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• W2164811748 abstract "In this study, differential gene expression between normal human mammary epithelial cells and their malignant counterparts (eight well established breast cancer cell lines) was studied using Incyte GeneAlbum 1–6, which contains 65,873 cDNA clones representing 33,515 individual genes. 3,152 cDNAs showed a ≥3.0-fold expression level change in at least one of the human breast cancer cell lines as compared with normal human mammary epithelial cells. Integration of breast tumor gene expression data with the genes in the tumor suppressor p53 signaling pathway yielded 128 genes whose expression is altered in breast tumor cell lines and in response to p53 expression. A hierarchical cluster analysis of the 128 genes revealed that a significant portion of genes demonstrate an opposing expression pattern, i.e. p53-activated genes are down-regulated in the breast tumor lines, whereas p53-repressed genes are up-regulated. Most of these genes are involved in cell cycle regulation and/or apoptosis, consistent with the tumor suppressor function of p53. Follow-up studies on one gene, RAI3, suggested that p53 interacts with the promoter of RAI3 and repressed its expression at the onset of apoptosis. The expression of RAI3 is elevated in most tumor cell lines expressing mutant p53, whereas RAI3 mRNA is relatively repressed in the tumor cell lines expressing wild-type p53. Furthermore, ectopic expression of RAI3 in 293 cells promotes anchorage-independent growth and small interfering RNA-mediated depletion of RAI3 in AsPc-1 pancreatic tumor cells induces cell morphological change. Taken together, these data suggest a role for RAI3 in tumor growth and demonstrate the predictive power of integrative genomics. In this study, differential gene expression between normal human mammary epithelial cells and their malignant counterparts (eight well established breast cancer cell lines) was studied using Incyte GeneAlbum 1–6, which contains 65,873 cDNA clones representing 33,515 individual genes. 3,152 cDNAs showed a ≥3.0-fold expression level change in at least one of the human breast cancer cell lines as compared with normal human mammary epithelial cells. Integration of breast tumor gene expression data with the genes in the tumor suppressor p53 signaling pathway yielded 128 genes whose expression is altered in breast tumor cell lines and in response to p53 expression. A hierarchical cluster analysis of the 128 genes revealed that a significant portion of genes demonstrate an opposing expression pattern, i.e. p53-activated genes are down-regulated in the breast tumor lines, whereas p53-repressed genes are up-regulated. Most of these genes are involved in cell cycle regulation and/or apoptosis, consistent with the tumor suppressor function of p53. Follow-up studies on one gene, RAI3, suggested that p53 interacts with the promoter of RAI3 and repressed its expression at the onset of apoptosis. The expression of RAI3 is elevated in most tumor cell lines expressing mutant p53, whereas RAI3 mRNA is relatively repressed in the tumor cell lines expressing wild-type p53. Furthermore, ectopic expression of RAI3 in 293 cells promotes anchorage-independent growth and small interfering RNA-mediated depletion of RAI3 in AsPc-1 pancreatic tumor cells induces cell morphological change. Taken together, these data suggest a role for RAI3 in tumor growth and demonstrate the predictive power of integrative genomics. Breast cancer is the most frequent cancer diagnosis, with an estimated 12% of women worldwide being at risk of developing the disease at some time in their lives (1.Salorafas G.H. Tsiotou A.G. Br. J. Surg. 2000; 87: 149-162Crossref PubMed Scopus (30) Google Scholar). Breast cancer is the second major cause of cancer death in women overall and the leading cause in women 40–55 years old (2.Winer E.P. Morrow M. Osborne C.K. Harris J.R. DeVita Jr., V.T. Hellman S. Rosenberg S.A. Cancer: Priciples and Practice of Oncology. 2. Lippincott Williams & Wilkins, Philadelphia, PA2001: 1651-1726Google Scholar, 3.Pisani P. Parkin D.M. Bray F. Ferlay J. Int. J. Cancer. 