Application of Metabonomics in the Treatment and Prognosis of Common Gynecological Tumors

doi:10.12280/gjfckx.20220026

Abstract

Abstract:

Ovarian cancer, endometrial cancer and cervical cancer are three major malignancies in gynecology. The prognosis of patients with gynecologic tumors has been improved significantly with the development of comprehensive treatments such as surgery, radiotherapy and chemotherapy, however, due to the lack of obvious symptoms and accurate diagnosis at early stages, there are still a considerable proportion of patients with poor prognosis life-threatening. Therefore, it is very important to identify new therapeutic targets and predictive markers for prognosis. Metabolomics is a popular research method in the field of cancer research. Its theoretical basis is that tumors have different metabolic characteristics from normal tissues, which are closely related to biological phenotypes. Through comprehensive analysis of endogenous metabolites in biological systems, metabolomics elucidates the remodeling mechanism of some key biochemical pathways during tumor development and progression, and provides analytical and precise intervention. This paper reviews the application of metabonomics in the treatment and prognosis of gynecological tumors, which is expected to provide potential targets for personalized and precise treatment of gynecological tumors, and provide important reference for selecting biomarkers for prognosis of gynecological tumors.

Key words: Ovarian neoplasms, Endometrial neoplasms, Uterine cervical neoplasms, Metabolomics, Therapy, Prognosis

PING Quan-hong, LI Na, HU Yuan-jing. Application of Metabonomics in the Treatment and Prognosis of Common Gynecological Tumors[J]. Journal of International Obstetrics and Gynecology, 2022, 49(4): 361-365.

