Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Whole exome sequencing analyses of human, IDH2-mutated, acute myeloid leukemia samples from patients before or during treatment with Enasidenib.

ABSTRACT: Mutations in isocitrate dehydrogenase 2 (IDH2) occur in many cancers including Acute Myeloid Leukemia (AML). In preclinical models mutant IDH2 causes partial hemopoietic differentiation arrest. Recently, we showed that single agent Enasidenib, a first-in-class, selective mutant IDH2 inhibitor, produces a 40% response in relapsed/refractory AML patients by promoting differentiation. Yet, the rate, extend and duration of the clinical benefits of Enasidenib vary from one patient to another. To investigate how the genetic mutational landscape, at baseline or at relapse, contributes in modulating response to Enasidenib, WES analyses on FACS-sorted blasts from baseline, best response and/or relapse samples from 16 Enasidenib-treated patients were performed. WES analyses were also performed on the CD3+ cells from the same patients, which may be used as germinal control samples.

INSTRUMENT(S): Illumina HiSeq 2000

ORGANISM(S): Homo sapiens

SUBMITTER: Muriel DAVID

PROVIDER: E-MTAB-6299 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Clonal heterogeneity of acute myeloid leukemia treated with the IDH2 inhibitor enasidenib.

Quek Lynn L David Muriel D MD Kennedy Alison A Metzner Marlen M Amatangelo Michael M Shih Alan A Stoilova Bilyana B Quivoron Cyril C Heiblig Maël M Willekens Christophe C Saada Véronique V Alsafadi Samar S Vijayabaskar M S MS Peniket Andy A Bernard Oliver A OA Agresta Sam S Yen Katharine K MacBeth Kyle K Stein Eytan E Vassiliou George S GS Levine Ross R De Botton Stephane S Thakurta Anjan A Penard-Lacronique Virginie V Vyas Paresh P

Nature medicine 20180716 8

Mutations in the gene encoding isocitrate dehydrogenase 2 (IDH2) occur in several types of cancer, including acute myeloid leukemia (AML). In model systems, mutant IDH2 causes hematopoietic differentiation arrest. Enasidenib, a selective small-molecule inhibitor of mutant IDH2, produces a clinical response in 40% of treated patients with relapsed/refractory AML by promoting leukemic cell differentiation. Here, we studied the clonal basis of response and acquired resistance to enasidenib treatmen ...[more]

PMID: 30013198

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Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.

Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array

Dataset Information

Whole exome sequencing analyses of human, IDH2-mutated, acute myeloid leukemia samples from patients before or during treatment with Enasidenib.

Publications

Clonal heterogeneity of acute myeloid leukemia treated with the IDH2 inhibitor enasidenib.

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