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accession-icon GSE16122
A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 158 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Mapping 50K Xba240 SNP Array (mapping50kxba240)

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

Publication Title

A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide gene dosage effect.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE13591
Integrated genomics approach to detect allelic imbalances in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 158 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

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.

Publication Title

A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide gene dosage effect.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE39683
Small nucleolar RNAs and small Cajal body-specific RNAs show distinct transcriptional profiles in the context of the molecular heterogeneity of multiple myeloma.
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs (scaRNAs) are non-coding RNAs involved in the maturation of other RNA molecules and generally located in the introns of host genes. It is now emerging that altered sno/scaRNAs expression may play a pathological role in cancer. This study elucidates the patterns of sno/scaRNAs expression in multiple myeloma (MM), by profiling puri?ed malignant plasma cells from 55 MMs, 8 secondary plasma cell leukemias (sPCL) and 4 normal controls. Overall, a global sno/scaRNAs down-regulation was found in MMs and at more extent in sPCLs compared to normal plasma cells. Whereas SCARNA22 resulted the only sno/scaRNA characterizing the TC4 MM, TC2 group displayed a distinct sno/scaRNA signature overexpressing members of SNORD115 and SNORD116 families located in a region finely regulated by imprinting mechanism at 15q11. However, the imprinting center resulted overall hypomethylated in MMs independently of the SNORD115 and SNORD116 expression levels. Finally, integrative analyses with available gene expression and genome-wide data revealed the occurrence of significant sno/scaRNAs/host genes co-expression and the putative influence of allelic imbalances on specific snoRNAs expression. Our data extend the current view of sno/scaRNAs deregulation in cancer and add novel information into the bio-molecular complexity of plasma cell dyscrasias.

Publication Title

The expression pattern of small nucleolar and small Cajal body-specific RNAs characterizes distinct molecular subtypes of multiple myeloma.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE66293
Assessment of MEK-ERK pathway targeting by BRAF, NRAS and KRAS gene mutations in plasma cell dyscrasias
  • organism-icon Homo sapiens
  • sample-icon 145 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Molecular spectrum of BRAF, NRAS and KRAS gene mutations in plasma cell dyscrasias: implication for MEK-ERK pathway activation.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE66291
Assessment of MEK-ERK pathway targeting by BRAF, NRAS and KRAS gene mutations in plasma cell dyscrasias [Patient samples]
  • organism-icon Homo sapiens
  • sample-icon 141 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Multiple myeloma (MM) is a malignant disorder characterized by the clonal proliferation of plasma cells (PCs) in the bone marrow (BM). The genetic background and clinical course of the disease are largely heterogeneous, and MM pathophysiology ranges from the premalignant condition of monoclonal gammopathy of undetermined significance (MGUS) to smoldering MM, symptomatic MM, and extramedullary MM/plasma cell leukemia (PCL). Recent genome-wide sequencing efforts have provided the rationale for molecularly aimed treatment approaches, identifying mutations that can be specifically targeted, such as those in the mitogen-activated protein kinase (MAPK) pathway, which represent the most prevalent mutations in MM. Among these, mutations affecting BRAF gene, detected in 4-15% of patients, are of potential immediate clinical relevance due to the availability of effective inhibitors of this serine-threonine kinase which are in fact being explored also in myeloma.

Publication Title

Molecular spectrum of BRAF, NRAS and KRAS gene mutations in plasma cell dyscrasias: implication for MEK-ERK pathway activation.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE66292
Assessment of MEK-ERK pathway targeting by BRAF, NRAS and KRAS gene mutations in plasma cell dyscrasias [U266 human myeloma cell line]
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Multiple myeloma (MM) is a malignant disorder characterized by the clonal proliferation of plasma cells (PCs) in the bone marrow (BM). The genetic background and clinical course of the disease are largely heterogeneous, and MM pathophysiology ranges from the premalignant condition of monoclonal gammopathy of undetermined significance (MGUS) to smoldering MM, symptomatic MM, and extramedullary MM/plasma cell leukemia (PCL). Recent genome-wide sequencing efforts have provided the rationale for molecularly aimed treatment approaches, identifying mutations that can be specifically targeted, such as those in the mitogen-activated protein kinase (MAPK) pathway, which represent the most prevalent mutations in MM. Among these, mutations affecting BRAF gene, detected in 4-15% of patients, are of potential immediate clinical relevance due to the availability of effective inhibitors of this serine-threonine kinase which are in fact being explored also in myeloma.

