Unknown,Transcriptomics,Genomics,Proteomics

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Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-hyperdiploid subtype

ABSTRACT: Currently, multiple myeloma (MM) patients are broadly grouped into a non-hyperdiploid Group (nh-MM), highly enriched for IgH translocations, or into a hyperdiploid Group (h-MM), which is typically characterized by trisomies of some odd-numbered chromosomes. We compared the miRNA expression profiles of these two groups and we identified 16 miRNAs that were downregulated in the h-MM group, relative to the nh-MM group. We found that target genes of the most differentially expressed miRNAs are directly involved in the pathogenesis of MM; specifically, the inhibition of hsa-miR-425, hsa-miR-152 and hsa-miR-24, which are all downregulated in h-MM, leads to the overexpression of CCND1, TACC3, MAFB, FGFR3 and MYC, which are the also the oncogenes upregulated by the most frequent IgH chromosomal translocations occurring in nh-MM. Importantly, we showed that the downregulation of these specific miRNAs and the upregulation of their targets also occur simultaneously in primary cases of h-MM. These data provide further evidence on the unifying role of cyclin C pathways deregulation as the key mechanism involved in the development of both groups of MM. Finally, they establish the importance of miRNA deregulation in the context of MM, thereby opening up the potential for future therapeutic approaches based on this molecular mechanism. miRNA expression profiling: The discovery series was composed of 53 CD138-positive de novo primary cases of Multiple Myeloma, of which 36 were classified as nh-MM and 17 as h-MM. Also included in this first analysis were 7 MM cell lines, six (JJN3, L363, OPM-2, K620, KMS28BM, KMS28PE) representing the nh-MM subtype and one (OH-2) as the model for h-MM. All samples, primary cases and cell lines, were labeled and hybridized in duplicate to the ‘8-pack’ Human miRNA Oligo Microarray G4470A (Agilent Technologies). We differentially expressed miRNA expression between the nh-MM and the h-MM subtypes were identified by standardized bioinformatics methods.

ORGANISM(S): Homo sapiens

SUBMITTER: Ana Rio-Machin

PROVIDER: E-GEOD-40308 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-hyperdiploid subtype.

Rio-Machin A A Ferreira B I BI Henry T T Gómez-López G G Agirre X X Alvarez S S Rodriguez-Perales S S Prosper F F Calasanz M J MJ Martínez J J Fonseca R R Cigudosa J C JC

Leukemia 20121022 4

Currently, multiple myeloma (MM) patients are broadly grouped into a non-hyperdiploid (nh-MM) group, highly enriched for IgH translocations, or into a hyperdiploid (h-MM) group, which is typically characterized by trisomies of some odd-numbered chromosomes. We compared the micro RNA (miRNA) expression profiles of these two groups and we identified 16 miRNAs that were downregulated in the h-MM group, relative to the nh-MM group. We found that target genes of the most differentially expressed miRN ...[more]

PMID: 23174883

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Project description:Karyotypic instability, including numerical and structural chromosomal aberrations, represents a distinct feature of multiple myeloma (MM). 40-50% of patients displayed hyperdiploidy, defined by recurrent trisomies of non-random chromosomes. To characterize hyperdiploid (H) and nonhyperdiploid (NH) MM molecularly, we analyzed the gene expression profiles of 66 primary tumors, and used FISH to investigate the major chromosomal alterations. The differential expression of 225 genes mainly involved in protein biosynthesis, transcriptional machinery and oxidative phosphorylation distinguished the 28 H-MM from the 38 NH-MM cases. The 204 upregulated genes in H-MM mapped mainly to the chromosomes involved in hyperdiploidy, and the29% up-regulated genes in NH-MM mapped to 16q. The identified transcriptional fingerprint was robustly validated on a publicly available gene expression dataset of 64 MM cases; and the global expression modulation of regions on the chromosomes involved in hyperdiploidy was verified using a self-developed non-parametric statistical method. We showed that H-MM could be further divided into two distinct molecular and transcriptional entities, characterized by the presence of trisomy 11 and 1q-extracopies/chromosome 13 deletion, respectively. Our data reinforce the importance of combining molecular cytogenetics and gene expression profiling to define a genomic framework for the study of MM pathogenesis and clinical management. Experiment Overall Design: This series of microarray experiments contains the gene expression profiles of purified plasma cells (PCs) obtained from 102 newly diagnosed multiple myeloma (MM). 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 and quantile-quantile normalised.

Project description: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.

Project description:The identification of deregulated miRNA in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In the present study, we take virtue of in silico integrative genomics analysis to generate an unprecedented global view of the transcriptional regulatory networks modulated in MM to define microRNAs impacting in regulatory circuits with potential functional and clinical relevance. miRNA and gene expression profiles in two large representative MM datasets, available from retrospective and prospective clinical trials and encompassing a total of 249 patients at diagnosis, were analyzed by means of two robust computational procedure to identify (i) relevant miRNA/transcription factors/target gene circuits in the disease and (ii) highly modulated miRNA-gene networks in those pathways enriched with miRNA-target gene interactions in specific MM subgroups. The analysis reinforced the pivotal role the miRNA cluster miR-99b/let-7e/miR-125a, specifically deregulated in MM patients with t(4;14) translocation, and disentangled its major relationships with transcriptional relevance. Integrated pathway analyses performed on the expression data of the MM patients stratified according to t(4;14) further allowed to define the pathway composed by the interactions that mainly characterize this MM subset and unravel connected pathways with putative role in the tumor biology. miRNA and transcripts expression data were analyzed using MAGIA2, to identify mixed circuits (triplets) involving miRNA/gene/transcription factor (TF; http://gencomp.bio.unipd.it/magia2/), as previously described [Bisognin A et al., 2012, Nucl Acid Res]. Specifically, Targetscan was used as target prediction algorithm, and Pearson coefficient was used to measure relationships between microRNA and target mRNA expression profiles. Only the most variable 75% genes according to the coefficient of variation were considered. Lower threshold for absolute correlation coefficients within circuits was set to 0.2; 0.4 was used for miRNA/target binary relationships. Micrographite pipeline allows integrating pathway topologies with predicted and validated miRNA-target interactions, to perform integrated analyses of miRNA and gene expression profiles, for the identification of modulated regulatory circuits involved in the disease in terms of both expression variations and differential strength of inferred interactions [Calura E et al., 2014, Nucl Acid Res]. Micrographite has two steps: i) the extension of pathway annotation using miRNA-target interaction and ii) recursive topological pathway analysis on these networks. We considered network topologies derived from KEGG database by Graphite package [Sales G et al., 2012, BMC Bioinformatics] and miRNA-target gene interactions identified by the above-described MAGIA2 analysis. Specifically, a miRNA was added to a pathway-derived network only if one (or more) of its validated or predicted target genes is a pathway component. Then, a modified recursive version of CliPPER topological pathway analysis [Martini P et al., 2013; Nucl Acid Res] was applied to the composite network, as previously described [Calura E et al., 2014, Nucl Acid Res] in order to identify the most important and non-redundant circuit modulated across groups. Briefly, (i) in the first step, the most significant pathways were selected using P<0.1 as cut-off value for significance; (ii) for each dataset, the upper-scored 10th percentile of the portion of these previously selected pathways (i.e. paths, calculated over a 10,000-permutation step) mostly associated with phenotype were selected; and (iii) for each dataset a meta-pathway was assembled using the paths extracted from previous step and finally re-analyzed. GSE73452 and GSE73454 Samples with the same patient number represent the same sample, profiled using two different Platforms.

Dataset Information

Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-hyperdiploid subtype

Publications

Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-hyperdiploid subtype.

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