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. 2021 Jan;56(1):e4659.
doi: 10.1002/jms.4659. Epub 2020 Oct 12.

SILAC quantitative proteomics analysis of ivermectin-related proteomic profiling and molecular network alterations in human ovarian cancer cells

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SILAC quantitative proteomics analysis of ivermectin-related proteomic profiling and molecular network alterations in human ovarian cancer cells

Na Li et al. J Mass Spectrom. 2021 Jan.

Abstract

The antiparasitic agent ivermectin offers more promises to treat a diverse range of diseases. However, a comprehensive proteomic analysis of ivermectin-treated ovarian cancer (OC) cells has not been performed. This study sought to identify ivermectin-related proteomic profiling and molecular network alterations in human OC cells. Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to study the human OC TOV-21G cells. After TOV-21G cells underwent 10 passages in SILAC-labeled growth media, TOV-21G cells were treated with 10 ml of 20 μmol/L ivermectin in cell growing medium for 24 h. The SILAC-labeled proteins were digested with trypsin; tryptic peptides were identified with mass spectrometry (MS). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to mine signaling pathway alterations with ivermectin-related proteins in TOV-21G cells. Gene ontology (GO) analysis was used to explore biological functions of ivermectin-related proteins, including biological processes (BPs), cellular components (CCs), and molecular functions (MFs). The protein-protein interaction network was analyzed with molecular complex detection (MCODE) to identify hub modules. In total, 4,447 proteins were identified in ivermectin-treated TOV-21G cells. KEGG analysis revealed 89 statistically significant signaling pathways. Interestingly, the clustering analysis of these pathways showed that ivermectin was involved in various cancer pathogenesis processes, including modulation of replication, RNA metabolism, and translational machinery. GO analysis revealed 69 statistically significant CCs, 87 MFs, and 62 BPs. Furthermore, MCODE analysis identified five hub modules, including 147 hub molecules. Those hub modules involved ribosomal proteins, RNA-binding proteins, cell-cycle progression-related proteins, proteasome subunits, and minichromosome maintenance proteins. These findings demonstrate that SILAC quantitative proteomics is an effective method to analyze ivermectin-treated cells, provide the first ivermectin-related proteomic profiling and molecular network alterations in human OC cells, and provide deeper insights into molecular mechanisms and functions of ivermectin to inhibit OC cells.

Keywords: biomarker; ivermectin; molecular network; ovarian cancer; quantitative proteomics; stable isotope labeling with amino acids in cell culture.

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