Key Candidate Genes – VSIG2 of Colon Cancer Identified by Weighted Gene Co-Expression Network Analysis

Abstract

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

Acknowledgments

We appreciate The Cancer Genome Atlas and Gene Expression Omnibus for the open data.

Abbreviations

CRC, colon cancer; COAD, colon adenocarcinoma; WGCNA, weighted gene co-expression network analysis; TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; BP, biological process; CC, cellular component; MF, molecular function; TIMER, Tumor IMmune Estimation Resource.

Data Sharing Statement

All data generated or analysed during this study are included in this published article.

Ethics Approval and Consent to Participate

The experiments were approved by the Ethics Committee of the Binzhou Medical University Hospital. Written informed consent was obtained from all patients. The experiments were carried out following the Declaration of Helsinki.No animal experiment is applicable.

Author Contributions

All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work. Zhongze Cui and Yangyang Li contributed as co-first authors.

Disclosure

All authors reported no conflicts of interest for this work.