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1.
EPMA J ; 11(2): 289-309, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-1086691

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 (p < 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.

2.
J Cell Physiol ; 236(4): 2959-2975, 2021 04.
Article in English | MEDLINE | ID: covidwho-777472

ABSTRACT

Viruses such as human cytomegalovirus (HCMV), human papillomavirus (HPV), Epstein-Barr virus (EBV), human immunodeficiency virus (HIV), and coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) represent a great burden to human health worldwide. FDA-approved anti-parasite drug ivermectin is also an antibacterial, antiviral, and anticancer agent, which offers more potentiality to improve global public health, and it can effectively inhibit the replication of SARS-CoV-2 in vitro. This study sought to identify ivermectin-related virus infection pathway alterations in human ovarian cancer cells. Stable isotope labeling by amino acids in cell culture (SILAC) quantitative proteomics was used to analyze human ovarian cancer cells TOV-21G treated with and without ivermectin (20 µmol/L) for 24 h, which identified 4447 ivermectin-related proteins in ovarian cancer cells. Pathway network analysis revealed four statistically significant antiviral pathways, including HCMV, HPV, EBV, and HIV1 infection pathways. Interestingly, compared with the reported 284 SARS-CoV-2/COVID-19-related genes from GencLip3, we identified 52 SARS-CoV-2/COVID-19-related protein alterations when treated with and without ivermectin. Protein-protein network (PPI) was constructed based on the interactions between 284 SARS-CoV-2/COVID-19-related genes and between 52 SARS-CoV-2/COVID-19-related proteins regulated by ivermectin. Molecular complex detection analysis of PPI network identified three hub modules, including cytokines and growth factor family, MAP kinase and G-protein family, and HLA class proteins. Gene Ontology analysis revealed 10 statistically significant cellular components, 13 molecular functions, and 11 biological processes. These findings demonstrate the broad-spectrum antiviral property of ivermectin benefiting for COVID-19 treatment in the context of predictive, preventive, and personalized medicine in virus-related diseases.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Ivermectin/pharmacology , Cell Line, Tumor , Humans , Proteomics/methods , SARS-CoV-2
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