Publication Title

Molecular spectrum of BRAF, NRAS and KRAS gene mutations in plasma cell dyscrasias: implication for MEK-ERK pathway activation.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE16746
Genomic approach in B-cell Chronic Lymphocytic Leukemia: molecularly distinct subgroups of patients with 13q14 deletion
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

B-cell chronic lymphocytic leukemia (B-CLL) is characterized by a highly variable clinical course that reflects its heterogeneous genomic pattern. To better define molecular subtypes of the disease, we performed SNP and gene expression profiling microarray analyses in a panel of early stage (Binet A) patients. A clustering analysis of genomic profiles identified four significant groups mainly driven by del(13)(q14) and trisomy 12. Notably, patients with del(13)(q14) were grouped in two separate clusters based on the presence of a biallelic loss and the extension of the deletion. The shorter monoallelic deleted 13q14 region was found to be 635 kb in length, not encompassing the mir-15a/16-1 locus. Interestingly, the mir-15a and mir-16 expression was found to be significantly down-regulated only in patients with biallelic loss. Furthermore, a multiclass supervised analysis identified a different transcriptional signatures in the two genomic subgroups with del(13)(q14). Finally, an integrative approach identified 93 transcripts, mainly mapped to chromosome 12 and 13q12-q14.3, whose expression was significantly correlated with the DNA copy number. Overall, our data further support the notion that transcription deregulation in B-CLL could be mostly due to a gene dosage effect and underscore the presence of two distinct molecular types of 13q14 deleted patients with potential clinical relevance.

Publication Title

Integrative genomics analyses reveal molecularly distinct subgroups of B-cell chronic lymphocytic leukemia patients with 13q14 deletion.

Sample Metadata Fields

Sex, Specimen part, Disease

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accession-icon GSE11038
Molecular and transcriptional characterization of chromosome 17p loss in chronic lymphocytic leukemia
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Distinct genetic abnormalities such as TP53 deletion at 17p13.1, have been identified as having an adverse prognostic relevance in B-cell chronic lymphocytic leukemia (B-CLL). Conventional cytogenetic studies have shown that TP53 deletion in B-CLL is associated predominantly with 17p loss resulting from complex chromosomal rearrangements. We performed genome-wide DNA (SNPs arrays), fluorescence in situ hybridization (FISH) and gene expression profiling (GEP) analyses to investigate the significance of 17p loss in a panel of 71 genetically well-characterized B-CLLs in Binet stage A, 18 of which carried a TP53 monoallelic deletion. Combined SNP arrays and FISH approaches showed 17p loss in all of the TP53-deleted cases, with breakpoints scattered along the 17p11.2 region. Mutations in exons 5 to 9 of TP53 were found in 9/12 deleted samples. GEP of 60 B-CLLs, including 7 patients with 17p loss, identified 40 differentially expressed genes in 17p- versus 17p normal samples, 35 of which were down-regulated in 17p- tumors. The majority (30/35) of these transcripts, including putative tumor suppressor genes, mapped to 17p. Overall, these data indicate that, beside TP53 deletion, the concomitant loss of 17p arm may contribute to the strong negative prognostic impact known to be associated with this lesion in B-CLL.

Publication Title

Molecular and transcriptional characterization of 17p loss in B-cell chronic lymphocytic leukemia.

Sample Metadata Fields

Sex

View Samples
accession-icon GSE9992
Molecular and transcriptional characterization of chromosome 17p loss in chronic lymphocytic leukemia, experiment A
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Distinct genetic abnormalities such as TP53 deletion at 17p13.1, have been identified as having an adverse prognostic relevance in B-cell chronic lymphocytic leukemia (B-CLL). Conventional cytogenetic studies have shown that TP53 deletion in B-CLL is associated predominantly with 17p loss resulting from complex chromosomal rearrangements. We performed genome-wide DNA (SNPs arrays), fluorescence in situ hybridization (FISH) and gene expression profiling (GEP) analyses to investigate the significance of 17p loss in a panel of 71 genetically well-characterized B-CLLs in Binet stage A, 18 of which carried a TP53 monoallelic deletion. Combined SNP arrays and FISH approaches showed 17p loss in all of the TP53-deleted cases, with breakpoints scattered along the 17p11.2 region. Mutations in exons 5 to 9 of TP53 were found in 9/12 deleted samples. GEP of 60 B-CLLs, including 7 patients with 17p loss, identified 40 differentially expressed genes in 17p- versus 17p normal samples, 35 of which were down-regulated in 17p- tumors. The majority (30/35) of these transcripts, including putative tumor suppressor genes, mapped to 17p. Overall, these data indicate that, beside TP53 deletion, the concomitant loss of 17p arm may contribute to the strong negative prognostic impact known to be associated with this lesion in B-CLL.

Publication Title

Molecular and transcriptional characterization of 17p loss in B-cell chronic lymphocytic leukemia.

Sample Metadata Fields

Sex

View Samples
accession-icon GSE39925
Transcriptional characterization of a prospective series of primary plasma cell leukemia revealed genes associated with tumor progression and poorest outcome
  • organism-icon Homo sapiens
  • sample-icon 76 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

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.

Publication Title

Transcriptional characterization of a prospective series of primary plasma cell leukemia revealed signatures associated with tumor progression and poorer outcome.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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