title: Integrating genomics and proteomics data to predict drug effects using binary linear programming.
abstract: The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be used to elucidate potential mechanisms of a compound's efficacy.
authors.affiliation: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina, United States of America; School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Ji
authors.affiliation: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina, United States of America.
authors.forename: Jing
authors.initials: J
authors.lastname: Su
authors.affiliation: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina, United States of America.
authors.forename: Chenglin
authors.initials: C
authors.lastname: Liu
authors.affiliation: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina, United States of America.
authors.forename: Hongyan
authors.initials: H
authors.lastname: Wang
authors.affiliation: School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China.
authors.forename: Deshuang
authors.initials: D
authors.lastname: Huang
authors.affiliation: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina, United States of America.
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Zhou
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology*; D001549:Benzamides / Q000494:pharmacology; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics / Q000378:metabolism; D002453:Cell Cycle / Q000187:drug effects / Q000235:genetics; D045744:Cell Line, Tumor; D050759:Cyclin-Dependent Kinase Inhibitor p21 / Q000378:metabolism; D004076:Digoxigenin / Q000494:pharmacology; D005260:Female; D015870:Gene Expression / Q000187:drug effects / Q000235:genetics; D053263:Gene Regulatory Networks / Q000187:drug effects* / Q000235:genetics*; D023281:Genomics / Q000379:methods; D018922:HL-60 Cells; D056572:Histone Deacetylase Inhibitors / Q000494:pharmacology; D006801:Humans; D006877:Hydroxamic Acids / Q000494:pharmacology; D061986:MCF-7 Cells; D010766:Phosphorylation / Q000187:drug effects / Q000235:genetics; D011382:Programming, Linear; D020543:Proteome / Q000378:metabolism*; D040901:Proteomics / Q000379:methods; D011725:Pyridines / Q000494:pharmacology; D015398:Signal Transduction / Q000187:drug effects* / Q000235:genetics*; D019311:Staurosporine / Q000494:pharmacology; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
chemical_list: D000970:Antineoplastic Agents; D001549:Benzamides; D050759:Cyclin-Dependent Kinase Inhibitor p21; D056572:Histone Deacetylase Inhibitors; D006877:Hydroxamic Acids; D020543:Proteome; D011725:Pyridines; D016159:Tumor Suppressor Protein p53; C118739:entinostat; C012589:trichostatin A; D019311:Staurosporine; D004076:Digoxigenin