DAC for "The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia"
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ABSTRACT:
PROVIDER: EGAC00001001501 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1, and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard-of-care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard-of-care diagnostics. KMT2A (MLL) rearrangements, although usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard-of-care testing in 9 patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the most common IKZF1 deletion from RNA-seq data and validated this using an RQ-PCR assay. We applied an expression classifier to identify Philadelphia chromosome-like B-ALL patients. T-ALL proved a rich source of novel gene fusions, which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.
| S-EPMC7065479 | biostudies-literature
Project description:Acute lymphoblastic leukemia (ALL) can be classified into different subgroups based on recurrent genetic alterations. Here, targeted RNA sequencing was used to identify the novel subgroups of ALL in 144 B-other and 40 "classical" ALL samples. The classical TCF3-PBX1, ETV6-RUNX1, KMT2A-rearranged, and BCR-ABL1, and novel P2RY8-CRLF2, ABL-, JAK2-, ZNF384-, MEF2D-, and NUTM1-fusions were easily identified by fusion transcript analysis. IGH-CRLF2 and IGH-EPOR were found by abnormally high levels of expression of CRLF2 or EPOR. DUX4-rearranged was identified by the unusual expression of DUX4 genes and an alternative exon of ERG, or by clustering analysis of gene expression. PAX5-driven ALL, including fusions, intragenic amplifications, and mutations were identified by single-nucleotide variant analysis and manual inspection using the IGV software. Exon junction analysis allowed detection of some intragenic ERG and IKZF1 deletions. CRLF2-high associated with initial white blood cell (WBC) counts of ≥50 × 103/μL and GATA3 risk alleles (rs3781093 and rs3824662), whereas ABL/JAK2/EPOR-fusions associated with high WBC counts, National Cancer Institute's high-risk classification, and IKZF1del. ZNF384-fusions associated with CALLA-negativity and NUTM1-fusions in infants. In conclusion, targeted RNA sequencing further classified 66.7% (96 of 144) B-other ALL cases. All BCP-ALL subgroups, except for iAMP21, hyperdiploid and hypodiploid cases, were identified. Curiously, we observed higher frequencies of females within B-rest ALLs and males in PAX5-driven cases.
| S-EPMC10320209 | biostudies-literature
Project description:Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Here, using whole-genome, exome and transcriptome sequencing of 2,754 childhood patients with ALL, we find that, despite a generally low mutation burden, ALL cases harbor a median of four putative somatic driver alterations per sample, with 376 putative driver genes identified varying in prevalence across ALL subtypes. Most samples harbor at least one rare gene alteration, including 70 putative cancer driver genes associated with ubiquitination, SUMOylation, noncoding transcripts and other functions. In hyperdiploid B-ALL, chromosomal gains are acquired early and synchronously before ultraviolet-induced mutation. By contrast, ultraviolet-induced mutations precede chromosomal gains in B-ALL cases with intrachromosomal amplification of chromosome 21. We also demonstrate the prognostic significance of genetic alterations within subtypes. Intriguingly, DUX4- and KMT2A-rearranged subtypes separate into CEBPA/FLT3- or NFATC4-expressing subgroups with potential clinical implications. Together, these results deepen understanding of the ALL genomic landscape and associated outcomes.
| S-EPMC9700506 | biostudies-literature
Project description: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.
| S-EPMC10709574 | biostudies-literature
Project description:Acute lymphoblastic leukaemia (ALL) is the most common childhood malignancy, and
implementation of risk-adapted therapy has been instrumental in the dramatic improvements in
clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of
individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions,
notably ETV6-RUNX1, TCF3-PBX1 and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing
(RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as
drivers in ALL, and identification of these new entities will contribute to refining ALL risk
stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of
including RNA-seq in standard of care diagnostic pipelines to detect gene rearrangements and
IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard of care
diagnostics. KMT2A-rearrangements (MLL), whilst usually identified, were the most commonly
missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not
detected by standard of care testing in nine patients. These were found in patients who were not
classifiable using standard molecular assessment. We developed an approach to detect the
commonest IKZF1 deletion from RNA-seq data and validated this using a RQ-PCR assay. We
applied an expression classifier to identify Ph-like B-ALL patients. T-ALL proved a rich source of
novel gene fusions which have clinical implications or provide insights into disease biology. Our
experience shows that RNA-seq can be implemented within an individual clinical service to
enhance the current molecular diagnostic risk classification of ALL.
| EGAS00001004212 | EGA
Project description: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.
