Comparative intraindividual transcriptome analysis of B-precursor ALL of childhood
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE42221 | GEO | 2013/09/17
SECONDARY ACCESSION(S): PRJNA179347
REPOSITORIES: GEO
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Project description:The objective of this study was the assessment of transcriptional dysregulation in particular with regard to B-cell differentiation factors. Most studies focus on cross-section analyses of various leukemia subtypes to identify differentially regulated genes lacking suitable reference models. Here we applied comparative intraindividual transcriptome analysis of B-precursor ALL of childhood, which introduces a side-by-side analysis of leukemic cells and matched normal lymphoblasts from the same individual in complete continuous remission after the end of re-induction therapy. This approach reduces noise by eliminating interindividual variability. Comparative matched pair analysis of (single sorted) initial leukemia and single sorted lymphoblasts isolated from the same individual, n=4 pairs, reference samples are the single sorted normal lymphoblasts. Please note that there are sorted samples form only three of the patients. Due to experimental circumstances, a "sorted" sample from the last patient was not included.
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Project description:ALL is the most common form of childhood cancer with >80% cured with contemporary treatment protocols. Accurate risk stratification in childhood ALL is essential to avoid under- and over-treatment. Currently, we use presenting clinical, biological features, and minimal residual disease (MRD) quantitation to risk stratify patients. Although whole genome gene expression profiling (GEP) can accurately classify patients with ALL into various WHO 2008 defined subgroups, its value in predicting relapse remained to be defined. We hypothesized that global time-series GEPs of bone marrow (BM) samples at diagnosis and specific points during initial remission-induction therapy can measure the success of cytoreduction and be used for relapse prediction. We generated time-series GEPs from 210 children with de novo ALL at diagnosis, and Day 8 of remission-induction therapy. We computed the time-series changes from diagnosis to follow-up time point of remission-induction, termed Effective Response Metric (ERM), that measures both the magnitude and direction of time-series change in multi-dimensional gene space towards the normal centroid, and we compared its ability to predict relapse against contemporary risk assignment methods including NCI criteria, cytogenetics and MRD.
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Project description:Glucocorticoids (GCs) cause cell cycle arrest and cell death in malignant lymphoblasts and constitute a principal component in the treatment of childhood acute lymphoblastic leukemia (chALL). To address the molecular mechanism of the anti-leukemic GC effects, we performed microarray-based whole-genome expression profiling of lymphoblasts from 46 patients undergoing systemic GC mono-therapy and combined these data with clinical information (e.g., molecular genotype, reduction in peripheral blood lymphoblasts, GC bioactivity in the patient's blood) using differential gene expression with GO analyses, regression modeling correlating transcriptional with clinical response, and an iterative elastic net approach to address combinatorial effects of gene expression and regulation. Our analysis revealed that, although there are a number of common response genes, the transcriptional response to GC in vivo varies considerably in the different molecular subtypes of this disease. Regarding the anti-leukemic response, repression of mRNA for key regulators of G2/M transition was commonly observed in all subtypes whereas we failed to observe a common transcriptional control of apoptosis genes. Although sets of genes were identified which in combination appear to contribute to the apoptotic response, the data as a whole suggest that GC-induced cell death does not result from conserved transcriptional regulation of the apoptotic machinery itself but might rather result from a wide spread deregulation of gene expression.
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Project description:The purpose of this study was the principal investigation and frequency of RTK expression in primary T-ALLs. Primary initial T-ALLs were assessed regarding their transcriptome-wide expression profiles and screend for prominent RTK expression. Naive primary T-ALL samples were evaluated with regard to global mRNA expression and screened for prominent RTK expression. The dataset was used to investigate RTK expression frequencies in T-ALLs.
