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Clinical and biological implications of genomic lesions in Chronic Lymphocytic Leukaemia

Clinical and biological implications of genomic lesions in Chronic Lymphocytic Leukaemia
Clinical and biological implications of genomic lesions in Chronic Lymphocytic Leukaemia
The aim of this thesis was to interrogate the application of targeted genomics in the clinical management of Chronic Lymphocytic Leukaemia (CLL), and to explore inhibitory compounds of recurrently mutated genes in CLL. The genomic landscape of the LRF CLL4 clinical trial (n=500) was conducted using a custom 25 gene targeted re-sequencing NGS panel, identifying 903 variants (1.8/patient). SF3B1 was identified as the most recurrently mutated gene in the cohort (26%), with the mutation landscape and subclonal architecture assessed for all 25 genes, identifying previously observed and novel associations. Clinical statistical survival analysis of the CLL4 TruSeq mutation data was undertaken for overall and progression-free survival, using traditional techniques and supervised machine learning tools. SF3B1 was identified to associate with OS independently of multiple CLL biomarkers in a multivariate model, and as an important feature by machine learning approaches. In addition, subclonal TP53 mutations predicted poor OS and PFS in cases treated with chlorambucil, and co-mutated/deleted del(11q) and BIRC3 were found to independently predict for a poor PFS. Since SF3B1 was found to be the most recurrently mutated gene in CLL4, and it associated with poor OS, it was selected for in vitro targeting using splicing inhibitors (Spliceostatin A and Meayamycin B) in CLL cells. Splicing inhibitors elicited substantial apoptosis, with Spliceostatin A inducing downregulation of Mcl-1 at the protein and RNA level, as well as acting synergistically with venetoclax in the context of micro-environmental support. Therefore, direct inhibition of Mcl-1 in CLL cells was undertaken using the Mcl-1 specific inhibitor UMI-77, eliciting apoptosis at micro molar concentrations. However, UMI-77 did induce resensitisation to the level of SSA in the context of CLL microenvironment support, suggesting that inhibition of Mcl-1 alone may not be sufficient to overcome BCL-2 inhibitor resistance in CLL. This work has demonstrated that the application of targeted genomic screening can offer added value to CLL patient management where the monitoring of SF3B1 mutations can identify additional adverse disease events. In relation to targeting drugs to the spliceosome pathway in CLL, where SF3B1 is a major component, the current work demonstrated effective re-sensitisation of CLL cells to combination inhibitor exposure. Together, this research has provided a greater understanding of the clinical utility of gene mutation screening and challenges surrounding development of the next generation of therapies to circumvent molecular pathways that CLL cells use to proliferate and drive disease progression.
University of Southampton
Blakemore, Stuart James
7800a021-1aa0-4d18-8c1c-b9de01f80472
Blakemore, Stuart James
7800a021-1aa0-4d18-8c1c-b9de01f80472
Strefford, Jon
3782b392-f080-42bf-bdca-8aa5d6ca532f
Cragg, Mark
ec97f80e-f3c8-49b7-a960-20dff648b78c
Steele, Andrew
4349f6aa-2e3a-49a8-be73-7716056ae089

Blakemore, Stuart James (2017) Clinical and biological implications of genomic lesions in Chronic Lymphocytic Leukaemia. University of Southampton, Doctoral Thesis, 352pp.

Record type: Thesis (Doctoral)

Abstract

The aim of this thesis was to interrogate the application of targeted genomics in the clinical management of Chronic Lymphocytic Leukaemia (CLL), and to explore inhibitory compounds of recurrently mutated genes in CLL. The genomic landscape of the LRF CLL4 clinical trial (n=500) was conducted using a custom 25 gene targeted re-sequencing NGS panel, identifying 903 variants (1.8/patient). SF3B1 was identified as the most recurrently mutated gene in the cohort (26%), with the mutation landscape and subclonal architecture assessed for all 25 genes, identifying previously observed and novel associations. Clinical statistical survival analysis of the CLL4 TruSeq mutation data was undertaken for overall and progression-free survival, using traditional techniques and supervised machine learning tools. SF3B1 was identified to associate with OS independently of multiple CLL biomarkers in a multivariate model, and as an important feature by machine learning approaches. In addition, subclonal TP53 mutations predicted poor OS and PFS in cases treated with chlorambucil, and co-mutated/deleted del(11q) and BIRC3 were found to independently predict for a poor PFS. Since SF3B1 was found to be the most recurrently mutated gene in CLL4, and it associated with poor OS, it was selected for in vitro targeting using splicing inhibitors (Spliceostatin A and Meayamycin B) in CLL cells. Splicing inhibitors elicited substantial apoptosis, with Spliceostatin A inducing downregulation of Mcl-1 at the protein and RNA level, as well as acting synergistically with venetoclax in the context of micro-environmental support. Therefore, direct inhibition of Mcl-1 in CLL cells was undertaken using the Mcl-1 specific inhibitor UMI-77, eliciting apoptosis at micro molar concentrations. However, UMI-77 did induce resensitisation to the level of SSA in the context of CLL microenvironment support, suggesting that inhibition of Mcl-1 alone may not be sufficient to overcome BCL-2 inhibitor resistance in CLL. This work has demonstrated that the application of targeted genomic screening can offer added value to CLL patient management where the monitoring of SF3B1 mutations can identify additional adverse disease events. In relation to targeting drugs to the spliceosome pathway in CLL, where SF3B1 is a major component, the current work demonstrated effective re-sensitisation of CLL cells to combination inhibitor exposure. Together, this research has provided a greater understanding of the clinical utility of gene mutation screening and challenges surrounding development of the next generation of therapies to circumvent molecular pathways that CLL cells use to proliferate and drive disease progression.

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S J Blakemore PhD Thesis - Version of Record
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Published date: November 2017

Identifiers

Local EPrints ID: 434952
URI: http://eprints.soton.ac.uk/id/eprint/434952
PURE UUID: abcfa787-9182-4339-a17d-36e17281a0e6
ORCID for Jon Strefford: ORCID iD orcid.org/0000-0002-0972-2881
ORCID for Mark Cragg: ORCID iD orcid.org/0000-0003-2077-089X
ORCID for Andrew Steele: ORCID iD orcid.org/0000-0003-0667-1596

Catalogue record

Date deposited: 17 Oct 2019 16:30
Last modified: 18 Oct 2019 00:37

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Contributors

Author: Stuart James Blakemore
Thesis advisor: Jon Strefford ORCID iD
Thesis advisor: Mark Cragg ORCID iD
Thesis advisor: Andrew Steele ORCID iD

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