Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multiomics Data Analysis.

ABSTRACT:

Methods

This study was based on the multiomics data (including mRNA, lncRNA, miRNA, methylation, and WES) of 258 ccRCC patients from TCGA database. Firstly, we screened the feature values that had impact on the prognosis and obtained two subtypes. Then, we used 10 algorithms to achieve multiomics clustering and conducted pseudotiming analysis to further validate the robustness of our clustering method, based on which the two subtypes of ccRCC patients were further subtyped. Meanwhile, the immune infiltration was compared between the two subtypes, and drug sensitivity and potential drugs were analyzed. Furthermore, to analyze the heterogeneity of patients at the multiomics level, biological functions between two subtypes were compared. Finally, Boruta and PCA methods were used for d

SUBMITTER: Jiang A 

PROVIDER: S-EPMC8752262 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature