title: Prediction of body fluids where proteins are secreted into based on protein interaction network.
abstract: Determining the body fluids where secreted proteins can be secreted into is important for protein function annotation and disease biomarker discovery. In this study, we developed a network-based method to predict which kind of body fluids human proteins can be secreted into. For a newly constructed benchmark dataset that consists of 529 human-secreted proteins, the prediction accuracy for the most possible body fluid location predicted by our method via the jackknife test was 79.02%, significantly higher than the success rate by a random guess (29.36%). The likelihood that the predicted body fluids of the first four orders contain all the true body fluids where the proteins can be secreted into is 62.94%. Our method was further demonstrated with two independent datasets: one contains 57 proteins that can be secreted into blood; while the other contains 61 proteins that can be secreted into plasma/serum and were possible biomarkers associated with various cancers. For the 57 proteins in first dataset, 55 were correctly predicted as blood-secrete proteins. For the 61 proteins in the second dataset, 58 were predicted to be most possible in plasma/serum. These encouraging results indicate that the network-based prediction method is quite promising. It is anticipated that the method will benefit the relevant areas for both basic research and drug development.
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai, China.
authors.forename: Le-Le
authors.initials: LL
authors.lastname: Hu
authors.forename: Tao
authors.initials: T
authors.lastname: Huang
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis / Q000378:metabolism*; D001826:Body Fluids / Q000737:chemistry* / Q000378:metabolism; D030562:Databases, Protein; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis* / Q000378:metabolism; D060066:Protein Interaction Maps; D011506:Proteins / Q000032:analysis* / Q000737:chemistry / Q000378:metabolism*
chemical_list: D014408:Biomarkers, Tumor; D011506:Proteins