Abstract Purpose: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. Experimental Design: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. Results: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. Conclusions: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838
Validated biomarker assays confirm that
ARID1A
loss is confounded with
MMR
deficiency,
CD8
Abstract A03: PrOTYPE (Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE): The development and validation of a clinical-grade consensus classifier for the molecular subtypes of high-grade serous tubo-ovarian cancer
Abstract Background: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC) are distinguished by differential immune and stromal infiltration and may provide opportunities for targeted therapies. Integration of molecular subtypes into clinical trials has been hindered by inconsistent subtyping methodology. Methods: Adopting two independent approaches, we derived and internally validated algorithms for molecular subtype prediction from gene-expression array data in 1,650 tumors. We applied resulting models to assign labels to 3829 HGSOCs from the Ovarian Tumor Tissue Analysis (OTTA) consortium evaluated on NanoString. Using the labeled NanoString data, we developed, confirmed, and validated a minimal gene set, clinical-grade test and prediction tool. We also used the OTTA dataset to evaluate associations between molecular subtype, biologic, and clinical features. Findings: The locked-down test included a model with 55 genes that predicted HGSOC molecular subtype with >95% accuracy. Subtype varied between primary and metastatic site taken at the time of primary surgery, and was significantly associated with age, stage, CD8+ lymphocyte infiltration, residual disease, and outcome. In multivariable models, molecular subtypes lose their prognostic significance in the presence of risk factors such as residual disease and BRCA1/2 germline mutations. Interpretation: We validated the Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE, or PrOTYPE, following the Institute of Medicine guidelines for the development of omics-based tests. This simple-to-use, cost-effective, fully defined, and locked-down clinical-grade assay will facilitate molecular subtype stratification into clinical trial design. PrOTYPE will allow for objective assessment of HGSOC molecular subtype predictive value in precision medicine applications. Citation Format: Aline Talhouk, Joshy George, Chen Wang, Ellen Goode, Susan Ramus, Jennifer Doherty, David Bowtell, Michael Anglesio, OTTA Consortium. PrOTYPE (Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE): The development and validation of a clinical-grade consensus classifier for the molecular subtypes of high-grade serous tubo-ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A03.
Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)
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
Molecular Classification of Epithelial Ovarian Cancer Based on Methylation Profiling: Evidence for Survival Heterogeneity
Abstract Purpose: Ovarian cancer is a heterogeneous disease that can be divided into multiple subtypes with variable etiology, pathogenesis, and prognosis. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes, copy number variation, RNA expression data, and outcomes. Experimental Design: A total of 162 paraffin-embedded ovarian epithelial tumor tissues, including the five major epithelial ovarian tumor subtypes (high- and low-grade serous, endometrioid, mucinous, and clear cell) and tumors of low malignant potential were selected from two different sources: The Polish Ovarian Cancer study, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR). Analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. For 45 tumors array copy number data were available. NanoString gene expression data for 39 genes were available for 61 high-grade serous carcinomas (HGSC). Results: Consensus nonnegative matrix factorization clustering of the 1,000 most variable CpG sites showed four major clusters among all epithelial ovarian cancers. We observed statistically significant differences in survival (log-rank test, P = 9.1 × 10−7) and genomic instability across these clusters. Within HGSC, clustering showed three subgroups with survival differences (log-rank test, P = 0.002). Comparing models with and without methylation subgroups in addition to previously identified gene expression subtypes suggested that the methylation subgroups added significant survival information (P = 0.007). Conclusions: DNA methylation profiling of ovarian cancer identified novel molecular subgroups that had significant survival difference and provided insights into the molecular underpinnings of ovarian cancer. See related commentary by Ishak et al., p. 5729
A gene expression prognostic signature for overall survival in patients with high-grade serous ovarian cancer.
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.
