Weighted correlation network analysis identifies FN1, COL1A1 and SERPINE1 associated with the progression and prognosis of gastric cancer

Article type: Research Article

Authors: Zhao, Qiaoyun^{a; 1} | Xie, Jun^{a; 1} | Xie, Jinliang^a | Zhao, Rulin^a | Song, Conghua^a | Wang, Huan^a | Rong, Jianfang^a | Yan, Lili^b | Song, Yanping^a | Wang, Fangfei^a | Xie, Yong^{a; *}

Affiliations: [a] Department of Gastroenterology, First Affiliated Hospital of Nanchang University, Donghu District, Nanchang, Jiangxi, China | [b] Laboratory of Biochemistry and Molecular Biology, Jiangxi Institute of Medical Sciences, Donghu District, Nanchang, Jiangxi, China

Correspondence: [*] Corresponding author: Yong Xie, Department of Gastroenterology, First Affiliated Hospital of Nanchang University, No.17 Yongwaizheng Street, Donghu District, Nanchang, Jiangxi 330006, China. Tel.: +86 131 7789 3950; E-mail: [email protected].

Note: [1] Equal contribution.

Abstract: BACKGROUND: Gastric cancer (GC) is one of the most deadliest tumours worldwide, and its prognosis remains poor. OBJECTIVE: This study aims to identify and validate hub genes associated with the progression and prognosis of GC by constructing a weighted correlation network. METHODS: The gene co-expression network was constructed by the WGCNA package based on GC samples and clinical data from the TCGA database. The module of interest that was highly related to clinical traits, including stage, grade and overall survival (OS), was identified. GO and KEGG pathway enrichment analyses were performed using the clusterprofiler package in R. Cytoscape software was used to identify the 10 hub genes. Differential expression and survival analyses were performed on GEPIA web resources and verified by four GEO datasets and our clinical gastric specimens. The receiver operating characteristic (ROC) curves of hub genes were plotted using the pROC package in R. The potential pathogenic mechanisms of hub genes were analysed using gene set enrichment analysis (GSEA) software. RESULTS: A total of ten modules were detected, and the magenta module was identified as highly related to OS, stage and grade. Enrichment analysis of magenta module indicated that ECM-receptor interaction, focal adhesion, PI3K-Akt pathway, proteoglycans in cancer were significantly enriched. The PPI network identified ten hub genes, namely COL1A1, COL1A2, FN1, POSTN, THBS2, COL11A1, SPP1, MMP13, COMP, and SERPINE1. Three hub genes (FN1, COL1A1 and SERPINE1) were finally identified to be associated with carcinogenicity and poor prognosis of GC, and all were independent risk factors for GC. The area under the curve (AUC) values of FN1, COL1A1 and SERPINE1 for the prediction of GC were 0.702, 0.917 and 0.812, respectively. GSEA showed that three hub genes share 15 common upregulated biological pathways, including hypoxia, epithelial mesenchymal transition, angiogenesis, and apoptosis. CONCLUSION: We identified FN1, COL1A1 and SERPINE1 as being associated with the progression and poor prognosis of GC.

Keywords: WGCNA, gastric cancer, progression, prognosis, hub genes, prediction, diagnosis

DOI: 10.3233/CBM-200594

Journal: Cancer Biomarkers, vol. 31, no. 1, pp. 59-75, 2021