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Acute myeloid leukemias (AML) are characterized by mutations of tumor suppressor and oncogenes, involving distinct genes in adults and children. While certain mutations have been associated with the increased risk of AML relapse, the genomic landscape of primary chemotherapy-resistant AML is not well defined. As part of the TARGET initiative, we performed whole-genome DNA and transcriptome RNA and miRNA sequencing analysis of pediatric AML with failure of induction chemotherapy. We identified at least three genetic groups of patients with induction failure, including those with NUP98 rearrangements, somatic mutations of WT1 in the absence of apparent NUP98 mutations, and additional recurrent variants including those in KMT2C and MLLT10 . Comparison of specimens before and after chemotherapy revealed distinct and invariant gene expression programs. While exhibiting overt therapy resistance, these leukemias nonetheless showed diverse forms of clonal evolution upon chemotherapy exposure. This included selection for mutant alleles of FRMD8 , DHX32 , PIK3R1 , SHANK3 , MKLN1 , as well as persistence of WT1 and TP53 mutant clones, and elimination of FLT3 , PTPN11 , and NRAS mutant clones. These findings delineate genetic mechanisms of primary chemotherapy resistance in pediatric AML, which should inform improved approaches for its diagnosis and therapy.

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach. Relapsed pediatric acute myeloid leukemia is associated with poor prognosis. Here, the authors use RNA-seq data from 1503 primary samples to create a combined transcriptional and cytomolecular signature to improve relapse risk prediction.

Oncogenic fusions formed through chromosomal rearrangements are hallmarks of childhood cancer that define cancer subtype, predict outcome, persist through treatment, and can be ideal therapeutic targets. However, mechanistic understanding of the etiology of oncogenic fusions remains elusive. Here we report a comprehensive detection of 272 oncogenic fusion gene pairs by using tumor transcriptome sequencing data from 5190 childhood cancer patients. We identify diverse factors, including translation frame, protein domain, splicing, and gene length, that shape the formation of oncogenic fusions. Our mathematical modeling reveals a strong link between differential selection pressure and clinical outcome in CBFB - MYH11 . We discover 4 oncogenic fusions, including RUNX1 - RUNX1T1 , TCF3 - PBX1 , CBFA2T3 - GLIS2 , and KMT2A - AFDN , with promoter-hijacking-like features that may offer alternative strategies for therapeutic targeting. We uncover extensive alternative splicing in oncogenic fusions including KMT2A - MLLT3 , KMT2A - MLLT10 , C11orf95 - RELA , NUP98 - NSD1 , KMT2A - AFDN and ETV6 - RUNX1 . We discover neo splice sites in 18 oncogenic fusion gene pairs and demonstrate that such splice sites confer therapeutic vulnerability for etiology-based genome editing. Our study reveals general principles on the etiology of oncogenic fusions in childhood cancer and suggests profound clinical implications including etiology-based risk stratification and genome-editing-based therapeutics. Oncogenic gene fusions are frequent in childhood cancers but remain poorly understood and untargeted. Here, the authors identify 272 oncogenic fusions in transcriptomics data from 5190 childhood cancer patients, revealing their possible etiologies, their links with tumor progression and evolution, and their potential as therapeutic targets.

High levels of the inflammatory cytokine IL-6 in the bone marrow are associated with poor outcomes in pediatric acute myeloid leukemia (pAML), but its etiology remains unknown. Using RNA-seq data from pre-treatment bone marrows of 1489 children with pAML, we show that > 20% of patients have concurrent IL-6, IL-1, IFNα/β, and TNFα signaling activity and poorer outcomes. Targeted sequencing of pre-treatment bone marrow samples from affected patients ( n  = 181) revealed 5 highly recurrent patterns of somatic mutation. Using differential expression analyses of the most common genomic subtypes (~60% of total), we identify high expression of multiple potential drivers of inflammation-related treatment resistance. Regardless of genomic subtype, we show that JAK1/2 inhibition reduces receptor-mediated inflammatory signaling by leukemic cells in-vitro. The large number of high-risk pAML genomic subtypes presents an obstacle to the development of mutation-specific therapies. Our findings suggest that therapies targeting inflammatory signaling may be effective across multiple genomic subtypes of pAML. IL6 expression in the bone marrow is associated with reduced survival in paediatric AML. Here, the authors used RNA-seq to identify treatment resistance-associated co-occurring inflammatory signalling in leukemic cells.

Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and posttranscriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways; up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms; and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T- and B-cell activation, and NF-κB signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors. Significance An important goal of cancer biology is to identify molecular differences between normal and cancer cells. Accordingly, many large-scale initiatives to characterize both solid and liquid tumor samples with genomics technologies are currently underway. Here, we show that standard blood collection procedures cause rapid changes to the transcriptomes of hematopoietic cells. The resulting transcriptional and posttranscriptional artifacts are visible in most published leukemia genomics datasets and hinder the identification and interpretation of cancer-specific alterations.

