tRNA(GlyGCC)-Derived Internal Fragment (i-tRF-GlyGCC) in Ovarian Cancer Treatment Outcome and Progression

SIMPLE SUMMARY: In the precision medicine era, epithelial ovarian cancer (EOC) is characterized by a high death-to-incidence rate and poor 5-year survival. The identification of novel molecular markers is of utmost importance to guide personalized prognosis. The objective of the present study has been to evaluate, for the first time, the prognostic utility of tRNA-derived fragments (tRFs) in ovarian carcinomas. In this context, we have performed in silico analysis and expression profiling, utilizing a TCGA-OV database, GEO datasets and our two institutionally-independent cohorts. The analysis highlighted the internal tRF derived from tRNA(GlyGCC) (i-tRF-GlyGCC) as a novel molecular predictor of EOC prognosis. More precisely, elevated i-tRF-GlyGCC levels were correlated with an aggressive phenotype of ovarian tumor and linked to adverse survival outcomes and early progression following debulking surgery and platinum-based chemotherapy. Interestingly, i-tRF-GlyGCC integration in multivariate strategies benefits prognostication and achieves superior patient risk-stratification, supporting precision medicine decisions. ABSTRACT: Epithelial ovarian cancer (EOC) remains a highly-lethal gynecological malignancy, characterized by frequent recurrence, chemotherapy resistance and poor 5-year survival. Identifying novel predictive molecular markers remains an overdue challenge in the disease’s clinical management. Herein, in silico analysis of TCGA-OV highlighted the tRNA-derived internal fragment (i-tRF-GlyGCC) among the most abundant tRFs in ovarian tumors, while target prediction and gene ontology (GO) enrichment analysis predicted its implication in key biological processes. Thereafter, i-tRF-GlyGCC levels were quantified in a screening EOC (n = 98) and an institutionally-independent serous ovarian cancer (SOC) validation cohort (n = 100, OVCAD multicenter study). Disease progression and patient death were used as clinical endpoints for the survival analysis. Internal validation was performed by bootstrap analysis and the clinical net benefit was estimated by decision curve analysis. The analysis highlighted the significant association of i-tRF-GlyGCC with advanced FIGO stages, suboptimal debulking and most importantly, with early progression and poor overall survival of EOC patients. The OVCAD validation cohort corroborated the unfavorable predictive value of i-tRF-GlyGCC in EOC. Ultimately, evaluation of i-tRF-GlyGCC with the established/clinically used prognostic markers offered superior patient risk-stratification and enhanced clinical benefit in EOC prognosis. In conclusion, i-tRF-GlyGCC assessment could aid towards personalized prognosis and support precision medicine decisions in EOC.