Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Characterization of gene expression profiles of gastric cancer in MD Anderson Cancer Center cohort

ABSTRACT: Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from patients with advanced gastric cancer and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis.

ORGANISM(S): Homo sapiens

PROVIDER: GSE28541 | GEO | 2012/04/30

SECONDARY ACCESSION(S): PRJNA139053

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Characterization of gene expression profiles of gastric cancer in MD Anderson Cancer Center cohort

Project description:Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from patients with advanced gastric cancer and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis. Using microarray technologies, we analyzed gene expression profiling data from patients with advanced gastric cancer and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis.

2012-04-29 | E-GEOD-28541 | biostudies-arrayexpress

Characterization of gene expression profiles of gastric cancer in Kosin University cohort

Project description:Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from gastric cancer patients and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis and response to adjuvant chemotherapy.

2016-12-31 | GSE26901 | GEO

Characterization of gene expression profiles of gastric cancer in the Korea University cohort

Project description:Clinical heterogeneity of gastric cancer reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of gastric cancer. Using microarray technologies, we analyzed gene expression profiling data from gastric cancer patients and uncovered potential prognostic subtypes and identify gene expression signature associated with prognosis and response to adjuvant chemotherapy.

2016-12-31 | GSE26899 | GEO

Mesenchymal subtypes of hepatocellular carcinoma

Project description:Clinical heterogeneity of hepatocellular carcinoma (HCC) reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of HCC. Using microarray technologies, we analyzed gene expression profiling data from HCC patients, uncovered mesenchymal subtype, and identified gene expression signature associated with mesenchymal phenotype of HCC.

2020-07-01 | GSE134568 | GEO

Proteomic characteristics of mesenchymal subtypes of hepatocellular carcinoma

Project description:Clinical heterogeneity of hepatocellular carcinoma (HCC) reflected in unequal outcome of treatment is poorly defined in molecular level, and molecular subtypes and their associated biomarkers have not been established to improve prognostification and treatment of HCC. Using reverse phase protein arrays (RPPA) technologies, we analyzed protein expression profiling data from HCC patients, uncovered mesenchymal subtype, and identified gene expression signature associated with mesenchymal phenotype of HCC.

2024-01-01 | GSE199141 | GEO

Gastric Cancer Subtyping (Australian Patient Cohort)

Project 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. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-xpression-based clustering of a large collection of gastric adenocarcinomas from Singaporean patients [GSE34942 and GSE15459]. We developed and validated a classifier for the three subtypes in Australian patient cohort. Profiling of 70 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from Peter MacCallum Cancer Center, Australia; the Research Ethics Review Committee; and signed patient informed consent.

2012-07-04 | E-GEOD-35809 | biostudies-arrayexpress

Gastric Cancer Subtyping (Australian Patient Cohort)

2012-07-05 | GSE35809 | GEO

Gastric cancer subtyping (Singapore Patient Cohort, batch B)

Project description:Genome-wide mRNA expression profiles of 56 primary gastric tumors from the Singapore patient cohort, batch B. 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. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-expression-based clustering of a large collection of gastric adenocarcinomas (with GSE15459) from Singaporean patients. Profiling of 56 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from the National Cancer Centre, Singapore; the Research Ethics Review Committee; and signed patient informed consent.

2014-09-05 | E-GEOD-34942 | biostudies-arrayexpress

Gastric cancer subtyping (Singapore Patient Cohort, batch B)

2014-09-05 | GSE34942 | GEO