Метаболомный профиль злокачественных опухолей яичника

Филиппов Федор Евгеньевич; Кутилин Денис Сергеевич; Максимов Алексей Юрьевич; Порханова Наталья Владимировна

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Scopus Author ID: 55328886800

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South Russian Journal of Cancer. 2024. Vol. 5, No. 3. P. 91-101

https://doi.org/10.37748/2686-9039-2024-5-3-8

https://elibrary.ru/avxoui

ORIGINAL

ARTICLE

Metabolomic profile of malignant ovarian tumors..

F. E. Filippov2, D. S. Kutilin1 , A. Yu. Maksimov1, N. V. Porkhanova2

1 National Medical Research Centre for Oncology, Rostov-on-Don, Russian Federation

2 Clinical Oncology Dispensary No. 1, Krasnodar, Russian Federation

k.denees@yandex.ru

ABSTRACT

Purpose of the study. Investigate the metabolomic profile in tissues of patients with serous ovarian adenocarcinoma.

Materials

and

methods. The

study included

100

patients

with

serous

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

ovarian

adenocarcinoma. Chromatographic separation

of

metabolites was performed on a Vanquish Flex UHPLC System

chromatograph,

which was coupled with an Orbitrap Exploris

480 mass spectrometer. Differences were assessed using the Mann-Whitney test with Bonferroni correction.

Results.

In ovarian tumor tissue, 20 compounds had abnormal concentrations compared to normal tissue: increased levels of

kynurenine, phenylalanylvaline, lysophosphatidylcholine (18:3), lysophosphatidylcholine (18:2), alanylleucine, L-phenylalanine,

phosphatidylinositol (34:1), 5-methoxytryptophan, lysophosphatidylcholine (14:0), indoleacrylic acid and decreased levels of

myristic acid, decanoylcarnitine, aspartylglycine, malonylcarnitine, 3-methylxanthine, 3-oxododecanoic acid, 2-hydroxymyristic

acid, N-acetylproline, L-octanoylcarnitine and capryloylglycine.

Conclusion. A

significant metabolic

imbalance was found in ovarian tumor

tissue,

expressed in abnormal concentrations

of fatty acids

and their derivatives, acylcarnitines, amino acids

and their derivatives, phospholipids

and nitrogenous

base

derivatives. The concentrations of these 20 metabolites in tissues can serve as diagnostic markers of ovarian cancer. Thus,

metabolomic tissue profiling allowed both to identify potential markers

of the disease and to better understand the molecular

mechanisms of changes underlying the development of this disease.

Keywords: metabolites, ultra-high performance liquid chromatography and mass spectrometry, ovarian serous

adenocarcinoma, biomarkers

For citation: Filippov F. E., Kutilin D. S., Maksimov A. Yu., Porkhanova N. V. Metabolomic profile of malignant ovarian tumors. South Russian Journal of

Cancer. 2024; 5(3): 91-101. (In Russ.). https://doi.org/10.37748/2686-9039-2024-5-3-8, https://elibrary.ru/avxoui

For correspondence: Denis S. Kutilin � PhD in Biology, Leading Researcher, Laboratory of Molecular Oncology, National Medical Research Centre for

Oncology, Rostov-on-Don, Russian Federation

Address: 63 14 line str., Rostov-on-Don 344037, Russian Federation

E-mail: k.denees@yandex.ru

ORCID: https://orcid.org/0000-0002-8942-3733

SPIN: 8382-4460, AuthorID: 794680

Scopus Author ID: 55328886800

Compliance with ethical standards: the research study is carried out in compliance with the ethical principles set forth by World Medical Association

Declaration of Helsinki, 1964, ed. 2013. The study was approved by the Committee on Biomedical Ethics at the National Medical Research Center for

Oncology (extract from the minutes of the meeting No. 17 dated 06/28/2022). Informed consent was received from all participants of the study

Funding: this work was not funded. The work was performed with scientific equipment provided by the Central Research Institute of the National Medical

Research Center for Oncology, the Russian Federation Ministry of Health: https://ckp-rf.ru/catalog/ckp/3554742/

Conflict of interest: the authors declare that there are no obvious and potential conflicts of interest associated with the publication of this article

The article was submitted 21.07.2024; approved after reviewing 27.08.2024; accepted for publication 29.08.2024

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4.

Meinhold-Heerlein I, Fotopoulou C, Harter P, Kurzeder C, Mustea A, Wimberger P, et al. The new WHOclassification of ovarian,

fallopian tube, and primary peritoneal cancer and its clinical implications. Arch Gynecol Obstet. 2016

Apr;293(4):695�700.

https://doi.org/10.1007/s00404-016-4035-8

5.

Rooth C. Ovarian cancer: risk factors, treatment and management. Br J Nurs. 2013 Sep 12;22(17):S23�30.

https://doi.org/10.12968/bjon.2013.22.Sup17.S23

6.

Ahmed-Salim Y, Galazis N, Bracewell-Milnes T, Phelps DL, Jones BP, Chan M, et al. The application of metabolomics in

ovarian cancer management: a systematic review. Int J Gynecol Cancer. 2021

May;31(5):754�774.

https://doi.org/10.1136/ijgc-2020-001862

7.

Plewa S, Horala A, Derezinski P, Nowak-Markwitz E, Matysiak J, Kokot ZJ. Wide spectrum targeted metabolomics identifies

potential ovarian cancer biomarkers. Life Sci. 2019 Apr 1;222:235�244. https://doi.org/10.1016/j.lfs.2019.03.004

8.

Swiatly A, Plewa S, Matysiak J, Kokot ZJ. Mass spectrometry-based proteomics techniques and their application in ovarian

cancer research. J Ovarian Res. 2018 Oct 1;11(1):88. https://doi.org/10.1186/s13048-018-0460-6

9.

Veenstra TD. Metabolomics: the final frontier? Genome Med. 2012

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

Apr 30;4(4):40. https://doi.org/10.1186/gm339

10.

�� . �., �� . �., �� . �., �� . �., ��

�. �., �� . �. � ��. ��

��

�

��

��.

��

��.

2023;22(3):43�50.

https://doi.org/10.17650/1726-9784-2023-22-3-43-50,

EDN:

KRLBXC

11.

�� . �., �� . �., �� . �., �� . �., �� . �., �� . �. � ��. ��

��

�

��

��.

��

�

��. 2023;(3):89. https://doi.org/10.17513/spno.32678, EDN: HJTHUD

12.

Jones E., Oliphant E., Peterson P. SciPy: Open source scientific tools for python, 2001.

13.

Koundouros N, Poulogiannis G. Reprogramming of fatty acid metabolism in cancer. Br J Cancer. 2020

Jan;122(1):4�22.

https://doi.org/10.1038/s41416-019-0650-z

14.

Zhao S, Cheng L, Shi

Y, Li

J, Yun

Q, Yang H. MIEF2

reprograms

lipid metabolism to drive progression

of ovarian

cancer through

ROS/AKT/mTOR signaling pathway. Cell Death Dis. 2021 Jan 5;12(1):18. https://doi.org/10.1038/s41419-020-03336-6

15.

Zazula R, Moravec M, Pehal F, Nejtek T, Protus M, Muller M. Myristic Acid Serum Levels and Their Significance for Diagnosis

of Systemic Inflammatory Response, Sepsis, and Bacteraemia. J Pers Med. 2021 Apr 16;11(4):306.

https://doi.org/10.3390/jpm11040306

16.

Matta M, Deubler E, Chajes V, Vozar B, Gunter MJ, Murphy N, et al. Circulating plasma phospholipid fatty acid levels

and breast cancer risk in the Cancer Prevention Study-II Nutrition Cohort. Int J Cancer. 2022 Dec 15;151(12):2082�2094.

https://doi.org/10.1002/ijc.34216

17.

