Refining risk prediction in pediatric acute lymphoblastic leukemia through DNA methylation profiling.

Acute lymphoblastic leukemia (ALL) is the most prevalent cancer in children, and despite considerable progress in treatment outcomes, relapses still pose significant risks of mortality and long-term complications. To address this challenge, we employed a supervised machine learning technique, specifically random survival forests, to predict the risk of relapse and mortality using array-based DNA methylation data from a cohort of 763 pediatric ALL patients treated in Nordic countries. The relapse risk predictor (RRP) was constructed based on 16 CpG sites, demonstrating c-indexes of 0.667 and 0.677 in the training and test sets, respectively. The mortality risk predictor (MRP), comprising 53 CpG sites, exhibited c-indexes of 0.751 and 0.754 in the training and test sets, respectively. To validate the prognostic value of the predictors, we further analyzed two independent cohorts of Canadian (n = 42) and Nordic (n = 384) ALL patients. The external validation confirmed our findings, with the RRP achieving a c-index of 0.667 in the Canadian cohort, and the RRP and MRP achieving c-indexes of 0.529 and 0.621, respectively, in an independent Nordic cohort. The precision of the RRP and MRP models improved when incorporating traditional risk group data, underscoring the potential for synergistic integration of clinical prognostic factors. The MRP model also enabled the definition of a risk group with high rates of relapse and mortality. Our results demonstrate the potential of DNA methylation as a prognostic factor and a tool to refine risk stratification in pediatric ALL. This may lead to personalized treatment strategies based on epigenetic profiling.

Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia.

Genomic analyses have redefined the molecular subgrouping of pediatric acute lymphoblastic leukemia (ALL). Molecular subgroups guide risk-stratification and targeted therapies, but outcomes of recently identified subtypes are often unclear, owing to limited cases with comprehensive profiling and cross-protocol studies. We developed a machine learning tool (ALLIUM) for the molecular subclassification of ALL in retrospective cohorts as well as for up-front diagnostics. ALLIUM uses DNA methylation and gene expression data from 1131 Nordic ALL patients to predict 17 ALL subtypes with high accuracy. ALLIUM was used to revise and verify the molecular subtype of 281 B-cell precursor ALL (BCP-ALL) cases with previously undefined molecular phenotype, resulting in a single revised subtype for 81.5% of these cases. Our study shows the power of combining DNA methylation and gene expression data for resolving ALL subtypes and provides a comprehensive population-based retrospective cohort study of molecular subtype frequencies in the Nordic countries.

Increased MYB alternative promoter usage is associated with relapse in acute lymphoblastic leukemia.

Therapy-resistant disease is a major cause of death in patients with acute lymphoblastic leukemia (ALL). Activation of the MYB oncogene is associated with ALL and leads to uncontrolled neoplastic cell proliferation and blocked differentiation. Here, we used RNA-seq to study the clinical significance of MYB expression and MYB alternative promoter (TSS2) usage in 133 pediatric ALLs. RNA-seq revealed that all cases analyzed overexpressed MYB and demonstrated MYB TSS2 activity. qPCR analyses confirmed the expression of the alternative MYB promoter also in seven ALL cell lines. Notably, high MYB TSS2 activity was significantly associated with relapse (p = 0.007). Moreover, cases with high MYB TSS2 usage showed evidence of therapy-resistant disease with increased expression of ABC multidrug resistance transporter genes (e.g., ABCA2, ABCB5, and ABCC10) and enzymes catalyzing drug degradation (e.g., CYP1A2, CYP2C9, and CYP3A5). Elevated MYB TSS2 activity was further associated with augmented KRAS signaling (p < 0.05) and decreased methylation of the conventional MYB promoter (p < 0.01). Taken together, our results suggest that MYB alternative promoter usage is a novel potential prognostic biomarker for relapse and therapy resistance in pediatric ALL.

Mutational patterns and clonal evolution from diagnosis to relapse in pediatric acute lymphoblastic leukemia.

The mechanisms driving clonal heterogeneity and evolution in relapsed pediatric acute lymphoblastic leukemia (ALL) are not fully understood. We performed whole genome sequencing of samples collected at diagnosis, relapse(s) and remission from 29 Nordic patients. Somatic point mutations and large-scale structural variants were called using individually matched remission samples as controls, and allelic expression of the mutations was assessed in ALL cells using RNA-sequencing. We observed an increased burden of somatic mutations at relapse, compared to diagnosis, and at second relapse compared to first relapse. In addition to 29 known ALL driver genes, of which nine genes carried recurrent protein-coding mutations in our sample set, we identified putative non-protein coding mutations in regulatory regions of seven additional genes that have not previously been described in ALL. Cluster analysis of hundreds of somatic mutations per sample revealed three distinct evolutionary trajectories during ALL progression from diagnosis to relapse. The evolutionary trajectories provide insight into the mutational mechanisms leading relapse in ALL and could offer biomarkers for improved risk prediction in individual patients.

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.

Refined detection and phasing of structural aberrations in pediatric acute lymphoblastic leukemia by linked-read whole-genome sequencing.

Structural chromosomal rearrangements that can lead to in-frame gene-fusions are a leading source of information for diagnosis, risk stratification, and prognosis in pediatric acute lymphoblastic leukemia (ALL). Traditional methods such as karyotyping and FISH struggle to accurately identify and phase such large-scale chromosomal aberrations in ALL genomes. We therefore evaluated linked-read WGS for detecting chromosomal rearrangements in primary samples of from 12 patients diagnosed with ALL. We assessed the effect of input DNA quality on phased haplotype block size and the detectability of copy number aberrations and structural variants in the ALL genomes. We found that biobanked DNA isolated by standard column-based extraction methods was sufficient to detect chromosomal rearrangements even at low 10x sequencing coverage. Linked-read WGS enabled precise, allele-specific, digital karyotyping at a base-pair resolution for a wide range of structural variants including complex rearrangements and aneuploidy assessment. With use of haplotype information from the linked-reads, we also identified previously unknown structural variants, such as a compound heterozygous deletion of ERG in a patient with the DUX4-IGH fusion gene. We conclude that linked-read WGS allows detection of important pathogenic variants in ALL genomes at a resolution beyond that of traditional karyotyping and FISH.

The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome.

We report a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. Differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.

Overexpression of chromatin remodeling and tyrosine kinase genes in iAMP21-positive acute lymphoblastic leukemia.

Intrachromosomal amplification of chromosome 21 (iAMP21) is a cytogenetic subtype associated with relapse and poor prognosis in pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL). The biology behind the high relapse risk is unknown and the aim of this study was to further characterize the genomic and transcriptional landscape of iAMP21. Using DNA arrays and sequencing, we could identify rearrangements and aberrations characteristic for iAMP21. RNA sequencing revealed that only half of the genes in the minimal region of amplification (20/45) were differentially expressed in iAMP21. Among them were the top overexpressed genes (p < 0.001) in iAMP21 vs. BCP ALL without iAMP21 and three candidate genes could be identified, the tyrosine kinase gene DYRK1A and chromatin remodeling genes CHAF1B and SON. While overexpression of DYRK1A and CHAF1B is associated with poor prognosis in malignant diseases including myeloid leukemia, this is the first study to show significant correlation with iAMP21-positive ALL.

CD99 expression is strongly associated with clinical outcome in children with B-cell precursor acute lymphoblastic leukaemia.

Our study aimed to determine the expression pattern and clinical relevance of CD99 in paediatric B-cell precursor acute lymphoblastic leukaemia (BCP-ALL). Our findings demonstrate that high expression levels of CD99 are mainly found in high-risk BCP-ALL, e.g. BCR-ABL1 and CRLF2Re/Hi, and that high CD99 mRNA levels are strongly associated with a high frequency of relapse, high proportion of positive for minimal residual disease at day 29 and poor overall survival in paediatric cohorts, which indicate that CD99 is a potential biomarker for BCP-ALL.

DNA methylation holds prognostic information in relapsed precursor B-cell acute lymphoblastic leukemia.

