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1 Departments of Pathology,
2 Surgery,
3 Oncology, and
4 Medicine, The Johns Hopkins Medical Institutions, Baltimore, Maryland;
5 Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas;
6 Department of Pathology, Wayne State University, Detroit, Michigan;
7 Gene Logic, Inc., Gaithersburg, Maryland; and
8 The Eppley Institute, University of Nebraska, Omaha, Nebraska
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ABSTRACT |
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 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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3-fold expression levels in pancreas cancer specimens as compared with nonneoplastic tissues, corresponding to 234 known genes. Serial analysis of gene expression libraries (http://www.ncbi.nlm.nih.gov/SAGE/) of two normal pancreatic ductal cell cultures (HX and H126) were used to exclude 17 genes with high expression levels in the normal duct epithelium (more than five tags/library). Of the remaining 217 known genes, 75 have been previously reported as highly expressed in pancreatic cancers, while the remaining 142 genes are novel. We used principal components analysis (PCA) to identify the genes among these 217 identified as the most differentially expressed and specific to pancreatic cancer tissues or cell lines. Among the most differentially expressed genes identified by PCA were Mesothelin, Muc4, Muc5A/C, Kallikrein 10, Transglutaminase 2, Fascin, TMPRSS3 and stratifin. The differential expression identified by PCA for these genes indicates they are among the more attractive targets for novel therapeutic targets, tumor markers, or as a means of screening pancreatic cancer samples for information regarding tumor classification or potential therapeutic responses. Our findings were also compared in detail to the previously reported findings of highly expressed genes in other studies of global gene expression in pancreatic cancers. We found that robust changes in gene expression were most often identified by more than one gene expression platform. Forty genes were identified by more than one method (U133 oligonucleotide arrays, cDNA arrays or serial analysis of gene expression), and 6 of these genes were identified by all three methods. Our findings identify a novel set of genes as highly expressed in pancreatic cancer, validate the differential expression of previously reported genes, and provide additional support for those genes most differentially expressed to be translated into clinically useful targets. |
INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The recent mapping of the human genome has greatly facilitated the success of global gene expression methodologies in the study of human cancers because these technologies are based on coding sequences derived from the human genome project (1 , 2) . Recently, Affymetrix, Inc., has produced the UG-133 GeneChip based on Build 133 of the human genome.9 One particular advantage of the UG-133 chip is that many transcripts previously identified only as expressed sequence tags (ESTs) have now been characterized, allowing for a more comprehensive view of gene expression in samples studied.
More than 100 novel overexpressed markers of pancreatic cancer have now been identified using a variety of global gene expression methodologies, including representational difference analysis and subtractive hybridization (3, 4, 5) , differential display (6) , serial analysis of gene expression (SAGE; 7, 8, 9 ), cDNA microarrays (10, 11, 12, 13) , and oligonucleotide arrays (14) . A major issue in the use of gene expression profiling is how these different platforms compare with each other with respect to various parameters such as sensitivity and specificity in detecting highly expressed genes. These and other factors may affect not only one’s choice of methodology used in designing an experiment, but also how the derived data should be interpreted.
In this study, we have analyzed a large set of pancreatic adenocarcinomas, pancreas cancer cell lines, chronic pancreatitis, normal pancreas, and normal duodenal tissues using the UG-133 GeneChip in an effort to (a) further characterize the gene expression signature of pancreatic cancers; (b) identify novel markers of pancreatic cancer not recognized using prior methods, including our previous study using UG-95 GeneChips; (c) identify those highly expressed genes with the most promise for development into novel diagnostic or therapeutic markers; and (d) compare our findings with previously reported studies of gene expression in pancreatic cancers.
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MATERIALS AND METHODS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Cell Lines.
