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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.

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.

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.

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., 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.

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., 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.

Genetic analysis of leukemic clones in monozygotic twins with concordant acute lymphoblastic leukemia (ALL) has proved a unique opportunity to gain insight into the molecular phylogenetics of leukemogenesis. Using whole-genome sequencing, we characterized constitutional and somatic single nucleotide variants/insertion-deletions (indels) and structural variants in a monozygotic twin pair with concordant ETV6-RUNX1(+) B-cell precursor ALL (BCP-ALL). In addition, digital PCR (dPCR) was applied to evaluate the presence of and quantify selected somatic variants at birth, diagnosis, and remission. A shared somatic complex rearrangement involving chromosomes 11, 12, and 21 with identical fusion sequences in leukemias of both twins offered direct proof of a common clonal origin. The ETV6-RUNX1 fusion detected at diagnosis was found to originate from this complex rearrangement. A shared somatic frameshift deletion in UBA2 was also identified in diagnostic samples. In addition, each leukemia independently acquired analogous deletions of 3 genes recurrently targeted in BCP-ALLs (ETV6, ATF7IP, and RAG1/RAG2), providing evidence of a convergent clonal evolution only explained by a strong concurrent selective pressure. Quantification of the UBA2 deletion by dPCR surprisingly indicated it persisted in remission. This, for the first time to our knowledge, provided evidence of a UBA2 variant preceding the well-established initiating event ETV6-RUNX1. Further, we suggest the UBA2 deletion exerted a leukemia predisposing effect and that its essential role in Small Ubiquitin-like Modifier (SUMO) attachment (SUMOylation), regulating nearly all physiological and pathological cellular processes such as DNA-repair by nonhomologous end joining, may hold a mechanistic explanation for the predisposition.

Pathogenic germline variants in ETV6 have been associated with familial predisposition to thrombocytopenia and hematological malignancies, predominantly childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL). In addition, overrepresentation of a high hyperdiploid subtype and older age at diagnosis have been reported among sporadic BCP-ALL cases with germline variants in ETV6. We studied a family with 2 second-degree relatives who developed childhood high hyperdiploid BCP-ALL at ages 8 and 12 years, respectively. A constitutional balanced reciprocal translocation t(12;14)(p13.2;q23.1) was discovered in both patients by routine karyotyping at diagnosis and, subsequently, in 7 healthy family members who had not experienced hematological malignancies. No carriers had thrombocytopenia. Whole-genome sequencing confirmed the translocation, resulting in 2 actively transcribed but nonfunctional fusion genes, causing heterozygous loss and consequently monoallelic expression of ETV6. Whole-genome sequencing analysis of the affected female subjects' leukemia excluded additional somatic aberrations in ETV6 and RTN1 as well as shared somatic variants in other genes. Expression studies, performed to confirm decreased expression of ETV6, were not conclusive. We suggest that germline aberrations resulting in monoallelic expression of ETV6 contribute to leukemia susceptibility, whereas more severe functional deficiency of ETV6 is required for developing THC5. To our knowledge, this report is the first of a constitutional translocation disrupting ETV6 causing predisposition to childhood ALL.

PIK3CA-related overgrowth spectrum is a group of rare genetic disorders with asymmetric overgrowth caused by somatic mosaic PIK3CA mutations. Here, we report clinical data and molecular findings from two patients with congenital muscular upper limb overgrowth and aberrant anatomy. During debulking surgery, numerous ectopic muscles were found in the upper limbs of the patients. DNA sequencing, followed by digital polymerase chain reaction, was performed on DNA extracted from biopsies from hypertrophic ectopic muscles and identified the somatic mosaic PIK3CA hotspot mutations c.3140A > G, p.(His1047Arg) and c.1624G > A, p.(Glu542Lys) in a male (patient 1) and a female (patient 2) patient, respectively. Patient 1 had four ectopic muscles and unilateral isolated muscular overgrowth while patient 2 had 13 ectopic muscles and bilateral isolated muscular overgrowth of both upper limbs, indicating that her mutation occurred at early pre-somitic mesoderm state. The finding of PIK3CA mutations in ectopic muscles highlights the importance of PIK3CA in cell fate in early human embryonic development. Moreover, our findings provide evidence that the disease phenotype depends on the timing of PIK3CA mutagenesis during embryogenesis and confirm the diagnostic entity PIK3CA-related muscular overgrowth with ectopic accessory muscles.

