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

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

Abstract

Acute myeloid leukemia (AML) is the most common diagnosed leukemia. In older adults, AML confers an adverse outcome1,2. 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.

Figures

Fig. 1 ∣. Overview of the Beat…
Fig. 1 ∣. Overview of the Beat AML trial.
a, AML prioritization by genomic or cytogenetic abnormality into groups. b, Patient distribution following enrollment on the Beat AML trial. c, Genomic assignment of eligible patients with AML by prioritization group. The asterisk denotes the hypermethylation group, which is defined by the TET2/WT1 mutations.
Fig. 2 ∣. Comutation oncoprint of eligible…
Fig. 2 ∣. Comutation oncoprint of eligible Beat AML trial patients.
Genes with genomic alterations (short variants and insertions/deletions) are listed in descending order of frequency and each column represents an individual patient. Red indicates that the alteration was present at an allele frequency of ≥30% and blue

Fig. 3 ∣. Overall survival estimates.

a…

Fig. 3 ∣. Overall survival estimates.

a , All eligible patients on the Beat AML…
Fig. 3 ∣. Overall survival estimates.
a, All eligible patients on the Beat AML trial. b, By treatment received including assigned Beat AML therapy, SOC (standard therapy), palliative care and alternative investigational therapy. Overall survival estimates were calculated with the Kaplan–Meier method and presented with 95% CIs constructed using the complementary log-log transformation. If a value could not be calculated, not evaluated is indicated. The 2 patients who did not consent to a Beat AML sub-study with unknown treatment were combined with the 38 patients who elected palliative care.
Fig. 3 ∣. Overall survival estimates.
Fig. 3 ∣. Overall survival estimates.
a, All eligible patients on the Beat AML trial. b, By treatment received including assigned Beat AML therapy, SOC (standard therapy), palliative care and alternative investigational therapy. Overall survival estimates were calculated with the Kaplan–Meier method and presented with 95% CIs constructed using the complementary log-log transformation. If a value could not be calculated, not evaluated is indicated. The 2 patients who did not consent to a Beat AML sub-study with unknown treatment were combined with the 38 patients who elected palliative care.

