Energy metabolism abnormality is the hallmark in epithelial ovarian carcinoma (EOC). This study aimed to investigate energy metabolism pathway alterations and their regulation by the antiparasite drug ivermectin in EOC for the discovery of energy metabolism pathway-based molecular biomarker pattern and therapeutic targets in the context of predictive, preventive, and personalized medicine (PPPM) in EOC.
iTRAQ-based quantitative proteomics was used to identify mitochondrial differentially expressed proteins (mtDEPs) between human EOC and control mitochondrial samples isolated from 8 EOC and 11 control ovary tissues from gynecologic surgery of Chinese patients, respectively. Stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative proteomics was used to analyze the protein expressions of energy metabolic pathways in EOC cells treated with and without ivermectin. Cell proliferation, cell cycle, apoptosis, and important molecules in energy metabolism pathway were examined before and after ivermectin treatment of different EOC cells.
In total, 1198 mtDEPs were identified, and various mtDEPs were related to energy metabolism changes in EOC, with an interesting result that EOC tissues had enhanced abilities in oxidative phosphorylation (OXPHOS), Kreb’s cycle, and aerobic glycolysis, for ATP generation, with experiment-confirmed upregulations of UQCRH in OXPHOS; IDH2, CS, and OGDHL in Kreb’s cycle; and PKM2 in glycolysis pathways. Importantly, PDHB that links glycolysis with Kreb’s cycle was upregulated in EOC. SILAC-based quantitative proteomics found that the protein expression levels of energy metabolic pathways were regulated by ivermectin in EOC cells. Furthermore, ivermectin demonstrated its strong abilities to inhibit proliferation and cell cycle and promote apoptosis in EOC cells, through molecular networks to target PFKP in glycolysis; IDH2 and IDH3B in Kreb’s cycle; ND2, ND5, CYTB, and UQCRH in OXPHOS; and MCT1 and MCT4 in lactate shuttle to inhibit EOC growth.
Our findings revealed that the Warburg and reverse Warburg effects coexisted in human ovarian cancer tissues, provided the first multiomics-based molecular alteration spectrum of ovarian cancer energy metabolism pathways (aerobic glycolysis, Kreb’s cycle, oxidative phosphorylation, and lactate shuttle), and demonstrated that the antiparasite drug ivermectin effectively regulated these changed molecules in energy metabolism pathways and had strong capability to inhibit cell proliferation and cell cycle progression and promote cell apoptosis in ovarian cancer cells. The observed molecular changes in energy metabolism pathways bring benefits for an in-depth understanding of the molecular mechanisms of energy metabolism heterogeneity and the discovery of effective biomarkers for individualized patient stratification and predictive/prognostic assessment and therapeutic targets/drugs for personalized therapy of ovarian cancer patients.
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one-dimensional gel electrophoresis
- 3P medicine:
predictive, preventive, and personalized medicine (PPPM)
ATP binding cassette subfamily B member 1
ATP-binding cassette, subfamily B (MDR/TAP), member 1B
ATP-binding cassette subfamily G member 2
cytoplasmic aconitate hydratase
alcohol dehydrogenase 5 class III chi polypeptide
AKT serine/threonine kinase 1
APC regulator of WNT signaling pathway
amyloid beta precursor protein
ATP synthase membrane subunit c locus 1
ATP synthase F0 subunit 6
ATPase H+ transporting V0 subunit c
ATPase H+ transporting V1 subunit D
BRCA1 DNA repair associated
BRCA2 DNA repair associated
cancer antigen 125
Cell Counting Kit-8
chronic myeloid leukemia
cytochrome c oxidase subunit
cytochrome c oxidase copper chaperone COX17
cytochrome c oxidase subunit II
cytochrome c oxidase subunit 4I1
cytochrome c oxidase subunit 4I2
cytochrome c oxidase subunit 6C
cytochrome c oxidase subunit 7A2
cytochrome c oxidase subunit 7A2-like
cytochrome P450 family 3 subfamily A member 4
mitochondrially encoded cytochrome b
eukaryotic translation initiation factor 4A3
epithelial ovarian carcinoma
mitogen-activated protein kinase 3
electron transport chain
fluorescence-activated cell sorting
Food and Drug Administration
G0/G cell cycle phase
glycine receptor beta
the half maximal inhibitory concentration
isocitrate dehydrogenase (NADP(+)) 2
isocitrate dehydrogenase [NAD] subunit alpha, mitochondrial
isocitrate dehydrogenase (NAD(+)) 3 noncatalytic subunit beta
Ingenuity Pathway Analysis
isobaric tags for relative and absolute quantitation
Kyoto Encyclopedia of Genes and Genomes
karyopherin subunit beta 1
- Kreb’s cycle:
tricarboxylic acid cycle
liquid chromatography-tandem mass spectrometry
lactate dehydrogenase A
lactate dehydrogenase B
long noncoding RNAs
mitogen-activated protein kinase 1
mitogen-activated protein kinase 13
mitogen-activated protein kinase 3
solute carrier family 16 member 1
solute carrier family 16 member 4
malate dehydrogenase 2
- M r :
protein molecular weight
multidrug resistance-associated protein 1
mitochondrial ribosomal protein L41
mitochondrial ribosomal protein L41
mitochondrial ribosomal protein L49
mitochondrial ribosomal protein L51
mitochondrial ribosomal protein L52
mitochondrial ribosomal protein L53
mitochondrial ribosomal protein L54
mitochondrial ribosomal protein L55
mitochondrial ribosomal protein S10
mitochondrial ribosomal protein S12
mitochondrial ribosomal protein S15
mitochondrial ribosomal protein S17
mitochondrial ribosomal protein S21
mitochondrial ribosomal protein S23
mitochondrial ribosomal protein S33
mitochondrial ribosomal protein S6
mitochondrial ribosomal protein S9
mitochondrial differentially expressed proteins
mechanistic target of rapamycin kinase
mitochondrially encoded NADH dehydrogenase 1
mitochondrially encoded NADH dehydrogenase 2
mitochondrially encoded NADH dehydrogenase 5
NFKB inhibitor alpha
oxoglutarate dehydrogenase L
cyclin-dependent kinase inhibitor 1A
cyclin-dependent kinase inhibitor 1B
purinergic receptor P2X 4
purinergic receptor P2X 7
p21 (RAC1)-activated kinase 1
polyADP-ribose polymerase inhibitor
phosphoenolpyruvate carboxykinase [GTP], mitochondrial
pyruvate dehydrogenase complex
pyruvate dehydrogenase E1 subunit beta
- pI :
pyruvate kinase muscle
pyruvate kinase M2
predictive, preventive, and personalized medicine
mitochondrial cytochrome b-c1 complex subunit 6
quantitative real-time PCR
SURP and G-patch domain containing 1
reactive oxygen species
strong cation exchange chromatography
stable isotope labeling with amino acids in cell culture
small nucleolar RNA host gene 3
signal transducer and activator of transcription 3
succinate–CoA ligase GDP-forming subunit beta
tumor necrosis factor
translocase of outer mitochondrial membrane 20
ubiquinol-cytochrome c reductase hinge protein
voltage-dependent anion channel 1
Chan JK, Cheung MK, Husain A, Teng NN, West D, Whittemore AS, et al. Patterns and progress in ovarian cancer over 14 years. Obstet Gynecol. 2006;108:521–8. https://doi.org/10.1097/01.AOG.0000231680.58221.a7.
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66:7–30. https://doi.org/10.3322/caac.21332.
Gadducci A, Cosio S, Zola P, Landoni F, Maggino T, Sartori E. Surveillance procedures for patients treated for epithelial ovarian cancer: a review of the literature. Int J Gynecol Cancer. 2007;17:21–31. https://doi.org/10.1111/j.1525-1438.2007.00826.x.
