1. New Molecular Abnormalities Recognized in AML
Elli Papaemmanuil, PhD
Associate Director
Center of Hematological Malignancies
Computational Oncology Service
Department of Epidemiology and Biostatistics
Memorial Sloan Kettering Cancer Center
New York, New York

2. Use of these Slides
Learners are welcome to use and share these slides in full or in part for educational purposes in noncommercial discussions with colleagues or patients.
The materials presented may discuss uses and dosages for therapeutic products that have not been approved by the United States Food and Drug Administration. Readers should verify all information and data before treating patients or using any therapies described in these materials.
The materials published reflect the views of the authors and not those of MediCom Worldwide, Inc. or the companies providing educational grant support.
These slides may not be published, posted online, or used in commercial presentations. 
Content presented live on 6/3/17

3. Today’s Talk Cancer genome introduction
AML diagnosis and clinical challenges
The genomic landscape of AML
Translating recent cancer genome discoveries

4. Genomic alterations define each tumor’s biology, clinical presentation and treatment response

6. The Promise Translating recent cancer genomic findings to:
Understand disease biology
Inform clinical practice

7. Early
Founder Mutations
Secondary
Cooperative
Late Events
Treatment
Resistance

8. Translating Genome Discoveries to Actionable, Durable & Optimal Clinical Management Strategies

9. Translating Genome Discoveries to Actionable, Durable & Optimal Clinical Management Strategies

10. Today’s Talk Cancer genome introduction
AML diagnosis and clinical challenges
The genomic landscape of AML
Translating recent cancer genome discoveries

11. 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

12. Characterization of Recurrent Cytogenetic Abnormalities in AML
Grimwade D, et al. Blood. 2016;127(1):29-41.
Grimwade D, et al. Hematology Am Soc Hematol Educ Program. 2009:

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

14. Cytogenetic Profiling Routine at Diagnosis
Favorable| Intermediate risk 2| Intermediate risk 1 | Adverse

15. Variability in Clinical Outcomes
Favorable| Intermediate risk 2| Intermediate risk 1 | Adverse
Suggest removal

16. Patient Course Through Clinic
Gerstung M, Papaemmanuil E, et al. Nature Genetics 2017.

17. Characterization of Recurrent Cytogenetic Abnormalities in AML
Grimwade D, et al. Blood. 2016;127(1):29-41.
Grimwade D, et al. Hematology Am Soc Hematol Educ Program. 2009:

18. The AML Genome 2013 TCGA
200 AML pts, median age: 55 yrs, 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):

19. How Do We Incorporate Gene Mutations
>100 recurrently mutated genes
Many genes per patient
Diverse prognostic relationships

20. Today’s Talk Cancer genome introduction
AML diagnosis and clinical challenges
The genomic landscape of AML
Translating recent cancer genome discoveries

21. Population Studies in AML
Is there evidence of recurrent molecular subgroups?
Clinical associations?
Therapeutic opportunities?

22. Mapping the AML Genome
Extend molecular classification in AML by considering gene mutations
Data
Sequenced 1,540 patients with AML
Demographic, cytogenetic, morphology and treatment
Examined 111 genes -> 5,234 driver mutations
Durable
Unsupervised de-novo classification of AML
Consideration of extended molecular structure to include patterns of co-mutation and mutual exclusivity
Reproducible
Validated in TCGA AML database and AML MRC trial (n=2,923, unpublished data )
Clinically Relevant
Combined genomic-based categories and overall survival data to evaluate risk for the new subcategories
Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

23. Understanding the Molecular Structure in AML
Cytogenetic profiling informative in ~50% of AML patients
At least one oncogenic event found in 97% of AML patients
At least two oncogenic events found in 86% of AML patients
Comprehensive molecular profiling can characterize almost every AML patient
How do we use this information?

24. Mapping the AML Genome Data Molecular Subgroups Validation
Sequenced 1,540 patients with AML
Demographic, cytogenetic, morphology and treatment
Examined 111 genes -> 5,234 driver mutations
Molecular Subgroups
Unsupervised de-novo classification of AML
Consideration of extended molecular structure to include patterns of co-mutation and mutual exclusivity
Validation
Validated in TCGA AML database and AML MRC trial (n=2,923, unpublished data )
Clinical Relevance
Combined genomic-based categories and overall survival data to evaluate risk for the new subcategories
Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

25. Characterization of 11 Non-overlapping Molecular Subgroups in AMLx
New categories
Provisional WHO categories
Existing WHO categories
48% (n=736) of patients fell outside existing WHO and risk categories
85% accounted for by at least one molecular subgroup
Validated 2 provisional WHO categories (WHO 2016)
NPM1 mutated AML
CEBPA bi-allelic
Defined 3 new AML subgroups:
Chromatin-spliceosome
TP53 and or chromosomal aneuploidies
IDH2R172
Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

26. Mapping the AML Genome
Extend molecular classification in AML by considering gene mutations
Data
Sequenced 1,540 patients with AML
Demographic, cytogenetic, morphology and treatment
Examined 111 genes -> 5,234 driver mutations
Molecular Subgroups
Unsupervised de-novo classification of AML
Consideration of extended molecular structure to include patterns of co-mutation and mutual exclusivity
Validation
Validated in TCGA AML database and AML MRC trial (n=2,923, unpublished data )
Clinical Relevance
Combined genomic-based categories and overall survival data to evaluate risk for the new subcategories
Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