1999; 83: 18-29Crossref PubMed Scopus (1440) Google Scholar). There are tremendous unmet medical needs in breast cancer therapy. Recently, high throughput gene expression technology has revolutionized our ability to simultaneously monitor expression of thousands of genes in the human genome. The power of genome-wide gene expression analysis has been demonstrated by using characteristic patterns of gene expression to reclassify breast tumors into clinically relevant subgroups (4.Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Eystein Lonning P. Borresen-Dale A.L. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 10869-10874Crossref PubMed Scopus (8416) Google Scholar, 5.van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Nature. 2002; 415: 530-536Crossref PubMed Scopus (7692) Google Scholar, 6.Perou C.M. Sorlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnson H. Akslen L.A. Fluge O. Pergamen-schikov A. Williams C. Zhu S.X. Lonning P.E. Borresen-Dale A.-L. Brown P.O. Botstein D. Nature. 2000; 406: 747-752Crossref PubMed Scopus (11476) Google Scholar, 7.Gruvberger S. Ringner M. Chen Y. Panavally S. Saal L.H. Borg A. Ferno M. Peterson C. Meltzer P.S. Cancer Res. 2001; 61: 5979-5984PubMed Google Scholar) and better predict resistance or sensitivity to treatment as compared with conventional clinical-pathological criteria (8.Sorlie T. Tibshirani R. Parker J. Hastie T. Marron J.S. Nobel A. Deng S. Johnsen H. Pesich R. Geisler S. Demeter J. Perou C.M. Lonning P.E. Brown P.O. Borresen-Dale A.L. Botstein D. Proc. Nat. Acad. Sci. U. S. A. 2003; 100: 8418-8423Crossref PubMed Scopus (4133) Google Scholar, 9.van de Vijver M.J. He Y.D. van't Veer L.J. Dai H. Hart A.A.M. Voskuil D.W. Schreiber G.J. Peterse H.L. Roberts C. Marton M.J. Parrish M. Atsma D. Witteveen A. Glas A. Delahaye L. ven der Velde T. Bartelink H. Rodenhuis S. Rutgers E.T. Friend S.H. Bernards R. N. Engl. J. Med. 2002; 347: 1999-2009Crossref PubMed Scopus (5218) Google Scholar). Although the reclassification of breast tumor subtypes provides striking initial examples, these advances have not yet yielded novel targets for breast cancer drug discovery. Target identification is limited, in part, by our understanding of the pathways involved with the cancer-associated genes. New approaches are required to take full advantage of the genomics revolution.Deregulation of the p53 pathway occurs as a common event in most if not all types of human cancers. Alterations in p53 protein were observed to be the single most adverse prognostic indicator for both recurrence and death in breast cancer (10.Borresen-Dale A.L. Hum. Mutat. 2003; 21: 292-300Crossref PubMed Scopus (267) Google Scholar). The biochemical activity of p53 that is most closely associated with tumor suppression is its function as a transcription factor. The transcriptional targets of p53 form a network involved in cell cycle regulation, apoptosis, DNA repair, differentiation, senescence, and development (11.Vogelstein B. Lane D. Levine A.J. Nature. 2000; 408: 307-310Crossref PubMed Scopus (5743) Google Scholar). Therefore, integration of the p53 pathway with the cancer-associated genes will assist in the identification of putative oncogenes with functional relevance.In our previous work, we have investigated p53 target genes in the human genome using bioinformatics and microarray approaches (12.Mirza A. Wu Q. Wang L. McClanahan T. Bishop W.R. Gheyas F. Ding W. Hutchins B. Hockenberry T. Kirschmeier P. Greene J.R. Liu S. Oncogene. 2003; 22: 3645Crossref PubMed Scopus (150) Google Scholar, 13.Wang L. Wu Q. Qiu P. Mirza A. McGuirk M. Kirschmeier P. Greene J.R. Wang Y. Pickett C.B. Liu S. J. Biol. Chem. 2001; 276: 43604-43610Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar). In this study, we determined the expression profile of normal and malignant mammary epithelial cells 1The GEO numbers of microarray data are as follows: GSM38895, GSM38896, GSM38897, GSM38898, GSM38899, GSM38900, GSM38901, GSM38902, GSM38903, GSM38904.1The GEO numbers of microarray data are as follows: GSM38895, GSM38896, GSM38897, GSM38898, GSM38899, GSM38900, GSM38901, GSM38902, GSM38903, GSM38904. and integrated the data with the microarray data that identify p53-responsive genes as well as the p53 target data base. We observed striking opposing expression patterns