Dataset Information

Molecular classification of multiple myeloma

ABSTRACT: PURPOSE. The deregulation of CCND1, CCND2 and CCND3 genes represents a common event in multiple myeloma (MM). The recently proposed TC classification grouped MM patients into five classes on the basis of their cyclins D expression profiles and the presence of the main translocations involving the immunoglobulin heavy-chain locus (IGH) at 14q32. In this study, we provide a molecular characterization of the identified TC groups. MATERIALS AND METHODS. The gene expression profiles of purified plasma cells from 50 MM cases were used to stratify the samples into the five TC classes and identify their transcriptional fingerprints. The cyclin D expression data were validated by means of real-time quantitative PCR analysis; fluorescence in-situ hybridization was used to investigate the cyclin D loci arrangements, and to detect the main IGH translocations and the chromosome 13q deletion. RESULTS. Class-prediction analysis identified 112 probe sets as characterizing the TC1, TC2, TC4 and TC5 groups, whereas the TC3 samples showed heterogeneous phenotypes and no marker genes. The TC2 group, which showed extra copies of the CCND1 locus and no IGH translocations or the chromosome 13q deletion, was characterized by the overexpression of genes involved in protein biosynthesis at translational level. A meta-analysis of published datasets validated the identified gene expression signatures. CONCLUSIONS. Our data contribute to the understanding of the molecular and biological features of distinct MM subtypes. The identification of a distinctive gene expression pattern in TC2 patients may improve risk stratification and indicate novel therapeutic targets. Keywords: other

ORGANISM(S): Homo sapiens

PROVIDER: GSE2912 | GEO | 2005/09/01

SECONDARY ACCESSION(S): PRJNA92601

REPOSITORIES: GEO

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Project description:PURPOSE. The deregulation of CCND1, CCND2 and CCND3 genes represents a common event in multiple myeloma (MM). The recently proposed TC classification grouped MM patients into five classes on the basis of their cyclins D expression profiles and the presence of the main translocations involving the immunoglobulin heavy-chain locus (IGH) at 14q32. In this study, we provide a molecular characterization of the identified TC groups. MATERIALS AND METHODS. The gene expression profiles of purified plasma cells from 50 MM cases were used to stratify the samples into the five TC classes and identify their transcriptional fingerprints. The cyclin D expression data were validated by means of real-time quantitative PCR analysis; fluorescence in-situ hybridization was used to investigate the cyclin D loci arrangements, and to detect the main IGH translocations and the chromosome 13q deletion. RESULTS. Class-prediction analysis identified 112 probe sets as characterizing the TC1, TC2, TC4 and TC5 groups, whereas the TC3 samples showed heterogeneous phenotypes and no marker genes. The TC2 group, which showed extra copies of the CCND1 locus and no IGH translocations or the chromosome 13q deletion, was characterized by the overexpression of genes involved in protein biosynthesis at translational level. A meta-analysis of published datasets validated the identified gene expression signatures. CONCLUSIONS. Our data contribute to the understanding of the molecular and biological features of distinct MM subtypes. The identification of a distinctive gene expression pattern in TC2 patients may improve risk stratification and indicate novel therapeutic targets. Experiment Overall Design: This series of microarray experiments contains the gene expression profiles of purified plasma cells (PCs) obtained from 50 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 hybridized to the Affymetrix HG-U133A chip following the manufacturer's instructions.

Project description: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.

Project description:MicroRNAs are small RNA species that regulate gene expression post-transcriptionally and are aberrantly expressed in many cancers including lymphoma. However, the role of microRNAs in the pathogenesis of multiple myeloma (MM) is poorly understood. We therefore elucidated the complete miRNome of purified tumor (CD138+) cells from 33 patients with MM, 5 patients with monoclonal gammopathy of undetermined significance (MGUS) and 9 disease controls. Unsupervised cluster analysis revealed that MM samples have a distinct microRNA expression profile. The majority of microRNAs aberrantly expressed in MM (109/129) were up-regulated. A comparison of these microRNAs with those aberrantly expressed in other B-cell and T-cell lymphomas revealed a surprising degree of similarity (~40%) suggesting the existence of a common lymphoma microRNA signature. We identified 39 microRNAs associated with the pre-malignant condition MGUS. Twenty-three (59%) of these were also aberrantly expressed in MM suggesting common microRNA expression events in MM progression. MM is characterized by multiple chromosomal abnormalities of varying prognostic significance. We identified specific microRNA signatures associated with the most common IgH translocations (t(4;14) and t(11;14)) and del(13q). Expression levels of these microRNAs were distinct between the genetic subtypes (by cluster analysis) and correctly predicted these abnormalities in >85% of cases using the support vector machine algorithm. Additionally, we identified microRNAs associated with light chain only myeloma, as well as IgG and IgA-type MM. Finally, we identified 32 microRNAs associated with event-free survival (EFS) in MM, ten of which were significant by univariate (logrank) survival analysis. In summary, this work has identified aberrantly expressed microRNAs associated with the diagnosis, pathogenesis and prognosis of MM, data which will prove an invaluable resource for understanding the role of microRNAs in this devastating disease.

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Molecular classification of multiple myeloma

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