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accession-icon GSE57200
Expression profile after stable HIF-1a inhibition in gastric cancer cells under normoxic conditions
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HumanRef-8 v3.0 expression beadchip

Description

Based on the results of numerous clinical and preclinical analyses, the transcription factor HIF-1a has been identified as an important tumor-promoting factor and is considered to be an attractive target for cancer therapy. To further deconstruct the molecular nature of HIF-1as role in tumorigenesis, we have applied lentiviral shRNA transduction to establish HIF-1a-deficient gastric cancer cells. Interestingly, functional analyses failed to show a significant growth defect of HIF-1a-deficient gastric cancer cells in vitro and in vivo. These observations led us to propose that stable inactivation of HIF-1a resulted in efficient compensation enabling cell growth and, ultimately, tumor progression in a HIF-1a-independent manner. To better understand the mechanisms that control this compensation, we performed transcriptomics of control (scrambled (SCR)) and HIF-1a-deficient (HIF) gastric cancer cells.

Publication Title

Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE15460
Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer
  • organism-icon Homo sapiens
  • sample-icon 351 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a), Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Oncogenic pathway combinations predict clinical prognosis in gastric cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE37023
Comprehensive Genomic Meta-analysis Identifies Intra-Tumoral Stroma as a Predictor of Gastric Cancer Patient Survival
  • organism-icon Homo sapiens
  • sample-icon 213 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Background and Aims: Gastric adenocarcinoma (gastric cancer, GC) is a major cause of global cancer mortality. Identifying molecular programs contributing to GC patient survival may improve our understanding of GC pathogenesis, highlight new prognostic factors, and reveal novel therapeutic targets. We aimed to produce a comprehensive inventory of gene expression programs expressed in primary GCs, and to identify those expression programs significantly associated with patient survival.

Publication Title

Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer.

Sample Metadata Fields

Specimen part

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accession-icon GSE15459
Gastric Cancer Project '08 (Singapore Patient Cohort)
  • organism-icon Homo sapiens
  • sample-icon 200 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133A Array (hgu133a)

Description

Genome-wide mRNA expression profiles of 200 primary gastric tumors from the Singapore patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups.

Publication Title

Oncogenic pathway combinations predict clinical prognosis in gastric cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE35809
Gastric Cancer Subtyping (Australian Patient Cohort)
  • organism-icon Homo sapiens
  • sample-icon 70 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities.

Publication Title

Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE22183
GEMINI (Gastric Encyclopedia of Molecular Interactions and Nodes for Intervention) : 37 unique Gastric cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Genome-wide mRNA expression profiles of 37 unique gastric cancer cell lines (GCCLs).

Publication Title

Oncogenic pathway combinations predict clinical prognosis in gastric cancer.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE15455
GEMINI (Gastric Encyclopedia of Molecular Interactions and Nodes for Intervention) Phases A-C
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Genome U133A Array (hgu133a)

Description

Genome-wide mRNA expression profiles of 25 unique gastric cancer cell lines (GCCLs). Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GCCLs, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups.

Publication Title

Oncogenic pathway combinations predict clinical prognosis in gastric cancer.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE15456
Primary Gastric Cancer Expression Profiles (UK Patient Cohort)
  • organism-icon Homo sapiens
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Genome-wide mRNA expression profiles of 31 primary gastric tumors from the UK patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups.

Publication Title

Oncogenic pathway combinations predict clinical prognosis in gastric cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE15537
GEMINI (Gastric Encyclopedia of Molecular Interactions and Nodes for Intervention) Phases A-C, normal skin fibroblasts
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Genome-wide mRNA expression profiles of normal skin fibroblasts, used as one of the (normal) references in the study. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups.

Publication Title

Oncogenic pathway combinations predict clinical prognosis in gastric cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE44675
Gaucher Disease: Transcriptome Analyses Using Microarray or mRNA Sequencing in a Mouse Model Treated with velaglucerase alfa or imiglucerase
  • organism-icon Mus musculus
  • sample-icon 55 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Gaucher disease: transcriptome analyses using microarray or mRNA sequencing in a Gba1 mutant mouse model treated with velaglucerase alfa or imiglucerase.

Sample Metadata Fields

Age, Specimen part, Treatment

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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