Patterns of miRNA expression in primary plasma cell leukemias: implications for tumor progression in multiple myeloma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE37053 | GEO | 2013/05/01
SECONDARY ACCESSION(S): PRJNA157835
REPOSITORIES: GEO
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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.
2013-05-01 | E-GEOD-37053 | biostudies-arrayexpress
Project description:Primary plasma cell leukemia (pPCL) is a highly aggressive plasma cell dyscrasia characterized by short remissions and very poor survival. Deletions of 17p13 are much more frequent in pPCL than in multiple myeloma (MM). Although the 17p deletion is associated with poor outcome and extramedullary disease in MM, its presence does not confer the degree of aggressiveness observed in pPCL. The comprehensive exploration of the transcriptome, including isoform expression and RNA splicing events, may provide novel information about biological differences between the two diseases carrying a 17p deletion. Transcriptomic studies were carried out with the Human Transcriptome Array in nine newly diagnosed pPCL and ten MM samples, all of which harbored the 17p deletion. Unsupervised cluster analysis clearly distinguished pPCL from MM samples. Indeed, 3,584 genes and 20,033 isoforms were found to be deregulated between pPCL and MM, most of which were underexpressed in pPCL. Pathway enrichment analysis at the gene and isoform levels revealed seven overlapping pathways mainly related to mRNA processing. There were 2,727 significantly deregulated isoforms of non-differentially expressed genes. Strangely enough, significant differences were observed in the expression of spliceosomal machinery components between pPCL and MM, in respect of the gene and isoform expression, and of the alternative splicing events. Furthermore, most of the deregulated exons have binding sites for most serine/arginine-rich proteins. In summary, transcriptome analysis revealed significant differences in the relative abundance of isoforms between pPCL and MM, even when they both had the 17p deletion. Importantly, the mRNA processing pathway including RNA splicing machinery emerged as one of the most remarkable mechanisms underlying the biological differences between the two entities.
2019-10-29 | GSE131216 | GEO
Project description:Plasma cell leukemia (PCL) is a rare form of plasma cell dyscrasia that presents either as a progression of previously diagnosed multiple myeloma (MM), namely secondary PCL (sPCL), or as the initial manifestation of disease, namely primary PCL (pPCL). Although presenting signs and symptoms include those seen in MM, pPCL is characterized by several aspects that clearly define more aggressive course. To provide insights into the biology of pPCL, we have investigated the transcriptional profiles of a cohort of 21 newly-diagnosed, homogeneously treated pPCL patients included in a multicenter prospective clinical trial. All but one pPCL had one of the main IGH translocations, whose associated transcriptional signatures resembled those observed in MM. A 503-gene signature was identified that distinguished pPCL from MM, from which emerged 28 genes whose trend in expression levels was found associated with the progressive stages of plasma cell dyscrasia in a large dataset of cases from multiple institutions, including samples from normal donors throughout PCL. The transcriptional pattern of the pPCL series was then evaluated in association with outcome. Three genes were identified having expression levels correlated with response to the first-line treatment with lenalidomide/dexamethasone, whereas a 27-gene signature was identified associated with overall survival independently of molecular alterations, hematological parameters and renal function. Overall, our data contribute to a fine dissection of pPCL and may provide novel insights into the molecular definition of a subgroup of high-risk pPCL.
2013-05-01 | GSE39925 | GEO
Project description:MicroRNAs (miRNAs) are a class of small non-coding single-stranded RNAs whose dysregulation of expression plays an important role in cancer development. Circulating miRNAs are novel biomarkers in several cancers. Thus, we explored whether the miRNAs in plasma could be useful clinical biomarkers for multiple myeloma (MM) patients. The expression levels of four miRNAs in plasma were upregulated while eight miRNAs were downregulated in MM patients compared with healthy controls according to microarray. MiRNA microarray was conducted to determine deregulated miRNAs in plasma of 9 MM patients and 7 healthy controls.
