus (GEO) was used to screen key genes involved in the development of gastric cancer in order to obtain molecular markers for diagnosis, target selection and prognosis prediction of gastric cancer. Methods:Thechipdatasetsrelatedtogastriccancer(GC)fromtheGEOdatabase were downloaded, and differentially expressed genes (DEG) were screened. Functional enrichment analysis on DEG was performed, and protein-protein interaction network (PPI) was constructed to screenkeygenes.Then,co-expressionnetworkswerefurtherconstructed,andsurvival curves were drawn and hierarchical clustering analysis was performed. Results: A total of 261 GC-related DEGs were selected, and 14 key genes were obtained through analysis, which were PLOD1, PLOD3, COL1A1, COL1A2, COL2A1, COL3A1, COL4A1, COL4A2, COL8A1, COL12A1, COL15A1, ITGA2, LUM and SERPINH1. Key genes are mainly involved in biological processes such as generation of collagen fiber tissues, extracellular matrix tissues, extracellular structure tissues, skin morphogenesis, collagen biosynthesis and vascular development. Survival curve analysis showed that the change in the expression of COL3A1 (P=0.0241) significantly reduced the overall survival rate of patients with gastric cancer; the change in the expression of ITGA2 (P=0.0679) also showed a correlation with the reduction of diseasefree survival in gastric cancer patients. Compared with normal gastric tissues, hierarchical cluster analysis showed that the expressions of genes PLOD1, PLOD3, COL3A1, ITGA2, COL1A2, COL1A1, COL4A1, LUM, COL12A1, SERPINH1 and COL8A1 in GC tissues were up-regulated. Conclusion: The key genes obtained after screening can be used as potential molecular markers for early diagnosis, treatment target selection and prognosis judgment of gastric cancer, which provide reference for subsequent research.
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Project Supported:
Project supported by the Natural Science Foundation of Shanxi Province (No. 201901D111412, 201901D111232), and the Graduate Education Innovation Project of Shanxi Province (No.2020SY197)
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