Methylomic Analysis of Ovarian Cancers Identifies Tumor-Specific Alterations Readily Detectable in Early Precursor Lesions

Abstract

Purpose: High-grade serous ovarian carcinoma (HGSOC) typically remains undiagnosed until advanced stages when peritoneal dissemination has already occurred. Here, we sought to identify HGSOC-specific alterations in DNA methylation and assess their potential to provide sensitive and specific detection of HGSOC at its earliest stages.

Experimental design: MethylationEPIC genome-wide methylation analysis was performed on a discovery cohort comprising 23 HGSOC, 37 non-HGSOC malignant, and 36 histologically unremarkable gynecologic tissue samples. The resulting data were processed using selective bioinformatic criteria to identify regions of high-confidence HGSOC-specific differential methylation. Quantitative methylation-specific real-time PCR (qMSP) assays were then developed for 8 of the top-performing regions and analytically validated in a cohort of 90 tissue samples. Lastly, qMSP assays were used to assess and compare methylation in 30 laser-capture microdissected (LCM) fallopian tube epithelia samples obtained from cancer-free and serous tubal intraepithelial carcinoma (STIC) positive women.

Results: Bioinformatic selection identified 91 regions of robust, HGSOC-specific hypermethylation, 23 of which exhibited an area under the receiver-operator curve (AUC) value ≥ 0.9 in the discovery cohort. Seven of 8 top-performing regions demonstrated AUC values between 0.838 and 0.968 when analytically validated by qMSP in a 90-patient cohort. A panel of the 3 top-performing genes (c17orf64, IRX2, and TUBB6) was able to perfectly discriminate HGSOC (AUC 1.0). Hypermethylation within these loci was found exclusively in LCM fallopian tube epithelia from women with STIC lesions, but not in cancer-free fallopian tubes.

Conclusions: A panel of methylation biomarkers can be used to accurately identify HGSOC, even at precursor stages of the disease.

Figure 1.. Discovery and Validation of Methylation Biomarkers for HGSOC.

Illustration of general anatomical locations, histology and number of the sample types used in this study, which assessed via both genome-wide (MethylationEPIC) and locus-specific (SMART-MSP) methylation assessment techniques. Fresh-frozen tumor tissues and normal mucosae were used for discovery and analytical validation of select differentially-methylated regions (DMRs). Nine pairs of FFPE STIC and adjacent, morphologically-normal epithelia as well as fallopian epithelia from 12 cancer-free women were initially assessed by immunohistochemistry (IHC) before being processed by LCM and evaluated for the presence of methylation within validated DMRs.

Figure 2.. Unsupervised analysis of genome-wide methylation in healthy and malignant gynecologic tissues.

(a) Methylation heatmap showing unsupervised clustering of the top 5000 differentially-methylated probes as determined by MethylationEPIC BeadChip analysis the discovery cohort of 96 gynecologic tissue samples. Sample types are indicated by colored bars on top. Shown below are the relative proportion of probes in each respective CpG-context. (b) Multidimensional analysis of the top 5000 DMRs, showing highly similar methylomes of healthy gynecologic mucosae that are readily distinguishable from the majority of malignant tissues.

Figure 3.. Overall schema for discovery and validation of HGSOC-specific methylation biomarkers.

After initial methylomic analysis of 96 tissue samples by the EPIC BeadChip platform, high-confidence DMRs meeting selective bioinformatics criteria were identified. SMART-MSP assays were then developed for eight of the top-performing DMRs and used to analytically validate their utility as tumor-specific methylation biomarkers. Lastly, assays for the seven validated biomarkers were used to assess methylation in laser capture microdissected STIC precursor lesions, respective adjacent epithelia and epithelia from cancer -free fallopian tubes.

Figure 4.. Collective EPIC BeadChip performance of the eight top-performing DMRs developed into SMART-MSP assays

(a) Average composite methylation levels and (b) ROC curve analysis of the eight top-performing, high-confidence DMRs (c17orf64, IRX2, TUBB6, c6orf174, NEUROD1, OTX2, LOC200726 and PTPRN) assayed by SMART-MSP in the validation cohort.

Figure 5.. Validation of eight top-performing DMRs.

Violin plots of percent methylated reference (PMR) values for the eight DMRs in each of the gynecologic sample types as determined by their respective SMART-MSP assay in the second, 90-patient, validation tissue cohort.

Figure 6.. ROC curve performance of eight top-performing DMRs.

(a) ROC curves of each SMART-MSP assay as well as the collective performance of the top 3 DMRs (IRX2, c17orf164, TUBB6) for discrimination of HGSOC from all healthy mucosae samples in the validation cohort. (b) Corresponding ROC AUC values for discrimination of HGSOC and other cancer types from all healthy mucosae.

Figure 7.. Assessment of hypermethylation in laser-capture microdissected STIC and normal fallopian tube epithelia.

(a) Anatomical diagrams showing the approximate locations of each STIC sample, as well as any associated tumors. Adjacent normal epithelial samples were taken from unspecified locations within the corresponding fallopian tube. (b) Hypermethylated loci detected in STIC (solid bars) and respective adjacent normal (dotted bars) laser-capture microdissected fallopian tube epithelia. None of loci exhibited hypermethylation in any of the 12 fallopian tube epithelial samples from cancer-free women. *Over PMR threshold