title: A Methodology for Cancer Therapeutics by Systems Pharmacology-Based Analysis: A Case Study on Breast Cancer-Related Traditional Chinese Medicines.
abstract: Breast cancer is the most common carcinoma in women. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effect and resistance against anticancer drugs. Complementary and alternative medicine (CAM) may avoid these problems, in which traditional Chinese medicine (TCM) has been highlighted. In this section, to analyze the mechanism through which TCM act on breast cancer, we have built a virtual model consisting of the construction of database, oral bioavailability prediction, drug-likeness evaluation, target prediction, network construction. The 20 commonly employed herbs for the treatment of breast cancer were used as a database to carry out research. As a result, 150 ingredient compounds were screened out as active molecules for the herbs, with 33 target proteins predicted. Our analysis indicates that these herbs 1) takes a 'Jun-Chen-Zuo-Shi" as rule of prescription, 2) which function mainly through perturbing three pathways involving the epidermal growth factor receptor, estrogen receptor, and inflammatory pathways, to 3) display the breast cancer-related anti-estrogen, anti-inflammatory, regulation of cell metabolism and proliferation activities. To sum it up, by providing a novel in silico strategy for investigation of the botanical drugs, this work may be of some help for understanding the action mechanisms of herbal medicines and for discovery of new drugs from plants.
authors.affiliation: Systems Biology Laboratory, Department of Computer Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America.|Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian, Liaoning, P R China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.affiliation: Systems Biology Laboratory, Department of Computer Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America.|Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian, Liaoning, P R China.
authors.forename: Jinghui
authors.initials: J
authors.lastname: Wang
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian, Liaoning, P R China.
authors.forename: Feng
authors.initials: F
authors.lastname: Lin
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology, Dalian, Liaoning, P R China.
authors.forename: Yinfeng
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Systems Biology Laboratory, Department of Computer Information Science and Engineering, University of Florida, Gainesville, Florida, United States of America.
authors.forename: Su-Shing
authors.initials: SS
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use; D001682:Biological Availability; D001943:Breast Neoplasms / Q000188:drug therapy; D016208:Databases, Factual; D004365:Drugs, Chinese Herbal / Q000494:pharmacology / Q000627:therapeutic use; D006801:Humans; D008516:Medicine, Chinese Traditional; D008954:Models, Biological; D015203:Reproducibility of Results
chemical_list: D000970:Antineoplastic Agents; D004365:Drugs, Chinese Herbal