Abstract IS01: METHYLATION PROFILING OF OVARIAN CANCER TO STUDY ETIOLOGIC AND PROGNOSTIC HETEROGENEITY AND TO DEVELOP A MOLECULAR CLASSIFIER
Authors: Bodelon Clara , Killian J. Keith , Sampson Joshua N. , Stevenson Holly , Anderson William F. , Matsuno Rayna , Brinton Louise A. , Lissowska Jolanta , Sherman Mark E. , Wentzensen Nicolas 
Published: June 2017

BACKGROUND. Ovarian cancer is a heterogeneous disease that is divisible into multiple subtypes with variable pathogenesis, etiology and biological behavior. We analyzed DNA methylation profiling data to identify biologic subgroups of ovarian cancer and study their relationship with histologic subtypes and prognosis. Additionally, we developed a molecular classifier for classification of ovarian tumors in epidemiologic studies.

METHODS. A total of 176 paraffin embedded ovarian epithelial tumor tissues, including the four major epithelial ovarian tumor subtypes (serous, endometrioid, mucinous and clear cell) and tumors of low malignant potential (LMP) were selected from two different sources: The Polish Ovarian Cancer study, an incident population–based case–control study conducted from 2001–2004, and the Surveillance, Epidemiology, and End Results Residual Tissue Repository (SEER RTR), which included ovarian tumors blocks collected between 1994 and 2004 from the Iowa and Hawaii SEER registries. The distributions of tumor histologic subtypes and grades from the studies were similar. All analyses were restricted to Caucasian women. Methylation profiling was conducted using the Illumina 450K methylation array. Analyses were restricted to the 22 autosomal chromosomes and non–SNP probes. Fourteen samples that did not pass quality control were excluded from the analysis.

RESULTS. Among 162 samples, 32 were from the Polish study and 130 were from the SEER RTR. Unsupervised hierarchical clustering of the 5,000 most variable CpG sites showed 4 major clusters: Cluster 1 with 79% invasive serous and 14% endometrioid carcinomas, including the majority of high grade carcinomas; cluster 2 with 77% either endometrioid or clear cell carcinomas; cluster 3 with 71% serous LMP; and cluster 4 with 73% mucinous carcinomas. We observed significant survival differences across these clusters (long–rank test P= 4.27×10–6), similar to differences observed for histologic subtypes. Within high grade (HG) serous carcinomas, clustering showed three subgroups with prognostic significance (long–rank test P= 0.008).

CONCLUSIONS. Our results suggest that methylation–based subtypes provide a classification of ovarian tumors that are in agreement with morphologic subtypes and probable mechanisms of origin. Unsupervised clustering analysis of HG serous carcinomas showed subtypes within HG serous with significance survival difference. Ongoing analyses will compare performance of the methylation classifier with histologic subtype in relation to risk factors and prognosis.

Citation Format: Clara Bodelon, J. Keith Killian, Joshua N. Sampson, Holly Stevenson, William F. Anderson, Rayna Matsuno, Louise A. Brinton, Jolanta Lissowska, Mark E. Sherman, Nicolas Wentzensen. METHYLATION PROFILING OF OVARIAN CANCER TO STUDY ETIOLOGIC AND PROGNOSTIC HETEROGENEITY AND TO DEVELOP A MOLECULAR CLASSIFIER [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr IS01.