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Clinical Trial
. 2017 Aug 10;130(6):732-741.
doi: 10.1182/blood-2017-04-779447. Epub 2017 Jun 6.

Enasidenib induces acute myeloid leukemia cell differentiation to promote clinical response

Michael D Amatangelo  1 , Lynn Quek  2 , Alan Shih  3 , Eytan M Stein  3 , Mikhail Roshal  3 , Muriel D David  4 , Benoit Marteyn  5 , Noushin Rahnamay Farnoud  6 , Stephane de Botton  7 , Olivier A Bernard  4 , Bin Wu  8 , Katharine E Yen  8 , Martin S Tallman  3 , Elli Papaemmanuil  6   9 , Virginie Penard-Lacronique  4 , Anjan Thakurta  1 , Paresh Vyas  2 , Ross L Levine  3   6   10
Affiliations
Clinical Trial

Enasidenib induces acute myeloid leukemia cell differentiation to promote clinical response

Michael D Amatangelo et al. Blood. .

Abstract

Recurrent mutations at R140 and R172 in isocitrate dehydrogenase 2 (IDH2) occur in many cancers, including ∼12% of acute myeloid leukemia (AML). In preclinical models these mutations cause accumulation of the oncogenic metabolite R-2-hydroxyglutarate (2-HG) and induce hematopoietic differentiation block. Single-agent enasidenib (AG-221/CC-90007), a selective mutant IDH2 (mIDH2) inhibitor, produced an overall response rate of 40.3% in relapsed/refractory AML (rrAML) patients with mIDH2 in a phase 1 trial. However, its mechanism of action and biomarkers associated with response remain unclear. Here, we measured 2-HG, mIDH2 allele burden, and co-occurring somatic mutations in sequential patient samples from the clinical trial and correlated these with clinical response. Furthermore, we used flow cytometry to assess inhibition of mIDH2 on hematopoietic differentiation. We observed potent 2-HG suppression in both R140 and R172 mIDH2 AML subtypes, with different kinetics, which preceded clinical response. Suppression of 2-HG alone did not predict response, because most nonresponding patients also exhibited 2-HG suppression. Complete remission (CR) with persistence of mIDH2 and normalization of hematopoietic stem and progenitor compartments with emergence of functional mIDH2 neutrophils were observed. In a subset of CR patients, mIDH2 allele burden was reduced and remained undetectable with response. Co-occurring mutations in NRAS and other MAPK pathway effectors were enriched in nonresponding patients, consistent with RAS signaling contributing to primary therapeutic resistance. Together, these data support differentiation as the main mechanism of enasidenib efficacy in relapsed/refractory AML patients and provide insight into resistance mechanisms to inform future mechanism-based combination treatment studies.

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Conflict of interest statement

Conflict-of-interest disclosure: B.W. and K.E.Y. are employed by and own equity in Agios Pharmaceuticals, Inc. M.D.A. and A.T. are employed by and own equity in Celgene Corporation. L.Q. was supported by a fellowship from Celgene. R.L.L. is a scholar of the Leukemia and Lymphoma Society. The remaining authors declare no competing financial interests.

