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

L Rai; A Ravaggi; E Bignotti; RL Hollis; DW Garsed; A Pandey; KB Papalois; F Patel; Y Kamel; L Campo; A Easton; J Nulsen; B Roskams-Hieter; M Artibani; L Wang; N Hussain; L Wang; N Zaarour; A Aggarwal; A Ahmed-Ebbiary; A Al-Deka; M Churchman; CS Herrington; L Ardighieri; F Ferrari; C Yau; C Gourley; F Odicino; AA Ahmed

Journal article

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

L Rai, A Ravaggi, E Bignotti, RL Hollis, DW Garsed, A Pandey, KB Papalois, F Patel, Y Kamel, L Campo, A Easton, J Nulsen, B Roskams-Hieter, M Artibani, L Wang, N Hussain, L Wang, N Zaarour, A Aggarwal, A Ahmed-Ebbiary Show all

Clinical Cancer Research | Published : 2026

DOI: 10.1158/1078-0432.CCR-24-4250

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, re-spectively; and a meta-analysis of 1,023 tum..

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