Smith RA, Manassaram-Baptiste D, Brooks D, Doroshenk M, Fedewa S, Saslow D, et al. Cancer screening in the United States, 2015: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2015;65:30–54. https://doi.org/10.3322/caac.21261.
Buchtel KM, Vogel Postula KJ, Weiss S, Williams C, Pineda M, Weissman SM. FDA approval of PARP inhibitors and the impact on genetic counseling and genetic testing practices. J Genet Couns. 2018;27(1):131–9. https://doi.org/10.1007/s10897-017-0130-7.
Lord CJ, Ashworth A. PARP inhibitors: synthetic lethality in the clinic. Science. 2017;355:1152–8. https://doi.org/10.1126/science.aam7344.
Jacob F, Meier M, Caduff R, Goldstein D, Pochechueva T, Hacker N, et al. No benefit from combining HE4 and CA125 as ovarian tumor markers in a clinical setting. Gynecol Oncol. 2011;121:487–91. https://doi.org/10.1016/j.ygyno.2011.02.022.
Vanni S. Omics of prion diseases. Prog Mol Biol Transl Sci. 2017;150:409–31. https://doi.org/10.1016/bs.pmbts.2017.05.004.
Zhan X, Wang X, Long Y, Desiderio DM. Heterogeneity analysis of the proteomes in clinically nonfunctional pituitary adenomas. BMC Med Genet. 2014;7:69. https://doi.org/10.1186/s12920-014-0069-6.
Sala S, Van Troys M, Medves S, Catillon M, Timmerman E, Staes A, et al. Expanding the interactome of TES by exploiting TES modules with different subcellular localizations. J Proteome Res. 2017;16:2054–71. https://doi.org/10.1021/acs.jproteome.7b00034.
Sassano ML, van Vliet AR, Agostinis P. Mitochondria-associated membranes as networking platforms and regulators of cancer cell fate. Front Oncol. 2017;7:174. https://doi.org/10.3389/fonc.2017.00174.
Strickertsson JAB, Desler C, Rasmussen LJ. Bacterial infection increases risk of carcinogenesis by targeting mitochondria. Semin Cancer Biol. 2017;47:95–100. https://doi.org/10.1016/j.semcancer.2017.07.003.
Wang Y, Zhang J, Li B, He QY. Proteomic analysis of mitochondria: biological and clinical progresses in cancer. Expert Rev Proteomics. 2017;14:891–903. https://doi.org/10.1080/14789450.2017.1374180.
Mintz HA, Yawn DH, Safer B, Bresnick E, Liebelt AG, Blailock ZR, et al. Morphological and biochemical studies of isolated mitochondria from fetal, neonatal, and adult liver and from neoplastic tissues. J Cell Biol. 1967;34:513–23.
Chen M, Huang H, He H, Ying W, Liu X, Dai Z, et al. Quantitative proteomic analysis of mitochondria from human ovarian cancer cells and their paclitaxel-resistant sublines. Cancer Sci. 2015;106:1075–83. https://doi.org/10.1111/cas.12710.
Li N, Li H, Cao L, Zhan X. Quantitative analysis of the mitochondrial proteome in human ovarian carcinomas. Endocr Relat Cancer. 2018;25:909–31. https://doi.org/10.1530/erc-18-0243.
Li N, Zhan X, Zhan X. The lncRNA SNHG3 regulates energy metabolism of ovarian cancer by an analysis of mitochondrial proteomes. Gynecol Oncol. 2018;150:343–54. https://doi.org/10.1016/j.ygyno.2018.06.013.
Vyas S, Zaganjor E, Haigis MC. Mitochondria and cancer. Cell. 2016;166:555–66. https://doi.org/10.1016/j.cell.2016.07.002.
