ArticleCancer management and research2021
Key Candidate Genes - VSIG2 of Colon Cancer Identified by Weighted Gene Co-Expression Network Analysis.
Article in Cancer management and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Identify the PANoptosis signature and prognostic model via a multimachine-learning computational framework for bladder urothelial carcinoma.Cancer cell international · 2026Article
- Olink proteomics identifies serum protein biomarkers and an age-stratified diagnostic model for diabetes in Chinese patients.Frontiers in endocrinology · 2026Article
- VSIG2 hinders gastric cancer progression by suppressing ANXA2-mediated NF-κB pathway activation.Acta biochimica et biophysica Sinica · 2025Article
- VSIG2 promotes malignant progression of pancreatic ductal adenocarcinoma by enhancing LAMTOR2-mediated mTOR activation.Cell communication and signaling : CCS · 2023Article
- V-Set and immunoglobulin domain containing (VSIG) proteins as emerging immune checkpoint targets for cancer immunotherapy.Frontiers in immunology · 2022Review
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColon 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.
methodsGene 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.
resultsKey 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:
conclusionsVSIG2 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.
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