| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Advances in Brief |
Genzyme Molecular Oncology, Framingham, Massachusetts 01701 [M. N., W. Z., J. M. P., B. P. C., Y. H. G., G. C., G. M. L., S. L. M.]; Department of Oncology, Novartis Institute for Biomedical Research, Summit, New Jersey 07901 [S. M.]; Lion Bioscience, Cambridge, Massachusetts 02141 [D. R.]; and Breast Cancer Program, Johns Hopkins Oncology Center, Baltimore, Maryland 21205 [A. T. F., S. S.]
 |
ABSTRACT |
|---|
 Top ABSTRACT IntroductionMaterials and MethodsResultsDiscussionREFERENCES |
|---|
|
Introduction |
|---|
|
TopABSTRACTIntroductionMaterials and MethodsResultsDiscussionREFERENCES |
|---|
A comparison of gene expression profiles in normal and tumor cells can yield critical information about the processes of transformation and metastasis. Although many studies have identified oncogenes and tumor suppressor genes that mark the transformation of cells from the colon, pancreas (9) , and lung (8) , comparable studies in breast cancer have met with limited success. This reflects both the difficulty in finding genetic and epigenetic alterations that are present in a significant proportion of breast cancers and the heterogeneity of breast cancer itself.
To help elucidate pathways that mediate breast cancer progression and to find targets for potential therapeutic intervention, we combined SAGE and custom array analysis. We identified differentially expressed genes by generating SAGE profiles of two well-characterized breast tumor cell lines, 21PT and 21MT, and two normal mammary epithelial cell cultures. To find genes and ESTs that are consistently expressed at different levels in diseased and normal tissues, a subset of the differentially expressed genes identified by SAGE was then spotted on an array and screened with complex cDNA probes extracted from 17 breast tumor samples and four normal breast epithelial cell cultures. SAGE analysis of 21PT, 21MT, and normal breast epithelial cells identified >200 transcripts that were differentially expressed at least 10-fold between cancer and normal cells. Custom array analysis verified the expression of some of these candidates in primary and metastatic tumors and identified several differences between the two cancerous states. Our data demonstrate that by coupling the advantages of SAGE and cDNA array technologies, we can identify genes and potential pathways that were not implicated previously in breast cancer. Moreover, this combination of techniques generated information about the similarities and differences in the expression profiles of primary and metastatic breast tumors.
|
Materials and Methods |
|---|
|
TopABSTRACTIntroductionMaterials and MethodsResultsDiscussionREFERENCES |
|---|
-MEM (Life Technologies, Inc., Gaithersburg, MD) supplemented with 10% FCS, 10 mM HEPES, 0.1 mM nonessential amino acids, 1 mM sodium pyruvate, 2 mM glutamine, 100 units/ml penicillin, 100 µg/ml streptomycin, 1 µg/ml insulin, 25 ng/ml epidermal growth factor, and 1 µg/ml hydrocortisone. 21PT and 21MT were not grown to confluence before preparing RNA for SAGE. Normal breast epithelial cells 184 were a generous gift of Dr. Martha Stampfer (University of California, Berkeley, CA) and were maintained according to her growth conditions described elsewhere.5
Additional normal breast epithelial cells used to screen the custom arrays were also obtained from Clonetics and maintained as described above. The cultures used to screen the arrays were propagated to passage 7 and either used at confluency or 4 days after confluency. Primary breast tumor tissues and metastatic samples were obtained immediately after surgical resection at Johns Hopkins University. Microscopic examination of representative tissue sections from each tumor revealed that these samples contained >50% tumor cells.
SAGE Analysis.
SAGE analysis was performed as described (1
, 9)
. The sequence and abundance of each of the transcript tags were determined by SAGE software as described previously (8)
.
RNA Extraction.
Total RNA was isolated from cultured cells using RNazol B (Biotecx Laboratories, Inc., Houston, TX), according to manufacturer’s instructions. poly(A)+ RNA was extracted using the Oligotex mRNA Midi kit (Qiagen Inc., CA). Total RNA was isolated from tumor samples using the acid phenol extraction method (11)
or Trizol reagent (Life Technologies, Inc.) according to manufacturer’s specifications.
Custom Array Generation and Analysis.
