ArticleCancer biomarkers : section A of Disease markers2024
Identification of Hub genes with prognostic values in colorectal cancer by integrated bioinformatics analysis.
Article in Cancer biomarkers : section A of Disease markers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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6 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Differential DNA methylation associated with delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a systematic review.Neurosurgical review · 2024Pooled it
- PDZ-binding kinase promotes ovarian cancer cell proliferation and invasion viaTranslational cancer research · 2026Article
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- Identification of a novel PANoptosis-associated prognostic signature and immune landscape analysis in neuroblastoma with experimental validation.Frontiers in immunology · 2026Article
- Integrative Bioinformatics and Experimental Validation Establish CCNB1 as a Potential Biomarker for Diagnosis and Prognosis in Colorectal Cancer.Current issues in molecular biology · 2025Article
- Data-Driven Identification of Early Cancer-Associated Genes via Penalized Trans-Dimensional Hidden Markov Models.Biomolecules · 2025Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOur study aimed to investigate the Hub genes and their prognostic value in colorectal cancer (CRC) via bioinformatics analysis.
methodsThe data set of colorectal cancer was downloaded from the GEO database (GSE21510, GSE110224 and GSE74602) for differential expression analysis using the GEO2R tool. Hub genes were screened by protein-protein interaction (PPI) comprehensive analysis. GEPIA was used to verify the expression of Hub genes and evaluate its prognostic value. The protein expression of Hub gene in CRC was analyzed using the Human Protein Atlas database. The cBioPortal was used to analyze the type and frequency of Hub gene mutations, and the effects of mutation on the patients' prognosis. The TIMER database was used to study the correlation between Hub genes and immune infiltration in CRC. Gene set enrichment analysis (GSEA) was used to explore the biological function and signal pathway of the Hub genes and corresponding co-expressed genes.
resultsWe identified 346 differentially expressed genes (DEGs), including 117 upregulated and 229 downregulated. Four Hub genes (AURKA, CCNB1, EXO1 and CCNA2) were selected by survival analysis and differential expression validation. The protein and mRNA expression levels of AURKA, CCNB1, EXO1 and CCNA2 were higher in CRC tissues than in adjacent tissues. There were varying degrees of immune cell infiltration and gene mutation of Hub genes, especially B cells and CD8+ T cells. The results of GSEA showed that Hub genes and their co-expressed genes mainly participated in chromosome segregation, DNA replication, translational elongation and cell cycle.
conclusionOverexpression of AURKA, CCNB1, CCNA2 and EXO1 had a better prognosis for CRC and this effect was correlation with gene mutation and infiltration of immune cells.
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