Human pancreatic cancer cell lines AsPc1, CAPAN1, CAPAN2, CFPAC1, COLO357, Hs766T, MiaPaCa2, and Panc-1 were obtained from the American Type Culture Collection (Manassas, VA). Panc 2.13, Panc 4.14, Panc 6.03, Panc 8.13, Panc 3.27, and PL4 are low-passage pancreatic carcinoma cell lines kindly provided by Dr. Elizabeth Jaffee (15)
. Panc 2.13, Panc 4.14, Panc 6.03, Panc 8.13, and Panc 3.27 were recently submitted to the American Type Culture Collection and are now more generally available online.10
All cell lines were cultured in DMEM supplemented with 10% FBS and antibiotics (100 units/ml penicillin and 100 µg/ml streptomycin) with the exception of the CAPAN1 and CAPAN2 cell lines cultured in RPMI 1640 (Life Technologies, Inc., Gaithersburg, MD) supplemented with 10% FBS and antibiotics (100 units/ml penicillin and 100 µg/ml streptomycin). The use of different media minimized the variance in growth rates that would otherwise be exaggerated with a single medium. Cells were incubated at 37°C in a humidified atmosphere of 5% CO2 in air.
mRNA Extractions and Affymetrix GeneChip Hybridization.
Sample preparation and processing procedure was performed as described in detail in the Affymetrix GeneChip Expression Analysis Manual (Santa Clara, CA) and in our prior publication (14)
with the exception that the labeled cRNA samples were hybridized to the complete human U133 GeneChip set (HG_U133 A and HG_U133 B).
Statistical Data Analysis.
The GeneExpress Software System Fold Change Analysis tool was used to identify all present genes expressed at least 3-fold greater in the pancreatic cancers compared with normal tissues. For each gene fragment, the ratio of the geometric means of the expression intensities in the normal control tissues and the pancreatic cancer samples was calculated, and the fold change was then calculated on a per fragment basis. Confidence limits were calculated using a two-sided Welch modified t test on the difference of the means of the logs of the intensities.
Biocomputational Tools.
The Cluster and TreeView computer programs were obtained from an online resource11
and used for principal component analysis (PCA) and visualization of the data (16)
. Raw expression data for all gene fragments corresponding to known genes were imported into the Cluster program, log-transformed, and PCA performed with visualization of the tree diagrams generated using the TreeView program.
SAGE.
SAGE library data from the short-term cultures of non-neoplastic pancreatic duct epithelial cells available on the Cancer Genome Anatomy Project web site11 as part of the SAGEmap database were used to identify genes expressed in normal ductal cells. The preparation and validation of these short-term cultures of nonneoplastic pancreatic ductal epithelial cells (HX and H126) were described previously (17)
.
Construction of Tissue Microarrays and Immunohistochemical Labeling.
Tissue microarrays containing 68 different surgically resected infiltrating ductal pancreatic adenocarcinomas and a variety of normal tissues were constructed as described previously (18)
. Each carcinoma was represented four times in each tissue microarray to account for potential tumor heterogeneity. Unstained 4-µm sections were cut from each tissue microarray and deparaffinized by routine techniques before placing in 200 ml of Target Retrieval Solution (pH 6.0, Envision Plus Detection kit; Dako, Carpenteria, CA) for 20 min at 100°C. After cooling for 20 min, slides were quenched with 3% H2O2 for 5 min before incubating with the appropriate dilution of each primary antibody (a 1:1000 dilution of mouse monoclonal antihuman Muc 5A/C or a 1:1000 dilution of polyclonal antihuman ESDN; Orbigen, San Diego, CA) for 30 min using the Dako Autostainer. Labeling was detected with the Dako Envision system following the manufacturers protocol. Labeling was detected by adding biotinylated secondary antibodies, avidin-biotin complex, and 3,3'-diaminobenzidine. All sections were counterstained with hematoxylin.
Comparison of Gene Expression Patterns Identified by Different Methodologies.
We have previously reported the gene expression profiles of pancreatic cancer identified by U95 oligonucleotide arrays (14)
by cDNA microarrays (10)
and by SAGE (7, 8, 9)
. The data obtained from these studies was compiled into one Excel spreadsheet for a comparison of gene expression profiling of pancreatic cancers, with all otherwise nonannotated (orphan) ESTs excluded because of the inability to cross validate the identities of many of these ESTs between different gene expression platforms.
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RESULTS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Identification of Highly Expressed Genes in Pancreatic Cancers.
Among these 279 fragments identified corresponding to known genes, 38 genes were represented by more than one Affymetrix fragment (range, 2–4). When these fragments were accounted for, 234 individual genes were identified. Those expressed 4-fold are listed in Table 1
. Eighty-one of these 234 known genes have been previously reported as overexpressed in pancreatic cancer (Table 2)
.
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PCA of Highly Expressed Genes.
