Showing papers by "Diane M. Simeone published in 2003"

Molecular Profiling of Pancreatic Adenocarcinoma and Chronic Pancreatitis Identifies Multiple Genes Differentially Regulated in Pancreatic Cancer

Abstract: The molecular basis of pancreatic cancer is not understood. Previous attempts to determine the specific genes expressed in pancreatic cancer have been hampered by similarities between adenocarcinoma and chronic pancreatitis. In the current study, microarrays (Affymetrix) were used to profile gene expression in pancreatic adenocarcinoma (10), pancreatic cancer cell lines (7), chronic pancreatitis (5), and normal pancreas (5). Molecular profiling indicated a large number of genes differentially expressed between pancreatic cancer and normal pancreas but many fewer differences between pancreatic cancer and chronic pancreatitis, likely because of the shared stromal influences in the two diseases. To specifically identify genes expressed in neoplastic epithelium, we selected genes more highly expressed (>2-fold, p < 0.01) in adenocarcinoma compared with both normal pancreas and chronic pancreatitis and which were also highly expressed in pancreatic cancer cell lines. This strategy yielded 158 genes, of which 124 were not previously associated with pancreatic cancer. Quantitative-reverse transcription-PCR for two molecules, S100P and 14-3-3sigma, validated the microarray data. Support for the success of the neoplastic cell gene expression identification strategy was obtained by immunocytochemical localization of four representative genes, 14-3-3sigma, S100P, S100A6, and beta4 integrin, to neoplastic cells in pancreatic tumors. Thus, comparisons between pancreatic adenocarcinoma, pancreatic cancer cell lines, normal pancreas, and chronic pancreatitis have identified genes that are selectively expressed in the neoplastic epithelium of pancreatic adenocarcinoma. These data provide new insights into the molecular pathology of pancreatic cancer that may be useful for detection, diagnosis, and treatment.

Nestin-lineage cells contribute to the microvasculature but not endocrine cells of the islet.

Abstract: To clarify the lineage relationship between cells that express the neural stem cell marker nestin and endocrine cells of the pancreas, we analyzed offspring of a cross between mice carrying a nestin promoter/enhancer-driven cre-recombinase (Nestin-cre) and C57BL/6J-Gtrosa26(tm1Sor) mice that carry a loxP-disrupted beta-galactosidase gene (Rosa26). In nestin-cre(+/tg);R26R(loxP/+) embryos, cre-recombinase was detected in association with nestin-positive cells in the pancreatic mesenchyme with some of the nestin-positive cells lining vascular channels. In postnatal mice, pancreatic beta-galactosidase expression was restricted to vascular endothelial cells of the islet and a subset of cells in the muscularis of arteries in a distribution identical to endogenous nestin expression. Ex vivo explants of mouse pancreatic ducts grew dense cultures that costained for nestin and beta-galactosidase, demonstrating recombination in vitro. The cultures could be differentiated into complex stereotypic structures that contain nestin- and insulin-expressing cells. Nestin-cre(+/tg);R26R(loxP/+)-derived duct cultures showed that insulin-positive cells were negative for beta-galactosidase. These results indicate that both in vivo and in vitro pancreatic endocrine cells arise independently of nestin-positive precursors. The apparent vascular nature of the nestin-positive cell population and the close association with endocrine cells suggest that nestin-positive cells play an important role in the growth and maintenance of the islet.

Accurate molecular classification of human cancers based on gene expression using a simple classifier with a pathological tree-based framework.

Abstract: Recent studies suggest accurate prediction of tissue of origin for human cancers can be achieved by applying sophisticated statistical learning procedures to gene expression data obtained from DNA microarrays. We have pursued the hypothesis that a more straightforward and equally accurate strategy for classifying human tumors is to use a simple algorithm that considers gene expression levels within a tree-based framework that encodes limited information about pathology and tissue ontogeny. By considering gene expression data within this framework, we found only a small number of genes were required to achieve a relatively high accuracy level in tumor classification. Using as few as 45 genes we were able to classify 157 of 190 human malignant tumors correctly, which is comparable to previous results obtained with sophisticated classifiers using thousands of genes. Our simple classifier accurately predicted the origin of metastatic tumors even when the classifier was trained using only primary tumors, and the classifier produced accurate predictions when trained and tested on expression data from different labs, and from different microarray platforms. Our findings suggest that accurate and robust cancer diagnosis from gene expression profiles can be achieved by mimicking the classification strategies routinely used by surgical pathologists.

Molecular profiling of pancreatic adenocarcinoma and chronic pancreatitis identifies multiple genes differentially regulated in pancreatic cancer (Cancer Research (2003) (2649-2657))

Abstract: The molecular basis of pancreatic cancer is not understood. Previous attempts to determine the specific genes expressed in pancreatic cancer have been hampered by similarities between adenocarcinoma and chronic pancreatitis. In the current study, microarrays (Affymetrix) were used to profile gene expression in pancreatic adenocarcinoma (10), pancreatic cancer cell lines (7), chronic pancreatitis (5), and normal pancreas (5). Molecular profiling indicated a large number of genes differentially expressed between pancreatic cancer and normal pancreas but many fewer differences between pancreatic cancer and chronic pancreatitis, likely because of the shared stromal influences in the two diseases. To specifically identify genes expressed in neoplastic epithelium, we selected genes more highly expressed (>2-fold, p < 0.01) in adenocarcinoma compared with both normal pancreas and chronic pancreatitis and which were also highly expressed in pancreatic cancer cell lines. This strategy yielded 158 genes, of which 124 were not previously associated with pancreatic cancer. Quantitative-reverse transcription-PCR for two molecules, S100P and 14-3-3sigma, validated the microarray data. Support for the success of the neoplastic cell gene expression identification strategy was obtained by immunocytochemical localization of four representative genes, 14-3-3sigma, S100P, S100A6, and beta4 integrin, to neoplastic cells in pancreatic tumors. Thus, comparisons between pancreatic adenocarcinoma, pancreatic cancer cell lines, normal pancreas, and chronic pancreatitis have identified genes that are selectively expressed in the neoplastic epithelium of pancreatic adenocarcinoma. These data provide new insights into the molecular pathology of pancreatic cancer that may be useful for detection, diagnosis, and treatment.