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Defining the Genomic Make up of Acute Myeloid Leukemia in Adolescents and Young Adults (AYA): Report from COG AAML03P1, AAML531 and SWOG S0106

Fabiana Ostronoff, Todd A. Alonzo, Megan Othus, Matthew A. Kutny, Robert B. Gerbing, Jerald P. Radich, Harry P Erba, Frederick R. Appelbaum, E. Anders Kolb, Alan S. Gamis, Derek L. Stirewalt and Soheil Meshinchi

Abstract

Acute myeloid leukemia (AML) is a genetically heterogeneous and highly resistant hematopoietic malignancy. Despite survival gains over the past several decades, adolescent and young adult (AYA) with AML demonstrate a consistent survival disadvantage as compared to younger patients (age < 15 years). This discrepancy in outcome is likely due to distinct aspects of disease biology in this patient population.

In recent years several somatic mutations with biological, prognostic and therapeutic significance have been identified in patients with AML. Nonetheless, these studies have been conducted in pediatric and older adult patients only. Therefore, the prevalence of these somatic mutations remains largely unknown in AYA patients.

Herein, we investigate the prevalence of common AML-associated mutations in AYA, here defined as age 15 to 39 years, aiming to characterize the disease and identify mutations that are relevant for therapeutic strategy in this age group. We compare the distribution of these mutations in the 3 age groups: children (age< 15 years), AYA (age 15 to 39 years) and older adults (age> 39 years).

Patients enrolled in the COG trials AAML03P1 and AAML0531 and in the SWOG trial S0106 were eligible for this study. Acute promyelocytic leukemia patients were excluded. AAML03P1 enrolled patients 0 to 21 years, AAML0531 enrolled patients 0 to 30 years and S0106 enrolled patients 18 to 60 years of age. We analyzed 1722 patients (age range 0 to 60 years) with newly diagnosed AML. Pre-treatment samples were obtained from AAML03P1 and AAML531 (N=1361) and S0106 (N=361). Mutation analyses were performed by a combination of targeted capture and fragment length analysis. Chi-square test was used to compare variables.

The prevalence of each mutation according to age groups is shown on Table 1. Similarly to what is observed in children and older adults, NPM1 and FLT3- ITD are the two most common mutations in AYA patients with a prevalence of 19% and 14%, respectively. When compared to the other age groups, we observe a significant increase in prevalence of both FLT3- ITD and NPM1 with aging, with a significant higher prevalence of these mutations in older adults as compared to AYA and children.

Previous studies have shown that mutations in epigenetic modifier genes are enriched in adults with AML as compared to pediatric patients. We evaluated the prevalence of mutations in these genes in the 3 age groups. We observed a significant increase in prevalence in mutations in all epigenetic modifiers genes with aging (Table 1). The combined prevalence of mutation in these genes (IDH1, IDH2, DNMT3A, ASXL1 and IDH1/2) in children, AYA and older adults were 9%, 19% and 39% (P< 0.0001), respectively, highlighting the clinical and biological importance of this class of genes in older patients.

In this large collaborative study, we define for the first time the prevalence of common mutations in AYA with AML. Our study shows that the genomic make up of patients with AYA are different from children and older adults, suggesting unique biology of the disease in this age group. Our data raise questions about future therapeutic strategies, which should take into account the age distribution of these genetic lesions. Finally, clinical correlations to determine the prognostic significance of these mutations in AYA are underway and should provide a framework for future disease risk stratification in this age group. In summary, our data shows the distinct genomic profiling of common mutations in AYA, arguing for age specific disease risk stratification as well as therapeutic strategies in this age group.

Children
(<15 years)
AYA
(15-39 years)
Older adults
(>40 years)
P value
FLT3-ITD13%19%23%0.0006
NPM16%14%32%< 0.00001
CEBPA5%8%3%0.02
WT16%9%5%0.154
IDH1/23%7%17%< 0.00001
DNMT3A0%2%16%< 0.00001
ASXL12%4%7%0.007
TET24%7%11%0.002
Table 1.

Prevalence of common mutations in children, adolescents and young adults (AYA) and older adults with AML

Disclosures Radich: Novartis: Consultancy, Research Funding; Incyte: Consultancy; Gilliad: Consultancy; Ariad: Consultancy. Erba: GlycoMimetics; Janssen: Other: Data Safety & Monitoring Committees; Sunesis; Pfizer; Daiichi Sankyo; Ariad: Consultancy; Millennium/Takeda; Celator; Astellas: Research Funding; Seattle Genetics; Amgen: Consultancy, Research Funding; Novartis; Incyte; Celgene: Consultancy, Patents & Royalties.

  • * Asterisk with author names denotes non-ASH members.