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. 2019 Oct;110(10):3358-3367.
doi: 10.1111/cas.14160. Epub 2019 Sep 10.

Integrated genetic and epigenetic analysis revealed heterogeneity of acute lymphoblastic leukemia in Down syndrome

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Integrated genetic and epigenetic analysis revealed heterogeneity of acute lymphoblastic leukemia in Down syndrome

Yasuo Kubota et al. Cancer Sci. 2019 Oct.

Abstract

Children with Down syndrome (DS) are at a 20-fold increased risk for acute lymphoblastic leukemia (ALL). Compared to children with ALL and no DS (non-DS-ALL), those with DS and ALL (DS-ALL) harbor uncommon genetic alterations, suggesting DS-ALL could have distinct biological features. Recent studies have implicated several genes on chromosome 21 in DS-ALL, but the precise mechanisms predisposing children with DS to ALL remain unknown. Our integrated genetic/epigenetic analysis revealed that DS-ALL was highly heterogeneous with many subtypes. Although each subtype had genetic/epigenetic profiles similar to those found in non-DS-ALL, the subtype distribution differed significantly between groups. The Philadelphia chromosome-like subtype, a high-risk B-cell lineage variant relatively rare among the entire pediatric ALL population, was the most common form in DS-ALL. Hypermethylation of RUNX1 on chromosome 21 was also found in DS-ALL, but not non-DS-ALL. RUNX1 is essential for differentiation of blood cells, especially B cells; thus, hypermethylation of the RUNX1 promoter in B-cell precursors might be associated with increased incidence of B-cell precursor ALL in DS patients.

Keywords: Down syndrome; acute lymphoblastic leukemia; children; epigenetic analysis; genetic analysis.

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Figures

Figure 1
Figure 1
Gene expression clusters in 143 samples of B‐cell precursor acute lymphoblastic leukemia (BCPALL) (25 samples from children with Down syndrome and ALL [DSALL] and 118 non‐DSALL samples) on hierarchical clustering. Hierarchical clustering reveals BCPALL samples are grouped into 6 clusters (E1‐E6). In those 6 clusters, DSALL samples are clustered into 4 clusters. Expression clusters, DSALL samples, subtypes, and genetic aberrations are shown by colors as indicated. DSALL and non‐DSALL are clustered into the same cluster corresponding to each biological subtype. Philadelphia chromosome (Ph)‐like signature is confirmed by recognition of outliers by sampling ends (ROSE) gene set clustering. HeH, high hyperdiploid
Figure 2
Figure 2
DNA methylation clusters in 723 B‐cell precursor acute lymphoblastic leukemia (BCPALL) samples on consensus unsupervised clustering. Consensus unsupervised clustering suggests 723 BCPALL samples are grouped into 5 clusters (M1‐M5). Clusters, cohorts, Down syndrome (DS)‐ALL samples, and subtypes are shown by colors as indicated. Methylation clusters M3 and M5 are heterogeneous clusters, which are reclustered into 5 and 6 clusters, respectively. As shown in the expression analysis, DSALL and non‐DSALL are clustered into the same cluster corresponding to each biological subtype. HeH, high hyperdiploid; NOPHO, Nordic Society for Pediatric Hematology and Oncology; Ph, Philadelphia chromosome
Figure 3
Figure 3
Methylation of RUNX1 promoter. A, Volcano plot comparing significant delta beta values between samples from children with Down syndrome and acute lymphoblastic leukemia (DSALL) and non‐DSALL samples. Significant probes showing the delta beta value greater than .2 or less than −.2, and −log10 (q value) greater than 10 are colored red. Among these probes, probes of promoter regions of RUNX1 are colored blue and significantly highly methylated in DSALL. q Values are calculated using the Wilcoxon rank‐sum test adjusted by the Benjamini‐Hochberg correction. B, Box plot comparing beta values of the most significant probe of RUNX1 promoter (cg22698744) in ALL samples (n = 723), CD19+ cells of fetuses (n = 16), CD34+ CD19 cells of fetuses (n = 6) and CD19+ cells of adults (n = 3), and CD19+ cells of DSALL samples in remission (n = 2). In normal samples, CD19+ cells of adults and DSALL samples in remission are highly methylated compared to fetal cells. q Values are calculated using the Wilcoxon rank‐sum test adjusted by the Benjamini‐Hochberg correction. BM, bone marrow
Figure 4
Figure 4
Relations of gene expression, DNA methylation, and genomic status. A, Mutational and copy number analysis in expression clusters (E1‐E6). Clusters, samples from children with Down syndrome and acute lymphoblastic leukemia (DSALL), subtypes, and genetic aberrations are shown by different colors as indicated. Copy number analysis of IKZF1 and PAX5 are represented in only DSALL samples. DSALL sample in E3 had PAX5 amplification. Samples with PAX5 alteration are clustered into E3 or E6. DSALL sample without ETV6‐RUNX1 has deletion of ETV6, implicating ETV6‐RUNX1‐like signature. All samples with JAK2 mutation and CRLF2 fusion, including DSALL samples, reveal Philadelphia chromosome (Ph)‐like signature. In contrast, mutations of RAS pathway genes are detected in several subtypes. B, Results of DNA methylation analysis are combined with results of mutational and copy number analyses. Copy number analyses of IKZF1 and PAX5 are represented in only DSALL samples. Samples with Ph‐like signature are divided into M3 and M5 clusters. Ph‐like samples in M3 and M5 are clustered in BCRABL1 and iAMP21 cluster, respectively. HeH, high hyperdiploid
Figure 5
Figure 5
Genetic landscape of Down syndrome and acute lymphoblastic leukemia (DSALL). A, Genetic landscape of DSALL combined with clinical information. The NCI criteria (standard risk [SR] or high risk [HR]), sex, and outcomes (alive or dead) together with subtypes, the affected genes, and the types of genomic aberrations are shown by colors as indicated. IKZF1plus was defined as IKZF1 deletions co‐occurring with deletions in CDKN2A,CDKN2B,PAX5, or PAR1 in the absence of ERG deletion. We detected Ph‐like, ETV6‐RUNX1‐like, PAX5 alteration, IGHCEBPA fusion, and IGHCEBPD fusion in addition to known subtypes such as ETV6‐RUNX1, high hyperdiploid, dic(9;20), TCF3‐PBX1, and BCRABL1. Samples are ordered by biological subtypes. B, The relation between mutational status and biological subtypes in DSALL samples. The upper half of this figure shows already known genetic alterations in DSALL; the lower half shows subtypes of ALL detected by our analysis. All samples with JAK2 mutations and CRLF2 fusions have the Philadelphia chromosome (Ph)‐like signature. In contrast, several subtypes of DSALL have mutations of RAS pathway genes

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