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accession-icon GSE7139
Comparative GeneChip expression profiling of four brain regions
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

Study on selective vulnerability of certain brain regions to oxidative stress. Here we selected 4 brain regions (hippocampal CA1 and CA3, cerebral cortex, and cerebellar granular layer) to study this phenomenon.

Publication Title

Genomic and biochemical approaches in the discovery of mechanisms for selective neuronal vulnerability to oxidative stress.

Sample Metadata Fields

Specimen part

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accession-icon GSE110695
TCPOBOP-induced hepatomegaly & hepatocyte proliferation is attenuated by combined disruption of MET & EGFR signaling in mice
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

TCPOBOP (1,4-Bis [2-(3,5-Dichloropyridyloxy)] benzene) is a constitutive androstane receptor (CAR) agonist that induces robust hepatocyte proliferation and hepatomegaly without any liver injury or tissue loss. TCPOBOP-induced direct hyperplasia has been considered to be CAR-dependent with no evidence of involvement of cytokines or growth factor signaling. Receptor tyrosine kinases (RTKs), MET and EGFR, are known to play a critical role in liver regeneration after partial hepatectomy, but their role in TCPOBOP-induced direct hyperplasia, not yet explored, is investigated in the current study. Disruption of the RTK-mediated signaling was achieved utilizing MET KO mice along with Canertinib treatment for EGFR inhibition. Combined elimination of MET and EGFR signaling [MET KO + EGFRi], but not individual disruption, dramatically reduced TCPOBOP-induced hepatomegaly and hepatocyte proliferation. TCPOBOP-driven CAR activation was not altered in [MET KO + EGFRi] mice, as measured by nuclear CAR translocation and analysis of typical CAR target genes. However, TCPOBOP induced cell cycle activation was impaired in [MET KO + EGFRi] mice due to defective induction of cyclins, which regulate cell cycle initiation and progression. TCPOBOP-driven induction of FOXM1, a key transcriptional regulator of cell cycle progression during TCPOBOP-mediated hepatocyte proliferation, was greatly attenuated in [MET KO + EGFRi] mice. Interestingly, TCPOBOP treatment caused transient decline in HNF4 expression concomitant to proliferative response; this was not seen in [MET KO + EGFRi] mice. Transcriptomic profiling revealed vast majority (~40%) of TCPOBOP-dependent genes mainly related to proliferative response, but not to drug metabolism, were differentially expressed in [MET KO + EGFRi] mice. Conclusion: Taken together, combined disruption of EGFR and MET signaling lead to dramatic impairment of TCPOBOP-induced proliferative response without altering CAR activation.

Publication Title

TCPOBOP-induced hepatomegaly & hepatocyte proliferation is attenuated by combined disruption of MET & EGFR signaling.

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

View Samples
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

View Samples
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 GSE117775
Effect of DGAT loss on hypoxic tumor cells growing under serum-deprived conditions
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

The metabolic enzyme diglyceride acyltransferase (DGAT) is responsible for the synthesis of triglycerides. Loss of its expression may sensitize cells to conditions of nutrient and oxygen that are commonly present in tumors. This study is designed to identify stress response pathways that may be induced following the shRNA-mediated knockdown of the two genes coding for the DGAT enzymes. In vitro growth conditions lacking serum and oxygen were used to mimic growth conditions commonly found in poorly perfused tumor domains

Publication Title

Triglycerides Promote Lipid Homeostasis during Hypoxic Stress by Balancing Fatty Acid Saturation.

Sample Metadata Fields

Specimen part, Cell line, Treatment

View Samples
accession-icon GSE117774
Effect of DGAT knockdown on gene expression in A498 xenograft tumors
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

The metabolic enzyme diglyceride acyltransferase (DGAT) is responsible for the synthesis of triglycerides. Loss of its expression may sensitize cells to conditions of nutrient and oxygen that are commonly present in tumors. This study is designed to identify stress response pathways that may be induced following the shRNA-mediated knockdown of the two genes coding for the DGAT enzymes.

Publication Title

Triglycerides Promote Lipid Homeostasis during Hypoxic Stress by Balancing Fatty Acid Saturation.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE77867
Combined blockade of MET and EGFR abolishes liver regeneration
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Receptor tyrosine kinases MET and EGFR are critically involved in initiation of liver regeneration. Other cytokines and signaling molecules also help in the early part of the process. Regeneration employs effective redundancy schemes to compensate for missing signals. Elimination of any single signaling pathway only delays but does not abolish the process. Our present study, however, shows that combined systemic elimination of MET and EGFR signaling abolishes liver regeneration, prevents restoration of liver mass and leads to liver decompensation. Our results demonstrate that liver function is dependent on synchronous availability of signaling from these two pathways. The study shows that MET and EGFR separately control many non-overlapping signaling endpoints, allowing for compensation when only one of the signals is blocked. The combined elimination of the signals however was not tolerated. The results provide critical new information on interactive MET and EGFR signaling and the contribution of their combined absence to regeneration arrest and liver decompensation.

Publication Title

Combined systemic elimination of MET and epidermal growth factor receptor signaling completely abolishes liver regeneration and leads to liver decompensation.

Sample Metadata Fields

Specimen part, Time

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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