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The Cancer Genome Atlas classification divides endometrial carcinoma in biologically distinct groups, and testing for p53, mismatch repair proteins (MMR), and polymerase ɛ (POLE) exonuclease domain mutations has been shown to predict the molecular subgroup and clinical outcome. While abnormalities in these markers have been described in ovarian endometrioid carcinoma, their role in predicting its molecular profile and prognosis is still not fully explored. Patients with ovarian endometrioid carcinomas treated surgically in a 14-year period were selected. Only tumors with confirmation of endometrioid histology and negative WT1 and Napsin-A were included. POLE mutational analysis and immunohistochemistry for p53, MLH1, MSH2, MSH6, and PMS2 was performed in formalin-fixed, paraffin-embedded tissue. Following the molecular classifier proposed for endometrial carcinoma (Br J Cancer2015;113:299-310), cases were classified as POLE mutated, MMR abnormal, p53 abnormal, and p53 wild type. Clinicopathologic information was recorded, including patient outcome. In all, 72 cases were included, distributed as follows: 7 (10%) POLE mutated; 6 (8%) MMR abnormal; 17 (24%) p53 abnormal; and 42 (58%) p53 wild type. The molecular classification correlated with disease-free survival in multivariate analysis (P=0.003), independently of tumor grade and stage. Correlation with overall survival approached statistical significance (P=0.051). POLE-mutated and MMR-abnormal tumors had excellent survival, whereas p53-abnormal tumors had significantly higher rates of recurrence and death. Ovarian endometroid carcinoma can be classified in clinically meaningful subgroups by testing for molecular surrogates, akin to endometrial cancer. MMR and POLE alterations seem to identify a subset of ovarian endometrioid carcinomas with excellent outcome; conversely, abnormal p53 carries a worse prognosis. In the era of personalized medicine, the use of these markers in the routine evaluation of ovarian endometrioid tumors should be considered.

Molecular-based classification algorithm for endometrial carcinoma categorizes ovarian endometrioid carcinoma into prognostically significant groups