between the genes showing aberrant expression in breast tumor cells and the genes transcriptionally regulated by p53. Most of these genes are involved in cell cycle regulation and cell death, consistent with p53 tumor suppressor function. Follow-up studies on one gene, RAI3 (an alternative name, RAIG1), suggested that RAI3 is a novel p53 transcriptional target gene and growth-promoting gene, agreed with the prediction of integrative genomics.MATERIALS AND METHODSCell Culture—Human breast cancer cell lines T47D, MCF7, ZR-75-1, MDA-MB-468, BT-20, BT-549, BT-474, and SK-BR-3, human pancreatic tumor cell line AsPc-1, and human cervical epithelioid tumor cell line HeLa were obtained from American Type Cell Collection (ATCC). 2774qw1 is a single clone derived from human ovarian tumor cell line 2774, which was obtained from ATCC (14.Wu Q. Kirschmeier P. Hockenberry T. Yang T.-Y. Brassard D.L. Wang L. McClanahan T. Black S. Rizzi G. Musco-Hobkinson M.L. Mirza A. Liu S. J. Biol. Chem. 2002; 277: 36329-36337Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar). Primary normal human mammary epithelial cell (HMEC) 2The abbreviations used are: HMEC, human mammary epithelial cell; RT-PCR, reverse transcription PCR; 23-kDa HBP, 23-kDa highly basic protein; ChIP, chromatin immunoprecipitation; siRNA, small interfering RNA; rAd-p53, recombinant adenovirus expressing wild-type p53; HEK, human embryonic kidney; FACS, fluorescence-activated cell sorter; MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; rAd-vector, recombinant adenovirus containing empty vector; HER2, human tyrosine kinase type 2 receptor. from 21- and 50-year old donors, designated HMEC21 and HMEC50, were obtained from Clonetics Corp. (Walkersville, MD). They were cultured from reduction mammoplasty and grown in short term culture. Culture conditions of all cell lines or primary cells followed the instruction from ATCC or Clonetics.RNA Isolation and Microarray Hybridization—Cells were harvested after passages 1–3 from Clonetics or ATCC stock. RNA preparation and microarray hybridization were performed as described previously (12.Mirza A. Wu Q. Wang L. McClanahan T. Bishop W.R. Gheyas F. Ding W. Hutchins B. Hockenberry T. Kirschmeier P. Greene J.R. Liu S. Oncogene. 2003; 22: 3645Crossref PubMed Scopus (150) Google Scholar).Quantitative RT-PCR Analysis—Quantitative reverse transcription PCR (RT-PCR) was performed as described previously (13.Wang L. Wu Q. Qiu P. Mirza A. McGuirk M. Kirschmeier P. Greene J.R. Wang Y. Pickett C.B. Liu S. J. Biol. Chem. 2001; 276: 43604-43610Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar). All measurements were done in at least two independent experiments each of which was done in triplicate. Sequences of the primers and probes for epithelium-specific transcription factor-1b, integrin α3, integrin α6, RAI3, and human 23 kDa highly basic protein (23-kDa HBP) gene, obtained from PerkinElmer Life Sciences, are listed in supplementary information S1. The results were normalized such that the value of human 23-kDa HBP gene expression was 10,000 in each sample.Statistical Analysis—The differentially expressed genes from microarray experiments were grouped according to the similarity of their expression patterns using a hierarchical clustering method described by Eisen et al. (15.Eisen M.B. Spellman P.T. Brown P.O. Botstein D. Proc. Nat. Acad. Sci. U. S. A. 1998; 95: 14863-14868Crossref PubMed Scopus (13132) Google Scholar). The clustering algorithm was implemented using the software package S-PLUS (Mathsoft Inc., Seattle, WA).Integration of Microarray Data with the p53 Target Data Base—To identify the genes that were activated in breast tumor cells and repressed by p53, the microarray data from 8 human breast tumor cell lines as well as human mammary epithelial cells from three donors were combined with another set of microarray data that identified p53-responsive genes (13.Wang L. Wu Q. Qiu P. Mirza A. McGuirk M. Kirschmeier P. Greene J.R. Wang Y. Pickett C.B. Liu S. J. Biol. Chem. 2001; 276: 43604-43610Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar). The detailed methodology was described in details elsewhere (16.Liu S. Mirza A. Wang L. Schönthal A.H. Methods in Molecular Biology, Checkpoint Controls and Cancer: Methods and Protocols. 