PO-386 Decoding the regulatory role and epiclonal dynamics of DNA methylation in 1482 breast tumours

Introduction Breast cancer is a clinically and molecularly heterogeneous disease displaying distinct therapeutic responses. Although recent studies have explored the genomic and transcriptomic landscapes, the epigenetic architecture has received less attention. Material and methods An optimised Reduced Representation Bisulfite Sequencing (RRBS) protocol was used to profile the methylomes of 1482 primary breast tumours (and 237 matched adjacent normal tissues) from the METABRIC cohort. Existing copy number, mRNA/miRNA expression and gene panel mutation data from the same tumours, previously published Curtis et al, Nature 2012 was available. Results and discussions Noticeable epigenetic drift (both gain and loss of homogeneous DNA methylation patterns) was observed in breast tumours when compared to normal tissues, with markedly higher differences in late replicating genomic regions. The extent of epigenetic drift was also found to be highly heterogeneous between the breast tumours and was sharply correlated with the tumour’s mitotic index, indicating that epigenetic drift is largely a consequence of accumulation of passive cell division related errors. A novel algorithm called DMARC (Directed Methylation Altered Regions in Cancer) was developed that utilised the tumour-specific drift rates to discriminate between methylation alterations attained as a consequence of stochastic cell division errors ( background ) and those reflecting a more deterministic biological process ( directed ). Directed methylation alterations were significantly enriched for gene expression changes in breast cancer, compared to background alterations. By integrating with copy number and mutational profiles for these tumours, mutually exclusive patterns between DNA methylation and genomic aberrations were detected. This led to the identification of potential tumour suppressors and oncogenes, and revealed the deterministic nature of these epigenetic alterations. Finally, intra-tumoural methylation content was analysed to identify tumours associated with low epigenetic polymorphism implying a deterministic process vs. those with high polymorphism reflecting a stochastic process. Intra-tumoural heterogeneity as well as the extent of epiallelic burden were found to be prognostic, and revealed a distinction in the role of epiclonal dynamics in different breast cancer subtypes. Conclusion This constitutes the largest breast cancer methylome study, and has revealed the DNA methylation basis of inter-patient as well as intra-tumour heterogeneity in breast cancer.