References 42

[1]	Vsiansky V, Svobodova M, Gumulec J, et al. Prognostic Significance of Serum Free Amino Acids in Head and Neck Cancers[J]. Cells, 2019, 8(5):428. doi: 10.3390/cells8050428. doi: 10.3390/cells8050428
[2]	Wang YP, Li JT, Qu J, et al. Metabolite sensing and signaling in cancer[J]. J Biol Chem, 2020, 295(33):11938-11946. doi: 10.1074/jbc.REV119.007624. doi: 10.1074/jbc.REV119.007624
[3]	Kuroki L, Guntupalli SR. Treatment of epithelial ovarian cancer[J]. BMJ, 2020, 371:m3773. doi: 10.1136/bmj.m3773. doi: 10.1136/bmj.m3773
[4]	Lertkhachonsuk AA, Buranawongtrakoon S, Lekskul N, et al. Serum CA19-9, CA-125 and CEA as tumor markers for mucinous ovarian tumors[J]. J Obstet Gynaecol Res, 2020, 46(11):2287-2291. doi: 10.1111/jog.14427. doi: 10.1111/jog.14427
[5]	Tiss A, Timms JF, Smith C, et al. Highly accurate detection of ovarian cancer using CA125 but limited improvement with serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling[J]. Int J Gynecol Cancer, 2010, 20(9):1518-1524. pmid: 21370595
[6]	Ahmed-Salim Y, Galazis N, Bracewell-Milnes T, et al. The application of metabolomics in ovarian cancer management: a systematic review[J]. Int J Gynecol Cancer, 2021, 31(5):754-774. doi: 10.1136/ijgc-2020-001862. doi: 10.1136/ijgc-2020-001862 pmid: 33106272
[7]	Terry KL, Schock H, Fortner RT, et al. A Prospective Evaluation of Early Detection Biomarkers for Ovarian Cancer in the European EPIC Cohort[J]. Clin Cancer Res, 2016, 22(18):4664-4675. doi: 10.1158/1078-0432.CCR-16-0316. doi: 10.1158/1078-0432.CCR-16-0316
[8]	Peng H, Wang Y, Luo W. Multifaceted role of branched-chain amino acid metabolism in cancer[J]. Oncogene, 2020, 39(44):6747-6756. doi: 10.1038/s41388-020-01480-z. doi: 10.1038/s41388-020-01480-z
[9]	Nguyen T, Kirsch BJ, Asaka R, et al. Uncovering the Role of N-Acetyl-Aspartyl-Glutamate as a Glutamate Reservoir in Cancer[J]. Cell Rep, 2019, 27(2):491-501.e6. doi: 10.1016/j.celrep.2019.03.036. doi: S2211-1247(19)30352-3 pmid: 30970252
[10]	Wu JY, Huang TW, Hsieh YT, et al. Cancer-Derived Succinate Promotes Macrophage Polarization and Cancer Metastasis via Succinate Receptor[J]. Mol Cell, 2020, 77(2):213-227.e5. doi: 10.1016/j.molcel.2019.10.023. doi: 10.1016/j.molcel.2019.10.023
[11]	Zhang J, Zhang Q, Yang Y, et al. Association Between Succinate Receptor SUCNR1 Expression and Immune Infiltrates in Ovarian Cancer[J]. Front Mol Biosci, 2020, 7:150. doi: 10.3389/fmolb.2020.00150. doi: 10.3389/fmolb.2020.00150
[12]	Xia L, Zhang H, Wang X, et al. The Role of Succinic Acid Metabolism in Ovarian Cancer[J]. Front Oncol, 2021, 11:769196. doi: 10.3389/fonc.2021.769196. doi: 10.3389/fonc.2021.769196
[13]	Muys BR, Sousa JF, Plaça JR, et al. miR-450a Acts as a Tumor Suppressor in Ovarian Cancer by Regulating Energy Metabolism[J]. Cancer Res, 2019, 79(13):3294-3305. doi: 10.1158/0008-5472.CAN-19-0490. doi: 10.1158/0008-5472.CAN-19-0490
[14]	Gan C, Huang X, Wu Y, et al. Untargeted metabolomics study and pro-apoptotic properties of B-norcholesteryl benzimidazole compounds in ovarian cancer SKOV3 cells[J]. J Steroid Biochem Mol Biol, 2020, 202:105709. doi: 10.1016/j.jsbmb.2020.105709. doi: 10.1016/j.jsbmb.2020.105709
[15]	Yang J, Zaman MM, Vlasakov I, et al. Adipocytes promote ovarian cancer chemoresistance[J]. Sci Rep, 2019, 9(1):13316. doi: 10.1038/s41598-019-49649-1. doi: 10.1038/s41598-019-49649-1
[16]	Li J, Xie H, Li A, et al. Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry[J]. Oncotarget, 2017, 8(29):46834-46845. doi: 10.18632/oncotarget.11603. doi: 10.18632/oncotarget.11603
[17]	Reinartz S, Lieber S, Pesek J, et al. Cell type-selective pathways and clinical associations of lysophosphatidic acid biosynthesis and signaling in the ovarian cancer microenvironment[J]. Mol Oncol, 2019, 13(2):185-201. doi: 10.1002/1878-0261.12396. doi: 10.1002/1878-0261.12396 pmid: 30353652
[18]	Braun MM, Overbeek-Wager EA, Grumbo RJ. Diagnosis and Management of Endometrial Cancer[J]. Am Fam Physician, 2016, 93(6):468-474.
[19]	Cao Y. Adipocyte and lipid metabolism in cancer drug resistance[J]. J Clin Invest, 2019, 129(8):3006-3017. doi: 10.1172/JCI127201. doi: 10.1172/JCI127201
[20]	Pierce SR, Fang Z, Yin Y, et al. Targeting dopamine receptor D2 as a novel therapeutic strategy in endometrial cancer[J]. J Exp Clin Cancer Res, 2021, 40(1):61. doi: 10.1186/s13046-021-01842-9. doi: 10.1186/s13046-021-01842-9
[21]	Altadill T, Dowdy TM, Gill K, et al. Metabolomic and Lipidomic Profiling Identifies The Role of the RNA Editing Pathway in Endometrial Carcinogenesis[J]. Sci Rep, 2017, 7(1):8803. doi: 10.1038/s41598-017-09169-2. doi: 10.1038/s41598-017-09169-2 pmid: 28821813
[22]	Herbert A. AD AR and Immune Silencing in Cancer[J]. Trends Cancer, 2019, 5(5):272-282. doi: 10.1016/j.trecan.2019.03.004. doi: S2405-8033(19)30069-X pmid: 31174840
