1. Treatment of Acute Myeloid Leukemia Current Evidence based on Karyotype and Molecular Genetics 13 th Evidence Based Management Conference Tata Memorial Centre 27 th to 1 st February 2015 Hari Menon

2. Outcomes with chemotherapy are punctuated by  Low CR rate  High treatment related morbidity and mortality  Short DFS and OS AML – Management A formidable challenge Elderly AML Adverse Cytogenetic Normal cytogenetics with Adverse molecular profile

3. Survival in AML by Time Period Kantarjian H, et al. Cancer. 2010;116:4896-4901. Overall < 60 yrs ≥ 60 yrs 1.0 0.8 0.6 0.4 0.2 0 012345678 Yrs Survival Probability Era 1960s 1970s 1980s 1990s 2000s 1.0 0.8 0.6 0.4 0.2 0 012345678 Yrs Survival Probability Era 1960s 1970s 1980s 1990s 2000s Total 104 530 652 1007 909 Died 103 492 586 849 560 P <.001 1.0 0.8 0.6 0.4 0.2 0 012345678 Yrs Survival Probability Era 1960s 1970s 1980s 1990s 2000s Total 39 166 263 495 486 Died 39 164 259 461 350 P <.001

4. MRC AML Trials: Overall Survival Survival in the younger patients (Age 15-59)

5. MRC AML Trials: Overall Survival Survival in the older patients (Age >60)

6. AML- Management  Therapy of AML – Impacted by increasing genomic complexity.  Multiple abnormalities  Chromosomal  Mutations  Interactions between cytogenetic abnormalities and mutations adds an additional layer of intricacy.  Epigenetic changes modify the genetic landscape – a third dimension.

7. Strategies to improve outcomes in AML Incorporating molecular data into risk stratification for AML Understanding the prognostic factors Understanding the cytogenetics

8. FactorComment AgeMajor impact at diagnosis WBCContinuous variable Prior therapy or MDS?Karyotype may be more important Extramedullary diseaseVariable Day 14 blast countHigher percentage worse # cycles of inductionOne better than two Cytogenetic/molecular profileMajor Impact at diagnosis Gene expression profileCan further subdivide patients MicroRNA expressionNeeds validation by other groups Gene sequencingFuture application MRD detection at CR??; seems like it should be useful Prognostic/predictive factors in AML

9. FactorComment AgeMajor impact at diagnosis WBCContinuous variable Prior therapy or MDS?Karyotype may be more important Extramedullary diseaseVariable Day 14 blast countHigher percentage worse # cycles of inductionOne better than two Cytogenetic/molecular profileMajor Impact at diagnosis Gene expression profileCan further subdivide patients MicroRNA expressionNeeds validation by other groups Gene sequencingFuture application MRD detection at CR??; seems like it should be useful Prognostic/predictive factors in AML

10. FactorComment AgeMajor impact at diagnosis WBCContinuous variable Prior therapy or MDS?Karyotype may be more important Extramedullary diseaseVariable Day 14 blast countHigher percentage worse # cycles of inductionOne better than two Cytogenetic/molecular profileMajor Impact at diagnosis Gene expression profileCan further subdivide patients MicroRNA expressionNeeds validation by other groups Gene sequencingFuture application MRD detection at CR??; seems like it should be useful Prognostic/predictive factors in AML

11. CALGB Database: Outcomes in AML Patients < 60 years of Age based on Karyotype at Diagnosis Major cytogenetic subgroups of acute myeloid leukemia (AML) (excluding acute promyelocytic leukemia) and associated gene mutations

13. Impact of karyotype complexity on survival in patients lacking cytogenetic abnormalities that confer relatively favourable or adverse prognoses in multivariable analysis.

15. The Monosomal Karyotype  2 autosomal monosomies OR  Single autosomal monosomy in combination  with at least one structural aberration  Incidence- 0% to 15%  Increases with age  Frequently associated with other adverse risk  cytogenetic abnormalities  Alterations in TP53 -80%  CR-18-38%  4-year overall survival rates between 3% and 9%

17. KIT mutations in CBF leukemia  KIT is a cytokine receptor with tyrosine kinase activity.  Involved in cell proliferation signalling.  Mutations in KIT - prevalent among CBF-leukemia.  Associated with increased relapse risk (Care et al, 2003; Paschka et al, 2006).  Deleterious effect of KIT mutations restricted to patients with t(8:21), not seen in patients with inv16 (Boissel et al, 2006; Park et al, 2011; Patel et al, 2012).  Doesn’t seem to impact pediatric leukemia with CBF.

18. Impact of additional cytogenetic abnormality in CBF AML

19. What do we know about the gene mutations in AML

20.  23 genes were significantly mutated  237 genes were mutated in 2 or more people..  Recurring, tier 1 mutations in each of the 200 samples Cancer Genome Atlas Research Network 200 patients with De novo AML Cancer Genome Atlas Research Network. NEJM 2013;368:2059e74.