Background: Few biological markers are associated with survival after relapse of B-cell precursor acute lymphoblastic leukemia (BCP-ALL). In pediatric T-cell ALL, we have identified promoter-associated methylation alterations that correlate with prognosis. Here, the prognostic relevance of CpG island methylation phenotype (CIMP) classification was investigated in pediatric BCP-ALL patients. Methods: Six hundred and one BCP-ALL samples from Nordic pediatric patients (age 1-18) were CIMP classified at initial diagnosis and analyzed in relation to clinical data. Results: Among the 137 patients that later relapsed, patients with a CIMP- profile (n = 42) at initial diagnosis had an inferior overall survival (pOS5years 33%) compared to CIMP+ patients (n = 95, pOS5years 65%) (p = 0.001), which remained significant in a Cox proportional hazards model including previously defined risk factors. Conclusion: CIMP classification is a strong candidate for improved risk stratification of relapsed BCP-ALL.

Transcriptome sequencing in pediatric acute lymphoblastic leukemia identifies fusion genes associated with distinct DNA methylation profiles.

BACKGROUND: Structural chromosomal rearrangements that lead to expressed fusion genes are a hallmark of acute lymphoblastic leukemia (ALL). In this study, we performed transcriptome sequencing of 134 primary ALL patient samples to comprehensively detect fusion transcripts. METHODS: We combined fusion gene detection with genome-wide DNA methylation analysis, gene expression profiling, and targeted sequencing to determine molecular signatures of emerging ALL subtypes. RESULTS: We identified 64 unique fusion events distributed among 80 individual patients, of which over 50% have not previously been reported in ALL. Although the majority of the fusion genes were found only in a single patient, we identified several recurrent fusion gene families defined by promiscuous fusion gene partners, such as ETV6, RUNX1, PAX5, and ZNF384, or recurrent fusion genes, such as DUX4-IGH. Our data show that patients harboring these fusion genes displayed characteristic genome-wide DNA methylation and gene expression signatures in addition to distinct patterns in single nucleotide variants and recurrent copy number alterations. CONCLUSION: Our study delineates the fusion gene landscape in pediatric ALL, including both known and novel fusion genes, and highlights fusion gene families with shared molecular etiologies, which may provide additional information for prognosis and therapeutic options in the future.

Deep targeted sequencing in pediatric acute lymphoblastic leukemia unveils distinct mutational patterns between genetic subtypes and novel relapse-associated genes.

To characterize the mutational patterns of acute lymphoblastic leukemia (ALL) we performed deep next generation sequencing of 872 cancer genes in 172 diagnostic and 24 relapse samples from 172 pediatric ALL patients. We found an overall greater mutational burden and more driver mutations in T-cell ALL (T-ALL) patients compared to B-cell precursor ALL (BCP-ALL) patients. In addition, the majority of the mutations in T-ALL had occurred in the original leukemic clone, while most of the mutations in BCP-ALL were subclonal. BCP-ALL patients carrying any of the recurrent translocations ETV6-RUNX1, BCR-ABL or TCF3-PBX1 harbored few mutations in driver genes compared to other BCP-ALL patients. Specifically in BCP-ALL, we identified ATRX as a novel putative driver gene and uncovered an association between somatic mutations in the Notch signaling pathway at ALL diagnosis and increased risk of relapse. Furthermore, we identified EP300, ARID1A and SH2B3 as relapse-associated genes. The genes highlighted in our study were frequently involved in epigenetic regulation, associated with germline susceptibility to ALL, and present in minor subclones at diagnosis that became dominant at relapse. We observed a high degree of clonal heterogeneity and evolution between diagnosis and relapse in both BCP-ALL and T-ALL, which could have implications for the treatment efficiency.

DNA methylome analysis of acute lymphoblastic leukemia cells reveals stochastic de novo DNA methylation in CpG islands.

AIM: To identify regions of aberrant DNA methylation in acute lymphoblastic leukemia (ALL) cells of different subtypes on a genome-wide scale. MATERIALS & METHODS: Whole-genome bisulfite sequencing (WGBS) was used to determine the DNA methylation levels in cells from four pediatric ALL patients of different subtypes. The findings were confirmed by 450k DNA methylation arrays in a large patient set. RESULTS: Compared with mature B or T cells WGBS detected on average 82,000 differentially methylated regions per patient. Differentially methylated regions are enriched to CpG poor regions, active enhancers and transcriptional start sites. We also identified approximately 8000 CpG islands with variable intermediate DNA methylation that seems to occur as a result of stochastic de novo methylation. CONCLUSION: WGBS provides an unbiased view and novel insights into the DNA methylome of ALL cells.

