Abstract
Acute megakaryoblastic leukemia (AMKL) is a subtype of acute myeloid leukemia (AML) in which cells morphologically resemble abnormal megakaryoblasts. While rare in adults, AMKL accounts for 4–15% of newly diagnosed childhood AML cases1,2,3. AMKL in individuals without Down syndrome (non-DS-AMKL) is frequently associated with poor clinical outcomes. Previous efforts have identified chimeric oncogenes in a substantial number of non-DS-AMKL cases, including RBM15-MKL1, CBFA2T3-GLIS2, KMT2A gene rearrangements, and NUP98-KDM5A4,5,6. However, the etiology of 30–40% of cases remains unknown. To better understand the genomic landscape of non-DS-AMKL, we performed RNA and exome sequencing on specimens from 99 patients (75 pediatric and 24 adult). We demonstrate that pediatric non-DS-AMKL is a heterogeneous malignancy that can be divided into seven subgroups with varying outcomes. These subgroups are characterized by chimeric oncogenes with cooperating mutations in epigenetic and kinase signaling genes. Overall, these data shed light on the etiology of AMKL and provide useful information for the tailoring of treatment.
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Acknowledgements
We thank all the patients and their parents who allowed their leukemic samples to be stored and studied. We thank the Tissue Resources Laboratory, the Flow Cytometry and Cell Sorting Core, and the Clinical Applications of Core Technology Laboratories of the Hartwell Center for Bioinformatics and Biotechnology of St. Jude Children's Research Hospital. J.D.E.d.R. was funded by Stichting Kinderoncologisch Centrum Rotterdam (KOCR). A.O. and L.J.V. were funded by KIKA (Children Cancer-Free Foundation). M.F. was supported by the Dutch Cancer Society (KWF). F.L. was supported by the Italian Association for Research on Cancer (Associazione Italiana Ricerca sul Cancro; Special Grant “5xmille”-9962). This work was funded by the St. Jude Children's Research Hospital–Washington University Pediatric Cancer Genome Project, the American Lebanese and Syrian Associated Charities of St. Jude Children's Research Hospital, and the Eric Trump Foundation.
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T.A.G. and M.F. designed all experiments. J.C., H.L.M., and J.E. constructed libraries and sequenced samples. J.M. led the sequencing analysis. J.M., Y.L., M.P.W., M.R., G.S., A.O., M.F., M.E., P.G., and J.Z. performed computational data analyses. J.D.E.d.R., C.B., and L.J.V. performed validation experiments. C.B., J.M., and T.A.G. manually filtered SNV and indel calls on unpaired samples. C.K. and J.D. performed functional work on the HOX fusions. J.D.E.d.R., M.Z., and M.F. performed outcome analysis. J.Y.S.L., K.R., M.P., A.E.J.Y., L.-Y.S., D.-C.L., S.H., D.S.K., F.L., D.R., M.M.v.d.H.-E., C.M.Z., and T.A.G. provided annotated patient samples. J.D.E.d.R., C.B., J.R.D., F.L., D.R., M.M.v.d.H.-E., and C.M.Z. performed critical reading and contributed to the writing of the manuscript. M.F. and T.A.G. wrote the manuscript.
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Integrated supplementary information
Supplementary Figure 1 HOX fusions enhance self-renewal capacity.
Mouse bone marrow was transduced with a retrovirus carrying one of three HOX fusion genes or the empty mCherry reporter construct as described in Online Methods. (a) At 1-week intervals, colonies were counted and cells were replated in duplicate for a total of four platings. Each bar donates colony counts for a replating round. Error bars indicate standard error of the mean. Data are compiled from two separate experiments with similar results. (b) Flow cytometry of colonies. Data shown are from one of two experiments with similar results.
Supplementary Figure 2 HOX rearranged subgroup gene expression signatures.
(a) HOX fusion partner genes are upregulated in HOX rearranged cases. Relative HOX gene expression values (row percentiles) are indicated by heat color (color key). Genes are ordered by chromosomal position. Arrows indicate direction of transcription of protein-coding HOX genes. Fusion genes are divided by coding (top) and non-coding HOX fusions and ordered by HOX fusion partner. Right column summarizes the expression value of the HOX gene involved in the rearrangement. (b) HOXA9 target genes are upregulated in the HOX rearranged subgroup. Distribution of expression of genes within the HOXA9 target upregulated gene set showing the highest association with AMKL subgroup10. Expression is highest in the HOX rearranged cases for both protein coding and non-protein coding HOX fusions (red circles).
