Utilizing Ubiquitination Patterns to Predict Prostate Cancer Prognosis and Devise a Therapeutic Response.

Abstract

Ubiquitination, a post-translational modification, is crucial for cancer regulation. However, the predictive significance of ubiquitination-related genes (URGs) for prostate adenocarcinoma (PRAD) remains unclear. The objectives of the study were to investigate the role of URGs in PRAD and their potential impact on patient prognosis. This study acquired data for more than 800 patients with PRAD from public databases. The unique ubiquitination-related patterns of PRAD were detected by unsupervised clustering approach. URGs relevant to the prognosis of patients with PRAD and a ubiquitination-related prognostic index (URPI) were identified and generated using the log-rank test, univariate and multivariate Cox proportional hazards regression, least absolute shrinkage and selection operator (LASSO) Cox regression, and bootstrap strategy. Four ubiquitination-related subpopulations were then defined, and 39 ubiquitination-related differentially expressed genes in prostate cancer and paracancerous samples were screened, with LASSO analysis distinguishing six of them. The URPI was built and verified using the identified URGs that played critical roles in survival stratification. Several potential URPI-targeting drugs were also analyzed. Subsequently, the URPI was combined with clinical characteristics, which provided a more accurate estimate of PRAD survival and was a superior choice for PRAD prognostic forecasts. This investigation has thus established and verified a URPI, which may provide unique insights to improve survival estimations for patients with PRAD.