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

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.

SUBMITTER: Panoutsopoulou K

PROVIDER: S-EPMC8750938 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Context: Papillary thyroid cancer (PTC) is the most common thyroid cancer with dramatically increasing worldwide. Accurate diagnosis is crucial to avoid unnecessary overtreatment for low-risk patients, but the currently available markers are still insufficient. tRNA-derived fragments (tRFs) are emerging as a new class of small non-coding RNAs due to their potential roles as novel biomarkers and therapeutic targets in cancer. However, their involvement in papillary thyroid carcinoma (PTC) is still unclear. Objectives: This study was performed to identify differentially expressed tRFs in PTC and investigate the role of serum tRFs to discriminate PTC from nodular goiters (NGs).Methods and Materials: tRF expression profiles were measured in pooled sera from patients with PTCs (n=6), NGs (n=6) and healthy subjects (n=6) using high-throughput sequencing (cohort1). One selected tRF candidate was validated in the same individual samples (cohort1) by qRT-PCR. The confirmed tRF was further validated in a larger second cohort including patients with PTCs (n=30), NGs (n=20) and healthy individuals (n=18).Results: Our sequencing results showed that circulating tRFs were differentially expressed in patients with PTC compared with those with NG and healthy people. After the validation in individual samples, tRF-Pro-AGG-018 was confirmed as differentially elevated in serum samples of patients with PTC. These results were further confirmed in a larger second cohort. Moreover, tRF-Pro-AGG-018 exhibited good diagnostic performance with a sensitivity of 0.7222 and a specificity of 0.8846 for PTC and it was associated with several targeted genes of PTC. Conclusions: Our study identified that the serum tRFs were differentially expressed in PTC compared with NG and healthy individuals. Notably, circulating tRF-Pro-AGG-018 was found to have a significant elevation in patients with PTC and exhibited good diagnostic performance with relatively high sensitivity and specificity for PTC. Our findings suggest tRFs might serve as novel circulating biomarkers in predicting patients with PTC, which may prevent unnecessary thyroid surgeries for low-risk and benefit from optimal

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

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OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

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