De 2 sista författarna delar sistaförfattarskapet.

PIK3CA-related overgrowth spectrum is a group of rare genetic disorders with asymmetric overgrowth caused by somatic mosaic PIK3CA mutations. Here, we report clinical data and molecular findings from two patients with congenital muscular upper limb overgrowth and aberrant anatomy. During debulking surgery, numerous ectopic muscles were found in the upper limbs of the patients. DNA sequencing, followed by digital polymerase chain reaction, was performed on DNA extracted from biopsies from hypertrophic ectopic muscles and identified the somatic mosaic PIK3CA hotspot mutations c.3140A > G, p.(His1047Arg) and c.1624G > A, p.(Glu542Lys) in a male (patient 1) and a female (patient 2) patient, respectively. Patient 1 had four ectopic muscles and unilateral isolated muscular overgrowth while patient 2 had 13 ectopic muscles and bilateral isolated muscular overgrowth of both upper limbs, indicating that her mutation occurred at early pre-somitic mesoderm state. The finding of PIK3CA mutations in ectopic muscles highlights the importance of PIK3CA in cell fate in early human embryonic development. Moreover, our findings provide evidence that the disease phenotype depends on the timing of PIK3CA mutagenesis during embryogenesis and confirm the diagnostic entity PIK3CA-related muscular overgrowth with ectopic accessory muscles.

PIK3CA-related overgrowth spectrum is a group of rare genetic disorders with asymmetric overgrowth caused by somatic mosaic PIK3CA mutations. Here, we report clinical data and molecular findings from two patients with congenital muscular upper limb overgrowth and aberrant anatomy. During debulking surgery, numerous ectopic muscles were found in the upper limbs of the patients. DNA sequencing, followed by digital polymerase chain reaction, was performed on DNA extracted from biopsies from hypertrophic ectopic muscles and identified the somatic mosaic PIK3CA hotspot mutations c.3140A > G, p.(His1047Arg) and c.1624G > A, p.(Glu542Lys) in a male (patient 1) and a female (patient 2) patient, respectively. Patient 1 had four ectopic muscles and unilateral isolated muscular overgrowth while patient 2 had 13 ectopic muscles and bilateral isolated muscular overgrowth of both upper limbs, indicating that her mutation occurred at early pre-somitic mesoderm state. The finding of PIK3CA mutations in ectopic muscles highlights the importance of PIK3CA in cell fate in early human embryonic development. Moreover, our findings provide evidence that the disease phenotype depends on the timing of PIK3CA mutagenesis during embryogenesis and confirm the diagnostic entity PIK3CA-related muscular overgrowth with ectopic accessory muscles.

PIK3CA-related overgrowth spectrum is a group of rare genetic disorders with asymmetric overgrowth caused by somatic mosaic PIK3CA mutations. Here, we report clinical data and molecular findings from two patients with congenital muscular upper limb overgrowth and aberrant anatomy. During debulking surgery, numerous ectopic muscles were found in the upper limbs of the patients. DNA sequencing, followed by digital polymerase chain reaction, was performed on DNA extracted from biopsies from hypertrophic ectopic muscles and identified the somatic mosaic PIK3CA hotspot mutations c.3140A > G, p.(His1047Arg) and c.1624G > A, p.(Glu542Lys) in a male (patient 1) and a female (patient 2) patient, respectively. Patient 1 had four ectopic muscles and unilateral isolated muscular overgrowth while patient 2 had 13 ectopic muscles and bilateral isolated muscular overgrowth of both upper limbs, indicating that her mutation occurred at early pre-somitic mesoderm state. The finding of PIK3CA mutations in ectopic muscles highlights the importance of PIK3CA in cell fate in early human embryonic development. Moreover, our findings provide evidence that the disease phenotype depends on the timing of PIK3CA mutagenesis during embryogenesis and confirm the diagnostic entity PIK3CA-related muscular overgrowth with ectopic accessory muscles.

