Somatic Characterization of Pediatric Acute Myeloid Leukemia Using Next-Generation Sequencing Heather L. Schuback,a Robert J. Arceci,b and Soheil Meshinchia Acute myeloid leukemia (AML) is a complex and heterogeneous disease with distinct age-associated genomic and epigenomic alterations. A large number of somatic karyotypic and molecular alterations have been identified in AML to date; however, very few predict outcome or identify potential therapeutic targets. Here we describe the current state of known molecular and genetic alterations in pediatric AML. Further, as recent advances in sequencing technologies have revolutionized our ability to interrogate cancer genome, transcriptome, and epigenome, we will also review the emerging genomic data identified by next-generation sequencing and discuss their potential impact as tools for therapeutic interventions in the near future. In coming years, a wealth of data from large-scale discovery phase projects such as the Children's Oncology Group/ National Cancer Institute (COG/NCI) TARGET AML initiative will be available to researchers to discover new biomarkers for risk and target identification in pediatric AML. Semin Hematol 50:325–332. C 2013 Elsevier Inc. All rights reserved.

A

cute myeloid leukemia (AML) is a hematopoietic malignancy of myeloid lineage that is defined by genetic and epigenetic alterations in the hematopoietic stem/progenitor cells, leading to dysregulation of critical signal transduction pathways that results in clonal expansion without complete differentiation. AML can be broadly divided into two categories: de novo AML and secondary AML. Secondary AML refers to the evolution of AML subsequent to exposure to cytotoxic therapy or antecedent hematopoietic insufficiency (eg, myelodysplastic syndrome [MDS] or marrow failure) leading to distinct karyotypic and molecular alterations; for example, MLL translocations are observed after exposure to topoisomerase inhibitors. As secondary AML is a distinct entity under active investigation,1 this review will focus on genomics of de novo AML. Large numbers of somatic karyotypic and molecular alterations have been identified in de novo AML. Despite

a

Clinical Research Division, Fred Hutchinson Cancer Research Center, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA. b Children’s Center for Cancer and Blood Disorders, Hematology/ Oncology, The Ron Matricaria Institute of Molecular Medicine At Phoenix Children’s Hospital, Department of Child Health, University of Arizona, College of Medicine–Phoenix Phoenix, AZ. Conflicts of interest: none. Address correspondence to Soheil Meshinchi, MD, PhD, Clinical Research Division, Fred Hutchinson Cancer Research Center, Department of Pediatrics, University of Washington School of Medicine, 1100 Fairview Ave N, D5-380, PO Box 19024, Seattle, WA 98109-1024. E-mail: [email protected] 0037-1963/$ - see front matter & 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1053/j.seminhematol.2013.09.003

early reports of possible associations with clinical phenotypes, the majority do not appear to have prognostic value, nor do they identify a specific target or a distinct pathway that can be readily exploited for therapeutic intervention. The paucity of targets is more notable in childhood AML, particularly since the observed, age-associated evolution of molecular alterations reveals a distinct profile for younger children with AML compared to older children and adolescents with AML. Furthermore, the landscape of genetic alterations differs markedly from AML in adults. Although AML can be diagnosed in young children and comprises nearly 25% of all leukemias in children, it is generally viewed as a disease of older adults, with a median age of diagnosis approaching 70 years. Data from the Surveillance, Epidemiology and End Results (SEER) database indicate that the incidence of AML in children and young adults is substantially lower compared to older adults (Figure 1A).2 In the pediatric setting, the highest incidence of AML is in the first year of life, with an incidence of 1.6 per 100,000, which declines by approximately 0.12 per 100,000 per year in the first decade of life (Figure 1B) to an incidence of 0.4 per 100,000 by age 10. In the following three decades, there is a minimal increase in AML of approximately 0.02 cases per 100,000 per year to that of 1.3 cases per 100,000 per year by age 40, nearly equivalent to that seen in infants. After the fourth decade, there is a substantial increase in the rate of AML diagnosis with a diagnosis of 0.18 per 100,000 per year, nearly 9 times the observed rate in the previous three decades to an incidence of 6.2 per 100,000 by age 65. In the following two decades, AML diagnosis increases

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Figure 1. Incidence of AML by age (A)2 and rate of change in AML incidence (per 100,000 per year); (B) in age groups calculated from (A).

substantially at a rate of 0.675 per 100,000, over 30-fold higher that seen in younger patients (age 10–40). The differences in the epidemiologic distribution of AML are also reflected in distinct patterns of abnormal karyotypes and more recently demonstrated genomic alterations. These differences provide important insights into the underlying biology and perhaps the clinical outcomes related to AML.

