RESUMO
Ovarian cancer (OC) remains a leading cause of gynecological cancer-related death worldwide, characterized by poor 5-year survival. Molecular markers could serve as crucial tools of personalized prognosis and therapy. Herein, we present miR-181a as novel predictor of OC prognosis, using five independent OC cohorts. In particular, a screening (n = 81) and an institutionally independent validation (n = 100, OVCAD multicenter study) serous OC (SOC) cohorts were analyzed. Bagnoli et al (2016) OC179 (n = 124) to OC133 (n = 100) and TCGA (n = 489) served as external validation cohorts. Patients' survival and disease progression were assessed as clinical endpoint events. Bootstrap analysis was performed for internal validation and decision curve analysis was utilized to evaluate clinical benefit. miR-181a overexpression was unveiled as powerful and independent molecular predictor of patients' poor survival and higher risk for disease progression after debulking surgery and platinum-based chemotherapy. Analysis of the OVCAD institutionally independent cohort, as well as of Bagnoli et al. and TCGA external cohorts further confirmed the unfavorable prognostic nature of miR-181a overexpression in SOC. Strikingly, multivariate prognostic models incorporating miR-181a with established disease markers clearly improved patients' risk-stratification and offered superior clinical benefit in OC prognostication. Conclusively, miR-181a evaluation could augment prognostic accuracy and support precision medicine decisions in OC.
Assuntos
Biomarcadores Tumorais/genética , Cistadenocarcinoma Seroso/terapia , MicroRNAs/genética , Neoplasias Ovarianas/terapia , Platina/uso terapêutico , Regulação para Cima , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Cistadenocarcinoma Seroso/genética , Procedimentos Cirúrgicos de Citorredução , Progressão da Doença , Feminino , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Pessoa de Meia-Idade , Neoplasias Ovarianas/genética , Prognóstico , Análise de Sobrevida , Resultado do TratamentoRESUMO
INTRODUCTION: Despite recent advances in epithelial ovarian cancer (EOC) management, the highly heterogenous histological/molecular tumour background and patients' treatment response obstructs personalised prognosis and therapeutics. Herein, we have studied the role and clinical utility of the novel subclass of tRNA-derived small RNA fragments emerging via 3'-trailer processing of pre-tRNAs (3'U-tRFs) in EOC. METHODS: SK-OV-3 and OVCAR-3 cells were used for in vitro study. Following transfection, cell growth and migration were assessed by CCK8 and wound healing assays, respectively. 3'U-tRFs levels were assessed by reverse transcription quantitative PCR (RT-qPCR), following 3'-end RNA polyadenylation. A screening (OVCAD, n = 100) and institutionally independent validation (TU Munich, n = 103) cohorts were employed for survival analysis using disease progression and patients' death as clinical end-points. Bootstrap analysis was performed for internal validation, and decision curve analysis was used to evaluate clinical benefit on disease prognosis. RESULTS: Following primary clinical assessment, target prediction and gene ontology analyses, the 3'U-tRFValCAC (derived from pre-tRNAValCAC) was highlighted to regulate cell proliferation and adhesion, and to correlate with inferior patients' outcome. 3'U-tRFValCAC transfection of SK-OV-3 and OVCAR-3 cells resulted in significantly increased cell growth and migration, in a dose-dependent manner. Elevated tumour 3'U-tRFValCAC levels were associated with significantly higher risk for early progression and worse survival following first-line platinum-based chemotherapy, independently of patients' clinicopathological data, chemotherapy response, and residual tumour. Interestingly, 3'U-tRFValCAC-fitted multivariate models improved risk stratification and provided superior clinical net benefit in prediction of treatment outcome compared to disease established markers. CONCLUSIONS: 3'U-tRFValCAC promotes tumour cell growth and migration and supports modern risk stratification and prognosis in EOC.