alexa Exploration of global gene expression patterns in pancreatic adenocarcinoma using cDNA microarrays.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): IacobuzioDonahue CA, Maitra A, Olsen M, Lowe AW, van Heek NT,

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Abstract Pancreatic cancer is the fifth leading cause of cancer death in the United States. We used cDNA microarrays to analyze global gene expression patterns in 14 pancreatic cancer cell lines, 17 resected infiltrating pancreatic cancer tissues, and 5 samples of normal pancreas to identify genes that are differentially expressed in pancreatic cancer. We found more than 400 cDNAs corresponding to genes that were differentially expressed in the pancreatic cancer tissues and cell lines as compared to normal pancreas. These genes that tended to be expressed at higher levels in pancreatic cancers were associated with a variety of processes, including cell-cell and cell-matrix interactions, cytoskeletal remodeling, proteolytic activity, and Ca(++) homeostasis. Two prominent clusters of genes were related to the high rates of cellular proliferation in pancreatic cancer cell lines and the host desmoplastic response in the resected pancreatic cancer tissues. Of 149 genes identified as more highly expressed in the pancreatic cancers compared with normal pancreas, 103 genes have not been previously reported in association with pancreatic cancer. The expression patterns of 14 of these highly expressed genes were validated by either immunohistochemistry or reverse transcriptase-polymerase chain reaction as being expressed in pancreatic cancer. The overexpression of one gene in particular, 14-3-3 sigma, was found to be associated with aberrant hypomethylation in the majority of pancreatic cancers analyzed. The genes and expressed sequence tags presented in this study provide clues to the pathobiology of pancreatic cancer and implicate a large number of potentially new molecular markers for the detection and treatment of pancreatic cancer.
This article was published in Am J Pathol and referenced in Journal of Proteomics & Bioinformatics

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