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Precision medicine treatment in acute myeloid leukemia using prospective genomic profiling: feasibility and preliminary efficacy of the Beat AML Master Trial.

ABSTRACT: Acute myeloid leukemia (AML) is the most common diagnosed leukemia. In older adults, AML confers an adverse outcome^1,2. AML originates from a dominant mutation, then acquires collaborative transformative mutations leading to myeloid transformation and clinical/biological heterogeneity. Currently, AML treatment is initiated rapidly, precluding the ability to consider the mutational profile of a patient's leukemia for treatment decisions. Untreated patients with AML ≥ 60 years were prospectively enrolled on the ongoing Beat AML trial (ClinicalTrials.gov NCT03013998 ), which aims to provide cytogenetic and mutational data within 7 days (d) from sample receipt and before treatment selection, followed by treatment assignment to a sub-study based on the dominant clone. A total of 487 patients with suspected AML were enrolled; 395 were eligible. Median age was 72 years (range 60-92 years; 38% ≥75 years); 374 patients (94.7%) had genetic and cytogenetic analysis completed within 7 d and were centrally assigned to a Beat AML sub-study; 224 (56.7%) were enrolled on a Beat AML sub-study. The remaining 171 patients elected standard of care (SOC) (103), investigational therapy (28) or palliative care (40); 9 died before treatment assignment. Demographic, laboratory and molecular characteristics were not significantly different between patients on the Beat AML sub-studies and those receiving SOC (induction with cytarabine + daunorubicin (7 + 3 or equivalent) or hypomethylation agent). Thirty-day mortality was less frequent and overall survival was significantly longer for patients enrolled on the Beat AML sub-studies versus those who elected SOC. A precision medicine therapy strategy in AML is feasible within 7 d, allowing patients and physicians to rapidly incorporate genomic data into treatment decisions without increasing early death or adversely impacting overall survival.

SUBMITTER: Burd A

PROVIDER: S-EPMC8530434 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Precision medicine treatment in acute myeloid leukemia using prospective genomic profiling: feasibility and preliminary efficacy of the Beat AML Master Trial.

Burd Amy A Levine Ross L RL Ruppert Amy S AS Mims Alice S AS Borate Uma U Stein Eytan M EM Patel Prapti P Baer Maria R MR Stock Wendy W Deininger Michael M Blum William W Schiller Gary G Olin Rebecca R Litzow Mark M Foran James J Lin Tara L TL Ball Brian B Boyiadzis Michael M Traer Elie E Odenike Olatoyosi O Arellano Martha M Walker Alison A Duong Vu H VH Kovacsovics Tibor T Collins Robert R Shoben Abigail B AB Heerema Nyla A NA Foster Matthew C MC Vergilio Jo-Anne JA Brennan Tim T Vietz Christine C Severson Eric E Miller Molly M Rosenberg Leonard L Marcus Sonja S Yocum Ashley A Chen Timothy T Stefanos Mona M Druker Brian B Byrd John C JC

Nature medicine 20201026 12

Acute myeloid leukemia (AML) is the most common diagnosed leukemia. In older adults, AML confers an adverse outcome<sup>1,2</sup>. AML originates from a dominant mutation, then acquires collaborative transformative mutations leading to myeloid transformation and clinical/biological heterogeneity. Currently, AML treatment is initiated rapidly, precluding the ability to consider the mutational profile of a patient's leukemia for treatment decisions. Untreated patients with AML ≥ 60 years were pros ...[more]

PMID: 33106665

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Project description:Advances in genomic technologies and an increased understanding of the molecular pathogenesis of cancer have resulted in development of new effective, mutation-targeted therapies. In turn, these informed the development of Master Trial designs to test these therapies. The Beat Acute Myeloid Leukemia (BAML) Master Trial (Sponsor: The Leukemia & Lymphoma Society) tests several targeted therapies in patients aged ≥ 60 years with AML based on genomic profiling obtained within 7 days of study enrollment. We hypothesized that integrating operational strategies with new electronic technologies (e-technologies) might streamline the conduct and management of this Master Trial. BAML's 5 core operational strategies revolve around the guiding principle of "patients first." The e-technology platforms employed in BAML include: Clinical Oversight Platform: a central collaborative tool; e-Protocol/e-Source Upload/Electronic Data Capture Platform: digitizes the protocol, allows remote data monitoring, and collects/exports data in Study Data Tabulation Model format; and Data Review Platform: ingests data from different sources for clinical response and safety data reviews. The operational approaches, e-technologies and sponsor/contract research organization's (CRO) expertise together allow: the complexity and size of the BAML Master Trial to be better managed; near real-time study data oversight; better collaboration, communication and training; improved data collection, enhanced transmission and accessibility; data integration, review and generation of reports; while maintaining data privacy, and compliance. Initial e-technology challenges were overcome through training, learning, discipline and adjustment. In conclusion, to successfully manage Master Trials, significant time should be spent re-evaluating, improving and developing new operational approaches.Clinical Trial Registration: Clinical Trials.gov Identifier: NCT03013998. https://clinicaltrials.gov/ct2/show/NCT03013998 .

Project description:Acute myeloid leukemia (AML), as the most common malignancy of the hematopoietic system, poses challenges in treatment efficacy, relapse, and drug resistance. In this study, we have utilized 151 RNA sequencing datasets, 194 DNA methylation datasets, and 200 somatic mutation datasets from the AML cohort in the TCGA database to develop a multi-omics stratification model. This model enables comparison of prognosis, clinical features, gene mutations, immune microenvironment and drug sensitivity across subgroups. External validation datasets have been sourced from the GEO database, which includes 562 mRNA datasets and 136 miRNA datasets from 984 adult AML patients. Through multi-omics-based stratification model, we classified 126 AML patients into 4 clusters (CS). CS4 had the best prognosis, with the youngest age, highest M3 subtype proportion, fewest copy number alterations, and common mutations in WT1, FLT3, and KIT genes. It showed sensitivity to HDAC inhibitors and BCL-2 inhibitors. Both the M3 subtype and CS4 were identified as independent protective factors for survival. Conversely, CS3 had the worst prognosis due to older age, high copy number alterations, and frequent mutations in RUNX1, DNMT3A, and TP53 genes. Additionally, it showed higher proportions of cytotoxic cells and Tregs, suggesting potential sensitivity to mTOR inhibitors. CS1 had a better prognosis than CS2, with more copy number alterations, while CS2 had higher monocyte proportions. CS1 showed good sensitivity to cytarabine, while CS2 was sensitive to RXR agonists. Both CS1 and CS2, which predominantly featured mutations in FLT3, NPM1, and DNMT3A genes, benefited from FLT3 inhibitors. Using the Kappa test, our stratification model underwent robust validation in the miRNA and mRNA external validation datasets. With advancements in sequencing technology and machine learning algorithms, AML is poised to transition towards multi-omics precision medicine in the future. We aspire for our study to offer new perspectives on multi-drug combination clinical trials and multi-targeted precision medicine for AML.

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 medicine treatment in acute myeloid leukemia using prospective genomic profiling: feasibility and preliminary efficacy of the Beat AML Master Trial.

Publications

Precision medicine treatment in acute myeloid leukemia using prospective genomic profiling: feasibility and preliminary efficacy of the Beat AML Master Trial.

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