27. Temporal and Structural Molecular Phylogenies
Early
Temporal and Structural Molecular Phylogenies
AML

28. Temporal and Structural Molecular Phylogenies
Intermediate
Temporal and Structural Molecular Phylogenies
AML

29. Temporal and Structural Molecular Phylogenies
Late
AML

30. Temporal and Structural Molecular Phylogenies

31. Temporal and Structural Molecular Phylogenies
Viny AD, et al. N Engl J Med. 2016;374(23):

32. Today’s Talk Cancer genome introduction
AML diagnosis and clinical challenges
The genomic landscape of AML
Translating recent cancer genome discoveries
Diagnosis
Prognosis – risk assessment
New therapies

33. Mapping the AML Genome
Extend molecular classification in AML by considering gene mutations
Data
Sequenced 1,540 patients with AML
Demographic, cytogenetic, morphology and treatment
Examined 111 genes -> 5,234 driver mutations
Molecular Subgroups
Unsupervised de-novo classification of AML
Consideration of extended molecular structure to include patterns of co-mutation and mutual exclusivity
Validation
Validated in TCGA AML database and AML MRC trial (n=2,923, unpublished data )
Clinical Relevance
Combined genomic-based categories and overall survival data to evaluate risk for the new subcategories
Papaemmanuil E, et al. N Engl J Med. 2016;374(23):

34. Prognostic Significance of AML Classes

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

36. New Therapeutic Targets
5,236 mutations in 1540 patients
FLT3 most frequently mutated gene followed by NPM1 and DNMT3A
Actionable genes in AML
FLT3 | FLT3 inhibition
KIT | KIT inhibition
DNMT3A, IDH1/2, TET2, WT1 | Hypo-methylating agents
EZH2, WT1| EZH2 inhibitor
KRAS, NRAS | RAS-pathway inhibition
MLL | DOT1L inhibition
JAK1, JAK2 | JAK2 inhibition
IDH1, IDH2 | IDH1/ IDH2 inhibition
SF3B1, SRSF2, U2AF1, ZRSR2 | Splicing factor inhibition
Coombs CC, et al. Nat Rev Clin Oncol. 2016;13(5):

37. Novel Therapeutic Targets
74% of AML patients have at least one mutation in a gene that could be targeted
45% of AML patients have at least two mutations in genes that could be targeted
16% of AML patients have at least three mutations in genes that could be targeted
Papaemmanuil E, et al. N Engl J Med. 2016;374(23): ; Coombs CC, et al. Nat Rev Clin Oncol. 2016;13(5):

38. Characterization of 11 Non-Overlapping Molecular Subgroups in AML

39. AML With NPM1 Mutations ~27% of AML Co-mutated with: No mutations in:
DNMT3A, TET2, IDH1, IDH2R140 *
NRAS, FLT3, KRAS, PTPN11 *
RAD21
No mutations in:
IDH2R172
EZH2
TP53
Splicing Factor genes
Fusion gene AML
Chromosomal aneuploidies
AML With NPM1 Mutations

40. 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 & FLT3ITD: Lower CR rates, increase in relapse /refractory disease
* Validation required in larger cohorts

41. Characterization of 11 Non-Overlapping Molecular Subgroups in AML

42. Chromatin Spliceosome
~27% of AML
Co-mutated with:
Chromatin
Cohesin
Splicing
No mutations in:
Low DNMT3A/IDH1/IDH2
Low RTK/RAS mutations
Chromatin Spliceosome

43. Chromatin Spliceosome Group

44. Chromatin Spliceosome Group
18% of patients in our cohort n = 275
78% Intermediate risk AML
90% de novo AML
Adverse prognostic group in need of better treatment options:
Older AML (Median age 58 years old)
Low complete remission rates & high relapse related mortality
<20% alive at last follow up
Investigational targeted therapies or stratified treatment protocols:
1 gene (83%) | 2 genes (41%) | 3 genes (12%)

45. Spliceosome Complex – A Therapeutic Opportunity?
Splicing factor mutations are disease defining in MDS
Spliceosome Complex – A Therapeutic Opportunity?
SF3B1
SRSF2
U2AF1
ZRSR2
Splicing factor mutations found in 1,935 out of 4,032 patients = 48%
Proportion of patients with a mutation in >1 factor at the same time is 2%
Courtesy of Omar Abdel Wahab

46. Spliceosome Complex – A Therapeutic Opportunity?
Courtesy of Omar Abdel Wahab

47. On Target Effects of Splicing Factor Mutations
Courtesy of Omar Abdel Wahab

48. Preferential Effects on Splicing Factor Mutated Leukemia
Courtesy of Omar Abdel Wahab

49. Preferential Effects on Splicing Factor Mutated Leukemia
Courtesy of Omar Abdel Wahab

50. Summary

51. Genetic Structure in AML Provides Unique Clinical Opportunities

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

53. 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

54. & PhD, Post-doc and laboratory positions available
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
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
PhD, Post-doc and laboratory positions available

55. A Resource for Information and Education in AML
A Resource for Information and Education in AML