Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human hyperdiploid multiple myeloma compared to non hyperdiploid multiple myeloma

ABSTRACT: Multiple myeloma is a relatively common B-cell malignancy that is currently incurable. Certain recurrent genetic abnormalities characteristics of different genetic subtypes have been described. Hyperdiploid myeloma characterized by recurrent trisomies is the most common genetic subtypes. However little is know about it's biology. Another common genetic abnormality is chromosome 13 deletion which is also associated with inferior prognosis. This abnormality is already present at the pre-malignant MGUS stage and is clonally selected with disease progression. Although it is biologically and clinically important the molecular consequence of chromosome 13 deletion is unknown. Experiment Overall Design: Hyperdiploid myeloma was identified using FISH. The gene expression profile of hyperdiploid MM is compared to that of non-hyperdiploid myeloma to identify differentially expressed genes. Molecular heterogeneity within H-MM is analyzed using unsupervised techniques. The distinctive subgroups identified are also tested in MGUS/SMM and NH-MM. The clinical relevance of these subtypes of hyperdiploid myeloma is then analyzed by correlating with relevant clinical information. Chromosome 13 deleted and undeleted MM are identified by FISH and their gene expression profile compared to identify molecular signature.

ORGANISM(S): Homo sapiens

SUBMITTER: Rafael Fonseca

PROVIDER: E-GEOD-6477 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Molecular dissection of hyperdiploid multiple myeloma by gene expression profiling.

Chng Wee J WJ Kumar Shaji S Vanwier Scott S Ahmann Greg G Price-Troska Tammy T Henderson Kim K Chung Tae-Hoon TH Kim Seungchan S Mulligan George G Bryant Barbara B Carpten John J Gertz Morie M Rajkumar S Vincent SV Lacy Martha M Dispenzieri Angela A Kyle Robert R Greipp Philip P Bergsagel P Leif PL Fonseca Rafael R

Cancer research 20070401 7

Hyperdiploid multiple myeloma (H-MM) is the most common form of myeloma. In this gene expression profiling study, we show that H-MM is defined by a protein biosynthesis signature that is primarily driven by a gene dosage mechanism as a result of trisomic chromosomes. Within H-MM, four independently validated patient clusters overexpressing nonoverlapping sets of genes that form cognate pathways/networks that have potential biological importance in multiple myeloma were identified. One prominent ...[more]

PMID: 17409404

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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. Plasma cells (CD138+) cells were purified from bone marrow samples of 33 patients with MM, 5 patients with monoclonal gammopathy of undetermined significance (MGUS) and 9 disease controls.

Project description:We have used genome-wide methylation microarrays to analyze differences in CpG methylation patterns in cells relevant to the pathogenesis of myeloma plasma cells, including B cells, normal plasma cells, MGUS, presentation myeloma, and plasma cell leukemia (PCL). We show that methylation patterns in these cell types are capable of distinguishing non-malignant from malignant cells and that the main reason for this difference is hypomethylation of the genome at the transition from MGUS to presentation myeloma. In addition, gene-specific hypermethylation was evident at the myeloma stage. Differential methylation was also evident at the transition from myeloma to PCL with re-methylation of the genome, specifically of genes involved in cell-cell signaling and cell adhesion, which may contribute to independence from the bone marrow microenvironment. There was a high degree of methylation variability within presentation myeloma samples and this was associated with the cytogenetic differences between samples. More specifically, we found that methylation subgroups were defined by translocations and hyperdiploidy, with t(4;14) myeloma having the largest impact on DNA methylation. Two groups of hyperdiploid samples were identified, based on unsupervised clustering, which had an impact on overall survival. Overall, DNA methylation has a large impact on disease progression and on myeloma cytogenetic subgroups. Bone marrow aspirates were obtained after informed consent. B cells (n=6) from normal individuals were selected from peripheral blood using CD19. Plasma cells (PC) from non-myeloma patients (normal plasma cell controls, n=3) as well as MGUS (n=4) and presentation myeloma patients (n=161) were selected to a purity of >90% using CD138 microbeads and magnet-assisted cell sorting (Miltenyi Biotech, Bisley, UK). Samples from PCL patients (n=7) were not CD138 selected but contained >90% plasma cell infiltration as determined by microscopy. In order to achieve a sufficient quantity of DNA some normal plasma cell control samples were pooled.

Dataset Information

Transcription profiling of human hyperdiploid multiple myeloma compared to non hyperdiploid multiple myeloma

Publications

Molecular dissection of hyperdiploid multiple myeloma by gene expression profiling.

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