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加权基因共表达网络分析鉴定结肠癌关键候选基因-VSIG2
Authors Cui Z, Li Y, He S, Wen F, Xu X, Lu L, Wu S
Received 27 April 2021
Accepted for publication 5 July 2021
Published 15 July 2021 Volume 2021:13 Pages 5739—5750
DOI https://doi.org/10.2147/CMAR.S316584
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Sanjeev Srivastava
Background: Colon adenocarcinoma (COAD) is one of the most common malignancies. To identify candidate genes that may be involved in colon adenocarcinoma development and progression, weighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression networks to explore associations between gene sets and clinical features and to identify candidate biomarkers. Moreover, we intend to make a preliminary exploration on it.
Methods: Gene expression profiles and clinical information were collected from The Cancer Genome Atlas COAD database for analysis. The gene expression profiles of GSE106582 and GSE110224 were screened from the Gene Expression Omnibus database for verification. WGCNA analysis, functional pathway enrichment analysis, and prognosis analysis were performed on three databases. Target genes were selected from the key genes for experimental verification and research.
Results: Key genes obtained by WGCNA analysis were mainly enriched in key functions and pathways such as drug metabolism, steroid hormones, and retinol metabolism. A total of four prognostic genes were screened out: SELENBP1, NAT2, VSIG2 , and CES2. VSIG2 was selected as the target gene for experimental verification, and its encoded protein was found to be mainly expressed in immune cells. Its expression was positively correlated with immune infiltration.
Conclusions: VSIG2 was shown to be associated with immune invasion and antigen presentation in COAD, suggesting it plays an important role in COAD development and progression. It could be used as a potential biomarker or therapeutic target for COAD.
Keywords: prognosis, WGCNA, immune-related gene, molecular biomarkers, The Cancer Genome Atlas, Gene Expression Omnibus