Li N, Zhan X. Signaling pathway network alterations in human ovarian cancers identified with quantitative mitochondrial proteomics. EPMA J. 2019;10:153–72. https://doi.org/10.1007/s13167-019-00170-5.
Kim A. Mitochondria in cancer energy metabolism: culprits or bystanders? Toxicol Res. 2015;31:323–30. https://doi.org/10.5487/tr.2015.31.4.323.
Warburg O. On the origin of cancer cells. Science. 1956;123:309–14.
Christofk HR, Vander Heiden MG, Harris MH, Ramanathan A, Gerszten RE, Wei R, et al. The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature. 2008;452:230–3. https://doi.org/10.1038/nature06734.
Birsoy K, Wang T, Chen WW, Freinkman E, Abu-Remaileh M, Sabatini DM. An essential role of the mitochondrial electron transport chain in cell proliferation is to enable aspartate synthesis. Cell. 2015;162:540–51. https://doi.org/10.1016/j.cell.2015.07.016.
Pavlides S, Whitaker-Menezes D, Castello-Cros R, Flomenberg N, Witkiewicz AK, Frank PG, et al. The reverse Warburg effect: aerobic glycolysis in cancer associated fibroblasts and the tumor stroma. Cell Cycle. 2009;8:3984–4001. https://doi.org/10.4161/cc.8.23.10238.
Bar-Or D, Carrick M, Tanner A 2nd, Lieser MJ, Rael LT, Brody E. Overcoming the Warburg effect: is it the key to survival in sepsis? J Crit Care. 2018;43:197–201. https://doi.org/10.1016/j.jcrc.2017.09.012.
Whitaker-Menezes D, Martinez-Outschoorn UE, Lin Z, Ertel A, Flomenberg N, Witkiewicz AK, et al. Evidence for a stromal-epithelial "lactate shuttle" in human tumors: MCT4 is a marker of oxidative stress in cancer-associated fibroblasts. Cell Cycle. 2011;10:1772–83. https://doi.org/10.4161/cc.10.11.15659.
Xu XD, Shao SX, Jiang HP, Cao YW, Wang YH, Yang XC, et al. Warburg effect or reverse Warburg effect? A review of cancer metabolism. Oncol Res Treat. 2015;38:117–22. https://doi.org/10.1159/000375435.
Chao TK, Huang TS, Liao YP, Huang RL, Su PH, Shen HY, et al. Pyruvate kinase M2 is a poor prognostic marker of and a therapeutic target in ovarian cancer. PLoS One. 2017;12:e0182166. https://doi.org/10.1371/journal.pone.0182166.
Suh DH, Kim HS, Kim B, Song YS. Metabolic orchestration between cancer cells and tumor microenvironment as a co-evolutionary source of chemoresistance in ovarian cancer: a therapeutic implication. Biochem Pharmacol. 2014;92:43–54. https://doi.org/10.1016/j.bcp.2014.08.011.
Chosidow O, Bernigaud C, Do-Pham G. High-dose ivermectin in malaria and other parasitic diseases: a new step in the development of a neglected drug. Parasite. 2018;25:33. https://doi.org/10.1051/parasite/2018039.
Omura S. A splendid gift from the earth: the origins and impact of the Avermectins (Nobel lecture). Angew Chem Int Ed Eng. 2016;55:10190–209. https://doi.org/10.1002/anie.201602164.
Crump A. Ivermectin: enigmatic multifaceted 'wonder' drug continues to surprise and exceed expectations. J Antibiot (Tokyo). 2017;70:495–505. https://doi.org/10.1038/ja.2017.11.
Drinyaev VA, Mosin VA, Kruglyak EB, Novik TS, Sterlina TS, Ermakova NV, et al. Antitumor effect of avermectins. Eur J Pharmacol. 2004;501:19–23. https://doi.org/10.1016/j.ejphar.2004.08.009.
Dou Q, Chen HN, Wang K, Yuan K, Lei Y, Li K, et al. Ivermectin induces cytostatic autophagy by blocking the PAK1/Akt axis in breast cancer. Cancer Res. 2016;76:4457–69. https://doi.org/10.1158/0008-5472.can-15-2887.
Zhu M, Li Y, Zhou Z. Antibiotic ivermectin preferentially targets renal cancer through inducing mitochondrial dysfunction and oxidative damage. Biochem Biophys Res Commun. 2017;492:373–8. https://doi.org/10.1016/j.bbrc.2017.08.097.
Wang J, Xu Y, Wan H, Hu J. Antibiotic ivermectin selectively induces apoptosis in chronic myeloid leukemia through inducing mitochondrial dysfunction and oxidative stress. Biochem Biophys Res Commun. 2018;497:241–7. https://doi.org/10.1016/j.bbrc.2018.02.063.
Kodama M, Kodama T. In vivo loss-of-function screens identify KPNB1 as a new druggable oncogene in epithelial ovarian cancer. Proc Natl Acad Sci U S A. 2017;114:E7301–e7310. https://doi.org/10.1073/pnas.1705441114.
Wang LN, Tong SW, Hu HD, Ye F, Li SL, Ren H, et al. Quantitative proteome analysis of ovarian cancer tissues using a iTRAQ approach. J Cell Biochem. 2012;113:3762–72. https://doi.org/10.1002/jcb.24250.
Lokich E, Singh RK, Han A, Romano N, Yano N, Kim K, et al. HE4 expression is associated with hormonal elements and mediated by importin-dependent nuclear translocation. Sci Rep. 2014;4:5500. https://doi.org/10.1038/srep05500.
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;3:243–6.
Bartolak-Suki E, Imsirovic J, Nishibori Y, Krishnan R, Suki B. Regulation of mitochondrial structure and dynamics by the cytoskeleton and mechanical factors. Int J Mol Sci. 2017;18. https://doi.org/10.3390/ijms18081812.
Schrader M, Costello J, Godinho LF, Islinger M. Peroxisome-mitochondria interplay and disease. J Inherit Metab Dis. 2015;38(4):681–702. https://doi.org/10.1007/s10545-015-9819-7.
Rezaul K, Wu L, Mayya V, Hwang SI, Han D. A systematic characterization of mitochondrial proteome from human T leukemia cells. Mol Cell Proteomics. 2005;4:169–81. https://doi.org/10.1074/mcp.M400115-MCP200.
Bragoszewski P, Wasilewski M, Sakowska P, Gornicka A, Bottinger L, Qiu J, et al. Retro-translocation of mitochondrial intermembrane space proteins. Proc Natl Acad Sci U S A. 2015;112:7713–8. https://doi.org/10.1073/pnas.1504615112.
Johnston IG, Williams BP. Evolutionary inference across eukaryotes identifies specific pressures favoring mitochondrial gene retention. Cell Syst. 2016;2:101–11. https://doi.org/10.1016/j.cels.2016.01.013.
Tekade RK, Sun X. The Warburg effect and glucose-derived cancer theranostics. Drug Discov Today. 2017;22:1637–53. https://doi.org/10.1016/j.drudis.2017.08.003.
Watanabe H, Takehana K, Date M, Shinozaki T, Raz A. Tumor cell autocrine motility factor is the neuroleukin/phosphohexose isomerase polypeptide. Cancer Res. 1996;56:2960–3.
Pavlides S, Vera I, Gandara R, Sneddon S, Pestell RG, Mercier I, et al. Warburg meets autophagy: cancer-associated fibroblasts accelerate tumor growth and metastasis via oxidative stress, mitophagy, and aerobic glycolysis. Antioxid Redox Signal. 2012;16:1264–84. https://doi.org/10.1089/ars.2011.4243.
Sullivan LB, Chandel NS. Mitochondrial reactive oxygen species and cancer. Cancer Metab. 2014;2:17. https://doi.org/10.1186/2049-3002-2-17.
Sakhuja S, Yun H, Pisu M, Akinyemiju T. Availability of healthcare resources and epithelial ovarian cancer stage of diagnosis and mortality among Blacks and Whites. J Ovarian Res. 2017;10:57. https://doi.org/10.1186/s13048-017-0352-1.
Min HY, Lee HY. Oncogene-driven metabolic alterations in cancer. Biomol Ther (Seoul). 2018;26:45–56. https://doi.org/10.4062/biomolther.2017.211.
Zhan X, Long Y, Lu M. Exploration of variations in proteome and metabolome for predictive diagnostics and personalized treatment algorithms: innovative approach and examples for potential clinical application. J Proteome. 2018;188:30–40. https://doi.org/10.1016/j.jprot.2017.08.020.
Qian S, Yang Y, Li N, Cheng T, Wang X, Liu J, et al. Prolactin variants in human pituitaries and pituitary adenomas identified with two-dimensional gel electrophoresis and mass spectrometry. Front Endocrinol (Lausanne). 2018;9:468. https://doi.org/10.3389/fendo.2018.00468.
Kobierzycki C, Piotrowska A, Latkowski K, Zabel M, Nowak-Markwitz E, Spaczynski M, et al. Correlation of pyruvate kinase M2 expression with clinicopathological data in ovarian cancer. Anticancer Res. 2018;38:295–300. https://doi.org/10.21873/anticanres.12221.
DeHart DN, Lemasters JJ, Maldonado EN. Erastin-like anti-Warburg agents prevent mitochondrial depolarization induced by free tubulin and decrease lactate formation in cancer cells. SLAS Discov. 2018;23:23–33. https://doi.org/10.1177/2472555217731556.
Yoshida GJ. Metabolic reprogramming: the emerging concept and associated therapeutic strategies. J Exp Clin Cancer Res. 2015;34:111. https://doi.org/10.1186/s13046-015-0221-y.
Godinot C, de Laplanche E, Hervouet E, Simonnet H. Actuality of Warburg's views in our understanding of renal cancer metabolism. J Bioenerg Biomembr. 2007;39:235–41. https://doi.org/10.1007/s10863-007-9088-8.
Lee M, Yoon JH. Metabolic interplay between glycolysis and mitochondrial oxidation: the reverse Warburg effect and its therapeutic implication. World J Biol Chem. 2015;6:148–61. https://doi.org/10.4331/wjbc.v6.i3.148.
Hernandez-Resendiz I, Roman-Rosales A, Garcia-Villa E, Lopez-Macay A, Pineda E, Saavedra E, et al. Dual regulation of energy metabolism by p53 in human cervix and breast cancer cells. Biochim Biophys Acta. 1853;2015:3266–78. https://doi.org/10.1016/j.bbamcr.2015.09.033.
Suganuma K, Miwa H, Imai N, Shikami M, Gotou M, Goto M, et al. Energy metabolism of leukemia cells: glycolysis versus oxidative phosphorylation. Leuk Lymphoma. 2010;51:2112–9. https://doi.org/10.3109/10428194.2010.512966.
Klepinin A, Ounpuu L, Guzun R, Chekulayev V, Timohhina N, Tepp K, et al. Simple oxygraphic analysis for the presence of adenylate kinase 1 and 2 in normal and tumor cells. J Bioenerg Biomembr. 2016;48:531–48.
Jin L, Feng X, Rong H, Pan Z, Inaba Y, Qiu L, et al. The antiparasitic drug ivermectin is a novel FXR ligand that regulates metabolism. Nat Commun. 2013;4:1937. https://doi.org/10.1038/ncomms2924.
Li N, Zhan X. Anti-parasite drug ivermectin can suppress ovarian cancer by regulating lncRNA-EIF4A3-mRNA axes. EPMA J. 2020;11:289–309. https://doi.org/10.1007/s13167-020-00209-y.
Zhan X, Giorgianni F, Desiderio DM. Proteomics analysis of growth hormone isoforms in the human pituitary. Proteomics. 2005;5:1228–41. https://doi.org/10.1002/pmic.200400987.
Zhan X, Li B, Zhan X, Schlüter H, Jungblut PR, Coorssen JR. Innovating the concept and practice of two-dimensional gel electrophoresis in the analysis of proteomes at the proteoform level. Proteomes. 2019;7(4):36. https://doi.org/10.3390/proteomes7040036.
Zhan X, Li N, Zhan X, Qian S. Revival of 2DE-LC/MS in proteomics and its potential for large-scale study of human proteoforms. Med One. 2018;3:e180008. https://doi.org/10.20900/mo.20180008.
Lu M. Wei Chen, Zhuang W, Zhan X. Label-free quantitative identification of abnormally ubiquitinated proteins as useful biomarkers for human lung squamous cell carcinomas. EPMA J. 2020;11(1):73–94. https://doi.org/10.1007/s13167-019-00197-8.
Janssens JP, Schuster K, Voss A. Preventive, predictive, and personalized medicine for effective and affordable cancer care. EPMA J. 2018;9(2):113–23. https://doi.org/10.1007/s13167-018-0130-1.
Samec M, Liskova A, Koklesova L, Samuel SM, Zhai K, Buhrmann C, et al. Flavonoids against the Warburg phenotype-concepts of predictive, preventive and personalised medicine to cut the Gordian knot of cancer cell metabolism. EPMA J. 2020;11(3):377–98. https://doi.org/10.1007/s13167-020-00217-y.
Golubnitschaja O, Flammer J. Individualised patient profile: clinical utility of Flammer syndrome phenotype and general lessons for predictive, preventive and personalised medicine. EPMA J. 2018;9(1):15–20. https://doi.org/10.1007/s13167-018-0127-9.
Lu M, Zhan X. The crucial role of multiomic approach in cancer research and clinically relevant outcomes. EPMA J. 2018;9(1):77–102. https://doi.org/10.1007/s13167-018-0128-8.
Li N, Zhan X. Identification of clinical trait-related lncRNA and mRNA biomarkers with weighted gene co-expression network analysis as useful tool for personalized medicine in ovarian cancer. EPMA J. 2019;10(3):273–90. https://doi.org/10.1007/s13167-019-00175-0.
Cheng T, Zhan X. Pattern recognition for predictive, preventive, and personalized medicine in cancer. EPMA J. 2017;8(1):51–60. https://doi.org/10.1007/s13167-017-0083-9.
The authors acknowledge the financial support from the Shandong First Medical University Talent Introduction Funds (to X.Z.) and the Hunan Provincial Hundred Talent Plan (to X.Z.).
The authors declare that they have no competing interests.
Consent for publication
All the patients were informed about the purposes of the study and, consequently, have signed their “consent of the patient.” All investigations conformed to the principles outlined in the Declaration of Helsinki and were performed with permission by the responsible Medical Ethics Committee of Xiangya Hospital, Central South University, China.
Abbreviations for all particular genes and proteins can be found at the following link: https://www.ncbi.nlm.nih.gov/gene/.
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Li, N., Li, H., Wang, Y. et al. 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 Journal (2020). https://doi.org/10.1007/s13167-020-00224-z
- Epithelial ovarian carcinoma
- Mitochondrial proteomics
- Warburg effect
- Reverse Warburg effect
- iTRAQ-based quantitative proteomics
- SILAC-based quantitative proteomics
- Energy metabolism pathway
- Aerobic glycolysis
- Kreb’s cycle
- Oxidative phosphorylation
- Lactate shuttle
- Molecular biomarker pattern
- Early diagnosis
- Prognostic assessment
- Predictive preventive personalized medicine (PPPM)