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accession-icon E-MEXP-152
Transcription profiling of response of adult Drosophila to oxidative and ER stress
  • organism-icon Drosophila melanogaster
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome Array (drosgenome1)

Description

We used oligonucleotide microarrays to address the specificities of transcriptional responses of adult Drosophila to different stresses induced by paraquat and H2O2, two oxidative stressors, and by tunicamycin which induces an endoplasmic reticulum (ER) stress. Flies were tested 24 hours after exposure to continuous stresses induced by ingestion of paraquat, H2O2 or tunicamycin at concentrations leading to similar effects on viability. We used concentrations of 1% H2O2, 5mM paraquat and 12uM of tunicamycin which lead to negligeable mortality at 24 hours. A paraquat concentration of 15mM was also used for comparison with previous studies Both specific and common responses to the three stressors were observed and whole genome functional analysis identified several important classes of stress responsive genes. Within some functional classes, we observed large variabilities of transcriptional changes between isozymes, which may reflect unsuspected functional specificities.

Publication Title

Genome wide analysis of common and specific stress responses in adult drosophila melanogaster.

Sample Metadata Fields

Sex, Age, Compound, Time

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accession-icon GSE46816
Gene expression data from 8 pairs of CD138+/- myeloma cell lines
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

8 pairs of myeloma cell lines were sorted by MACS CD138-microbead, and the each cell lines were divided into two fraction CD138+ and CD138-.

Publication Title

RARα2 expression confers myeloma stem cell features.

Sample Metadata Fields

Cell line

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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 GSE27838
Gene expression of expanded and non-expanded natural killer cells from healthy donor and myeloma patients
  • organism-icon Homo sapiens
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Natural Killer cells (NK), a major constituent of innate immune system, have the ability to kill the transformed and infected cells without prior sensitization; can be put to immunotherapeutic use against various malignancies. NK cells discriminate between normal cells and transformed cells via a balance of inhibitory and activating signals induced by interactions between NK cell receptors and target cell ligands. Present study investigates whether expansion of NK cells could augment their anti-myeloma (MM) activity. For NK cell expansion, peripheral blood mononuclear cells from healthy donors and myeloma patients were co-cultured with irradiated K562 cells transfected with 4-1BBL and membrane-bound IL15 (K562-mb15-41BBL). A genome-wide profiling approach was performed to identify gene expression signature in expanded NK (ENK) cells and non-expanded NK cells isolated from healthy donors and myeloma patients. A specific set of genes involved in proliferation, migration, adhesion, cytotoxicity, and activation were up regulated post expansion, also confirmed by flow cytometry. Exp-NK cells killed both allogeneic and autologous primary MM cells more avidly than non-exp-NK cells in vitro. Multiple receptors, particularly NKG2D, natural cytotoxicity receptors, and DNAM-1 contributed to target lysis, via a perforin mediated mechanism. In summary, vigorous expansion and high anti-MM activity both in vitro and in vivo provide the rationale for testing exp-NK cells in a clinical trial for high risk MM.

Publication Title

Highly activated and expanded natural killer cells for multiple myeloma immunotherapy.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE106865
A longitudinal gene expression microarray analysis of skeletal muscle resistance training
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Skeletal muscle adapts to resistance exercise (RE) performance acutely and chronically. An important regulatory step of muscle adaptation to RE is gene expression. Microarray analysis can be used as an exploratory method to investigate how genes and gene clusters are modulated acutely and chronically by RE. The purpose of the present study was to investigate the effect of training status in the basal (rested) and pre- to 24h post-RE on the global transcriptome in vastus lateralis muscle biopsies of young men. Muscle biopsies of nine young men who undertook RE training for 10-wks were collected pre and 24h post-RE at the first (W1) and last (W10) weeks of training and analysed using microarray. An unaccustomed RE bout (at W1) up-regulated muscle gene transcripts related to stress (e.g., heat shock proteins), damage and inflammation, structural remodelling, protein turnover and increased translational capacity. Trained muscles (at W10) became more efficient metabolically, as training favoured a more oxidative metabolism, refined response to stress, showed by genes suppression related to RE-induced stress and inflammation, and up-regulated genes indicating greater muscle contractile efficiency and contribution to promote muscle growth and development. These data highlight that chronic repetition of RE increases muscle efficiency and adapt muscles to respond more specifically and accurately to RE-induced stress.

