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Molecular Biology and Genetics |
Arizona Cancer Center [H. H., D. J. B., R. C., R. B. N., D. D. V. H.] and Department of Pathology [W. B., R. C., R. B. N.], University of Arizona, Tucson, Arizona 85724
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ABSTRACT |
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 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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75% of pancreatic tumors, whereas p16 is lost in 95% of all pancreatic cancers (7
, 8)
. DPC4, also known as SMAD4, is a tumor growth factor-ß signaling pathway member and is inactivated in 50% of all pancreatic cancers (9)
. Other tumor suppressor genes that are altered in pancreatic cancer include BRCA2 (10)
, ALK-5 (11)
, MKK4 (12)
, and STK11 (13)
. One oncogene that is commonly mutated in pancreatic cancer is K-ras. K-ras mutations have been found in 90% of the pancreatic cancers, with most of these being point mutations on codon 12 (7
, 14)
. Some other cancer-related genes such as Her-2/neu, COX-2, and VEGF have also been reported to be overexpressed in pancreatic cancer cells (15, 16, 17)
. Microsatellite instability in cancer cells usually suggests a defective mismatch repair system (18)
. Yamamoto et al. (19)
have reported recently that 26 of 100 sporadic pancreatic tumors showed microsatellite instability, indicating mutations in mismatch repair genes in those tumors. The identification and characterization of these cancer-related genes have increased our understanding of pancreatic cancer development, but unfortunately the treatment of pancreatic cancer has not advanced as much in the past 20 years. This is mainly attributable to the lack of early diagnosis and effective chemotherapeutic treatments. To increase the survival rate of pancreatic cancer patients, better tumor markers for diagnosis and new molecular targets for drug development are desperately needed.
Because the development and progression of pancreatic cancer is a very complicated process, we hypothesized that many other genes, as yet undiscovered, are potential tumor markers or drug targets. However, identifying these genes by conventional methods such as Northern blots, differential display, and serial analysis of gene expression has been either labor intensive or nonsystematic (20 , 21) . Proteomics have provided some promise for massive protein analysis, but techniques involved are still in the stage of early development (22) . In this study, we have used a high-density cDNA microarray technique to assess the gene expression levels in neoplastic versus normal pancreatic cells. This DNA microarray technique allows simultaneous comparison of a large number of genes in two samples in a quantitative and expeditious way (21) . We used a cDNA microarray slide containing 5289 unique cDNA sequences and compared the mRNA levels of nine pancreatic cell lines with that of normal pancreas. We characterized gene-expression profiles that molecularly discriminate pancreatic cancer cell lines from normal pancreas cells. Moreover, we identified genes that may be involved in pancreatic tumorigenesis as well as genes that are potential clinical biomarkers that may lead to an improved early diagnosis for this disease. Several of these genes may also constitute potential novel therapeutic targets.
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MATERIALS AND METHODS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Microarray Sample Preparation and Hybridization.
cDNA microarray slides used in this study were fabricated in the microarray core facilities at the Arizona Cancer Center (24)
. Briefly, each slide has 5760 spots divided into four blocks, with each containing eight identical ice plant genes from Mesembryanthemum crystallinum and 23 different housekeeping genes as references for data normalization. Each slide had 5289 unique human cDNA sequences.
