OMIC-06. MOLECULAR SUBGROUPING OF MEDULLOBLASTOMA VIA LOW-DEPTH WHOLE GENOME BISULFITE SEQUENCING. (1st June 2021) - Thompson, Dean; Castle, Jemma; Hicks, Debbie; Clifford, Steve; Schwalbe, Ed
Abstract: Introduction: International consensus recognises four molecular subgroups of medulloblastoma, each with distinct molecular features and clinical outcomes. The current gold-standard for subgroup assignment is DNA methylation microarray. There is an unmet need to develop platform-independent subgrouping assays which are both non-proprietary and compatible with rapidly-expanding WGS capacity in healthcare. Whole Genome Bisulfite Sequencing (WGBS) enables the assessment of genome-wide methylation status at single-base resolution. Previously, WGBS adoption has been limited by cost and sample quality/quantity requirements. Its application for routine detection of medulloblastoma subgroups has not previously been reported. Methodology: Two datasets were utilised; 36 newly-sequenced low-depth (10x coverage) and 34 publicly-available high-depth (30x) WGBS medulloblastomas, all with matched DNA methylation microarray data. We compared platform concordance and identified molecular subgroups. Machine-learning WGBS-based subgroup classifiers were optimised and compared between platforms. Aneuploidy and mutation detection using WGBS was optimised and compared to microarray-derived estimates where possible. Finally, comprehensive subgroup-specific DNA methylation signatures were identified. Results: We optimised a pipeline for processing, quality control and analysis of low-depth WGBS data, suitable for routine molecular subgrouping and aneuploidy assessment. We demonstrated the suitability of fresh-frozen and FFPE DNA for WGBS, and, using downsampling, showed that subgroup calling is robust at coverages as low as 2x. We identified differentially methylated regions that, due to poor representation, could not be detected using methylation microarrays. Molecular subgroups of medulloblastoma assigned using WGBS were concordant with array-based definitions, and WGBS-derived classifier performance measures exceeded microarray-derived classifiers. Conclusion: We describe a platform-independent assay for molecular subgrouping of medulloblastoma using WGBS. It performs equivalently to current array-based methods at comparable cost ($405 vs $596) and provides a proof-of-concept for its routine clinical adoption using standard WGS technology. Finally, the full methylome enabled elucidation of additional biological heterogeneity that has hitherto been inaccessible.