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accession-icon GSE27678
Gene expression analysis in a variety of normal, premalignant and squamous cell carcinomas of the cervix
  • organism-icon Homo sapiens
  • sample-icon 76 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We sought to apply the technologies of gene expression profiling to detect genes significant in the aetiology of cervical carcinoma . We investigated 14 normal (NAD), 11 low grade squamous intrapepithelial lesions (LSIL), 21 high grade squamous intraepithelial lesions (HSIL) and 28 squamous cell carcinomas by Affymetrix GeneChip whole transcriptome profiling. Two SCC cell lines were also included in the cohort. Normal and SILS were profiled using the Affymetrix U133A platform, while SCCs and Cell lines were profiled using the Affymetrix U133A plus 2.0 array.

Publication Title

Gain and overexpression of the oncostatin M receptor occur frequently in cervical squamous cell carcinoma and are associated with adverse clinical outcome.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE25136
Optimizing molecular signatures for prostate cancer recurrence
  • organism-icon Homo sapiens
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The derivation of molecular signatures indicative of disease status and predictive of subsequent behavior could facilitate the optimal choice of treatment for prostate cancer patients. In this study, we conducted a computational analysis of gene expression profile data obtained from 79 cases, 39 of which were classified as having disease recurrence, to investigate whether advanced computational algorithms can derive more accurate prognostic signatures for prostate cancer. At the 90% sensitivity level, a newly derived prognostic genetic signature achieved 85% specificity. This is the first reported genetic signature to outperform a clinically used postoperative nomogram. Furthermore, a hybrid prognostic signature derived by combination of the nomogram and gene expression data significantly outperformed both genetic and clinical signatures, and achieved a specificity of 95%. Our study demonstrates the feasibility of utilizing gene expression information for highly accurate prostate cancer prognosis beyond the current clinical systems, and shows that more advanced computational modeling of tissue-derived microarray data is warranted before clinical application of molecular signatures is considered.

Publication Title

Optimizing molecular signatures for predicting prostate cancer recurrence.

Sample Metadata Fields

Specimen part

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accession-icon GSE35581
Transcriptomic profiling of chicken adipose tissue in response to insulin neutralization and fasting
  • organism-icon Gallus gallus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Chicken Genome Array (chicken)

Description

Domestic broiler chickens rapidly accumulate adipose tissue due to intensive genetic selection for rapid growth and are naturally hyperglycemic and insulin resistant, making them an attractive addition to the suite of rodent models used for studies of obesity and type 2 diabetes in humans. Furthermore, chicken adipose tissue is considered as poorly sensitive to insulin and lipolysis is under glucagon control. Excessive fat accumulation is also an economic and environmental concern for the broiler industry due to the loss of feed efficiency and excessive nitrogen wasting, as well as a negative trait for consumers who are increasingly conscious of dietary fat intake. Understanding the control of avian adipose tissue metabolism would both enhance the utility of chicken as a model organism for human obesity and insulin resistance and highlight new approaches to reduce fat deposition in commercial chickens.

Publication Title

Transcriptomic and metabolomic profiling of chicken adipose tissue in response to insulin neutralization and fasting.

Sample Metadata Fields

Specimen part

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accession-icon E-MEXP-1193
Transcription profiling time series of wheat cv. Hereward grown under control, hot, dry and hot and dry conditions to illustrate the importance of developmental context in interpretation
  • organism-icon Triticum aestivum
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Wheat Genome Array (wheat)

Description

The aim of the experiment is provide a reference dataset for placing wheat grain transcriptome experiments in a developmental context. RNA was isolated from whole grain tissue of replicate wheat cv. Hereward plants at 6, 8, 10, 12, 14, 17, 21, 28, 35 and 42 days after anthesis (daa). Also supplied are array data for grain sampled at 14, 21 and 28 daa under control, hot, dry and hot&dry conditions to illustrate the importance of developmental context in interpretation.

Publication Title

Transcriptome analysis of grain development in hexaploid wheat.

Sample Metadata Fields

Age, Specimen part, Time

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accession-icon GSE16475
Expression data from side population subfraction hematopoietic stem cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The traditional view of hematopoiesis has been that all the cells of the peripheral blood are the progeny of a unitary homogeneous pool of hematopoietic stem cells (HSCs). Recent evidence suggests that the hematopoietic system is actually maintained by a consortium of HSC subtypes with distinct functional characteristics. We show here that myeloid-biased HSCs (My-HSCs) and lymphoid-biased (Ly-HSCs) can be purified according to their capacity for Hoechst dye efflux in combination with canonical HSC markers.