Plasmids containing cDNA sequences for genes of interest were obtained from Genome Systems (St. Louis, MO). cDNA target sequences were amplified by PCR, purified using QIAQuick PCR purification kit or QIAQuick Gel extraction kit (Qiagen Inc. CA), and arrays were prepared by spotting the targets on replicate nylon membranes (Biotrans; ICN, Costa Mesa, CA) at a concentration of 2 ng of DNA/spot, using a BIOMEK 2000 robot (Beckman Coulter, Inc., Fullerton, CA). Each target was spotted in quadruplicate. For probes, poly(A)+ RNA was isolated from cell lines and tissues as described above. poly(A)+ RNA (70 ng) was converted to cDNA and labeled with [-32P]dCTP by reverse transcription using Superscript II RT (Life Technologies, Inc.). Hybridizations were performed overnight at 42°C in 6x SSC/0.1% SDS/50% formamide/5x Denhardt’s solution. Membranes were washed three times in 2x SSC/0.1% SDS at room temperature for 10 min each, followed by three high stringency washes in 0.1x SSC/0.1% SDS at 65°C for 30 min each. Hybridization intensities were quantitated on a STORM PhosphorImager (Molecular Dynamics, Sunnyvale, CA), and an average signal for each set of four targets was determined. The coefficient of variation for each set of four spots was 
30% (data not shown). For each membrane, the signal intensity of each cDNA was graphed, and a normalization factor based on the 95% of gene expression was applied to each data point to generate normalized values.
|
Results |
|---|
|
TopABSTRACTIntroductionMaterials and MethodsResultsDiscussionREFERENCES |
|---|
. SAGE generates a 14- or 15-bp "tag" sequence from a defined position within the transcript, which is sufficient to uniquely identify individual transcripts (1)
. A total of 228,652 tags were sequenced, with 48,691 representing unique tags. Ten % (4,916) of the unique tags matched to known mRNA sequences in GenBank, and 73% of the unique tags appeared more than once in the libraries. Fifty-six % (27,415) of the unique tags matched to either known genes or EST clusters in the Unigene database. Although 21,276 (44%) of the unique tags did not match to any known sequences in the database, the majority of these tags (17,674 tags or 83%) appeared only once in the sequenced libraries. Previous SAGE studies found that sequencing errors produce a tag error rate of 7% (9)
. Therefore, some of the tags that only appeared once may be due to sequencing errors (1,237), whereas others may represent genes expressed at very low levels. 3,603 (7.4%) tags represent potentially novel genes that appeared more than once.
|
The SAGE data revealed differential expression of several genes that have been implicated previously in breast and other cancers (Table 2)
. Table 2A
describes those known genes that were expressed at elevated levels in the tumor cell lines. The tags representing two well-known breast tumor-associated antigens, HER2/neu and Mucin, were highly overexpressed in the tumor cell lines. The HER2/neu oncogene encodes a tyrosine kinase receptor with homology to the epidermal growth factor receptor. Overexpression of HER2/neu has been observed in a variety of cancers, including 30% of breast cancers (reviewed in Ref. 12
). Similarly, epithelial mucin, encoded by the MUC-1 gene, is highly expressed in many invasive tumors including carcinomas of the colon (13)
and breast (reviewed in Ref. 14
). Another secreted protein, zinc--2-glycoprotein, has been detected at elevated levels in the serum and breast fluids of breast cancer patients, particularly in those with well-differentiated tumors (15)
.
|
Changes in cytoskeletal structure also accompany neoplastic transitions. Accordingly, alterations in cytokeratin expression, especially K8, K18, and K19, have been correlated with breast cancer progression (21) . Similarly, elevated levels of FGF-1 were observed in the cancer cells and have been associated with hormone-independent breast tumor growth, vascularization, and increased metastatic potential (12) . SAGE tags for each of these genes were found to be overrepresented in breast cancer cells compared with normal breast epithelial cells. Moreover, a member of the MMP family (MMP-15) was highly expressed in the tumor lines, consistent with previous observations for other MMPs (12) . MMP proteins are able to degrade collagen and therefore may aide epithelial cell migration associated with metastatic progression (22) .
SAGE analysis also identified genes that are known to be underexpressed in transformed cells (Table 2B)
. Several genes encoding proteins with tumor suppressor capabilities were detected. Maspin, a member of the serpin superfamily of protease inhibitors, was highly overexpressed in the normal breast cells with respect to the tumor cell lines, as described previously (23)
. Although the target protease of maspin remains unknown, the protein has been shown to inhibit mammary tumor cell invasion and metastasis. Thrombospondin, an inhibitor of both tumorigenic and angiogenic activity in breast and other tissues (12)
, was also overexpressed in the normal breast samples. Furthermore, IGF binding protein-2, a modulator of the mitogenic activities of IGFs, was very highly expressed in the normal breast cells. Many studies have implicated IGF pathways in breast cancer progression (24
, 25)
.
