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Human mammary epithelium and breast cancer

ABSTRACT: Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. cDNA microarrays and a clustering algorithm were used to identify patterns of gene expression in human mammary epithelial cells growing in culture and in primary human breast tumors. Clusters of coexpressed genes identified through manipulations of mammary epithelial cells in vitro also showed consistent patterns of variation in expression among breast tumor samples. By using immunohistochemistry with antibodies against proteins encoded by a particular gene in a cluster, the identity of the cell type within the tumor specimen that contributed the observed gene expression pattern could be determined. Clusters of genes with coherent expression patterns in cultured cells and in the breast tumors samples could be related to specific features of biological variation among the samples. Two such clusters were found to have patterns that correlated with variation in cell proliferation rates and with activation of the IFN-regulated signal transduction pathway, respectively. Clusters of genes expressed by stromal cells and lymphocytes in the breast tumors also were identified in this analysis. These results support the feasibility and usefulness of this systematic approach to studying variation in gene expression patterns in human cancers as a means to dissect and classify solid tumors. This study is described more fully in Perou CM, et al. 1999. Proc Natl Acad Sci USA 96:9212-7 Keywords: other

ORGANISM(S): Homo sapiens

PROVIDER: GSE53 | GEO | 2002/06/27

SECONDARY ACCESSION(S): PRJNA85267

REPOSITORIES: GEO

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Human mammary epithelium and breast cancer

Project description:Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. cDNA microarrays and a clustering algorithm were used to identify patterns of gene expression in human mammary epithelial cells growing in culture and in primary human breast tumors. Clusters of coexpressed genes identified through manipulations of mammary epithelial cells in vitro also showed consistent patterns of variation in expression among breast tumor samples. By using immunohistochemistry with antibodies against proteins encoded by a particular gene in a cluster, the identity of the cell type within the tumor specimen that contributed the observed gene expression pattern could be determined. Clusters of genes with coherent expression patterns in cultured cells and in the breast tumors samples could be related to specific features of biological variation among the samples. Two such clusters were found to have patterns that correlated with variation in cell proliferation rates and with activation of the IFN-regulated signal transduction pathway, respectively. Clusters of genes expressed by stromal cells and lymphocytes in the breast tumors also were identified in this analysis. These results support the feasibility and usefulness of this systematic approach to studying variation in gene expression patterns in human cancers as a means to dissect and classify solid tumors. This study is described more fully in Perou CM, et al. 1999. Proc Natl Acad Sci USA 96:9212-7

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Mammary epithelial cells have lineage-rooted metabolic identities

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Project description:Unsupervised hierarchical clustering of ovarian cell lines and ovarian cancers. Cell lines were not co-clustered with the tumor specimens, because these cell lines have a very prominent proliferation cluster (Perou et al., 1999; Ross et al., 2000) that significantly influences the clustering of the tumor samples if the two sample sets are not analyzed separately. Ovarian cancer specimens and cell lines were clustered based on variation of expression of 1,558 genes, as detailed in Methods. Genes were clustered based on similarity in their expression patterns among these cancers. Eight gene clusters are highlighted in this display. (A) Lymphocyte cluster, (B) Epithelial/Keratin expression (C) Ascites Signature, (D) Clear cell over-expressed genes, (E) Extracellular Matrix/Stromal cluster, (F) Proliferation cluster, (G) Heterogeneity across ovarian cases, and (H) Clear cell under-expressed genes. The color contrast of the scale bar indicates the fold of gene expression change in log2 space (numbers above the bar).

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