Examining Genetics and Genomics of Acute Myeloid Leukemia in 2017

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1 Examining Genetics and Genomics of Acute Myeloid Leukemia in 2017 Elli Papaemmanuil, PhD Memorial Sloan Kettering Cancer Center New York, New York, United States

2 Today s Talk Cancer genome introduction Acute myeloid leukemia (AML) diagnosis and clinical challenges The genomic landscape of AML Translating recent cancer genome discoveries

3 Genomic alterations define each tumor s biology, clinical presentation, and treatment response

4

5 Early Founder Mutations Secondary Cooperative Late Events Treatment Resistance

6 Today s Talk Cancer genome introduction Acute myeloid leukemia (AML) diagnosis and clinical challenges The genomic landscape of AML Translating recent cancer genome discoveries

7 1. National Cancer Institute. Adult Acute Myeloid Leukemia Treatment (PDQ ) Health Professional Version. Accessed 20 June Medinger M, et al. Leuk Res Rep. 2016;6: National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology: Acute Myeloid Leukemia. Version Accessed 20 June Acute Myeloid Leukemia 20,000 New Cases 10,000 Deaths Risk Factors: AGE (median age = 69 years) Acquired mutations Prior chemotherapy for other cancers Ionizing radiation Industrial solvents Percent of New Cases by Age Group: All Races, Both Sexes; SEER

8 1. National Cancer Institute. Adult Acute Myeloid Leukemia Treatment (PDQ ) Health Professional Version. Accessed 20 June Medinger M, et al. Leuk Res Rep. 2016;6: National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology: Acute Myeloid Leukemia. Version Accessed 20 June Acute Myeloid Leukemia 20,000 New Cases 10,000 Deaths Treatment: Chemotherapy (7 + 3, Cytarabine and Ara-C) Bone marrow transplantation 26% 5-year survival Treatment improvements Transplantation Dose optimization and scheduling of approved chemotherapies > Myelosuppressive, toxic, and have a negative impact on quality of life (QOL)

9 AML: Not Much Improvement Over Time, Especially in Older Adults Ages Years Ages 60 Years Burnett A, et al. J Clin Oncol. 2011;29(5):

10 Characterization of Recurrent Cytogenetic Abnormalities in AML Grimwade D, et al. Blood. 2016;127(1): Grimwade D, et al. Hematology Am Soc Hematol Educ Program. 2009:

11 Characterization of Recurrent Cytogenetic Abnormalities in AML Diagnostic biomarkers Prognostic algorithms Guide clinical decision making Understand the biologic mechanisms that cause AML Deliver new and effective therapeutic interventions (PML-RARA, t(15;17))

12 Incorporation of Molecular Characterization at AML Diagnosis

13 Grimwade D, et al. Blood. 2016;127(1): Grimwade D, et al. Hematology Am Soc Hematol Educ Program. 2009:

14 The AML Genome 2013 TCGA 200 AML patients, median age: 55 years, only de novo AML; whole genome (n = 50) and whole exome (n = 150) sequencing The Cancer Genome Atlas (TCGA) Research Network. N Engl J Med. 2013;368(22):

15 200 Recurrently Mutated Genes 23 Significant 3 Incorporated Into Diagnostic and Prognostic Schemas WHO Classification of AML With Recurrent Genetic Abnormalities AML with t(8;21)(q22;q22); RUNX1-RUNX1T1 AML with inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB- MYH11 AML with t(15;17)(q22;q12); PML-RARA AML with t(9;11)(p22;q23); MLLT3-MLL AML with t(6;9)(p23;q34); DEK-NUP214 AML with inv(3)(q21;q26.2) or t(3;3)(q21;q26.2); RPN1-EVI1 AML (megakaryoblastic) with t(1;22)(p13;q13); RBM15-MKL1 Provisional entity: AML with mutated NPM1 Provisional entity: AML with mutated CEBPA ELN Risk Groups Favorable Inter-I Inter-II Adverse Molecular Subsets t(8;21)(q22;q22); RUNX1-RUNX1T1; inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 Mutated NPM1 without FLT3-ITD (normal karyotype) Mutated CEBPA (normal karyotype) Mutated NPM1 and FLT3-ITD (normal karyotype) Wildtype NPM1 and FLT3-ITD (normal karyotype) Wildtype NPM1 without FLT3-ITD (normal karyotype) t(9;11)(p22;q23); MLLT3-MLL Cytogenetic abnormalities not classified as favorable or adverse inv(3)(q21q26.2) or t(3;3)(q21;q26.2); RPN1-EVI1 t(6;9)(p23;q34); DEK-NUP214; t(v;11)(v;q23); MLL rearranged 5 or del(5q); 7; abnl(17p); complex karyotype

16 N = 1,540 Cytogenetics PBC + Morphology Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

17 Understanding the Molecular Structure in AML Cytogenetic profiling informative in ~50% of patients with AML At least one oncogenic event found in 97% of patients with AML At least two oncogenic events found in 86% of patients with AML Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

18 Genomic Classification in AML o o 85% of AML classified in at least one molecular subgroup Each group defined by specific and ordered in time cooperating mutations Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

