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accession-icon GSE104786
Expression data from Neuroendocrine Prostate Cancer and Primary Small Cell Prostatic Carcinoma
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Neuroendocrine prostate cancer (NEPC) is rare historically but may be increasingin prevalence as patients potentially develop resistance to contemporary anti-androgen treatment through a neuroendocrine phenotype. Diagnosis can be straightforward when classic morphological features are accompanied by a prototypical immunohistochemistry profile, however there is increasing recognition of disease heterogeneity and hybrid phenotypes. In the primary setting, small cell prostatic carcinoma (SCPC) is frequently admixed with adenocarcinomas that may be clonally related, while a small fraction of SCPCs express markers typical of prostatic adenocarcinoma. Gene expression patterns may eventually help elucidate the biology underlying equivocal cases with discordant IHC, however studies to date have focused on prototypical cases and been based on few patients due to disease rarity.

Publication Title

Gene expression signatures of neuroendocrine prostate cancer and primary small cell prostatic carcinoma.

Sample Metadata Fields

Subject

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accession-icon GSE57933
Discovery and validation of a novel expression signature for recurrence in high-risk bladder cancer post-cystectomy
  • organism-icon Homo sapiens
  • sample-icon 199 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Purpose: Selecting muscle-invasive bladder cancer patients for adjuvant therapy is currently based on clinical variables with limited power. We hypothesized that genomic-based signatures can outperform clinical models to identify patients at higher risk. Method:Transcriptome-wide expression profiles were generated using 1.4 million feature-arrays on archival tumors from 225 patients who underwent radical cystectomy and had muscle-invasive and/or node-positive bladder cancer. A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set.

Publication Title

Discovery and validation of novel expression signature for postcystectomy recurrence in high-risk bladder cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE72220
Application of a clinical assay for staging and prognosis of prostate cancer diagnosed in needle core biopsy specimens
  • organism-icon Homo sapiens
  • sample-icon 147 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed and paraffin-embedded (FFPE) biopsies has many unique challenges. Here we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers from diagnostic prostate needle core biopsies.

Publication Title

Application of a Clinical Whole-Transcriptome Assay for Staging and Prognosis of Prostate Cancer Diagnosed in Needle Core Biopsy Specimens.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE80683
Association of Multiparametric MRI Quantitative Imaging Features with Prostate Cancer Gene Expression in MRI-targeted Prostate Biopsies
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective is to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues.

Publication Title

Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE73989
Chromatin relaxation is a feature of advanced prostate cancer
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Androgen Receptor Deregulation Drives Bromodomain-Mediated Chromatin Alterations in Prostate Cancer.

Sample Metadata Fields

Specimen part, Cell line, Time

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accession-icon GSE73930
Chromatin relaxation is a feature of advanced prostate cancer [expression]
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Altered patterns of transcription factor (TF) binding are now accepted as a hallmark of many aggressive cancers including prostate and breast cancers1,2. This implies that underlying global changes in chromatin accessibility may drive cancer progression, as previously hypothesized3-5. In addition there are epigenetic readers such as bromodomain containing protein 4 (BRD4), which have been shown to associate with these TFs6-8 and also to contribute to aggressive cancers of many types8,9 including prostate cancer (PC)6,10. Here we show for the first time that formaldehyde-assisted isolation of regulatory elements followed by sequencing (FAIRE-seq) applied to human prostate tumors tissue can define castrate-resistant prostate cancer (CRPC) and can be used to inform the discovery of gene-level classifiers for therapy. In addition, we show that the androgen receptor (AR) overexpression alone is a primary driver for chromatin relaxation and that this effect can be reversed using bromodomain inhibitors. We also report that bromodomain-containing proteins (BRDs) are overexpressed in advanced CRPCs and that ATAD2 and BRD2 have prognostic value. In conclusion, this is the first study demonstrating a major impact of BRDs on chromatin accessibility in CRPC in patient samples. Consequently, targeting bromodomains provides a compelling rational for combination therapy in which BRD-mediated TF binding is enhanced or modified as cancer progresses.

Publication Title

Androgen Receptor Deregulation Drives Bromodomain-Mediated Chromatin Alterations in Prostate Cancer.

Sample Metadata Fields

Time

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accession-icon GSE66852
Therapy-Induced Developmental Reprogramming of Prostate Cancer Cells and Acquired Resistance
  • organism-icon Homo sapiens
  • sample-icon 6 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

Therapy-induced developmental reprogramming of prostate cancer cells and acquired therapy resistance.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE149596
Transcriptomic fingerprints of C. elegans exposed to sodium perchlorate.
  • organism-icon Caenorhabditis elegans
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Gene 1.0 ST Array (elegene10st)

Description

The excessive perchlorate utilization as an oxidizer in rocket propellants and blasting agents had led to the contamination of surface and ground waters. This chemical is known to compete with iodine for binding to the thyroid membrane receptors potentially causing hypothyroidism and fetal retardation in pregnant women. Nevertheless, to date, its biological effects are not completely understood. We have investigated the molecular mechanisms responsive to perchlorate in the nematode C. elegans to nominate a candidate gene for further peruse in the development of a C.elegans perchlorate biosensor. Perchlorate (1 mg/mL) affected the transcriptional response of Regulation of developmental process, growth, defense mechanisms and stress response, among other biological processes.

Publication Title

Perchlorate detection <i>via</i> an invertebrate biosensor.

Sample Metadata Fields

Treatment

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accession-icon GSE70051
Identifying pH independent hypoxia induced genes in human squamous cell carcinomas in vitro
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background: Genes upregulated by low oxygen have been suggested as endogenous markers for tumor hypoxia. Yet, most of the genes investigated have shown inconsistent results, which have led to concerns about their ability to be true hypoxia markers. Previous studies have demonstrated that expression of hypoxia induced genes can be affected by extracellular pH (pH e ). Methods: Five different human cell lines (SiHa, FaDu DD, UTSCC5, UTSCC14 and UTSCC15) were exposed to different oxygen concentrations and pH (7.5 or 6.3), and gene expression analyzed with microarray (Affymetrix - Human Genome U133 Plus 2.0 Array). Results: An analysis of two of the cell lines using SAM identified 461 probesets that were able to separate the four groups Normal oxygen, normal pH , Low oxygen, normal pH , Normal oxygen, low pH and Low oxygen, low pH . From here it was possible to identify a fraction of probesets induced at low oxygen independent of pH in these two cell lines, this fraction included HIG2, NDRG1, PAI1 and RORA. Further verifi cation by qPCR highlighted the necessity of using more cell lines to obtain a robust gene expression profi les. To specifi cally select pH independent hypoxia regulated genes across more cell lines, data for FaDu DD, UTSCC5, UTSCC14 and UTSCC15 were analyzed to identify genes that were induced by hypoxia in each cell line, where the induction was not affected by low pH, and where the gene was not signifi cantly induced by low pH alone. Each cell line had 65 122 probesets meeting these criteria. For genes to be considered as target genes (hypoxia inducible pH independent), genes had to be present in three of four cell lines. Conclusion: The result is a robust hypoxia profile unaffected by pH across cell lines consisting of 27 genes. This study demonstrates a way to identify hypoxia markers by microarray, where other factors in the tumor microenvironment are taken into account.

Publication Title

Identifying pH independent hypoxia induced genes in human squamous cell carcinomas in vitro.

Sample Metadata Fields

Cell line

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accession-icon GSE65675
LOXL2 dependent genes in RA induced mES differentiation
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Our results indicate that oxidation of TAF10 by LOXL2 induces its release from its promoters, leading to a block in TFIID-dependent gene transcription. Since TFIID complex is crucial for the expression of Nanog, Klf4, Sox2 and Oct4 and for maintaining the pluripotent state of embryonic stem cells, TAF10 oxidation by LOXL2 leads to inactivation of the pluripotency genes and a loss of pluripotent capacity in embryonic stem cells. Moreover, in vivo results demonstrate an essential role of LOXL2 in neural differentiation during zebrafish development: in the absence of LOXL2 the neural progenitor gene Sox2 is aberrantly overexpressed and neural differentiation is impaired.

Publication Title

LOXL2 Oxidizes Methylated TAF10 and Controls TFIID-Dependent Genes during Neural Progenitor Differentiation.

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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