Unknown,Transcriptomics,Genomics,Proteomics

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Comparison of gene expression data from human and mouse breast cancers: Identification of conserved breast tumor genes

ABSTRACT: The aim of our work was the comparison of human and mouse gene expression data and to identify a conserved breast tumor gene set. The results encourage the usefulness of transgenic mice as a model for human breast cancer formation and therapy. Keywords: Comparison of gene expression data The aim of our work was to establish a database for breast cancer gene expression data in order to compare human and mouse breast cancer. We identified human and mouse homologues genes and compared the expression profile of 24 human breast tumors with six WAP-SVT/t breast tumors (WAP-SVT/t animals, line 8). Our studies confirmed the heterogeneity in gene expression of human as well as mouse breast cancer cells. However, 63 genes were found to be differentially expressed (upregulated: 40; downregulated: 23 genes) in at least 75% of the breast tumors of both species.

ORGANISM(S): Homo sapiens

SUBMITTER: Andreas Klein

PROVIDER: E-GEOD-6596 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Comparison of gene expression data from human and mouse breast cancers: identification of a conserved breast tumor gene set.

Klein Andreas A Wessel Ralf R Graessmann Monika M Jürgens Martin M Petersen Iver I Schmutzler Rita R Niederacher Dieter D Arnold Norbert N Meindl Alfons A Scherneck Siegfried S Seitz Susanne S Graessmann Adolf A

International journal of cancer 20070801 3

The aim of our work was to establish a database for breast cancer gene expression data in order to compare human and mouse breast cancer. We identified human and mouse homologues genes and compared the expression profile of 24 human breast tumors with 6 WAP-SVT/t breast tumors (WAP-SVT/t animals, line 8). Our studies confirmed the heterogeneity in gene expression of human as well as mouse breast cancer cells. However, 63 genes were found to be differentially expressed (upregulated: 40; downregul ...[more]

PMID: 17410534

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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

Comparison of gene expression data from human and mouse breast cancers: Identification of conserved breast tumor genes

Publications

Comparison of gene expression data from human and mouse breast cancers: identification of a conserved breast tumor gene set.

Similar Datasets

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