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Prediction Model for the Cellular Immortalization and Transformation Potentials of Cell Substrates  

Lee, Min-Su (Department of Computer Science and Engineering, Ewha Womans University)
Matthews Clayton A. (Human Genome Research Institute and Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine)
Chae Min-Ju (Human Genome Research Institute and Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine)
Choi, Jung-Yun (Biologics Headquater, Korea Food and Drug Administration)
Sohn Yeo-Won (Biologics Headquater, Korea Food and Drug Administration)
Kim, Min-Jung (Laboratory of Radiation Experimental Therapeutics, Korea Institute of Radiological & Medical Sciences)
Lee, Su-Jae (Laboratory of Radiation Experimental Therapeutics, Korea Institute of Radiological & Medical Sciences)
Park, Woong-Yang (Human Genome Research Institute and Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine)
Publication Information
Genomics & Informatics / v.4, no.4, 2006 , pp. 161-166 More about this Journal
Abstract
The establishment of DNA microarray technology has enabled high-throughput analysis and molecular profiling of various types of cancers. By using the gene expression data from microarray analysis we are able to investigate diagnostic applications at the molecular level. The most important step in the application of microarray technology to cancer diagnostics is the selection of specific markers from gene expression profiles. In order to select markers of Immortalization and transformation we used c-myc and $H-ras^{V12}$ oncogene-transfected NIH3T3 cells as our model system. We have identified 8751 differentially expressed genes in the immortalization/transformation model by multivariate permutation F-test (95% confidence, FDR<0.01). Using the support vector machine algorithm, we selected 13 discriminative genes which could be used to predict immortalization and transformation with perfect accuracy. We assayed $H-ras^{V12}$-transfected 'transformed' cells to validate our immortalization/transformation dassification system. The selected molecular markers generated valuable additional information for tumor diagnosis, prognosis and therapy development.
Keywords
microarray; NIH3T3; immortalization; transformation; c-myc; $H-ras^{V12}$; Prediction model; SVM;
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