GENOMIC LANDSCAPE OF CHILDHOOD AML Differences in the distribution of karyotypic alterations in younger (o55 years) and older adults has been well documented, as well as their association with clinical outcome.3 However, since the comprehensive investigation of genomic variation in childhood AML is ongoing, the preliminary findings have begun to uncover distinct patterns of chromosomal events observed by karyotypes or single-nucleotide polymorphism (SNP) microarrays that are under active investigation. Characterization of the landscape of somatic genomic changes has provided new insights into the biology of pediatric AML, affording an opportunity to begin to correlate these changes with clinical and biological phenotypes. To date, diseaseassociated genomic alterations, whether translocations, numerical structural alterations (eg, monosomies, trisomies), or sequence variations (point mutations and indels), have been investigated as powerful tools for prediction of response and outcome in a subset of patients.

Karyotypic Alterations Cytogenetic alterations have been the cornerstone of diagnosis in AML. As a diagnostic tool, cytogenetics have been instrumental for classification and, more importantly, stratification for treatment based on risk categorization. Although a large number of chromosomal alterations have been described in AML, the majority of pediatric AML cases separate into distinct cytogenetic categories based on specific chromosomal events (Figure 2): 25% have either a

translocation of t(8;21) or an inversion, Inv(16), which are collectively referred to as core binding factor AML (CBFAML); 12% have a distinct translocation, t(15;17); 20% have rearrangements involving the MLL gene and 20% do not have a discernible karyotypic abnormality (normal karyotype). In addition to karyotypic alterations, diseaseassociated mutations have been identified in AML, with the highest fraction observed in those with a normal karyotype. Overall, more than 90% of pediatric AML cases have at least one genomic alteration that can be detected by current methods. Sub-karyotypic, Abnormalities

Cryptic

Chromosomal

Cytogenetic abnormalities of large chromosomal regions can be detected by conventional cytogenetics. Karyotypic analysis in AML is limited by the ability to culture leukemic cells in vitro, as well as the size of the region involved. Small structural alterations, including deletions or duplications, can escape detection by conventional cytogenetics and may require more specialized techniques such as fluorescence in situ hybridization (FISH). Loss of heterozygosity (LOH) that is generally associated with deletions leads to haplo-insufficiency that can contribute to malignant transformation. SNP microarray analysis can detect copy number change at a resolution smaller than detectable by conventional karyotyping, but bounded on the lower threshold by size of the fragments involved. In this regard, it is possible to identify smaller regions of copy number variations (CNVs) that may not be amenable to identification by cytogenetics. Combination of copy number and SNP markers also enables identification of regions of copy-neutral LOH (CN-LOH), also referred to as acquired uniparental disomy (aUPD),4–6 a homologous recombinationmediated process in which a homozygous state across a genomic fragment arises after an initial acquisition of a heterozygous mutation. Using the SNP genotyping arrays (DNA array), large pediatric and adult studies have

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evaluated the utility of these methodologies for identification of clinically meaningful somatic alterations.7,8 These genome-wide array studies have identified recurrent regions of somatic CNVs and CN-LOH, but they failed to identify clinically useful alterations that could be advanced in the clinical arena. Despite the promise of using large structural abnormalities (eg, somatic translocations and inversions), the application of nextgeneration sequencing technologies to diagnostic and recurrent pediatric AML promises to characterize new alterations, particularly single-nucleotide variants and small CNVs. In turn, some of these findings could lead to clinical studies and could be used as important prognostic factors for therapeutic risk stratification.

