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Kellie J Archer, Valeria R Mas, Krystle David, Daniel G Maluf, Karen Bornstein, Robert A Fisher
In this study, we used the Affymetrix HG-U133A version 2.0 GeneChips to identify genes capable of distinguishing cirrhotic liver tissues with and without hepatocellular carcinoma by modeling the high-dimensional dataset using an L(1) penalized logistic regression model, with error estimated using N-fold cross-validation. Genes identified by gene expression microarray included those that have important links to cancer development and progression, including VAMP2, DPP4, CALR, CACNA1C, and EGR1. In addition, the selected molecular markers in the multigenic gene expression classifier were subsequently validated using reverse transcriptase-real time PCR, and an independently acquired gene expression microarray dataset was downloaded from Gene Expression Omnibus...
November 2009: Cancer Epidemiology, Biomarkers & Prevention
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