A novel risk model of three SUMOylation genes based on RNA expression for potential prognosis and treatment sensitivity prediction in kidney cancer
Introduction: Kidney cancer is one of the most common and lethal urological malignancies. Discovering a biomarker that can predict prognosis and potential drug treatment sensitivity is necessary for managing patients with kidney cancer. SUMOylation is a type of posttranslational modification that co...
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| Main Authors: | , , , , , |
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| Format: | Book |
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Frontiers Media S.A.,
2023-05-01T00:00:00Z.
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| Summary: | Introduction: Kidney cancer is one of the most common and lethal urological malignancies. Discovering a biomarker that can predict prognosis and potential drug treatment sensitivity is necessary for managing patients with kidney cancer. SUMOylation is a type of posttranslational modification that could impact many tumor-related pathways through the mediation of SUMOylation substrates. In addition, enzymes that participate in the process of SUMOylation can also influence tumorigenesis and development.Methods: We analyzed the clinical and molecular data which were obtanied from three databases, The Cancer Genome Atlas (TCGA), the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC), and ArrayExpress.Results: Through analysis of differentially expressed RNA based on the total TCGA-KIRC cohort, it was found that 29 SUMOylation genes were abnormally expressed, of which 17 genes were upregulated and 12 genes were downregulated in kidney cancer tissues. A SUMOylation risk model was built based on the discovery TCGA cohort and then validated successfully in the validation TCGA cohort, total TCGA cohort, CPTAC cohort, and E-TMAB-1980 cohort. Furthermore, the SUMOylation risk score was analyzed as an independent risk factor in all five cohorts, and a nomogram was constructed. Tumor tissues in different SUMOylation risk groups showed different immune statuses and varying sensitivity to the targeted drug treatment.Discussion: In conclusion, we examined the RNA expression status of SUMOylation genes in kidney cancer tissues and developed and validated a prognostic model for predicting kidney cancer outcomes using three databases and five cohorts. Furthermore, the SUMOylation model can serve as a biomarker for selecting appropriate therapeutic drugs for kidney cancer patients based on their RNA expression. |
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| Item Description: | 1663-9812 10.3389/fphar.2023.1038457 |