References

    1. Karjalainen E & Repasky GA Molecular changes during acute myeloid leukemia (AML) evolution and identification of novel treatment strategies through molecular stratification. Prog. Mol. Biol. Transl. Sci 144, 383–436 (2016).
    1. Khwaja A et al. Acute myeloid leukaemia. Nat. Rev. Dis. Primers 2, 16010 (2016).
    1. Chen J et al. Myelodysplastic syndrome progression to acute myeloid leukemia at the stem cell level. Nat. Med 25, 103–110 (2019).
    1. Desai P et al. Somatic mutations precede acute myeloid leukemia years before diagnosis. Nat. Med 24, 1015–1023 (2018).
    1. Abelson S et al. Prediction of acute myeloid leukaemia risk in healthy individuals. Nature 559, 400–404 (2018).
    1. Takahashi K et al. Preleukaemic clonal haemopoiesis and risk of therapy-related myeloid neoplasms: a case-control study. Lancet Oncol. 18, 100–111 (2017).
    1. Vasu S et al. Ten-year outcome of patients with acute myeloid leukemia not treated with allogeneic transplantation in first complete remission. Blood Adv. 2, 1645–1650 (2018).
    1. Stone A, Zukerman T, Flaishon L, Yakar RB & Rowe JM Efficacy outcomes in the treatment of older or medically unfit patients with acute myeloid leukaemia: a systematic review and meta-analysis. Leuk. Res 82, 36–42 (2019).
    1. Lübbert M et al. Low-dose decitabine versus best supportive care in elderly patients with intermediate- or high-risk myelodysplastic syndrome (MDS) ineligible for intensive chemotherapy: final results of the randomized phase III study of the European Organisation for Research and Treatment of Cancer Leukemia Group and the German MDS Study Group. J. Clin. Oncol 29, 1987–1996 (2011).
    1. Fenaux P et al. Azacitidine prolongs overall survival compared with conventional care regimens in elderly patients with low bone marrow blast count acute myeloid leukemia. J. Clin. Oncol 28, 562–569 (2010).
    1. Kantarjian HM et al. Multicenter, randomized, open-label, phase III trial of decitabine versus patient choice, with physician advice, of either supportive care or low-dose cytarabine for the treatment of older patients with newly diagnosed acute myeloid leukemia. J. Clin. Oncol 30, 2670–2677 (2012).
    1. Stone RM et al. Midostaurin plus chemotherapy for acute myeloid leukemia with a FLT3 mutation. N. Engl. J. Med 377, 454–464 (2017).
    1. Uy GL et al. A phase 2 study incorporating sorafenib into the chemotherapy for older adults with FLT3-mutated acute myeloid leukemia: CALGB 11001. Blood Adv. 1, 331–340 (2017).
    1. Bertoli S et al. Time from diagnosis to intensive chemotherapy initiation does not adversely impact the outcome of patients with acute myeloid leukemia. Blood 121, 2618–2626 (2013).
    1. Eisfeld A-K et al. Mutation patterns identify adult patients with de novo acute myeloid leukemia aged 60 years or older who respond favorably to standard chemotherapy: an analysis of Alliance studies. Leukemia 32, 1338–1348 (2018).
    1. Becker H et al. Favorable prognostic impact of NPM1 mutations in older patients with cytogenetically normal de novo acute myeloid leukemia and associated gene- and microRNA-expression signatures: a Cancer and Leukemia Group B study. J. Clin. Oncol 28, 596–604 (2010).
    1. Koszarska M et al. Type and location of isocitrate dehydrogenase mutations influence clinical characteristics and disease outcome of acute myeloid leukemia. Leuk. Lymphoma 54, 1028–1035 (2013).
    1. Yang H et al. Gain of function of ASXL1 truncating protein in the pathogenesis of myeloid malignancies. Blood 131, 328–341 (2018).
    1. Mill CP et al. RUNX1-targeted therapy for AML expressing somatic or germline mutation in RUNX1. Blood 134, 59–73 (2019).
    1. Fong JY et al. Therapeutic targeting of RNA splicing catalysis through inhibition of protein arginine methylation. Cancer Cell 36, 194–209.e9 (2019).
    1. Nguyen HD et al. Spliceosome mutations induce R loop-associated sensitivity to ATR inhibition in myelodysplastic syndromes. Cancer Res. 78, 5363–5374 (2018).
    1. Mardis ER et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. N. Engl. J. Med 361, 1058–1066 (2009).
    1. Patel JP et al. Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. N. Engl. J. Med 366, 1079–1089 (2012).
    1. Papaemmanuil E et al. Genomic classification and prognosis in acute myeloid leukemia. N. Engl. J. Med 374, 2209–2221 (2016).
    1. Eisfeld A-K et al. The mutational oncoprint of recurrent cytogenetic abnormalities in adult patients with de novo acute myeloid leukemia. Leukemia 31, 2211–2218 (2017).
    1. DiNardo CD et al. Durable remissions with ivosidenib in IDH1-mutated relapsed or refractory AML. N. Engl. J. Med 378, 2386–2398 (2018).
    1. DiNardo C & Lachowiez C Acute myeloid leukemia: from mutation profiling to treatment decisions. Curr. Hematol. Malig. Rep 14, 386–394 (2019).
    1. Intlekofer AM et al. Integrated DNA/RNA targeted genomic profiling of diffuse large B-cell lymphoma using a clinical assay. Blood Cancer J. 8, 60 (2018).
    1. Frampton GM et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat. Biotechnol 31, 1023–1031 (2013).
    1. van Buuren S Multiple imputation of discrete and continuous data by fully conditional specification. Stat. Methods Med. Res 16, 219–242 (2007).

Source: PubMed

3
订阅