Filters
Technology
Platform
GSE13898
Homo sapiens
118 Downloadable Samples
Illumina human-6 v2.0 expression beadchip
Description
Despite continual efforts to rationalize a prognostic stratification of patients with esophageal adenocarcinoma (EAC) before treatment, current staging system only shows limited success owing to the lack of molecular and genetic markers that reflect prognostic features of the tumor. To develop molecular predictors of prognosis, we used systems-level characterization of tumor transcriptome. Using DNA microarray, genome-wide gene expression profiling was performed on 75 biopsy samples from patients with untreated EAC. Various statistical and informatical methods were applied to gene expression data to identify potential biomarkers associated with prognosis. Potential marker genes were validated in an independent cohort using quantitiative RT-PCR to measure gene expression. Distinct subgroups of EAC were uncovered by systems-level characterization of tumor transcriptome. We also identified a six-gene expression signature that could be used to predict overall survival (OS) of EAC patients. In particular, expression of SPARC and SPP1 was a strong independent predictor of OS, and a combined gene expression signature with these two genes was associated with prognosis (P < 0.024), even when all relevant pathological variables were considered together in multivariate Cox hazard regression analysis. Our findings suggest that molecular features reflected in gene expression signatures may dictate the prognosis of EAC patients, and these gene expression signatures can be used to predict the likelihood of prognosis at the time of diagnosis and before treatment.
Publication Title
Prognostic biomarkers for esophageal adenocarcinoma identified by analysis of tumor transcriptome.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 90 Downloadable Samples
- Illumina HumanWG-6 v3.0 expression beadchip
Description
Despite continual efforts to establish pre-operative prognostic model of gastric cancer by using clinical and pathological parameters, a staging system that reliably separates patients with early and advanced gastric cancer into homogeneous groups with respect to prognosis does not exist. With use of microarray and quantitative RT-PCR technologies, we exploited series of experiments in combination with complementary data analyses on tumor specimens from 161 gastric cancer patients. Various statistical analyses were applied to gene expression data to uncover subgroups of gastric cancer, to identify potential biomarkers associated with prognosis, and to construct molecular predictor of risk from identified prognostic biomarkers.Two subgroups of gastric cancer with strong association with prognosis were uncovered. The robustness of prognostic gene expression signature was validated in independent patient cohort with use of support vector machines prediction model. For easy translation of our finding to clinics, we develop scoring system based on expression of six genes that can predict the likelihood of recurrence after curative resection of tumors. In multivariate analysis, our novel risk score was an independent predictor of recurrence (P=0.004) in cohort of 96 patients, and its robustness was validated in two other independent cohorts. We identified novel prognostic subgroups of gastric cancer that are distinctive in gene expression patterns. Six-gene signature and risk score derived from them has been validated for predicting the likelihood of survival at diagnosis.
Publication Title
Gene expression signature-based prognostic risk score in gastric cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 213 Downloadable Samples
- 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
View Samples- Homo sapiens
- 70 Downloadable Samples
- 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- Homo sapiens
- 17 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
H19 Noncoding RNA, an Independent Prognostic Factor, Regulates Essential Rb-E2F and CDK8-β-Catenin Signaling in Colorectal Cancer.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
Knockdown of H19 leads to cell cycle arrest, reduced cell proliferation, and reduced cell migration in HCT116 cells.
Publication Title
H19 Noncoding RNA, an Independent Prognostic Factor, Regulates Essential Rb-E2F and CDK8-β-Catenin Signaling in Colorectal Cancer.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 4 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
We used microarrays to detail the global programme of gene expression following CTNNB1 knockdown in HCT116 cells
Publication Title
H19 Noncoding RNA, an Independent Prognostic Factor, Regulates Essential Rb-E2F and CDK8-β-Catenin Signaling in Colorectal Cancer.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 4 Downloadable Samples
Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
We used microarrays to detail the global programme of gene expression following CDK8 knockdown in HCT116 cells
Publication Title
H19 Noncoding RNA, an Independent Prognostic Factor, Regulates Essential Rb-E2F and CDK8-β-Catenin Signaling in Colorectal Cancer.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 3 Downloadable Samples
- Affymetrix Human Transcriptome Array 2.0 (hta20)
Description
Knockdown of H19 leads to cell cycle arrest, reduced cell proliferation, and reduced cell migration in DLD1 cells.
Publication Title
H19 Noncoding RNA, an Independent Prognostic Factor, Regulates Essential Rb-E2F and CDK8-β-Catenin Signaling in Colorectal Cancer.
Sample Metadata Fields
Cell line, Treatment
View Samples- Homo sapiens
- 57 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
We study the global gene expression profiles of BKV viremia and nephropathy patients using microarrays in order to better understand the immunologic response to polyomavirus BK (BKV).
Publication Title
Genomics of BK viremia in kidney transplant recipients.
Sample Metadata Fields
Specimen part, Disease
View Samples