In the evaluation of highly expressed genes in pancreatic cancer, it would be useful to identify those genes that may be differentially expressed between the normal and neoplastic epithelium (as opposed to those genes generally up-regulated in the presence of chronic pancreatitis) and therefore more specific tumor markers and therapeutic targets. We used PCA to identify those highly expressed genes that are most differentially expressed among all 217 known genes identified. PCA can provide a global overview of the relatedness of gene expression profiles among samples while better avoiding the deterministic and rather arbitrary nature of hierarchical clustering. This delineation allows not only for a better understanding of the role of these genes in pancreas cancers but also those most promising for development into novel screening tests and therapeutic targets.
PCA of the expression data derived from 96 samples representing the 50 normal, 7 chronic pancreatitis, and 39 pancreatic cancers confirmed the overall high levels of expression of these genes in cancer tissue and cell line samples in comparison to normal duodenal or pancreas tissues (Fig. 1)
. However, three patterns were visualized based on this analysis. First, we noted that some of these genes were only expressed within the resected cancer tissues (e.g., collagen type X
1) or the cancer cell lines (e.g., pleckstrin homology-like domain and family A member 1) as compared with normal tissues but not in both the resected cancers and the cancer cell lines. Those genes expressed among the resected pancreas cancer tissues and not the cell lines may reflect either genes expressed by the cellular components of the host stromal response or genes expressed by the neoplastic epithelium as a result of its interactions with the juxtatumoral stroma (19
, 20)
. In contrast, genes expressed by the pancreas cancer cell lines but not the resected cancer tissues may reflect the enhanced proliferation rate commonly observed for cells growing in artificial conditions. For example, the Ki67 proliferation antigen was highly expressed in the pancreas cancer cell lines and normal duodenal mucosa (a highly proliferative tissue) but not the resected cancers.
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In the third pattern revealed by PCA, many genes were noted to be specifically expressed among both the resected cancer tissues and cancer cell lines but were not detected in normal pancreas, normal duodenum, or chronic pancreatitis tissues. These genes appear to be the most specifically expressed within pancreas cancers among all of the highly expressed genes identified. Some of these genes have previously been reported as highly expressed in pancreatic cancer (e.g., mesothelin, TMPRSS3, Muc5A/C, and Fascin), whereas several others identified with this pattern are novel (e.g., antigen p97, BCL-2 interacting killer, cathepsin L2, kallikrein 10, and matrilin 3).
Of note, one sample of normal pancreas tissue (np17) was found to have gene expression levels similar to those seen in some of the pancreatic cancers. The pathology report of this sample was reviewed and indicated that foci of pancreatic intraepithelial neoplasia, but not infiltrating carcinoma, were present within the sample.
Verification and Localization of Selected Candidate Tumor Markers.
A number of highly expressed genes identified in this study have previously been validated as overexpressed in pancreas cancers, including mesothelin (9)
, PSCA (8)
, Muc4 (21)
, Fascin (18)
, and topoisomerase II (14)
, consistent with our findings using PCA. Two additional genes (Muc5A/C and ESDN) were selected for verification of the expression patterns identified by PCA in normal pancreas and resected pancreatic cancer tissues using immunohistochemical labeling (Fig. 2)
.
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. Normal duct epithelium was negative for Muc 5A/C, with exception of scattered ducts in areas of atrophy, which showed only weak labeling.
ESDN was one of the genes that, although consistently expressed in normal pancreas or duodenal tissues, were expressed at higher levels in the chronic pancreatitis and pancreatic cancer samples. Immunohistochemical labeling for ESDN protein was consistent with this pattern. ESDN protein was detected in all 66 paraffin-embedded pancreas cancers (100%) analyzed, and it was expressed in both the neoplastic epithelium and desmoplastic stroma. The neoplastic epithelium labeled in a cytoplasmic distribution and the stroma labeling was noted both within fibroblasts and inflammatory cells. ESDN labeling was also noted within all samples of normal pancreas or duodenal mucosa. However, the intensity of labeling within both the neoplastic epithelium and the intervening stroma was significantly greater than that observed within the normal pancreas tissues (Fig. 2, C and D)
.
Comparison of Gene Expression Patterns Identified among Different Technologies.
Of major interest would be the direct comparison of competing expression profiling technologies. We previously reported the gene expression profiles of pancreatic cancer identified by oligonucleotide arrays (14)
, cDNA microarrays (10)
, and SAGE (7, 8, 9)
. We chose to compare the previously generated cDNA microarray and SAGE data we have to the current findings to determine the similarities of each method in detecting robust increases in gene expression.
Among the three methods, a total of 422 unique genes or hypothetical proteins were identified (Fig. 3)
. A total of 263 overexpressed genes or hypothetical proteins was identified in this current analysis, 55 by our previous SAGE analysis, and 150 by our previous cDNA microarrays analysis in which we used Statistical Analysis of Microarray. Forty of these 422 genes were identified by more than one method (Table 3)
. Six of these 40 genes were commonly identified by all three methods, 26 of 40 were identified by both oligonucleotide arrays and cDNA microarrays only, 5 of 40 genes by both oligonucleotide arrays and SAGE only, and 3 of 40 genes by SAGE and cDNA microarrays only. Fifteen of these 40 genes have previously been reported as highly expressed in pancreas cancer (Table 3)
. These 15 genes comprised 3 of 6 genes common to all three methods of detection, 9 of 26 additional genes common to the U133 arrays and cDNA microarrays, 1 of 3 additional genes common to SAGE and cDNA microarrays, and 2 of 5 additional genes common to SAGE and U133 arrays. These numbers could be expected to vary, differing on the cutoff criteria applied to individual technologies and the effort devoted to additional validation efforts. Nevertheless, overexpressed genes can be identified by more than one method, and genes identifiable by more than one method were preferentially enriched in the prior literature.
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DISCUSSION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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When using gene expression profiling to understand human neoplasms, long lists of genes are produced that require further categorization into meaningful groups. In this study, we used PCA to identify the patterns of differential gene expression and therefore most promising for translation into useful clinical targets. Among the most differentially expressed genes identified by PCA were Muc4, Muc5A/C, Fascin, epiregulin, TMPRSS3, mesothelin, and topoisomerase II. These genes have been previously identified as highly expressed in pancreatic cancers (Table 2)
, and there differential expression identified by PCA indicates they are among the more attractive targets for novel therapeutic strategies. Several other genes that have not been previously reported also showed differential expression among pancreatic cancer specimens, including, tumor antigen p97, cadherin EGF LAG seven-pass G-type receptor 1, cathepsin L2, matrilin3, and kallikrein 10.
Tumor antigen 97 and cadherin EGF LAG seven-pass G-type receptor 1 are both membrane-bound proteins. Tumor antigen p97, also known as melanotransferrin, is a membrane-bound transferrin homologue with several characteristics in common with serum transferrin. Tumor antigen p97 is found at high levels in melanoma cells and binds ferritin (23) . Cadherin EGF LAG seven-pass G-type receptor 1 (also known as flamingo homologue, Drosophilia) is a G protein-coupled receptor thought to function in contact-mediated communication between cells. Within its external domain are several cadherin-like repeats and seven EGF-like repeats, both known mediators of protein-protein interactions (24) .
Cathepsin L2, matrilin 3, and kallikrein 10 are not membrane-bound. Cathepsin L2 is one of several cysteine proteinases that are involved in a variety of normal cellular processes and up-regulated in breast and colorectal cancers (25) . Cysteine proteinases are synthesized as preproenzymes, which are processed to the corresponding proenzymes. The proenzymes are either targeted to the lysosome or continue along the cellular secretory route where they may become activated in the extracellular space. Kallikrein 10 and matrilin 3 also function within the extracellular space. Kallikrein 10 is a member of the kallikrein family of secreted serine proteases that include 15 proteins, including the prostate-specific antigen, also known as hK3 (26 , 27) . Matrilin 3 is one of a family of matrilin proteins that are components of the extracellular matrix. Matrilin 3 contains a von Willebrand factor type A-like domain thought to be necessary for interactions with collagen (28) .
Overexpressed genes that are not expressed in normal tissues and that encode for membrane bound proteins (mesothelin, TMPRSS3, Muc4, Muc5A/C, or tumor antigen p97) hold the most promise for use as specific targets for antibody or cell-mediated vaccines for pancreatic cancer. For example, cell-mediated immunotherapy can be both safe and effective in generating immune responsiveness in patients with pancreatic cancer (15) . Thus, each of these differentially expressed membrane bound genes represents a potential target for the development of a cell-mediated vaccine or antibody-based immunotherapy against pancreatic cancers expressing these antigens (29, 30, 31, 32) . Membrane-bound proteins such as TMPRSS3 are additionally interesting because their proteolytic activity can be exploited to activate prodrugs at the cell surface (33) . In contrast, differentially expressed genes that encode for cytoplasmic or lysosomal enzymes may be more ideal for targeting by novel chemotherapeutic agents or radioimaging such as the lysosomal enzyme cathepsin L2 (25) .
Seventy-five of the overexpressed genes identified in this study have been previously reported as highly expressed in pancreatic cancer (Table 2)
. These 75 genes validate our approach in gene marker discovery within pancreatic cancers, and these 75 genes, in turn, are also validated as potentially important due to their repeated identification as overexpressed in pancreatic cancer by multiple platforms. We also identified 142 additional genes not previously reported as overexpressed in pancreatic cancer. The large number of genes identified as highly expressed in this study may indicate a greater sensitivity of the UG-133 GeneChip as compared with other studies but may also be accounted for by the greater number and type of specimens used or the relatively low threshold criterion (fold-change) used. Some of the genes identified in this analysis are likely attributable to expression by entrapped residual pancreatic acini or islet cells within the resected pancreatic cancer samples (i.e., biliverdin reductase A or glucosidase ß). Thus, it is likely that not all of the 143 genes identified will ultimately represent clinically useful targets for therapeutic development, and additional studies to evaluate the use of these genes are warranted.
The redundancy observed in published reports for many of the highly expressed genes identified in pancreatic cancers lends support to these genes playing a role in the neoplastic process in pancreatic cancers. We also found that a considerable overlap exists in the gene expression detected using three of the major global gene expression methodologies currently used in transcription profiling. Moreover, the genes commonly detected by these methods are among those that have been identified as highly expressed by a variety of independent investigators such as Trop-2 (identified by SAGE and U133 arrays; Ref. 34 ), myoferlin and lipocalin 2 (identified by U133 arrays and cDNA arrays; Refs. 11 , 35 ), or claudin 4 (identified by SAGE and cDNA arrays; Ref. 36 ). Six genes were identified by all three methodologies (keratin 19, retinoic acid-induced 3, secretory leukocyte protease inhibitor, stratifin, tetraspan 1, and transglutaminase 2), three of which have been previously reported as highly expressed in pancreatic cancers (37, 38, 39) .
One sample of normal pancreas was found to have high levels of expression of a number of genes also highly expressed in pancreatic cancers. This normal pancreas was found upon review to contain pancreatic intraepithelial neoplasia, the presumed precursor to invasive pancreatic cancer, suggesting that some of the genes identified may be up-regulated in expression early in the neoplastic progression to invasive carcinoma (40) . Indeed, Muc4 was one of the genes expressed by this normal pancreas sample. Muc4 has been shown by Swartz et al. (21) to be expressed at high levels in pancreatic intraepithelial neoplasias and in invasive pancreatic cancers, indicating that some of these genes may have use as markers for detecting preinvasive duct lesions in addition to invasive cancers. Similarly, genes highly expressed within pancreatic intraepithelial neoplasias may provide targets for imaging of preinvasive neoplastic lesions within the pancreatic duct system. The identification of early, preinvasive lesions is of particular interest for patients with a strong family history of pancreatic cancer whose lifetime risk for developing pancreatic cancer may be increased (41) .
The benefits to be derived from transcription profiling of pancreatic cancer will only be realized with the pursuit of those targets most meaningful for translation into useful clinical modalities for treating this lethal disease. Our comprehensive characterization of those genes most highly expressed within pancreas ductal adenocarcinomas provides validation of a number of genes identified as highly expressed and also provides clues as to which genes are most promising for additional evaluation.
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Requests for reprints: Christine A. Iacobuzio-Donahue, The Johns Hopkins Hospital, Division of Gastrointestinal/Liver Pathology, 720 Rutland Street, Ross Building Room 632, Baltimore, MD 21205. Phone: (410) 955-3511; Fax: (410) 614-0671; E-mail: ciacobu{at}jhmi.edu
9 Internet address: http://www.affymetrix.com. 
10 Internet address: http://www.atcc.org.
11 Internet address: http://www.microarrays.org/software.html.
12 Internet address: http://www.ncbi.nlm.nih.gov/SAGE/.
Received 1/24/03. Revised 8/ 1/03. Accepted 8/27/03.
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D.-S. Kim, S.-S. Park, B.-H. Nam, I.-H. Kim, and S.-Y. Kim Reversal of Drug Resistance in Breast Cancer Cells by Transglutaminase 2 Inhibition and Nuclear Factor-{kappa}B Inactivation. Cancer Res., November 15, 2006; 66(22): 10936 - 10943. [Abstract] [Full Text] [PDF]
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K. Ohuchida, K. Mizumoto, T. Egami, H. Yamaguchi, K. Fujii, H. Konomi, E. Nagai, K. Yamaguchi, M. Tsuneyoshi, and M. Tanaka S100P Is an Early Developmental Marker of Pancreatic Carcinogenesis. Clin. Cancer Res., September 15, 2006; 12(18): 5411 - 5416. [Abstract] [Full Text] [PDF]
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X. Deng, D. Z. Ewton, S. Li, A. Naqvi, S. E. Mercer, S. Landas, and E. Friedman The Kinase Mirk/Dyrk1B Mediates Cell Survival in Pancreatic Ductal Adenocarcinoma. Cancer Res., April 15, 2006; 66(8): 4149 - 4158. [Abstract] [Full Text] [PDF]
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N. Koide, T. Yamada, R. Shibata, T. Mori, M. Fukuma, K. Yamazaki, K. Aiura, M. Shimazu, S. Hirohashi, Y. Nimura, et al. Establishment of Perineural Invasion Models and Analysis of Gene Expression Revealed an Invariant Chain (CD74) as a Possible Molecule Involved in Perineural Invasion in Pancreatic Cancer Clin. Cancer Res., April 15, 2006; 12(8): 2419 - 2426. [Abstract] [Full Text] [PDF]
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A. Jimeno and M. Hidalgo Molecular biomarkers: their increasing role in the diagnosis, characterization, and therapy guidance in pancreatic cancer. Mol. Cancer Ther., April 1, 2006; 5(4): 787 - 796. [Abstract] [Full Text] [PDF]
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 T. S. Kim, C. Heinlein, R. C. Hackman, and P. S. Nelson Phenotypic Analysis of Mice Lacking the Tmprss2-Encoded Protease Mol. Cell. Biol., February 1, 2006; 26(3): 965 - 975. [Abstract] [Full Text] [PDF]
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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]
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H. Matsubayashi, M. Canto, N. Sato, A. Klein, T. Abe, K. Yamashita, C. J. Yeo, A. Kalloo, R. Hruban, and M. Goggins DNA Methylation Alterations in the Pancreatic Juice of Patients with Suspected Pancreatic Disease Cancer Res., January 15, 2006; 66(2): 1208 - 1217. [Abstract] [Full Text] [PDF]
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J. Koopmann, C. N. W. Rosenzweig, Z. Zhang, M. I. Canto, D. A. Brown, M. Hunter, C. Yeo, D. W. Chan, S. N. Breit, and M. Goggins Serum Markers in Patients with Resectable Pancreatic Adenocarcinoma: Macrophage Inhibitory Cytokine 1 versus CA19-9 Clin. Cancer Res., January 15, 2006; 12(2): 442 - 446. [Abstract] [Full Text] [PDF]
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 S. C. Garrett, K. M. Varney, D. J. Weber, and A. R. Bresnick S100A4, a Mediator of Metastasis J. Biol. Chem., January 13, 2006; 281(2): 677 - 680. [Full Text] [PDF]
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M. Gronborg, T. Z. Kristiansen, A. Iwahori, R. Chang, R. Reddy, N. Sato, H. Molina, O. N. Jensen, R. H. Hruban, M. G. Goggins, et al. Biomarker Discovery from Pancreatic Cancer Secretome Using a Differential Proteomic Approach Mol. Cell. Proteomics, January 1, 2006; 5(1): 157 - 171. [Abstract] [Full Text] [PDF]
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M. Buchholz, H. A. Kestler, A. Bauer, W. Bock, B. Rau, G. Leder, W. Kratzer, M. Bommer, A. Scarpa, M. K. Schilling, et al. Specialized DNA Arrays for the Differentiation of Pancreatic Tumors Clin. Cancer Res., November 15, 2005; 11(22): 8048 - 8054. [Abstract] [Full Text] [PDF]
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K. Ohuchida, K. Mizumoto, N. Ishikawa, K. Fujii, H. Konomi, E. Nagai, K. Yamaguchi, M. Tsuneyoshi, and M. Tanaka The Role of S100A6 in Pancreatic Cancer Development and Its Clinical Implication as a Diagnostic Marker and Therapeutic Target Clin. Cancer Res., November 1, 2005; 11(21): 7785 - 7793. [Abstract] [Full Text] [PDF]
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M. Goggins Molecular Markers of Early Pancreatic Cancer J. Clin. Oncol., July 10, 2005; 23(20): 4524 - 4531. [Abstract] [Full Text] [PDF]
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J. Qian, J. Niu, M. Li, P. J. Chiao, and M.-S. Tsao In vitro Modeling of Human Pancreatic Duct Epithelial Cell Transformation Defines Gene Expression Changes Induced by K-ras Oncogenic Activation in Pancreatic Carcinogenesis Cancer Res., June 15, 2005; 65(12): 5045 - 5053. [Abstract] [Full Text] [PDF]
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D. Segara, A. V. Biankin, J. G. Kench, C. C. Langusch, A. C. Dawson, D. A. Skalicky, D. C. Gotley, M. J. Coleman, R. L. Sutherland, and S. M. Henshall Expression of HOXB2, a Retinoic Acid Signaling Target in Pancreatic Cancer and Pancreatic Intraepithelial Neoplasia Clin. Cancer Res., May 1, 2005; 11(9): 3587 - 3596. [Abstract] [Full Text] [PDF]
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J. M. A. Moreira, G. Ohlsson, F. E. Rank, and J. E. Celis Down-regulation of the Tumor Suppressor Protein 14-3-3{sigma} Is a Sporadic Event in Cancer of the Breast Mol. Cell. Proteomics, April 1, 2005; 4(4): 555 - 569. [Abstract] [Full Text] [PDF]
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R. Chen, S. Pan, T. A. Brentnall, and R. Aebersold Proteomic Profiling of Pancreatic Cancer for Biomarker Discovery Mol. Cell. Proteomics, April 1, 2005; 4(4): 523 - 533. [Abstract] [Full Text] [PDF]
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N. B. Prasad, A. V. Biankin, N. Fukushima, A. Maitra, S. Dhara, A. G. Elkahloun, R. H. Hruban, M. Goggins, and S. D. Leach Gene Expression Profiles in Pancreatic Intraepithelial Neoplasia Reflect the Effects of Hedgehog Signaling on Pancreatic Ductal Epithelial Cells Cancer Res., March 1, 2005; 65(5): 1619 - 1626. [Abstract] [Full Text] [PDF]
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 P. B. Liton, X. Liu, W. D. Stamer, P. Challa, D. L. Epstein, and P. Gonzalez Specific Targeting of Gene Expression to a Subset of Human Trabecular Meshwork Cells Using the Chitinase 3-Like 1 Promoter Invest. Ophthalmol. Vis. Sci., January 1, 2005; 46(1): 183 - 190. [Abstract] [Full Text] [PDF]
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 S. E. Dowen, T. Crnogorac-Jurcevic, R. Gangeswaran, M. Hansen, J. J. Eloranta, V. Bhakta, T. A. Brentnall, J. Luttges, G. Kloppel, and N. R. Lemoine Expression of S100P and Its Novel Binding Partner S100PBPR in Early Pancreatic Cancer Am. J. Pathol., January 1, 2005; 166(1): 81 - 92. [Abstract] [Full Text] [PDF]
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J. Shen, M. D. Person, J. Zhu, J. L. Abbruzzese, and D. Li Protein Expression Profiles in Pancreatic Adenocarcinoma Compared with Normal Pancreatic Tissue and Tissue Affected by Pancreatitis as Detected by Two-Dimensional Gel Electrophoresis and Mass Spectrometry Cancer Res., December 15, 2004; 64(24): 9018 - 9026. [Abstract] [Full Text] [PDF]
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 P. Carter, L. Smith, and M. Ryan Identification and validation of cell surface antigens for antibody targeting in oncology Endocr. Relat. Cancer, December 1, 2004; 11(4): 659 - 687. [Abstract] [Full Text] [PDF]
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C. A. Borgono, I. P. Michael, and E. P. Diamandis Human Tissue Kallikreins: Physiologic Roles and Applications in Cancer Mol. Cancer Res., May 1, 2004; 2(5): 257 - 280. [Abstract] [Full Text] [PDF]
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