ArticleFrontiers in genetics2023
Regularized survival learning and cross-database analysis enabled identification of colorectal cancer prognosis-related immune genes.
Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Construction of a risk scoring model based on machine learning and validation of the role of the key gene SERPINE1 in the progression of colon cancer.Cancer cell international · 2026Article
- Integration of single-cell and bulk RNA-seq via machine learning to reveal ferroptosis- and lipid metabolism-driven immune landscape heterogeneity and predict immunotherapy response in colon cancer.Frontiers in immunology · 2025Article
- TRPM6 acts as a prognostic biomarker and mediates MgFrontiers in immunology · 2025Article
- CD72, a new immune checkpoint molecule, is a novel prognostic biomarker for kidney renal clear cell carcinoma.European journal of medical research · 2023Article
- A bioinformatics approach to identify a disulfidptosis-related gene signature for prognostic implication in colon adenocarcinoma.Scientific reports · 2023Article
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7 authors.
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Abstract
Colon adenocarcinoma is the most common type of colorectal cancer. The prognosis of advanced colorectal cancer patients who received treatment is still very poor. Therefore, identifying new biomarkers for prognosis prediction has important significance for improving treatment strategies. However, the power of biomarker analyses was limited by the used sample size of individual database. In this study, we combined Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to expand the number of healthy tissue samples. We screened differentially expressed genes between the GTEx healthy samples and TCGA tumor samples. Subsequently, we applied least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis to identify nine prognosis-related immune genes:
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