Exploring prognostic implications of miRNA signatures and telomere maintenance genes in kidney cancer

Mol Ther Oncol. 2024 Sep 10;32(4):200874. doi: 10.1016/j.omton.2024.200874. eCollection 2024 Dec 19.

Abstract

Kidney cancer, particularly clear cell renal cell carcinoma (KIRC), presents significant challenges in disease-specific survival. This study investigates the prognostic potential of microRNAs (miRNAs) in kidney cancers, including KIRC and kidney papillary cell carcinoma (KIRP), focusing on their interplay with telomere maintenance genes. Utilizing data from The Cancer Genome Atlas, miRNA expression profiles of 166 KIRC and 168 KIRP patients were analyzed. An evolutionary learning-based kidney survival estimator identified robust miRNA signatures predictive of 5-year survival for both cancer types. For KIRC, a 37-miRNA signature showed a correlation coefficient (R) of 0.82 and mean absolute error (MAE) of 0.65 years. Similarly, for KIRP, a 23-miRNA signature exhibited an R of 0.82 and MAE of 0.64 years, demonstrating comparable predictive accuracy. These signatures also displayed diagnostic potential with receiver operating characteristic curve values between 0.70 and 0.94. Bioinformatics analysis revealed targeting of key telomere-associated genes such as TERT, DKC1, CTC1, and RTEL1 by these miRNAs, implicating crucial pathways such as cellular senescence and proteoglycans in cancer. This study highlights the significant link between miRNAs and telomere genes in kidney cancer survival, offering insights for therapeutic targets and improved prognostic markers.

Keywords: MT: Regular Issue; cancer survival estimation; kidney cancer; machine learning; miRNA signature; telomere maintenance genes.