2. Humana, Totowa, NJ2004: 33-54Google Scholar).Cell Cycle Analysis—HeLa cells, obtained from ATCC, were treated with 400 μm mimosine, 2 mm thymidine, or 0.4 μg/ml nocodazole for 16 h at 37 °C, respectively. The chemicals were all obtained from Sigma. The synchronized cells were fixed and processed for cell cycle analysis as described previously (14.Wu Q. Kirschmeier P. Hockenberry T. Yang T.-Y. Brassard D.L. Wang L. McClanahan T. Black S. Rizzi G. Musco-Hobkinson M.L. Mirza A. Liu S. J. Biol. Chem. 2002; 277: 36329-36337Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar).Quantitative Chromatin Immunoprecipitation (ChIP) Analysis—Human ovarian tumor cell line 2774qw1 was infected with adenovirus expressing p53 (rAd-p53) or adenovirus containing empty vector (rAd-vector) for 1 h and harvested 16-h postinfection. The ChIP assays were performed as described previously (13.Wang L. Wu Q. Qiu P. Mirza A. McGuirk M. Kirschmeier P. Greene J.R. Wang Y. Pickett C.B. Liu S. J. Biol. Chem. 2001; 276: 43604-43610Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar). The sequences of primers and probes used in the ChIP assays, obtained from PerkinElmer Life Sciences, are listed in supplementary information S6.RNA-mediated Interference Experiments—Small interfering RNAs (siRNA) were purchased from Sequitur, Inc. (Boston, MA). The transfection of siRNA was performed on 30–50% confluent cells using Oligofectamine (Invitrogen) according to the manufacturer's instructions. The cellular delivery of siRNA was optimized with various doses and post-transfection time using fluorescein isothiocyanate-siRNA (Sequitur, Inc., Boston, MA). Five different siRNAs targeting RAI3 were tested, and one of them that showed greatest gene knocked down effect was chosen for further study. Double-stranded siRNAs against RAI3 were introduced into AsPc-1 pancreatic tumor cells by performing three successive transfections of siRNA (85 nm) at 5-day intervals to visualize the cell morphology change. Experiments were repeated in three independent studies, and each study was performed in triplicate. mRNA in siRNA-transfected samples analyzed by quantitative RT-PCR were normalized with respect to the 23-kDa HBP expression level. The toxicity of cells transfected with siRNA was assessed by cell viability.Establishment of 293 Cells Stably Expressing RAI3 Receptor—Serum-free medium-adapted HEK-293 F cells were grown at 37 °C in a humidified atmosphere with 5% CO2 in Dulbecco's modified Eagle's medium containing 10% (v/v) fetal bovine serum. Cells were transfected with the N-terminal FLAG-tagged RAI3 cDNA in pME18 vector using Effectent reagent (Qiagen, Valencia, CA) and, at 48 h post-transfection, the medium was replaced using selection medium (growth medium plus 0.5 mg/ml G418). The stable surface expression of RAI3 receptors in HEK-293 F was then confirmed by FACS analysis after being grown on selection medium for 2 weeks.Analysis of Surface Expression of RAI3—RAI3 receptor expression on the cell surface was determined by flow cytometric analysis using a FACSCalibur flow cytometer (BD Biosciences). Cells were harvested in 5 mm EDTA in PBSF (PBS free of Ca2+ and Mg2+), washed once with PBSF, and stained with biotinylated anti-FLAG M2 monoclonal antibody (1:500 dilution) (Sigma) or stained with biotinylated mouse IgG1, K (1:5 dilution) (Pharmingen), for 20 min. After being washed once with PBSF, the cells were then stained with phycoerythrin-conjugated streptavidin (Pharmingen) (1:1,000 dilution) for 20 min and washed twice with PBSF before being analyzed by FACS Calibur flow cytometer.Soft Agar Experiments—Soft agar assays were performed in 6-well dishes by seeding 1,000, 2,500, or 5,000 cells in each well. Cells were plated in top 0.35% low melting point agarose in Dulbecco's modified Eagle's medium with 10% fetal bovine serum over a bottom 0.6% low melting point agarose feeding layer. Cells were grown for ∼2 weeks, and colonies were stained with 1% MTT in phosphate-buffered saline. The plates were then scanned, and the colony area was quantified as the sum of the areas stained by MTT. The statistical significance of the soft agar data was analyzed by Student's t test.RESULTS