Aglago EK, Murphy N, Huybrechts I, Nicolas G, Casagrande C, Fedirko V, et al. Dietary intake and plasma phospholipid concentrations

of saturated, monounsaturated and trans fatty acids and colorectal cancer risk in the European Prospective

Investigation into Cancer and Nutrition cohort. Int J Cancer. 2021

Apr 28;149(4):865�882.

https://doi.org/10.1002/ijc.33615

18.

Brown DG, Rao S, Weir TL, O�Malia J, Bazan M, Brown RJ, et al. Metabolomics and metabolic pathway networks from human

colorectal cancers, adjacent mucosa, and stool. Cancer Metab. 2016;4:11. https://doi.org/10.1186/s40170-016-0151-y

19.

Sinha R, Ahn J, Sampson JN, Shi J, Yu G, Xiong X, et al. Fecal Microbiota, Fecal Metabolome, and Colorectal Cancer Interrelations.

PLoS

One.

2016;11(3):e0152126.

https://doi.org/10.1371/journal.pone.0152126

20.

Wang X, Wang J, Rao B, Deng L. Gut flora profiling and fecal metabolite composition of colorectal cancer patients and

healthy individuals. Exp Ther Med. 2022 Apr;23(4):250. https://doi.org/10.3892/etm.2022.11175

21.

Jenske R, Vetter W. Enantioselective analysis of 2- and 3-hydroxy fatty acids in food samples. J Agric Food Chem. 2008

Dec 24;56(24):11578�11583. https://doi.org/10.1021/jf802772a

22.

Lemay AM, Courtemanche O, Couttas TA, Jamsari G, Gagne A, Bosse Y, et al. High FA2H and UGT8

transcript levels predict

hydroxylated hexosylceramide accumulation in lung adenocarcinoma. J Lipid Res. 2019

Oct;60(10):1776�1786.

https://doi.org/10.1194/jlr.M093955

23.

Sun

L,

Yang

X,

Huang

X,

Yao

Y,

Wei

X,

Yang

S,

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

et

al.

2-Hydroxylation

of

Fatty

Acids

Represses

Colorectal

Tumorigenesis

and

Metastasis via the YAP Transcriptional Axis. Cancer Res. 2021 Jan 15;81(2):289�302.

https://doi.org/10.1158/0008-5472.CAN-20-1517

South Russian Journal of Cancer 2024. Vol. 5, No. 3. P. 91-101

Filippov F. E., Kutilin D. S. , Maksimov A. Yu., Porkhanova N. V. Metabolomic profile of malignant ovarian tumors

24.

Batsika CS, Mantzourani C, Gkikas D, Kokotou MG, Mountanea OG, Kokotos CG, et al. Saturated Oxo Fatty Acids (SOFAs):

A Previously Unrecognized Class of Endogenous Bioactive Lipids Exhibiting a Cell Growth Inhibitory Activity. J Med Chem.

2021

May 13;64(9):5654�5666. https://doi.org/10.1021/acs.jmedchem.0c02058

25.

McCann MR, George De la Rosa MV, Rosania GR, Stringer KA. L-Carnitine and Acylcarnitines: Mitochondrial Biomarkers for

Precision Medicine. Metabolites. 2021 Jan 14;11(1):51. https://doi.org/10.3390/metabo11010051

26.

Console L, Scalise M, Mazza T, Pochini L, Galluccio M, Giangregorio N, et al. Carnitine Traffic in Cells. Link With Cancer.

Front Cell Dev Biol. 2020;8:583850. https://doi.org/10.3389/fcell.2020.583850

27.

Warburg O, Wind F, Negelein E. The metabolism of tumors in the body. J Gen Physiol. 1927 Mar 7;8(6):519�530.

https://doi.org/10.1085/jgp.8.6.519

28.

Ganapathy V, Thangaraju M, Prasad PD. Nutrient transporters in cancer: relevance to Warburg hypothesis and beyond.

Pharmacol Ther. 2009 Jan;121(1):29�40. https://doi.org/10.1016/j.pharmthera.2008.09.005

29.

Zhang J, Wu G, Zhu H, Yang F, Yang S, Vuong AM, et al. Circulating Carnitine Levels and Breast Cancer: A Matched Retrospective

Case-Control Study. Front Oncol. 2022;12:891619. https://doi.org/10.3389/fonc.2022.891619

30.

