DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA methylation as a complement to current diagnostic methods. A secondary aim was to gain insight into the functional role of DNA methylation in ALL.We used the methylation status of ~450,000 CpG sites in 546 well-characterized patients with T-ALL or seven recurrent B-cell precursor ALL subtypes to design and validate sensitive and accurate DNA methylation classifiers. After repeated cross-validation, a final classifier was derived that consisted of only 246 CpG sites. The mean sensitivity and specificity of the classifier across the known subtypes was 0.90 and 0.99, respectively. We then used DNA methylation classification to screen for subtype membership of 210 patients with undefined karyotype (normal or no result) or non-recurrent cytogenetic aberrations ('other' subtype). Nearly half (n = 106) of the patients lacking cytogenetic subgrouping displayed highly similar methylation profiles as the patients in the known recurrent groups. We verified the subtype of 20% of the newly classified patients by examination of diagnostic karyotypes, array-based copy number analysis, and detection of fusion genes by quantitative polymerase chain reaction (PCR) and RNA-sequencing (RNA-seq). Using RNA-seq data from ALL patients where cytogenetic subtype and DNA methylation classification did not agree, we discovered several novel fusion genes involving ETV6, RUNX1, and PAX5.Our findings indicate that DNA methylation profiling contributes to the clarification of the heterogeneity in cytogenetically undefined ALL patient groups and could be implemented as a complementary method for diagnosis of ALL. The results of our study provide clues to the origin and development of leukemic transformation. The methylation status of the CpG sites constituting the classifiers also highlight relevant biological characteristics in otherwise unclassified ALL patients.Swedish Foundation for Strategic Research RBc08-008 Swedish Cancer Society CAN2010/592 Swedish Childhood Cancer Foundation 11098 Swedish Research Council for Science and Technology 90559401 Swedish Research Council FORTE Swedish Research Council FORMAS Swedish Research Council VINNOVA Swedish Research Council VR 259-2012-2

DNA Methylation Analysis of Bone Marrow Cells at Diagnosis of Acute Lymphoblastic Leukemia and at Remission

To detect genes with CpG sites that display methylation patterns that are characteristic of acute lymphoblastic leukemia (ALL) cells, we compared the methylation patterns of cells taken at diagnosis from 20 patients with pediatric ALL to the methylation patterns in mononuclear cells from bone marrow of the same patients during remission and in non-leukemic control cells from bone marrow or blood. Using a custom-designed assay, we measured the methylation levels of 1,320 CpG sites in regulatory regions of 413 genes that were analyzed because they display allele-specific gene expression (ASE) in ALL cells. The rationale for our selection of CpG sites was that ASE could be the result of allele-specific methylation in the promoter regions of the genes. We found that the ALL cells had methylation profiles that allowed distinction between ALL cells and control cells. Using stringent criteria for calling differential methylation, we identified 28 CpG sites in 24 genes with recurrent differences in their methylation levels between ALL cells and control cells. Twenty of the differentially methylated genes were hypermethylated in the ALL cells, and as many as nine of them (AMICA1, CPNE7, CR1, DBC1, EYA4, LGALS8, RYR3, UQCRFS1, WDR35) have functions in cell signaling and/or apoptosis. The methylation levels of a subset of the genes were consistent with an inverse relationship with the mRNA expression levels in a large number of ALL cells from published data sets, supporting a potential biological effect of the methylation signatures and their application for diagnostic purposes

Correlation matrix and variability of the methylation levels measured at 1,320 CpG sites across the 63 samples included in the study.

<p>(A) Each individual sample is indicated by a black line on the axes. The methylation levels in the samples taken at remission during induction therapy at day 29 and during consolidation therapy at days 50 and 106 are highly correlated with the methylation levels in the non-leukemic samples (median Pearson's correlation coefficient (<i>R</i>) = 0.96), while the diagnostic ALL samples are less similar both to each other and to the samples taken after treatment, and to the non-leukemic samples (median <i>R</i> = 0.83). The scale for the correlation coefficients is shown to the right of the matrix. The red color indicates higher correlation (greater similarity), while the light yellow indicates less correlation (less similarity). (B) Histograms of the standard deviations (SD) for the methylation levels measured for 1,320 CpG sites across 20 ALL samples (blue) and across the combined 33 remission samples and 13 non-leukemic controls (red). SD bins are shown on the horizontal axis. The vertical bars show the proportion of observations in each SD bin. The CpG sites show greater variability in the ALL samples than in the remission samples and non-leukemic controls (Wilcoxon Rank-Sum P<0.001).</p

CopyNumber450kCancer : baseline correction for accurate copy number calling from the 450k methylation array

The Illumina Infinium HumanMethylation450 BeadChip (450k) is widely used for the evaluation of DNA methylation levels in large-scale datasets, particularly in cancer. The 450k design allows copy number variant (CNV) calling using existing bioinformatics tools. However, in cancer samples, numerous large-scale aberrations cause shifting in the probe intensities and thereby may result in erroneous CNV calling. Therefore, a baseline correction process is needed. We suggest the maximum peak of probe segment density to correct the shift in the intensities in cancer samples

Differential methylation in ALL cells.

