Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Identification of MicroRNA Expression Patterns and a MicroRNAs/mRNA Regulatory Network in Multiple Myeloma

ABSTRACT: To date, little evidence of miRNA expression/deregulation in multiple myeloma (MM) has been reported. To characterize miRNA expression profiling of MM plasma cells (PCs) and integrate miRNA expression data with other molecular features of MM patients, global miRNA expression profiles were generated for PCs isolated from BM biopsies of 38 newly diagnosed MM, 2 plasma cell leukemia patients, and 3 healthy donors; the samples were also profiled for global gene expression, and nineteen of them underwent genome-wide DNA analysis using high-density SNP-microarrays. Differential miRNA expression patterns were mainly identified in association with the major IGH translocations: in particular, t(4;14) showed specific over-expression of let-7e, miR-125a-5p and miR-99b belonging to a cluster at 19q13.33. The occurrence of other lesions, such as 1q gain, 13q and 17p deletions, and hyperdiploidy, was less well characterized by specific miRNA signatures. Genome-wide analysis showed that some allelic imbalances led to the significantly altered expression of miRNAs located in the involved regions, such as let-7b at 22q13.31 loss and miR-142-3p at 17q22 gain. The integrative analysis based on computational target prediction, miRNA and mRNA profiling defined a network of putative functional miRNA-target regulatory relations supported by expression data. This series of microarray experiments contains the microRNA profiles of purified plasma cells (PCs) obtained from 3 normal donor (N), 38 multiple myeloma (MM) and 2 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. 500 nanograms of total RNA was processed in accordance with the manufacturer's protocols (Agilent Technologies) to generate Cy3-labeled RNA which were purified on chromatography columns (Micro Biospin 6, Bio-Rad, Hercules, CA) and hybridized on an Agilent microarray (G4470B) at 55Â°C for 17 hr in a rotating oven. Images at 5 um resolution were generated using an Agilent scanner G2505B. The Feature Extraction 9.5 software (Agilent Technologies) was used to obtain the raw microarray data. The human miRNAs included in the platform were annotated according to Sanger miRBase Release 12.0. After discarding non-human miRNAs, the data were normalized using the Aroma Light package for Bioconductor. To overcome scaling biases due to background subtraction, the data were converted to obtain positive values throughout the dataset, at a minimum value of 1. The global gene expression raw data used in this study was originally deposited as GSE13591 and renormalized for this study. The genome wide profile (DNA) analysis was originally deposited as GSE16121.

ORGANISM(S): Homo sapiens

SUBMITTER: Silvio Bicciato

PROVIDER: E-GEOD-17498 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Identification of microRNA expression patterns and definition of a microRNA/mRNA regulatory network in distinct molecular groups of multiple myeloma.

Lionetti Marta M Biasiolo Marta M Agnelli Luca L Todoerti Katia K Mosca Laura L Fabris Sonia S Sales Gabriele G Deliliers Giorgio Lambertenghi GL Bicciato Silvio S Lombardi Luigia L Bortoluzzi Stefania S Neri Antonino A

Blood 20091201 25

To date, little evidence of miRNA expression/deregulation in multiple myeloma has been reported. To characterize miRNA in the context of the major multiple myeloma molecular types, we generated miRNA expression profiles of highly purified malignant plasma cells from 40 primary tumors. Furthermore, transcriptional profiles, available for all patients, were used to investigate the occurrence of miRNA/predicted target mRNA pair anticorrelations, and the miRNA and genome-wide DNA data were integrate ...[more]

PMID: 19846888

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Project description:Primary plasma cell leukemia (pPCL) is a rare and very aggressive form of plasma cell dyscrasias. To date, no information of microRNA expression in pPCL has been reported. To investigate the role of miRNAs in pPCL, we analyzed global miRNA expression profiles of highly purified malignant plasma cells from 18 previously untreated patients included in a prospective clinical trial. MiRNA expression patterns were evaluated in the context of the molecular abnormalities of the disease and in comparison with a representative cohort of multiple myeloma (MM) patients. We identified a series of deregulated miRNAs in pPCL (42 up-regulated and 41 down-regulated) which may have a putative role in contributing to tumor progression in MM. Furthermore, we integrated miRNA and gene expression data with computational prediction of miRNA targets, finding that miRNAs differentially expressed between MM and pPCL could regulate genes with important functions in cancer. Overall, our study represents the first attempt to investigate the involvement of miRNAs in pPCL and may contribute to develop functional approaches to investigate the activity of deregulated miRNAs in aggressive forms of plasma cell dyscarsias and their possible role as novel therapeutic targets. This series of microarray experiments contains the microRNA profiles of purified plasma cells (PCs) obtained from 39 multiple myeloma (MM) and 18 primary plasma cell leukemia (pPCL) 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. 500 nanograms of total RNA was processed in accordance with the manufacturer's protocols (Agilent Technologies) to generate Cy3-labelled RNA, which were purified on chromatography columns (Micro Biospin 6, Bio-Rad, Hercules, CA) and then hybridized on an Agilent microarray (G4470B) at 55M-BM-!C for 17 hr in a rotating oven. Images at 5 um resolution were generated using an Agilent scanner G2505B. The Feature Extraction 10.7.3.1 software (Agilent Technologies) was used to obtain the microarray raw-data. The raw gTotalGeneSignal has been recalculated using the procedures described in Agilent Feature Extraction Software version 10.1 manual. Non-human probes, miRNAs flagged as M-CM-^RabsentM-CM-^S (i.e. expressed below background levels) throughout the whole dataset and miRNAs expired according to Sanger miRBase Release 15 (April 2010) were discarded, and a quantile normalization was applied on raw data using the aroma.light package for Bioconducor. The data were then converted to obtain positive values throughout the dataset, at a minimum value of 1, and log2 transformed.

Project description: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.

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Dataset Information

Identification of MicroRNA Expression Patterns and a MicroRNAs/mRNA Regulatory Network in Multiple Myeloma

Publications

Identification of microRNA expression patterns and definition of a microRNA/mRNA regulatory network in distinct molecular groups of multiple myeloma.

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