Mutational Burden in Acute Myeloid Leukemia Is Largely Age Dependent
Authors: Shaver Aaron C. , Seegmiller Adam C. , Strickland Stephen A. , Daber Robert D. , Mohan Sanjay R. , Ferrell Paul Brent , Vnencak-Jones Cindy , Head David R. , Kim Annette S. , Zutter Mary M. , Savona Michael R. 
Published: October 2019

Abstract
Risk stratification of acute myeloid leukemia (AML) is important for prognosis and for guiding treatment decisions. The National Comprehensive Cancer Network (NCCN) classifies AML into three risk categories (favorable, intermediate, or poor) based on recurrent cytogenetic or molecular abnormalities. Clinical next-generation sequencing (NGS) is beginning to clarify the relationship between these categories and the spectra of oncogenic mutations, and leading to the development of new targeted therapies. The role of NGS data in favorable risk disease and the interaction of the NCCN classification with other prognostic risk factors such as age are not fully understood.
Here, we assess 32 favorable risk [12 inv(16), 2 t(8;21), and 18 normal karyotype NPM1 mutated/FLT3 ITD negative] and 88 poor risk (33 transformed from documented MDS, 47 with complex or monosomal karyotype without previous documented MDS, and 8 therapy-related with normal karyotype) cases of AML. Results of NGS using a 37 gene, myeloid neoplasm-specific panel were incorporated with conventional cytogenetics and FISH results, as well as clinical history including patient age and survival data. Genes were arranged into four functional groups: splicing, epigenetic, signaling, and transcription (see Table 1).
Analysis of the mutational spectra categorized by NCCN risk category and by age reveals several patterns (see Table 1). TP53 mutations were associated with a low total mutation number, as previously reported. Core binding factor (CBF) AMLs were primarily seen in young patients (<60 years) and were associated with a predominance of signaling mutations, without splicing or epigenetic mutations. A similar pattern was seen in young patients with favorable risk, NPM1-positive cases as well as in young patients with non-TP53-mutated poor risk AML. Older patients (≥60 years) with non-TP53-mutation poor risk AML had a high number of splicing and epigenetic mutations, as expected, but so did older patients with favorable risk, NPM1-positive disease.
For favorable risk and non-TP53-mutated poor risk AML, stratification by age (younger/older than 60 years) provided significant differentiation between total mutations and mutation categories superior to stratification by risk group (see Table 2). Stratifying mutation spectrum by age demonstrates no significant difference between younger and older poor risk TP53-mutated cases.
To determine the degree to which the effect of age and risk category on survival is driven by the increased likelihood of splicing or epigenetic mutations, Cox regression analysis was performed on retrospective overall survival data for favorable risk and non-TP53-mutated poor risk cases. This analysis demonstrated the expected significant independent effects of risk category and age, but showed no significant independent effect of the presence of splicing or epigenetic mutations (see Table 3).
These preliminary findings suggest that the mutation spectrum of AML is more a function of age than of NCCN risk category. Additionally, in our analysis, the primary effect of age on survival is independent of mutation profile.
Table 1. Category CBF NPM1 pos, FLT3-ITD neg, normal karyotype Known MDS Complex cytogenetics with no known history of MDS Treatment related, normal karyotype TP53 mutated poor risk Age <60 <60 ≥60 <60 ≥60 <60 ≥60 <60 ≥60 <60 ≥60 N 13 5 13 4 19 9 17 3 5 11 20 Total mutations 1.2±0.3 2.6±0.4 3.5±0.2 2.8±0.8 3.5±0.3 2.0±0.3 2.8±0.5 0.3±0.3 3.4±1.2 1.7±0.2 1.9±0.3 Mutations by gene group Splicing1 0 0 5 0 13 0 9 0 2 1 4 Epigenetic2 0 2 16 2 23 3 17 0 4 1 7 Signaling3 10 4 5 3 8 8 4 1 7 4 2 Transcription4 2 0 2 2 9 0 10 0 1 0 1 1: SRSF2, U2AF1, ZRSR2, SF3B1 2: DNMT3A, IDH1, IDH2, TET2, EZH2, ASXL1 3: FLT3, KIT, KRAS, NRAS, PTPN11, WT1, CBL, MYD88 4: GATA2, PHF6, RUNX1, BCOR, BCORL1, ETV6
Table 2. Data set TP53 -mutated Poor Risk Favorable Risk and Non-TP53 -mutated Poor Risk Comparison Younger vs. Older Younger vs. Older Favorable vs. Poor Risk Total mutations, P value1 NS < 0.0001 NS Mutations by gene group, P value2 Splicing NS < 0.0001 0.04 Epigenetic NS < 0.0001 NS Signaling NS 0.05 NS Transcription NS 0.01 0.03 NS: Not significant. 1: T-test 2: Fisher's exact test
Table 3. P value Hazard Ratio NCCN Risk Category (Favorable vs. Poor) <0.001 3.637 Age (< or ≥60) 0.038 2.006 Presence of Splicing or Epigenetic Mutations 0.788 0.922 Cox regression analysis of overall survival

Disclosures
Strickland: Sunesis Pharmaceuticals: Other: Steering Committee and Advisory Board Participation; Boehringer-Ingelheim: Other: Advisory Board Particpation; Daiichi-Sankyo: Other: Advisory Board Particpation; Alexion Pharmaceuticals: Other: Advisory Board Particpation; Amgen: Other: Advisory Board Particpation. Daber:Archer Diagnostics: Membership on an entity's Board of Directors or advisory committees; BioReference Laboratories: Employment. Savona:Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.