Abstract

Myelodysplastic syndromes (MDS) are a heterogeneous group of blood cancers leading to an ineffective production of blood cells. I will present computational methods and results from a large screen of 111 cancer genes sequenced at 250x coverage in 738 MDS patients. To analyse such data we have developed a new variant caller which analyses all samples jointly to estimate the local distributions of sequencing artefacts, for an increased specificity. At the same time this method gains power from incorporating prior knowledge about mutational hotspots. The resulting mutational landscape of MDS displays complex patterns of pairwise association between genes, indicative of epistatic interactions involving components of the spliceosome machinery and epigenetic modifiers. Coupled with inferences on subclonal mutations, these data suggest a hypothesis of genetic ‘predestination’, in which early driver mutations, typically affecting genes involved in RNA splicing, dictate future trajectories of disease evolution with distinct clinical phenotypes. Driver mutations had equivalent prognostic significance whether clonal or subclonal, and leukemia-free survival deteriorated steadily as numbers of driver mutations increased. Thus, analysis of oncogenic mutations in large, well-characterized cohorts of patients illustrates the interconnections between the cancer genome and disease biology, with considerable potential for clinical application.