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Project description:Glucocorticoids (GC) are in most chemotherapy protocols for lymphoid malignancies, particularly childhood acute lymphoblastic leukaemia (ALL) for their ability to induce apoptosis in malignant blast. The underlying mechanism, however, has so far only been investigated in model systems. This study comprises Affymetrix hgu133 plus 2.0 analyses of Peripheral blood lymphoblasts purified at three time points (0h, 6-8h, 24h after treatment initiation) from 13 children under therapy for ALL . Treated samples were compared to untreated (0h). This series consists of this set of microarrays. For comparison, expression profiles were generated from an adult ALL patient, peripheral blood lymphocytes from GC-exposed healthy donors, GC-sensitive and -resistant ALL cell lines and mouse thymocytes treated with GC in vivo and in vitro. Findings. An essentially complete list of GC-regulated candidate genes in clinical settings experimental and was generated, enabling immediate analysis of any gene with respect to its potential significance for GC-induced apoptosis in these systems. Gene regulations previously thought responsible for cell death in experimental systems were reconfirmed in few children only. In contrast, a small number of genes, most not implicated in GC-induced apoptosis previously, were co-ordinately regulated in the majority of children. Keywords = ALL Keywords = apoptosis Keywords = glucocorticoid Keywords = leukemia Keywords = pediatric oncology Keywords: other
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Project description:Although acute lymphoblastic leukemia (ALL) is highly responsive to chemotherapy, it is unknown how and which host immune factors influence the long-term remission of this cancer. To this end, we systematically evaluated the effects of T cell immunity on ALL chemotherapy outcomes. Using murine BCR-ABL1 ALL model, we showed that loss of total T cells, CD4 cells, or CD8 cells in the host drastically increased leukemia relapse following dasatinib or cytotoxic chemotherapy. Although ABL1 mutations emerged early during dasatinib treatment in both immunocompetent and immunocompromised hosts, T cell immunity was essential for suppressing the outgrowth of drug-resistant leukemia. Bulk and single-cell transcriptome profiling of T cells during therapy pointed to the activation Type I immunity-related cytokine signaling linked to long-term leukemia remission in mice. Consistent with these observations, IFNG and IL12 directly modulated dasatinib anti-leukemia efficacy in vivo. Finally, we evaluated peripheral blood immune cell composition in 102 children with ALL during chemotherapy and observed a significant association of T cell abundance with treatment outcomes. Together, these results suggest that T cell immunity plays pivotal roles in maintaining long-term remission of ALL, highlighting that the interplay between host immunity and drug resistance can be harnessed to improve ALL chemotherapy outcomes.
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Project description:B-cell precursor acute lymphoblastic leukemia (pre-B ALL) is the most common pediatric cancer. Although the genetic origin of the disease remains unclear, epigenetic modifications including DNA methylation are suggested to contribute significantly to leukemogenesis. We assessed the DNA methylation status of 402,842 CpG-sites across the genome (Illumina 450k array) in tumor and remission samples of 46 pre-B ALL patients, thus generating the most comprehensive single CpG-site resolution pre-B ALL methylomes so far. Unsupervised hierarchical clustering of CpG-site neighborhood, protein-coding gene, or miRNA gene associated methylation levels separated the tumor cohort according to major pre-B ALL subtypes, and methylation in CpG islands, shores, and in regions around the transcription start site of protein-coding genes strongly correlated with transcript expression. Focusing on samples carrying the t(12;21)(p13;q22) translocation (ETV6-RUNX1 fusion gene) we identified subtype-specific methylation of 430 CpG-sites. Pathway analyses implied the associated genes in hematopoiesis and cancer. Further intersection with transcriptome data identified methylation to impact expression of 18 genes. In summary, our data illustrate the power of methylation profiling to classify leukemic subtypes and to identify subtype-specific methylation markers. Further, we demonstrate that integration of methylome and transcriptome alterations allows the study of downstream effects of individual genomic rearrangements in cancer. Bisulfite converted DNA of tumor (isolated on day of diagnosis) and remission (isolated after disease remission) samples derived from 46 patients of French-Canadian origin diagnosed with pre-B ALL were analyzed on the Illumina Infinium HumanMethylation 450k BeadChips.
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Project description:We identified germline single nucleotide polymorphisms (SNPs) associated with childhood acute lymphoblastic leukemia (ALL) and its subtypes. Using the Affymetrix 500K Mapping array and publicly available genotypes, we identified 18 SNPs whose allele frequency differed (P<1x10-5) between a pediatric ALL population (n=317) and non-ALL controls (n=17,958). Six of these SNPs differed (P≤0.05) in allele frequency among four ALL subtypes. Two SNPs in ARID5B not only differed between ALL and non-ALL groups (rs10821936, P=1.4x10-15, odds ratio[OR]=1.91; rs10994982, P=5.7x10-9, OR=1.62) but also distinguished B-hyperdiploid ALL from other subtypes (rs10821936, P=1.62 x10-5, OR=2.17; rs10994982, P=0.003, OR 1.72). These ARID5B SNPs also distinguished B-hyperdiploid ALL from other subtypes in an independent validation cohort (n=124 children with ALL) (P=0.003 and P=0.0008, OR 2.45 and 2.86, respectively) and were associated with methotrexate accumulation and gene expression pattern in leukemic lymphoblasts. We conclude that germline genomic variations affect susceptibility to and characteristics of specific ALL subtypes. We used microarrays to detail the global program of gene expression in primary leukemic blasts cells from children diagnosed with acute lymphoblastic leukemia.
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