AND DISCUSSIONDifferentially Expressed Transcripts in Breast Tumor Cells— One aim of this study is to identify genes in normal HMECs that become activated during malignant transformation. Although the approach of differential hybridization analysis is powerful, an appropriate model system is an essential prerequisite. Most cancers originate from epithelial tissues in which oncogenes are activated or tumor-suppressor genes are lost. Such genetically abnormal epithelium is supported by normal stromal cells that become activated during tumor progression to produce proteases, inhibitors, and other regulatory factors. Therefore, it is imperative to start with human malignant mammary epithelial cells. In this study, eight well established human breast cancer epithelial cell lines from ATCC were chosen to use in the microarray experiments: MCF-7, T47D, ZR-75-1, MDA-MB-468, BT-20, BT-474, BT-549, and SK-BR-3. A reliable source of normal HMECs is critical, because the differential expression analysis would be made between probe pairs from malignant mammary epithelial cell lines against normal primary mammary epithelial cells. We used primary normal HMEC from 3 donors (HMEC21, HMEC41, and HMEC50) cultured from reduction mammoplasty and grown in short term culture. The molecular characterization of cells and cell lines used in microarray experiments is shown in supplementary information S2 and S3.The mRNA isolated from HMEC50 was labeled with the fluorescent dye, Cy5, and used in all probe pairs as a common reference, and the mRNA isolated from other cells or cell lines was labeled with fluorescent dye, Cy3. The labeled cDNAs from each probe pair were mixed and hybridized to the cDNA microarray as described under “Methods and Materials.” The microarrays, Incyte GeneAlbum 1–6, used for the hybridization consisted of 65,873 cDNA clones (57,172 clones excluding controls), representing 33,515 individual genes. 59,579 of 65,873 elements (90%) on microarrays gave signals.1 Most transcripts were expressed at similar levels in normal and malignant mammary cells. 17,635 cDNAs showed ≥2.0-fold expression level change, 7,273 cDNAs showed ≥2.5-fold expression level change, and 3,152 cDNAs showed ≥3.0-fold expression level change in any of human breast cancer cell lines as compared with HMEC50. The hybridization results for each probe pair are shown in Table I.Table IDistribution of differentially expressed genes in breast tumor cell linesProbe 2aThe common probe 1 is HMEC50No. of cDNAs that exhibit differential expressionbMinimum differential expression is a 3.0-fold change as compared with HMEC50HMEC4122HMEC21105T47D1152MCF7857ZR-75-1677MB-468486BT-20695BT-474876SK-BR-3418BT-549863a The common probe 1 is HMEC50b Minimum differential expression is a 3.0-fold change as compared with HMEC50 Open table in a new tab To validate the reliability of the changes we observed from microarray hybridization, we checked expression profile of known breast cancer-associated genes. For example, the human tyrosine kinase type 2 receptor (HER2) was identified as overexpressed in SK-BR-3 and BT-474 breast tumor cell lines (17.Harwerth I.-M. Wels W. Marte B.M. Hynes N.E. J. Biol. Chem. 1992; 267: 15160Abstract Full Text PDF PubMed Google Scholar, 18.Shawver L.K. Mann E. Elliger S.S. Dugger T.C. Arteaga C.L. Cancer Res. 1994; 54: 1367PubMed Google Scholar). It was observed that HER2 exhibited 7.4-, 11.3-, 7.5-, and 11.8-fold changes in SK-BR-3 breast tumor cells and 7.0-, 10.8-, 18.4-, and 10.1-fold changes in BT-474 breast tumor cells as compared with normal HMEC50 cells from four individual clones on the microarrays. HER2 was also found to be overexpressed in ZR-75-1 breast tumor cell line (3.0-, 2.5-, 4.0-, and 2.6-fold change from four individual clones on the microarrays). This has not being previously reported in the literature. In addition, overexpression of the estrogen-inducible pS2 gene was observed in MCF-7 (44.0-fold change) and ZR-75-1 (3.0-fold change) breast tumor cell lines, not in other breast tumor cell lines (e.g. BT-20 and T47D), or the normal epithelial mammary cells from three donors. This result agreed with observations made in other laboratories (19.Zajchowski D. Band V. Paauzie N. Tager A. Stampfer