Markers of normal mammary epithelium were also detected by SAGE. CaN19 is a member of the S100 family of Ca2+ binding proteins. Unlike other S100 proteins, CaN19 expression is high in normal mammary epithelia and lost in tumor cells (26) . Loss of CaN19 expression in tumor cells may contribute to the calcification seen in mammograms as an early marker for breast cancer (26) . As described above, tumor cells produce mainly keratins K8, K18, and K19, whereas nonhyperplastic cells express a different subset of keratins, including K15 and K17 (27) , consistent with our results. The GST-pi gene was highly expressed in the normal breast cultures when compared with the tumor cell lines. Accordingly, GST-pi has been found to be hypermethylated and not expressed in tumors of the prostate, kidney, and breast (28 , 29) . Galectin-7, a protein involved in cell-cell and cell-matrix interactions, was abundant in the normal breast cells and has been observed previously in nontransformed cells but not in carcinoma cells (30) . Interestingly, Galectin-7 was found to be a P53-inducible gene in a SAGE analysis of colorectal cancer cells (7) , although the tag sequence was different from the one detected here, suggesting that there are alternative splice forms of the mRNA. Tropomyosin 2 was also detected at elevated levels in the normal cells. High molecular weight tropomyosins, which regulate microfilament stability, are more highly expressed in noncancerous mammary cells than in breast tumors (31) . Finally, hemidesmosomes, adhesion structures found in stationary epithelial cells but not in migratory cells, are readily detected in normal mammary epithelial cells but are lost in invasive carcinoma cells (32) . Bullous pemphigoid antigen, a protein associated with hemidesmosomes, was found overexpressed by 12-fold in the normal breast cells compared with the breast tumor cell lines.
Confirmation of SAGE-identified, Differentially Expressed cDNAs with Clinical Tumors.
Genes that are highly expressed, or repressed, in breast tumors may be useful as tumor markers and may also play a functional role in disease progression. To extend the SAGE results to a larger set of samples with more clinical relevance, a subset of the differentially expressed genes identified by SAGE was spotted on an array and further screened using clinical tumors as probes. Sixty-eight known genes and ESTs, corresponding to SAGE tags that were either up- or down-regulated at least 5-fold, on average, in 21PT and 21MT with respect to the normal cells, were spotted on replicate nylon membranes. In addition to spotting genes already implicated in breast cancer, genes and ESTs not known previously to be involved in breast cancer were also included on the arrays for further study. SAGE analysis had detected little variation in the averaged expression of EF-1, 
-actin, -tubulin, and cyclophilin in the tumor and normal samples (data not shown), and these genes were included on the arrays as controls. mRNA was extracted from 7 primary breast tumors, 10 metastatic breast tumors, and 4 normal human mammary epithelial cell cultures. The transcripts were converted to 32P-labeled cDNAs and were used to screen replicate membranes. The signals from each hybridization were quantitated and normalized to decrease variations attributable to differences in overall hybridization efficiency. For each spotted cDNA target, the average signal intensity was calculated for hybridizations with the primary tumors, metastatic tumors, and normal breast tissue. Array expression profiles for the primary and metastatic tumors were compared with the array expression profiles for the normal breast cells.
As expected from the SAGE results, EF-1, -actin, -tubulin, and cyclophilin showed relatively even expression by array analysis (Fig. 1)
. The average of the tumor versus normal ratios for these four control genes was 1.1.
|
and Fig. 1
). However, only 6 of the top 10 differentially expressed targets were found in both primary and metastatic tumors (Table 3, A and B)
. Notably, 2 uncharacterized ESTs were among the 10 most differentially expressed genes in the primary tumor analysis, and 4 undefined ESTs were among the 10 most differentially expressed genes in the metastatic tumor analysis. As expected, MUC-1, HER2/neu, and Zinc--2-glycoprotein were overexpressed in the tumors. SAGE had detected the tag for the Claudin-7 gene 12 times in the tumor cell lines, whereas no Claudin-7 tags were found in the normal breast cultures. Accordingly, the array analysis showed that Claudin-7 was nearly undetectable in the normal cells but was highly induced in both primary and metastatic tumors (Fig. 1
and Table 3
). Claudin-7 is a new member of the multigene claudin family (33)
, which has not been implicated previously in cancers.
|
. Among the transcripts overexpressed in the normal cells were genes involved in cell adhesion and migration [Plakophilin-1 (34)
and Integrin -6 (35)
], a serine protease with an IGF-binding domain that is inhibited in tumors [PRSS11 (36)
], a known tumor suppressor [MEN1 (37)
], a DNA damage response gene [Ataxia-telangiectasia (12)
] and a cell cycle regulator shown previously to be underexpressed in breast carcinoma [cyclin D2 or CCND2 (38)
]. Consistent with the SAGE analysis (Table 2)
, GST-pi was highly overexpressed in the normal breast cells (Fig. 1
and Table 3, C and D
). Intriguingly, an uncharacterized EST was suppressed more than 6-fold in both primary and metastatic breast tumors. The custom array analysis detected the gene encoding a small proline-rich protein, SPR1, as the most highly differentially expressed transcript screened in the normal samples. This gene has been found in normal bronchial epithelial cells (39)
and keratinocytes (40)
but not in malignant counterparts.
