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accession-icon GSE8753
Sequential responses to high-fat feeding in an obese mouse model
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

We examined the effects of high-fat diet on feeding behaviour, body weight regulation and common biomarkers associated with weight gain in the C57BL/6J mice over a period of 10 weeks, making measurements at weeks 2, 4 and 10. We examined the transcriptomic profile of hepatic genes involved in the major lipid metabolic pathways, validating the key genes with quantitative real-time reverse-transcription PCR (qRT-PCR) and their gene products with western blots.

Publication Title

Sequential responses to high-fat and high-calorie feeding in an obese mouse model.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE54002
Gene expression profiling of LCM captured breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 425 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The purpose of this study is to obtain comprehensive gene expression profiles in breast cancer. Mammary gland cells were specifically isolated from 433 clinical tissue samples by laser capture microdissection (LCM). Total RNAs were extracted from LCM captured samples. We investigated gene expression profiles in 417 patients with breast cancer and 16 non-tumor tissues as a normal control using an Affymetrix GeneChip.

Publication Title

Epithelial-mesenchymal transition spectrum quantification and its efficacy in deciphering survival and drug responses of cancer patients.

Sample Metadata Fields

Specimen part

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accession-icon GSE67684
Time-series Gene Expression Profiling of Childhood Acute Lymphoblastic Leukemia
  • organism-icon Homo sapiens
  • sample-icon 418 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

ALL is the most common form of childhood cancer with >80% cured with contemporary treatment protocols. Accurate risk stratification in childhood ALL is essential to avoid under- and over-treatment. Currently, we use presenting clinical, biological features, and minimal residual disease (MRD) quantitation to risk stratify patients. Although whole genome gene expression profiling (GEP) can accurately classify patients with ALL into various WHO 2008 defined subgroups, its value in predicting relapse remained to be defined. We hypothesized that global time-series GEPs of bone marrow (BM) samples at diagnosis and specific points during initial remission-induction therapy can measure the success of cytoreduction and be used for relapse prediction.

Publication Title

Effective Response Metric: a novel tool to predict relapse in childhood acute lymphoblastic leukaemia using time-series gene expression profiling.

Sample Metadata Fields

Specimen part, Disease, Subject, Time

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accession-icon GSE47856
Expression data from cultured human ovarian carcinoma cell lines with and without Cisplatin treatment
  • organism-icon Homo sapiens
  • sample-icon 170 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Chemo-resistance to platinum such as cisplatin is critical in the treatment of ovarian cancer. Recent evidences have linked epithelial-mesenchymal transition (EMT) with the drug resistance as a contributing mechanism. The current study explored the connection between cellular responses to cisplatin with EMT in ovarian cancer.

Publication Title

Epithelial-mesenchymal status renders differential responses to cisplatin in ovarian cancer.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE69207
Gene expression data of ovarian cancer from Singapore
  • organism-icon Homo sapiens
  • sample-icon 99 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A collection of 100 ovarian cancer sample gene expression data from Singapore.

Publication Title

CSIOVDB: a microarray gene expression database of epithelial ovarian cancer subtype.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE7897
Expression data from Mouse Lymphoma
  • organism-icon Mus musculus
  • sample-icon 57 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We have made use of the E-myc transgenic mouse, a model for the study of B-cell lymphoma development that is initiated through a defined genetic alteration, to explore the contributions of additional somatic alterations that contribute to the heterogeneity of the resulting tumors. As one example of such heterogeneity, we have focused on the observation that lymphomas develop in E-myc mice with a variable time of onset. Twenty-five early-onset, 25 late-onset lymphomas and 10 normal samples were each assayed on an Affymetrix Mouse Genome 430 2.0 array.

Publication Title

Utilization of pathway signatures to reveal distinct types of B lymphoma in the Emicro-myc model and human diffuse large B-cell lymphoma.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE26168
Type 2 Diabetes mellitus: mRNA and miRNA profiling
  • organism-icon Homo sapiens, Rattus norvegicus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

MicroRNA 144 impairs insulin signaling by inhibiting the expression of insulin receptor substrate 1 in type 2 diabetes mellitus.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage

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accession-icon GSE15181
Expression profiles of cancer cells with anchorage-independent growth ability
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Anchorage-independent cell growth signature identifies tumors with metastatic potential.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE21321
Blood microRNA profiles and upregulation of hsa-miR-144 in males with type 2 diabetes mellitus.
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

In this study, we compared the expression profiles of miRNAs in blood samples from Impaired Fasting Glucose (IFG) and T2D male patients. Healthy adult males with no past history of T2D (n=158) and with desirable cholesterol and blood pressure profiles were enrolled in this study. They were then classified according to fasting glucose levels to have T2D, IFG or as healthy controls (CTL), for comparison of miRNA expression profiles. Employing miRNA microarray, we identified signature miRNAs in peripheral blood samples that distinguished IFG and T2D. Eight selected miRNAs were further validated using stem-loop real-time RT-PCR. miR-144 expression was found to be dysregulated in Type 2 Diabetes, wherein its expression was significantly higher than in healthy controls. Insulin receptor substrate 1 (IRS1) has been predicted to be a potential target of miR-144. Consistent with this observation, IRS1 mRNA and protein levels, verified by quantitative real-time PCR and western blotting respectively, were found to be down-regulated.

Publication Title

MicroRNA 144 impairs insulin signaling by inhibiting the expression of insulin receptor substrate 1 in type 2 diabetes mellitus.

Sample Metadata Fields

Sex

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accession-icon GSE20126
Transcriptome analysis of human Whartons jelly stem cells
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Human Whartons jelly stem cells (hWJSCs) are derived ethically in large amounts from the umbilical cord matrix. Besides their differentiation capabilities, WJSCs also display a notable lack of ability to form teratoma. hWJSCs have been shown to exert immunomodulatory effects and have recently been reported to kill or diminish cancer cell growth. These characteristics are important considerations for their use in cell therapy. In this transcriptome analysis, hWJSCs were profiled using Affymetrix DNA microarrays and compared to a panel of human stem cells and stromal cells. Although hWJSCs are multipotent, they expressed very low levels of the majority of stem cell markers, including POU5F1, NANOG, SOX2 and LIN28. BIRC5 has recently been shown to be required for teratoma formation in SCID mice. The lower levels of BIRC5 expression in hWJSCs compared to hESCs and the very low levels of stem cell markers might account for hWJSCs inability to form teratomas. IL12A which is known to be associated with the induction of apoptosis, was amongst the several cytokines identified to be significantly upregulated in hWJSCs. The ability of hWJSCs to compliment the host immune responses was further highlighted with the GO Biological Process analysis showing high association with immune system, chemotaxis and cell death. The ability to modulate immune responses confers hWJSCs an additional advantage in stem cell therapy and potentially allows hWJSCs as a form of treatment for cancer and immune disorders. In summary, the transcriptome profile of hWJSCs has provided indications on the genetic basis for their biological characteristics in immunomodulatory response, anti-cancer effects, and the lack of teratoma formation.

Publication Title

Human Wharton's jelly stem cells have unique transcriptome profiles compared to human embryonic stem cells and other mesenchymal stem cells.

Sample Metadata Fields

Specimen part

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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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