ArticleFrontiers in oncology2021
The Bioinformatics-Based Analysis Identifies 7 Immune-Related Genes as Prognostic Biomarkers for Colon Cancer.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- Multi-omics interrogation identifies IRF4 as a causal transcription factor in monocytes that suppresses colorectal cancer progression by remodeling the immune microenvironment and inhibiting EMT.Translational oncology · 2026Article
- Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures.NPJ precision oncology · 2025Article
- Development and validation of G2M signature-based prognostic model for stratifying colon cancer prognosis.Discover oncology · 2025Article
- A Transcriptomic Analysis of Laryngeal Dysplasia.International journal of molecular sciences · 2024Review
- Article
- Integrating TCGA and single-cell sequencing data for colorectal cancer: a 10-gene prognostic risk assessment model.Discover oncology · 2023Article
- A novel investigation into an E2F transcription factor-related prognostic model with seven signatures for colon cancer patients.IET systems biology · 2023Article
- Article
- Sex-Biased Control of Inflammation and Metabolism by a Mitochondrial Nod-Like Receptor.Frontiers in immunology · 2022Article
- CD8+ T cell-associated genes MS4A1 and TNFRSF17 are prognostic markers and inhibit the progression of colon cancer.Frontiers in oncology · 2022Article
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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
Colon cancer poses a great threat to human health. Currently, there is no effective treatment for colon cancer due to its complex causative factors. Immunotherapy has now become a new method for tumor treatment. In this study, 487 DEGs were screened from The Cancer Genome Atlas (TCGA) database and ImmPort database, and GeneOntology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Hierarchical clustering of all samples revealed a significant correlation between colon cancer and immunity. The weighted gene co-expression network analysis (WGCNA) algorithm was used to identify key gene modules associated with immunity in colon cancer, here, module grey60 showed the highest correlation. A protein-protein interaction (PPI) network was constructed using the STRING database to screen hub genes, and subsequently, 7 immune-related genes the most closely associated with colon cancer were identified by differential expression in cancer and paracancer. Finally, a risk prediction model was developed using least absolute shrinkage and selection operator (LASSO) COX analysis, and the accuracy of the model was validated by GSE14333. This study determined that IRF4 and TNFRSF17 were immune-related genes in colon cancer, providing immune-related prognostic biomarkers for colon cancer.
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