Characterisation of the mutational landscape of chronic lymphocytic leukaemia using genome-wide approaches

Chronic lymphocytic leukaemia (CLL) is characterised by a chronically relapsing course and clinical and biological heterogeneity, and none of the conventional treatment options are curative. CLL cases lack disease-defining mutations but they can be broadly classified into two prognostic groups by the immunoglobulin heavy chain variable (IgHV) gene mutational status, where CLL patients with IgHV unmutated status are associated with a more aggressive clinical course. This broad prognostic sub-classification was improved by the establishment of the Döhner five hierarchical classifications based on cytogenetic abnormalities, which do not entirely explain the genetic basis of the clinical heterogeneity of CLL patients. Recent genome-wide technologies have identified multiple additional recurrent alterations, some of which may have independent prognostic value. This increase in the number of potential CLL genomic markers necessitates the simultaneous screening of multiple genes in the clinic. Next Generation Sequencing (NGS) technologies offer significant advantages over other conventional molecular techniques in screening these genes, however, they have not been evaluated sufficiently, nor standardised for clinical implementation. Moreover, most CLL whole genome sequencing (WGS) and whole exome sequencing (WES) studies investigating the genetic heterogeneity of CLL have looked only at the coding regions, and data concerning the significance of recurrent mutations in regulatory elements is lacking. The elucidation of CLL genomic complexity and heterogeneity may contribute to our understanding about molecular pathogenesis in CLL, and may subsequently lead to an improved clinical management through specifically designed targeted therapies. Thus, the goal of this thesis was to characterise, using genome-wide technologies, the genomic landscape of CLL patients. This thesis also validated both the sensitivity and specificity of targeted sequencing panel (TSP) and WGS for clinical implementation in routine diagnostics, by investigating well-established and novel genomic markers of CLL.
An integrated approach using TSP technologies with genome-wide high-density SNP array data was used to investigate candidate genes that are disrupted or mutated in CLL. This analysis was based on the hypothesis that minimally overlapping regions (MORs) would pinpoint genes that harboured recurrent acquired mutations driving CLL pathogenesis, and/or may also be enriched with common inherited single nucleotide SNPs that predispose for the development of CLL. Accordingly, this analysis identified recurrent somatic mutations affecting FBXW7 and SETD2, which was found to be consistent with findings of recent literature. Additionally, it identified a common SNP in TLR4 with a higher frequency in the CLL cohort compared to the normal population. The comparison between TSP and WGS highlighted the advantage of each technique and showed the importance of validating TSP bioinformatics pipelines before introducing them to clinical service and in the diagnostic services. Finally, functional annotation of WGS data of 46 CLL genomes revealed distinct genomic profiles in the two CLL IgHV subgroups, which may be explained, to some extent, by the prevalence of extracted mutational signatures in the two groups. Collectively, the data presented by this thesis provide a new insight into CLL genomic complexity and heterogeneity.

Advisor: Schuh, A
Knight, S