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In vitro modeling of hepatocellular carcinoma molecular subtypes for anti-cancer drug assessment.

ABSTRACT: Tractable experimental model that accounts for inter-tumor molecular heterogeneity is a key element of anti-cancer drug development. Hepatocellular carcinoma is known to exhibit highly heterogeneous molecular aberrations across the tumors, including somatic genetic and epigenetic alterations. Previous studies showed that molecular tumor subtypes determined by transcriptome, as a comprehensive functional readout, are reproducibly observed across global patient populations irrespective of geographic and etiological variations. Here we demonstrate that transcriptomic hepatocellular carcinoma subtypes, S1 and S2, determined by our previous transcriptome meta-analysis of multiple clinical hepatocellular carcinoma cohorts, are presented in a panel of hepatoma cell lines widely used by the research community. Interestingly, cell line that resembles gene expression pattern of S3 subtype, representing less aggressive tumors, was not identified in the panel. MYC pathway-activated S2-like cell lines showed higher sensitivity to a small molecule BET bromodomain inhibitor, (+)-JQ1, which has anti-MYC activity. These results support the use of hepatoma cell lines as models to evaluate molecular subtype-specific drug response, which is expected to lead to development of tailored, precision care of the patients with hepatocellular carcinoma.

SUBMITTER: Hirschfield H

PROVIDER: S-EPMC5992986 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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In vitro modeling of hepatocellular carcinoma molecular subtypes for anti-cancer drug assessment.

Hirschfield Hadassa H Bian C Billie CB Higashi Takaaki T Nakagawa Shigeki S Zeleke Tizita Z TZ Nair Venugopalan D VD Nair Venugopalan D VD Fuchs Bryan C BC Hoshida Yujin Y

Experimental & molecular medicine 20180105 1

Tractable experimental model that accounts for inter-tumor molecular heterogeneity is a key element of anti-cancer drug development. Hepatocellular carcinoma is known to exhibit highly heterogeneous molecular aberrations across the tumors, including somatic genetic and epigenetic alterations. Previous studies showed that molecular tumor subtypes determined by transcriptome, as a comprehensive functional readout, are reproducibly observed across global patient populations irrespective of geograph ...[more]

PMID: 29303513

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Project description:Hepatocellular carcinoma (HCC) is the major life-threatening primary liver malignancy in both sexes all over the world. Unfortunately, the majority of patients are diagnosed at later stages because HCC does not elicit obvious symptoms during its early incidence. Consequently, most individuals escape the first-line HCC treatments and are treated with chemotherapy. Regrettably, the therapeutic outcomes for those patients are usually poor because of the development of multidrug resistance phenomena. Furthermore, most anti-HCC therapies cause severe undesired side effects that notably interfere with the life quality of such patients. Accordingly, there is an important need to search for an alternative therapeutic drug or adjuvant which is more efficient with safe or even minimal side effects for HCC treatment. Melatonin was recently reported to exert intrinsic antitumor activity in different cancers. However, the regulatory pathways underlying the antitumor activity of melatonin are poorly understood in resistant liver cells. Furthermore, a limited number of studies have addressed the therapeutic role of melatonin in HCC cells resistant to doxorubicin chemotherapy. In this study, we investigated the antitumor effects of melatonin in doxorubicin-resistant HepG2 cells and explored the regulatory pivotal targets underlying these effects. To achieve our aim, an MTT assay was used to calculate the 50% inhibitory concentration of melatonin and evaluate its antiproliferative effect on resistant cells. Additionally, qRT-PCR was used to quantify genes having a role in drug resistance phenotype (ABCB1, ABCC1, ABCC2, ABCC3, ABCC4, ABCC5, and ABCG2); apoptosis (caspases-3, and -7, Bcl2, Bax, and p53); anti-oxidation (NRF2); expression of melatonin receptors (MT1, MT2, and MT3); besides, programmed death receptor PD-1 gene. The active form of the caspase-3 enzyme was estimated by ELISA. A human inflammatory antibody membrane array was employed to quantify forty inflammatory factors expressed in treated cells. We observed that melatonin inhibited the proliferation of doxorubicin-resistant HepG2 cells in a dose-dependent manner after 24-h incubation time with a calculated IC50 greater than 10 mM (13.4 mM), the expression levels of genes involved in drug resistance response (ABCB1, ABCC1, ABCC5, and ABCG2) were downregulated. Also, the expression of caspase-3, Caspase-7, NRF2, and p53 genes were expressed at higher levels as compared to control (DMSO-treated cells). An active form of caspase-3 was confirmed by ELISA. Moreover, the anti-inflammatory effect of melatonin was detected through the calculated fold change to control which was reduced for various mediators that have a role in the inflammation pathway. The current findings introduce melatonin as a promising anti-cancer treatment for human-resistant HCC which could be used in combination with current chemotherapeutic regimens to improve the outcome and reduce the developed multidrug resistance.

Project description:BackgroundHepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, with a high mortality rate and poor prognosis. Mutated or dysregulated transcription factors (TFs) are significantly associated with carcinogenesis. The aim of this study was to develop a TF-related prognostic risk model to predict the prognosis and guide the treatment of HCC patients.MethodsRNA sequencing data were obtained from the TCGA database. The ICGC and GEO databases were used as validation datasets. The consensus clustering algorithm was used to classify the molecular subtypes of TFs. Kaplan‒Meier survival analysis and receiver operating characteristic (ROC) analysis were applied to evaluate the prognostic value of the model. The immunogenic landscape differences of molecular subtypes were evaluated by the TIMER and xCell algorithms. Autodock analysis was used to predict possible binding sites of trametinib to TFs. RT‒PCR was used to verify the effect of trametinib on the expression of core TFs.ResultsAccording to the differential expression of TFs, HCC samples were divided into two clusters (C1 and C2). The survival time, signaling pathways, abundance of immune cell infiltration and responses to chemotherapy and immunotherapy were significantly different between C1 and C2. Nine TFs with potential prognostic value, including HMGB2, ESR1, HMGA1, MYBL2, TCF19, E2F1, FOXM1, CENPA and ZIC2, were identified by Cox regression analysis. HCC patients in the high-risk group had a poor prognosis compared with those in the low-risk group (p < 0.001). Moreover, the area under the ROC curve (AUC) values of the 1-year, 2-year and 3-year survival rates were 0.792, 0.71 and 0.695, respectively. The risk model was validated in the ICGC database. Notably, trametinib sensitivity was highly correlated with the expression of core TFs, and molecular docking predicted the possible binding sites of trametinib with these TFs. More importantly, the expression of core TFs was downregulated under trametinib treatment.ConclusionsA prognostic signature with 9 TFs performed well in predicting the survival rate and chemotherapy/immunotherapy effect of HCC patients. Trimetinib has potential application value in HCC by targeting TFs.

Dataset Information

In vitro modeling of hepatocellular carcinoma molecular subtypes for anti-cancer drug assessment.

Publications

In vitro modeling of hepatocellular carcinoma molecular subtypes for anti-cancer drug assessment.

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