Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: GSE20713
PROVIDER: PRJNA124907 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Epigenetic portraits of human breast cancers (methylation data)
| PRJNA129579 | ENA
Project description:Epigenetic portraits of human breast cancers (expression data)
| PRJNA129577 | ENA
Project description:Epigenetic portraits of human breast cancers (methylation data 2)
| PRJNA128645 | ENA
Project description:Epigenetic portraits of human breast cancers (HCT116 cell line data)
| PRJNA129631 | ENA
Project description:Epigenetic portraits of human breast cancers (various cell lines expression data)
| PRJNA128647 | ENA
Project description:Epigenetic portraits of human breast cancers (various cell lines methylation data)
| PRJNA128711 | ENA
Project description:Breast cancer is a molecularly, biologically and clinically heterogeneous group of disorders. Understanding this diversity is essential to improving diagnosis and optimising treatment. Both genetic and acquired epigenetic abnormalities participate in cancer, but information is scant on the involvement of the epigenome in breast cancer and its contribution to the complexity of the disease. Here we used the Infinium Methylation Platform to profile at single-CpG resolution (over 14,000 genes interrogated) the methylomes of 119 breast tumours. It emerges that many genes whose expression is linked to the ER status are epigenetically controlled (or/ we show that the two major phenotypes of breast cancers determined by ER status are widely involving epigenetic regulatory mechanisms), offering the prospect of a novel approach to treating ER-positive tumours. We have distinguished methylation-profile-based tumour clusters, some coinciding with known “expression subtypes” but also new entities that may provide a meaningful basis for refining breast tumour typology. We show that methylation patterns may reflect the cellular origins of tumours. Having highlighted an unexpectedly strong epigenetic component in the regulation of key immune pathways, we show that a set of immune genes have high prognostic value in specific tumour categories. By laying the ground for better understanding of breast cancer heterogeneity and improved tumour taxonomy, the precise epigenetic portraits drawn here should contribute to better management of breast cancer patients. Gene expression profiling cell lines. Study of epigenetic variation (methylation) linked to gene expression. No replicate, no reference sample.
2011-10-18 | E-GEOD-22250 | biostudies-arrayexpress
Project description:Breast cancer is a molecularly, biologically and clinically heterogeneous group of disorders. Understanding this diversity is essential to improving diagnosis and optimising treatment. Both genetic and acquired epigenetic abnormalities participate in cancer, but information is scant on the involvement of the epigenome in breast cancer and its contribution to the complexity of the disease. Here we used the Infinium Methylation Platform to profile at single-CpG resolution (over 14,000 genes interrogated) the methylomes of 119 breast tumours. It emerges that many genes whose expression is linked to the ER status are epigenetically controlled (or/ we show that the two major phenotypes of breast cancers determined by ER status are widely involving epigenetic regulatory mechanisms), offering the prospect of a novel approach to treating ER-positive tumours. We have distinguished methylation-profile-based tumour clusters, some coinciding with known “expression subtypes” but also new entities that may provide a meaningful basis for refining breast tumour typology. We show that methylation patterns may reflect the cellular origins of tumours. Having highlighted an unexpectedly strong epigenetic component in the regulation of key immune pathways, we show that a set of immune genes have high prognostic value in specific tumour categories. By laying the ground for better understanding of breast cancer heterogeneity and improved tumour taxonomy, the precise epigenetic portraits drawn here should contribute to better management of breast cancer patients. 125 gene expression profiling of breast tissues (117 tumors + 8 normal). Study of epigenetic variation (methylation) linked to gene expression. No replicate, no reference sample.
2011-10-18 | E-GEOD-22249 | biostudies-arrayexpress
Project description:Breast cancer is a molecularly, biologically and clinically heterogeneous group of disorders. Understanding this diversity is essential to improving diagnosis and optimising treatment. Both genetic and acquired epigenetic abnormalities participate in cancer, but information is scant on the involvement of the epigenome in breast cancer and its contribution to the complexity of the disease. Here we used the Infinium Methylation Platform to profile at single-CpG resolution (over 14,000 genes interrogated) the methylomes of 119 breast tumours. It emerges that many genes whose expression is linked to the ER status are epigenetically controlled (or/ we show that the two major phenotypes of breast cancers determined by ER status are widely involving epigenetic regulatory mechanisms), offering the prospect of a novel approach to treating ER-positive tumours. We have distinguished methylation-profile-based tumour clusters, some coinciding with known “expression subtypes” but also new entities that may provide a meaningful basis for refining breast tumour typology. We show that methylation patterns may reflect the cellular origins of tumours. Having highlighted an unexpectedly strong epigenetic component in the regulation of key immune pathways, we show that a set of immune genes have high prognostic value in specific tumour categories. By laying the ground for better understanding of breast cancer heterogeneity and improved tumour taxonomy, the precise epigenetic portraits drawn here should contribute to better management of breast cancer patients. 123 gene expression profiling breast cancer patients. Study of epigenetic variation (methylation) linked to gene expression. No replicate, no reference sample.
2011-10-18 | E-GEOD-20712 | biostudies-arrayexpress