Dataset Information

Integration of cytogenomic data for furthering the characterization of pediatric B-cell acute lymphoblastic leukemia: a multi-institution, multi-platform microarray study.

ABSTRACT: It is well documented that among subgroups of B-cell acute lymphoblastic leukemia (B-ALL), the genetic profile of the leukemic blasts has significant impact on prognosis and stratification for therapy. Recent studies have documented the power of microarrays to screen genome-wide for copy number aberrations (CNAs) and regions of copy number-neutral loss of heterozygosity (CNLOH) that are not detectable by G-banding or fluorescence in situ hybridization (FISH). These studies have involved application of a single array platform for the respective cases. The present investigation demonstrates the feasibility and usefulness of integrating array results from multiple laboratories (ARUP, The Children's Hospital of Philadelphia, Cincinnati Children's Hospital Medical Center, and University of Minnesota Medical Center) that utilize different array platforms (Affymetrix, Agilent, or Illumina) in their respective clinical settings. A total of 65 patients enrolled on the Children's Oncology Group (COG) study AALL08B1 were identified for study, as cytogenetic and FISH studies had also been performed on these patients, with a central review of those results available for comparison. Microarray data were first analyzed by the individual laboratories with their respective software systems; raw data files were then centrally validated using NEXUS software. The results demonstrated the added value of integrating multi-platform data with cytogenetic and FISH data and highlight novel findings identified by array including the co-occurrence of low and high risk abnormalities not previously reported to coexist within a clone, novel regions of chromosomal amplification, clones characterized by numerous whole chromosome LOH that do not meet criteria for doubling of a near-haploid, and characterization of array profiles associated with an IKZF1 deletion. Each of these findings raises questions that are clinically relevant to risk stratification.

SUBMITTER: Baughn LB

PROVIDER: S-EPMC5361577 | biostudies-literature | 2015 Jan-Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integration of cytogenomic data for furthering the characterization of pediatric B-cell acute lymphoblastic leukemia: a multi-institution, multi-platform microarray study.

Baughn Linda B LB Biegel Jaclyn A JA South Sarah T ST Smolarek Teresa A TA Volkert Suzanne S Carroll Andrew J AJ Heerema Nyla A NA Rabin Karen R KR Zweidler-McKay Patrick A PA Loh Mignon M Hirsch Betsy B

Cancer genetics 20141121 1-2

It is well documented that among subgroups of B-cell acute lymphoblastic leukemia (B-ALL), the genetic profile of the leukemic blasts has significant impact on prognosis and stratification for therapy. Recent studies have documented the power of microarrays to screen genome-wide for copy number aberrations (CNAs) and regions of copy number-neutral loss of heterozygosity (CNLOH) that are not detectable by G-banding or fluorescence in situ hybridization (FISH). These studies have involved applicat ...[more]

PMID: 25678190

Similar Datasets

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.

Project description:The current study investigated the molecular mechanisms underlying pediatric acute lymphoblastic leukemia (ALL) and screened for small molecular drugs as supplementary drugs to aid current therapy. Gene expression data of Gene Expression Omnibus (GEO) DataSet GSE42221, which consists of 7 primary human B-precursor samples and 4 control B-cell progenitor lymphoblast samples from patients with pediatric ALL, were downloaded from the public GEO database. Linear Models for Microarray Analysis package for R statistical software was used to identify differentially expressed genes (DEGs). Subsequently, biclustering analysis of DEGs was performed using pheatmap package for R. Functional enrichment analysis of DEGs was conducted using the Database for Annotation, Visualization and Integrated Discovery tool. Additionally, Search Tool for the Retrieval of Interacting Genes software was used to screen protein-protein interactions (PPIs) of the DEGs, and Connectivity Map database was employed to obtain small-molecule drugs that were significantly associated with DEGs. In total, 116 genes were identified as DEGs in pediatric ALL, including 56 downregulated and 60 upregulated genes. Functional enrichment analysis identified that upregulated DEGs, including marker of proliferation Ki-67, cyclin F and nucleolar and spindle associated protein 1, were significantly enriched in mesenchymal cell differentiation and development processes, whilst downregulated DEGs, including bone marrow morphogenetic protein 2, semaphoring 3F and ephrin B1 were enriched in cell cycle process. Amongst the DEGs, 169 PPIs were identified. Notably, carbimazole and quinostatin were associated with DEGs. Additionally, a number of DEGs were targeted by the two drugs, including signal transducer and activator of transcription 3, nucleolar and spindle associated protein 1 and cell division cycle 20. Mesenchymal cell differentiation and development as well as cell cycle processes may be important for pediatric ALL. Quinostatin may be used as a potent supplementary drug for treating pediatric ALL.

Dataset Information

Integration of cytogenomic data for furthering the characterization of pediatric B-cell acute lymphoblastic leukemia: a multi-institution, multi-platform microarray study.

Publications

Integration of cytogenomic data for furthering the characterization of pediatric B-cell acute lymphoblastic leukemia: a multi-institution, multi-platform microarray study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets