Open Access is an initiative that aims to make scientific research freely available to all. To date our community has made over 100 million downloads. It’s based on principles of collaboration, unobstructed discovery, and, most importantly, scientific progression. As PhD students, we found it difficult to access the research we needed, so we decided to create a new Open Access publisher that levels the playing field for scientists across the world. How? By making research easy to access, and puts the academic needs of the researchers before the business interests of publishers.
We are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including Nobel Prize winners and some of the world’s most-cited researchers. Publishing on IntechOpen allows authors to earn citations and find new collaborators, meaning more people see your work not only from your own field of study, but from other related fields too.
Ivermectin is an old, common, and classic anti-parasite drug, which has been found to have a broad-spectrum anti-cancer effect on multiple human cancers. This chapter will focus on the anti-cancer effects of ivermectin on ovarian cancer. First, ivermectin was found to suppress cell proliferation and growth, block cell cycle progression, and promote cell apoptosis in ovarian cancer. Second, drug pathway network, qRT-PCR, and immunoaffinity blot analyses found that ivermectin acts through molecular networks to target the key molecules in energy metabolism pathways, including PFKP in glycolysis, IDH2 and IDH3B in Kreb’s cycle, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation, and MCT1 and MCT4 in lactate shuttle, to inhibit ovarian cancer growth. Third, the integrative analysis of TCGA transcriptomics and mitochondrial proteomics in ovarian cancer revealed that 16 survival-related lncRNAs were mediated by ivermectin, SILAC quantitative proteomics analysis revealed that ivermectin extensively inhibited the expressions of RNA-binding protein EIF4A3 and 116 EIF4A3-interacted genes including those key molecules in energy metabolism pathways, and also those lncRNAs regulated EIF4A3-mRNA axes. Thus, ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer capability. Further, lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565), which is significantly associated with overall survival and clinicopathologic characteristics in ovarian cancer patients. These ivermectin-related molecular pattern alterations benefit for prognostic assessment and personalized drug therapy toward 3P medicine practice in ovarian cancer.
University Creative Research Initiatives Center, Shandong First Medical University, China
Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, China
Na Li
University Creative Research Initiatives Center, Shandong First Medical University, China
Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, China
*Address all correspondence to: yjzhan2011@gmail.com
1. Introduction
Ivermectin is chemically derived from avermectin that was discovered and isolated from soil in Jan by Omura in 1973 [1]. It was approved by Federal Drug Administration (FDA) to use for anti-parasite drug in 1987, which has significantly improved global public health as an antiparasite medicine [2]. In 2015, its discovers Drs. Omura and Campbell earned the Nobel Prize in physiology or medicine [2]. Recent years, many studies have demonstrated that ivermectin has extensive roles in anti-bacteria, anti-virus, and anticancer, except for its anti-parasite effects [3, 4, 5]. Its anticancer effect has been shown by many in vitro and in vivo experiments in multiple cancers, including ovarian cancer, breast cancer, triple-negative breast cancer, cervical cancer, lung cancer, gastric cancer, colon cancer, glioblastoma, melanoma, and leukemia [4, 6], with a wide safe and clinically reachable drug concentration of anticancer according to its pharmacokinetic range in treatment of a parasite-infected patient [7]. It offers a promising opportunity to develop a new anticancer drug via drug repositioning of this existing compound with confirmed clinical safety [8].
Ovarian cancer, a very common cancer with high mortality and poor survival in women [9, 10], are involved in multiple signaling pathway network changes [11, 12]. Many intracellular molecules and signaling pathways would be the targets of ivermectin [13]. Ivermectin have shown a potential addition role for ovarian cancer treatment. For example, ivermectin can improve the chemosensitivity of overran cancer via targeting Akt/mTOR signaling pathway [14], and can inhibit PAK1-dependent growth of ovarian cancer cells via blocking the oncogenic kinase PAK1 [15]. Ivermectin also acts as a PAK1 inhibitor to induce autophagy in breast cancer [16]. Ivermectin can enhance p53 expression and cytochrome C release, and reduce the expression levels of CDK2, CDK4, CDK6, Bcl-2, cyclin E, and cyclin D1 in glioblastoma, those promoted the cancer cell apoptosis [17]. Ivermectin can inhibit cancer cell proliferation via decreasing YAP1 protein expression in the Hippo pathway [18]. Ivermectin represses WNT-TCF pathway in WNT-TCF-dependent disease [19]. Ivermectin can promote TFE3 (Ser321) dephosphorylation to block the binding between TFE3 and 14-3-3, and induce TFE3 accumulation in the nucleus of human melanoma cells [20]. Moreover, ivermectin also affects other signaling pathway network in human cancers, including oxidative stress, mitochondrial dysfunction, angiogenesis, epithelial-mesenchymal transition, drug resistance, and stemness in tumor [6]. Thereby, ivermectin demonstrates the potential therapeutic efficiency in multiple malignant tumors.
This book chapter discussed the anti-cancer effects of ivermectin on ovarian cancer in the following aspects: (i) ivermectin inhibited cell proliferation and growth, blocked cell cycle progression, and promoted cell apoptosis in ovarian cancer [4, 21]; (ii) ivermectin inhibited ovarian cancer growth through molecular networks to target the key molecules in energy metabolism pathways, including glycolysis, Kreb’s cycle, oxidative phosphorylation, and lactate shuttle pathways [21]; (iii) Integrated omics revealed that ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer capability [4, 13]; and (iv) lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565) that is significantly related to overall survival and clinicopathologic characteristics of ovarian cancers [4].
2.1 Ovarian cancer cell biological behaviors affected by ivermectin
The normal ovarian cells IOSE80 and ovarian cancer cells TOV-21 and SKOV3 were treated with ivermectin to measure ivermectin-mediated ovarian cancer cell biological behavior changes. (i) IOSE80, TOV-21G, and SKOV3 were treated with ivermectin (0–60 μM) for 24 h, followed by the use of CCK8 to measure the IC50 of ivermectin in each cell. (ii) TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, followed by the use of EdU assay to measure DNA synthesis in each cell. (iii) TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 48 h, followed by clonogenic assay to measure the in vitro effects of ivermectin in each cell. (iv)TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, followed by flow cytometry to measure cell cycle and cell apoptosis changes in each cell. (v) When A2780 and TOV-21G seeded in 6-well plates were grown to approximately 90% confluency, followed by the use of 10-μl pipette tip to make an artificial wound, and then treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, and measure the wound healing. The relative percentage of wound healing = (the width of wound at 0 h − the width of wound at 24 h)/the width of wound at 0 h. The detailed procedure was described previously [4, 21].
2.2 Ivermectin-mediated pathway network predicted by ingenuity pathway analysis
The classical pathway network analysis software, Ingenuity Pathway Analysis (IPA) (http://www.ingenuity.com) [5] was used to predict ivermectin-related potential target molecules in three energy metabolism pathways. For this analysis, ivermectin and target genes in three energy metabolism pathways are all input into the IPA tool. The detailed procedure was described previously [21]. The predicted ivermectin-mediated targets in energy metabolism pathways were the basis for further experiment verification.
2.3 Ivermectin-mediated target molecule changes in energy metabolism pathways verified at the mRNA and protein levels
TOV-21G and SKOV3 were treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) for 24 h, and 48 h. At the 24 h time point, the RNAs were extracted for quantitative real-time PCR (qRT-PCR) analysis to measure the mRNA expression of target molecules (CS, PDHB, IDH2, IDH3A, IDH3B, PFKP, PKM, MCT1, MCT4, OGDHL, ND2, ND5, CYTB, and UQCRH) in energy metabolism pathways. At the 48 h time point, the proteins were extracted for Western blot analysis to measure the protein expression of target molecules (CS, PDHB, IDH2, IDH3A, IDH3B, PFKP, PKM, MCT1, MCT4, OGDHL, ND2, ND5, CYTB, and UQCRH) in energy metabolism pathways. The detailed procedure was described previously [21].
2.4 Ivermectin-mediated proteome changes in ovarian cancer identified by SILAC-based quantitative proteomics
SILAC (stable isotope labeling with amino acids in cell culture)-based quantitative proteomics was used to identified differentially expressed proteins in ovarian cancer TOV-21G treated with and without 20 μM ivermectin [13]. The identified differentially expressed proteins were used for molecular network and signaling pathway analyses to obtain ivermectin-related signaling pathway networks [13]. The detailed procedure was described previously [13].
2.5 Transcriptomics and clinical data of ovarian cancer patients extracted from TCGA database
Level 3 RNA-seq V2 transcriptomics data of 411 OC patients were extracted from The Cancer Genome Atlas (TCGA) data portal (http://cancergenome.nih.gov/) with the corresponding clinical data, including cancer status (with tumor or tumor-free), clinical stage (stages IIA, IIB, IIC, IIIA, IIIB, IIIC, and IV), neoplasm histologic grade (G1, G2, G3, G4, and GX), anatomic neoplasm subdivision (right, left, and bilateral), age at initial pathologic diagnosis (aged from 30 to 87), lymphatic invasion (yes/no), primary therapy outcome success (complete remission/response, partial remission/response, progressive disease, and stable disease), additional radiation therapy (yes/no), survival time (days), tumor residual disease (no macroscopic disease, 1–10 mm, 11–20 mm, and > 20 mm), survival status (0 = alive, and 1 = dead), and PANCAN (Pan-Cancer Atlas). TANRIC (http://ibl.mdanderson.org/tanric/design/basic/index.html) was used for survival analysis of lncRNAs in ovarian cancer. The large-scale CLIP-Seq data with starBasev 2.0 (http://starbase.sysu.edu.cn/mirCircRNA.php) was used to predict the EIF4A3-binding mRNAs. The Kaplan–Meier method relative to the log-rank test was used for survival analysis of mRNAs in ovarian cancers. Statistical significance was set as p value <0.05. GenCLiP 3 (http://ci.smu.edu.cn/genclip3/analysis.php) was used for pathway enrichment analysis of the association of EIF4A3-binding mRNAs and patient survival rates. The detailed procedure was described previously [4].
2.6 Ivermectin-related lncRNAs verified with qRT-PCR
TRizol® Reagent (Invitrogen, CA, USA) was used to extract total RNAs of cells TOV21G and A2780 treated with different concentration of ivermectin (0 μM, 10 μM, 20 μM, and 30 μM). The extracted total RNAs was reversely transcribed into cDNAs for qRT-PCR analysis of each lncRNA expression, including KIF9-AS1, HCG15, PDCD4-AS1, ZNRF3-AS1, ZNF674-AS1, LINC00565, SOS1-IT1, WWTR1-AS1, PLCH1-AS1, LINC00517, SNHG3, STARD13-IT1, AL109767.1, HOXC-AS3, LEMD1-AS1, and LBX2-AS1. Beta-actin was set as internal control for qRT-PCR analysis. The detailed procedure was described previously [4].
2.7 LncRNA-based prognostic signature optimized with lasso regression for ovarian cancers
Lasso regression means least absolute shrinkage and selection operator regression, which was used to optimize and construct lncRNA-based prognostic signature, and the glmnet R package was used to measure the association between survival risk and lncRNA signature in ovarian cancers. Moreover, univariate and multivariate Cox regression, and Kaplan–Meier method were used to identify overall survival-related clinical characteristics described above in ovarian cancers to confirm the established lncRNA-based prognostic model. The detailed procedure was described previously [4].
2.8 Statistical significance
Benjamini–Hochberg (FDR) for multiple testing was used to correct the p values of IPA, GO, and KEGG analyses. Student’s t test was used for qRT-PCR and western blot data (p < 0.05) with data expression of mean ± SD (n = 3).
3.1 Effects of ivermectin on biological behaviors of ovarian cancers
First, CCK8 experiments were used to measure cell proliferation changes between ovarian cancer cells (SKOV3; TOV-21G) and control cells (IOSE80), treated with and without ivermectin (Figure 1). Each type of cells was significantly inhibited by ivermectin with a dose-dependent relationship. The IC50 (half maximal inhibitory concentration) was 29.46 μM for IOSE80 cells, 20.85 μM for SKOV3, and 22.54 μM for TOV-21G (Figure 1A). The IC50 of ovarian cancers were significantly lower than the normal controls. Further, 20 μM ivermectin - slightly lower than IC50 – can effectively inhibit ovarian cancer proliferation (Figure 1B and C) [21]. For in vivo human trial, the highest FDA-approved ivermectin dose was 200 μg/kg for human use in anti-parasite; however, a study on 68 human subjects found that the dose up to 2,000 μg/kg still worked well without CNS toxicity. The mean area under the curve ratios for the 30 and 60 mg doses were 1.24 and 1.40, indicating a minimal accumulation of ivermectin [5, 22]. These data demonstrate that ivermectin was a well-tolerated safe drug. Second, EdU cell proliferation experiments also confirmed that ivermectin significantly suppressed cell proliferation of ovarian cancers with a time-dependent relationship (Figure 1D-F) [21]. Third, Clonogenic survival experiments confirmed that ivermectin effectively inhibited the formation of cell clones with a time-dependent relationship (Figure 1G-H) [21]. Moreover, 10 μM ivermectin cannot effectively inhibit cell proliferation of ovarian cancers, 30 μM ivermectin caused cell death of ovarian cancers, and 20 μM ivermectin was a suitable dose to significantly suppress growth and proliferation of ovarian cancer cells.
Figure 1.
Ivermectin suppressed ovarian cancer cell proliferation in vitro, measured with CCK8 (A-C), EdU (D-F), and clonogenic experiments (G, H). Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.2 Effects of ivermectin on cell cycle and apoptosis in ovarian cancers
Flow cytometry was used to measure cell cycle and apoptosis of ovarian cancer cells treated with and without ivermectin (Figure 2) [21]. First, the cell proportion was significantly increased in G0/G phase, decreased in S phase, and no change in G2/M phase in the high concentration (20- and 30-μM) compared to the low concentration (0- and 10-μM) of ivermectin groups (Figure 2A-C). Second, compared to control group, the proportion of apoptosis cells was significantly increased in different concentration of ivermectin groups, with a dose-dependent relationship (Figure 2D and E).
Figure 2.
Ivermectin blocked cell cycle progression (A, B, C) and promoted cell apoptosis (D, E) of ovarian cancer cells. Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.3 Effect of ivermectin on cell migration in ovarian cancers
Wound healing experiment was used to test the effect of ivermectin on cell migration of ovarian cancer cells. The results showed that cell migration was significantly inhibited in cells A2780 and TOV-21G after treatment of 20 μM and 30 μM ivermectin (Figure 3) [4].
Figure 3.
Ivermectin inhibited cell migration of ovarian cancer cells TOV-21G relative to control cells A2780, analyzed with wound healing experiments. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
3.4 Pharmaceutic molecular network predicted the association of ivermectin with ROS and energy metabolism
Ingenuity Pathway Analysis (IPA) was used for pharmaceutic molecular network analysis of ivermectin. The results showed that ivermectin was significantly associated with reactive oxygen species (ROS) and energy metabolism pathways, including pyruvate kinase muscle (PKM), oxoglutarate dehydrogenase L (OGDHL), mitochondrially encoded NADH dehydrogenase 2 (ND2), mitochondrially encoded NADH dehydrogenase 5 (ND5), CytB, and ubiquinolcytochrome c reductase hinge protein (UQCRH) (Figure 4) [21]. Moreover, ivermectin directly regulated Rbp, CYP3A4, P2RX7, ABCB1, GLRB, ABCG2, P2RX4, P glycoprotein, Abcb1b, strychnine, cytokine, and insulin; and indirectly regulated TNF, APP, MAPK1, ERK1/2, MAPK3, MAPK13, ROS, NFKBIA, testosterone, and STAT3 [21].
Figure 4.
Pharmaceutic molecular network predicted the associations of ivermectin with reactive oxygen species (ROS) and energy metabolism pathways (A) Disease and functional analysis of ivermectin based on IPA database (B-G). The association of ivermectin with PKM (B), OGDHL (C), ND2 (D), UQCRH (E), ND5 (F), and CYTB (G). Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.5 SILAC quantitative proteomics revealed the effects of ivermectin on key proteins in energy metabolism pathways in ovarian cancer cells
SILAC quantitative proteomics was used to detect, identify, and quantify the key protein alterations in energy metabolic pathways in ovarian cancer cells treated with (SILAC: H) and without (SILAC: L) 20 μM ivermectin for 24 h (Table 1) [21]. This study found that ivermectin significantly reduced (i) the expression levels of glycolysis-related enzymes, including ADH5, ENO1, GPI, GAPDH, LDHA, LDHB, PFKP, and PKM; (ii) the Kreb’s cycle-related enzymes, including ACON, PCK2, PDHB, MDH2, CS, IDH2, IDH3A, IDH3B, SUCLG2, and OGDHL; (iii) the OXPHOS-related enzymes, including CYTB, UQCRH, COX17, COX1, COX6C, COX4I1, COX2, COX7A2L, COX7A2, ATP6V0C, and ATP6; and (iv) the lactate shuttle proteins MCT1 and MCT4, in ovarian cancer cells.
Pathway
Protein ID
Gene name
Protein name
Q-value
Intensity H
Intensity L
Ratio H/L
Glycolysis pathway
PFKAP
PFKP
ATP-dependent 6-phosphofructokinase, platelet type
cDNA FLJ53399, highly similar to Monocarboxylate transporter 1
0.00E+00
23799000
115420000
0.53
MOT4
MCT4
Monocarboxylate transporter 4
0.00E+00
818320000
2103700000
0.38
Table 1.
SILAC quantitative proteomics revealed the protein expression changes of key molecules in energy metabolic pathways in ovarian cancer cells TOV-21G treated with (SILAC: H) and without (SILAC: L) 20 μM ivermectin for 24 h. - means the protein expressed in L group but not in H group. + means the protein expressed in H group but not in L group. /means the protein with expressed value 0 in both H and L groups. Ratio H/L means the ratio of the ivermectin-treated group (SILAC: H) to the no ivermectin-treated group (SILAC: L). Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.6 RT-qPCR and Western blot confirmed the effects of ivermectin on the key molecules in energy metabolism pathways at the mRNA and protein levels
RT-qPCR analysis confirmed the mRNA expression alterations of key molecules in energy metabolism pathways in ovarian cancer cells treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) (Figure 5), and further western blot analysis confirmed the protein expression alterations of those corresponding key molecules (Figure 6) [21]. These key molecules included PFKP, and PKM in glycolysis pathway, PDHB, CS, IDH2, IDH3A, IDH3B, and OGDHL in Kreb’s cycle pathway, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation pathway, MCT1, and MCT4 in lactate shuttle. These results clearly showed that ivermectin regulated energy metabolism pathways in ovarian cancer cells.
Figure 5.
RT-qPCR confirmed the effects of ivermectin on the mRNA expressions of key molecules in the energy metabolism pathways in ovarian cancer cells (a-f). The effects of different concentration of ivermectin (0, 10, 20, and 30 μM) on mRNA expressions of PFKP, PKM, CS, PDHB, IDH2, IDH3A, IDH3B, OGDHL, ND5, ND2, CYTB, UQCRH, MCT1, and MCT4. n = 3. *p < 0.05, **p < 0.01, ***p < 0.001. Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
Figure 6.
Western blot confirmed the effects of ivermectin on the protein expressions of key molecules in the energy metabolism pathways in ovarian cancer cells. n = 3. *p < 0.05, **p < 0.01, ***p < 0.001. Reproduced from Li et al. [21], with copyright permission from nature springer publisher, copyright 2020.
3.7 Ivermectin regulated lncRNA-EIF4A3-mRNA axis in ovarian cancer cells
Our quantitative mitochondrial proteomics data identified 1198 differentially mitochondrial proteins (mtDEPs) in human ovarian cancer tissues relative to control ovary tissues [11, 23]. Six RNA-binding proteins among those 1198 mtDEPs were identified, including EIF4A3, SFRS1, IGF2BP2, UPF1, C22ORF28, and EWSR1. Of them, only EIF4A3 was predicted to bind to the mRNA of key molecules in energy metabolism pathways. Further, Starbase predicted 3636 EIF4A3-biding mRNAs in various cancer; and of them, 306 EIF4A3-binding mRNAs was associated with ovarian cancer survival rate. Among 306 EIF4A3-binding mRNAs, the protein expressions of 116 EIF4A3-binding mRNAs and EIF4A3 were found to be inhibited by ivermectin, identified by SILAC quantitative proteomics in ovarian cancer cells treated with and without ivermectin (Table 2) [4].
Mediator of RNA polymerase II transcription subunit 20
MED20
0.01
2
0
18220000
NaN
H3BR38
Target of rapamycin complex subunit LST8
MLST8
0
3
0
13473000
NaN
P52815
39S ribosomal protein L12, mitochondrial
MRPL12
0.01
2
0
0
NaN
A0A024R1I3
Pyridoxal phosphate phosphatase
PDXP
0
6
0
40714000
NaN
A0A2R8YDS2
Ras/Rap GTPase-activating protein SynGAP
SYNGAP1
0
2
0
18400000
NaN
J3KQA0
Synaptotagmin-1
SYT1
0
26
0
339450000
NaN
Q5W0C6
Torsin-3A
TOR3A
0
3
0
16493000
NaN
B4DSK7
Mediator of RNA polymerase II transcription subunit 1
MED1
0
2
0
14356000
NaN
Q99549
M-phase phosphoprotein 8
MPHOSPH8
0
12
0
15782000
NaN
Table 2.
The proteins of 116 EIF4A3-biding mRNAs and EIF4A3 were inhibited by ivermectin, identified with SILAC quantitative proteomics in ovarian cancer cells treated with (H) and without (L) ivermectin. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
Moreover, TCGA transcriptomics analysis found that 16 lncRNAs had binding sites with EIF4A3 and associated with ovarian cancer survival rate, including SNHG3, HCG15, PDCD4-AS1, KIF9-AS1, ZNRF3-AS1, ZNF674-AS1, LINC00565, SOS1-IT1, WWTR1-AS1, PLCH1-AS1, LINC00517, STARD13-IT1, LEMD1-AS1, AL109767.1, HOXC-AS3, and LBX2-AS1 [23]. Further, RT-qPCR analysis of these 16 lncRNA expressions in ovarian cancer cells treated with ivermectin (0 μM, 10 μM, 20 μM, and 30 μM) compared to control cells, which found 9 lncRNAs (PDCD4-AS1, ZNRF3-AS1, HCG15, KIF9-AS1, LINC00565, ZNF674-AS1, AL109767.1, SOS1-IT1, and LBX2-AS1) were significantly affected by ivermectin (Figure 7) [4].
Figure 7.
RT-qPCR analysis revealed the effects of ivermectin on lncRNAs in ovarian cancers relative to control cells. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
These findings clearly demonstrated that ivermectin regulated lncRNA-EIF4A3-mRNA axis in ovarian cancer cells, and these mRNAs included the key molecules in energy metabolism pathways in ovarian cancer cells.
3.8 The prognostic model of ivermectin-related three-lncRNA signature for ovarian cancers identified and optimized by lasso regression
Based on those nine ivermectin-mediated lncRNAs in ovarian cancers, survival analysis and lasso regression were used to identify and optimize the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565) (Figure 8) [4]. This prognostic model was significantly related to overall survival and clinicopathologic characteristics in ovarian cancer patients [4], which might benefit for prognostic assessment and personalized drug therapy toward 3P medicine practice in ovarian cancer.
Figure 8.
Lasso regression identified and optimized the prognostic model of ivermectin-related three-lncRNA signature in ovarian cancers. (A and B). Lasso regression complexity is controlled by lambda using the glmnet R package. (C). Overall survival analysis of three-lncRNA signature between high-risk and low-risk groups. Reproduced from Li et al. [4], with copyright permission from nature springer publisher, copyright 2020.
Ivermectin, as an old, common, and classic anti-parasite drug, has demonstrated its effective in vitro anti-cancer efficiency for ovarian cancer. Ivermectin significantly inhibited cell proliferation, growth and migration, blocked cell cycle progression, and promoted cell apoptosis of human ovarian cancer cells. Drug pathway network analysis of ivermectin revealed that it was significantly related to the key molecules of four energy metabolism pathways, and RT-qPCR and immunoaffinity blot analyses found that ivermectin significantly regulated these key molecules for those energy metabolism pathways, including PFKP in glycolysis, IDH2 and IDH3B in Kreb’s cycle, ND2, ND5, CYTB, and UQCRH in oxidative phosphorylation, and MCT1 and MCT4 in lactate shuttle. The integrative analysis of TCGA transcriptomics and mitochondrial proteomics in ovarian cancer revealed that 16 survival-related lncRNAs were mediated by ivermectin, which were further confirmed with RT-qPRC in human ovarian cancer cells. SILAC quantitative proteomics analysis revealed that the expressions of RNA-binding protein EIF4A3 and 116 EIF4A3-interacted genes were extensively inhibited by ivermectin. Those 116 EIF4A3-interacted proteins included those key molecules in four energy metabolism pathways, and those lncRNAs regulated EIF4A3-mRNA axes. Thus, ivermectin mediated lncRNA-EIF4A3-mRNA axes in ovarian cancer to exert its anticancer activities. Moreover, lasso regression identified the prognostic model of ivermectin-related three-lncRNA signature (ZNRF3-AS1, SOS1-IT1, and LINC00565), which was significantly associated with overall survival and clinicopathologic characteristics of ovarian cancer patients. These ivermectin-related molecular pattern alterations benefit for prognostic assessment and personalized drug therapy in the context of 3P medicine practice in ovarian cancer.
Moreover, one must realize that these achieved data about the anti-cancer activities of ivermectin in ovarian cancers are derived from the in vitro cell models. It is necessary to expand it into the in vivo animal experiments and pre-clinical and clinical experiments for its real application in ovarian cancers.
The authors acknowledge the financial supports from the Shandong First Medical University Talent Introduction Funds (to X.Z.), the Hunan Provincial Hundred Talent Plan (to X.Z.), and the grants from China “863” Plan Project (Grant No. 2014AA020610-1 to XZ).
X.Z. conceived the concept, designed the manuscript, wrote and critically revised the manuscript, coordinated and was responsible for the correspondence work and financial support. N.L. participated in preparing figures, and partial literature analysis.
stable isotope labeling with amino acids in cell culture
TCGA
The Cancer Genome Atlas
References
1.Burg RW, Miller BM, Baker EE, et al. Avermectins, new family of potent anthelmintic agents: producing organism and fermentation. Antimicrob Agents Chemother 1979; 15(3): 361–367
2.Crump A. Ivermectin: enigmatic multifaceted 'wonder' drug continues to surprise and exceed expectations. J Antibiot (Tokyo) 2017; 70(5): 495–505
3.Laing R, Gillan V, Devaney E. Ivermectin—old drug, new tricks? Trends Parasitol 2017; 33(6): 463–472
4.Li N, Zhan X. Anti-parasite drug ivermectin can suppress ovarian cancer by regulating lncRNA-EIF4A3-mRNA axes. EPMA J 2020; 11(2): 289–309
5.Li N, Zhao L, Zhan X. Quantitative proteomics reveals a broad-spectrum antiviral property of ivermectin, benefiting for COVID-19 treatment. J Cell Physiol 2020. DOI: 10.1002/jcp.30055
6.Liu J, Zhang K, Cheng L, Zhu H, Xu T. Progress in understanding the molecular mechanisms underlying the antitumour effects of ivermectin. Drug Des Devel Ther 2020; 14: 285–296
7.Juarez M, Schcolnik-Cabrera A, Duenas-Gonzalez A. The multitargeted drug ivermectin: from an antiparasitic agent to a repositioned cancer drug. Am J Cancer Res 2018; 8(2): 317–331
8.Kobayashi Y, Banno K, Kunitomi H, Tominaga E, Aoki D. Current state and outlook for drug repositioning anticipated in the field of ovarian cancer. J Gynecol Oncol 2019; 30(1): e10
9.Triarico S, Capozza MA, Mastrangelo S, Attinà G, Maurizi P, Ruggiero A. Gynecological cancer among adolescents and young adults (AYA). Ann Transl Med 2020; 8(6): 397
10.Li N, Zhan X. Mass spectrometry-based mitochondrial proteomics in human ovarian cancer. Mass Spectrom Rev 2020; 39(5–6): 471–498
11.Li N, Zhan X. Signaling pathway network alterations in human ovarian cancers identified with quantitative mitochondrial proteomics. EPMA J 2019; 10(2): 153–172
12.Li N, Li H, Cao L, Zhan X. Quantitative analysis of the mitochondrial proteome in human ovarian carcinomas. Endocr Relat Cancer 2018; 25(10): 909–931
13.Li N, Li J, Desiderio DM, Zhan X. SILAC quantitative proteomics analysis of vermectin-related proteomic profiling and molecular network alterations in human ovarian cancer cells. J Mass Spectrom 2020; e4659. DOI: 10.1002/jms.4659
14.Zhang X, Qin T, Zhu Z, et al. Ivermectin augments the in vitro and in vivo efficacy of cisplatin in epithelial ovarian cancer by suppressing Akt/mTOR signaling. Am J Med Sci 2020; 359(2): 123–129
15.Hashimoto H, Messerli SM, Sudo T, Maruta H. Ivermectin inactivates the kinase PAK1 and blocks the PAK1-dependent growth of human ovarian cancer and NF2 tumor cell lines. Drug Discov Ther 2009; 3(6): 243–246
16.Dou Q, Chen HN, Wang K, et al. Ivermectin induces cytostatic autophagy by blocking the PAK1/Akt axis in breast cancer. Cancer Res 2016; 76(15): 4457–4469
17.Song D, Liang H, Qu B, et al. Ivermectin inhibits the growth of glioma cells by inducing cell cycle arrest and apoptosis in vitro and in vivo. J Cell Biochem 2019; 120(1): 622–633
18.Nambara S, Masuda T, Nishio M, et al. Antitumor effects of the antiparasitic agent ivermectin via inhibition of Yes-associated protein 1 expression in gastric cancer. Oncotarget 2017; 8(64): 107666–107677
19.Melotti A, Mas C, Kuciak M, Lorente-Trigos A, Borges I, Ruiz i Altaba A. The river blindness drug ivermectin and related macrocyclic lactones inhibit WNT-TCF pathway responses in human cancer. EMBO Mol Med 2014; 6(10): 1263–1278
20.Slade L, Pulinilkunnil T. The MiTF/TFE family of transcription tactors: master regulators of organelle signaling, metabolism, and stress adaptation. Mol Cancer Res 2017; 15(12):1637–1643
21.Li N, Li H, Wang Y, Cao L, Zhan X. Quantitative proteomics revealed energy metabolism pathway alterations in human epithelial ovarian carcinoma and their regulation by the antiparasite drug ivermectin: data interpretation in the context of 3P medicine. EPMA J 2020; 11: 661–694
22.Guzzo CA, Furtek CI, Porras AG, Chen C, Tipping R, Clineschmidt CM, Lasseter KC. Safety, tolerability, and pharmacokinetics of escalating high doses of ivermectin in healthy adult subjects. J Clin Pharmacol. 2002; 42(10): 1122–1133
23.Li N, Zhan X, Zhan X. The lncRNA SNHG3 regulates energy metabolism of ovarian cancer by an analysis of mitochondrial proteomes. Gynecol Oncol. 2018; 150: 343–354
Written By
Xianquan Zhan and Na Li
Submitted: December 14th, 2020Reviewed: December 19th, 2020Published: January 13th, 2021
Open access peer-reviewed chapter
