title: Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma.
abstract: Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.
authors.affiliation: Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan.
authors.forename: Ming-Huang
authors.initials: MH
authors.lastname: Chen
authors.forename: Wu-Lung R
authors.initials: WL
authors.lastname: Yang
authors.forename: Kuan-Ting
authors.initials: KT
authors.lastname: Lin
authors.forename: Chia-Hung
authors.initials: CH
authors.lastname: Liu
authors.forename: Yu-Wen
authors.initials: YW
authors.lastname: Liu
authors.forename: Kai-Wen
authors.initials: KW
authors.lastname: Huang
authors.forename: Peter Mu-Hsin
authors.initials: PM
authors.lastname: Chang
authors.forename: Jin-Mei
authors.initials: JM
authors.lastname: Lai
authors.forename: Chun-Nan
authors.initials: CN
authors.lastname: Hsu
authors.forename: Kun-Mao
authors.initials: KM
authors.lastname: Chao
authors.forename: Cheng-Yan
authors.initials: CY
authors.lastname: Kao
authors.forename: Chi-Ying F
authors.initials: CY
authors.lastname: Huang
mesh_terms: D000818:Animals; D006528:Carcinoma, Hepatocellular / Q000188:drug therapy* / Q000235:genetics; D049109:Cell Proliferation / Q000187:drug effects; D002746:Chlorpromazine / Q000494:pharmacology; D003625:Data Collection / Q000379:methods; D030561:Databases, Nucleic Acid; D018492:Dopamine Antagonists / Q000494:pharmacology; D055808:Drug Discovery / Q000379:methods*; D004353:Drug Evaluation, Preclinical / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic / Q000187:drug effects*; D006801:Humans; D008113:Liver Neoplasms / Q000188:drug therapy* / Q000235:genetics; D008722:Methods; D051379:Mice; D014268:Trifluoperazine / Q000494:pharmacology
chemical_list: D018492:Dopamine Antagonists; D014268:Trifluoperazine; D002746:Chlorpromazine
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