Abstract 3340: A miRNA based signature for the individual assessment of the prognosis of patients with seminoma

Abstract Introduction: Due to the risk of long-term toxicities in young seminoma patients, surveillance regimens nowadays are the standard of care in patients without metastases. Nevertheless, up to 20% will relapse with the necessity of definitive treatment exposing them to an even higher amount of therapy compared to in the adjuvant setting. This study seeks to establish a prognostic miRNA profile on primary tumors utilizing bioinformatics tools to differentiate between metastatic (m) and non-metastatic (nm) seminomas. Materials and methods: MiRNA was extracted from formalin-fixed paraffin-embedded sections. Two cohorts of patients with seminoma (each 24 patients, each 12 nm and 12 m) were investigated by microarray analysis. Validation was performed in 103 patients (47 nm and 56 m) through quantitative PCR (qPCR) using the TaqMan® assay, with RNU48, miR-191-5p, and miR-361-5p serving as references. Statistical and bioinformatics analyses were performed by using the Mann-Whitney U test and machine learning algorithms. Results: The bioinformatics analysis of microarrays identified 16 miRNAs exhibiting an accuracy >70% in differentiating m tumors from nm ones. qPCR analysis of seven selected miRNAs demonstrated significant expression differences between m and nm tumors for miRNA-371a-5p, miR-512-3p and miR-517a-3p (p<0.05), contingent upon the reference used. Analyzing metachronous and synchronous m tumours separately, all 3 miRNAs showed significantly different expression only in synchronous m, although a trend was observed in metachronous m. Conclusions: By employing machine-learning on microarray data, we established a miRNA signature that differentiates metastatic from non-metastatic seminomas with high accuracy. The findings have been validated for 3 miRNAs in independent cohorts by qPCR, reinforcing the potential of miRNAs as prognostic markers in seminomas. Ongoing validation efforts are currently being conducted in independent cohorts to define a robust miRNA signature. Citation Format: Farzaneh Zohari, Lea Eckhart, Hiresh Ayoubian, Hans-Peter Lenhof, Rainer Bohle, Felix Bremmer, Fabian A. Gayer, Yue Che, Marieke Vermeulen-Spohn, Tim Nestler, Michael Stöckle, Julia Heinzelbecker, Kerstin Junker. A miRNA based signature for the individual assessment of the prognosis of patients with seminoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3340.