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. 2011;6(11):e27186.
doi: 10.1371/journal.pone.0027186. Epub 2011 Nov 7.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma

Ming-Huang Chen  1 , Wu-Lung R Yang, Kuan-Ting Lin, Chia-Hung Liu, Yu-Wen Liu, Kai-Wen Huang, Peter Mu-Hsin Chang, Jin-Mei Lai, Chun-Nan Hsu, Kun-Mao Chao, Cheng-Yan Kao, Chi-Ying F Huang
Affiliations

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma

Ming-Huang Chen et al. PLoS One. 2011.

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Collection, intersection, and validation of HCC-related genes in EHCO2.
(A) Gene sets in EHCO2 and their intersecting genes. The gray box indicates the number of genes reported in each set, while the intersection cell indicates the numbers of common genes. Each pair of datasets shares a small number of common genes, suggesting the heterogeneous nature of HCC. The bottom-left insert shows the frequency of genes reported. Most genes are reported only once. (B) Validation of up-regulated genes via Q-RT-PCR. RHAMM, INTS8, CDCA8, DEPDC1B, and KIAA0195 are over-expressed in 21 paired HCC patient samples.
Figure 2
Figure 2. Flowchart and comparisons of prediction accuracy.
(A) The CMap analysis flowchart. All eight sets from EHCO2 (Group 1), 100-member random sets, Frequent sets, and Clique sets (Group 2) were individually queried with CMap. Only drugs with a p-value of less than 0.05 and a negative enrichment score were retained. (B) Comparison of the accuracy of predicted drugs from each set. The top 10 drugs from each set were labeled according to their anti-cancer effects. (C) The comparison of the Frequency sets and the Clique sets. The average effectiveness of drugs was compared side by side.
Figure 3
Figure 3. Effectiveness of drugs in Group 1 and Group 2.
The top 10 drugs from each set were labeled according to their anti-cancer effects.
Figure 4
Figure 4. In-vitro and in-vivo effects of chlorpromazine and trifluoperazine.
(A) Chlorpromazine and trifluoperazine inhibit clonogenic survival. Huh7 cells were incubated with chlorpromazine and trifluoperazine at various concentrations (1, 3.3, and 10 µM) for 15 days. Cell colonies were counted and expressed in terms of percent survival relative to the control. The data represent the mean±SD from three independent experiments. In vivo effects of chlorpromazine and trifluoperazine on BNL cell orthotopic liver tumor models. (B) The ratio of tumor size enlargement obtained from all animals in the therapeutic group after 21 days of treatment was calculated. (C) The sizes of the tumors obtained from the animals in the prophylactic group 21 days after tumor implantation were measured. *P<0.05, **P<0.005, compared to the control group. (D) The sizes of tumors obtained from the animals in the prophylactic group 21 days after tumor implantation were measured. Black arrows show the liver tumors.
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