title: Identification of Potential Drug Targets in Cancer Signaling Pathways using Stochastic Logical Models.
abstract: The investigation of vulnerable components in a signaling pathway can contribute to development of drug therapy addressing aberrations in that pathway. Here, an original signaling pathway is derived from the published literature on breast cancer models. New stochastic logical models are then developed to analyze the vulnerability of the components in multiple signalling sub-pathways involved in this signaling cascade. The computational results are consistent with the experimental results, where the selected proteins were silenced using specific siRNAs and the viability of the cells were analyzed 72 hours after silencing. The genes elF4E and NFkB are found to have nearly no effect on the relative cell viability and the genes JAK2, Stat3, S6K, JUN, FOS, Myc, and Mcl1 are effective candidates to influence the relative cell growth. The vulnerabilities of some targets such as Myc and S6K are found to vary significantly depending on the weights of the sub-pathways; this will be indicative of the chosen target to require customization for therapy. When these targets are utilized, the response of breast cancers from different patients will be highly variable because of the known heterogeneities in signaling pathways among the patients. The targets whose vulnerabilities are invariably high might be more universally acceptable targets.
authors.affiliation: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
authors.forename: Peican
authors.initials: P
authors.lastname: Zhu
authors.affiliation: School of Pharmacy, Chapman University, Irvine, CA 92618, USA.|Department of Chemical and Material Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
authors.forename: Hamidreza Montazeri
authors.initials: HM
authors.lastname: Aliabadi
authors.affiliation: Department of Chemical and Material Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
authors.forename: Hasan
authors.initials: H
authors.lastname: Uludağ
authors.affiliation: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
authors.forename: Jie
authors.initials: J
authors.lastname: Han
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology*; D001943:Breast Neoplasms / Q000188:drug therapy / Q000378:metabolism*; D045744:Cell Line, Tumor; D049109:Cell Proliferation / Q000187:drug effects; D002470:Cell Survival / Q000187:drug effects; D019295:Computational Biology / Q000379:methods*; D005260:Female; D015972:Gene Expression Regulation, Neoplastic / Q000187:drug effects; D006801:Humans; D034741:RNA, Small Interfering / Q000235:genetics; D015398:Signal Transduction / Q000187:drug effects*; D013269:Stochastic Processes
chemical_list: D000970:Antineoplastic Agents; D034741:RNA, Small Interfering