Publication Title

Distinct hematopoietic stem cell subtypes are differentially regulated by TGF-beta1.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE51373
Gene expression data from high grade serous ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Resistance to platinum-based chemotherapy remains a major impediment in the treatment of serous epithelial ovarian cancer. The objective of this study was to use gene expression profiling to delineate major deregulated pathways and biomarkers associated with the development of intrinsic chemotherapy resistance upon exposure to standard first-line therapy for ovarian cancer. Methods: The study cohort comprised 28 patients divided into two groups based on their varying sensitivity to first-line chemotherapy using progression free survival (PFS) as a surrogate of response. All 28 patients had advanced stage, high-grade serous ovarian cancer, and were treated with the same standard platinum-based chemotherapy. Twelve patient tumors demonstrating relative resistance to platinum chemotherapy corresponding to shorter PFS (< eight months) were compared to sixteen tumors from platinum-sensitive patients (PFS > eighteen months). Whole transcriptome profiling was performed using a Affymetrix high-resolution microarray platform to permit global comparisons of gene expression profiles between tumors from the resistant group and the sensitive group. Results: Microarray data analysis revealed a set of 204 discriminating genes possessing expression levels, which could influence differential chemotherapy response between the two groups. Robust statistical testing was then performed which eliminated a dependence on the normalization algorithm employed, producing a restricted list of differentially regulated genes, and which found IGF1 to be the most strongly differentially expressed gene. Pathway analysis, based on the list of 204 genes, revealed enrichment in genes primarily involved in the IGF1/PI3K/NFB/ERK gene signalling networks. Conclusions: This study has identified pathway specific prognostic biomarkers possibly underlying a differential chemotherapy response in patients undergoing standard platinum-based treatment of serous epithelial ovarian cancer. Future studies to validate these markers are necessary to apply this knowledge to biomarker-based clinical trials.

Publication Title

Identification of the IGF1/PI3K/NF κB/ERK gene signalling networks associated with chemotherapy resistance and treatment response in high-grade serous epithelial ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE31189
Molecular Biomarker Signature for Bladder Cancer Detection
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

In this study we applied differential gene expression analysis to exfoliated human urothelia obtained from patients of known bladder disease status. Selected targets from the microarray data were validated in an independent set of samples using a quantitative PCR approach.

Publication Title

A candidate molecular biomarker panel for the detection of bladder cancer.

Sample Metadata Fields

Specimen part, Disease

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accession-icon GSE20427
Characterization of hepatic gene expression during liver regeneration in response to partial hepatectomy
  • organism-icon Mus musculus
  • sample-icon 79 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Elevated interferon gamma signaling contributes to impaired regeneration in the aged liver.

Sample Metadata Fields

Sex, Treatment

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accession-icon GSE20425
Hepatic gene expression during liver regeneration in response to partial hepatectomy: early time points (0.5h,1h,2h,4h)
  • organism-icon Mus musculus
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

The process of liver regeneration can be divided into a series of stages that include initial inductive or priming events through cellular mitosis. Following two-thirds liver resection, the liver undergoes the priming phase, in which cytokines TNF-a and IL-6 activate their respective receptors in hepatocytes. This leads to the activation of several key transcription factors: NF-kB, AP-1, Stat 3, Stat 1, and C/EBP-b and -d . These transcription factors induce the expression of immediate early genes. HGF is also expressed at this time and involved in the transition of quiescent hepatocytes into the G1 phase of the cell cycle. During the G1 phase, delayed early genes are expressed followed by induction of cell cyclerelated genes, both of which require new protein synthesis for their production. Increased expression of FoxM1B and TGF-a occurs at the G1/S transition and is correlated with increased expression of cyclinD1 and decreased expression of cdk inhibitors. During the G2/M phase of the cell cycle, FoxM1B directly elevates cyclinB1, cyclinB2, and cdc25B expression. Additionally, FoxM1B is associated with increased cyclinF and p55cdc, which are involved in completion of the cell cycle following partial hepatectomy. In mice, two-thirds partial hepatectomy promotes proliferation of liver cells and rapid growth of the remaining liver tissue, resulting in complete restoration of organ mass in approximately 7 days (Mackey S. et al. Hepatology 2003 Dec;38(6):1349-52).

Publication Title

Elevated interferon gamma signaling contributes to impaired regeneration in the aged liver.

Sample Metadata Fields

Sex, Treatment

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accession-icon GSE20426
Hepatic gene expression during liver regeneration in response to partial hepatectomy: late time points (24h, 38h, 48h)
  • organism-icon Mus musculus
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The process of liver regeneration can be divided into a series of stages that include initial inductive or priming events through cellular mitosis. Following two-thirds liver resection, the liver undergoes the priming phase, in which cytokines TNF-a and IL-6 activate their respective receptors in hepatocytes. This leads to the activation of several key transcription factors: NF-kB, AP-1, Stat 3, Stat 1, and C/EBP-b and -d . These transcription factors induce the expression of immediate early genes. HGF is also expressed at this time and involved in the transition of quiescent hepatocytes into the G1 phase of the cell cycle. During the G1 phase, delayed early genes are expressed followed by induction of cell cyclerelated genes, both of which require new protein synthesis for their production. Increased expression of FoxM1B and TGF-a occurs at the G1/S transition and is correlated with increased expression of cyclinD1 and decreased expression of cdk inhibitors. During the G2/M phase of the cell cycle, FoxM1B directly elevates cyclinB1, cyclinB2, and cdc25B expression. Additionally, FoxM1B is associated with increased cyclinF and p55cdc, which are involved in completion of the cell cycle following partial hepatectomy. In mice, two-thirds partial hepatectomy promotes proliferation of liver cells and rapid growth of the remaining liver tissue, resulting in complete restoration of organ mass in approximately 7 days (Mackey S. et al. Hepatology 2003 Dec;38(6):1349-52).

Publication Title

Elevated interferon gamma signaling contributes to impaired regeneration in the aged liver.

Sample Metadata Fields

Sex, Treatment

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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