[23]	Dalla Pozza E, Dando I, Pacchiana R, et al. Regulation of succinate dehydrogenase and role of succinate in cancer[J]. Semin Cell Dev Biol, 2020, 98:4-14. doi: 10.1016/j.semcdb.2019.04.013. doi: 10.1016/j.semcdb.2019.04.013
[24]	Jiang S, Yan W. Succinate in the cancer-immune cycle[J]. Cancer Lett, 2017, 390:45-47. doi: 10.1016/j.canlet.2017.01.019. doi: 10.1016/j.canlet.2017.01.019
[25]	Iplik ES, Catmakas T, Cakmakoglu B. A new target for the treatment of endometrium cancer by succinic acid[J]. Cell Mol Biol(Noisy-le-grand), 2018, 64(1):60-63. doi: 10.14715/cmb/2018.64.1.11. doi: 10.14715/cmb/2018.64.1.11
[26]	Hu G, Zhang J, Zhou X, et al. Roles of estrogen receptor α and β in the regulation of proliferation in endometrial carcinoma[J]. Pathol Res Pract, 2020, 216(10):153149. doi: 10.1016/j.prp.2020.153149. doi: 10.1016/j.prp.2020.153149
[27]	Audet-Delage Y, Grégoire J, Caron P, et al. Estradiol metabolites as biomarkers of endometrial cancer prognosis after surgery[J]. J Steroid Biochem Mol Biol, 2018, 178:45-54. doi: 10.1016/j.jsbmb.2017.10.021. doi: 10.1016/j.jsbmb.2017.10.021
[28]	Liput KP, Lepczyński A, Ogłuszka M, et al. Effects of Dietary n-3 and n-6 Polyunsaturated Fatty Acids in Inflammation and Cancerogenesis[J]. Int J Mol Sci, 2021, 22(13):6965. doi: 10.3390/ijms22136965. doi: 10.3390/ijms22136965
[29]	Lunde S, Nguyen HT, Petersen KK, et al. Chronic Postoperative Pain After Hysterectomy for Endometrial Cancer: A Metabolic Profiling Study[J]. Mol Pain, 2020, 16:1744806920923885. doi: 10.1177/1744806920923885. doi: 10.1177/1744806920923885
[30]	Kawaguchi K, Kinameri A, Suzuki S, et al. The cancer-promoting gene fatty acid-binding protein 5 (FABP5) is epigenetically regulated during human prostate carcinogenesis[J]. Biochem J, 2016, 473(4):449-461. doi: 10.1042/BJ20150926. doi: 10.1042/BJ20150926 pmid: 26614767
[31]	Zhang C, Liao Y, Liu P, et al. FABP5 promotes lymph node metastasis in cervical cancer by reprogramming fatty acid metabolism[J]. Theranostics, 2020, 10(15):6561-6580. doi: 10.7150/thno.44868. doi: 10.7150/thno.44868
[32]	Hayashi Y, Yokota A, Harada H, et al. Hypoxia/pseudohypoxia-mediated activation of hypoxia-inducible factor-1α in cancer[J]. Cancer Sci, 2019, 110(5):1510-1517. doi: 10.1111/cas.13990. doi: 10.1111/cas.13990
[33]	Castelli S, Ciccarone F, Tavian D, et al. ROS-dependent HIF1α activation under forced lipid catabolism entails glycolysis and mitophagy as mediators of higher proliferation rate in cervical cancer cells[J]. J Exp Clin Cancer Res, 2021, 40(1):94. doi: 10.1186/s13046-021-01887-w. doi: 10.1186/s13046-021-01887-w
[34]	Xu LX, Hao LJ, Ma JQ, et al. SIRT3 promotes the invasion and metastasis of cervical cancer cells by regulating fatty acid synthase[J]. Mol Cell Biochem, 2020, 464(1/2):11-20. doi: 10.1007/s11010-019-03644-2. doi: 10.1007/s11010-019-03644-2
[35]	Dong B, Yang Y, Han A, et al. Ectopic expression of HSDL2 is related to cell proliferation and prognosis in breast cancer[J]. Cancer Manag Res, 2019, 11:6531-6542. doi: 10.2147/CMAR.S205316. doi: 10.2147/CMAR.S205316
[36]	Yang Y, Han A, Wang X, et al. Lipid metabolism regulator human hydroxysteroid dehydrogenase-like 2 (HSDL2) modulates cervical cancer cell proliferation and metastasis[J]. J Cell Mol Med, 2021, 25(10):4846-4859. doi: 10.1111/jcmm.16461. doi: 10.1111/jcmm.16461
[37]	Gadducci A, Cosio S. Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer: Review of the Literature and Perspectives of Clinical Research[J]. Anticancer Res, 2020, 40(9):4819-4828. doi: 10.21873/anticanres.14485. doi: 10.21873/anticanres.14485 pmid: 32878770
[38]	Song Y, Liu Y, Lin M, et al. Efficacy of neoadjuvant platinum-based chemotherapy during the second and third trimester of pregnancy in women with cervical cancer: an updated systematic review and meta-analysis[J]. Drug Des Devel Ther, 2018, 13:79-102. doi: 10.2147/DDDT.S186966. doi: 10.2147/DDDT.S186966
[39]	Hou Y, Yin M, Sun F, et al. A metabolomics approach for predicting the response to neoadjuvant chemotherapy in cervical cancer patients[J]. Mol Biosyst, 2014, 10(8):2126-2133. doi: 10.1039/c4mb00054d. doi: 10.1039/c4mb00054d
[40]	Abudula A, Rouzi N, Xu L, et al. Tissue-based metabolomics reveals potential biomarkers for cervical carcinoma and HPV infection[J]. Bosn J Basic Med Sci, 2020, 20(1):78-87. doi: 10.17305/bjbms.2019.4359. doi: 10.17305/bjbms.2019.4359
[41]	Lin F, Zheng R, Yu C, et al. Predictive role of serum cholesterol and triglycerides in cervical cancer survival[J]. Int J Gynecol Cancer, 2021, 31(2):171-176. doi: 10.1136/ijgc-2020-001333. doi: 10.1136/ijgc-2020-001333
[42]	Zhou H, Li Q, Wang T, et al. Prognostic biomarkers of cervical squamous cell carcinoma identified via plasma metabolomics[J]. Medicine(Baltimore), 2019, 98(26):e16192. doi: 10.1097/MD.0000000000016192. doi: 10.1097/MD.0000000000016192