PIK3CA-related overgrowth spectrum is a group of rare genetic disorders with asymmetric overgrowth caused by somatic mosaic PIK3CA mutations. Here, we report clinical data and molecular findings from two patients with congenital muscular upper limb overgrowth and aberrant anatomy. During debulking surgery, numerous ectopic muscles were found in the upper limbs of the patients. DNA sequencing, followed by digital polymerase chain reaction, was performed on DNA extracted from biopsies from hypertrophic ectopic muscles and identified the somatic mosaic PIK3CA hotspot mutations c.3140A > G, p.(His1047Arg) and c.1624G > A, p.(Glu542Lys) in a male (patient 1) and a female (patient 2) patient, respectively. Patient 1 had four ectopic muscles and unilateral isolated muscular overgrowth while patient 2 had 13 ectopic muscles and bilateral isolated muscular overgrowth of both upper limbs, indicating that her mutation occurred at early pre-somitic mesoderm state. The finding of PIK3CA mutations in ectopic muscles highlights the importance of PIK3CA in cell fate in early human embryonic development. Moreover, our findings provide evidence that the disease phenotype depends on the timing of PIK3CA mutagenesis during embryogenesis and confirm the diagnostic entity PIK3CA-related muscular overgrowth with ectopic accessory muscles.

The detection of recurrent somatic chromosomal rearrangements is standard of care for most leukemia types. Even though karyotype analysis-a low-resolution genome-wide chromosome analysis-is still the gold standard, it often needs to be complemented with other methods to increase resolution. To evaluate the feasibility and applicability of mate pair whole genome sequencing (MP-WGS) to detect structural chromosomal rearrangements in the diagnostic setting, we sequenced ten bone marrow samples from leukemia patients with recurrent rearrangements. Samples were selected based on cytogenetic and FISH results at leukemia diagnosis to include common rearrangements of prognostic relevance. Using MP-WGS and in-house bioinformatic analysis all sought rearrangements were successfully detected. In addition, unexpected complexity or additional, previously undetected rearrangements was unraveled in three samples. Finally, the MP-WGS analysis pinpointed the location of chromosome junctions at high resolution and we were able to identify the exact exons involved in the resulting fusion genes in all samples and the specific junction at the nucleotide level in half of the samples. The results show that our approach combines the screening character from karyotype analysis with the specificity and resolution of cytogenetic and molecular methods. As a result of the straightforward analysis and high-resolution detection of clinically relevant rearrangements, we conclude that MP-WGS is a feasible method for routine leukemia diagnostics of structural chromosomal rearrangements.

Most balanced translocations are thought to result mechanistically from nonhomologous end joining or, in rare cases of recurrent events, by nonallelic homologous recombination. Here, we use low-coverage mate pair whole-genome sequencing to fine map rearrangement breakpoint junctions in both phenotypically normal and affected translocation carriers. In total, 46 junctions from 22 carriers of balanced translocations were characterized. Genes were disrupted in 48% of the breakpoints; recessive genes in four normal carriers and known dominant intellectual disability genes in three affected carriers. Finally, seven candidate disease genes were disrupted in five carriers with neurocognitive disabilities (SVOPL, SUSD1, TOX, NCALD, SLC4A10) and one XX-male carrier with Tourette syndrome (LYPD6, GPC5). Breakpoint junction analyses revealed microhomology and small templated insertions in a substantive fraction of the analyzed translocations (17.4%; n = 4); an observation that was substantiated by reanalysis of 37 previously published translocation junctions. Microhomology associated with templated insertions is a characteristic seen in the breakpoint junctions of rearrangements mediated by error-prone replication-based repair mechanisms. Our data implicate that a mechanism involving template switching might contribute to the formation of at least 15% of the interchromosomal translocation events.

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 o, De två sista författarna delar sistaförfattarskapet.

Paediatric B-cell precursor acute lymphoblastic leukaemias (BCP ALL) with IKZF1 deletions (IKZF1) are associated with a poor outcome. However, there are conflicting data as to whether IKZF1 is an independent risk factor if minimal residual disease (MRD) and other copy number alterations also are taken into account. We investigated 334 paediatric BCP ALL, diagnosed 1992-2013 and treated according to Nordic Society for Paediatric Haematology and Oncology ALL protocols, with known IKZF1 status based on either single nucleotide polymorphism array (N=218) or multiplex ligation-dependent probe amplification (N=116) analyses. IKZF1, found in 15%, was associated with inferior 10-year probabilities of event-free (60% vs. 83%; P<0001) and overall survival (pOS; 73% vs. 89%; P=0001). Adjusting for known risk factors, including white blood cell (WBC) count and MRD, IKZF1 was the strongest independent factor for relapse and death. IKZF1 was present in 27% of cases with non-informative cytogenetics (BCP-other') and a poor 10-year pOS was particularly pronounced in this group (58% vs. 90%; P<0001). Importantly, neither MRD nor WBC count predicted events in the IKZF1-positive cases. Co-occurrence of pseudoautosomal region 1 (PAR1) deletions in Xp22.33/Yp11.32 (P2RY8-CRLF2) and IKZF1 increased the risk of relapse (75% vs. 30% for cases with only IKZF1; P=0045), indicating that BCP-other ALL with both P2RY8-CRLF2 and IKZF1 constitutes a particularly high-risk group.

