miRTARGET: An integrated web tool for the identification of microRNA targets with potential therapeutic or prognostic value in cancer

Rokavec, Matjaz; Hermeking, Heiko (2025): miRTARGET: An integrated web tool for the identification of microRNA targets with potential therapeutic or prognostic value in cancer. Neoplasia, 67: 101202. ISSN 14765586

Abstract

miRTARGET (https://www.mirtarget.com) is a web tool for the identification of miRNA targets. It integrates experimental miRNA-related datasets and computational algorithms to generate prediction scores for targets of 1744 human miRNAs. The score is based on four dataset categories: mRNA profiling in cells or mice after (1) ectopic miRNA expression or (2) miRNA inactivation by knock-out or knock-down, (3) correlation analyses of mRNA and miRNA expression profiles, and (4) ten computational miRNA target prediction algorithms. Our validation analyses demonstrated a significant enrichment of published/validated miRNA targets among the predicted miRNA targets, underlining the reliability of the miRTARGET prediction score. In addition, miRTARGET integrates cancer-related datasets from primary tumors and cell lines, allowing users to filter/extract miRNA targets based on cancer cell line dependency, survival associations, and differential expression between tumor and normal tissues across 32 cancer entities. As a proof-of-concept, miRTARGET identified CDC7 and its regulatory unit DBF4 as the top cancer-associated predicted targets of the tumor suppressive miRNA miR-30a. Therefore, the CDC7-DBF4 complex may represent an attractive candidate therapeutic target for the treatment of cancers with miR-30a inactivation. Altogether, miRTARGET is a powerful and user-friendly web tool for exploring miRNA targets with therapeutic or prognostic potential in cancer.

• Dokumententyp: Artikel (LMU)
• Organisationseinheit (Fakultäten): 07 Medizin > Pathologisches Institut
• DFG-Fachsystematik der Wissenschaftsbereiche: Lebenswissenschaften
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892