Abstract BRCA-associated homologous recombination deficiency (HRD) is present in ~ 50% of high-grade serous carcinomas (HGSC) and predicts sensitivity to platinum-based therapy. However, there is little understanding of why some patients with BRCA-deficient tumors experience unexpectedly poor outcomes. We profiled 154 tumors, enriched for patients with BRCA-deficient tumors that experienced short overall survival (≤ 3 years, n = 42), using whole-genome, transcriptome, and methylation analyses. All but one BRCA-deficient tumor exceeded an accepted HRD genomic scarring threshold. However, patients with BRCA1-deficient HGSC with a more elevated HRD score survived significantly longer. Patients with BRCA2-deficient HGSC and loss of NF1 survived twice as long as those without NF1 loss, whereas PIK3CA or RAD21 amplification defined BRCA2-deficient HGSC with exceptionally short survival. BRCA1-deficient tumors in short survivors had evidence of immunosuppressive c-kit signaling and EMT. In a large HGSC cohort (n = 1,389) including 282 individuals with pathogenic germline BRCA variants (gBRCApv), the location of the mutation within functional domains stratified clinical outcomes. Notably, residual disease after primary surgery had limited prognostic effect in gBRCApv-carriers compared to non-carriers. Our findings indicate that tumor HR proficiency in the context of therapy response and survival is not a binary property, and highlight genomic and immune modifiers of outcomes in BRCA-deficient HGSC.
CCNE1 and survival of patients with tubo‐ovarian high‐grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study
Cancer | December 27, 2022 | Volume: 129 | Issue: 5 | Pages: 697-713
AbstractBackgroundCyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo‐ovarian high‐grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large‐scale, histotype‐specific validation has been performed. The hypothesis was that high‐level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.MethodsWithin the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.ResultsHigh‐level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high‐level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08‐1.47, p = .034, and HR, 1.18; 95% CI, 1.05‐1.32, p = .015, respectively). This was also true for cases with combined high‐level amplification/overexpression (HR, 1.26; 95% CI, 1.09‐1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1‐SD increase; 95% CI, 0.94‐1.06; p = .58). CCNE1 high‐level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.ConclusionThis study provides large‐scale validation that CCNE1 high‐level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.
Validated biomarker assays confirm that
ARID1A
loss is confounded with
MMR
deficiency,
CD8
The Journal of Pathology | December 13, 2021 | Volume: 256 | Issue: 4 | Pages: 388-401
Abstract Purpose: Gene expression–based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications. See related commentary by McMullen et al., p. 5271
Association of p16 expression with prognosis varies across ovarian carcinoma histotypes: an Ovarian Tumor Tissue Analysis consortium study
The Journal of Pathology: Clinical Research | July 30, 2018 | Volume: 4 | Issue: 4 | Pages: 250-261
AbstractWe aimed to validate the prognostic association of p16 expression in ovarian high‐grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical‐grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis‐associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47–2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30–2.75, p = 0.004), while absence was associated with shorter OS in low‐grade serous carcinomas (HR: 2.95, 95% CI 1.61–5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype‐specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low‐grade serous carcinoma justifies CDK4 inhibition.
Etiology of hormone receptor positive breast cancer differs by levels of histologic grade and proliferation
International Journal of Cancer | March 1, 2018 | Volume: 143 | Issue: 4 | Pages: 746-757
Limited epidemiological evidence suggests that the etiology of hormone receptor positive (HR+) breast cancer may differ by levels of histologic grade and proliferation. We pooled risk factor and pathology data on 5,905 HR+ breast cancer cases and 26,281 controls from 11 epidemiological studies. Proliferation was determined by centralized automated measures of KI67 in tissue microarrays. Odds ratios (OR), 95% confidence intervals (CI) and p‐values for case–case and case–control comparisons for risk factors in relation to levels of grade and quartiles (Q1–Q4) of KI67 were estimated using polytomous logistic regression models. Case–case comparisons showed associations between nulliparity and high KI67 [OR (95% CI) for Q4 vs. Q1 = 1.54 (1.22, 1.95)]; obesity and high grade [grade 3 vs. 1 = 1.68 (1.31, 2.16)] and current use of combined hormone therapy (HT) and low grade [grade 3 vs. 1 = 0.27 (0.16, 0.44)] tumors. In case–control comparisons, nulliparity was associated with elevated risk of tumors with high but not low levels of proliferation [1.43 (1.14, 1.81) for KI67 Q4 vs. 0.83 (0.60, 1.14) for KI67 Q1]; obesity among women ≥50 years with high but not low grade tumors [1.55 (1.17, 2.06) for grade 3 vs. 0.88 (0.66, 1.16) for grade 1] and HT with low but not high grade tumors [3.07 (2.22, 4.23) for grade 1 vs. 0.85 (0.55, 1.30) for grade 3]. Menarcheal age and family history were similarly associated with HR+ tumors of different grade or KI67 levels. These findings provide insights into the etiologic heterogeneity of HR+ tumors.
Dose-Response Association of CD8
+
Tumor-Infiltrating Lymphocytes and Survival Time in High-Grade Serous Ovarian Cancer
AbstractAutomated methods are needed to facilitate high‐throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large‐scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37–0.87) and study (kappa range = 0.39–0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p‐value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000–4,500 cells: kappa = 0.78) than those with lower counts (50–500 cells: kappa = 0.41; p‐value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre‐ and post‐analytical quality control procedures are necessary in order to ensure satisfactory performance.
A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11
Human Molecular Genetics | September 14, 2012 | Volume: 21 | Issue: 24 | Pages: 5373-5384