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accession-icon GSE27020
Identification and validation of a multigene predictor of recurrence in primary laryngeal cancer.
  • organism-icon Homo sapiens
  • sample-icon 109 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Background: Local recurrence is the major manifestation of treatment failure in patients with operable laryngeal carcinoma. Established clinicopathological factors cannot sufficiently predict patients that are likely to recur after treatment. Additional tools are therefore required to accurately identify patients at high risk for recurrence. Methods: Using Affymetrix U133A Genechips, we profiled fresh-frozen tumor tissues from 59 patients with operable laryngeal cancer. All patients were treated locally with surgery, with or without radiation therapy. We performed Cox regression proportional hazards modeling to identify multigene predictors of recurrence. The end-point of our analysis was disease-free survival (DFS). Gene models were directly validated in a separate, similarly treated cohort of 50 patients using Affymetrix chips. In an attempt to further validate our results, we profiled 12 selected genes of our model in formalin-fixed tumor tissues from an independent cohort of 75 patients, using quantitative real time-polymerase chain reaction (qRT-PCR). Results: We focused on genes univariately associated with DFS (p<0.05) in the training set. Among several gene models comprising different numbers of genes, a 30-gene model demonstrated optimal performance (log-rank, p<0.001). We directly applied these gene models to the validation set, after adjusting for non-biological experimental variability, and observed similar results. Specifically, median DFS, as predicted by the 30-gene model, was 34 and 80 months for high- and low-risk patients, respectively (p=0.01). Hazard Ratio (HR) for recurrence for the high-risk group was 3.87 (95% CI 1.28-11.73, p=0.017). Furthermore, unsupervised hierarchical clustering of the 75 patients, based on the qRT-PCR 12-gene profile, yielded two groups, which differed significantly in DFS (log-rank, p=0.027). HR= for recurrence was 2.26, (95% CI 1.08-4.76, p=0.031). Conclusion: We have established and validated gene models that can successfully stratify patients with laryngeal cancer, based on their risk for recurrence. Thus, patients with unfavorable prognosis, when accurately identified, could be ideal candidates for the application of more aggressive treatment modalities.

Publication Title

Identification and validation of a multigene predictor of recurrence in primary laryngeal cancer.

Sample Metadata Fields

Age, Specimen part, Disease stage

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accession-icon GSE13525
Carboplatin-induced gene expression changes in vitro are prognostic of survival in epithelial ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We performed a time-course microarray experiment to define the transcriptional response to carboplatin in vitro, and to correlate this with clinical outcome in epithelial ovarian cancer (EOC). RNA was isolated from carboplatin and control-treated 36M2 ovarian cancer cells at several time points, followed by oligonucleotide microarray hybridization. Carboplatin induced changes in gene expression were assessed at the single gene as well as at the pathway level. Clinical validation was performed in publicly available microarray datasets using disease free and overall survival endpoints.

Publication Title

Carboplatin-induced gene expression changes in vitro are prognostic of survival in epithelial ovarian cancer.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE19829
A gene expression profile of BRCAness that is associated with outcome in ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 70 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A gene expression profile of BRCAness was defined in publicly available expression data of 61 patients with epithelial ovarian cancer (34 patients with BRCA-1 or BRCA-2 mutations and 27 patients with sporadic disease). This dataset is publicly available at http://jnci.oxfordjournals.org/cgi/content/full/94/13/990/DC1

Publication Title

Gene expression profile of BRCAness that correlates with responsiveness to chemotherapy and with outcome in patients with epithelial ovarian cancer.

Sample Metadata Fields

Age, Disease stage

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accession-icon GSE13671
Expression data from mammary epithelial cells from BRCA1 mutation carriers and non BRCA1 mutation carriers
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Female BRCA1 mutation carriers have a nearly 80% probability of developing breast cancer during their life-time. We hypothesized that the breast epithelium at risk in BRCA1 mutation carriers harbors mammary epithelial cells (MECs) with altered proliferation and differentiation properties.

Publication Title

Altered proliferation and differentiation properties of primary mammary epithelial cells from BRCA1 mutation carriers.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16709
Ovarian serous cancer
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip, Illumina HumanWG-6 v3.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Molecular profiling uncovers a p53-associated role for microRNA-31 in inhibiting the proliferation of serous ovarian carcinomas and other cancers.

Sample Metadata Fields

Disease, Disease stage, Cell line

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accession-icon GSE16708
Gene expression analysis of ovarian serous adenocarcinoma cell lines and tumors
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge IconIllumina HumanWG-6 v3.0 expression beadchip, Illumina HumanHT-12 V3.0 expression beadchip

Description

A variety of human cancers demonstrate alterations in microRNA expression. We hypothesized that regulatory defects in microRNAs play a central early role in organizing the molecular changes involved in ovarian cancer (OvCa). Using both gene arrays and deep sequencing, we comprehensively profiled mRNA and microRNA expression, respectively, in human serous epithelial OvCa cell lines, serous tumors, and short-term primary cultures of normal ovarian surface epithelium (NOSE). We expected that over-expression of a specific microRNA would lead to lower expression of its mRNA targets, and under-expression of a specific microRNA would lead to higher expression of its target genes. Using our expression data in conjunction with established in silico algorithms, we found putative microRNA:mRNA functional pairs.

Publication Title

Molecular profiling uncovers a p53-associated role for microRNA-31 in inhibiting the proliferation of serous ovarian carcinomas and other cancers.

Sample Metadata Fields

Disease, Disease stage, Cell line

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accession-icon GSE16700
Gene expression analyses of mir-31 overexpression in ovarian serous cancer cell line
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V3.0 expression beadchip

Description

A variety of human cancers demonstrate alterations in microRNA expression. We hypothesized that regulatory defects in microRNAs play a central early role in organizing the molecular changes involved in ovarian cancer (OvCa). Using both gene arrays and deep sequencing, we comprehensively profiled mRNA and microRNA expression, respectively, in human serous epithelial OvCa cell lines, serous tumors, and short-term primary cultures of normal ovarian surface epithelium (NOSE). We expected that over-expression of a specific microRNA would lead to lower expression of its mRNA targets, and under-expression of a specific microRNA would lead to higher expression of its target genes. Using our expression data in conjunction with established in silico algorithms, we found putative microRNA:mRNA functional pairs. Furthermore, gene expression profiles were taken of serous cultures having functional knockdown or over-expression of specific microRNAs of interest. Over-expression of mir-31 (found under-expressed in serous OvCa) resulted in down-regulation in vitro of a significant number of the in silico predicted mir-31 target genes.

Publication Title

Molecular profiling uncovers a p53-associated role for microRNA-31 in inhibiting the proliferation of serous ovarian carcinomas and other cancers.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE11852
Effect of uniconazole on wt and pkl mutant germinating seeds
  • organism-icon Arabidopsis thaliana
  • sample-icon 23 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Relative expression data from germinating seeds of Columbia (wt), the pkl mutant (pkl), Columbia plus uniconazole-P (Uwt) and the pkl-mutant plus uniconazole-P (Upkl).

Publication Title

The CHD3 remodeler PICKLE promotes trimethylation of histone H3 lysine 27.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE12767
Chorionic villus sampling (CVS) microarray in preeclampsia
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

4 chorionic villus sampling specimens in pregnancies destined for preeclampsia and 8 matched controls were analyzed

Publication Title

Altered global gene expression in first trimester placentas of women destined to develop preeclampsia.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE109597
Predictive computational obesity risk framework through integration of gene expression profiles and genetic risk score.
  • organism-icon Homo sapiens
  • sample-icon 82 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We aimed to predict obesity risk with genetic data, specifically, obesity-associated gene expression profiles. Genetic risk score was computed. The genetic risk score was significantly correlated with BMI when an optimization algorithm was used. Linear regression and built support vector machine models predicted obesity risk using gene expression profiles and the genetic risk score with a new mathematical method.

Publication Title

A computational framework for predicting obesity risk based on optimizing and integrating genetic risk score and gene expression profiles.

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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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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