Linking gene expression patterns to therapeutic groups in breast cancer.

A major objective of current cancer research is to develop a detailed molecular characterization of tumor cells and tissues that is linked to clinical information. Toward this end, we have identified approximately one-quarter of all genes that were aberrantly expressed in a breast cancer cell line using differential display. The cancer cells lost the expression of many genes involved in cell adhesion, communication, and maintenance of cell shape, while they gained the expression of many synthetic and metabolic enzymes important for cell proliferation. High-density, membrane-based hybridization arrays were used to study mRNA expression patterns of these genes in cultured cells and archived tumor tissue. Cluster analysis was then used to identify groups of genes, the expression patterns of which correlated with clinical information. Two clusters of genes, represented by p53 and maspin, had expression patterns that strongly associated with estrogen receptor status. A third cluster that included HSP-90 tended to be associated with clinical tumor stage, whereas a forth cluster that included keratin 14 tended to be associated with tumor size. Expression levels of these clinically relevant gene clusters allowed breast tumors to be grouped into distinct categories. Gene expression fingerprints that include these four gene clusters have the potential to improve prognostic accuracy and therapeutic outcomes for breast cancer patients.

[1]  R. Sager.  Expression genetics in cancer: shifting the focus from DNA to RNA. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Daniel Teichroew,et al.  Mining protein data from two‐dimensional gels: Tools for systematic post‐planned analyses , 1999 .

[3]  J. Connolly,et al.  Tumor progression in four mammary epithelial cell lines derived from the same patient. , 1990, Cancer research.

[4]  G. Moffat,et al.  Structural features of the human C3 gene: intron/exon organization, transcriptional start site, and promoter region sequence. , 1991, Biochemistry.

[5]  D. Latchman,et al.  Autoantibodies to 90 kD heat-shock protein in sera of breast cancer patients , 1995, The Lancet.

[6]  U. Alon,et al.  Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[7]  B. Gusterson,et al.  Distribution of myoepithelial cells and basement membrane proteins in the normal breast and in benign and malignant breast diseases. , 1982, Cancer research.

[8]  M. Bittner,et al.  Expression profiling using cDNA microarrays , 1999, Nature Genetics.

[9]  V. Band,et al.  Distinctive traits of normal and tumor-derived human mammary epithelial cells expressed in a medium that supports long-term growth of both cell types. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[10]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[11]  S. Davies,et al.  An immunomagnetic separation method using superparamagnetic (MACS) beads for large-scale purification of human mammary luminal and myoepithelial cells. , 1994, Epithelial cell biology.

[12]  S. Barsky,et al.  The myoepithelial defense: a host defense against cancer. , 1997, Medical hypotheses.

[13]  J. Foekens,et al.  p53 protein accumulation predicts poor response to tamoxifen therapy of patients with recurrent breast cancer. , 1998, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[14]  M. Hendrix,et al.  Maspin, a serpin with tumor-suppressing activity in human mammary epithelial cells. , 1994, Science.

[15]  M. Baum.  Tamoxifen--the treatment of choice. Why look for alternatives? , 1998, British Journal of Cancer.

[16]  M. Garabedian,et al.  Role for Hsp90-Associated Cochaperone p23 in Estrogen Receptor Signal Transduction , 1999, Molecular and Cellular Biology.

[17]  Christian A. Rees,et al.  Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[18]  H. Nguyen,et al.  Differential expression of multiple MDM2 messenger RNAs and proteins in normal and tumorigenic breast epithelial cells. , 1995, Clinical cancer research : an official journal of the American Association for Cancer Research.

[19]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[20]  S. Sheng,et al.  Classification of Breast Cancer Cells on the Basis of a Functional Assay for Estrogen Receptor , 1998, Molecular medicine.

[21]  A. Bankfalvi,et al.  Gains and losses of CD44 expression during breast carcinogenesis and tumour progression , 1998, Histopathology.

[22]  E. Robecchi.  [Pathology of the breast]. , 1954, Minerva ginecologica.

[23]  Michael L. Bittner,et al.  Informatic selection of a neural crest-melanocyte cDNA set for microarray analysis , 1999 .

[24]  Ash A. Alizadeh,et al.  Genome-wide analysis of DNA copy-number changes using cDNA microarrays , 1999, Nature Genetics.

[25]  W. Rutter,et al.  Isolation of biologically active ribonucleic acid from sources enriched in ribonuclease. , 1979, Biochemistry.

[26]  R. Sager,et al.  Differential expression of elafin in human normal mammary epithelial cells and carcinomas is regulated at the transcriptional level. , 1995, Cancer research.

[27]  E. Gratton,et al.  Fluorescence fluctuation spectroscopy. , 1999, Methods.

[28]  K. Martin,et al.  A direct-sequencing-based strategy for identifying and cloning cDNAs from differential display gels. , 1997, Methods in molecular biology.

[29]  K. Martin,et al.  Identification and verification of differential display cDNAs using gene-specific primers and hybridization arrays. , 1998, BioTechniques.

[30]  L. Murphy,et al.  Estrogen Regulates the Association of Intermediate Filament Proteins with Nuclear DNA in Human Breast Cancer Cells* , 1998, The Journal of Biological Chemistry.

[31]  Z. Naito,et al.  Expression and Roles of Heat Shock Proteins in Human Breast Cancer , 1996, Japanese journal of cancer research : Gann.

[32]  Ji Huang,et al.  [Serial analysis of gene expression]. , 2002, Yi chuan = Hereditas.

[33]  S. Safe,et al.  Role of estrogen receptor/Sp1 complexes in estrogen-induced heat shock protein 27 gene expression. , 1996, Molecular endocrinology.

[34]  A. Ljubimov,et al.  Myoepithelial and basement membrane antigens in benign and malignant human breast tumors , 1993, International journal of cancer.

[35]  P. Brown,et al.  Combining SSH and cDNA microarrays for rapid identification of differentially expressed genes. , 1999, Nucleic acids research.

[36]  K. Martin,et al.  Principles of differential display. , 1999, Methods in enzymology.

[37]  A. Pardee,et al.  Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction. , 1992, Science.

[38]  Marcel Garcia,et al.  Estradiol increases the production of α1-antichymotrypsin in MCF7 and T47D human breast cancer cell lines , 1985, Molecular and Cellular Endocrinology.

[39]  E. Lane,et al.  Keratin expression in human mammary epithelial cells cultured from normal and malignant tissue: relation to in vivo phenotypes and influence of medium. , 1989, Journal of cell science.

[40]  Chen,et al.  Protection of human breast cancer cells from complement‐mediated lysis by expression of heterologous CD59 , 1999, Clinical and experimental immunology.

[41]  A. Long,et al.  A human cell line from a pleural effusion derived from a breast carcinoma. , 1973, Journal of the National Cancer Institute.

[42]  Identification of the sequences within the human complement 3 promoter required for estrogen responsiveness provides insight into the mechanism of tamoxifen mixed agonist activity. , 1996 .