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Precision therapy for acute myeloid leukemia.

ABSTRACT: Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous disease. Despite advances in understanding the pathogenesis of AML, the standard therapy remained nearly unchanged over the past three decades. With the poor survival for older patients and high relapse rate, multiple studies are ongoing to address this important issue. Novel therapies for AML, including the refinements of conventional cytotoxic chemotherapies and genetic and epigenetic targeted drugs, as well as immunotherapies, have been developed in recent years. Here, we present a mechanism-based review of some promising new drugs with clinical efficacy, focus on targeted drugs that are most potential to pave the road to success, and put forward the major challenges in promoting the precision therapy for AML.

SUBMITTER: Yang X

PROVIDER: S-EPMC5755341 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Precision therapy for acute myeloid leukemia.

Yang Xue X Wang Jianxiang J

Journal of hematology & oncology 20180105 1

Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous disease. Despite advances in understanding the pathogenesis of AML, the standard therapy remained nearly unchanged over the past three decades. With the poor survival for older patients and high relapse rate, multiple studies are ongoing to address this important issue. Novel therapies for AML, including the refinements of conventional cytotoxic chemotherapies and genetic and epigenetic targeted drugs, as well as immunoth ...[more]

PMID: 29301553

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Project description:BackgroundOlder patients (≥ 60 years) with acute myeloid leukemia (AML) often have multiple, sequentially acquired, somatic mutations that drive leukemogenesis and are associated with poor outcome. Beat AML is a Leukemia and Lymphoma Society-sponsored, multicenter umbrella study that algorithmically segregates AML patients based upon cytogenetic and dominant molecular abnormalities (variant allele frequencies (VAF) ≥ 0.2) into different cohorts to select for targeted therapies. During the conception of the Beat AML design, a historical dataset was needed to help in the design of the genomic algorithm for patient assignment and serve as the basis for the statistical design of individual genomic treatment substudies for the Beat AML study.MethodsWe classified 563 newly diagnosed older AML patients treated with standard intensive chemotherapy on trials conducted by Cancer and Leukemia Group B based on the same genomic algorithm and assessed clinical outcomes.ResultsOur classification identified core-binding factor and NPM1-mutated/FLT3-ITD-negative groups as having the best outcomes, with 30-day early death (ED) rates of 0 and 20%, respectively, and median overall survival (OS) of > 1 year and 3-year OS rates of ≥ 20%. All other genomic groups had ED rates of 17-42%, median OS ≤ 1 year and 3-year OS rates of ≤ 15%.ConclusionsBy classifying patients through this genomic algorithm, outcomes were poor and not unexpected from a non-algorithmic, non-dominant VAF approach. The exception is 30-day ED rate typically is not available for intensive induction for individual genomic groups and therefore difficult to compare outcomes with targeted therapeutics. This Alliance data supported the use of this algorithm for patient assignment at the initiation of the Beat AML study. This outcome data was also used for statistical design for Beat AML substudies for individual genomic groups to determine goals for improvement from intensive induction and hopefully lead to more rapid approval of new therapies. Trial registration ClinicalTrials.gov Identifiers: NCT00048958 (CALGB 8461), NCT00900224 (CALGB 20202), NCT00003190 (CALGB 9720), NCT00085124 (CALGB 10201), NCT00742625 (CALGB 10502), NCT01420926 (CALGB 11002), NCT00039377 (CALGB 10801), and NCT01253070 (CALGB 11001).

Dataset Information

Precision therapy for acute myeloid leukemia.

Publications

Precision therapy for acute myeloid leukemia.

Similar Datasets

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