Dissertation committee:
Ανδρέας Σκορίλας, Καθηγητής, Τμήμα Βιολογίας, ΕΚΠΑ
Διαμάντης Σίδερης, Καθηγητής, Τμήμα Βιολογίας, ΕΚΠΑ
Ιωάννης Τρουγκάκος, Καθηγητής, Τμήμα Βιολογίας, ΕΚΠΑ
Διδώ Βασιλακοπούλου, Αναπληρώτρια Καθηγήτρια, Τμήμα Βιολογίας, ΕΚΠΑ
Μαργαρίτης Αυγέρης, Αναπληρωτής Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Μιχαήλ Λιόντος, Επίκουρος Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Νικόλαος Αφράτης, Επίκουρος Καθηγητής, Τμήμα Αγροτικής Ανάπτυξης Αγροδιατροφής & Διαχείρισης Φυσικών Πόρων, ΕΚΠΑ
Summary:
Ovarian cancer (OC) is the second most frequently diagnosed and the most lethal gynecological malignancy in developed countries, accounting for approximately 5% of female cancer-related mortality worldwide. Even though early-diagnosis (FIGO I/II) has a 5-year survival up to 90%, most of the patients (~75%) are diagnosed in advanced disease stages (FIGO III/IV) with a 5-year survival of ~25%, the poorest among all gynecological malignancies. Early-diagnosis is proving difficult, while the significant progress in surgical techniques and targeted therapies has only modestly improved the relatively high death-to-incidence rate of patients diagnosed in advanced disease stages. Moreover, the high heterogeneity of tumors’ molecular background and patients’ treatment response hinders personalized prognosis and tailored therapies. Therefore, the identification of novel molecular markers could be a valuable tool to support personalized prognosis, benefit risk-stratification and therapeutic decisions, as well as to ameliorate the quality-of-life of the patients. In the present PhD thesis, recognizing the clinical need of identifying new molecular biomarkers in ovarian cancer, we aimed at studying the expression and evaluating the clinical significance of non-coding RNA (ncRNA) in cancer cell lines and ovarian tumors. According to the ENCODE project, more than 75% of the genome is actively transcribed in ncRNAs. Among them, microRNAs (miRNAs) have emerged as potent post-transcriptional regulators of gene expression. Moreover, it has been established that numerous miRNAs exert oncogenic or tumor-suppressive roles in ovarian cancer tumorigenesis and progression, thus representing promising molecular markers to support precision medicine. Additionally, tRNA-derived fragments (tRFs), initially thought to be random by-products of tRNA metabolism, constitute an abundant and evolutionarily conserved class of small non-coding RNAs with precise sequence and defined biological roles. Unsurprisingly, numerous research groups have identified tRFs as potential prognostic molecular markers in various cancer types. The evaluation of the clinical utility of miR-203 expression in the two institutionally-independent cohorts revealed an independent and unfavorable significance of miR-203 expression, concerning prognosis of epithelial ovarian cancer patients. In particular, miR-203 overexpression was significantly associated with worse survival outcome of patients, following tumor resection and first-line platinum-based chemotherapy compared to patients underexpressing miR-203, independently of FIGO stage, tumor grade, residual tumor size, chemotherapy response and age. Additionally, multivariate models incorporating miR-203 expression with the widely-used prognostic disease markers resulted in superior positive prediction of the patients at higher risk for poor treatment outcome, as well as in improved patients’ risk-stratification and clinical benefit of ovarian cancer prognosis. Furthermore, miR-181a assessment in the two institutionally-independent cohorts and three external publicly available datasets unveiled that miR-181a is associated with adverse clinicopathological characteristics of the patients and could promote patients’ personalized prognosis and improve the prediction of treatment outcome in serous ovarian cancer. More precisely, miR-181a overexpression was significantly correlated with a worse outcome of the patients following cytoreductive surgery and first-line platinum-based chemotherapy, compared to the patients expressing lower levels of miR-181a. Strikingly, miR-181a retained its independent prognostic value in multivariate prognosis model that included FIGO stage, tumor grade, residual tumor size and chemotherapy response. In the study design, the analysis of the two institutionally-independent cohorts, with a median follow-up time that exceeds five years, along with the three external publicly available datasets corroborates the unfavorable clinical impact of miR-181a overexpression on the treatment response and survival of serous ovarian patients. Finally, the evaluation of the additional impact of its overexpression on ameliorating the prognostic power of established clinical disease markers resulted in a superior positive prediction and an improved patients’ risk-stratification. Regarding the evaluation of tRNA-derived fragments (tRFs), the analysis of the TCGA-OV dataset, revealed the abundance of the i-tRFs and the high proportion of fragments derived from tRNAGlyGCC in ovarian tumors, while gene ontology analysis of i-tRF-GlyGCC predicted targets resulted in enriched key signaling pathways in ovarian cancer onset and progression. Strikingly, i-tRF-GlyGCC emerged as an independent and powerful prognostic indicator in epithelial ovarian cancer since its overexpression could accurately predict unfavorable overall survival and early progression. Moreover, multivariate prognosis models highlighted that i-tRF-GlyGCC evaluation ameliorates the prognostic power of widely-used clinical variables and offers superior risk-stratification of the patients. Finally, decision curve analysis (DCA) elucidated the significantly enhanced clinical net benefit of the multivariate models combining i-tRF-GlyGCC levels along with disease established markers in epithelial ovarian cancer prognostication. Ultimately, tRFs derived from pre-tRNAs, namely 3'U-tRFs, have also been studied in the present PhD thesis. Herein, following a primary clinical evaluation, target prediction and gene ontology analysis of 3’U-tRFs candidates, 3'U-tRF derived from pre-tRNAValCAC (3'U-tRFValCAC) was associated with adverse prognosis and linked to cell signaling, cell proliferation, and cell adhesion pathways, and, thus, was selected for further investigation. Strikingly, its ectopic expression in vitro significantly increased cell proliferation and migration of SK-OV-3 and OVCAR-3 tumor cells in a dose-dependent manner, verifying its active implication in key biological processes. By an in-depth clinical evaluation in the screening OVCAD and institutionally-independent TU Munich validation cohort, 3’U-tRFValCAC was unveiled as a powerful prognostic indicator in epithelial ovarian cancer since its elevated levels were statistically correlated with poor overall and progression-free survival. Moreover, multivariate analysis demonstrated that the inferior outcome of “3’U-tRFValCAC high” group is independent of the patients’ clinicopathological data and the established clinical markers. In this regard, 3’U-tRFValCAC-fitted multivariate models ameliorated the prognostic power of the clinically used markers and offered superior risk-stratification of the patients.