Poly(A)+ RNA was directly isolated from cell pellets using the FastTrack 2.0 kit (Invitrogen, Carlsbad, CA), following the instruction manual provided by the manufacturer. Normal pancreas poly(A)+ RNA was isolated from total RNA, which was purchased from Clontech Laboratories (Palo Alto, CA) using the Oligotex Direct mRNA kit (Qiagen, Inc., Valencia, CA). This "normal pancreata" consisted of a pool of two tissue specimens donated by two male Caucasians 18 and 40 years of age. Labeling and purification of cDNA probes were carried out using the MICROMAX direct cDNA microarray system (NEN Life Science Products, Boston, MA). Two to 4 µg of the poly(A)+ RNA samples were used for each labeling. Probes for each pancreatic cell line were labeled with Cy5,3 and probes for HeLa cells were labeled with Cy3. For HeLa cell versus normal pancreas hybridization, a normal pancreas sample was labeled with Cy3, and a HeLa cell sample was labeled with Cy5. Purified cDNA probes were dried and dissolved in 15 µl of hybridization buffer (included in the MICROMAX direct cDNA microarray system kit). The probes were then denatured by heating at 95°C for 2 min and applied to the array area of a predenatured microarray slide. The microarray slide was covered with a 22 x 22-cm slide coverslip and incubated in a HybChamber (GeneMachines, San Carlos, CA) at 62°C for overnight. On the second day, the slide was washed in 0.5x SSC, 0.01% SDS for 5 min; 0.06x SSC, 0.01% SDS for 5 min; and 0.06x SSC for 2 min. Finally, the slide was dried by spinning at 500 x g for 1 min and scanned in a dual-laser (635 nm for red fluorescent Cy5 and 532 nm for green fluorescent Cy3) microarray scanner (GenePix 4000; Axon Instruments, Foster City, CA).
Data Normalization and Analysis.
Fluorescence intensities for both dyes (Cy3 and Cy5) and local background subtracted values for individual spots were obtained using the GenePix 4000 microarray scanner and accompanying software (Axon Instruments). The data were imported into Microsoft Excel spreadsheets for analysis. Defective spots, ones that are substandard on the scanned image or have negative background subtracted values, were first excluded. To minimize the effects of measurement variations introduced by artificial sources during experiments, we only included the spots that had significant signals in both channels. The determination of this significance is based on signal intensities of nonhomologous ice plant genes. Generally, if the signal intensity of a spot is less than the average of ice plant spots, we considered the signal as nonsignificant. In this analysis, we empirically determined the significance cutoff for signal:background ratio as 1.4. In other words, a spot was excluded from further analysis if it had a signal:background ratio of <1.4 in both channels. For each spot, the median of ratios (the median of the pixel-by-pixel ratios of pixel intensities that have the median background intensity subtracted) was used in subsequent analysis. Spots representing housekeeping genes were used to normalize the entire slide so that all slides could be compared directly. For each pancreatic cell line, at least two hybridizations were carried out. The average of median ratios from replicates was calculated for each spot.
To ensure that the exact same reference samples were used for all necessary experiments, we used a HeLa cell mRNA pool as our universal reference for all microarray hybridizations. In other words, the Cy5-labeled probes for each pancreatic cell line were mixed with Cy3-labeled probes for HeLa cells and hybridized to one slide to obtain the ratio of pancreatic cell line versus HeLa cell. On the other hand, Cy5-labeled HeLa cell probes were mixed with Cy3-labeled normal pancreas probes and hybridized to a slide to obtain the ratio of HeLa cell versus normal pancreas. Each slide was normalized by the housekeeping genes; therefore, errors caused by hybridization differences from slide to slide are minimized. The two ratios were then multiplied to generate the ratio of pancreatic cancer cell line versus normal pancreas. Finally, the ratios were taken as log2 transformation, and the SDs of the mean were then calculated from these log2 ratios for each cell line. We used 2.0 SD as our cutoff for the determination of expression outliners (see "Results").
RT-PCR.
Two µg of total RNA isolated from pancreatic cancer cell pellets or frozen pancreatic tumor tissues were used for reverse transcriptase reactions (20 µl in total volume), which were carried out using the Omniscript RT kit (Qiagen, Inc.), following the manufacturer’s protocol. The PCRs were then carried out by mixing 2 µl of reverse transcriptase reaction mixture, 5 µl of 10x PCR buffer containing 15 mM Mg2+, 1 µl of 10 mM deoxynucleotide triphosphate mixture, 2.5 µl of 5 µM PCR primer pair for specific gene, 1 µl of ß-actin primer pair, 1 µl of ß-actin competimers (Ambion, Inc., Austin, TX), 37 µl of H2O, and 0.5 µl of 5 units/µl Taq polymerase (Promega Corp., Madison, WI). The amplification cycle (94°C for 30 s; 56°C for 45 s; and 72°C for 1 min) was repeated 29 times. PCR primers for individual genes were designed to generate a DNA fragment 600 bp in length (if the mRNA itself is less than 600 bases, PCR products were generated in maximal length) using the Primer3 program (25)
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Northern Blot.
RNA electrophoresis and transferring to Zeta-Probe GT membranes (Bio-Rad, Hercules, CA) were performed as described previously (24)
. 32P-labeled probes were made from the agarose gel-purified RT-PCR products of each gene using the RadPrime DNA Labeling System (Invitrogen). The probe hybridization and stripping buffers and conditions were as provided by the membrane manufacturer. Hybridized membranes were exposed to a PhosporImager (Molecular Dynamics, Sunnyvale, CA), and signals were quantified using the ImageQuant software.
Pancreatic Tumor Tissue Array Construction and Immunohistochemistry.
Morphologically representative areas of 42 archival cases of pancreatic tumors, 35 of which are documented ductal adenocarcinomas, from the University of Arizona Health Sciences Center and the Tucson Veterans Administration Medical Center, were selected from formalin-fixed tissue samples embedded in paraffin blocks. Two 1.5-mm-diameter cores/case were re-embedded in a tissue microarray using a tissue arrayer (Beecher Instruments, Silver Spring, MD) according to a method described previously (26)
. Serial sections of the paraffin-embedded pancreatic tissue array were deparaffinized and reacted with primary antibodies specific for c-Myc (clone 9E10.3; NeoMarkers, Fremont, CA) or Rad51 (Oncogene, Boston, MA). Before antibody incubation, the slides were processed for antigen retrieval. This consisted of microwaving the slides in citrate buffer (0.1 M, pH 6.0) in a pressure cooker for 25 min and then were left to cool. The slides were incubated with the antibody for 1 h. Biotinylated antimouse/antirabbit secondary antibodies were applied, followed by streptavidin-peroxidase complex (DAKO, Carpinteria, CA). Colored products were produced using the diaminobenzidine substrate. Staining reactions were scored as diffuse or focal and were graded (from 0, negative to 4+, intensely positive) for both neoplasm and background stroma.
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RESULTS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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95% confidence interval. All cell lines except SU.86.86 had about 30–50 genes that survived this cutoff at either end (overexpression or underexpression). SU.86.86 had 10 genes that survived this cutoff. We then examined the expression levels of individual outliers across the nine pancreatic cell lines and chose those that exhibited a significant expression change (2.0 SD from the mean) in at least three of the nine cell lines as our "true" differentially expressed genes. There were a total of 58 genes that met those analysis criteria for differential expression (30 genes for overexpression and 28 genes for underexpression). They accounted for 1.1% of the 5289 unique cDNA clones included in the microarrays. These genes are listed in Table 1
(overexpressed genes) and Table 2
(underexpressed genes). From a drug design perspective, the overexpressed genes represent greater potential as targets for the development of small molecule inhibitors, whereas the underexpressed genes are possible candidates for gene therapy or other functional replacement treatment. In this study, we focused on the validation of overexpressed genes.
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. Many of these genes, such as annexin I (27
, 28)
, c-Myc (v-myc avian myelocytomatosis viral oncogene homologue; Ref. 29
), uPAR (30)
, HMG protein isoforms I and Y (31
, 32)
, PCNA (33)
, and nonspecific cross-reacting antigen (34)
, are known to be up-regulated in cancers. Genes that have been reported previously as being overexpressed in pancreatic cancer are noted in Table 1
. There were also genes that are not reported previously, including prion protein, myoferlin, and primase polypeptide 1. However, the identification of cytochrome c and Rad51 as up-regulated in pancreatic cancer cells is unexpected because cytochrome c is a key proapoptotic molecule in mitochondria (35)
, and Rad51 is involved in DNA double-strand break repair (36)
. Other pancreatic cancer-associated genes reported previously showed some evidence of up-regulation in our microarray experiments but failed to meet our strict criterion of 2.0 SD of the mean in at least three cell lines.
Table 2
lists the genes that were down-regulated in pancreatic cancer cells. A few of these have been reported previously to be down-regulated in cancers. For instance, down-regulation of gelsolin was found to correlate with progression to breast carcinoma (37)
, lack of glutathione S-transferase 
is considered to be related to increased risk of various cancers (38)
, and the death-associated proteins, a new class of proapoptotic molecules, have been shown to be tumor suppressive (39, 40, 41)
. Many of these genes, however, were either not considered previously to be cancer-associated or not functionally characterized.
RT-PCR and Northern Blot Validation of Overexpressed Genes.
To validate the microarray data, we further investigated the mRNA levels of the genes that exhibited up-regulated expression on cDNA microarray using quantitative RT-PCR and Northern blots. Among the 30 up-regulated genes, 25 had at least some known functions and were selected for RT-PCR and Northern blot analysis. Although the expression ratios calculated from microarray data varied in levels, most of the 25 genes explored by RT-PCR and Northern blots showed overexpression in all nine pancreatic cancer cell lines (Table 3)
. A few genes, however, such as NGAL and Rho-GDI, exhibited very dramatic expression variations across the cell lines. NGAL was up-regulated by >27-fold in three cell lines (AsPC-1, HPAF II, and SU.86.86). Its expression in MIA PaCa-2 and Mutj was down-regulated to 0.7 and 0.3 of normal pancreas, respectively (Table 3)
. Rho-GDI was overexpressed by 6–8-fold in BxPC-3, Capan-1, and SU.86.86 cell lines, whereas in AsPC-1, MIA PaCa-2, Mutj, and PANC-1, it was down-regulated to 0.2–0.7-fold of normal pancreas (Table 3)
.
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and 2
, RT-PCR and Northern results demonstrate an increase in expression for most genes in all nine cell lines. Quantitation of the RT-PCR and Northern blots showed that the fold of increase was in the same range as expected from microarray data with the exception of uPAR in the MIA PaCa-2 cell line (quantitation data not shown). The microarray data predicted that uPAR expression would be slightly lower in MIA PaCa-2 cells than in normal pancreas (expression ratio, 0.9; Table 3
). Both RT-PCR and Northern blot analysis, however, showed increased expression in MIA PaCa-2 cells (4.3-fold in RT-PCR and 2.4-fold in Northern blot). Intriguingly, the expression patterns of NGAL and Rho-GDI are correlated very well with the microarray data. In both RT-PCR (Fig. 1)
and Northern blots (Fig. 2)
, NGAL is highly up-regulated in AsPC-1, Capan-1, CFPAC-1, HPAF II, and Su.86.86 but not in Mutj and MIA PaCa-2. Quantitation of the Northern blots showed a slight decrease of NGAL expression in both Mutj and MIA PaCa-2 cell lines (quantitation data not shown). The expression pattern of Rho-GDI shown by RT-PCR and Northern blot also matches the pattern shown by microarray analysis with up-regulation in BxPC-3, Capan-1, and SU.86.86 and down-regulation in AsPC-1, MIA PaCa-2, Mutj, and PANC-1 (Figs. 1
and 2
; quantitation of RT-PCR and Northern blot are not shown). Noticeably, the RT-PCR and Northern blot agree for most of the genes.
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shows the RNA levels of c-Myc and Rad51 in eight pancreatic tumor samples. c-Myc is highly overexpressed in patient samples 6 and 8 and moderately overexpressed in patient samples 4 and 5 (Fig. 3
, upper panel; quantitation not shown). Therefore, the overall overexpression rate for the c-Myc gene in tumor tissues is 50%. Rad51 was overexpressed in three tissue samples (Fig. 3
, patients 3, 4, and 8), one of which (patient 4) had >11-fold up-regulation (Fig. 3
, lower panel; quantitation not shown).
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. Fig. 4, B and C
, showed some examples of positive staining of c-Myc and Rad51. The overall c-Myc-positive staining (tumor score is at least 1+ over background stroma score; see "Materials and Methods") frequency is 71.8%. About 15.6% of the tumors showed very strong c-Myc staining (scored 3+ or over). Rad51 has a positive staining frequency of 74.2%, with 12.9% of tumors showing very strong staining (scored 3+ or more). These results were consistent with the RNA expression data shown by RT-PCR (Fig. 3)
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DISCUSSION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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. The first major group of genes was transcription or translation-related genes and included transcription factors such as c-Myc, HMG protein isoforms I and Y, fos-like antigen-1 (31)
, and transcriptional or translational machinery-related genes. The overexpression of these genes was not unexpected because they are involved in the regulation of cell growth and proliferation. Cell adhesion and migration-related genes were another major group of genes overexpressed in pancreatic cancer cells. This group includes uPAR (42) and transmembrane protein Fn14 (43) . Two calcium-binding proteins, S100A11 (calgizzatin) and annexin I, were also highly expressed in pancreatic cancer cells. Both genes have been reported previously to be up-regulated in tumor cells (44, 45, 46) .
Other groups of genes that were found up-regulated and have known functions include DNA replication and mitosis-related genes such as primase 1, PCNA, STK15, CDC28 protein kinase 2, and DNA repair gene Rad51. STK15 encodes a centrosome-associated kinase and is thought to be important for centrosome duplication and distribution (47) . CDC28 protein kinase 2 (cyclin-dependent kinase subunit 2) binds to cyclin-dependent kinases, but its precise function is unclear. Recently, its expression has been linked to human lymphoid cell proliferation (48) . The identification of Rad51 is rather surprising because one would not expect a DNA repair gene to be overexpressed in cancer cells. It is possible, however, that deregulated or increased DNA repair results in genomic instability and therefore tumorigenesis. In fact, Maacke et al. (49 , 50) reported that Rad51 is overexpressed in human pancreatic cancer, and the overexpression of wild-type Rad51 correlates with histological grading of invasive ductal breast cancer.
RT-PR and tissue microarray immunohistochemistry studies in clinical tumor samples confirmed that c-Myc and Rad51 were overexpressed in a majority of pancreatic cancers (Figs. 3
and 4
). These findings were important because only if the genes are overexpressed in clinical samples and at the protein level are they potential targets for screening and therapeutic development. These results also indicate that findings in cell lines can be verified in tissue samples, and gene expression at the RNA level can be translated to expression at the protein level. Tissue microarray is a recently developed technology that enables the simultaneous examination of multiple histological sections at one time as compared with one section at a time for the conventional method (26)
. In this study, we constructed a pancreatic tumor tissue microarray that contained 35 different adenocarcinoma tissue samples, each of which having two representative 1.5-mm disks from the different areas of the same paraffin-embedded section. Immunohistochemical studies using the whole tumor sections demonstrated that the two 1.5-mm disks were highly representative of the tissues from which they originated (data not shown). We are now using the same pancreatic tissue microarray to verify the overexpression of other genes manifested in the cDNA microarray study.
Cancer cells from different tumor types share many features at both the cellular and the molecular levels. However, because of their nature of increased genetic instability, human cancers are highly heterogeneous, even within a single tumor. To identify genes that are most consistently and frequently overexpressed during pancreatic tumorigenesis, we used stringent criteria in our microarray data analysis as described above. Although we may have missed some genes, we believe that the genes recorded in Table 1
represent a list of genes potentially important to the tumorigenesis process in the pancreas. Within the set of genes we identified, some may represent potential tumor markers or drug targets. At present, we are evaluating some of these genes as potential candidates for targeted drug development.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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1 Supported in part by a grant from the National Foundation for Cancer Research and the Arizona Cancer Center. D. V. H. is a fellow of National Foundation for Cancer Research. 
2 To whom requests for reprints should be addressed, at Arizona Cancer Center, University of Arizona, P. O. Box 245024, Tucson, AZ 85724-5024. Phone: (520) 626-7925; Fax: (520) 626-6898; E-mail: dvonhoff{at}azcc.arizona.edu
3 The abbreviations used are: Cy5, cyanine 5; Cy3, cyanine 3; RT-PCR, reverse transcription-PCR; uPAR, urokinase-type plasminogen activator receptor; NGAL, neutrophil gelatinase-associated lipocalin; Rho-GDI, Rho GDP dissociation inhibitor-ß; HMG, high mobility group; PCNA, proliferating cell nuclear antigen; STK15, serine/threonine kinase; NCA, nonspecific cross-reacting antigen.
Received 9/21/01. Accepted 3/ 7/02.
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C. Jakupoglu, G. K. H. Przemeck, M. Schneider, S. G. Moreno, N. Mayr, A. K. Hatzopoulos, M. H. de Angelis, W. Wurst, G. W. Bornkamm, M. Brielmeier, et al. Cytoplasmic Thioredoxin Reductase Is Essential for Embryogenesis but Dispensable for Cardiac Development Mol. Cell. Biol., March 1, 2005; 25(5): 1980 - 1988. [Abstract] [Full Text] [PDF]
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 N. L. Tran, W. S. McDonough, B. A. Savitch, T. F. Sawyer, J. A. Winkles, and M. E. Berens The Tumor Necrosis Factor-like Weak Inducer of Apoptosis (TWEAK)-Fibroblast Growth Factor-inducible 14 (Fn14) Signaling System Regulates Glioma Cell Survival via NF{kappa}B Pathway Activation and BCL-XL/BCL-W Expression J. Biol. Chem., February 4, 2005; 280(5): 3483 - 3492. [Abstract] [Full Text] [PDF]
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J.-M. Kim, H.-Y. Sohn, S. Y. Yoon, J.-H. Oh, J. O. Yang, J. H. Kim, K. S. Song, S.-M. Rho, H. S. Yoo, Y. S. Kim, et al. Identification of Gastric Cancer-Related Genes Using a cDNA Microarray Containing Novel Expressed Sequence Tags Expressed in Gastric Cancer Cells Clin. Cancer Res., January 15, 2005; 11(2): 473 - 482. [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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S. Aguilar, J. M. Corominas, N. Malats, J. A. Pereira, M. Dufresne, F. X. Real, and P. Navarro Tissue Plasminogen Activator in Murine Exocrine Pancreas Cancer: Selective Expression in Ductal Tumors and Contribution to Cancer Progression Am. J. Pathol., October 1, 2004; 165(4): 1129 - 1139. [Abstract] [Full Text] [PDF]
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S. Rojanala, H. Han, R. M. Munoz, W. Browne, R. Nagle, D. D. Von Hoff, and D. J. Bearss The mitotic serine threonine kinase, Aurora-2, is a potential target for drug development in human pancreatic cancer Mol. Cancer Ther., April 1, 2004; 3(4): 451 - 457. [Abstract] [Full Text] [PDF]
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J. Koopmann, P. Buckhaults, D. A. Brown, M. L. Zahurak, N. Sato, N. Fukushima, L. J. Sokoll, D. W. Chan, C. J. Yeo, R. H. Hruban, et al. Serum Macrophage Inhibitory Cytokine 1 as a Marker of Pancreatic and Other Periampullary Cancers Clin. Cancer Res., April 1, 2004; 10(7): 2386 - 2392. [Abstract] [Full Text] [PDF]
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 J. Koopmann, N. S. Fedarko, A. Jain, A. Maitra, C. Iacobuzio-Donahue, A. Rahman, R. H. Hruban, C. J. Yeo, and M. Goggins Evaluation of Osteopontin as Biomarker for Pancreatic Adenocarcinoma Cancer Epidemiol. Biomarkers Prev., March 1, 2004; 13(3): 487 - 491. [Abstract] [Full Text]
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N. Sato, N. Fukushima, A. Maitra, C. A. Iacobuzio-Donahue, N. T. van Heek, J. L. Cameron, C. J. Yeo, R. H. Hruban, and M. Goggins Gene Expression Profiling Identifies Genes Associated with Invasive Intraductal Papillary Mucinous Neoplasms of the Pancreas Am. J. Pathol., March 1, 2004; 164(3): 903 - 914. [Abstract] [Full Text] [PDF]
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C. A. Iacobuzio-Donahue, R. Ashfaq, A. Maitra, N. V. Adsay, G. L. Shen-Ong, K. Berg, M. A. Hollingsworth, J. L. Cameron, C. J. Yeo, S. E. Kern, et al. Highly Expressed Genes in Pancreatic Ductal Adenocarcinomas: A Comprehensive Characterization and Comparison of the Transcription Profiles Obtained from Three Major Technologies Cancer Res., December 15, 2003; 63(24): 8614 - 8622. [Abstract] [Full Text] [PDF]
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J. P. MacKeigan, C. M. Clements, J. D. Lich, R. M. Pope, Y. Hod, and J. P-Y. Ting Proteomic Profiling Drug-Induced Apoptosis in Non-Small Cell Lung Carcinoma: Identification of RS/DJ-1 and RhoGDI{alpha} Cancer Res., October 15, 2003; 63(20): 6928 - 6934. [Abstract] [Full Text] [PDF]
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N. Sato, A. Maitra, N. Fukushima, N. T. van Heek, H. Matsubayashi, C. A. Iacobuzio-Donahue, C. Rosty, and M. Goggins Frequent Hypomethylation of Multiple Genes Overexpressed in Pancreatic Ductal Adenocarcinoma Cancer Res., July 15, 2003; 63(14): 4158 - 4166. [Abstract] [Full Text] [PDF]
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S. L. Warner, D. J. Bearss, H. Han, and D. D. Von Hoff Targeting Aurora-2 Kinase in Cancer Mol. Cancer Ther., June 1, 2003; 2(6): 589 - 595. [Abstract] [Full Text] [PDF]
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S. P. Linke, S. Sengupta, N. Khabie, B. A. Jeffries, S. Buchhop, S. Miska, W. Henning, R. Pedeux, X. W. Wang, L. J. Hofseth, et al. p53 Interacts with hRAD51 and hRAD54, and Directly Modulates Homologous Recombination Cancer Res., May 15, 2003; 63(10): 2596 - 2605. [Abstract] [Full Text] [PDF]
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C. D. Logsdon, D. M. Simeone, C. Binkley, T. Arumugam, J. K. Greenson, T. J. Giordano, D. E. Misek, and S. Hanash Molecular Profiling of Pancreatic Adenocarcinoma and Chronic Pancreatitis Identifies Multiple Genes Differentially Regulated in Pancreatic Cancer Cancer Res., May 15, 2003; 63(10): 2649 - 2657. [Abstract] [Full Text] [PDF]
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C. A. Iacobuzio-Donahue, A. Maitra, M. Olsen, A. W. Lowe, N. T. Van Heek, C. Rosty, K. Walter, N. Sato, A. Parker, R. Ashfaq, et al. Exploration of Global Gene Expression Patterns in Pancreatic Adenocarcinoma Using cDNA Microarrays Am. J. Pathol., April 1, 2003; 162(4): 1151 - 1162. [Abstract] [Full Text] [PDF]
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H. Vankayalapati, D. J. Bearss, J. W. Saldanha, R. M. Munoz, S. Rojanala, D. D. Von Hoff, and D. Mahadevan Targeting Aurora2 Kinase in Oncogenesis: A Structural Bioinformatics Approach to Target Validation and Rational Drug Design Mol. Cancer Ther., March 1, 2003; 2(3): 283 - 294. [Abstract] [Full Text] [PDF]
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 Y. Li and F. H. Sarkar Gene Expression Profiles of Genistein-Treated PC3 Prostate Cancer Cells J. Nutr., December 1, 2002; 132(12): 3623 - 3631. [Abstract] [Full Text] [PDF]
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