CCNE1 amplification is a recurrent alteration associated with unfavourable outcome in tubo-ovarian highgrade serous carcinoma (HGSC). We aimed to investigate whether immunohistochemistry (IHC) can be used to identify CCNE1 amplification status and to validate whether CCNE1 high-level amplification and overexpression are prognostic in HGSC. A testing set of 528 HGSC samples stained with two optimised IHC assays (clones EP126 and HE12) was subjected to digital image analysis and visual scoring. DNA and RNA chromogenic in situ hybridisation for CCNE1 were performed. IHC cutoff was determined by receiver operating characteristics (ROC). Survival analyses (endpoint ovarian cancer specific survival) were performed and validated in an independent validation set of 764 HGSC. Finally, combined amplification/expression status was evaluated in cases with complete data (n = 1114). CCNE1 high-level amplification was present in 11.2% of patients in the testing set and 10.2% in the combined cohort. The optimal cutoff for IHC to predict CCNE1 high-level amplification was 60% positive tumour cells with at least 5% strong staining cells (sensitivity 81.6%, specificity 77.4%). CCNE1 high-level amplification and overexpression were associated with survival in the testing and validation set. Combined CCNE1 high-level amplification and overexpression was present in 8.3% of patients, mutually exclusive to germline BRCA1/2 mutation and significantly associated with a higher risk of death in multivariate analysis adjusted for age, stage and cohort (hazard ratio = 1.78, 95 CI% 1.38-2.26, p < 0.0001). CCNE1 high-level amplification combined with overexpression identifies patients with a sufficiently poor prognosis that treatment alternatives are urgently needed. Given that this combination is mutually exclusive to BRCA1/2 germline mutations, a predictive marker for PARP inhibition, CCNE1 high-level amplification combined with overexpression may serve as a negative predictive test for sensitivity to PARP inhibitors.

Ovarian carcinoma histotypes are critical for research and patient management and currently assigned by a combination of histomorphology +/- ancillary immunohistochemistry (IHC). We aimed to validate the previously described IHC algorithm (Calculator of Ovarian carcinoma Subtype/histotype Probability version 3, COSPv3) in an independent population-based cohort, and to identify problem areas for IHC predictions. Histotype was abstracted from cancer registries for eligible ovarian carcinoma cases diagnosed from 2002 to 2011 in Alberta and British Columbia, Canada. Slides were reviewed according to World Health Organization 2014 criteria, tissue microarrays were stained with and scored for the 8 COSPv3 IHC markers, and COSPv3 histotype predictions were calculated. Discordant cases for review and COSPv3 prediction were arbitrated by integrating morphology with IHC results. The integrated histotype (N=880) was then used to identify areas of inferior COSPv3 performance. Review histotype and integrated histotype demonstrated 93% agreement suggesting that IHC information revises expert review in up to 7% of cases. There was also 93% agreement between COSPv3 prediction and integrated histotype. COSPv3 errors predominated in 4 areas: endometrioid carcinoma (EC) versus clear cell (N=23), EC versus low-grade serous (N=15), EC versus high-grade serous (N=11), and high-grade versus low-grade serous (N=6). Most problems were related to Napsin A-negative clear cell, WT1-positive EC, and p53 IHC wild-type high-grade serous carcinomas. Although 93% of COSPv3 prediction accuracy was validated, some histotyping required integration of morphology with ancillary test results. Awareness of these limitations will avoid overreliance on IHC and misclassification of histotypes for research and clinical management.