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 o, De två sista författarna delar sistaförfattarskapet.

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 o, De två sista författarna delar sistaförfattarskapet.

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 similar to 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 d

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 similar to 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 d

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 similar to 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 d

Paediatric B-cell precursor acute lymphoblastic leukaemias (BCP ALL) with IKZF1 deletions (IKZF1) are associated with a poor outcome. However, there are conflicting data as to whether IKZF1 is an independent risk factor if minimal residual disease (MRD) and other copy number alterations also are taken into account. We investigated 334 paediatric BCP ALL, diagnosed 1992-2013 and treated according to Nordic Society for Paediatric Haematology and Oncology ALL protocols, with known IKZF1 status based on either single nucleotide polymorphism array (N=218) or multiplex ligation-dependent probe amplification (N=116) analyses. IKZF1, found in 15%, was associated with inferior 10-year probabilities of event-free (60% vs. 83%; P<0001) and overall survival (pOS; 73% vs. 89%; P=0001). Adjusting for known risk factors, including white blood cell (WBC) count and MRD, IKZF1 was the strongest independent factor for relapse and death. IKZF1 was present in 27% of cases with non-informative cytogenetics (BCP-other') and a poor 10-year pOS was particularly pronounced in this group (58% vs. 90%; P<0001). Importantly, neither MRD nor WBC count predicted events in the IKZF1-positive cases. Co-occurrence of pseudoautosomal region 1 (PAR1) deletions in Xp22.33/Yp11.32 (P2RY8-CRLF2) and IKZF1 increased the risk of relapse (75% vs. 30% for cases with only IKZF1; P=0045), indicating that BCP-other ALL with both P2RY8-CRLF2 and IKZF1 constitutes a particularly high-risk group.

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 o, De två sista författarna delar sistaförfattarskapet.

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 o, De två sista författarna delar sistaförfattarskapet.

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 o, De två sista författarna delar sistaförfattarskapet.

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

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 similar to 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 d

Paediatric B-cell precursor acute lymphoblastic leukaemias (BCP ALL) with IKZF1 deletions (∆IKZF1) are associated with a poor outcome. However, there are conflicting data as to whether ∆IKZF1 is an independent risk factor if minimal residual disease (MRD) and other copy number alterations also are taken into account. We investigated 334 paediatric BCP ALL, diagnosed 1992-2013 and treated according to Nordic Society for Paediatric Haematology and Oncology ALL protocols, with known IKZF1 status based on either single nucleotide polymorphism array (N = 218) or multiplex ligation-dependent probe amplification (N = 116) analyses. ∆IKZF1, found in 15%, was associated with inferior 10-year probabilities of event-free (60% vs. 83%; P < 0·001) and overall survival (pOS; 73% vs. 89%; P = 0·001). Adjusting for known risk factors, including white blood cell (WBC) count and MRD, ∆IKZF1 was the strongest independent factor for relapse and death. ∆IKZF1 was present in 27% of cases with non-informative cytogenetics ('BCP-other') and a poor 10-year pOS was particularly pronounced in this group (58% vs. 90%; P < 0·001). Importantly, neither MRD nor WBC count predicted events in the ∆IKZF1-positive cases. Co-occurrence of pseudoautosomal region 1 (PAR1) deletions in Xp22.33/Yp11.32 (P2RY8-CRLF2) and ∆IKZF1 increased the risk of relapse (75% vs. 30% for cases with only ∆IKZF1; P = 0·045), indicating that BCP-other ALL with both P2RY8-CRLF2 and ∆IKZF1 constitutes a particularly high-risk group.

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 similar to 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 d