Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia
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Open Access
- 5 June 2011
- journal article
- research article
- Published by Springer Nature in Nature
- Vol. 475 (7354) , 101-105
- https://doi.org/10.1038/nature10113
Abstract
Analysis of the genomes of four patients with chronic lymphocytic leukaemia, and validation in more than 300 patients, has identified four genes — NOTCH1, MYD88, XPO1 and KLHL6 — that are recurrently mutated in the condition. Mutations in NOTCH1, MYD88 and XPO1 are thought to contribute to the clinical evolution of the disease. Evidence that NOTCH1 and MYD88 mutations are activating events highlights them as potential therapeutic targets. Chronic lymphocytic leukaemia (CLL), the most frequent leukaemia in adults in Western countries, is a heterogeneous disease with variable clinical presentation and evolution1,2. Two major molecular subtypes can be distinguished, characterized respectively by a high or low number of somatic hypermutations in the variable region of immunoglobulin genes3,4. The molecular changes leading to the pathogenesis of the disease are still poorly understood. Here we performed whole-genome sequencing of four cases of CLL and identified 46 somatic mutations that potentially affect gene function. Further analysis of these mutations in 363 patients with CLL identified four genes that are recurrently mutated: notch 1 (NOTCH1), exportin 1 (XPO1), myeloid differentiation primary response gene 88 (MYD88) and kelch-like 6 (KLHL6). Mutations in MYD88 and KLHL6 are predominant in cases of CLL with mutated immunoglobulin genes, whereas NOTCH1 and XPO1 mutations are mainly detected in patients with unmutated immunoglobulins. The patterns of somatic mutation, supported by functional and clinical analyses, strongly indicate that the recurrent NOTCH1, MYD88 and XPO1 mutations are oncogenic changes that contribute to the clinical evolution of the disease. To our knowledge, this is the first comprehensive analysis of CLL combining whole-genome sequencing with clinical characteristics and clinical outcomes. It highlights the usefulness of this approach for the identification of clinically relevant mutations in cancer.Keywords
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