ArticleCancer control : journal of the Moffitt Cancer Center
Construction of a 12-Gene Prognostic Risk Model and Tumor Immune Microenvironment Analysis Based on the Clear Cell Renal Cell Carcinoma Model.
Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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14 authors.
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Abstract
objectivesAccurate survival predictions and early interventional therapy are crucial for people with clear cell renal cell carcinoma (ccRCC).
methodsIn this retrospective study, we identified differentially expressed immune-related (DE-IRGs) and oncogenic (DE-OGs) genes from The Cancer Genome Atlas (TCGA) dataset to construct a prognostic risk model using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. We compared the immunogenomic characterization between the high- and low-risk patients in the TCGA and the PUCH cohort, including the immune cell infiltration level, immune score, immune checkpoint, and T-effector cell- and interferon (IFN)-γ-related gene expression.
resultsA prognostic risk model was constructed based on 9 DE-IRGs and 3 DE-OGs and validated in the training and testing TCGA datasets. The high-risk group exhibited significantly poor overall survival compared with the low-risk group in the training (
conclusionThe 12-gene prognostic risk model can reliably predict overall survival outcomes and is strongly associated with the tumor immune microenvironment of ccRCC.
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