2023-10-17 | GSE227832 | GEO
Project description:The outcomes of pediatric acute lymphoblastic leukemia (ALL) have improved remarkably during the last five decades. Such improvements were made possible by the incorporation of new diagnostic technologies, the effective administration of conventional chemotherapeutic agents, and the provision of better supportive care. With the 5-year survival rates now exceeding 90% in high-income countries, the goal for the next decade is to improve survival further toward 100% and to minimize treatment-related adverse effects. Based on genome-wide analyses, especially RNA-sequencing analyses, ALL can be classified into more than 20 B-lineage subtypes and more than 10 T-lineage subtypes with prognostic and therapeutic implications. Response to treatment is another critical prognostic factor, and detailed analysis of minimal residual disease can detect levels as low as one ALL cell among 1 million total cells. Such detailed analysis can facilitate the rational use of molecular targeted therapy and immunotherapy, which have emerged as new treatment strategies that can replace or reduce the use of conventional chemotherapy.
| S-EPMC8124693 | biostudies-literature
Project description:Genomic landscapes of 92 adult and 111 pediatric patients with B-cell acute lymphoblastic leukemia (B-ALL) were investigated using next-generation sequencing and copy number alteration analysis. Recurrent gene mutations and fusions were tested in an additional 87 adult and 93 pediatric patients. Among the 29 newly identified in-frame gene fusions, those involving MEF2D and ZNF384 were clinically relevant and were demonstrated to perturb B-cell differentiation, with EP300-ZNF384 inducing leukemia in mice. Eight gene expression subgroups associated with characteristic genetic abnormalities were identified, including leukemia with MEF2D and ZNF384 fusions in two distinct clusters. In subgroup G4 which was characterized by ERG deletion, DUX4-IGH fusion was detected in most cases. This comprehensive dataset allowed us to compare the features of molecular pathogenesis between adult and pediatric B-ALL and to identify signatures possibly related to the inferior outcome of adults to that of children. We found that, besides the known discrepancies in frequencies of prognostic markers, adult patients had more cooperative mutations and greater enrichment for alterations of epigenetic modifiers and genes linked to B-cell development, suggesting difference in the target cells of transformation between adult and pediatric patients and may explain in part the disparity in their responses to treatment.
| S-EPMC4919728 | biostudies-literature
Project description:Differences in survival have been reported between pediatric and adult acute lymphoblastic leukemia. The inferior prognosis in adult acute lymphoblastic leukemia is not fully understood but could be attributed, in part, to differences in genomic alterations found in adult as compared to in pediatric acute lymphoblastic leukemia.We compared two different sets of high-density single nucleotide polymorphism array genotyping data from 75 new diagnostic adult and 399 previously published diagnostic pediatric acute lymphoblastic leukemia samples. The patients' samples were randomly acquired from among Caucasian and Asian populations and hybridized to either Affymetrix 50K or 250K single nucleotide polymorphism arrays. The array data were investigated with Copy Number Analysis for GeneChips (CNAG) software for allele-specific copy number analysis.The high density single nucleotide polymorphism array analysis of 75 samples of adult acute lymphoblastic leukemia led to the identification of numerous cryptic and submicroscopic genomic lesions with a mean of 7.6 genomic alterations per sample. The patterns and frequencies of lesions detected in the adult samples largely reproduced known genomic hallmarks detected in previous single nucleotide polymorphism-array studies of pediatric acute lymphoblastic leukemia, such as common deletions of 3p14.2 (FHIT), 5q33.3 (EBF), 6q, 9p21.3 (CDKN2A/B), 9p13.2 (PAX5), 13q14.2 (RB1) and 17q11.2 (NF1). Some differences between adult and pediatric acute lymphoblastic leukemia were identified when the pediatric data set was partitioned into hyperdiploid and non-hyperdiploid cases and then compared to the nearly exclusively non-hyperdiploid adult samples. In this analysis, adult samples had a higher rate of deletions of chromosome 17p (TP53) and duplication of 17q.Our analysis of adult acute lymphoblastic leukemia cases led to the identification of new potential target lesions relevant for the pathogenesis of acute lymphoblastic leukemia. However, no unequivocal pattern of submicroscopic genomic alterations was found to separate adult acute lymphoblastic leukemia from pediatric acute lymphoblastic leukemia. Therefore, apart from different therapy regimen, differences of prognosis between adult and pediatric acute lymphoblastic leukemia are probably based on genetic subgroups according to cytogenetically detectable lesions but not focal genomic copy number microlesions.
| S-EPMC2930948 | biostudies-literature
Project description:Pediatric acute lymphoblastic leukemia (ALL) is the most common neoplasm and one of the primary causes of death in children. Its treatment is highly dependent on the correct classification of subtype. Previously, we developed a microarray-based subtype classifier based on the relative expression levels of 62 marker genes, which can predict 7 different ALL subtypes with an accuracy as high as 97% in completely independent samples. Because the classifier is based on gene expression rank values rather than actual values, the classifier enables an individualized diagnosis, without the need to reference the background distribution of the marker genes in a large number of other samples, and also enables cross platform application. Here, we demonstrate that the classifier can be extended from a microarray-based technology to a multiplex qPCR-based technology using the same set of marker genes as the advanced fragment analysis (AFA). Compared to microarray assays, the new assay system makes the convenient, low cost and individualized subtype diagnosis of pediatric ALL a reality and is clinically applicable, particularly in developing countries.
| S-EPMC4508914 | biostudies-literature