ID

45786

Descrição

The implementation of targeted therapies for acute myeloid leukemia has been challenged by complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here, we report initial findings from the Beat AML program on a cohort of 672 tumor specimens collected from 562 patients. We assessed these specimens using whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses. Our data reveal novel mutational events not previously detected in AML. We show association of drug response with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA-sequencing also revealed gene expression signatures, which predict a role of specific gene networks in drug response. Collectively, this report offers a dataset, accessible by the Beat AML data viewer, that can be leveraged to address clinical, genomic, transcriptomic, and functional inquiries into the biology of AML. NCT 01728402 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001657

Link

dbGaP study = phs001657

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Versões (8)

1. 27/04/2022 27/04/2022 - Martin Dugas
2. 27/04/2022 27/04/2022 - Martin Dugas
3. 27/04/2022 27/04/2022 - Martin Dugas
4. 27/04/2022 27/04/2022 - Martin Dugas
5. 12/05/2022 12/05/2022 - Martin Dugas
6. 12/05/2022 12/05/2022 - Martin Dugas
7. 12/10/2022 12/10/2022 - Adrian Schulz
8. 22/06/2023 22/06/2023 - Dr. Christian Niklas

Titular dos direitos

Jeffrey W. Tyner, PhD. Oregon Health and Science University, Knight Cancer Institute, Portland, OR, USA

Transferido a

22 de junho de 2023

DOI

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