ArticlePeerJ2020
Identification of 10 Hub genes related to the progression of colorectal cancer by co-expression analysis.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Identification of heterogeneity and common characteristics in colorectal carcinoma located in distinct sites.Scientific reports · 2025Article
- Increased protein expression of interleukin-10 and its signalling molecules in colon cancer progression: potential prognostic and therapeutic targets.Discover oncology · 2025Article
- New treatment alternatives for primary and metastatic colorectal cancer by an integrated transcriptome and network analyses.Scientific reports · 2024Article
- Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways.BMC bioinformatics · 2024Article
- Article
- CXCL5 and CXCL14, but not CXCL16 as potential biomarkers of colorectal cancer.Scientific reports · 2023Article
- Metallothionein 2A (MT2A) controls cell proliferation and liver metastasis by controlling the MST1/LATS2/YAP1 signaling pathway in colorectal cancer.Cancer cell international · 2022Article
- In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps.PloS one · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal cancer (CRC) is the third most common cancer in the world. The present study is aimed at identifying hub genes associated with the progression of CRC.
methodThe data of the patients with CRC were obtained from the Gene Expression Omnibus (GEO) database and assessed by weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses performed in R by WGCNA, several hub genes that regulate the mechanism of tumorigenesis in CRC were identified. Differentially expressed genes in the data sets GSE28000 and GSE42284 were used to construct a co-expression network for WGCNA. The yellow, black and blue modules associated with CRC level were filtered. Combining the co-expression network and the PPI network, 15 candidate hub genes were screened.
resultsAfter validation using the TCGA-COAD dataset, a total of 10 hub genes (MT1X, MT1G, MT2A, CXCL8, IL1B, CXCL5, CXCL11, IL10RA, GZMB, KIT) closely related to the progression of CRC were identified. The expressions of MT1G, CXCL8, IL1B, CXCL5, CXCL11 and GZMB in CRC tissues were higher than normal tissues (
conclusionsBy combinating with a series of methods including GO enrichment analysis, KEGG pathway analysis, PPI network analysis and gene co-expression network analysis, we identified 10 hub genes that were associated with the progression of CRC.
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