Prognostic marker identification based on weighted gene co-expression network analysis and associated in vitro confirmation in gastric cancer

• Main Authors: Haonan Guo, Jun Yang, Shanshan Liu, Tao Qin, Qianwen Zhao, Xianliang Hou, Lei Ren
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2021-01-01
• Series: Bioengineered
• Subjects: gastric cancer; wgcna; cemip; prognostic biomarker; tumor infiltration
• Online Access: http://dx.doi.org/10.1080/21655979.2021.1957645

The aim of this study was to explore the potential molecular mechanisms of Gastric cancer (GC) and identify new prognostic markers for GC. RNA sequencing data were downloaded from the Gene Expression Omnibus database, and 418 differentially expressed genes (DEGs) were screened. Weighted correlation network analysis (WGCNA) was performed to identify six hub modules related to the clinical features of GC. Cytoscape software was used to identify five hub genes in the co-expression network, including CST1, CEMIP, COL8A1, PMEPA1, and MSLN. The TCGA database was used to verify hub gene expression in GC. The overall survival in the high CEMIP expression group was significantly lower than that of patients in the low CEMIP expression group. CEMIP expression was also found to be negatively correlated with B cell and CD4 + T cell infiltration. Further, associated in vitro experiments confirmed that CEMIP downregulation suppressed the proliferation and migration of GC cells and impaired the chemoresistance of GC cells to 5-fluorouracil. Our study effectively identified and validated prognostic biomarkers for GC, laying a new foundation for the therapeutic target, occurrence, and development of gastric cancer.