Somatic Mutations in Childhood AML Somatic mutations in genes known to regulate hematopoiesis have been identified in a significant proportion of childhood AML. In a subset, these mutations have been shown to be valuable in clinical risk stratification and in a few circumstances, they were predictive of clinical outcome. As discovery studies proceed rapidly, many novel mutations have been implicated in AML pathogenesis 26–28. So far, recent studies have shown that mutations in any of three genes (eg, FLT3, NPM1, and CEBPA) could have important clinical implications in childhood AML and have been incorporated in clinical trials either as prognostic markers or as therapeutic targets, or both. The most commonly mutated gene in childhood AML is FMS-like tyrosine kinase 3 (FLT3), which leads to constitutive activation of the receptor kinase activity. Two distinct types of mutations have been described: one in the internal tandem duplication (FLT3/ITD) of the juxtamembrane domain coding sequence and the second is a missense mutation in the activation loop domain (FLT3/ ALM).9,10 Early surveys indicate that FLT3/ITD is detected in 15% of all children with AML and has been shown to be highly associated with poor response to induction chemotherapy, as well as a high relapse rate.11,12 Despite biologic similarity to FLT3/ITD, those with FLT3/ALM do not have an increase in failure rate for induction or survivorship.11 Several studies have shown that patients with FLT3/ITD who receive allogeneic stem cell transplantation while in complete remission have an

improved outcome, thus providing a target-based therapy allocation for this high-risk cohort of patients.11,13,14 Further, novel kinase inhibitors have shown efficacy in inducing a high rate of remission in patients with FLT3/ITD, although the long-term benefits of such interventions have yet to be determined in ongoing studies.15 Again, in contrast to FLT3/ITD, the class of FLT3/ALM mutations does not appear to be comparably amenable to inhibition by the new targeted kinase inhibitors.16–18 Mutations in nucleophosmin (NPM1) are common in AML, with a prevalence of 30% in adult AML and 8%– 10% in pediatric AML.19–22 NPM1 mutations appear to be more prevalent in AML with normal karyotype, with a prevalence of nearly 40%–50% in adults and 20% in pediatric AML. NPM1 mutations are particularly interesting because the gene encodes a ubiquitously expressed molecular chaperone that shuttles rapidly between the nucleus and cytoplasm, thus implicating a key, novel pathway in myeloid differentiation. Disease-associated mutations, characterized by 4 base insertions in exon 12 of the NPM gene, lead to impaired nuclear localization of the nucleophosmin protein. The presence of NPM mutations appears to be associated with a favorable outcome with reduced relapse risk and improved survival; those with NPM mutations have a similar outcome as those with CBF-AML. In pediatric AML, the presence of NPM1 mutations appears to overlap with the subsubset of patients with FLT3/ITD; there is an early suggestion that its co-expression appears to partially ameliorate the poor prognosis conferred by FLT3/ITD alone.21 Mutations in the transcription factor, CCAAT/ enhancer binding protein-alpha, (CEBPA) occur in approximately 5% of childhood AML cases. The majority of cases with these mutations occur in a bi-allelic manner, in which two distinct mutations occur, one in the N-terminal domain (NTD) and the second in the opposite allele affecting the bZip domain.23 Such a bi-allelic mutation results in the expression of a truncated protein, which has been shown to be sufficient for development of AML.24 This is particularly interesting because of the role CEBPA plays in the regulation of myeloid proliferation and terminal granulocytic differentiation. Children’s Oncology Group (COG) studies have demonstrated that CEBPA mutations occur in patients with normal

Figure 2. Karyotypic alterations in childhood versus adult AML.