M. Sager R. Cancer Res. 1988; 48: 7041-7047PubMed Google Scholar). In addition, we measured mRNA levels of several genes, including epithelium-specific transcription factor-1b, integrin α3, and integrin α6, by TaqMan RT-PCR analysis using the same RNA samples used in microarray hybridizations (data not shown). In general, these two independent quantitation methods gave very similar results.Distinct Gene Expression Patterns between Tumor and Normal Cells Analyzed by Hierarchical Cluster Method—Hierarchical cluster analysis was performed on the basis of similarities in their overall patterns of gene expression measured over the group of 8 breast tumor cell lines as well as normal mammary epithelial cells, HMEC21 and HMEC40, versus HMEC50 as a common reference (Fig. 1). 2,108 elements or cDNAs on the microarrays used in the analysis were differentially expressed with at least or equal to 3.0-fold change at one or more probes and had not more than 1 missing value of 10 data points (supplementary information S4). Estrogen receptor-positive breast tumor cell lines, T47D, MCF7, BT-474 and ZR-75-1, were clustered together in the bottom branch of the dendrogram. Whereas estrogen receptor-negative breast tumor cell lines, MDA-MB-468, BT-20, SK-BR-3, and BT-549 exhibited less relatedness. As expected, normal mammary epithelial cells from two donors were found to group together and have the least relatedness as compared with the breast tumor cell lines. Therefore, unsupervised clustering methods were able to distinguish between tumor and normal cells and breast tumors are classified, to some extent, on the basis of estrogen receptor status. This is in agreement with recent reports (4.Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Eystein Lonning P. Borresen-Dale A.L. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 10869-10874Crossref PubMed Scopus (8416) Google Scholar, 5.van't Veer L.J. Dai H. van de Vijver M.J. He Y.D. Hart A.A. Mao M. Peterse H.L. van der Kooy K. Marton M.J. Witteveen A.T. Schreiber G.J. Kerkhoven R.M. Roberts C. Linsley P.S. Bernards R. Friend S.H. Nature. 2002; 415: 530-536Crossref PubMed Scopus (7692) Google Scholar). Interestingly, one of the breast tumor cell lines, BT-549, exhibited the least relatedness to any other tumor cell line as shown in the dendrogram (Fig. 1). It was previously suggested that the origin of the BT-549 breast cancer cell line was more stromal rather than epithelial by cluster analysis (6.Perou C.M. Sorlie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Rees C.A. Pollack J.R. Ross D.T. Johnson H. Akslen L.A. Fluge O. Pergamen-schikov A. Williams C. Zhu S.X. Lonning P.E. Borresen-Dale A.-L. Brown P.O. Botstein D. Nature. 2000; 406: 747-752Crossref PubMed Scopus (11476) Google Scholar). Notably, elevated expression of epithelium-specific transcription factor-1b in all epithelial breast tumor cell lines but not in BT-549 breast tumor cell line was observed, supporting this notion.We further clustered the elements or cDNAs on the microarray on the basis of similarity of their expression patterns (Fig. 1). We observed that multiple independent clones or cDNA representing the same gene usually clustered together, either very near each other or immediately adjacent to each other. These independent clones were mostly spotted on different locations on the microarrays. The genes in the clusters are listed in supplementary information S4.An interesting feature of the gene expression patterns of 156 cDNAs seen in the uppermost portion of the dendrogram (Fig. 1, cluster A) is their similar gene expression level among normal epithelial mammary cells from different donors and their up-regulation of expression in most breast tumor cell lines, suggesting that this pattern may identify genes involved in the process of tumorigenesis. This set included many genes involved in cell cycle regulation, cell cycle checkpoint, DNA synthesis, and DNA replication as well as the proliferation-associated antigen Ki-67, which is often used to gauge the proliferation index of a tumor biopsy. Cluster B, consisting of 30 cDNAs, showed a unique gene expression pattern. The genes in this distinctive cluster included many extracellular matrix proteins and were