Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Integrated genomics approach to detect allelic imbalances in multiple myeloma, SNP data

ABSTRACT: A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide dosage effect on gene and microRNA expression Multiple myeloma (MM) is characterized by marked genomic instability. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To better elucidate the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. Using a self-developed procedure to infer exact local copy numbers for each sample, we identified a significant fraction of patients showing marked aneuploidy. A conventional clustering analysis showed that aneuploidy, chromosome 1 alterations, hyperdiploidy and recursive deletions at 1p and chromosomes 13, 14 and 22 were the main aberrations driving samples grouping. Then, we integrated mapping information with gene and microRNAs expression profiles: a multiclass analysis of the identified clusters showed a marked gene-dosage effect, particularly concerning 1q transcripts, also confirmed by correlating gene expression levels and local copy number alterations. A wide dosage effect affected also microRNAs, indicating that structural abnormalities in MM closely reflect in their expression imbalances. Finally, we identified several loci in which genes and microRNAs expression correlated with loss-of-heterozygosity occurrence. Our results provide insights into the composite network linking genome structure and gene/microRNA transcriptional features in MM. Keywords: Integrated genomics approach based on SNP microarray and FISH procedures to detect allelic imbalances in multiple myeloma. Pathological bone marrow specimens from 41 MM and four plasma cell leukemia (PCL) patients at diagnosis. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 40 micrograms of fragmented biotin-labelled DNA were hybridized on GeneChip Human Mapping 50K XbaI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChip® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. Genomic Smoothing analysis was performed by using the smoothing window of 0 Mb, and inferred copy number states were derived from a Hidden Markov Model (HMM) based algorithm implemented in CNAT 4.0.1. Circular Binary Segmentation (Ohlsen et al., 2004) was applied using DNAcopy package for R Bioconductor on raw data. FBN procedure was finally applied to infer exact local copy number as described in the mentioned Reference.

ORGANISM(S): Homo sapiens

SUBMITTER: Antonino Neri

PROVIDER: E-GEOD-16121 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide gene dosage effect.

Agnelli Luca L Mosca Laura L Fabris Sonia S Lionetti Marta M Andronache Adrian A Kwee Ivo I Todoerti Katia K Verdelli Donata D Battaglia Cristina C Bertoni Francesco F Deliliers Giorgio Lambertenghi GL Neri Antonino A

Genes, chromosomes & cancer 20090701 7

Multiple myeloma (MM) is characterized by marked genomic heterogeneity. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To elucidate better the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. We firstly generated genome-wide profiles of 41 MMs and four plasma cell leukemias, using a self-developed procedure to infer exact local copy ...[more]

PMID: 19396863

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Project description:Primary plasma cell leukaemia (pPCL) is a rare, yet aggressive form of de novo plasma cell tumor, distinguished from secondary PCL (sPCL) which represents a leukemic transformation of pre-existing multiple myeloma (MM). Here, we performed a comprehensive molecular analysis of a prospective series of pPCLs by means of FISH, single nucleotide polymorphism (SNP) array and gene expression profiling (GEP). IGH@ translocations were identified in 87% of pPCL cases, with prevalence of t(11;14) (40%) and t(14;16) (30.5%), whereas the most frequently altered regions were located at 1p (38%), 1q (48%), 6q (29%), 8p (42%), 13q (74%), 14q (71%), 16q (53%) and 17p (35%). A relevant finding of our study was the identification of a minimal biallelical deletion (1.5 Mb) in 8p21.2 encompassing the putative tumor suppressor gene PPP2R2A that was significantly down-regulated in deleted cases. Mutations of TP53 were identified in 4 cases all but one associated with a monoallelic deletion of the gene, whereas activating mutations of BRAF occurred in one case and were absent for N- and K-RAS. To evaluate the influence of allelic imbalances in transcriptional expression we performed an integrated genomic analysis with GEP data, showing a significant dosage effect of genes involved in transcription, translation, methyltransferases activity, apoptosis as well as Wnt and NF-kB signaling pathways. Overall, we provide a compendium of genomic alterations in a prospective series of pPCLs which may contribute to our understanding of this particular form of plasma cell dyscrasia and to better elucidate the mechanisms of tumor progression in MM. This series of microarray experiments contains the genome-wide profiles of 17 primary Plasma Cell Leukemia. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 90 micrograms of fragmented biotin-labeled DNA were hybridized on GeneChip Human Mapping 250K NspI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChipÂ® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. The raw data for individual SNPs were extracted from CEL files and converted into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares using the Hidden Markov Model algorithm with a genomic smoothing window set to 0. After the pre-processing, piecewise constant estimates of the underlying local DNA copy number (CN) variation was calculated using the DNAcopy Bioconductor package, which looks for optimal breakpoints using circular binary segmentation (CBS). genotyping analysis of 17 primary Plasma Cell Leukemia