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

UNLABELLED: 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. AVAILABILITY AND IMPLEMENTATION: CopyNumber450kCancer is implemented as an R package. The package with examples can be downloaded at http://cran.r-project.org CONTACT: nour.marzouka@medsci.uu.se SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

The mutational landscape in pediatric acute lymphoblastic leukemia deciphered by whole genome sequencing.

Genomic characterization of pediatric acute lymphoblastic leukemia (ALL) has identified distinct patterns of genes and pathways altered in patients with well-defined genetic aberrations. To extend the spectrum of known somatic variants in ALL, we performed whole genome and transcriptome sequencing of three B-cell precursor patients, of which one carried the t(12;21)ETV6-RUNX1 translocation and two lacked a known primary genetic aberration, and one T-ALL patient. We found that each patient had a unique genome, with a combination of well-known and previously undetected genomic aberrations. By targeted sequencing in 168 patients, we identified KMT2D and KIF1B as novel putative driver genes. We also identified a putative regulatory non-coding variant that coincided with overexpression of the growth factor MDK. Our results contribute to an increased understanding of the biological mechanisms that lead to ALL and suggest that regulatory variants may be more important for cancer development than recognized to date. The heterogeneity of the genetic aberrations in ALL renders whole genome sequencing particularly well suited for analysis of somatic variants in both research and diagnostic applications.

Accurate detection of subclonal single nucleotide variants in whole genome amplified and pooled cancer samples using HaloPlex target enrichment.

BACKGROUND: Target enrichment and resequencing is a widely used approach for identification of cancer genes and genetic variants associated with diseases. Although cost effective compared to whole genome sequencing, analysis of many samples constitutes a significant cost, which could be reduced by pooling samples before capture. Another limitation to the number of cancer samples that can be analyzed is often the amount of available tumor DNA. We evaluated the performance of whole genome amplified DNA and the power to detect subclonal somatic single nucleotide variants in non-indexed pools of cancer samples using the HaloPlex technology for target enrichment and next generation sequencing. RESULTS: We captured a set of 1528 putative somatic single nucleotide variants and germline SNPs, which were identified by whole genome sequencing, with the HaloPlex technology and sequenced to a depth of 792-1752. We found that the allele fractions of the analyzed variants are well preserved during whole genome amplification and that capture specificity or variant calling is not affected. We detected a large majority of the known single nucleotide variants present uniquely in one sample with allele fractions as low as 0.1 in non-indexed pools of up to ten samples. We also identified and experimentally validated six novel variants in the samples included in the pools. CONCLUSION: Our work demonstrates that whole genome amplified DNA can be used for target enrichment equally well as genomic DNA and that accurate variant detection is possible in non-indexed pools of cancer samples. These findings show that analysis of a large number of samples is feasible at low cost, even when only small amounts of DNA is available, and thereby significantly increases the chances of indentifying recurrent mutations in cancer samples.

Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia.

BACKGROUND: Although aberrant DNA methylation has been observed previously in acute lymphoblastic leukemia (ALL), the patterns of differential methylation have not been comprehensively determined in all subtypes of ALL on a genome-wide scale. The relationship between DNA methylation, cytogenetic background, drug resistance and relapse in ALL is poorly understood. RESULTS: We surveyed the DNA methylation levels of 435,941 CpG sites in samples from 764 children at diagnosis of ALL and from 27 children at relapse. This survey uncovered four characteristic methylation signatures. First, compared with control blood cells, the methylomes of ALL cells shared 9,406 predominantly hypermethylated CpG sites, independent of cytogenetic background. Second, each cytogenetic subtype of ALL displayed a unique set of hyper- and hypomethylated CpG sites. The CpG sites that constituted these two signatures differed in their functional genomic enrichment to regions with marks of active or repressed chromatin. Third, we identified subtype-specific differential methylation in promoter and enhancer regions that were strongly correlated with gene expression. Fourth, a set of 6,612 CpG sites was predominantly hypermethylated in ALL cells at relapse, compared with matched samples at diagnosis. Analysis of relapse-free survival identified CpG sites with subtype-specific differential methylation that divided the patients into different risk groups, depending on their methylation status. CONCLUSIONS: Our results suggest an important biological role for DNA methylation in the differences between ALL subtypes and in their clinical outcome after treatment.

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.