Computational multi-omics modelling identifies TOP2A as a central prognostic biomarker and therapeutic target in renal cell carcinoma.
Summary
This multi-omics bioinformatics study investigated the significance of TOP2A in renal cell carcinoma subtypes KIRC, KIRP, and KICH. Analyses revealed significant TOP2A overexpression associated with advanced pathological stages, high tumor grades, and poor patient outcomes. Genomic alterations, primarily amplifications and mutations, were identified at the TOP2A locus. The study suggests that TOP2A regulates the cell cycle, influences the immune microenvironment, and modulates key signaling pathways, positioning it as a prognostic biomarker and a potential therapeutic target.
Analysis
CLINIQUE : This study identifies TOP2A as a central prognostic biomarker in KIRC, KIRP, and KICH renal cell carcinomas, with high expression consistently linked to aggressive tumor characteristics and poor patient outcomes. Furthermore, drug sensitivity analysis suggests that elevated TOP2A levels could predict enhanced sensitivity to certain anticancer treatments, paving the way for clinical trials to validate its role as a predictive biomarker. This could potentially guide personalized therapeutic strategies in the long term (5+ years). BIOMOL : The major molecular discovery is the identification of TOP2A as a key player in renal cell carcinoma tumorigenesis, exhibiting significant overexpression and frequent genomic alterations (amplifications, mutations). The study highlights its involvement in abnormal cell cycle regulation via association with CDK family members, its role in shaping the tumor immune microenvironment, and its influence on multiple cancer-related signaling pathways. These mechanistic insights provide a strong foundation for translational research aimed at developing TOP2A inhibitors or using it as a target for combination therapies. BIOINFO : The study employed a robust integrative and multi-omics bioinformatics approach, leveraging TCGA data and multiple databases (cBioPortal, UALCAN, GEPIA, TIMER, KM Plotter, TISIDB, OncoDB, ENCORI, MEXPRESS, String, GeneMANIA, Human Protein Atlas). This methodology allowed for a systematic investigation of TOP2A, correlating its expression with clinical and molecular parameters, and identifying protein-protein interaction networks. The integration of these diverse data sources is crucial for biomarker and therapeutic target discovery, and this approach is reproducible for other genes or diseases.