title: Combining genomic and network characteristics for extended capability in predicting synergistic drugs for cancer.
abstract: The identification of synergistic chemotherapeutic agents from a large pool of candidates is highly challenging. Here, we present a Ranking-system of Anti-Cancer Synergy (RACS) that combines features of targeting networks and transcriptomic profiles, and validate it on three types of cancer. Using data on human β-cell lymphoma from the Dialogue for Reverse Engineering Assessments and Methods consortium we show a probability concordance of 0.78 compared with 0.61 obtained with the previous best algorithm. We confirm 63.6% of our breast cancer predictions through experiment and literature, including four strong synergistic pairs. Further in vivo screening in a zebrafish MCF7 xenograft model confirms one prediction with strong synergy and low toxicity. Validation using A549 lung cancer cells shows similar results. Thus, RACS can significantly improve drug synergy prediction and markedly reduce the experimental prescreening of existing drugs for repurposing to cancer treatment, although the molecular mechanism underlying particular interactions remains unknown.
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Yi
authors.initials: Y
authors.lastname: Sun
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Sheng
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Chao
authors.initials: C
authors.lastname: Ma
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Kailin
authors.initials: K
authors.lastname: Tang
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Ruixin
authors.initials: R
authors.lastname: Zhu
authors.affiliation: Shanghai Research Center for Model Organisms, Shanghai 200092, China.
authors.forename: Zhuanbin
authors.initials: Z
authors.lastname: Wu
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.|Shanghai Research Center for Model Organisms, Shanghai 200092, China.
authors.forename: Ruling
authors.initials: R
authors.lastname: Shen
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Feng
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Dingfeng
authors.initials: D
authors.lastname: Wu
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Danyi
authors.initials: D
authors.lastname: Huang
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Dandan
authors.initials: D
authors.lastname: Huang
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Fei
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Qi
authors.initials: Q
authors.lastname: Liu
authors.affiliation: School of Life Sciences and Technology, Tongji University, Shanghai 200092, China.
authors.forename: Zhiwei
authors.initials: Z
authors.lastname: Cao
mesh_terms: D000818:Animals; D000970:Antineoplastic Agents / Q000494:pharmacology* / Q000627:therapeutic use; D004357:Drug Synergism; D023281:Genomics; D006801:Humans; D061986:MCF-7 Cells; D008962:Models, Theoretical; D009369:Neoplasms / Q000188:drug therapy*; D023041:Xenograft Model Antitumor Assays; D015027:Zebrafish
chemical_list: D000970:Antineoplastic Agents