The Bioinformatics-Based Analysis Identifies 7 Immune-Related Genes as Prognostic Biomarkers for Colon Cancer.

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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.", "claims": [{"id": "claim-method", "statement": "The relationship between prognostic immune-related gene expression and OS (overall survival) was assessed using LASSO COX analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34900677", "locator": "sections[8] \"Construction of a Prognostic Feature Model\" paragraph 2", "quote": "The relationship between prognostic immune-related gene expression and OS (overall survival) was assessed using LASSO COX analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are publicly available. 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