Wellcome Trust PhD Programme in Mathematical Genomics and Medicine. (360G-Wellcome-102276_Z_13_Z)

Breast cancer is one of the I eading causes of cancer death in women and is widely considered a heterogeneous disease with very different therapeutic responses and outcomes. Whi le recent advances have I ed to the integration of the genomic and transcriptomic architecture of breast cancers to refine the molecular classification of the disease, the methylation landscape has received less attention. By conducting the largest Next-generation sequencing based breast cancer methylome study, we aim to provide insights into the epigenetic mechanism of tumorigenesis. Furthermore, integrating the methylation landscape with other molecular data such as copy number aberrations (CNA), gene expression and mutations may identify therapeutically tractable signatures and improve classification towards a driver-based taxonomy.The predictive value of the candidate drivers will be investigated in Patient Derived Tumour Xenogra ffts, one of the best pre-clinical models that are able to recapitulate inter- and intratumour he terogeneity observed in patients. Multi-dimensional molecular data and high throughput drug screenings will be integrated to identify novel pharmacogenomics associations.Finally, a portfolio of rele van! molecular signatures will be defined for the purpose of characterisation of circulating tumour DNA. This would enable the possibility of a liquird biopsy for systemic non-invasive monitoring of breast cancer to guide therapeutic stra tegy.