Publication Title

Resistance training in young men induces muscle transcriptome-wide changes associated with muscle structure and metabolism refining the response to exercise-induced stress.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE25206
Transcriptomic shifts in rice roots in response to Cr (VI) stress
  • organism-icon Oryza sativa indica group
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Detailed analysis of genome-wide transcriptome profiling in rice root is reported here, following Cr-plant interaction. Such studies are important for the identification of genes responsible for tolerance, accumulation and defense response in plants with respect to Cr stress. Rice root metabolome analysis was also carried out to relate differential transcriptome data to biological processes affected by Cr (VI) stress in rice.

Publication Title

Transcriptomic and metabolomic shifts in rice roots in response to Cr (VI) stress.

Sample Metadata Fields

Age, Specimen part, Treatment

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accession-icon GSE19249
Quantitative Gene Expression Profiling in Formalin-Fixed Paraffin-Embedded Samples by Affymetrix Microarrays
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: To date, few studies have systematically characterized microarray gene expression signal performance with degraded RNA from formalin-fixed paraffin-embedded (FFPE) specimens in comparison to intact RNA from unfixed fresh-frozen (FF) specimens.

Publication Title

Quantitative expression profiling in formalin-fixed paraffin-embedded samples by affymetrix microarrays.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE60618
Treatment of primary effusion lymphoma cell lines with lenalidomide
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Technical replicates from BC3 and BCBL1 cell lines were treated with DMSO or 5 micromoles of lenalidomide for 24 hours.

Publication Title

Immunomodulatory drugs target IKZF1-IRF4-MYC axis in primary effusion lymphoma in a cereblon-dependent manner and display synergistic cytotoxicity with BRD4 inhibitors.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE92689
caArray_trich-00099: Identification of a PAX-FKHR gene expression signature that defines molecular classes and determines the prognosis of alveolar rhabdomyosarcomas
  • organism-icon Homo sapiens
  • sample-icon 185 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Alveolar rhabdomyosarcomas (ARMS) are aggressive soft-tissue sarcomas affecting children and young adults. Most ARMS tumors express the PAX3-FKHR or PAX7-FKHR (PAX-FKHR) fusion genes resulting from the t(2;13) or t(1;13) chromosomal translocations, respectively. However, up to 25% of ARMS tumors are fusion negative, making it unclear whether ARMS represent a single disease or multiple clinical and biological entities with a common phenotype. To test to what extent PAX-FKHR determine class and behavior of ARMS, we used oligonucleotide microarray expression profiling on 139 primary rhabdomyosarcoma tumors and an in vitro model. We found that ARMS tumors expressing either PAX-FKHR gene share a common expression profile distinct from fusion-negative ARMS and from the other rhabdomyosarcoma variants. We also observed that PAX-FKHR expression above a minimum level is necessary for the detection of this expression profile. Using an ectopic PAX3-FKHR and PAX7-FKHR expression model, we identified an expression signature regulated by PAX-FKHR that is specific to PAX-FKHR-positive ARMS tumors. Data mining for functional annotations of signature genes suggested a role for PAX-FKHR in regulating ARMS proliferation and differentiation. Cox regression modeling identified a subset of genes within the PAX-FKHR expression signature that segregated ARMS patients into three risk groups with 5-year overall survival estimates of 7%, 48%, and 93%. These prognostic classes were independent of conventional clinical risk factors. Our results show that PAX-FKHR dictate a specific expression signature that helps define the molecular phenotype of PAX-FKHR-positive ARMS tumors and, because it is linked with disease outcome in ARMS patients, determine tumor behavior.

Publication Title

Identification of a PAX-FKHR gene expression signature that defines molecular classes and determines the prognosis of alveolar rhabdomyosarcomas.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

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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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