Project description:The role of microRNAs (miRNAs) in multiple myeloma (MM) has yet to be fully elucidated. To identify miRNAs that are potentially deregulated in MM, we investigated those mapping within transcription units, based on evidence that intronic miRNAs are frequently coexpressed with their host genes. To this end, we monitored host transcript expression values in a panel of 20 human MM cell lines (HMCLs) profiled on Affymetrix U133A oligonucleotide microarrays and focused on transcripts whose expression varied significantly across the dataset. We identified transcripts specific to six miRNA host genes (CCPG1, GULP1, EVL, TACSTD1, MEST, and TNIK) whose average changes in expression varied at least 2-fold from the mean of the examined dataset. We evaluated the expression levels of the corresponding intronic miRNAs by quantitative real-time RT-PCR. There was a significant correlation between the expression levels of MEST, EVL, and GULP1 and those of the corresponding miRNAs miR-335, miR-342-3p, and miR-561, respectively. Genome-wide profiling of the 20 HMCLs with the Affymetrix GeneChip human mapping 250K array set indicated that the increased expression of the three host genes and their corresponding intronic miRNAs was not correlated with local copy number variations. Notably, miRNAs and their host genes were overexpressed in a fraction of primary tumors with respect to normal plasma cells; however, this finding was not correlated with known molecular myeloma groups. The predicted putative miRNA targets, as well as the transcriptional profiles associated with the primary tumors, suggest that MEST/miR-335 and EVL/miR-342-3p may play a role in plasma cell homing and/or interactions with the bone marrow microenvironment. Our data support the idea that intronic miRNAs and their host genes are regulated dependently, and may contribute to the understanding of their biological roles in cancer. To our knowledge, this is the first evidence of deregulated miRNA expression in MM, providing insights that may lead to the identification of new biomarkers and altered molecular pathways of the disease. Keywords: integrative genomic analysis of miR-335, miR-342, and miR-561 in multiple myeloma This series of microarray experiments contains the genome-wide profiles of 20 HMCLs. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 90 micrograms of fragmented biotin-labelled DNA were hybridized on GeneChip® Human Mapping 250K NspI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip® Scanner 3000 7G. The images were acquired using Affymetrix GeneChip® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. Raw data were extracted using the Hidden Markov Model Genomic Smoothing window was set to 0. After the preprocessing, piecewise constant estimates of the underlying local DNA CN variation was calculated using the DNA copy Bioconductor package, which looks for optimal breakpoints using circular binary segmentation (CBS).

