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Ebook Cancer systems biology: Part 2

(BQ) Part 2 book “Cancer systems biology” has contents: Cancer gene prediction using a network approach, cancer genomics to cancer biology, tumors and their microenvironments, gene set and pathway-based analysis for cancer omics, and other contents. | Chapter 11 Cancer Gene Prediction Using a Network Approach Xuebing Wu and Shao Li Contents 11.1 Introduction 11.2 Molecular Networks and Human Diseases 11.3 Network Approach for Cancer Gene Prediction 11.3.1 Prioritize by Network Proximity 11.3.1.1 Proximity to Known Disease Genes of the Same Disease 11.3.1.2 Proximity of Candidate Gene Pairs: Enabling de Novo Discovery 11.3.2 Phenotype Similarity-Assisted Methods 11.3.2.1 Calculating and Validating Phenotypic Similarity 11.3.2.2 Modeling with Molecular Network and Phenotype Similarity 11.3.3 Prioritize by Network Centrality 11.3.3.1 Centrality in a Context-Specific Gene Network 11.3.3.2 Centrality in a Genomic-Phenomic Network 11.3.4 Other Methods 11.4 Discussion Acknowledgments References 191 192 195 196 196 200 200 200 202 205 205 205 206 207 208 208 11.1╇ Introduction Cancer is a genetic disease (Vogelstein and Kinzler 2004). Decades of research in molecular genetics have identified a number of important genes responsible for the genesis of various types of cancer (Futreal et al. 2004) and drugs targeting these mutated cancer genes have brought dramatic therapeutic advances and substantially improved and prolonged the lives of cancer patients (Huang and Harari 1999). However, cancer is extremely complex and heterogeneous. It has been suggested that 5% to 10% of the human genes probably contribute to oncogenesis (Strausberg, Simpson, and Wooster 2003), while current experimentally validated cancer genes only cover 1% of human genome (Futreal et al. 2004), 191 192    ◾    Xuebing Wu and Shao Li suggesting that there are still hundreds or even thousands of cancer genes that remain to be identified. For example, in breast cancer, known susceptibility genes, including BRCA1 (Miki et al. 1994) and BRCA2 (Wooster et al. 1995), can only explain less than 5% of the total breast cancer incidence and less than 25% of the familial risk (Oldenburg et al. 2007). The same challenge is also faced by .