title: Mining for novel tumor suppressor genes using a shortest path approach.
abstract: Cancer, being among the most serious diseases, causes many deaths every year. Many investigators have devoted themselves to designing effective treatments for this disease. Cancer always involves abnormal cell growth with the potential to invade or spread to other parts of the body. In contrast, tumor suppressor genes (TSGs) act as guardians to prevent a disordered cell cycle and genomic instability in normal cells. Studies on TSGs can assist in the design of effective treatments against cancer. In this study, we propose a computational method to discover potential TSGs. Based on the known TSGs, a number of candidate genes were selected by applying the shortest path approach in a weighted graph that was constructed using protein-protein interaction network. The analysis of selected genes shows that some of them are new TSGs recently reported in the literature, while others may be novel TSGs.
authors.affiliation: a College of Life Science , Shanghai University , Shanghai 200444 , P.R. China.|b College of Information Engineering , Shanghai Maritime University , Shanghai 201306 , P.R. China.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: c The Key Laboratory of Stem Cell Biology , Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS) , Shanghai 200025 , P.R. China.
authors.forename: Jing
authors.initials: J
authors.lastname: Yang
authors.affiliation: c The Key Laboratory of Stem Cell Biology , Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS) , Shanghai 200025 , P.R. China.
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.affiliation: c The Key Laboratory of Stem Cell Biology , Institute of Health Sciences, Shanghai Jiao Tong University School of Medicine (SJTUSM) and Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS) , Shanghai 200025 , P.R. China.
authors.forename: Xiangyin
authors.initials: X
authors.lastname: Kong
authors.affiliation: d Department of Radiology , Columbia University Medical Center , New York , NY 10032 , USA.
authors.forename: Lin
authors.initials: L
authors.lastname: Lu
authors.affiliation: a College of Life Science , Shanghai University , Shanghai 200444 , P.R. China.
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D019295:Computational Biology / Q000379:methods; D030541:Databases, Genetic; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D056726:Genetic Association Studies; D006801:Humans; D058977:Molecular Sequence Annotation; D009154:Mutation; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods; D060066:Protein Interaction Maps; D015398:Signal Transduction; D025521:Tumor Suppressor Proteins / Q000235:genetics / Q000378:metabolism*
chemical_list: D025521:Tumor Suppressor Proteins
keywords: DAVID; protein–protein interactions; shortest path approach; tumor suppressor genes; weighted graph