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Supplementary data from lncRNAs as Novel Indicators of Patients' Prognosis in Stage I Epithelial Ovarian Cancer: A Retrospective and Multicentric Study

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posted on 2023-03-31, 19:41 authored by Paolo Martini, Lara Paracchini, Giulia Caratti, Maurizia Mello-Grand, Robert Fruscio, Luca Beltrame, Enrica Calura, Gabriele Sales, Antonella Ravaggi, Eliana Bignotti, Franco E. Odicino, Enrico Sartori, Patrizia Perego, Dionyssios Katsaros, Ilaria Craparotta, Giovanna Chiorino, Stefano Cagnin, Laura Mannarino, Lorenzo Ceppi, Costantino Mangioni, Chiara Ghimenti, Maurizio D'Incalci, Sergio Marchini, Chiara Romualdi

Supplementary data, material and results. Figure S1.1. Overall analysis schema Table S1.1 REMARK form. Figure S1.2 a) Kaplan Meier curves of patients divided by tumor grades (OS and PFS model). The table below summarizes the models used. Figure S1.2 b) Kaplan Meier curves of patients divided in patients who received chemotherapy (Yes) and patients who did not undergo chemotherapy (No). Figure S1.2 c) Kaplan Meier curves of patients divided in FIGO substages. The table below summarizes the models used.

Funding

Nerina and Mario Mattioli Foundation

Alleanza Contro il Tumore Ovarico (ACTO)

Italian Association for Cancer Research

CARIPLO Foundation

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ARTICLE ABSTRACT

Purpose: Stage I epithelial ovarian cancer (EOC) represents about 10% of all EOCs and is characterized by good prognosis with fewer than 20% of patients relapsing. As it occurs less frequently than advanced-stage EOC, its molecular features have not been thoroughly investigated. We have demonstrated that in stage I EOC miR-200c-3p can predict patients' outcome. In the present study, we analyzed the expression of long non-coding RNAs (lncRNA) to enable potential definition of a non-coding transcriptional signature with prognostic relevance for stage I EOC.Experimental Design: 202 snap-frozen stage I EOC tumor biopsies, 47 of which relapsed, were gathered together from three independent tumor tissue collections and subdivided into a training set (n = 73) and a validation set (n = 129). Median follow up was 9 years. LncRNAs' expression profiles were correlated in univariate and multivariate analysis with overall survival (OS) and progression-free survival (PFS).Results: The expression of lnc-SERTAD2-3, lnc-SOX4-1, lnc-HRCT1-1, and PVT1 was associated in univariate and multivariate analyses with relapse and poor outcome in both training and validation sets (P < 0.001). Using the expression profiles of PVT1, lnc-SERTAD2-3, and miR-200c-3p simultaneously, it was possible to stratify patients into high and low risk. The OS for high- and low-risk individuals are 36 and 123 months, respectively (OR, 15.55; 95% confidence interval, 3.81–63.36).Conclusions: We have identified a non-coding transcriptional signature predictor of survival and biomarker of relapse for stage I EOC. Clin Cancer Res; 23(9); 2356–66. ©2016 AACR.

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    Clinical Cancer Research

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    Keywords

    Cancer InterceptionBiomarkers and interventionCancer PreventionEarly DetectionComputational MethodsGene expression profilingGene RegulationPosttranscriptional and translational controlGynecological CancersOvarian cancerOncogenes & Tumor Suppressors

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