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Identification of Niclosamide as a Novel Anticancer Agent for Adrenocortical Carcinoma.

ABSTRACT: PURPOSE:Adrenocortical carcinoma (ACC) is a rare and aggressive cancer, and no current effective therapy is available for locally advanced and metastatic ACC. Drug repurposing is an emerging approach for identifying new indications for existing drugs, especially for rare cancers such as ACC. The objective of this study was to use quantitative high-throughput screening to identify agents with antineoplastic activity against ACC. EXPERIMENTAL DESIGN:A screening of 4,292 compounds was performed on three ACC cell lines: BD140A, SW-13, and NCI-H295R. RESULTS:Twenty-one active compounds were identified, with an efficacy of >80% in all three cell lines. Of these, niclosamide showed higher efficacy and lower IC50 than established anti-ACC drugs. We then validated niclosamide-inhibited cellular proliferation in all three ACC cell lines. Next, we investigated the mechanism by which niclosamide inhibited ACC cell proliferation, and found that it induced caspase-dependent apoptosis and G1 cell-cycle arrest. Niclosamide also decreased cellular migration and reduced the level of mediators of epithelial-to-mesenchymal transition, such as N-cadherin and vimentin. Furthermore, niclosamide treatment resulted in decreased expression of ?-catenin. We also evaluated the effect of niclosamide on energy metabolism in ACC cell lines and found it resulted in mitochondrial uncoupling. Niclosamide treatment inhibited ACC tumor growth with no observed toxicity in mice in vivo CONCLUSIONS:Our findings suggest that niclosamide has anti-ACC activity through its inhibition of multiple altered cellular pathways and cellular metabolism in ACC. Our results provide a preclinical rationale for evaluating niclosamide therapy in a clinical trial for ACC. Clin Cancer Res; 22(14); 3458-66. ©2016 AACR.

SUBMITTER: Satoh K

PROVIDER: S-EPMC4947455 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Identification of Niclosamide as a Novel Anticancer Agent for Adrenocortical Carcinoma.

Satoh Kei K Zhang Lisa L Zhang Yaqin Y Chelluri Raju R Boufraqech Myriem M Nilubol Naris N Patel Dhaval D Shen Min M Kebebew Electron E

Clinical cancer research : an official journal of the American Association for Cancer Research 20160212 14

<h4>Purpose</h4>Adrenocortical carcinoma (ACC) is a rare and aggressive cancer, and no current effective therapy is available for locally advanced and metastatic ACC. Drug repurposing is an emerging approach for identifying new indications for existing drugs, especially for rare cancers such as ACC. The objective of this study was to use quantitative high-throughput screening to identify agents with antineoplastic activity against ACC.<h4>Experimental design</h4>A screening of 4,292 compounds wa ...[more]

PMID: 26873959

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Project description:BACKGROUND:The 7th AJCC T-stage system for adrenocortical carcinoma (ACC), based on size and extra-adrenal invasion, does not adequately stratify patients by survival. Lymphovascular invasion (LVI) is a known poor prognostic factor. We propose a novel T-stage system that incorporates LVI to better risk-stratify patients undergoing resection for ACC. METHOD:Patients undergoing curative-intent resections for ACC from 1993 to 2014 at 13 institutions comprising the US ACC Group were included. Primary outcome was disease-specific survival (DSS). RESULTS:Of the 265 patients with ACC, 149 were included for analysis. The current T-stage system failed to differentiate patients with T2 versus T3 disease (p = 0.10). Presence of LVI was associated with worse DSS versus no LVI (36 mo vs. 168 mo; p = 0.001). After accounting for the individual components of the current T-stage system (size, extra-adrenal invasion), LVI remained a poor prognostic factor on multivariable analysis (hazard ratio 2.14, 95% confidence interval 1.05-4.38, p = 0.04). LVI positivity further stratified patients with T2 and T3 disease (T2: 37 mo vs. median not reached; T3: 36 mo vs. 96 mo; p = 0.03) but did not influence survival in patients with T1 or T4 disease. By incorporating LVI, a new T-stage classification system was created: [T1: ≤ 5 cm, (-)local invasion, (+/-)LVI; T2: > 5 cm, (-)local invasion, (-)LVI OR any size, (+)local invasion, (-)LVI; T3: > 5 cm, (-)local invasion, (+)LVI OR any size, (+)local invasion, (+)LVI; T4: any size, (+)adjacent organ invasion, (+/-)LVI]. Each progressive new T-stage group was associated with worse median DSS (T1: 167 mo; T2: 96 mo; T3: 37 mo; T4: 15 mo; p < 0.001). CONCLUSIONS:Compared with the current T-stage system, the proposed T-stage system, which incorporates LVI, better differentiates T2 and T3 disease and accurately stratifies patients by disease-specific survival. If externally validated, this T-stage classification should be considered for future AJCC staging systems.

Project description:Objective: Adrenocortical carcinoma (ACC) is a rare but aggressive malignant cancer that has been attracting growing attention over recent decades. This study aims to integrate protein interaction networks with gene expression profiles to identify potential biomarkers with prognostic value in silico. Methods: Three microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) according to the normalization annotation information. Enrichment analyses were utilized to describe biological functions. A protein-protein interaction network (PPI) of the DEGs was developed, and the modules were analyzed using STRING and Cytoscape. LASSO Cox regression was used to identify independent prognostic factors. The Kaplan-Meier method for the integrated expression score was applied to analyze survival outcomes. A receiver operating characteristic (ROC) curve was constructed with area under curve (AUC) analysis to determine the diagnostic ability of the candidate biomarkers. Results: A total of 150 DEGs and 24 significant hub genes with functional enrichment were identified as candidate prognostic biomarkers. LASSO Cox regression suggested that ZWINT, PRC1, CDKN3, CDK1 and CCNA2 were independent prognostic factors in ACC. In multivariate Cox analysis, the integrated expression scores of the modules showed statistical significance in predicting disease-free survival (DFS, P = 0.019) and overall survival (OS, P < 0.001). Meanwhile, ROC curves were generated to validate the ability of the Cox model to predict prognosis. The AUC index for the integrated genes scores was 0.861 (P < 0.0001). Conclusion: In conclusion, the present study identifies DEGs and hub genes that may be involved in poor prognosis and early recurrence of ACC. The expression levels of ZWINT, PRC1, CDKN3, CDK1 and CCNA2 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ACC. Further studies are required to elucidate molecular pathogenesis and alteration in signaling pathways for these genes in ACC.

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Identification of Niclosamide as a Novel Anticancer Agent for Adrenocortical Carcinoma.

Publications

Identification of Niclosamide as a Novel Anticancer Agent for Adrenocortical Carcinoma.

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