Exploring the Prognostic Value of Tumour-Associated Genes in Clear Cell Renal Cell Carcinoma Through Single-Cell RNA Sequencing Insights.

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) characterised by its diversity and a tendency to defy standard therapeutic approaches. Amidst the advent of immunotherapy, it has become imperative to pinpoint prognostic indicators of the tumour microenvironment (TME) influence the efficacy of treatments. Employing single-cell RNA sequencing (scRNA-seq), this research delved into the diverse landscape of ccRCC, uncovering its complex underpinnings and pinpointing molecular avenues for therapeutic intervention. We constructed a prognostic model using 101 machine learning algorithms and integrated data from multiple cohorts, including TCGA, ICGC, and microarray datasets. The model's efficacy was assessed using the Concordance Index (C-index), and further analyses included pseudotime analysis of tumour

SUBMITTER: Fu T 

PROVIDER: S-EPMC11661917 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature