MiRNA expression signatures in multiple myeloma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE125363 | GEO | 2020/01/24
REPOSITORIES: GEO
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Project description:In the present study, the gene expression profiling was carried out to identify the gene targets affected by miRNAs deregulated in multiple myeloma. A gene expression signature was generated for 45 patients of multiple myeloma as compared to controls (Pooled from 10 Hodgkin's disease samples).
2020-01-24 | GSE125361 | GEO
Project description:miRNA profiling in multiple myeloma - microRNAs represent a class of noncoding regulators of gene expression implicated in several biological and pathophysiological processes, including cancer. We investigate here their role in multiple myeloma using miChip-arrays interrogating 559 miRNAs in 92 purified myeloma-, MGUS-, normal plasma cell- and myeloma cell line samples. Impact on gene expression is assessed by Affymetrix U133 2.0 DNA-microarrays in 741 samples including two cohorts of 332 and 345 myeloma patients; chromosomal aberrations are assessed by iFISH, survival for 247 and 345 patients undergoing up-front high-dose therapy and autologous stem cell transplantation. Compared to normal plasma cells, 67/559 (12%) miRNAs are differentially expressed with fold changes of 4.6 to -3.1 in myeloma-, 20 (3.6%) in MGUS-samples, and three (0.5%) between MGUS- and myeloma-samples. Expression of miRNAs is associated with biological and pathophysiological parameters, i.e. proliferation, chromosomal aberrations, e.g. t(4;14), tumor mass, and gene expression-based high-risk scores. This holds true for target-gene signatures of regulated mRNAs. miRNA-expression confers prognostic significance for event-free (72/559) and overall survival (69/559), as do respective target-gene signatures. In conclusion, the miRNome of myeloma confers a pattern of small changes of individual miRNAs compared to normal plasma cells impacting on gene expression, biological functions, and survival.
2014-01-09 | E-MTAB-1363 | biostudies-arrayexpress
Project description: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.
2008-06-15 | E-GEOD-6477 | biostudies-arrayexpress
Project description:Gene expression signatures in multiple myeloma
| PRJNA521958 | ENA
Project description:miRNA expression signatures in multiple myeloma
| PRJNA515993 | ENA
Project description:Myeloma is a heterogeneous disease. In this work we used global microRNA profiling to classify clinical samples from UK MRC Myeloma IX, and developed a microRNA-based M-bM-^@M-^\outcome classifierM-bM-^@M-^] for risk stratification. Global microRNA expression profiling was carried out in 163 newly diagnosed samples from CD138+ cell selection
2013-07-31 | E-GEOD-41276 | biostudies-arrayexpress
Project description:The objective of this study is to identify genes involved in the pathogenesis of multiple myeloma (MM). In this study, we performed gene expression profiling of a total of 29 samples consisting of 19 clinical specimens, 7 myeloma cell lines and 3 normal samples. The microarray data were analysed by GeneSpring Software v14.9. A total of 5124 DEGs were identified in MM group vs control group (fold change≥2.0; P<0.05). Out of 5124 DEGs, 2696 and 2428 genes were up-regulated and down-regulated, respectively in MM group compared to the normal control group.
2022-07-20 | GSE72213 | GEO
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.
2009-05-16 | GSE16121 | GEO
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.
2010-09-29 | E-GEOD-24371 | biostudies-arrayexpress