Supplementary Figure 3 Genomic driver mutations in adult AMKL.
Recurrently mutated genes in the adult cohort as determined by whole exome sequencing, copy number alterations, and cytogenetics (see Supplementary Tables 7 and 8 for detailed information on each mutation).
Supplementary Figure 4 Genomic driver mutations in pediatric AMKL.
Recurrently mutated genes in the pediatric cohort as determined by whole exome sequencing, copy number alterations, and cytogenetics (see Supplementary Tables 6 and 8 for detailed information on each mutation).
Supplementary Figure 5 Down syndrome AML and chromosome 21 gene expression patterns.
(a) GATA1 mutant non-DS-AMKL and DS-AML gene expression patterns correlate. Scatterplots of relative gene expression values (log2 ratios) of differentially expressed genes in DS-AML compared to non-DS AML (y-axes) and those of the different non-DS AMKL subgroups relative to the other groups combined (x-axes). Spearman correlation coefficients of comparisons are shown to the right. (b) Chromosome 21 expression levels. Relative expression of genes on chromosome 21 in the AMKL subgroups is shown. Genomic amplification status for each sample is indicated by the circles. Filled circles, amplified chromosome 21; open circles, chromosome 21 status not analyzed/unknown.
Supplementary Figure 6 RB1 expression levels.
RB1 expression levels as determined by RNA-seq are shown for NUP98-KDM5A specimens vs. others.
Supplementary Figure 7 Cooperation of MPL mutations and HOX rearrangements.
Murine bone marrow was co-transduced with a retrovirus carrying a HOX fusion gene and an MPL gene in the following combinations: mCherry (MIC)+GFP(MIG); MIC+MPL wild type (MPLwt); MIC+MPL S505N mutant (MPLS505N); MIC+MPL W515L mutant (MPLW515L); GATA2-HOXA9+MIG; GATA2-HOXA9+MPLwt; GATA2-HOXA9+MPLS505N; GATA2-HOXA9+MPLW515L; NIPBL-HOXB9+MIG; NIPBL-HOXB9+MPLwt; NIPBL-HOXB9+MPLS505N; NIPBL-HOXB9+MPLW515L. Double-positive transduced cells were flow sorted using mCherry and GFP markers. (a) MPL mutations do not enhance self-renewal. Sorted cells were grown on methylcellulose supplemented with cytokines. At 1-week intervals, colonies were counted and cells were replated for a total of three platings. Each bar donates colony counts for a replating round. Error bars indicate standard error of the mean. Data are compiled from two separate experiments with similar results. (b) MPL mutations enhance cytokine-independent growth. 5 x 105 cells from the third CFU plating were removed and placed in liquid culture in the absence of cytokines in triplicate. Viable cells were counted daily for one week. Error bars indicate standard error of the mean. Data shown are from one of two experiments with similar results.
Supplementary Figure 8 MPL mutations enhance JAK2 signaling.
Colonies from the third plating as described in Supplementary Figure 7 were removed and placed in liquid culture in the absence of cytokines. After 48 hours of growth, cells were harvested and subjected to western blot analysis. The ratio of phosphorylated JAK2 to total JAK2 protein as determined by densitometry and phosphorylated STAT5 to total STAT5 protein are shown below. Data shown are from one of two experiments with similar results.
Supplementary Figure 9 Non-DS-AMKL subgroups correlate with outcome.
(a-c) Comparison of event free survival (a), overall survival (b), and cumulative incidence of relapse or non-response (c) across AMKL subgroups. Each group was tested against the other groups combined. P values were determined by log-rank tests from either Cox proportional hazards regression models (a,b) or Gray's K-sample tests (c). All P values for competing risk differences were > 0.25.
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de Rooij, J., Branstetter, C., Ma, J. et al. Pediatric non–Down syndrome acute megakaryoblastic leukemia is characterized by distinct genomic subsets with varying outcomes. Nat Genet 49, 451–456 (2017). https://doi.org/10.1038/ng.3772
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DOI: https://doi.org/10.1038/ng.3772
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