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Figure 3. Association of age with karyotypic alterations (A) or somatic mutations (B) in pediatric AML.

cytogenetic profiles and are associated with decreased relapse risk, as well as improved survival, compared to patients without a mutation.25

Age-Associated Genomic Variation in Childhood AML The biology of AML also differs with age, particularly from newborn to adults; for instance, the prevalence and significance of genomic alterations in childhood malignancies should be considered based on the age of the patient. The age-based variation in the type and the prevalence of structural and sequence alterations is notable in childhood AML (Figure 3). For example, MLL translocations, collectively seen in 20% of AML in children, are highly prevalent in infants, in which nearly 60% of infants under 1 year of age harbor 11q23 alterations. This rapid evolution of disease, within weeks to months of birth strongly suggests the impact of MLL translocations in myeloid leukemogenesis. The MLL prevalence declines over the following decade of life, to less than 10%, similar to what is observed in younger adults (Figure 3A). In addition, CBF-AML, which is quite rare in infants, increases in prevalence by age to nearly 30% by the second decade of life, and similarly, those without karyotypic alterations (normal karyotype) are rare in younger patients (likely due to the high prevalence of MLL translocations) and their prevalence increases to nearly adult prevalence of nearly 50% in adolescents and young adults. In addition to the aforementioned alterations present in a high fraction of childhood AML, the structural alterations seen in adults and in particular individuals with either a preexisting condition or prior therapy with anthracyclines are less common in children. Notable examples are monosomy 7 (-7), monosomy 5, and deletion 5q (-5/del5q), which cumulatively account for 2%–4% of cases of childhood AML and more than 10% of adult AML cases. Although specific genes in these chromosomal regions that contribute

to disease pathogenesis have not been identified, the presence of these alterations is associated with resistance to chemotherapy and extremely poor survival.26 Similar to the cytogenetic alterations, sequence variations also vary by age; the prevalence of commonly mutated genes is extremely low (o1%) in cases diagnosed early in life and rapidly increases in the first decade of life (Figure 2B). Similar age-associated variation in somatic mutations, namely in FLT3, NPM, and CEBPA, are the most prevalent and clinically relevant mutations in childhood AML but are not usually detected in the first year of life. However, with increasing age, the frequency of these mutations also increases to a level commensurate to that observed in adults.

NEXT-GENERATION SEQUENCING IN CHILDHOOD AML In the past decade, technological advances in sequencing of nucleic acids have revolutionized our ability to interrogate cancer genomes, culminating in whole-genome sequencing (WGS), whole-exome sequencing (WES), and transcriptome sequencing (RNA Seq). These approaches provide comprehensive coverage of the majority of the genome at a single base resolution of the genome, exome, or transcriptome, respectively. WGS, in addition to identifying sequence variations (SNVs and indels) provides additional layers of information, including structural alterations such as deletions, duplications, and inter- and intra-chromosomal junctions. Transcriptome sequencing provides sequence and fusion data, as well as mRNA expression levels that are not available by WGS. However, RNA Seq data are limited by their ability to identify genomic alterations that are expressed at the transcript level. For example, mutations that cause silencing of genes would not be detected. In addition, structural alterations such as segmental deletions or duplications are not easily detected by RNA Seq. As a result, complementary data provided by at least two sequencing methodologies, ie,

