PURPOSE: The association between epithelial-to-mesenchymal transition (EMT) in high-grade serous ovarian cancer (HGSOC) and poor prognosis is known. However, molecularly defining a subset of tumors that reproducibly associates with poor prognosis has been an elusive goal in this disease. A molecular signature that can robustly identify patients with poor prognosis and guide treatment decisions, including surgical strategy and targeted therapies, can improve survival rates. EXPERIMENTAL DESIGN: We carried out RNA sequencing of 139 tumor samples (Brescia cohort); an external validation on 362 and 126 patients from the Scottish and Garsed cohorts, respectively; and a meta-analysis of 1,023 tumors to develop clinically useful risk groups. Identification of therapeutic targets was carried out by transcriptomic analyses of fluorescence-activated cell sorted (FACS) tumor epithelial cells and multiplex immunofluorescence assessment of tissue sections. RESULTS: In this study, we have validated the prognostic strength of the Oxford Classic-defined EMT in three independent patient cohorts: Brescia [HR = 3.6; 95% confidence interval (CI) of 1.59-7.97; P = 1.99e-03], Scottish (HR = 1.71; 95% CI of 1.08-2.70; P = 2.23e-02), and Garsed (Kruskal-Wallis P = 0.00071). OxC-based risk stratification of HGSOC could robustly identify poor-risk patients with a 5-year median survival for OxC high-risk and OxC low-risk groups of 13% and 50%, respectively (95% CI of 7.1%-23.5% vs. 36.1%-69.3%) in the Brescia cohort. Further analysis of the risk groups suggests that an alternative surgical strategy and a combination therapy involving EMT targeting drugs and immunomodulators could elicit improved clinical response in poor-risk patients. CONCLUSIONS: This study provides a clinically useful risk stratification strategy for HGSOC, as well as targeted treatment options for high-risk patients. See related commentary by Venegas et al., p. 10.

Oxford Classic-Defined EMT Risk Stratification of High-Grade Serous Ovarian Cancer for Guiding Treatment Decisions

Ravaggi A.;Bignotti E.;Ardighieri L.;Ferrari F.;Odicino F.;
2026-01-01

Abstract

PURPOSE: The association between epithelial-to-mesenchymal transition (EMT) in high-grade serous ovarian cancer (HGSOC) and poor prognosis is known. However, molecularly defining a subset of tumors that reproducibly associates with poor prognosis has been an elusive goal in this disease. A molecular signature that can robustly identify patients with poor prognosis and guide treatment decisions, including surgical strategy and targeted therapies, can improve survival rates. EXPERIMENTAL DESIGN: We carried out RNA sequencing of 139 tumor samples (Brescia cohort); an external validation on 362 and 126 patients from the Scottish and Garsed cohorts, respectively; and a meta-analysis of 1,023 tumors to develop clinically useful risk groups. Identification of therapeutic targets was carried out by transcriptomic analyses of fluorescence-activated cell sorted (FACS) tumor epithelial cells and multiplex immunofluorescence assessment of tissue sections. RESULTS: In this study, we have validated the prognostic strength of the Oxford Classic-defined EMT in three independent patient cohorts: Brescia [HR = 3.6; 95% confidence interval (CI) of 1.59-7.97; P = 1.99e-03], Scottish (HR = 1.71; 95% CI of 1.08-2.70; P = 2.23e-02), and Garsed (Kruskal-Wallis P = 0.00071). OxC-based risk stratification of HGSOC could robustly identify poor-risk patients with a 5-year median survival for OxC high-risk and OxC low-risk groups of 13% and 50%, respectively (95% CI of 7.1%-23.5% vs. 36.1%-69.3%) in the Brescia cohort. Further analysis of the risk groups suggests that an alternative surgical strategy and a combination therapy involving EMT targeting drugs and immunomodulators could elicit improved clinical response in poor-risk patients. CONCLUSIONS: This study provides a clinically useful risk stratification strategy for HGSOC, as well as targeted treatment options for high-risk patients. See related commentary by Venegas et al., p. 10.
2026
Inglese
32
1
188
202
15
Goal 3: Good health and well-being
29
info:eu-repo/semantics/article
262
Rai, L.; Ravaggi, A.; Bignotti, E.; Hollis, R. L.; Garsed, D. W.; Pandey, A.; Papalois, K. B.; Patel, F.; Kamel, Y.; Campo, L.; Easton, A.; Nulsen, J....espandi
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/636746
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