title: OPMSP: A Computational Method Integrating Protein Interaction and Sequence Information for the Identification of Novel Putative Oncogenes.
abstract: Oncogenes are genes that have the potential to cause cancer. Oncogene research can provide insight into the occurrence and development of cancer, thereby helping to prevent cancer and to design effective treatments. This study proposes a network method called the oncogene prediction method based on shortest path algorithm (OPMSP) for the identification of novel oncogenes in a large protein network built using protein-protein interaction data. Novel putative genes were extracted from the shortest paths connecting any two known oncogenes. Then, they were filtered by a randomization test, and the linkages among them and known oncogenes were measured by protein interaction and sequence data. Thirty-seven new putative oncogenes were identified by this method. The enrichment analysis of the 37 putative oncogenes indicated that they are highly associated with several biological processes related to the initiation, progression and metastasis of tumors. Six of these genes-ESR1, CDK9, SEPT2, HOXA10, LMX1B, and NR2C2-are extensively discussed. Several lines of evidence indicate that they may be novel oncogenes.
authors: College of Information Engineering, Shanghai Maritime University, People's Republic of China. chen_lei1@163.com.
authors: Lei
authors: L
authors: Chen
authors: Baoman
authors: B
authors: Wang
authors: ShaoPeng
authors: S
authors: Wang
authors: Jing
authors: J
authors: Yang
authors: Jerry
authors: J
authors: Hu
authors: ZhiQun
authors: Z
authors: Xie
authors: Yuwei
authors: Y
authors: Wang
authors: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, People's Republic of China. tohuangtao@126.com.
authors: Tao
authors: T
authors: Huang
authors: College of Life Science, Shanghai University, People's Republic of China. cai_yud@126.com.
authors: Yu-Dong
authors: YD
authors: Cai
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D042863:Cyclin-Dependent Kinase 9 / Q000235:genetics; D047628:Estrogen Receptor alpha / Q000235:genetics; D000080905:Homeobox A10 Proteins; D018398:Homeodomain Proteins / Q000235:genetics; D060850:LIM-Homeodomain Proteins / Q000235:genetics; D009369:Neoplasms / Q000235:genetics*; D009857:Oncogenes / Q000235:genetics*; D060066:Protein Interaction Maps / Q000235:genetics*; D011987:Receptors, Steroid / Q000235:genetics; D011988:Receptors, Thyroid Hormone / Q000235:genetics; D058112:Septins / Q000235:genetics; D014157:Transcription Factors / Q000235:genetics
chemical_list: C506487:ESR1 protein, human; D047628:Estrogen Receptor alpha; D000080905:Homeobox A10 Proteins; D018398:Homeodomain Proteins; C112149:LIM homeobox transcription factor 1 beta; D060850:LIM-Homeodomain Proteins; C490515:NR2C2 protein, human; D011987:Receptors, Steroid; D011988:Receptors, Thyroid Hormone; D014157:Transcription Factors; C069634:HOXA10 protein, human; C467969:CDK9 protein, human; D042863:Cyclin-Dependent Kinase 9; C000602252:SEPTIN2 protein, human; D058112:Septins