Abstract 2471: Pan-cancer catalog of Differentially Methylated Regions by Rocker-meth, a new computational method
Authors: Matteo Benelli, Alberto Magi, Dario Romagnoli, Gian Marco Franceschini, Chiara Biagioni, Ilenia Migliaccio, Luca Malorni, Angelo Di Leo, Francesca Demichelis
Journal: Cancer Research (2019)

Abstract DNA methylation (DNAm) is an essential player of gene regulation and therefore one of the most studied epigenetic mechanisms. Alterations of DNAm have been associated with a wide range of diseases, including cancer. Most studies on DNAm focused on the characterization of methylation sites, despite the recognition that DNAm changes spanning entire genomic regions are common in cancer tissues with respect to benign cells, referred to as Differentially Methylated Regions (DMRs). Here we report on a new computational method to identify DMRs both from array and Bisulfite Sequencing data. Rocker-meth consists of four main modules: 1) computation of Area Under the Curve (AUC) values from Receiver operating characteristic (ROC) Curve analysis of methylation levels (i.e., beta values) in tumor versus normal samples; 2) segmentation of AUC values by a tailored Heterogeneous Shifting Level Model (HSLM); 3) estimation of the statistical significance of AUC segments by Wilcoxon-Mann-Whitney test on beta values of tumor versus normal samples; 4) identification of sample specific DMRs by Z-score statistics. Tests on synthetic DNAm profiles demonstrated that Rocker-meth outperforms current state-of-the-art tools. Specifically, it showed markedly higher precision and recall in the presence of the lowest signal-to-noise ratios that mimic more than 40% of real human samples data. By exploiting well known features of DNAm in human cancers, we also demonstrated that Rocker-meth outperforms the most used array-based DMR detection tools in real data. We then drafted the first pan-cancer catalog of DMRs based on the characterization of more than 6,000 human samples DNAm data of 14 tumor types from TCGA and other recent studies and studied the characteristics of hyper and hypo DMRs in terms of structure, genomic locations and functional role. Pan-cancer integrative analysis of DMRs and gene expression recapitulated well-known associations, validating the accuracy of our method. Finally, we demonstrated the reliability of Rocker-meth to perform sample-wise analysis. This was possible thanks to the intrinsic characteristic of DMRs to be extremely recurrent within a given tumor type, supporting our previous observation for methylation sites and in contrast to genomic alterations such as Single Nucleotide Variants (SNVs) and Somatic Copy Number Variants (SCNAs). Strikingly, DMRs detected by Rocker-meth were informative in segregating prostate and breast adenocarcinoma based on their molecular subtypes, confirming the results from DNAm site analyses. The pan-cancer catalog of DMRs with sample level characterization could be used to investigate across cancer mechanisms of tumorigenesis or to query synthetic lethal events. Citation Format: Matteo Benelli, Alberto Magi, Dario Romagnoli, Gian Marco Franceschini, Chiara Biagioni, Ilenia Migliaccio, Luca Malorni, Angelo Di Leo, Francesca Demichelis. Pan-cancer catalog of Differentially Methylated Regions by Rocker-meth, a new computational method [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2471.