Project description:Multiple myeloma (MM) is characterized by marked genomic instability. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To better elucidate the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. Using a self-developed procedure to infer exact local copy numbers for each sample, we identified a significant fraction of patients showing marked aneuploidy. A conventional clustering analysis showed that aneuploidy, chromosome 1 alterations, hyperdiploidy and recursive deletions at 1p and chromosomes 13, 14 and 22 were the main aberrations driving samples grouping. Then, we integrated mapping information with gene and microRNAs expression profiles: a multiclass analysis of the identified clusters showed a marked gene-dosage effect, particularly concerning 1q transcripts, also confirmed by correlating gene expression levels and local copy number alterations. A wide dosage effect affected also microRNAs, indicating that structural abnormalities in MM closely reflect in their expression imbalances. Finally, we identified several loci in which genes and microRNAs expression correlated with loss-of-heterozygosity occurrence. Our results provide insights into the composite network linking genome structure and gene/microRNA transcriptional features in MM. Experiment Overall Design: This series of microarray experiments contains the gene expression profiles of purified plasma cells (PCs) obtained from 4 normal donor (N), 11 monoclonal gammopathy of undetermined significance (MGUS), 133 multiple myeloma (MM) and 9 plasma cell leukemia (PCL) at diagnosis. PCs were purified from bone marrow specimens, after red blood cell lysis with 0.86% ammonium chloride, using CD138 immunomagnetic microbeads. The purity of the positively selected PCs was assessed by morphology and flow cytometry and was > 90% in all cases. 5 micrograms of total RNA was processed and, in accordance with the manufacturer's protocols, 15 micrograms of fragmented biotin-labelled cRNA were hybridized on GeneChip Human Genome U133A Arrays (Affymetrix Inc.). The arrays were scanned using the Agilent GeneChip Scanner G2500A. The images were acquired using Affymetrix MicroArray Suite (MAS) 5.0 software and the probe level data converted to expression values using the Bioconductor function for the Robust Multi-Array average (RMA) procedure (Irizarry et al, 2003), in which perfect match intensities are background adjusted, quantile-quantile normalised and log2 transformed.

Project description:Distinct genetic abnormalities such as TP53 deletion at 17p13.1, have been identified as having an adverse prognostic relevance in B-cell chronic lymphocytic leukemia (B-CLL). Conventional cytogenetic studies have shown that TP53 deletion in B-CLL is associated predominantly with 17p loss resulting from complex chromosomal rearrangements. We performed genome-wide DNA (SNPs arrays), fluorescence in situ hybridization (FISH) and gene expression profiling (GEP) analyses to investigate the significance of 17p loss in a panel of 71 genetically well-characterized B-CLLs in Binet stage A, 18 of which carried a TP53 monoallelic deletion. Combined SNP arrays and FISH approaches showed 17p loss in all of the TP53-deleted cases, with breakpoints scattered along the 17p11.2 region. Mutations in exons 5 to 9 of TP53 were found in 9/12 deleted samples. GEP of 60 B-CLLs, including 7 patients with 17p loss, identified 40 differentially expressed genes in 17p- versus 17p normal samples, 35 of which were down-regulated in 17p- tumors. The majority (30/35) of these transcripts, including putative tumor suppressor genes, mapped to 17p. Overall, these data indicate that, beside TP53 deletion, the concomitant loss of 17p arm may contribute to the strong negative prognostic impact known to be associated with this lesion in B-CLL. Keywords: genomic analysis of B-CLL with 17p loss patients This series of microarray experiments contains the genome-wide profiles of purified B-cell chronic lymphocytic leukemia (B-CLL) cells obtained from 12 newly diagnosed patients (Binet stage A). Peripheral blood mononuclear cells from B-CLL patients were isolated by Ficoll-Hypaque density-gradient centrifugation and the proportion of CD5/CD19/CD23 triple positive B cells in the suspension was determined by direct immunofluorescence performed using a FACS-sort flow cytometer with antibodies to: CD19 FITC/PE, CD23 PE and CD5 Cy-Chrome. If B-CLL cells were less than 90%, T cells, NK cells and monocytes were removed by negative selection using CD3, CD56, CD16, and CD14 monoclonal antibody treatment followed by magnetic beads. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 40 micrograms of fragmented biotin-labelled DNA were hybridized on GeneChip Human Mapping 50K XbaI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChipÂ® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. Genomic Smoothing analysis was performed by using the smoothing window of 1 Mb, and inferred copy number states were derived from a Hidden Markov Model (HMM) based algorithm implemented in CNAT 4.0.1.

Dataset Information

Integrated genomics approach to detect allelic imbalances in multiple myeloma, SNP data

Publications

A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide gene dosage effect.

Similar Datasets

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