22.  Class I mutation ( FLT3, KIT, N/KRAS, PTPN11, JAK1/3 and TP53 mutations)  Causes constitutive activation of intracellular signals that contribute to the growth and survival.  Class II mutation ( NPM1, CEBPA, RUNX1 and GATA2 mutations, and RUNX1- RUNX1T1 and CBFB-MYH11)  Blocks differentiation and/or enhance self-renewal by altered transcription factors.  Epigenetic status (ASXL1, ATRX, EZH2, TET2, PBRM1, DNMT3A, IDH1/2, KDM6A, MLL and DOT1L mutations)  generate a new class because of their overlap mutations both with class I and class II mutations Kihara –et al Leukemia (2014) 28, 1586-1595

23. Differentially methylated regions (DMRs) in gene mutations in AML

25. Can we use the mutations in normal Karyotype /intermediate risk to influence the way we treat AML?

26.  NPM1 mutations represent the most frequent gene mutation in AML.  Overall incidence of 25%–35%  CN-AML, 45%–60%,  NPM1 mutations have been associated with chemo-sensitivity in younger and older patients.  The sensitivity is decreased with presence of FLT3 mutation. NPM1 mutation

27.  Impact of other co-occurring lesions, such as DNMT3A and IDH1/IDH2 mutations, is less clear.  Minimal residual disease has become relevant tool with which to identify patients with NPM1-mutated AML who are at high risk for relapse.  Patient with MRD positivity are at higher risk of relapse and are candidates for transplant. NPM1 mutation

28. JMD TK1 TK2 1. Nakao M, et al. Leukemia. 1996;10:1911-1918. 2. Whitman SP, et al. Cancer Res. 2001;61:7233-7239. 3.Thiede C, et al. Blood. 2006;107:4011-4020. 4.Thiede C, et al. Blood. 2002;99:4326-4335. 5.Kottaridis PD, et al. Blood. 2002;100:2393- 2398. 6. Gale RE, et al. Blood. 2008;111:2776-2784. 7. Breitenbuecher F, et al. Blood. 2009;113:4063-4073. FLT3 Mutations in AML 20% to 25% of patients with AML [1,2] High incidence in AML with o NPM1 mutations (40%) [3] o t(15;17)(q24;q21)/PML-RARA (40% to 45%) [4] o t(6;9)(p23;q34)/DEK-NUP214 (90%) [4] Associated with inferior prognosis o Allelic ratio (mut/wt) o ITD insertion site FMS-like tyrosine kinase 3

29. FLT3 ITD mutations Is more intricate understanding throwing light? 2 important aspects:  The mutant-to-wild type ratio  ITD insertion site.  Allelic ratio consistently show an association between high allelic burden. A threshold of +0.50, and unfavorable outcome has been shown by AMLSG.  The prognostic impact of low and intermediate FLT3-ITD allelic ratio is still unclear.  ITD insertion, particularly in the B1 sheet of the tyrosine kinase domain (TKD) 1 that is present in approx 1/4 of the cases, has been shown to be associated with very poor prognosis.  NPM-1 may have a protective role..

30. DNMT3A mutations  Methyltransferase that methylates cytosines in CpG dinucleotides.  Recurrent mutations at the highly conserved R882 residue.  Found in more than 20% of adult AML patients, making it the second most common somatic mutation, after FLT3 mutations, in de novo AML.  Tumor-suppressor role for DNMT3A in AML.

31. DNMT3A mutation Inferior DFS and in trend for a shorter OS. Age-dependent impact of different DNMT3A mutation types. Affection of codon R882 were associated with worse outcome in terms of relapse-free survival and mutations not affecting codon R882 were favorable in terms of OS. Unfavourable effect of DNMT3A mutations could be overcome by increasing the dose of daunorubicin during induction therapy

32. New England Journal of Medicine, Patel et al (2012) Mutated DNMT3A Unmutated DNMT3A

33. So how does understanding all this heterogeneity at genetic and epigenetic level?  Does it guide therapy?  Are they only predictive markers?  Can they function as targets that can be perturbed?

34. Revised risk stratification of patients with AML on the basis of integrated genetic analysis.

35. .

37. Epigenetic targeting in AML  What is the target?  Whom to target?  When to target?  How and when to assess efficacy?  What is the duration of therapy?  What is the right combination?

38. Conclusions Cytogenetic profiling continues to be critical in defining AML subsets and defining plan of therapy. Understanding the heterogeneity of the CK AML has been critical in modifying the way we look at this subset. Gene profiling will allow a more precise diagnosis and the identification of patient subsets with distinct gene signatures. Integrative mutational analysis may be instrumental to identifying patients who will benefit from novel molecular-targeted therapies. Although genetic profiling will be predictive it its several interactions need to be understood better for more rational use