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WGS and RNA Seq, can provide the most comprehensive, current approach to interrogating cancer genomes. WES, by the virtue of limiting the sequencing to the coding sequence, provides a more rapid and cost-effective evaluation of somatic mutations in regions that are readily interpretable, namely, referenced genes. However, structural or expression data cannot be directly assessed by this methodology. Next-generation sequencing (NGS) technologies have rapidly transformed the genomic landscape in cancer by providing high-throughput, comprehensive genomic profiles in a large number of patients.27 Ley et al identified IDH1 and DNMT3A to be two highly prevalent, clinically significant somatic alterations in adult AML.28,29 Despite confirmation of the prevalence and clinical utility of these mutations in adult AML, these mutations appear to be rare or absent in childhood AML (Figure 4),30,31 highlighting the significant differences between AML in older and younger patients. More recent data from The Cancer Genome Atlas Research Network (TCGA) AML study demonstrated that 23 genes were significantly mutated in the studied cohort. Of the 23 genes, 14 are well-known mutations in AML that have also been well studied in childhood AML and, with the exception of a few (FLT3, NPM, WT1), have been shown to be rare events in childhood AML. The catalog of karyotypic subtypes observed in this adult study highlights the genomic differences one would expect between adult and pediatric AML. For example, MLL and CBF alterations accounted for only 15% of all studied cases, whereas they are present in nearly half of pediatric AML cases. Thus, differences in molecular profile between adult and pediatric patients most likely exist based on the patient distribution by karyotype. Based on the significant age-associated differences in somatic alteration in AML, a concerted effort has been devoted to the characterization of genomic and epigenomic profiles for the spectrum of childhood AML. Two such projects, the St. Jude/Washington University Pediatric Cancer Genome Project (PCGP) and COG/National Cancer Institute (NCI) Therapeutically Applicable Research to Generate Effective Treatments (TARGET) AML initiative have initiated comprehensive evaluations of the genomic landscape of childhood AML using currently available NGS approaches.32,33 Early data emerging from these studies have provided new biological insights, and the data will be available to bona fide researchers in the coming years to further investigate the molecular basis of childhood AML. Already new insights have emerged from these projects. Based on an analysis of RNA Seq, the St. Jude PCGP project evaluated the transcriptome profile of a subset of patients with megakaryocytic leukemia (French-AmericanBritish [FAB] stage M7), known to be associated with a poor outcome in children. This study identified a cryptic translocation between the CBFA2T3 and GLIS2 genes in nearly 30% of children with FAB M7 AML. They further

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demonstrated that the CBFA2T3-GLIS2 fusion provides enhanced self-renewal capacity in colony-forming assay and its presence is associated with adverse outcome in FAB M7 AML.34 Further investigation by Masetti et al confirmed these findings in an independent cohort of children with FAB M7 AML. The investigators further demonstrated that the translocations are not restricted to patients with megakaryocytic leukemia, including detection in patients with a normal classical karyotype form of childhood AML; the data also suggest that its presence could be associated with adverse outcome in patients with no other known risk factors, but further studies are required to confirm this preliminary finding.35 The COG/NCI-sponsored TARGET AML initiative is using WGS and RNA Seq to establish the genomic profile of childhood AML in a cohort of more than 200 children with AML. The study design also targets the genomic evolution of childhood AML from diagnosis to relapse in trios of specimens (diagnosis, remission, and relapse) from 100 patients. The pilot phase of TARGET AML initiative used WES to evaluate diagnostic and relapse specimens from 20 patients who lacked karyotypic high-risk features to identify somatic alterations that contribute to AML pathogenesis, as well as to study genomic evolution from diagnosis to relapse.33 In this study, of the 195 distinct nonsynonymous mutations present in 180 genes, mutations in six genes were detected in more than one patient, including ETV6, KIT, KRAS, and NRAS in two patients and TET2 or WT1 in three patients, suggesting that, as seen in adult AML, there may not be a set of highly recurrent mutations in childhood AML. Although the majority of the identified mutations had been previously described as somatic alterations in pediatric AML, subsequent frequency validation of somatic mutations in ETV6 showed the ETV6 mutations to be present in 6% of childhood AML cases and in less than 1% of adults with AML. In this study, the presence of ETV6 mutations, which were primarily observed in those without previously known risk factors, were highly associated with risk of relapse (P ¼ .004) and significantly worse survival (P ¼ .006).36 In addition to identification of the somatic mutations in AML at diagnosis, this study surveyed the genomic landscape at relapse compared to that seen at diagnosis, demonstrating significant clonal evolution from diagnosis to relapse, where nearly one third of total mutations identified at diagnosis persisted at relapse with acquisition of a myriad of new mutations at relapse, indicating significant genomic evolution of diagnostic clone en route to relapse. Further, a large number of diagnostic events, primarily minor and sub-clonal events resolved from diagnosis to relapse.33 These findings were in line with observations in eight matched diagnostic/ relapse pairs previously reported by Ley et al in adult AML using WGS, where they identified “founding” clones in the primary tumor that gained novel mutations evolving into the relapse clone.37 This observation indicates that in addition to the genomic alterations that may lead to

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Figure 4. Prevalence of somatic mutations in pediatric versus adult AML. Shaded area demonstrates absence of mutations in IDH1 and DNMT3A genes in pediatric AML.

disease evolution, additional events, whether genomic or epigenomic, may arise or be selected that may mediate resistance to therapy and emergence of new leukemic clones with a genomic profile distinct from that of diagnostic one.