2014-01-16 | E-GEOD-54156 | biostudies-arrayexpress
Project description:Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM), which is associated with a very poor prognosis. Specific molecular patterns distinguish pPCL in comparison to MM and in relation to main genomic alterations. In the present study, a whole-genome methylation profiling analysis by high-density array revealed a global gene hypomethylation profile in pPCL. Lower methylation levels were particularly observed in the promoter and 5’ untranslated regions (5’UTR), whereas higher levels were evidenced in gene body or 3’ untranslated regions (3’UTR). CpG islands (CGI) resulted largely hypomethylated, whereas higher methylation levels were observed in CGI distal regions. Peculiar differential methylation patterns were identified in association to major chromosomal aberrations and DIS3 mutational status and involved genes playing roles in cell migration, bone metabolism, transcription regulation or DNA damage response. Finally, decreasing methylation levels were evidenced for few genes in association to MM disease progression, from healthy condition to MM and pPCL. Our data may provide new insights into the molecular characterization of pPCL patients, thus being potentially useful in the prognostic stratification or identification of novel molecular targets.
2018-10-10 | GSE104770 | GEO
Project description:Plasma cell leukemia (PCL) is a rare form of plasma cell dyscrasia that presents either as a progression of previously diagnosed multiple myeloma (MM), namely secondary PCL (sPCL), or as the initial manifestation of disease, namely primary PCL (pPCL). Although presenting signs and symptoms include those seen in MM, pPCL is characterized by several aspects that clearly define more aggressive course. To provide insights into the biology of pPCL, we have investigated the transcriptional profiles of a cohort of 21 newly-diagnosed, homogeneously treated pPCL patients included in a multicenter prospective clinical trial. All but one pPCL had one of the main IGH translocations, whose associated transcriptional signatures resembled those observed in MM. A 503-gene signature was identified that distinguished pPCL from MM, from which emerged 28 genes whose trend in expression levels was found associated with the progressive stages of plasma cell dyscrasia in a large dataset of cases from multiple institutions, including samples from normal donors throughout PCL. The transcriptional pattern of the pPCL series was then evaluated in association with outcome. Three genes were identified having expression levels correlated with response to the first-line treatment with lenalidomide/dexamethasone, whereas a 27-gene signature was identified associated with overall survival independently of molecular alterations, hematological parameters and renal function. Overall, our data contribute to a fine dissection of pPCL and may provide novel insights into the molecular definition of a subgroup of high-risk pPCL. This series of microarray experiments contains the gene expression profiles of purified plasma cells (PCs) obtained from 21 pPCL and 55 MM at diagnosis. PCs were purified from bone marrow samples using CD138 immunomagnetic microbeads according to the manufacturer's instructions (MidiMACS system, Miltenyi Biotec); the purity of the positively selected PCs was assessed by morphology and flow cytometry and was > 90% in all cases. 5.5 micrograms of single-stranded DNA target obtained from 100 ng of purified total RNA was fragmented and then labeled using the WT Terminal Labeling Kit according to the standard Affymetrix protocol (GeneChip¨ Whole Transcript (WT) Sense Target Labeling Assay Manual). The fragmented labeled single-stranded DNA target was hybridized for 16 hours and 30 minutes at 45¡C on GeneChip¨ Gene 1.0 ST array according to the standard Affymetrix protocol. Washing and scanning were performed using GeneChip System of Affymetrix (GeneChip Hybridization Oven 640, GeneChip Fluidics Station 450 and GeneChip Scanner 7G). Log2-transformed expression values were extracted from CEL files and normalized using NetAffx Transcript Cluster Annotations, Release 31 and robust multi-array average (RMA) procedure in Expression Console software (Affymetrix Inc.). Non-annotated transcript clusters were discarded. The expression values of transcript cluster ID specific for loci representing naturally occurring read-through transcriptions or mapped to more than one chromosomal location were summarized as median value for each sample. gene expression analysis of 21 primary Plasma Cell Leukemia and 55 multiple myeloma tumors
2013-05-01 | E-GEOD-39925 | biostudies-arrayexpress
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-11-09 | GSE106745 | GEO
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-11-09 | GSE106744 | GEO
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-02-10 | GSE87829 | GEO
Project description:The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNAs (ceRNAs) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed significant correlation between lncRNA and miRNA expression levels, we identified 10 lncRNA-miRNA relationships suggestive of novel ceRNA network with relevance in MM.
2017-02-10 | GSE87828 | GEO