Gene expression patterns in the primary and metastatic tumors were further analyzed by examining the individual expression levels of the most highly differential genes in each of the tumors used to screen the arrays (Table 4)
. Although MUC-1 showed an average overexpression of 32-fold in the primary tumors and 23-fold in the metastatic tumors (Table 3, A and B)
, 5 of 7 of the primary tumors and 7 of 10 of the metastatic tumors actually expressed it >100-fold greater than normal cells. Similarly, Claudin-7 was overexpressed >100-fold by 6 of 7 (85%) of the primary tumors and 6 of 10 (60%) of the metastatic tumors. The induction of HER-2/neu was <10-fold in 100% of the primary tumors and 70% of the metastatic tumors. Interestingly, B94, a truncated form of apolipoprotein B, showed a >3-fold induction in all but one of the primary tumors but was induced <3-fold in 60% of the metastatic tumors. Previous studies have found correlations between low expression of apolipoprotein B and both familial breast cancer (41)
and breast cancer recurrence (42)
. An uncharacterized EST (GenBank accession number R08988) showed 3–10-fold overexpression in 43% of the primary tumors (data not shown) and 60% of the metastatic tumors (Table 4B)
. Finally, thrombospondin (THBS1), a gene known to be involved in preventing angiogenesis, was actually slightly overexpressed by each of the primary tumors (Table 4A
and data not shown) but was underexpressed by 90% of the metastatic tumors (Table 4B
and data not shown).
|
. SPR1 showed at least 10-fold repression in all of the tumors, and approximately half of all of the tumors showed an underexpression of ataxia-telangiectasia group D (ATDC) of at least 10-fold. Interestingly, GST-pi was repressed 3–10-fold in 6 of 7 primary tumors, but it was repressed more than 10-fold in 7 of 10 metastatic tumors. In contrast, the gene encoding cyclin D2 was repressed >10-fold in only 1 of 7 primary tumors but was repressed at least 10-fold in nearly half of the metastatic tumors. The uncharacterized EST (GenBank accession number R08988) was repressed >10-fold in 41% of the tumors. |
Discussion |
|---|
|
TopABSTRACTIntroductionMaterials and MethodsResultsDiscussionREFERENCES |
|---|
Our SAGE analysis of breast tumor cell lines and normal mammary epithelial cell cultures revealed >200 genes that were differentially expressed at least 10-fold in the normal and diseased cells. Of the 119 tags overexpressed in the breast tumors at least 10-fold, 50 corresponded to uncharacterized ESTs, and 12 tags did not match anything in either the known mRNA or EST databases, suggesting that they represent novel genes. Similarly, of the 94 genes overexpressed at least 10-fold in the normal cells, 21 are uncharacterized ESTs and 9 are potentially novel genes.
SAGE analysis identified several genes that have already been implicated in breast cancer, such as HER2/neu, MUC-1, and FGF-1. In the normal breast cells, SAGE detected genes thought to be involved in differentiation and growth control, such as cytokeratins K15 and K17, IGF-BP2, and the gene encoding maspin, PI5. In addition, this analysis uncovered many genes and ESTs not implicated previously in breast cancer.
To validate the clinical relevance of the expression profiles seen in the cancer cell lines, a subset of the differentially expressed sequences identified by SAGE was further screened, in array format, against four normal breast epithelial cell cultures and 17 human primary and metastatic breast tumors. The 17 clinical tumors allowed us to find consistent patterns of gene expression in breast cancers. Of particular interest, Claudin-7, a gene cloned recently, was significantly overexpressed in all of the breast tumors examined (at least 100-fold in 85% of the primary tumors and >10-fold in all of the metastatic tumors). Claudins are proteins found in the specialized membrane domain of epithelial and endothelial cells known as tight junctions. In addition to facilitating cell-cell adhesion, tight junctions help maintain cell polarity and serve as a physical barrier to the passing of solutes and water from the paracellular space (43) . The expression pattern of Claudin-7 suggests that it plays a role in promoting or maintaining tumorigenesis, perhaps by altering adhesion properties of the cells and/or by allowing the flow of soluble growth factors or angiogenic molecules that are normally prevented from passing. Alternatively, Claudin-7 may create a barrier against angiogenesis inhibitors and/or proteins that hinder cell growth. Because Claudin-7 is not expressed in normal breast epithelial cells but is readily detectable in all of the breast tumors examined, it may serve as a good marker of breast carcinogenesis.
