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抗寄生虫药物伊维菌素可通过调节lncRNA-EIF4A3-mRNA轴来抑制卵巢癌。

Anti-parasite drug ivermectin can suppress ovarian cancer by regulating lncRNA-EIF4A3-mRNA axes.

作者信息

Li Na, Zhan Xianquan

机构信息

University Creative Research Initiatives Center, Shandong First Medical University, 6699 Qingdao Road, Jinan, 250117 Shandong People's Republic of China.

Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.

出版信息

EPMA J. 2020 May 28;11(2):289-309. doi: 10.1007/s13167-020-00209-y. eCollection 2020 Jun.

DOI:10.1007/s13167-020-00209-y
PMID:32549918
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7272521/
Abstract

RELEVANCE

Ivermectin, as an old anti-parasite drug, can suppress almost completely the growth of various human cancers, including ovarian cancer (OC). However, its anticancer mechanism remained to be further studied at the molecular levels. Ivermectin-related molecule-panel changes will serve a useful tool for its personalized drug therapy and prognostic assessment in OCs.

PURPOSE

To explore the functional significance of ivermectin-mediated lncRNA-EIF4A3-mRNA axes in OCs and ivermectin-related molecule-panel for its personalized drug therapy monitoring.

METHODS

Based on our previous study, a total of 16 lncRNA expression patterns were analyzed using qRT-PCR before and after ivermectin-treated different OC cell lines (TOV-21G and A2780). Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to analyze the protein expressions of EIF4A3 and EIF4A3-binding mRNAs in ovarian cancer cells treated with and without ivermectin. A total of 411 OC patients from the Cancer Genome Atlas (TCGA) database with the selected lncRNA expressions and the corresponding clinical data were included. Lasso regression was constructed to examine the relationship between lncRNA signature and OC survival risk. The overall survival analysis between high-risk and low-risk groups used the Kaplan-Meier method. Heatmap showed the correlation between risk groups and clinical characteristics. The univariate and multivariate models were established with Cox regression.

RESULTS

SILAC-based quantitative proteomics found the protein expression levels of EIF4A3 and 116 EIF4A3-binding mRNAs were inhibited by ivermectin in OC cells. Among the analyzed 16 lncRNAs (HCG15, KIF9-AS1, PDCD4-AS1, ZNF674-AS1, ZNRF3-AS1, SOS1-IT1, LINC00565, SNHG3, PLCH1-AS1, WWTR1-AS1, LINC00517, AL109767.1, STARD13-IT1, LBX2-AS1, LEMD1-AS1, and HOXC-AS3), only 7 lncRNAs (HCG15, KIF9-AS1, PDCD4-AS1, ZNF674-AS1, ZNRF3-AS1, SOS1-IT1, and LINC00565) were obtained for further lasso regression when combined with the results of drug testing and overall survival analysis. Lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565). The high-risk and low-risk groups based on the prognostic model were significantly related to overall survival and clinicopathologic characteristics (survival status, lymphatic invasion, cancer status, and clinical stage) in OC patients and remained independent risk factors according to multivariate COX analysis ( < 0.05).

CONCLUSION

Those findings provided the potential targeted lncRNA-EIF4A3-mRNA pathways of ivermectin in OC, and constructed the effective prognostic model, which benefits discovery of novel mechanism of ivermectin to suppress ovarian cancer cells, and the ivermectin-related molecule-panel changes benefit for its personalized drug therapy and prognostic assessment towards its predictive, preventive, and personalized medicine (PPPM) in OCs.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/9931ef323042/13167_2020_209_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/013d422fbc0e/13167_2020_209_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/9edae66bca19/13167_2020_209_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/5eddccaf1538/13167_2020_209_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/91ba184cacf5/13167_2020_209_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/5a5ea3ac7ece/13167_2020_209_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/18e2a3a00cc4/13167_2020_209_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/9931ef323042/13167_2020_209_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/013d422fbc0e/13167_2020_209_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/9edae66bca19/13167_2020_209_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/5eddccaf1538/13167_2020_209_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/91ba184cacf5/13167_2020_209_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/5a5ea3ac7ece/13167_2020_209_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/18e2a3a00cc4/13167_2020_209_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/717e/7272521/9931ef323042/13167_2020_209_Fig7_HTML.jpg
摘要

相关性

伊维菌素作为一种古老的抗寄生虫药物，几乎可以完全抑制包括卵巢癌（OC）在内的各种人类癌症的生长。然而，其抗癌机制在分子水平上仍有待进一步研究。伊维菌素相关的分子图谱变化将为其在卵巢癌中的个性化药物治疗和预后评估提供有用的工具。

目的

探讨伊维菌素介导的lncRNA-EIF4A3-mRNA轴在卵巢癌中的功能意义以及伊维菌素相关分子图谱用于其个性化药物治疗监测的情况。

方法

基于我们之前的研究，使用qRT-PCR分析了伊维菌素处理不同卵巢癌细胞系（TOV-21G和A2780）前后的16种lncRNA表达模式。基于细胞培养中氨基酸的稳定同位素标记（SILAC）定量蛋白质组学用于分析用和不用伊维菌素处理的卵巢癌细胞中EIF4A3和与EIF4A3结合的mRNA的蛋白表达。纳入了癌症基因组图谱（TCGA）数据库中411例具有选定lncRNA表达及相应临床数据的卵巢癌患者。构建套索回归以检验lncRNA特征与卵巢癌生存风险之间的关系。高风险和低风险组之间的总生存分析采用Kaplan-Meier方法。热图显示了风险组与临床特征之间的相关性。使用Cox回归建立单变量和多变量模型。

结果

基于SILAC的定量蛋白质组学发现伊维菌素可抑制卵巢癌细胞中EIF4A3和116种与EIF4A3结合的mRNA的蛋白表达水平。在分析的16种lncRNA（HCG15、KIF9-AS1、PDCD4-AS1、ZNF67-AS1、ZNRF3-AS1、SOS1-IT1、LINC00565、SNHG3、PLCH1-AS1、WWTR1-AS1、LINC00517、AL109767.1、STARD13-IT1、LBX2-AS1、LEMD1-AS1和HOXC-AS3）中，结合药物测试和总生存分析结果后，仅7种lncRNA（HCG15、KIF9-AS1、PDCD4-AS1、ZNF674-AS1、ZNRF3-AS1、SOS1-IT1和LINC00565）用于进一步的套索回归。套索回归确定了伊维菌素相关的三lncRNA特征（ZNRF3-AS1、SOS1-IT1和LINC00565）的预后模型。基于该预后模型的高风险和低风险组与卵巢癌患者的总生存和临床病理特征（生存状态、淋巴浸润、癌症状态和临床分期）显著相关，并且根据多变量COX分析仍然是独立的风险因素（P<0.05）。

结论

这些发现提供了伊维菌素在卵巢癌中潜在的靶向lncRNA-EIF4A3-mRNA途径，并构建了有效的预后模型，这有助于发现伊维菌素抑制卵巢癌细胞的新机制，并且伊维菌素相关的分子图谱变化有利于其在卵巢癌中的个性化药物治疗和预后评估，朝着其预测、预防和个性化医学（PPPM）发展。

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