Genomics of acute myeloid leukemia

Abstract

The acute myeloid leukemia (AML) genome has been the subject of intensive research over the past 4 decades. New technologies, enabling characterization of the AML genome at increased resolution, have revealed deeper layers of complexity that have provided insights into the biological basis of this disease, nominated targets for therapy, and identified biomarkers predictive of response to therapy or long-term prognosis. Still, our understanding of AML genomics is incomplete. Recent publications have demonstrated that whole genome sequencing of primary AML samples is feasible and can detect novel, clinically relevant mutations. New insights are emerging from this work, including the clonal heterogeneity of this disease and clonal evolution that occurs over time. Some of the novel mutations are highly recurrent (>20% of patients), but there appears to be a continuum of mutation frequency down to rare (<5%) or even singleton mutations that may be relevant for the biology of this disease. Large cohorts of well-annotated samples are needed to establish mutation frequencies, implicate biological pathways, and demonstrate genotype-phenotype correlations. Although many technical and logistical challenges must be overcome, the capacity of whole genome sequencing to detect all classes of inherited and acquired genetic abnormalities makes it an attractive candidate for development as a clinical diagnostic test.

Figure 1. Clonal evolution between diagnosis and relapse in AML

Whole genome sequencing (WGS) was performed on sample trios from patients with AML: the normal genome (obtained from a skin biopsy), the primary AML genome (obtained from a bone marrow aspirate at initial diagnosis), and the relapse genome (obtained from a bone marrow biopsy after the patients received chemotherapy, entered a morphologic remission, and subsequently relapsed). All putative mutations detected by WGS were confirmed by designing custom oligonucleotide arrays to capture sites containing putative mutations, then resequencing the enriched targets to >500-fold depth in the normal, diagnostic, and relapse samples. Distinct clonal populations comprised of cells containing mutations with similar allele frequencies were identified by unsupervised clustering. The model depicts the pattern of clonal evolution that can be predicted from these mutational frequencies (modified from: L. Ding, et al, 2011, under review). In this example, three clones, each containing clusters of several hundred somatic mutations (grey, orange, purple dots) were apparent at AML diagnosis. At relapse, a subclone re-emerged (containing grey, orange mutation clusters) and acquired a cluster of additional mutations (red dot). Inherited variants (white dots) may also play a role in AML susceptibility and response to chemotherapy.