expressed at high levels only in BT-549 stromal cell line (Fig. 1). The other interesting cluster, cluster C (Fig. 1), at the lowermost portion of the dendrogram, consists of 145 elements or cDNAs. This cluster includes several HMEC molecular markers (laminin-5 β3 and α3b, cytokeratins types 2, 5, 6, 15, 16, and 17, and type I epidermal keratin). These genes were down-regulated in malignant mammary cells as compared with normal HMECs, consistent with previous reports (4.Sorlie T. Perou C.M. Tibshirani R. Aas T. Geisler S. Johnsen H. Hastie T. Eisen M.B. van de Rijn M. Jeffrey S.S. Thorsen T. Quist H. Matese J.C. Brown P.O. Botstein D. Eystein Lonning P. Borresen-Dale A.L. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 10869-10874Crossref PubMed Scopus (8416) Google Scholar). In contrast, there is no differential expression of these genes observed among normal epithelial mammary cells from three donors.Identification of Breast Tumor-associated Genes in the p53 Pathway—We observed that a significant portion of genes exhibited differential expression in breast tumor cells as compared with their normal counterpart. How the expression levels of thousands of genes are regulated in tumors remains a significant challenge in tumor biology. Central to this mechanism are transcription factors, including the p53 tumor suppressor protein. A perturbation in function of the p53 protein is one of the most common features associated with human cancer (11.Vogelstein B. Lane D. Levine A.J. Nature. 2000; 408: 307-310Crossref PubMed Scopus (5743) Google Scholar). In breast cancer, p53 mutation has been found to be an early event in breast tumorigenesis and is associated with rapid proliferation and poor prognosis (10.Borresen-Dale A.L. Hum. Mutat. 2003; 21: 292-300Crossref PubMed Scopus (267) Google Scholar).In our previous work, parallel microarray experiments were carried out with the same set of Incyte GeneAlbum microarrays using mRNA isolated from a human ovarian tumor cell line, 2774qw1 cells at various times post-infection with 1010 particles/ml rAd-p53 or rAd-vector (12.Mirza A. Wu Q. Wang L. McClanahan T. Bishop W.R. Gheyas F. Ding W. Hutchins B. Hockenberry T. Kirschmeier P. Greene J.R. Liu S. Oncogene. 2003; 22: 3645Crossref PubMed Scopus (150) Google Scholar). 1,501 genes were found to respond to p53 expression at one or more time points using a 2.5-fold change as a cutoff. To identify the genes that show differential expression in breast tumor cells and respond to p53 expression, the microarray data derived from the breast tumor cell lines was combined with the microarray data derived from the p53-expressing human ovarian tumor cell line. We identified 128 cDNAs, for which transcript levels changed 3-fold or more in at least one breast tumor cell line and for which expression changed in at least one time point in response to p53 (supplementary information S5). The unsupervised hierarchical cluster analysis grouped samples into four groups (Fig. 2A). Normal mammary epithelial cells from two donors (HMEC21 and HMEC41) and the sample from 2774qw1 cells at 4-h post-infection of rAd-p53 that show least differential expression grouped together. All other samples from 2774qw1 cells at 8–24-h post-infection of rAd-p53 were in the same cluster. Interestingly, estrogen receptor-positive breast tumor cell lines, T47D, MCF7, BT-474, and ZR-75-1, separated from estrogen receptor-negative breast tumor cell lines, MDA-MB-468, BT-20, and SK-BR-3. The BT-549 breast cancer cell line with more stromal tissue origin had least relatedness as compared with any other samples.Fig. 2Hierarchical cluster image showing opposing expression patterns of breast tumor associated genes and p53 responsive genes. 128 cDNAs on the microarrays were used in the cluster analysis. Criteria were differential expression of at least 3.0-fold changes at one or more probes as compared with the corresponding reference HMEC50 or sample infected with rAd-vector and not more than 1 miss" @default.
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• W2164811748 title "Integrative Genomics Revealed RAI3 Is a Cell Growth-promoting Gene and a Novel P53 Transcriptional Target" @default.
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