Abstract A27: The ovarian tumor tissue analysis (OTTA) consortium
Abstract Our understanding of ovarian cancer is complicated by disease heterogeneity. There are five major histological types, each with alterations in different pathways and distinct clinical outcomes. Even within these histological types there is clinical and molecular heterogeneity. The Ovarian Tumor Tissue Analysis (OTTA) consortium was established to validate prognostic markers for ovarian cancer in a large population of patients to allow stratification by histological type and molecular subtype. OTTA is currently a collaboration among 38 studies and has tissue microarrays (TMAs) from over 8,000 tumors available for immunohistochemical (IHC) analysis. In addition formalin fixed paraffin embedded (FFPE) tissue on slides or cores are available from the majority of OTTA studies for DNA and RNA analysis. Approximatley 60% of the cases are part of the Ovarian Cancer Association Consortium (OCAC) and have genotype data on over 200,000 single nucleotide polymorphisms and extensive epidemiological data. We recently performed IHC analysis of 12 markers using centralised staining and scoring to reduce heterogeneity and improve power to validate biomarkers. We showed that estrogen receptor and progesterone receptor were prognostic markers for endometrioid and high-grade serous carcinomas by performing the first robust subtype-specific analyses of these biomarkers in nearly 3000 patients. In contrast, FOLR1 expression was not associated with survival in 1507 high-grade serous carcinomas. We have shown that FFPE material from OTTA is suitable for RNA expression analysis on high through-put platforms such as the NanoString GX system. Expression analysis of 50 candidate genes in 244 high grade serous ovarian cancer cases has validated prognostic markers identified by The Cancer Genome Atlas (TCGA) project and investigated a series of novel candidate genes. IHC and RNA expression profiling from formalin fixed paraffin embedded (FFPE) tumor tissue is being used to better subclassify the ovarian tumors for further analysis. We would welcome groups with collections of ovarian tumor samples and corrsponding clinical data to join OTTA and participate in ongoing collaborative projects. Citation Format: Susan J. Ramus, Martin Köbel, Weiva Sieh, Michael S. Anglesio, Joshua Millstein, David D. Bowtell, James D. Brenton, Estrid Høgdall, Paul DP Pharoah, Ellen L. Goode, David G. Huntsman. The ovarian tumor tissue analysis (OTTA) consortium. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr A27.
Abstract A18: Defining ovarian mucinous tumors: Cancer genes and heterogeneity
Abstract Background: Mucinous ovarian carcinomas (MC) and mucinous borderline ovarian tumours (MBOT) are associated with ERBB2 amplification and KRAS activating mutations. These events occur in a near-mutually exclusive pattern, and KRAS mutations are more prevalent in MBOTs than MC's whereas ERBB2 amplification is more frequently seen in MCs. Frequencies of mutations in other oncogenes and tumour suppressor genes in MC are not well established though TP53, BRAF, NRAS, and CDKN2A mutations have all been reported. As these carcinomas are commonly chemo-resistant a definitive molecular categorization of this subtype is needed as treatment options are explored. Methods: We undertook review of pathology reports and after exclusion of potential gastric, appendiceal or pancreatic involvement over 100 mucinous ovarian tumours were identified. HPV testing was undertaken to exclude rare metastasis from endocervical primary site. All specimens were assayed for p53 expression via TMA and subject to sequencing of common cancer gene hotspots using Ion-Torrent or Illumina MiSeq. Previously derived data on ERBB2 status was combined in our analysis and, where available, samples showing heterogeneity of ERBB2 amplification and any other Ras-pathway activating mutation were microdissected with components evaluated independently for concurrent hotspot mutations. Results: All samples were consistent with mucinous tumours of ovarian origin and none were HPV positive. We detected mutations in KRAS, BRAF, CDKN2A, TP53, PTEN, PIK3CA as well as presumed somatic/detrimental, variants in APC that have not previously been reported in mucinous tumours. Despite some samples having enriched tumour content, lower than expected allelic frequencies of KRAS activating mutations suggested intra-tumoural heterogeneity. This was consistent with results observed previously with rare ERBB2 amplification coinciding KRAS mutations. Conclusions: The prevalence of Ras-pathway mutations, especially amongst borderline lesions, suggests these mutations are critical for tumour onset. However varying allelic frequencies of KRAS mutations suggest progression to carcinoma is strongly influenced by other molecular features. Citation Format: Michael S. Anglesio, Robertson Mackenzie, Stefan Kommoss, Boris J. Winterhoff, Benjamin Kipp, Jaoquin Garcia, Jesse S. Voss, Kevin Halling, Sarah Kerr, Janine Senz, Winnie Yang, Magnus von Knebel Doeberitz, Elena-Sophie Prigge, Miriam Reuschenbach, Anna V. Tinker, Blake Gilks, Jamie N. Bakkum-Gamez, David G. Huntsman, Jessica N. McAlpine. Defining ovarian mucinous tumors: Cancer genes and heterogeneity. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr A18.