Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA140851 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The aim of this study is to identify prognostic gene expression signatures associated with two molecularly distinct subtypes of colorectal cancer. Samples were taken from colorectal cancers in surgically resected specimens in 96 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133Plus 2.0 arrays. This is a test set for validation of prognostic gene expression signature that was developed from GSE14333. All data were normalized by using the RMA method (affy package in R/Bioconductor).
2011-06-20 | GSE29971 | GEO
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
Project description:Wiskott-Aldrich syndrome (WAS) predisposes patients to leukemia and lymphoma. WAS is caused by mutations in the protein WASP which impair its interaction with the WIPF1 protein. Here, we aim to identify a module of WIPF1-coexpressed genes and to assess its use as a prognostic signature for colorectal cancer, glioma, and breast cancer patients. Two public colorectal cancer microarray data sets were used for discovery and validation of the WIPF1 co-expression module. Based on expression of the WIPF1 signature, we classified more than 400 additional tumors with microarray data from our own experiments or from publicly available data sets according to their WIPF1 signature expression. This allowed us to separate patient populations for colorectal cancers, breast cancers, and gliomas for which clinical characteristics like survival times and times to relapse were analyzed. Groups of colorectal cancer, breast cancer, and glioma patients with low expression of the WIPF1 co-expression module generally had a favorable prognosis. In addition, the majority of WIPF1 signature genes are individually correlated with disease outcome in different studies. Literature gene network analysis revealed that among WIPF1 co-expressed genes known direct transcriptional targets of c-myc, ESR1 and p53 are enriched. The mean expression profile of WIPF1 signature genes is correlated with the profile of a proliferation signature. The WIPF1 signature is the first microarray-based prognostic expression signature primarily developed for colorectal cancer that is instrumental in other tumor types: low expression of the WIPF1 module is associated with better prognosis. We used microarrays for the validation of a WIPF1 co-expression module which was developed on two publically available datasets. Keywords: disease state analysis For the generation of our own microarray data set, 62 CRC patients undergoing elective standard oncological resection at the Department of General, Vascular and Thoracic Surgery, Campus Benjamin Franklin, Charité, were prospectively recruited.
2009-05-04 | E-GEOD-12945 | biostudies-arrayexpress
Project description:Integrated analyses reveal two molecularly and clinically distinct subtypes of H3 K27M-mutant diffuse midline gliomas with prognostic significance
| PRJNA1129172 | ENA
Project description:Wiskott-Aldrich syndrome (WAS) predisposes patients to leukemia and lymphoma. WAS is caused by mutations in the protein WASP which impair its interaction with the WIPF1 protein. Here, we aim to identify a module of WIPF1-coexpressed genes and to assess its use as a prognostic signature for colorectal cancer, glioma, and breast cancer patients. Two public colorectal cancer microarray data sets were used for discovery and validation of the WIPF1 co-expression module. Based on expression of the WIPF1 signature, we classified more than 400 additional tumors with microarray data from our own experiments or from publicly available data sets according to their WIPF1 signature expression. This allowed us to separate patient populations for colorectal cancers, breast cancers, and gliomas for which clinical characteristics like survival times and times to relapse were analyzed. Groups of colorectal cancer, breast cancer, and glioma patients with low expression of the WIPF1 co-expression module generally had a favorable prognosis. In addition, the majority of WIPF1 signature genes are individually correlated with disease outcome in different studies. Literature gene network analysis revealed that among WIPF1 co-expressed genes known direct transcriptional targets of c-myc, ESR1 and p53 are enriched. The mean expression profile of WIPF1 signature genes is correlated with the profile of a proliferation signature. The WIPF1 signature is the first microarray-based prognostic expression signature primarily developed for colorectal cancer that is instrumental in other tumor types: low expression of the WIPF1 module is associated with better prognosis. We used microarrays for the validation of a WIPF1 co-expression module which was developed on two publically available datasets. Keywords: disease state analysis
2009-05-04 | GSE12945 | GEO
Project description:Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme
| PRJNA95201 | ENA
Project description:A gene expression signature identifies two prognostic subgroups of basal breast cancer
| PRJNA125879 | ENA
Project description:The objective of this study is to identify a prognostic signature in colorectal cancer (CRC) patients with diverse progression and heterogeneity of CRCs. We generated RNA-seq data of 54 samples (normal colon, primary CRC, and liver metastasis) from 18 CRC patients and, from the RNA-seq data, identified significant genes associated with aggressiveness of CRC. Through diverse statistical methods including generalized linear model likelihood ratio test, two significantly activated regulators were identified. In the validation cohorts, two activated regulators were independent risk factors and potential chemotherapy-sensitive agenets in colorectal cancers.
2014-08-31 | GSE50760 | GEO
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.
2012-04-30 | GSE28541 | GEO
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