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accession-icon GSE33874
Identification of a Potential Ovarian Cancer Stem Cell Gene Expression Profile from Advanced Stage Papillary Serous Ovarian Cancer
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

To identify the potential ovarian cancer stem cell gene expression profile from isolated side population of fresh ascites obtained from women with high-grade advanced stage papillary serous ovarian adenocarcinoma

Publication Title

Identification of a potential ovarian cancer stem cell gene expression profile from advanced stage papillary serous ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE48567
Expression data of A224 cell with ectopic overexpression of FGF18 and RFP
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We have identified the overexpression of FGF18 as an independent predictive marker for poor clinical outcome in patients with advanced stage, high-grade serous ovarian cancer. Functional studies have demonstrated that FGF18 promotes migration, invasion and tumorigenicity of ovarian cancer cells in vitro and in vivo.

Publication Title

FGF18 as a prognostic and therapeutic biomarker in ovarian cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE30161
Genomic Multivariate Predictors of Response to Adjuvant Chemotherapy in Ovarian Carcinoma: Predicting Platinum Resistance
  • organism-icon Homo sapiens
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients.

Publication Title

Multi-gene expression predictors of single drug responses to adjuvant chemotherapy in ovarian carcinoma: predicting platinum resistance.

Sample Metadata Fields

Age, Specimen part, Disease stage, Race

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accession-icon GSE40595
A cancer associated fibroblasts (CAFs) specific gene signature in high grade serous ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 72 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Ovarian cancer is the most lethal malignancy in the United States. In the year 2012, there will be an estimated 22,280 new cases and 15,500 deaths from ovarian cancer in the country (Siegel et al., 2012). While studies on ovarian cancer pathogenesis were mainly focused on the epithelial component of the tumor, understanding in the role of cancer associated fibroblasts (CAFs) in ovarian cancer progression is limited. We hypothesized that comparing the gene expression profiles of different components from laser capture microdissected ovarian tissue will allow us to identify an ovarian CAFs specific gene signature which accounts for the supportive role of CAFs in ovarian cancer progression. In this study, gene expression profiling was completed for 31 cancer stroma samples and 32 samples of epithelial component from high grade serous ovarian cancer patients. 8 microdissected normal ovarian stroma and 6 normal human ovarian surface epithelium (HOSE) samples were also included in the study. By comparing the expression data from cancer stroma against that from normal stroma, cancer cells and HOSE, we identified a set of differential expressed genes in ovarian CAFs which showed correlation with cancer patient survival. Further study on these genes can reveal their roles in ovarian cancer progression and pathogenesis. Ultimately, ovarian CAFs specified genes identified in this study may aid in the classification and enhancement of patient outcome.

Publication Title

TGF-β modulates ovarian cancer invasion by upregulating CAF-derived versican in the tumor microenvironment.

Sample Metadata Fields

Specimen part

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accession-icon GSE40266
Expression data from TGF-beta-treated human ovarian fibroblasts
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Ovarian cancer cells are known to have diminished response to TGF-beta, but it remains unclear whether TGF-beta can modulate ovarian cancer cell growth in an indirect manner through cancer-associated fibroblasts (CAFs). Using transcriptome profiling analyses on TGF-beta-treated ovarian fibroblasts, we identified a TGF-beta-responsive gene signature in ovarian fibroblasts. Identifying TGF-beta-regulated genes in the ovarian microenvironment helps in understanding the role of TGF-beta in ovarian cancer progression.

Publication Title

TGF-β modulates ovarian cancer invasion by upregulating CAF-derived versican in the tumor microenvironment.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE10585
Egr1 regulates the coordinated expression of numerous EGF receptor target genes as identified by ChIP-on-chip
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Previous studies have revealed that UV-stimulation of a variety of cells leads to activation of the EGF receptor, induction of Egr1, growth inhibition and apoptosis. On the other hand both Egr1 and EGF receptor activation are implicated in promoting the progression of prostate cancer. We treated M12 tumorigenic prostate epithelial cells which express little Egr1 with UV irradiation which rapidly activated the EGF receptor and elevated Egr1. Treatment with specific EGFR and ERKI/II inhibitors (PD153035 and UO126, respectively) confirmed that the upregulation of Egr1 was downstream of EGFR and ERKI/II Map kinase pathway. ChIP on chip experiments using Egr1 antibody identified 288 significantly bound promoters upon UV stimulation. Of these target genes, 40% had consensus Egr1 site in their promoters, considerably greater than that expected by chance (p < 0.005). The array binding results were validated by PCR analysis of 25 genes using DNA from conventional IP experiment. Affymetrix gene expression analysis of UV treated and control cells confirmed that a significant number of these bound promoters showed gene expression changes. Addition of siRNA to Egr1 confirmed that the gene expression changes were dependent upon Egr1 expression. Addition of EGF led to similar expression changes for nine tested genes. Proliferation and apoptosis assays confirmed that M12 cells undergo growth arrest and apoptosis following UV irradiation. Moreover, addition of EGF also promoted significant growth inhibition. These results indicate the M12 cells undergo a EGF receptor dependent apoptosis response upon UV-stimulation and that Egr1 mediates the regulation of numerous genes downstream of the EGF receptor that are associated with this response.

Publication Title

Egr1 regulates the coordinated expression of numerous EGF receptor target genes as identified by ChIP-on-chip.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE40241
Expression data from Versican (VCAN) protein treated ovarian cancer cell line OVCA433
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Advanced ovarian cancer is the most lethal gynecologic malignancy in the United States. Currently patients are treated by surgical cytoreductive surgery with the aim of reducing tumor burden to microscopic disease followed by adjuvant combined treatment with a platinum and taxane containing chemotherapy, which affords 80% of patients an initial complete response. However, Abdominal and pelvic recurrence rates are high and response to further chemotherapy is limited. Attempts at introducing biologic therapeutic agents to improve outcome in this disease are ongoing, while prognostic or predictive biomarkers that can stratify patients for treatment are still lacking. Using transcriptome profiling of microdissected tissue samples from high-grade serous ovarian cancer patients, we identified a cancer associated fibroblast (CAF) specific gene signature. Versican, which encodes a extracellular matrix protein, was one of the identified genes which demonstrated up-regulation in cancer stroma. To investigate the function roles, signaling machanism and the effect of versican treatment on ovarian cancer cells, transcriptome profiling of versican treated OVCA433 high-grade serous ovarian cancer cells was performed.

Publication Title

TGF-β modulates ovarian cancer invasion by upregulating CAF-derived versican in the tumor microenvironment.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE26712
A Gene Signature Predicting for Survival in Suboptimally Debulked Patients with Ovarian Cancer
  • organism-icon Homo sapiens
  • sample-icon 195 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

To identify a prognostic gene signature accounting for the distinct clinical outcomes in ovarian cancer patients

Publication Title

A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE27651
The Anterior Gradient Homolog 3 (AGR3) Gene Is Associated with Differentiation and Survival in Ovarian Cancer
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Low-grade serous ovarian carcinoma is believed to arise from serous borderline ovarian tumors, yet the progression from serous borderline tumors to low-grade serous ovarian carcinoma remains poorly understood. The purpose of this study was to identify differentially expressed genes between the two groups. Expression profiles were generated from 6 human ovarian surface epithelia (HOSE), 8 serous borderline ovarian tumors (SBOT), 13 low-grade serous ovarian carcinomas (LG), and 22 high-grade serous ovarian carcinomas (HG). The anterior gradient homolog 3 (AGR3) gene was found to be highly upregulated in serous borderline ovarian tumors; this finding was validated by real-time quantitative RT-PCR, Western blotting, and immunohistochemistry. Anti-AGR3 immunohistochemistry was performed on an additional 56 LG and 103 HG tissues and the results were correlated with clinical data. Expression profiling determined that 1254 genes were differentially expressed (P < 0.005) between SBOT, LG and HG tumors. Serous borderline ovarian tumors exhibited robust positive staining for AGR3, with a lower percentage of tumor cells stained in LG and HG. Immunofluorescence staining indicated that AGR3 expression was limited to ciliated cells. Tumor samples with a high percentage (>10%) of AGR3 positively stained tumor cells were associated with improved longer median survival in both the LG (P = 0.013) and HG (P = 0.008) serous ovarian carcinoma groups. The progression of serous borderline ovarian tumors to low-grade serous ovarian carcinoma may involve the de-differentiation of ciliated cells. AGR3 could serve as a prognostic marker for survival in patients with low-grade and high-grade serous ovarian carcinomas.

Publication Title

The anterior gradient homolog 3 (AGR3) gene is associated with differentiation and survival in ovarian cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE54809
RNA profiling from ovarian and prostate FFPE specimens
  • organism-icon Homo sapiens
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Comparing Platforms for Messenger RNA Expression Profiling of Archival Formalin-Fixed, Paraffin-Embedded Tissues.

Sample Metadata Fields

Specimen part, Disease

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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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