<p>(A) Heatmap of the methylation profiles of the 28 CpG sites that are differentially methylated between the diagnostic ALL samples, bone marrow cells at remission and non-leukemic bone marrow cells. The ALL samples (orange) and bone marrow cells during remission (blue) form two distinct groups. Thirteen bone marrow cell samples from non-leukemic controls (purple) cluster among the samples collected during remission. The scale for the methylation β-values is shown below the heatmap. The elongated heights of the dendrogram branches between the ALL samples compared to the normal samples illustrate the increased variability in the ALL samples for the 28 CpG sites. Graphs showing the differences in methylation level between CpG sites in the (B) <i>WDR35</i> and (C) <i>FXYD2</i> genes at the time of diagnosis (left vertical axis) and during remission (right vertical axis). The data points for each paired sample are connected with a red line for B-cell precursor (BCP) samples and with a blue line for T-ALL samples. The corresponding CpG methylation levels in 13 non-leukemic control samples are shown as black horizontal lines to the right of the graphs. The CpG site at chr2:20,052,748 in the <i>WDR35</i> gene (B) was hypermethylated in diagnostic ALL samples and hypomethylated at remission and in non-leukemic controls, while the CpG site at chr11:7,203,745 in the <i>FXYD2</i> gene (C) displayed the opposite pattern. The BCP and T-ALL samples display the same pattern of methylation difference in these two genes.</p

Clinical information for the 20 patients with acute lymphoblastic leukemia and 13 controls included in the study.

<p>BCP indicates B-cell precursor ALL; T-ALL, T-cell ALL; HeH, high hyperdiploidy; amp(21), amplification of chr 21; HR, high risk; SR, standard risk; IR, intermediate risk; NA, not available.</p>a<p>White blood cell count at diagnosis (10⁹/L).</p>b<p>The NOPHO ALL 2000 protocol was used.</p>c<p>DNA from was available from bone marrow taken from the patients on day 29,50, and/or 106 after the initiation of therapy, all patients were in morphological remission with less than 5% leukemic blasts.</p

RAG1 co-expression signature identifies ETV6-RUNX1-like B-cell precursor acute lymphoblastic leukemia in children

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) can be classified into subtypes according to the genetic aberrations they display. For instance, the translocation t(12;21)(p13;q22), representing the ETV6-RUNX1 fusion gene (ER), is present in a quarter of BCP-ALL cases. However, around 10% of the cases lack classifying chromosomal abnormalities (B-other). In pediatric ER BCP-ALL, rearrangement mediated by RAG (recombination-activating genes) has been proposed as the predominant driver of oncogenic rearrangement. Herein we analyzed almost 1600 pediatric BCP-ALL samples to determine which subtypes express RAG. We demonstrate that RAG1 mRNA levels are especially high in the ETV6-RUNX1 (ER) subtype and in a subset of B-other samples. We also define 31 genes that are co-expressed with RAG1 (RAG1-signature) in the ER subtype, a signature that also identifies this subset of B-other samples. Moreover, this subset also shares leukemia and pro-B gene expression signatures as well as high levels of the ETV6 target genes (BIRC7, WBP1L, CLIC5, ANGPTL2) with the ER subtype, indicating that these B-other cases are the recently identified ER-like subtype. We validated our results in a cohort where ER-like has been defined, which confirmed expression of the RAG1-signature in this recently described subtype. Taken together, our results demonstrate that the RAG1-signature identifies the ER-like subtype. As there are no definitive genetic markers to identify this novel subtype, the RAG1-signature represents a means to screen for this leukemia in children

Correlation between the methylation levels (β-values) of two CpG sites located in the <i>COL6A2</i>, <i>EYA4</i>, <i>FXYD2</i> and <i>MYO3A</i> genes.

<p>The Pearson's correlation coefficients (<i>R</i>) across the 20 acute lymphoblastic leukemia (ALL) samples taken at ALL diagnosis (green) and the 20 matched bone marrow samples taken at remission (blue) for the four genes are shown in panels A–D. The positions of the CpG sites for which the β-values are plotted are indicated on the axes in each panel (Human Genome Build 36). The inter-individual variation between the pairs of CpG sites in the remission cells is consistently lower than between the ALL cells, which speaks against the variation in ALL cells arising because of methodological factors.</p