5 research outputs found

    Characterization of gene mutations and copy number changes in acute myeloid leukemia using a rapid target enrichment protocol

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    Prognostic stratification is critical for making therapeutic decisions and maximizing survival of patients with acute myeloid leukemia. Advances in the genomics of acute myeloid leukemia have identified several recurrent gene mutations whose prognostic impact is being deciphered. We used HaloPlex target enrichment and Illumina-based next generation sequencing to study 24 recurrently mutated genes in 42 samples of acute myeloid leukemia with a normal karyotype. Read depth varied between and within genes for the same sample, but was predictable and highly consistent across samples. Consequently, we were able to detect copy number changes, such as an interstitial deletion of BCOR, three MLL partial tandem duplications, and a novel KRAS amplification. With regards to coding mutations, we identified likely oncogenic variants in 41 of 42 samples. NPM1 mutations were the most frequent, followed by FLT3, DNMT3A and TET2. NPM1 and FLT3 indels were reported with good efficiency. We also showed that DNMT3A mutations can persist post-chemotherapy and in 2 cases studied at diagnosis and relapse, we were able to delineate the dynamics of tumor evolution and give insights into order of acquisition of variants. HaloPlex is a quick and reliable target enrichment method that can aid diagnosis and prognostic stratification of acute myeloid leukemia patients.This project was funded by the Wellcome Trust. NB is a fellow of the European Hematology Association and was supported by the Academy of Medical Sciences. EP is a European Hematology Association Advanced Research Fellow. GV is a Wellcome Trust Senior Fellow in Clinical Science. IV is funded by Spanish Ministerio de EconomĂ­a y Competitividad subprograma RamĂłn y Cajal

    Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups

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    International audienceIn multiple myeloma, next generation sequencing (NGS) has expanded our knowledge of genomic lesions, and highlighted a dynamic and heterogeneous composition of the tumor. Here, we used NGS to characterize the genomic landscape of 418 multiple myeloma cases at diagnosis and correlate this with prognosis and classification. Translocations and copy number changes (CNAs) had a preponderant contribution over gene mutations in defining the genotype and prognosis of each case. Known and novel independent prognostic markers were identified in our cohort of proteasome inhibitor and IMiD-treated patients with long follow-up, including events with context-specific prognostic value, such as deletions of the PRDM1 gene. Taking advantage of the comprehensive genomic annotation of each case, we used innovative statistical approaches to identify potential novel myeloma subgroups. We observed clusters of patients stratified based on the overall number of mutations and number/type of CNAs, with distinct effects on survival, suggesting that extended genotype of multiple myeloma at diagnosis may lead to improved disease classification and prognostication
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