Project description:MicroRNA-sequencing of the bone marrow samples from Brazilian pediatric patients with B-cell acute lymphoblastic leukemia (B-ALL) and T-cell acute lymphoblastic leukemia (T-ALL).
Project description:This data set consists of pediatric acute lymphoblastic leukemia (ALL) primary bone marrow biopsies from the BC Children's Hospital BioBank, pediatric ALL cell lines, non-cancer bone marrow biopsies, and few ALL PDX. All files are DIA and searched by Spectronaut with a spectral library.
Project description:RNA was extracted from the diagnostic bone marrow specimens of 50 T-cell acute lymphoblastic leukemia pediatric patients and analysed by Affymetrix microarray to model gene classifiers predictive of clinical outcome
Project description:The development of a clinically relevant xenograft model of pediatric acute lymphoblastic leukemia, using a 4-drug treatment regimen designed to mimic pediatric remission induction therapy. Relapse and acquired drug resistance in T-cell acute lymphoblastic leukemia (T-ALL) remains a significant clinical problem. This study was designed to establish a preclinical model of resistance to induction therapy in childhood T-ALL to examine the emergence of drug resistance and identify novel therapies. We performed transcription profiling by array of human CD45-positive human lymphocytes from patients with acute pediatric lymphoblastic leukemia, and from xenografted NOD/SCID mice treated with vincristine, daunorubicin, dexamethasone and L-asparagine. Several different treatment regimes were used in this study (VLXD, VLXDR, VLXD2, VXL and VLXD2-ALL31) and are summarised in the protocols associated with this submission.
Project description:DS-ALL is a highly heterogeneous disease with predominance of an aberrant exp. of CRLF2 cooperating with mutated JAK2 Acute lymphoblastic pediatric leukemia specimens of Down's syndrome are examined for gene expression profiles and specific genetic aberrations. Gene expression profiling and specific genetic variation analysis identify novel pathways involved in DS-ALL pathogenesis.
Project description:The aim of this study was to investigate the transcriptome of 54 primary samples of pediatric patients diagnosed with T-cell acute lymphoblastic leukemia. Samples were collected before treatment. Sequencing libraries were obtained with Illumina TruSeq Stranded mRNA protocol, with modified conditions of RNA fragmentation (90°C for 2 minutes). All libraries were sequenced on Illumina NovaSeq6000 platform, in 2x150PE mode (paired end sequencing with 150 nt reads), with a coverage of 150M reads/sample.
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.