Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA140059 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Gene expression profiles were generated from 199 primary breast cancer patients. Samples 1-176 were used in another study, GEO Series GSE22820, and form the training data set in this study. Sample numbers 200-222 form a validation set. This data is used to model a machine learning classifier for Estrogen Receptor Status. RNA was isolated from 199 primary breast cancer patients. A machine learning classifier was built to predict ER status using only three gene features.
2013-01-01 | E-GEOD-29210 | biostudies-arrayexpress
Project description:Gene expression profiles were generated from 199 primary breast cancer patients. Samples 1-176 were used in another study, GEO Series GSE22820, and form the training data set in this study. Sample numbers 200-222 form a validation set. This data is used to model a machine learning classifier for Estrogen Receptor Status.
2013-01-01 | GSE29210 | GEO
Project description:MicroRNA signatures predict Estrogen receptor, Progesterone receptor and HER2/neu receptor status in Breast Cancer
| PRJNA117047 | ENA
Project description:Lipid metabolism genes in contralateral unaffected breast and estrogen receptor status of breast cancer
| PRJNA177679 | ENA
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Keywords: Tumor sample comparison
2006-08-23 | GSE5546 | GEO
Project description:Comparison between Estrogen receptor positive and Estrogen receptor negative breast cancer samples
| PRJNA107971 | ENA
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1μg Cy3 labeled cRNA and 1 μg Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.
2008-06-13 | E-GEOD-5546 | biostudies-arrayexpress
Project description:Gene expression profiling of invasive breast cancer events from the tamoxifen prevention trial validates low estrogen receptor mRNA level as the main determinant of tamoxifen resistance in estrogen receptor positive breast cancer. In NSABP Breast Cancer Prevention Trial (BCPT), tamoxifen reduced the incidence of estrogen receptor (ER) positive tumors but not estrogen receptor negative breast cancer. More importantly, only 69% of estrogen receptor positive tumors were prevented by tamoxifen. The ER positive tumors arising in tamoxifen arm provides an ideal clinical model for acquired tamoxifen resistance. Based on data from NSABP trial B14 which showed linear prediction of the degree of benefit from adjuvant tamoxifen by the levels of ESR1 mRNA coding for ER-alpha, we hypothesized a priori that level of ESR1 mRNA would be lower in ER positive tumors arising in tamoxifen arm compared to those in placebo arm of BCPT. Keywords: Gene expression profiling analysis
2011-12-08 | GSE12665 | GEO
Project description:Expression levels of proteins and phosphoproteins, covering major cancer signaling pathways with a special focus on breast cancer biology, were obtained for a series of 109 breast cancer tumor specimens with positive estrogen receptor status.
2014-02-18 | GSE47066 | GEO
Project description:Expression levels of proteins and phosphoproteins, covering major cancer signaling pathways with a special focus on breast cancer biology, were obtained for a series of 164 breast cancer tumor specimens with positive estrogen receptor status.
2014-02-18 | GSE50861 | GEO