Acute Myeloid Leukemia (AML) develops due to the acquisition of mutations from multiple functional classes. Here, we demonstrate that activating mutations in the granulocyte colony stimulating factor receptor (CSF3R), cooperate with loss of function mutations in the transcription factor CEBPA to promote acute leukemia development. The interaction between these distinct classes of mutations occurs at the level of myeloid lineage enhancers where mutant CEBPA prevents activation of a subset of differentiation associated enhancers. To confirm this enhancer-dependent mechanism, we demonstrate that CEBPA mutations must occur as the initial event in AML initiation. This improved mechanistic understanding will facilitate therapeutic development targeting the intersection of oncogene cooperativity. Acute Myeloid Leukemia (AML) develops following multiple mutations of differing impact. Here, the authors show that activating mutations of CSF3R co-operate with loss-of-function mutations of CEBPA to promote AML development through an enhancer-dependent mechanism.

The t(8;21) and Inv(16) translocations disrupt the normal function of core binding factors alpha (CBFA) and beta (CBFB), respectively. These translocations represent two of the most common genomic abnormalities in acute myeloid leukemia (AML) patients, occurring in approximately 25% pediatric and 15% of adult with this malignancy. Both translocations are associated with favorable clinical outcomes after intensive chemotherapy, and given the perceived mechanistic similarities, patients with these translocations are frequently referred to as having CBF-AML. It remains uncertain as to whether, collectively, these translocations are mechanistically the same or impact different pathways in subtle ways that have both biological and clinical significance. Therefore, we used transcriptome sequencing (RNA-seq) to investigate the similarities and differences in genes and pathways between these subtypes of pediatric AMLs. Diagnostic RNA from patients with t(8;21) (N = 17), Inv(16) (N = 14), and normal karyotype (NK, N = 33) were subjected to RNA-seq. Analyses compared the transcriptomes across these three cytogenetic subtypes, using the NK cohort as the control. A total of 1291 genes in t(8;21) and 474 genes in Inv(16) were differentially expressed relative to the NK controls, with 198 genes differentially expressed in both subtypes. The majority of these genes (175/198; binomial test p-value < 10(-30)) are consistent in expression changes among the two subtypes suggesting the expression profiles are more similar between the CBF cohorts than in the NK cohort. Our analysis also revealed alternative splicing events (ASEs) differentially expressed across subtypes, with 337 t(8;21)-specific and 407 Inv(16)-specific ASEs detected, the majority of which were acetylated proteins (p = 1.5 x 10(-51) and p = 1.8 x 10(-54) for the two subsets). In addition to known fusions, we identified and verified 16 de novo fusions in 43 patients, including three fusions involving NUP98 in six patients. Clustering of differentially expressed genes indicated that the homeobox (HOX) gene family, including two transcription factors (MEIS1 and NKX2-3) were down-regulated in CBF compared to NK samples. This finding supports existing data that the dysregulation of HOX genes play a central role in biology CBF-AML hematopoiesis. These data provide comprehensive transcriptome profiling of CBF-AML and delineate genes and pathways that are differentially expressed, providing insights into the shared biology as well as differences in the two CBF subsets.

Cytogenetic analysis of acute myeloid leukemia (AML) cells has accelerated the identification of genes important for AML pathogenesis. To complement cytogenetic studies and to identify genes altered in AML genomes, we performed genome-wide copy number analysis with paired normal and tumor DNA obtained from 86 adult patients with de novo AML using 1.85 million feature SNP arrays. Acquired copy number alterations (CNAs) were confirmed using an ultra-dense array comparative genomic hybridization platform. A total of 201 somatic CNAs were found in the 86 AML genomes (mean, 2.34 CNAs per genome), with French-American-British system M6 and M7 genomes containing the most changes (10-29 CNAs per genome). Twenty-four percent of AML patients with normal cytogenetics had CNA, whereas 40% of patients with an abnormal karyotype had additional CNA detected by SNP array, and several CNA regions were recurrent. The mRNA expression levels of 57 genes were significantly altered in 27 of 50 recurrent CNA regions <5 megabases in size. A total of 8 uniparental disomy (UPD) segments were identified in the 86 genomes; 6 of 8 UPD calls occurred in samples with a normal karyotype. Collectively, 34 of 86 AML genomes (40%) contained alterations not found with cytogenetics, and 98% of these regions contained genes. Of 86 genomes, 43 (50%) had no CNA or UPD at this level of resolution. In this study of 86 adult AML genomes, the use of an unbiased high-resolution genomic screen identified many genes not previously implicated in AML that may be relevant for pathogenesis, along with many known oncogenes and tumor suppressor genes.

Pediatric acute myeloid leukemia (AML) is an aggressive blood cancer with a poor prognosis and high relapse rate. Current challenges in the identification of immunotherapy targets arise from patient-specific blast immunophenotypes and their change during disease progression. To overcome this, we present a new computational research tool to rapidly identify malignant cells. We generated single-cell flow cytometry profiles of 21 pediatric AML patients with matched samples at diagnosis, remission, and relapse. We coupled a classifier to an autoencoder for anomaly detection and classified malignant blasts with 90% accuracy. Moreover, our method assigns a developmental stage to blasts at the single-cell level, improving current classification approaches based on differentiation of the dominant phenotype. We observed major immunophenotype and developmental stage alterations between diagnosis and relapse. Patients with KMT2A rearrangement had more profound changes in their blast immunophenotypes at relapse compared to patients with other molecular features. Our method provides new insights into the immunophenotypic composition of AML blasts in an unbiased fashion and can help to define immunotherapy targets that might improve personalized AML treatment.