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accession-icon GSE118985
The pattern of Mesenchymal stem cell expression is an independent marker of outcome in multiple myeloma
  • organism-icon Homo sapiens
  • sample-icon 750 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Mesenchymal stem cells (MSCs) are an essential component of the bone marrow (BM) microenvironment and have shown to support cancer evolution in multiple myeloma (MM). Despite the increasing evidence that MM MSCs differ from their healthy counterparts, little knowledge exists as to whether MSCs independently influence disease outcome. The aim of the present study was to determine the importance of MSCs in disease progression and outcome in MM.

Publication Title

The Pattern of Mesenchymal Stem Cell Expression Is an Independent Marker of Outcome in Multiple Myeloma.

Sample Metadata Fields

Specimen part, Disease, Subject

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accession-icon GSE5900
Gene Expression of Bone Marrow Plasma Cells from Healthy Donors (N=22), MGUS (N=44), and Smoldering Myeloma (N=12)
  • organism-icon Homo sapiens
  • sample-icon 68 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This series represents bone marrow aspirates from smoldering multiple myeloma patients

Publication Title

Gene-expression signature of benign monoclonal gammopathy evident in multiple myeloma is linked to good prognosis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE19554
Expression data from bone marrow of primary multiple myeloma patients
  • organism-icon Homo sapiens
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Drug resistance is a major obstacle in cancer therapy. The molecular mechanisms of drug resistance still remain largely elusive. Microarray analyses on paired primary myeloma samples at baseline and after therapy or at relapse showed that NEK2 was one of the most up-regulated genes in myeloma cells after high-dose chemotherapy or at relapse. By analyzing the published (> 2,500) microarrays and clinical datasets, we found that NEK2 expression is increased in many malignancies, and that high expression of NEK2 was associated with a shorter event-free and overall survival. Moreover, NEK2 expression was typically increased in tumors with aggressive subtype and advanced TNM stage. Our studies indicate that over-expressing NEK2 in cancer cells resulted in enhanced cell proliferation and drug resistance, whereas knockdown of NEK2 induced significant cancer cell death and growth inhibition. We found that NEK2 over-expression activates cell cycle progression and cell division through the stimulation of cell cycling genes CDC2/CCNB1 and PBK. Interestingly, NEK2-overexpression also activated the Wnt/-catenin signaling pathway. We conclude that NEK2 represents a predictor for drug resistance and poor prognosis in cancers and could be a potential target for cancer therapy.

Publication Title

NEK2 induces drug resistance mainly through activation of efflux drug pumps and is associated with poor prognosis in myeloma and other cancers.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE38092
Diet-Induced Obesity Reprograms the Inflammatory Response of the Murine Lung to Inhaled Endotoxin
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

To identify key biological pathways that define susceptibility factors for pulmonary infection during obesity, diet-induced obese (DIO) and regular weight (RW) C57BL/6 mice were exposed to 0.5 g/L inhaled lipopolysaccharide (LPS) for 1 hr/d for 4 days over a period of 2 weeks.

Publication Title

Diet-induced obesity reprograms the inflammatory response of the murine lung to inhaled endotoxin.

Sample Metadata Fields

Specimen part

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accession-icon GSE13005
Macrophage response to silica nanoparticles
  • organism-icon Mus musculus
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

Using a macrophage cell line, we demonstrate the ability of amorphous silica particles to stimulate inflammatory protein secretion and induce cytotoxicity. Whole genome microarray analysis of early gene expression changes induced by 10nm and 500nm particles showed that the magnitude of change for the majority of genes correlated more tightly with particle surface area than either particle mass or number. Gene expression changes that were size-specific were also identified, however the overall biological processes represented by all gene expression changes were nearly identical, irrespective of particle diameter. Our results suggest that on an equivalent nominal surface area basis, common biological modes of action are expected for nano- and supranano-sized silica particles.

Publication Title

Macrophage responses to silica nanoparticles are highly conserved across particle sizes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE76148
Genome wide comparison of the inducible transcriptomes of CAR, PXR and PPAR in primary human hepatocytes
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

To identify the CAR-, PXR- and PPAR-specific genome-wide expression changes, hepatocyte cultures from six individual donors were treated with the prototypical ligands for

Publication Title

Genomewide comparison of the inducible transcriptomes of nuclear receptors CAR, PXR and PPARα in primary human hepatocytes.