19 Molecular Classes and Concurrent Mutations RUNX1 ~40% MLL-PTD ~25% ASXL1 ~20% DNMT3A ~20% SRSF2 ~20% STAG2 ~15% NRAS ~15% FLT3-ITD ~15% TET2 ~15% BCOR ~10% U2AF1 ~10% PHF6 ~10% ZRSR2 ~5% SF3B1 ~10% EZH2 ~5% Chromatin-spliceosome 13% IDH2 R172 1% DNMT3A ~70% No class 5% No drivers 3% t(15;17)(q22;q21); PML-RARA 13% FLT3-ITD ~35% FLT3-TKD ~15% WT1 ~15% t(8;21)(q22;q22.1); RUNX1-RUNX1T1 7% inv(16)(p13.1q22); CBFB-MYH11 5% KIT ~25% NRAS ~20% Cohesin a ~20% ASXL2 ~20% ZBTB7A ~20% ASXL1 ~10% EZH2 ~5% KDM6A ~5% MGA ~5% DHX15 ~5% NRAS ~40% KIT ~35% FLT3-TKD ~20% KRAS ~15% TP53 mutant - chromosomal aneuploidy 10% bicebpa mutant 4% GATA2 ~30% NRAS ~30% WT1 ~20% CSF3R ~20% NPM1 mutant 30% DNMT3A ~50% FLT3-ITD ~40% Cohesin a ~20% NRAS ~20% IDH1 ~15% IDH2 R140 ~15% PTPN11 ~15% TET2 ~15% t(v;11q23.3); X-KMT2A 4% t(9;22)(q34.1;q11.2); BCR-ABL1 1% t(6;9)(p23;q34.1); DEK-NUP214 1% t(5;11)(q35.2;p15.4); NUP98-NSD1 1% KRAS ~20% NRAS ~20% FLT3-ITD ~70% KRAS ~20% FLT3-ITD ~85% inv(3)(q21.3q26.2); GATA2,MECOM 1% Other rare fusions 1% NRAS ~30% KRAS ~15% t(3;5)(q25.1;q35.1); NPM1-MLF1 t(8;16)(p11.2;p13.3); KAT6A-CREBBP t(16;21)(p11.2;q22.2); FUS-ERG t(10;11)(p12.3;q14.2); PICALM-MLLT10 t(7;11)(p15.4;p15.2); NUP98-HOXA9 t(3;21)(q26.2;q22); RUNX1-MECOM PTPN11 ~20% GATA2 ~15% PHF6 ~15% BCOR ~10% NF1 ~10% SF3B1 ~20% ETV6 ~15% RUNX1 ~10% ASXL1 ~10% Döhner H, et al. Blood. 2017;129(4):

20 Age-Related Frequency of Selected Gene Mutations Analysis based on 10,622 patients with AML from the AMLSG data base Age distribution: <45 years, n = 2228; years, n = 3392; years, 2517; >70 years, n = 2,485 Bullinger L, et al. J Clin Oncol. 2017;35(9):

21 Prognostic Significance of AML Classes Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

22 Prognostic Significance of AML Classes Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

23 NPM1 Mutated AML RAD21, NRAS G12/G13 : High CR1 rates, low relapse rates, good long term survival IDH1, IDH2 & chromatin spliceosome: Lower CR rates / primary refractory DNMT3A & FLT3 ITD : Lower CR rates, increase in relapse / refractory disease * Validation required in larger cohorts Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

24 AML Genomic Blueprint Unique Clinical Opportunities

25 Therapeutic Targets 5236 mutations in 1540 patients FLT3 most frequently mutated gene followed by NPM1 and DNMT3A Actionable genes in AML FLT3 FLT3 inhibition MLL DOT1L inhibition KIT KIT inhibition JAK1, JAK2 JAK2 inhibition DNMT3A, IDH1/2, TET2, WT1 Hypo-methylating agents IDH1, IDH2 IDH1/ IDH2 inhibition EZH2, WT1 EZH2 inhibitor SF3B1, SRSF2, U2AF1, ZRSR2 Splicing factor inhibition KRAS, NRAS RAS-pathway inhibition

26 Approaches to the Analysis of Complex, Heterogeneous, and Evolving Cancer Genomes Translating recent cancer genomic findings to: Understand disease biology Inform clinical practice Diagnosis Risk stratification Gene-treatment interactions Models of disease biology

27 & Pap Lab: Gunes Gundem Matahi Moarrii Elsa Bernard Kelly Bolton Dan Leongamornlert Andrés Deslaulier Adi Deshpante Leukemia genomics MSK: Franck Rapaport Juan Medina Noushin Farnoud Venkata Yellapantula Mathieu Najm University of ULM Hartmut Döhner Konstanze Döhner Lars Bullinger Richard Schlenk Welcome Trust Sanger Institute Peter Campbell Moritz Gerstung CHM Translation team: Minal Patel Erin McGovern Chris Famulare Akshar Patel Working Groups: International Working Group MDS Pan Myeloid working group UK ALL clinical trials working group

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