Figures

Figure 1.
Figure 1.
mIDH2 inhibition is associated with potent reduction of 2-HG in mIDH2 AML. (A) Dot plot with median and interquartile range showing maximum 2-HG suppression (percentage change from baseline) in blood observed in patients segregated by R140 and R172 mIDH2. Numbers indicate number of patients from each genotype graphed. (B) Dot plot with median and interquartile range showing maximum 2-HG suppression (percentage change from baseline) observed in patients segregated by total daily dose received (<100 mg in green, 100 mg in blue, >100 mg in purple) and stratified by R140 and R172 mIDH2. (C) Dot plot with median and interquartile range showing blood plasma 2-HG (ng/mL) at screening in patients segregated by best response achieved and stratified by R172 (red) and R140 (blue) mIDH2. Response (R) is defined as CR, CRi, CRp, MLFS, or PR. NR is defined as stable disease or progressive disease. (D) Whisker plot indicating mean and standard deviation of cycle to CR, BR, or maximum 2-HG suppression stratified by R172 (red) and R140 (blue) mIDH2. Max 2-HG, maximum 2-HG suppression.
Figure 2.
Figure 2.
Clinical responses to mIDH2 inhibition do not correlate with mIDH2 allele burden. (A) Dot plot of mIDH2 VAF (R140 mIDH2 in blue and R172 mIDH2 in red) in patient samples measured at screening in either peripheral blood or bone marrow by FoundationOne Heme panel. Measurements are separated by the best response achieved by patients, as defined in Figure 1. Numbers indicate the number of patient samples in the graph. (B) Waterfall plot indicating absolute change in mIDH2 VAF from screening to achievement of best response measured by Sysmex OncoBeam digital PCR. Responders are plotted in green and nonresponders in red. Patients achieving CR are outlined in black. The dotted line indicates the largest VAF decrease observed in a nonresponder. (C) Line graph of mIDH2 VAF over time (days of treatment) in 9 patients achieving molecular remission (undetectable mIDH2) for at least 1 time point during treatment. (D) Scatter plot of bone marrow mIDH2 VAF versus blast percentage measured by flow cytometry in 9 responsive patients in samples taken pretreatment (red) and at response (CR, CRi, CRp, or MLFS; green). Blue line indicates expected ratio (2:1) between blast percentage:mIDH2 VAF in clonal mIDH2 disease. Three data points (in green) are superimposed with values close to or at zero. BM, bone marrow; PB, peripheral blood; pre-Rx, pretreatment.
Figure 3.
Figure 3.
Clinical response to mIDH2 inhibition is associated with induction of myeloid differentiation. (A) Representative immunophenotypic analyses by flow cytometry on sequential bone marrow samples. Cell-surface markers studied are shown. Data from a responding patient (pretreatment to CR to relapse) (left). Data from a nonresponding patient (pretreatment to progressive disease) who remained in stable disease during treatment (right). Numbers in FACS plots refer to the size of the population as a percentage of lineage-negative bone marrow mononuclear cells. For normal bone marrow (n = 12), the standard deviation is ±2.7% for immature progenitor, ±9.6% for immature precursors, and ±9.7% for mature myeloid cells. (B) Graph showing ratio of immature to mature cell populations by flow cytometry from bone marrow over time (top): the average ratios of myeloid progenitor or myeloid precursors to mature myeloid cells in bone marrow from normal donors (n = 12) and 5 patients who had either a CR or a PR with enasidenib are shown. In patient 201-010, the changing size of myeloid precursor (red) cell populations in relation to mature myeloid cells is shown. In the remaining 3 patients, the changing size of myeloid progenitor (blue) populations to mature cells is shown. Colored bars represent the 95% confidence intervals in normal controls. The mIDH2 VAF in each patient at different time points in all bone marrow mononuclear cells (VAF total) and in FACS-sorted mature myeloid cells (CD34−CD117−) are shown (bottom). (C) mIDH2 VAF in bone marrow mononuclear cells prior to treatment (blue) and in sorted peripheral blood neutrophils at time of best response (red) in 7 patients achieving CR (top). VAF of indicated mutation in bone marrow mononuclear cells prior to treatment and in sorted peripheral blood neutrophils at time of best response in 2 patients achieving CR (middle and bottom). (D) Histogram of the percentages of functional neutrophils observed in ex vivo enasidenib-treated patient samples (left) and representative images (right) assessed by phagocytic assay quantifying neutrophils (blue) that contained latex beads (green). The percentage of neutrophils containing beads was measured by scoring 5 different fields of view per sample. BRCA2, breast cancer type 2; Gran, granulocyte; PD, progressive disease; Post, time of best response; Pre, prior to treatment; TNC, total nucleated cell count.
Figure 4.
Figure 4.
Association of co-occurring mutations with clinical response and classification of patients from cytogenetic and molecular abnormalities. (A) Tile plot showing the number of co-occurring somatic mutations by gene identified in FoundationOne Heme panel from efficacy-evaluable patients separated by R140 and R172 mIDH2. Only mutated genes occurring in 2 or more patients are shown. Mutations associated with higher risk are in red and mutations associated with lower risk are in green, as defined by Grimwade et al. (B) Histogram of the number of mutations identified in each gene from all 100 patient samples analyzed. The number of mutations identified in responding patients are in blue, the number of mutations identified in nonresponding patients are in red, and the number of mutations in patients who were not efficacy evaluable are in gray. (C) Pie charts of proportions of patients in various risk categories according to European LeukemiaNet (ELN) 2010 AML risk stratification, ELN 2017 AML risk stratification, and Grimwade et al, on the basis of cytogenetic testing completed before the start of cycle 2 and mutations identified at screening. (D) Pie chart of proportions of patients in various genomic classifications according to Papaemmanuil et al, on the basis of cytogenetic testing completed before the start of cycle 2 and mutations identified at screening. CEBPA, CCAAT/enhancer-binding protein alpha; MLL, mixed-lineage leukemia.
Figure 5.
Figure 5.
Comutational burden and NRAS mutations are associated with lack of response. (A) Scatter plot showing mean and standard deviation of number of mutations found per patient, separated by response. P < .001, comparing the difference between nonresponders and either responders (R: CRi, CRp, MLFS, or PR) or patients achieving a CR. (B) Pie charts of response assessment and ORR (patients achieving CR, CRi, CRp, MLFS, or PR) in patients with the lowest third number of comutations (≤3 mutations) and the highest third (≥6 mutations). (C) Pie chart indicating proportion of responders and nonresponders in the 14 efficacy evaluable patients with NRAS comutations (mNRAS), specifically at G12, G13, and Q61. (D) Number of mutations found per patient separated by the presence of G12, G13, or Q61 mutant mNRAS, indicating that patients with mNRAS at G12, G13, or Q61 have an increased mutational burden in this cohort. The only mNRAS+ patient to achieve a CR is highlighted in green. (E) Dot plot of mIDH2 (blue) and mNRAS (red) VAF in the same patient in the 14 efficacy-evaluable patients with NRAS comutations specifically at G12, G13, and Q61. NRASwt, NRAS wild-type.
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References

    1. Gross S, Cairns RA, Minden MD, et al. Cancer-associated metabolite 2-hydroxyglutarate accumulates in acute myelogenous leukemia with isocitrate dehydrogenase 1 and 2 mutations. J Exp Med. 2010;207(2):339-344. - PMC - PubMed
    1. Ward PS, Patel J, Wise DR, et al. The common feature of leukemia-associated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate. Cancer Cell. 2010;17(3):225-234. - PMC - PubMed
    1. Fathi AT, Sadrzadeh H, Borger DR, et al. Prospective serial evaluation of 2-hydroxyglutarate, during treatment of newly diagnosed acute myeloid leukemia, to assess disease activity and therapeutic response. Blood. 2012;120(23):4649-4652. - PubMed
    1. Janin M, Mylonas E, Saada V, et al. Serum 2-hydroxyglutarate production in IDH1- and IDH2-mutated de novo acute myeloid leukemia: a study by the Acute Leukemia French Association group. J Clin Oncol. 2014;32(4):297-305. - PubMed
    1. Xu W, Yang H, Liu Y, et al. Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of α-ketoglutarate-dependent dioxygenases. Cancer Cell. 2011;19(1):17-30. - PMC - PubMed

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