Treatment of Acute Myeloid Leukemia

Current Evidence based on Karyotype and Molecular Genetics

13th Evidence Based Management ConferenceTata Memorial Centre

27th to 1st February 2015

Hari Menon

• Outcomes with chemotherapy are punctuated by Low CR rate High treatment related morbidity and mortality Short DFS and OS

AML – ManagementA formidable challenge

Elderly AML

Adverse Cytogenetic

Normal cytogenetics with Adverse molecular profile

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

00 1 2 3 4 5 6 7 8

Yrs

Sur

viva

l Pro

bab

ility

Era1960s1970s1980s1990s2000s

1.0

0.8

0.6

0.4

0.2

00 1 2 3 4 5 6 7 8

Yrs

Sur

viva

l Pro

bab

ility

Era1960s1970s1980s1990s2000s

Total104530652

1007909

Died103492586849560

P < .001

1.0

0.8

0.6

0.4

0.2

00 1 2 3 4 5 6 7 8

Yrs

Sur

viva

l Pro

bab

ility Era

1960s1970s1980s1990s2000s

Total39

166263495486

Died39

164259461350

P < .001

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

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

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.

Strategies to improve outcomes in AML

Incorporating molecular data into risk stratification

for AML

Understanding the prognostic factors

Understanding the cytogenetics

Factor CommentAge Major impact at diagnosis

WBC Continuous variable

Prior therapy or MDS? Karyotype may be more important

Extramedullary disease Variable

Day 14 blast count Higher percentage worse

# cycles of induction One better than two

Cytogenetic/molecular profile Major Impact at diagnosis

Gene expression profile Can further subdivide patients

MicroRNA expression Needs validation by other groups

Gene sequencing Future application

MRD detection at CR ??; seems like it should be useful

Prognostic/predictive factors in AML

Factor CommentAge Major impact at diagnosis

WBC Continuous variable

Prior therapy or MDS? Karyotype may be more important

Extramedullary disease Variable

Day 14 blast count Higher percentage worse

# cycles of induction One better than two

Cytogenetic/molecular profile Major Impact at diagnosis

Gene expression profile Can further subdivide patients

MicroRNA expression Needs validation by other groups

Gene sequencing Future application

MRD detection at CR ??; seems like it should be useful

Prognostic/predictive factors in AML

Factor CommentAge Major impact at diagnosis

WBC Continuous variable

Prior therapy or MDS? Karyotype may be more important

Extramedullary disease Variable

Day 14 blast count Higher percentage worse

# cycles of induction One better than two

Cytogenetic/molecular profile Major Impact at diagnosis

Gene expression profile Can further subdivide patients

MicroRNA expression Needs validation by other groups

Gene sequencing Future application

MRD detection at CR ??; seems like it should be useful

Prognostic/predictive factors in AML

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

Impact of karyotype complexity on survival

in patients lacking cytogenetic abnormalities that confer relatively favourable or adverse prognoses in

multivariable analysis.

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%

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.

Impact of additional cytogenetic abnormality in CBF AML

What do we know about the gene mutations in

AML

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.

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

Differentially methylated regions (DMRs)

in gene mutations in AML

Can we use the mutations in normal Karyotype /intermediate

risk to influence the way we treat AML?

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

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

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 witho 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 prognosiso Allelic ratio (mut/wt)o ITD insertion site

FMS-like tyrosine kinase 3

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..

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.

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

New England Journal of Medicine, Patel et al (2012)

Mutated DNMT3A Unmutated DNMT3A

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?

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

.

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?

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