Predicting prostate cancer progression with a Multi-lncRNA expression-based risk score and nomogram integrating ISUP grading.

ABSTRACT: Prostate cancer is a highly heterogeneous disease; therefore, estimating patient prognosis accurately is challenging due to the lack of biomarkers with sufficient specificity and sensitivity. One of the current challenges lies in integrating genomic and transcriptomic data with clinico-pathological features and in incorporating their application in everyday clinical practice. Therefore, we aimed to model a risk score and nomogram containing long non-coding RNA (lncRNA) expression and clinico-pathological data to better predict the probability of prostate cancer progression. We performed bioinformatics analyses to identify lncRNAs differentially expressed across various prostate cancer stages and associated with progression-free survival. This information was further integrated into a progn

SUBMITTER: Ledesma-Bazan S 

PROVIDER: S-EPMC10993238 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature