Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression

Abstract

Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available online SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human genome and better biocomputational techniques have substantially improved the assignment of differentially expressed SAGE "tags" to human genes. These improvements have provided us with an opportunity to re-evaluate global gene expression in pancreatic cancer using existing SAGE libraries. SAGE libraries generated from six pancreatic cancers were compared to SAGE libraries generated from 11 non-neoplastic tissues. Compared to normal tissue libraries, we identified 453 SAGE tags as differentially expressed in pancreatic cancer, including 395 that mapped to known genes and 58 "uncharacterized" tags. Of the 395 SAGE tags assigned to known genes, 223 were overexpressed in pancreatic cancer, and 172 were underexpressed. In order to map the 58 uncharacterized differentially expressed SAGE tags to genes, we used a newly developed resource called TAGmapper (http://tagmapper.ibioinformatics.org), to identify 16 additional differentially expressed genes. The differential expression of seven genes, involved in multiple cellular processes such as signal transduction (MIC-1), differentiation (DMBT1 and Neugrin), immune response (CD74), inflammation (CXCL2), cell cycle (CEB1) and enzymatic activity (Kallikrein 6), was confirmed by either immunohistochemical labeling of tissue microarrays (Kallikrein 6, CD74 and DMBT1) or by Neugrin, MIC1 and CXCL2). Of note, Neugrin was one of the genes whose previously uncharacterized SAGE tag was correctly assigned using TAGmapper, validating the utility of this program. Novel differentially expressed genes in a cancer type can be identified by revisiting updated and expanded SAGE databases. TAGmapper should prove to be a powerful tool for the discovery of novel tumor markers through assignment of uncharacterized SAGE tags.

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

“…Moreover, preclinical studies in B-cell lymphoma and multiple myeloma showed CD74 was a novel and promising therapeutic target because binding of anti-CD74 monoclonal antibodies became rapidly cointernalized (38 -40). Recently, serial analysis of gene expression showed CD74 overexpression in pancreatic cancer (16). In the present study, we confirmed that CD74 was positive in 52 cases (78%) and was overexpressed in cancer cells compared with the pancreatic duct in clinical cases.…”

“…Recently, pancreatic cancerspecific expression profiles using cDNA microarrays (11 -13), Affymetrix gene chip (14,15), and serial analysis of gene expression (16) have been used by many investigators. However, the molecular mechanisms of hepatic metastasis and perineural invasion in pancreatic cancer are far from clear.…”

Sperm-associated antigen 1 is expressed early in pancreatic tumorigenesis and promotes motility of cancer cells

“…We and others have recently undertaken such analyses of normal pancreas and pancreatic adenocarcinoma (Crnogorac-Jurcevic et al, 2003;Logsdon et al, 2003;Hustinx et al, 2004;Grutzmann et al, 2005) and our cDNA array data showed overexpression of spermassociated antigen 1 (SPAG1) in cancer cells (Missiaglia et al, 2004).…”

Expression of the Clustered NeuAcα2–3Galβ O-Glycan Determines the Cell Differentiation State of the Cells

“…The mortality rate of pancreatic cancer is so high in part because it usually does not produce symptoms until being metastasized and because there are no sensitive and specific tools to screen for early disease (33). Mucin-like protein DMBT1 binds to a variety of host proteins including IgA, C1q, lactoferrin, mucin 5B, and trefoil factor 2, which are all involved in innate immunity (34).…”