Abstract
Background: Colon cancer is one of the most common cancers worldwide and has a poor prognosis. Through the analysis of transcriptome and clinical data of colon cancer, an immune gene-set signature was identified by single sample enrichment analysis (ssGSEA) scoring to predict patient survival and discover new therapeutic targets.
Objective: To study the role of immune gene-set signature in colon cancer.
Methods: First, RNASeq and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA). Immune gene-related gene sets were collected from the ImmPort database. Genes and immunological pathways related to prognosis were screened in the training set and integrated for feature selection using random forest. The immune gene-related prognosis model was verified in the entire TCGA test set and GEO validation set and compared with immune cells scores and matrix score.
Results: A total of 1650 prognostic genes and 13 immunological pathways were identified. These genes and pathways are closely related to the development of tumors. 13-immune gene-set signature was established, which is an independent prognostic factor for patients with colon cancer. Risk stratification of samples could be carried out in the training set, test set, and external validation set. The AUC of five-year survival in the training set and validation set is greater than 0.6. Immunosuppression occurs in high-risk samples and compared with published models, riskScore has a better prediction effect.
Conclusion: This study constructed a 13-immune gene-set signature as a new prognostic marker to predict the survival of patients with colon cancer, and provided new diagnostic/prognostic biomarkers and therapeutic targets for colon cancer.
Keywords: Bioinformatics, prognostic markers, TCGA, colon cancer, biomarker, cell mutation.
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