Artificial Intelligence-Driven SELEX Design of Aptamer Panels for Urinary Multi-Biomarker Detection in Prostate Cancer: A Systematic and Bibliometric Review.

ABSTRACT: Background/Objectives: The limited specificity of prostate-specific antigen (PSA) drives unnecessary biopsies in prostate cancer (PCa). Urinary extracellular vesicles (uEVs) provide a non-invasive reservoir of tumor-derived nucleic acids and proteins. Aptamers selected by SELEX enable highly specific capture, and artificial intelligence (AI) can accelerate their optimization. This systematic review evaluated AI-assisted SELEX for urine-derived and exosome-enriched aptamer panels in PCa detection. Methods: Systematic searches of PubMed, Scopus, and Web of Science (1 January 2010-24 August 2025; no language restrictions) followed PRISMA 2020 and PRISMA-S. The protocol is registered on OSF (osf.io/b2y7u). After deduplication, 1348 records were screened; 129 studies met the eligi

SUBMITTER: Slalmi A 

PROVIDER: S-EPMC12731070 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature