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accession-icon GSE138086
Expression data from SAN tissue of WT and HCN4FEA mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.1 ST Array (mogene21st)

Description

HCN4 channels are the major HCN channel isoform expressed in the sinoatrial node (SAN) and play a key role in cardiac pacemaking. We have characterized the gene expression profile in the SAN of adult mice expressing cAMP-insensitive HCN4 channels (HCN4FEA mice) in comparison to WT mice.

Publication Title

cAMP-dependent regulation of HCN4 controls the tonic entrainment process in sinoatrial node pacemaker cells.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE33774
Expression data from gingival tissue
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The experiment aims to identify transcriptional effects differences between periimplantitis, Parodontitis and healthy gingival tissue

Publication Title

Peri-implantitis versus periodontitis: functional differences indicated by transcriptome profiling.

Sample Metadata Fields

Specimen part

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accession-icon GSE3254
Variability in Microarray Labeling Methods
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95 Version 2 Array (hgu95av2)

Description

Considerable variation in gene expression data from different DNA microarray platforms has been demonstrated. However, no characterization of the source of variation arising from labeling protocols has been performed. To analyze the variation associated with T7-based RNA amplification/labeling methods, aliquots of the Stratagene Human Universal Reference RNA were labeled using 3 eukaryotic target preparation methods and hybridized to a single array type (Affymetrix U95Av2). Variability was measured in yield and size distribution of labeled products, as well as in the gene expression results. All methods showed a shift in cRNA size distribution, when compared to un-amplified mRNA, with a significant increase in short transcripts for methods with long IVT reactions. Intra-method reproducibility showed correlation coefficients >0.99, while inter-method comparisons showed coefficients ranging from 0.94 to 0.98 and a nearly two-fold increase in coefficient of variation. Fold amplification for each method was positively correlated with the number of present genes. Two factors that introduced significant bias in gene expression data were observed: a) number of labeled nucleotides that introduces sequence dependent bias, and b) the length of the IVT reaction that introduces a transcript size dependent bias. This study provides evidence of amplification method dependent biases in gene expression data.

Publication Title

In vitro transcription amplification and labeling methods contribute to the variability of gene expression profiling with DNA microarrays.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE6919
Expression Data from Normal and Prostate Tumor Tissues
  • organism-icon Homo sapiens
  • sample-icon 503 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95C Array (hgu95c)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Age, Specimen part, Race

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accession-icon GSE6606
Expression data from Primary Prostate Tumor
  • organism-icon Homo sapiens
  • sample-icon 196 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95B Array (hgu95b)

Description

Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Specimen part

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accession-icon GSE6608
Expression data from Normal Prostate Tissue Adjacent to Tumor
  • organism-icon Homo sapiens
  • sample-icon 181 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95C Array (hgu95c)

Description

Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Specimen part

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accession-icon GSE6605
Expression data from Metastatic Prostate Tumor
  • organism-icon Homo sapiens
  • sample-icon 74 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a), Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95B Array (hgu95b)

Description

Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE6604
Expression data from Normal Prostate Tissue free of any pathological alteration
  • organism-icon Homo sapiens
  • sample-icon 52 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95A Array (hgu95a)

Description

Prostate cancer is characterized by heterogeneity in the clinical course that often does not to correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. The metastatic samples are highly heterogeneous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodeling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.

Publication Title

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Sample Metadata Fields

Age, Specimen part, Race

View Samples
accession-icon GSE68555
caArray_becic-00235: Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy
  • organism-icon Homo sapiens
  • sample-icon 444 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95A Array (hgu95a)

Description

The incidence of prostate cancer is frequent, occurring in almost one-third of men older than 45 years. Only a fraction of the cases reach the stages displaying clinical significance. Despite the advances in our understanding of prostate carcinogenesis and disease progression, our knowledge of this disease is still fragmented. Identification of the genes and patterns of gene expression will provide a more cohesive picture of prostate cancer biology. PATIENTS AND METHODS: In this study, we performed a comprehensive gene expression analysis on 152 human samples including prostate cancer tissues, prostate tissues adjacent to tumor, and organ donor prostate tissues, obtained from men of various ages, using the Affymetrix (Santa Clara, CA) U95a, U95b, and U95c chip sets (37,777 genes and expression sequence tags). RESULTS: Our results confirm an alteration of gene expression in prostate cancer when comparing with nontumor adjacent prostate tissues. However, our study also indicates that the gene expression pattern in tissues adjacent to cancer is so substantially altered that it resembles a cancer field effect. CONCLUSION: We also found that gene expression patterns can be used to predict the aggressiveness of prostate cancer using a novel model.

Publication Title

Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE3325
Integrative Genomic and Proteomic Analysis of Prostate Cancer Reveals Signatures of Metastatic Progression
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed revealing only 48-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors.

Publication Title

Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression.

Sample Metadata Fields

No sample metadata fields

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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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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