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Title: Exploring novel stratified therapeutic targets in B-cell chronic lymphocytic leukaemia
Author: Shelmani, Ghalia M. A.
ISNI:       0000 0004 6494 5628
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 2017
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Chronic lymphocytic leukaemia (CLL) is a heterogeneous B-cell malignancy with multiple genetic abnormalities, which have been used to stratify patient’s treatments and prognosis. For instance, genetic alterations have been identified in CLL patients, such as SF3B1, Notch1, TP53, and Myd88, and they have been related to prediction of progression and survival. Moreover, mitogen activated protein kinase (MAPK) signalling is crucial in the pathogenesis of a number of cancers, and it has also showed increased expression in a large subset of CLL patients. In this project, we investigated the sensitivity of five leukaemic cell lines to 22 targeted inhibitors. We found that cells with V600EBRAF mutations showed greater sensitivity to MAPK inhibition, while cells with K601NBRAF mutations were more resistant. Wild type BRAF CLL cells showed varied sensitivity to 16 different inhibitors but not to MAPK inhibitors. Combination of a MAPK inhibitor (Sorafenib) and CUDC-907 (CDK/HDAC inhibitor) showed strong synergism in CLL cells at nanomolar concentration, suggesting a potential therapeutic application of blocking both pathways simultaneously. BRAF exon 15 mutations had low frequencies in our cohort (1.052%), but we also found Notch1 mutations (14.81%), Myd88 (1.35%) and SF3B1 (16.21%, 20.8% of which were first-time reports of non-coding regions). Notch1 mutants were more resistant to pladienolide B and more sensitive to MK-0752. On the other hand Myd88 mutants were more sensitive to IRAK1/4 inhibitors. In conclusion, our results showed that therapies for CLL can be stratified based on in vitro information of drug sensitivity in relation to mutations present in the cells and suggest that inhibiting the MAPK pathway could be an effective approach in combination therapies. These preclinical data could be applied in CLL management in the near future.
Supervisor: Macip, Salvador ; Dyer, Martin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available