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accession-icon GSE119642
Expression data from ectopic expression of BDH2 in Nasopharyngeal carcinoma (NPC) cell lines
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Compare with normal nasopharyngeal epithelial cells, we found BDH2 was decreased in NPC cells, we found that BDH2 inhibited proliferation, colony formation, migration and invasion in NPC cells.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE155206
Expression data from ectopic expression of ACAT1 in Nasopharyngeal carcinoma (NPC) cell lines
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Compare with normal nasopharyngeal epithelial cells, we found ACAT1 was decreased in NPC cells, we found that ACAT1 inhibited proliferation, colony formation, migration and invasion in NPC cells. We used microarrays to identify differential genes regulated by ACAT1 in NPC cell lines.

Publication Title

Epigenetic Inactivation of Acetyl-CoA Acetyltransferase 1 Promotes the Proliferation and Metastasis in Nasopharyngeal Carcinoma by Blocking Ketogenesis.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE118807
Expression data from EBV-encoded latent membrane protein 2A (LMP2A) positive and negative nasopharyngeal carcinoma (NPC) cell lines
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Latent infection with Epstein-Barr virus (EBV) is recognised as a factor in the pathogenesis of nasopharyngeal carcinoma (NPC). We found that EBV encoded Latent membrane protein 2A (LMP2A) enhances lipid accumulation significantly in NPC cells.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Specimen part, Cell line

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accession-icon GSE60327
Expression data from the rituximab-resistant lymphoma cell lines and the parental cell lines
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Rituximab, a monoclonal antibody against CD20, has achieved great success in the treatment of B cell lymphoma, but many patients have shown resistance to it and led to disease progression eventually. At present, the mechanism of resistance is still not clear, but we consider that it may involve the multiple genes and multiple signaling pathways. Therefore, our study aimed at searching differentially expressed genes of rituximab resistant cell lines (RRCL) by cDNA microarray, and exploring the resistant mechanism of RRCL by using the subsequent bioinformatics methods. In this study, we successfully identified seventy up-regulated genes and forty-two down-regulated genes in both two RRCL. We also isolated the MAPK signaling pathway, which was the significantly enriched pathway in resistant mechanism, through KEGG pathway analysis. Moreover, we discovered the biological behaviors of RRCL that mainly inhibit apoptosis, promote cellular proliferation, transcription and angiogenesis through Gene Ontology (GO) terms analysis. In conclusion, our results suggested that the most closely related pathway to rituximab resistance was MAPK signaling pathway, which may partly be related to its inhibiting the apoptosis of cells and promoting the proliferation of cells and vascular development.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE75118
Expression Profile of alloreactive CD8 and CD4 induced regulatory T cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Adoptive natural regulatory T cell (nTreg) therapy has improved the outcome for patients suffering from graft-versus-host disease (GVHD) following allogeneic hematopoietic cell transplantation (allo-HCT). However, fear of broad immune suppression and subsequent dampening of beneficial graft-versus-leukemic (GVL) responses remains a challenge. To address this concern, we generated alloreactive induced Tregs (iTregs) from resting CD4 or CD8 T cells and tested their ability to suppress GVH and maintain GVL responses. We utilized major mismatched and haploidentical murine models of HCT with host-derived lymphoma or leukemia cell lines to evaluate GVH and GVL responses simultaneously. Alloreactive CD4 iTregs were effective in preventing GVHD, but abrogated the GVL effect against aggressive leukemia. Alloreactive CD8 iTregs moderately attenuated GVHD while sparing the GVL effect. Hence, we reasoned that using a combination of CD4 and CD8 iTregs could achieve the optimal goal of allo-HCT. Indeed, the combinational therapy was superior to CD4 or CD8 iTreg singular therapy in GVHD control; importantly, the combinational therapy maintained GVL responses. Cellular analysis uncovered potent suppression of both CD4 and CD8 effector T cells by the combinational therapy that resulted in effective prevention of GVHD, which could not be achieved by either singular therapy. Gene expression profiles revealed alloreactive CD8 iTregs possess elevated expression of multiple cytolytic molecules compared to CD4 iTregs, which likely contributes to GVL preservation. Our study uncovers unique differences between alloreactive CD4 and CD8 iTregs that can be harnessed to create an optimal iTreg therapy for GVHD prevention with maintained GVL responses.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE44104
COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer.
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Biomarkers that predict disease progression might assist the development of better therapeutic strategies for aggressive cancers, such as ovarian cancer. Here, we investigated the role of collagen type XI alpha 1 (COL11A1) in cell invasiveness and tumor formation and the prognostic impact of COL11A1 expression in ovarian cancer. Microarray analysis suggested that COL11A1 is a disease progression-associated gene that is linked to ovarian cancer recurrence and poor survival.

Publication Title

COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE145127
Microarray analysis of dithranol-treated psoriasis
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.1 ST Array (hugene21st)

Description

Microarray analysis of dithranol-treated psoriasis lesions before, during and after therapy

Publication Title

Dithranol targets keratinocytes, their crosstalk with neutrophils and inhibits the IL-36 inflammatory loop in psoriasis.

Sample Metadata Fields

Time

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accession-icon GSE67851
Expression data from AT/RTs, AT/RT-like tumors and medulloblastomas
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Integrated genomics has identified a new AT/RT-like yet INI1-positive brain tumor subtype among primary pediatric embryonal tumors.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage

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accession-icon GSE46495
Transcriptome signature of white adipose tissue, liver, and skeletal muscle in 24 hours fasted mice (C57Bl/6J)
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Fasting is the process of metabolic adaption to food deprivation that is taking place in most organisms, e.g. during the daily resting phase in mammals. Furthermore, in biomedical research fasting is used in most metabolic studies to synchronize nutritional states of study subjects. Because there is a lack of standardization for this procedure, we need a deeper understanding of the dynamics and the molecular players in fasting. In this study we investigated the transcriptome signature of white adipose tissue, liver, and skeletal muscle in 24 hours fasted mice (and chow fat controls) using Affymetrix whole-genome microarrays.

Publication Title

Metabolite and transcriptome analysis during fasting suggest a role for the p53-Ddit4 axis in major metabolic tissues.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE63941
Expression data from cultured human esophageal squamous cell carcinoma cell lines and cultured human fibroblasts.
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Cancer cells express different sets of receptor type tyrosine kinases. These receptor kinases may be activated through autocrine or paracrine mechanisms. Fibroblasts may modify the biologic properties of surrounding cancer cells through paracrine mechansms.

Publication Title

The role of HGF/MET and FGF/FGFR in fibroblast-derived growth stimulation and lapatinib-resistance of esophageal squamous cell carcinoma.

Sample Metadata Fields

Specimen part, Cell line

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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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