Clinical Implications of Genomic Alterations in AML Until recently, cytogenetic alterations were the only means of risk identification in AML, where those with CBF-AML were shown to have a lower risk of relapse and those with monosomy -7 or -5/del5q were at high risk of failure. However, the majority of children with AML lack clinically informative karyotypes and are not amenable to risk stratification based solely on cytogenetic subgroups. More recently, somatic mutations in the FLT3, NPM, and CEBPA genes have been shown to correlate with outcome,11,22,25 and have already been incorporated into clinical practice. Cumulatively, clinically significant cytogenetic alterations or somatic mutations account for nearly 35% of AML cases in children, leaving the majority of

children with AML without a prognostic biomarker. Although other clinically significant mutations have been demonstrated in adult AML, such mutations are either not seen in childhood AML (IDH1, DNMT3A mutations)30,31 or are not independently prognostic (WT1 mutations).38 In those with AML without an informative genomic biomarker, response to therapy as defined by multidimensional flow cytometry (MDF) has been used to inform relapse risk.39,40 In the ongoing COG de novo AML trial, combination of diagnostic molecular risk factors with the postinduction response assessment by MDF has allowed risk assessment in all patients with AML, where those with informative molecular markers are assigned to the appropriate risk class and those without such markers (standard risk) are assigned based on the presence or absence of residual disease at the end of induction chemotherapy. Such an approach allows appropriate risk stratification for nearly all patients by creating a two-tier risk allocation system in which patients are assigned to either a high-risk (cyto/molecular high-risk or standard risk with minimal residual disease [MRD]) or low-risk (cyto/molecular low

Figure 5. Newly devised risk stratification for AML. (A) Overall disease-free survival for all patients. Incorporation of known cytogenetic and molecular risk factors creates a three- tier risk stratification schema (B), allocating 35% of patients to cyto/ molecular high risk (10%) or low risk (25%), while 65% of patients without informative cyto/molecular markers remain in the standard-risk group. Incorporation of disease assessment by MDF after the initial induction allows for identification of risk groups within the standard risk cohort, providing a two-tier risk stratification schema by combining the cyto/molecular and minimal residual disease (MRD) data (C).

Pediatric AML in the TOC risk or standard risk without MRD) arm (Figure 5). Emergence of novel biomarkers will allow refinement of the existing risk-based therapy schema, where those with either high risk of relapse or those with appropriate targets for directed therapy can be allocated to an alternate therapy to optimize outcome and minimize undue toxicity.

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CONCLUSIONS AML is a complex disease characterized by a wide spectrum of genomic and epigenomic alterations that interact to create a wide variety of different disease subtypes having significantly different outcomes. This level of heterogeneity has precluded uniform outcome given the uniform approach to AML therapy for all patients. Genomic alterations, whether karyotypic abnormalities or specific disease-associated mutations, provide a great deal of information for clinical decision-making. Until recently, genomic profiling only provided clinical prognostic information that led to therapy intensity modulation and with the exception of FLT3/ITD, there is a paucity of potential therapeutic targets. More comprehensive genomic profiling will not only lead to new tools for risk identification but also may define lesions that may provide targets for more personalized and directed therapy. This may obviate the need for highly intensive, cytotoxic therapies with their short- and long-term side effects. New discovery phase initiatives, the including NCI-sponsored TARGET AML initiative, are aimed at discovering novel biomarkers to be used for more precise risk identification, as well as to identify potential therapeutic targets. With the increase in the number of tools for interrogation of AML genome and epigenome, the ability to allocate patients to individualized therapy directed by the underlying biology of their disease is anticipated. We are emerging from one the most exciting eras in cancer biology, where NGS has provided the tools for comprehensive interrogation of the cancer genome, whose data will be mined for years to come to identify new biomarkers for risk and target identification for more appropriate risk- and target-based therapeutic interventions and to make “personalized medicine.”

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