title: Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach.
abstract: Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of "cancer drivers" connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, People's Republic of China.|College of Information Engineering, Shanghai Maritime University, Shanghai 201306, People's Republic of China.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.affiliation: Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.
authors.forename: Yu-Hang
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People's Republic of China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, People's Republic of China.
authors.forename: Mingyue
authors.initials: M
authors.lastname: Zheng
authors.affiliation: School of Life Sciences, Shanghai University, Shanghai 200444, People's Republic of China.
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D000077192:Adenocarcinoma of Lung; D063646:Carcinogenesis / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D019175:DNA Methylation; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D009154:Mutation; D009363:Neoplasm Proteins / Q000235:genetics* / Q000378:metabolism; D025941:Protein Interaction Mapping; D012333:RNA, Messenger / Q000235:genetics* / Q000378:metabolism; D015398:Signal Transduction; D049490:Systems Biology / Q000379:methods; D059016:Tumor Microenvironment / Q000235:genetics
chemical_list: D035683:MicroRNAs; D009363:Neoplasm Proteins; D012333:RNA, Messenger