Genomic determinants of chronic lymphocytic leukemia progression: from individual drivers to a heterogeneous genetic makeup

[eng] Chronic lymphocytic leukemia (CLL) is the most common form of adult leukemia in Western countries. Although the disease might follow an indolent course, it rapidly progresses in a fraction of cases, become resistant to treatment, and eventually transform to a more aggressive B-cell lymphoma, k...

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Detalles Bibliográficos
Autor: Nadeu Prat, Ferran
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/171259
Acceso en línea:https://hdl.handle.net/2445/171259
http://hdl.handle.net/10803/669770
Access Level:acceso abierto
Palabra clave:Ciències de la salut
Bioinformàtica
Genòmica
Càncer
Leucèmia limfocítica crònica
Medical sciences
Bioinformatics
Genomics
Cancer
Chronic lymphocytic leukemia
Descripción
Sumario:[eng] Chronic lymphocytic leukemia (CLL) is the most common form of adult leukemia in Western countries. Although the disease might follow an indolent course, it rapidly progresses in a fraction of cases, become resistant to treatment, and eventually transform to a more aggressive B-cell lymphoma, known as Richter syndrome. The mechanisms underlying these distinct clinical courses are not fully understood. In this Thesis, we aimed to elucidate the genomic determinants of CLL progression, to provide tools to characterize these tumors from next-generation sequencing data, and to extract key biological findings that could improve the management of the patients. In the first chapter (Studies 1 and 2), we characterized a noncoding mutation effecting the small nuclear RNA U1, a component of the spliceosome involved in the 5’ splice site recognition via base paring. Mutations in this gene altered the splicing and expression of multiple genes, were found in CLL tumors lacking clinically relevant genomic alterations, and were independently associated with patients’ outcome. In the next chapter (Studies 3, 4, and 5), we aimed to deeper into the subclonal architecture of CLL. We identified mutations present in small subpopulations associated with disease progression, recognized common evolutionary trajectories, and showed that the integration of the whole tumor architecture into prognostic models could improve the stratification of the patients. In the third chapter (Study 6), we analyzed the whole genome of CLL patients undergoing Richter syndrome and observed that this transformation was accompanied by an increased mutational and genomic complexity. We identified a unifying mutational process that could orchestrate this genomic chaos. In the fourth chapter (Studies 7 and 8), we developed a bioinformatic algorithm aimed to reconstruct the immunoglobulin gene rearrangements in lymphoid neoplasms from whole-genome sequencing, which might facilitate the use of this methodology in the future clinical practice. By applying this algorithm, we studied a recurrent mutation in the IGLV3-21 gene associated with an aggressive disease with a strong influence on the current and future risk stratification of CLL patients. Altogether, this Thesis has contributed to understand the genomic determinants of CLL progression through the analysis of its dynamic and heterogeneous genetic makeup.