Another protein thought to be involved in transport of lipophilic substances, neutrophil gelatinase-associated lipocalin (NGAL/Lipocalin-2), was heterogeneously overexpressed in the breast tumors examined (Tables 3
and 4
), as was reported previously (44)
. This gene has also been detected at relatively high levels in cancers of the pancreas (45)
and colon (46)
, and its tag was found to be overrepresented in colon cancers.6
Several of the genes expressed at relatively high levels in normal breast epithelial cells, including the heparin binding protein HBp17, Ataxia telangiectasia group D, and GST-pi, were also detected at higher levels in our analyses of normal melanocytes and nontransformed cells of the lung and colon.7 This suggests that these genes may be involved in controlling the normal growth of multiple cell types. The tumor suppressor, maspin, however, was detected in normal breast, lung, and prostate epithelia but not in normal colon cells or melanocytes,7 suggesting that this protein may have a more specialized function.
An uncharacterized EST (W30727) that was elevated >6-fold in the normal breast cells with respect to both primary and metastatic tumors may represent a breast-specific epithelial cell marker because it was not observed in the >674,000 tags analyzed by SAGE from normal and transformed cells of the lung, prostate, colon, and melanocytes.7
Overall, primary and metastatic breast tumors showed similar gene expression profiles. Both types of cancers showed relatively high levels of induction of the genes encoding Mucin, Claudin-7, HER2/neu, B94, NGAL/Lipocalin 2, and an uncharacterized EST (N77731). This EST was induced >10-fold in three of the breast tumors, with one of the metastatic tumors expressing it >100-fold higher than normal cells.
Interestingly, there were some genes more highly induced in either the primary or metastatic tumors, with several of them representing uncharacterized ESTs. These may be unknown genes involved in genome instability, cell motility, or invasion. Zinc--2-glycoprotein was more highly expressed in primary breast tumors than in metastatic tissues, suggesting that it may be involved in early events in the tumorigenesis pathway. Given its similarity to MHC genes and its proposed function in intercellular processing of antigens (47)
, it is interesting to speculate that this protein helps tumor cells evade the host immune system.
The profile of genes that were underexpressed in primary tumors was strikingly similar to those genes underexpressed in metastatic tumors. Of all of the genes screened, the small proline-rich protein, SPR1 (also called SPRR1b), was the most highly overexpressed in normal cells when compared with all of the tumor tissues examined. Interestingly, previous work has shown that SPR1 is a specific marker for squamous lung carcinoma (48) . Accordingly, the tag corresponding to SPR1 was detected in SAGE libraries of squamous lung tumors but not in the >674,000 tags analyzed in libraries generated from malignancies of the colon, pancreas, prostate, or melanocytes.7 SPR1 is an envelope protein found commonly in epithelial cells and believed to be involved in cross-bridging. Therefore, SPR1 may contribute to the mechanical properties of cell envelopes (49) , and loss of this protein may promote tumorigenesis by facilitating invasion or loss of contact inhibition.
Overall, there were more differences seen in genes induced when comparing primary and metastatic tumors than when comparing normal cells with either tumor type. This suggests that the transition from normal regulated growth to cancer, and specifically from a primary tumor to a metastatic state, may require a positive, growth-promoting transcriptional program to be initiated. Accordingly, genes involved in maintaining normal regulated growth would be more consistently expressed with respect to either tumor type.
Combining two powerful gene expression profiling technologies allowed the rapid and efficient identification of many clinically relevant genes potentially involved in preventing or promoting breast cancer. The data from our SAGE analysis of tumor cell lines and array analysis using clinical tumors indicated some differences in gene expression profiles. This underscores the importance of applying a level of screening that includes clinical tumor samples. This broad study has identified several genes previously unknown to be involved in breast carcinogenesis. Many of these genes may be useful as diagnostic markers or prognostic indicators. In addition, studying the function of some of these genes may uncover new pathways for therapeutic intervention.
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
1 The research was funded by Genzyme Molecular Oncology and by USPHS Grants T32 CA09630 (to A. T. F.), CA48943, and P21 CA/ES 66204, a grant from the Susan G. Komen Foundation, and a grant from Johns Hopkins Oncology Research Funds (to S. S.). 
2 Present address: Calydon, Inc., 1324 Chesapeake Terrace, Sunnyvale, CA 94089.
3 To whom requests for reprints should be addressed, at Johns Hopkins Oncology Center, 370 Ross, 720 Rutland Avenue, Baltimore MD 21205. Phone: (410) 614-2479; Fax: (410) 614-4073; E-mail: saras{at}pop.jhmi.edu
4 The abbreviations used are: SAGE, serial analysis of gene expression; EST, expressed sequence tag; HMEC, human mammary epithelial cell; poly(A)+, polyadenylated; HMG, high mobility group; MMP, matrix metalloproteinase; GST, glutathione S-transferase; IGF, insulin-like growth factor.
5 Internet address: http://www.lbl.gov/LBL-Programs/mrgs/review.html.
6 Internet address: www.ncbi.nlm.nih.gov/SAGE/, and unpublished data.
Received 8/ 6/99. Accepted 9/17/99.
|
REFERENCES |
|---|
|
TopABSTRACTIntroductionMaterials and MethodsResultsDiscussionREFERENCES |
|---|
2-glycoprotein levels in breast cancer cytosols and correlation with clinical, histological and biochemical parameters. Eur. J Cancer, 9: 1256-1260, 1993.
61 in metastatic breast carcinoma cells assessed by expression of a dominant-negative receptor. Cancer Res., 56: 959-963, 1996.2-glycoprotein. complete genomic sequence, identification of a related pseudogene and relationship to class I major histocompatibility complex genes. Genomics, 18: 575-587, 1993.[Medline]
This article has been cited by other articles:
|
|
 |
|
  K. F. Rodriguez, L. A. Blomberg, K. A. Zuelke, J. R. Miles, J. E. Alexander, and C. E. Farin Identification of candidate mRNAs associated with gonadotropin-induced maturation of murine cumulus oocyte complexes using serial analysis of gene expression Physiol Genomics, November 21, 2006; 27(3): 318 - 327. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Dolled-Filhart, L. Ryden, M. Cregger, K. Jirstrom, M. Harigopal, R. L. Camp, and D. L. Rimm Classification of breast cancer using genetic algorithms and tissue microarrays. Clin. Cancer Res., November 1, 2006; 12(21): 6459 - 6468. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. V. Fournier, K. J. Martin, P. A. Kenny, K. Xhaja, I. Bosch, P. Yaswen, and M. J. Bissell Gene expression signature in organized and growth-arrested mammary acini predicts good outcome in breast cancer. Cancer Res., July 15, 2006; 66(14): 7095 - 7102. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. Guo, Y. Ma, R. Ward, V. Castranova, X. Shi, and Y. Qian Constructing Molecular Classifiers for the Accurate Prognosis of Lung Adenocarcinoma. Clin. Cancer Res., June 1, 2006; 12(11): 3344 - 3354. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. C. Cunningham, F. Kamangar, M. P. Kim, S. Hammoud, R. Haque, C. A. Iacobuzio-Donahue, A. Maitra, R. Ashfaq, S. Hustinx, R. E. Heitmiller, et al. Claudin-4, mitogen-activated protein kinase kinase 4, and stratifin are markers of gastric adenocarcinoma precursor lesions. Cancer Epidemiol. Biomarkers Prev., February 1, 2006; 15(2): 281 - 287. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. J. Morin Claudin Proteins in Human Cancer: Promising New Targets for Diagnosis and Therapy Cancer Res., November 1, 2005; 65(21): 9603 - 9606. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. E. Adair, Y. Kwon, G. A. Dement, M. J. Smerdon, and R. Reeves Inhibition of Nucleotide Excision Repair by High Mobility Group Protein HMGA1 J. Biol. Chem., September 16, 2005; 280(37): 32184 - 32192. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. B. Vos, M. A. van Sterkenburg, K. F. Rabe, J. Schalkwijk, P. S. Hiemstra, and N. A. Datson Transcriptional response of bronchial epithelial cells to Pseudomonas aeruginosa: identification of early mediators of host defense Physiol Genomics, May 11, 2005; 21(3): 324 - 336. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. S. Parker, P. Argani, B. P. Cook, H. Liangfeng, S. D. Chartrand, M. Zhang, S. Saha, A. Bardelli, Y. Jiang, T. B. St. Martin, et al. Alterations in Vascular Gene Expression in Invasive Breast Carcinoma Cancer Res., November 1, 2004; 64(21): 7857 - 7866. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. L. Kominsky, M. Vali, D. Korz, T. G. Gabig, S. A. Weitzman, P. Argani, and S. Sukumar Clostridium perfringens Enterotoxin Elicits Rapid and Specific Cytolysis of Breast Carcinoma Cells Mediated through Tight Junction Proteins Claudin 3 and 4 Am. J. Pathol., May 1, 2004; 164(5): 1627 - 1633. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Mehrotra, M. Vali, M. McVeigh, S. L. Kominsky, M. J. Fackler, J. Lahti-Domenici, K. Polyak, N. Sacchi, E. Garrett-Mayer, P. Argani, et al. Very High Frequency of Hypermethylated Genes in Breast Cancer Metastasis to the Bone, Brain, and Lung Clin. Cancer Res., May 1, 2004; 10(9): 3104 - 3109. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. D Stein, T. Litman, T. Fojo, and S. E Bates A Serial Analysis of Gene Expression (SAGE) Database Analysis of Chemosensitivity: Comparing Solid Tumors with Cell Lines and Comparing Solid Tumors from Different Tissue Origins Cancer Res., April 15, 2004; 64(8): 2805 - 2816. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. K. Dougherty and D. K. Morrison Unlocking the code of 14-3-3 J. Cell Sci., April 15, 2004; 117(10): 1875 - 1884. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Moore, Z. Medarova, A. Potthast, and G. Dai In Vivo Targeting of Underglycosylated MUC-1 Tumor Antigen Using a Multimodal Imaging Probe Cancer Res., March 1, 2004; 64(5): 1821 - 1827. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. B. A. Rangel, R. Agarwal, T. D'Souza, E. S. Pizer, P. L. Alo, W. D. Lancaster, L. Gregoire, D. R. Schwartz, K. R. Cho, and P. J. Morin Tight Junction Proteins Claudin-3 and Claudin-4 Are Frequently Overexpressed in Ovarian Cancer but Not in Ovarian Cystadenomas Clin. Cancer Res., July 1, 2003; 9(7): 2567 - 2575. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. P. M. Reddy, H. Vuong, and P. Adiseshaiah Interplay between Proximal and Distal Promoter Elements Is Required for Squamous Differentiation Marker Induction in the Bronchial Epithelium: ROLE FOR ESE-1, Sp1, AND AP-1 PROTEINS J. Biol. Chem., June 6, 2003; 278(24): 21378 - 21387. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Jiang, W. Zhang, K. Kondo, J. M. Klco, T. B. St. Martin, M. R. Dufault, S. L. Madden, W. G. Kaelin Jr, and M. Nacht Gene Expression Profiling in a Renal Cell Carcinoma Cell Line: Dissecting VHL and Hypoxia-Dependent Pathways Mol. Cancer Res., April 1, 2003; 1(6): 453 - 462. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. F. Schlaak, C. M. U. Hilkens, A. P. Costa-Pereira, B. Strobl, F. Aberger, A.-M. Frischauf, and I. M. Kerr Cell-type and Donor-specific Transcriptional Responses to Interferon-alpha . USE OF CUSTOMIZED GENE ARRAYS J. Biol. Chem., December 13, 2002; 277(51): 49428 - 49437. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W. D. Patino, O. Y. Mian, and P. M. Hwang Serial Analysis of Gene Expression: Technical Considerations and Applications to Cardiovascular Biology Circ. Res., October 4, 2002; 91(7): 565 - 569. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. S. Wilson, H. Roberts, R. Leek, A. L. Harris, and J. Geradts Differential Gene Expression Patterns in HER2/neu-Positive and -Negative Breast Cancer Cell Lines and Tissues Am. J. Pathol., October 1, 2002; 161(4): 1171 - 1185. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Koenig, S. R. Bianco, S. Fosmire, J. Wojcieszyn, and J. F. Modiano Expression and Significance of p53, Rb, p21/waf-1, p16/ink-4a, and PTEN Tumor Suppressors in Canine Melanoma Vet. Pathol., July 1, 2002; 39(4): 458 - 472. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. A. Iacobuzio-Donahue, A. Maitra, G. L. Shen-Ong, T. van Heek, R. Ashfaq, R. Meyer, K. Walter, K. Berg, M. A. Hollingsworth, J. L. Cameron, et al. Discovery of Novel Tumor Markers of Pancreatic Cancer using Global Gene Expression Technology Am. J. Pathol., April 1, 2002; 160(4): 1239 - 1249. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. K. Richer, B. M. Jacobsen, N. G. Manning, M. G. Abel, D. M. Wolf, and K. B. Horwitz Differential Gene Regulation by the Two Progesterone Receptor Isoforms in Human Breast Cancer Cells J. Biol. Chem., February 8, 2002; 277(7): 5209 - 5218. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 I. Sargiannidou, J. Zhou, and G. P. Tuszynski The Role of Thrombospondin-1 in Tumor Progression Experimental Biology and Medicine, September 1, 2001; 226(8): 726 - 733. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 F. Song, M. Srinivasan, R. Aalinkeel, and M. S. Patel Use of a cDNA Array for the Identification of Genes Induced in Islets of Suckling Rats by a High-Carbohydrate Nutritional Intervention Diabetes, September 1, 2001; 50(9): 2053 - 2060. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. A. Porter, I. E. Krop, S. Nasser, D. Sgroi, C. M. Kaelin, J. R. Marks, G. Riggins, and K. Polyak A SAGE (Serial Analysis of Gene Expression) View of Breast Tumor Progression Cancer Res., August 1, 2001; 61(15): 5697 - 5702. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W.-K. Hofmann, S. de Vos, K. Tsukasaki, W. Wachsman, G. S. Pinkus, J. W. Said, and H. P. Koeffler Altered apoptosis pathways in mantle cell lymphoma detected by oligonucleotide microarray Blood, August 1, 2001; 98(3): 787 - 794. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Koenig, J. Wojcieszyn, B. R. Weeks, and J. F. Modiano Expression of S100a, Vimentin, NSE, and Melan A/MART-1 in Seven Canine Melanoma Cell Lines and Twenty-nine Retrospective Cases of Canine Melanoma Vet. Pathol., July 1, 2001; 38(4): 427 - 435. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. A. Zajchowski, M. F. Bartholdi, Y. Gong, L. Webster, H.-L. Liu, A. Munishkin, C. Beauheim, S. Harvey, S. P. Ethier, and P. H. Johnson Identification of Gene Expression Profiles That Predict the Aggressive Behavior of Breast Cancer Cells Cancer Res., July 1, 2001; 61(13): 5168 - 5178. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Y. Ljubimova, A. J. Lakhter, A. Loksh, W. H. Yong, M. S. Riedinger, J. H. Miner, L. M. Sorokin, A. V. Ljubimov, and K. L. Black Overexpression of {alpha}4 Chain-containing Laminins in Human Glial Tumors Identified by Gene Microarray Analysis Cancer Res., July 1, 2001; 61(14): 5601 - 5610. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. Polyak and G. J. Riggins Gene Discovery Using the Serial Analysis of Gene Expression Technique: Implications for Cancer Research J. Clin. Oncol., June 1, 2001; 19(11): 2948 - 2958. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. V. Anisimov, E. G. Lakatta, and K. R. Boheler Discovering altered genomic expression patterns in heart: transcriptome determination by serial analysis of gene expression Eur J Heart Fail, June 1, 2001; 3(3): 271 - 281. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. P. Hale, D. T. Price, L. M. Sanchez, W. Demark-Wahnefried, and J. F. Madden Zinc {{alpha}}-2-Glycoprotein Is Expressed by Malignant Prostatic Epithelium and May Serve as a Potential Serum Marker for Prostate Cancer Clin. Cancer Res., April 1, 2001; 7(4): 846 - 853. [Abstract] [Full Text]
|
|
|
|
|
|
T. Thykjaer, C. Workman, M. Kruhøffer, K. Demtröder, H. Wolf, L. D. Andersen, C. M. Frederiksen, S. Knudsen, and T. F. Ørntoft Identification of Gene Expression Patterns in Superficial and Invasive Human Bladder Cancer Cancer Res., March 1, 2001; 61(6): 2492 - 2499. [Abstract] [Full Text]
|
|
|
|
|
|
E. Evron, C. B. Umbricht, D. Korz, V. Raman, D. M. Loeb, B. Niranjan, L. Buluwela, S. A. Weitzman, J. Marks, and S. Sukumar Loss of Cyclin D2 Expression in the Majority of Breast Cancers Is Associated with Promoter Hypermethylation Cancer Res., March 1, 2001; 61(6): 2782 - 2787. [Abstract] [Full Text]
|
|
|
|
 |
|
 R. Reeves, D. D. Edberg, and Y. Li Architectural Transcription Factor HMGI(Y) Promotes Tumor Progression and Mesenchymal Transition of Human Epithelial Cells Mol. Cell. Biol., January 15, 2001; 21(2): 575 - 594. [Abstract] [Full Text]
|
|
|
|
 |
|
 F. Bertucci, R. Houlgatte, A. Benziane, S. Granjeaud, J. Adelaide, R. Tagett, B. Loriod, J. Jacquemier, P. Viens, B. Jordan, et al. Gene expression profiling of primary breast carcinomas using arrays of candidate genes Hum. Mol. Genet., December 1, 2000; 9(20): 2981 - 2991. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. D. Hough, C. A. Sherman-Baust, E. S. Pizer, F. J. Montz, D. D. Im, N. B. Rosenshein, K. R. Cho, G. J. Riggins, and P. J. Morin Large-Scale Serial Analysis of Gene Expression Reveals Genes Differentially Expressed in Ovarian Cancer Cancer Res., November 1, 2000; 60(22): 6281 - 6287. [Abstract] [Full Text]
|
|
|
|
|
|
K. Ono, T. Tanaka, T. Tsunoda, O. Kitahara, C. Kihara, A. Okamoto, K. Ochiai, T. Takagi, and Y. Nakamura Identification by cDNA Microarray of Genes Involved in Ovarian Carcinogenesis Cancer Res., September 1, 2000; 60(18): 5007 - 5011. [Abstract] [Full Text]
|
|
|
|
|
|
D. Scheurle, M. P. DeYoung, D. M. Binninger, H. Page, M. Jahanzeb, and R. Narayanan Cancer Gene Discovery Using Digital Differential Display Cancer Res., August 1, 2000; 60(15): 4037 - 4043. [Abstract] [Full Text]
|
|
|
|
 |
|
 A. T. Ferguson, E. Evron, C. B. Umbricht, T. K. Pandita, T. A. Chan, H. Hermeking, J. R. Marks, A. R. Lambers, P. A. Futreal, M. R. Stampfer, et al. High frequency of hypermethylation at the 14-3-3 sigma locus leads to gene silencing in breast cancer PNAS, May 23, 2000; 97(11): 6049 - 6054. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Meeting Abstracts Online |
