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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

View Samples
accession-icon SRP155901
KLF4 as a rheostat of osteolysis and osteogenesis in prostate tumors in the bone
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We previously found that KLF4, a gene highly expressed in adult prostate stem cells, blocks the progression of indolent intraepithelial prostatic lesions into aggressive and rapidly growing tumors. To test whether this anti-cancer effect of KLF4 can also prevent prostate cancer-induced damage to the bone, we ablated KLF4 in human PC3 prostate cancer cells using CRISPR/Cas9-mediated genome editing and compared their behavior to null cells transduced with a DOX inducible KLF4 expression system. KLF4 re-expression inhibited growth of PC3 null cells in monolayer and as colonies in soft agar in a dose-dependent manner. When injected into the mouse femurs, PC3 null cells proliferated rapidly, forming very large, invasive and osteolytic tumors. Induction of KLF4 expression in PC3 null cells immediately after their intra-femoral inoculation blocked the development of tumors while preserving the normal bone architecture. KLF4 re-expression in established PC3 bone tumors inhibited osteolytic effects of PC3 null cells, preventing bone fractures and inducing a significant osteogenic response with regions of new bone formation. Transcriptome analyses of PC3 cells with no or high KLF4 expression revealed KLF4-dependent osteolytic or osteogenic transcriptional programs, respectively. Importantly, these KLF4-dependent functions significantly overlapped with metastatic prostate cancers in patients. Overall design: Uninfected PC3 KLF4 wild-type cells and uninfected PC3 KLF4 null cells were grown for 48 hours and collected for RNA extraction. Another cohort of PC3 KLF4 null cells was infected with lentiviruses expressing a DOX inducible KLF4 expression construct (BFP-T2A-hKLF4) or the control empty vector (BFP-T2A). After 48 hours, DOX (10 ng/ml) was added to the culture medium to induce KLF4 expression. Control and KLF4-overexpressing cells were collected for RNA extraction after a 48-hour incubation with DOX. Total RNA was extracted using the RNeasy kit (Qiagen, CA, USA). RNA-Seq libraries were prepared with the TruSeq sample preparation kit (Illumina, CA, USA).

Publication Title

KLF4 as a rheostat of osteolysis and osteogenesis in prostate tumors in the bone.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

View Samples
accession-icon GSE70323
Reconstruction of microRNA/genes transcriptional regulatory networks of multiple myeloma through in silico integrative genomics analysis
  • organism-icon Homo sapiens
  • sample-icon 246 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

Disentangling the microRNA regulatory milieu in multiple myeloma: integrative genomics analysis outlines mixed miRNA-TF circuits and pathway-derived networks modulated in t(4;14) patients.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject

View Samples
accession-icon GSE70319
Reconstruction of microRNA/genes transcriptional regulatory networks of multiple myeloma through in silico integrative genomics analysis [MM, gene]
  • organism-icon Homo sapiens
  • sample-icon 93 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The identification of deregulated miRNA in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In the present study, we take virtue of in silico integrative genomics analysis to generate an unprecedented global view of the transcriptional regulatory networks modulated in MM to define microRNAs impacting in regulatory circuits with potential functional and clinical relevance. miRNA and gene expression profiles in two large representative MM datasets, available from retrospective and prospective clinical trials and encompassing a total of 249 patients at diagnosis, were analyzed by means of two robust computational procedure to identify (i) relevant miRNA/transcription factors/target gene circuits in the disease and (ii) highly modulated miRNA-gene networks in those pathways enriched with miRNA-target gene interactions in specific MM subgroups. The analysis reinforced the pivotal role the miRNA cluster miR-99b/let-7e/miR-125a, specifically deregulated in MM patients with t(4;14) translocation, and disentangled its major relationships with transcriptional relevance. Integrated pathway analyses performed on the expression data of the MM patients stratified according to t(4;14) further allowed to define the pathway composed by the interactions that mainly characterize this MM subset and unravel connected pathways with putative role in the tumor biology.

Publication Title

Disentangling the microRNA regulatory milieu in multiple myeloma: integrative genomics analysis outlines mixed miRNA-TF circuits and pathway-derived networks modulated in t(4;14) patients.

Sample Metadata Fields

Disease, Disease stage

View Samples
accession-icon SRP131125
A compendium of long non-coding RNAs transcriptional fingerprint in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Multiple myeloma (MM) is a malignant proliferation of bone marrow plasma cells (PCs) characterized by highly heterogeneous genetic background and clinical course, and whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis, cancer metastasis and invasion. Although still in its infancy, the knowledge of the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. Herein, we assessed the lncRNAs expression profiling by RNA-sequencing in a cohort of 30 MM patients, aimed at defining a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. We identified 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship. Overall design: Total RNA samples from highly purified plasma cells of 30 MM cases at onset

Publication Title

Expression Pattern and Biological Significance of the lncRNA ST3GAL6-AS1 in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject

View Samples
accession-icon GSE73452
Reconstruction of microRNA/genes transcriptional regulatory networks of multiple myeloma through in silico integrative genomics analysis [PCL, gene]
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The identification of deregulated miRNA in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In the present study, we take virtue of in silico integrative genomics analysis to generate an unprecedented global view of the transcriptional regulatory networks modulated in MM to define microRNAs impacting in regulatory circuits with potential functional and clinical relevance. miRNA and gene expression profiles in two large representative MM datasets, available from retrospective and prospective clinical trials and encompassing a total of 249 patients at diagnosis, were analyzed by means of two robust computational procedure to identify (i) relevant miRNA/transcription factors/target gene circuits in the disease and (ii) highly modulated miRNA-gene networks in those pathways enriched with miRNA-target gene interactions in specific MM subgroups. The analysis reinforced the pivotal role the miRNA cluster miR-99b/let-7e/miR-125a, specifically deregulated in MM patients with t(4;14) translocation, and disentangled its major relationships with transcriptional relevance. Integrated pathway analyses performed on the expression data of the MM patients stratified according to t(4;14) further allowed to define the pathway composed by the interactions that mainly characterize this MM subset and unravel connected pathways with putative role in the tumor biology.

Publication Title

Disentangling the microRNA regulatory milieu in multiple myeloma: integrative genomics analysis outlines mixed miRNA-TF circuits and pathway-derived networks modulated in t(4;14) patients.

Sample Metadata Fields

Specimen part, Disease, Subject

View Samples
accession-icon GSE66618
Expression data from multiple myeloma cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Melphalan-induced modulation of miR-221/222 levels in MM cells. Melphalan-resistant U266/LR7 cells showed the highest induction of miR-221/222 after drug exposure. To study the transcriptome perturbation induced in MM cells following the combination of miR-221/222 inhibitors plus melphalan we used the whole gene expression data

Publication Title

A 13 mer LNA-i-miR-221 Inhibitor Restores Drug Sensitivity in Melphalan-Refractory Multiple Myeloma Cells.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE51649
The Fragile X Mental Retardation Protein (FMRP) controls diacylglycerol kinase in neurons
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

In this study, we sought to identify the mRNAs associated to FMRP protein in mouse cortical neuron using a cross linking immunoprecipitation and microarray (CLIP-microarray).

Publication Title

Fragile X Mental Retardation Protein (FMRP) controls diacylglycerol kinase activity in neurons.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE46261
Small nucleolar RNAs as new biomarkers in chronic lymphocytic leukemia
  • organism-icon Homo sapiens
  • sample-icon 228 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs are non-coding RNAs involved in the maturation of other RNA molecules. Alterations of sno/scaRNA expression may play a role in cancerogenesis. This study elucidates the patterns of sno/scaRNA expression in highly purified cells from 211 chronic lymphocytic leukemia (CLL) patients (Binet stage A) also in comparison with those of different normal B-cell subsets. CLLs display a sno/scaRNAs expression profile similar to normal memory, nave and marginal-zone B-cells, with the exception of a few down-regulated transcripts (SNORA31, -6, -62, and -71C). Our analyses also suggest some heterogeneity in the pattern of sno/scaRNAs expression which is apparently unrelated to the major biological (ZAP-70 and CD38), molecular (IGHV mutation) and cytogenetic markers. Moreover, we found that SNORA70F was significantly down-regulated in poor prognostic subgroups and this phenomenon was associated with the down-regulation of its host gene COBLL1. Finally, we generated an independent model based on SNORA74A and SNORD116-18 expression, which appears to distinguish two different prognostic CLL groups. These data extend the view of sno/scaRNAs deregulation in cancer and may contribute to discover novel biomarkers associated with the disease and potentially useful to predict the clinical outcome of early stage CLL patients.

Publication Title

Small nucleolar RNAs as new biomarkers in chronic lymphocytic leukemia.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE108824
Drugging the lncRNA MALAT1 via LNA gapmeR ASO inhibits gene expression of proteasome subunits and triggers anti-multiple myeloma activity
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The biological role and therapeutic potential of long non-coding RNAs (lncRNAs) in multiple myeloma (MM) are still to be investigated. Here, we studied the functional significance and the druggability of the oncogenic lncRNA MALAT1 in MM. Targeting MALAT1 by novel LNA-gapmeR anti-sense oligonucleotide antagonized MM cell proliferation and triggered apoptosis both in vitro and in vivo in a murine xenograft model of human MM. Of note, antagonism of MALAT1 dowmodulated the two major transcriptional activators of proteasome subunit genes, namely NRF1 and NRF2, and resulted in reduced trypsin, chymotrypsin and caspase-like proteasome activities and in accumulation of polyubiquitinated proteins. NRF1 and NRF2 decrease upon MALAT1-targeting was due to transcriptional activation of their negative regulator KEAP1, and resulted in reduced expression of anti-oxidant genes and increased ROS levels. In turn, NRF1 promoted MALAT1 expression thus establishing a positive feedback loop. Our findings demonstrate a crucial role of MALAT1 in the regulation of the proteasome machinery, and provide proof-of-concept that its targeting is a novel powerful option for the treatment of MM.

Publication Title

Drugging the lncRNA MALAT1 via LNA gapmeR ASO inhibits gene expression of proteasome subunits and triggers anti-multiple myeloma activity.

Sample Metadata Fields

Specimen part, Cell line, Time

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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