Sample Metadata Fields

Sex, Age

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accession-icon GSE82307
Clonal selection and double hit events involving tumor suppressor genes underlie relapse from chemotherapy: myeloma as a model
  • organism-icon Homo sapiens
  • sample-icon 65 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To elucidate the mechanisms underlying relapse from chemotherapy in multiple myeloma we performed a longitudinal study of 33 patients entered into Total Therapy protocols investigating them using gene expression profiling, high resolution copy number arrays and whole exome sequencing. The study illustrates the mechanistic importance of acquired mutations in known myeloma driver genes and the critical nature of bi-allelic inactivation events affecting tumor suppressor genes, especially TP53. The end result being resistance to apoptosis and increased proliferation rates, which drive relapse by Darwinian type clonal evolution. The number of copy number aberration changes and bi-allelic inactivation of tumor suppressor genes was increased in GEP70 high risk, consistent with genomic instability being a key feature of high risk. In conclusion, the study highlights the impact of acquired genetic events, which enhance the evolutionary fitness level of myeloma propagating cells to survive multi-agent chemotherapy and to result in relapse.

Publication Title

Clonal selection and double-hit events involving tumor suppressor genes underlie relapse in myeloma.

Sample Metadata Fields

Sex, Specimen part, Disease stage

View Samples
accession-icon GSE29868
Inferring drug-induced gene regulatory relationships in primary human hepatocytes
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Statins are widely used cholesterol-lowering drugs that inhibit HMG-CoA reductase, a key enzyme in cholesterol synthesis. In some cases, however, these drugs may cause a number of toxic side effects in hepatocytes and skeletal muscle tissue. Currently, the specific molecular mechanisms that cause these adverse effects are not sufficiently understood. In this work, genome-wide RNA expression changes in primary human hepatocytes of six individuals were measured at five time points upon atorvastatin treatment. A novel systems-level analysis workflow was applied to reconstruct regulatory mechanisms based on these drug-response data and available knowledge about transcription factor binding specificities, protein-protein interactions and protein-drug interactions. Several previously unknown transcription factors, regulatory cofactors and signaling molecules were found to be involved in atorvastatin-responsive gene expression. Some novel relationships, e.g., the regulatory influence of nuclear receptor NR2C2 on CYP3A4, were successfully validated in wet-lab experiments.

Publication Title

Inferring statin-induced gene regulatory relationships in primary human hepatocytes.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE40564
Targeting the Phosphoinositide 3-Kinase p110 Isoform Impairs Cell Proliferation, Survival and Tumor Growth in Small Cell Lung Cancer
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: The phosphoinositide 3-kinase (PI3K) pathway is fundamental for cell proliferation and survival and is frequently altered and activated in neoplasia, including carcinomas of the lung. In this study we investigated the potential of targeting the catalytic class IA PI3K isoforms in small cell lung cancer (SCLC), which is the most aggressive of all lung cancer types. Experimental Design: The expression of PI3K isoforms in patient specimens was analyzed. The effects on SCLC cell survival and downstream signaling were determined following PI3K isoform inhibition by selective inhibitors or down-regulation by small interfering RNA. Results: Over-expression of the PI3K isoforms p110 and p110 was shown by immunohistochemistry in primary SCLC tissue samples. Targeting the PI3K p110 with RNA interference (RNAi) or selective pharmacological inhibitors resulted in strongly affected cell proliferation of SCLC cells in vitro and in vivo, while targeting p110 was less effective. Inhibition of p110 also resulted in increased apoptosis and autophagy, which was accompanied by decreased phosphorylation of Akt and components of the mammalian target of rapamycin (mTOR) pathway, such as the ribosomal S6 protein, and the eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1). A DNA microarray analysis revealed that p110 inhibition profoundly affected the balance of pro- and anti-apoptotic Bcl-2 family proteins. Finally, p110 inhibition led to impaired SCLC tumor formation and vascularization in vivo. Conclusion: Together our data demonstrate the key involvement of the PI3K isoform p110 in multiple tumor-promoting processes in SCLC.

Publication Title

Targeting the phosphoinositide 3-kinase p110-α isoform impairs cell proliferation, survival, and tumor growth in small cell lung cancer.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE14062
MLL rearrangements in pediatric ALL and AML: MLL specific and lineage specific signatures
  • organism-icon Homo sapiens
  • sample-icon 139 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gene expression analysis identified a MLL translocation-specific signature of differentially expressed genes discriminating ALL and AML with and without MLL rearrangements.

Publication Title

MLL rearrangements in pediatric acute lymphoblastic and myeloblastic leukemias: MLL specific and lineage specific signatures.

Sample Metadata Fields

No sample metadata fields

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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Developed by the Childhood Cancer Data Lab

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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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