Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Breast cancer relapse free survival

ABSTRACT: This series represents 180 lymph-node negative relapse free patients and 106 lymph-node negate patients that developed a distant metastasis. Please see attached patient clinical parameters sheet for more information (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?view=data&acc=GSE2034&id=40089&db=GeoDb_blob26). Keywords: other

ORGANISM(S): Homo sapiens

SUBMITTER: Tim Jatkoe

PROVIDER: E-GEOD-2034 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genome-wide analysis of estrogen receptor binding sites.

Carroll Jason S JS Meyer Clifford A CA Song Jun J Li Wei W Geistlinger Timothy R TR Eeckhoute Jérôme J Brodsky Alexander S AS Keeton Erika Krasnickas EK Fertuck Kirsten C KC Hall Giles F GF Wang Qianben Q Bekiranov Stefan S Sementchenko Victor V Fox Edward A EA Silver Pamela A PA Gingeras Thomas R TR Liu X Shirley XS Brown Myles M

Nature genetics 20061001 11

The estrogen receptor is the master transcriptional regulator of breast cancer phenotype and the archetype of a molecular therapeutic target. We mapped all estrogen receptor and RNA polymerase II binding sites on a genome-wide scale, identifying the authentic cis binding sites and target genes, in breast cancer cells. Combining this unique resource with gene expression data demonstrates distinct temporal mechanisms of estrogen-mediated gene regulation, particularly in the case of estrogen-suppre ...[more]

PMID: 17013392

Publication: 1/2

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Project description:Lymph node involvement is the most important prognostic factor in breast cancer, but little is known about the underlying molecular changes. First, to identify a molecular signature associated with nodal metastasis, gene expression analysis was performed on a homogeneous group of 96 primary breast tumors, balanced for lymph node involvement. Each tumor was diagnosed as a poorly differentiated, estrogen positive, her2-neu negative invasive ductal cancer. (Affymetrix Human U133 Plus 2.0 microarray chips). A model, including 241 genes was built and validated on an internal and external dataset performed with Affymetrix technology. All samples used for validation had the same characteristics as the initial tumors. The area under the ROC curve (AUC) for the internal dataset was 0.646 and 0.651 for the external datasets. Thus, the molecular profile of a breast tumor reveals information about lymph node involvement, even in a homogeneous group of tumors. However, an AUC of 0.65 indicates only a weak correlation. Our model includes multiple kinases, apoptosis related and zinc ion binding genes. Pathway analysis using the Molecular Signatures Database revealed relevant gene sets (BAF57, Van 't Veer). Next, miRNA profiling was performed on 82/96 tumors using Human MiRNA microarray chips (Illumina). Eight miRNAs were significantly differentially expressed according to lymph node status at a significance level of 0.05, without correcting for multiple testing. The analysis of the inverse correlation between a miRNA and its computationally predicted targets point to general deregulation of the miRNA machinery potentially responsible for lymph node invasion. In conclusion, our results provide evidence that lymph node involvement in breast cancer is not a random process. Gene expression profiling: A training set of 96 patients and an independent internal dataset of 20 patients balanced for lymph node involvement was selected from the multidisciplinary breast centre database miRNA profiling not provided in this Series.

Dataset Information

Breast cancer relapse free survival

Publications

Genome-wide analysis of estrogen receptor binding sites.

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