Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.758012
Title: Applications of next-generation technologies in the diagnosis of haematological diseases and cancer
Author: Burns, Adam D.
ISNI:       0000 0004 7430 8163
Awarding Body: Oxford Brookes University
Current Institution: Oxford Brookes University
Date of Award: 2016
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Abstract:
The advent of massively-parallel next-generation sequencing (NGS) methods has provided researchers with a powerful tool with which to interrogate and characterise the molecular landscape of cancer genomes. Compared to existing methods of DNA sequencing, NGS platforms generate massive amounts of sequence data and, as a consequence, can reveal information not just on single nucleotide variations (SNVs), but also on copy-number aberrations, translocations and large insertions and deletions in a single experiment. Furthermore, targeted NGS provides the capability to focus on a small number of targets simultaneously, with high accuracy and sensitivity. The presence of specific molecular markers acts as predictors of disease outcome, survival rates and treatment response in individual patients. Screening for such markers has become routine practice in diagnostic laboratories using traditional methods of DNA analysis, are widely used in diagnostic laboratories around the world. Whilst these methods are proven and reliable, their limitations lie in the fact that they focus on only the most prevalent mutations in a particular cancer. The ability to investigate multiple gene targets within individual patients, to a high level of accuracy, and to monitor these changes over time will be a valuable tool in cancer diagnostics. As such, there is a potential use case for NGS techniques in routine diagnostics. Therefore, this thesis investigated the extent to which NGS platforms could be used in a clinical setting for the diagnosis and risk-stratification of both lymphoid and myeloid malignancies. A targeted next-generation sequencing panel was designed and validated against existing diagnostic methods. All mutations in the validation cohort were correctly identified. Both the specificity and sensitivity of the assay were determined and were considerably better than those of the current ‘gold-standard’ techniques. This panel has been fully validated and implemented into the diagnostic service at the John Radcliffe Hospital. The research applications of this panel were also demonstrated through the sequencing of a cohort of del(5q) MDS patients. It was not only found that mutations in TP53 and ASXL1 may be key drivers in the progression of del(5q) MDS into AML but also that 40% of del(5q) patients harboured at least one mutation. A number of mutations were below the limit of detection for Sanger sequencing, and so this study expands our knowledge of the del(5q) mutational landscape. Whole genome sequencing of 42 CLL cases revealed a high level of molecular heterogeneity, with mutations in key CLL driver genes including TP53, SF3B1, NOTCH1 and ATM. Both clinically relevant CNAs and translocations were detected in the cohort. Four mutation signatures were detected across the CLL genomes and are both associated with, and vary in their prevalence according to, specific clinical characteristics, including age and chemo-refractoriness. Mutations introduced as part of the SHM process in B-cells are present throughout the genome, including in patients with unmutated IgHV genes. Regions of localised hypermutation are present in CLL, with a number affecting genes associated with coding mutations in CLL, including ATM, KLHL6 and MEGF9. A number of mutation clusters are also identified in potentially regulatory regions of genes. In summary, this thesis demonstrates that both whole genome sequencing and targeted sequencing panels can be introduced into diagnostics to aid the clinical decision-making process and also reveal important new findings that increase our understanding of the pathogenesis of leukaemia.
Supervisor: Schuh, Anna ; Brooks, Susan Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.758012  DOI:
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