Wang Y, Chen Y, Guan L, Zhang H, Huang Y, Johnson CH, et al. Carnitine palmitoyltransferase 1C regulates cancer cell senescence

through mitochondria-associated metabolic reprograming. Cell Death Differ. 2018 Mar;25(4):735�748.

https://doi.org/10.1038/s41418-017-0013-3

31.

Ganti S, Taylor SL, Kim K, Hoppel CL, Guo L, Yang J, et al. Urinary acylcarnitines are altered in human kidney cancer. Int

J Cancer. 2012 Jun 15;130(12):2791�2800. https://doi.org/10.1002/ijc.26274

32.

Santer R, Fingerhut R, Lassker U, Wightman PJ, Fitzpatrick DR, Olgemoller B, et al. Tandem mass spectrometric determination

of malonylcarnitine: diagnosis and neonatal screening of malonyl-CoA decarboxylase deficiency. Clin Chem. 2003

Apr;49(4):660�662. https://doi.org/10.1373/49.4.660

33.

Huang Z, Lin L, Gao Y, Chen Y, Yan X, Xing J, et al. Bladder cancer determination via two urinary metabolites: a biomarker

pattern approach. Mol Cell Proteomics. 2011 Oct;10(10):M111.007922. https://doi.org/10.1074/mcp.M111.007922

34.

Chace DH, DiPerna JC, Adam BW, Hannon WH. Errors caused by the use of D,L-octanoylcarnitine for blood-spot calibrators.

Clin Chem. 2001 Apr;47(4):758�3869.

35.

Chang W, Fa H, Xiao D, Wang J. Targeting phosphatidylserine for Cancer therapy: prospects and challenges. Theranostics.

2020;10(20):9214�9229. https://doi.org/10.7150/thno.45125

36.

Rolin J, Maghazachi AA. Effects of lysophospholipids on tumor microenvironment. Cancer Microenviron. 2011Dec;4(3):393�

403.

https://doi.org/10.1007/s12307-011-0088-1

37.

Li X, Nakayama K, Goto T, Kimura H, Akamatsu S, Hayashi Y, et al. High level of phosphatidylcholines/lysophosphatidylcholine

ratio in urine is associated with prostate cancer. Cancer Sci. 2021 Oct;112(10):4292�4302.

https://doi.org/10.1111/cas.15093

38.

Min HK, Lim S, Chung BC, Moon MH. Shotgun lipidomics for candidate biomarkers of urinary phospholipids in prostate

cancer. Anal Bioanal Chem. 2011 Jan;399(2):823�830. https://doi.org/10.1007/s00216-010-4290-7

39.

Zeleznik OA, Clish CB, Kraft P, Avila-Pacheco J, Eliassen AH, Tworoger SS. Circulating Lysophosphatidylcholines, Phosphatidylcholines,

Ceramides, and Sphingomyelins and Ovarian Cancer Risk: A 23-Year Prospective Study. J Natl Cancer Inst.

2020

Jun 1;112(6):628�636. https://doi.org/10.1093/jnci/djz195

40.

Li X, Wang L, Fang P, Sun Y, Jiang X, Wang H, et al. Lysophospholipids induce innate immune transdifferentiation of endothelial

cells, resulting in prolonged endothelial activation. J Biol Chem. 2018 Jul 13;293(28):11033�11045.

https://doi.org/10.1074/jbc.RA118.002752

41.

Kaynak A, Davis HW, Kogan AB, Lee JH, Narmoneva DA, Qi X. Phosphatidylserine: The Unique Dual-Role Biomarker for Cancer

Imaging and Therapy. Cancers (Basel). 2022 May 21;14(10):2536. https://doi.org/10.3390/cancers14102536

42.

Wood MN, Ishiyama N, Singaram I, Chung CM, Flozak AS, Yemelyanov A, et al. .-Catenin homodimers are recruited to phosphoinositide-

activated membranes to promote adhesion. J Cell Biol. 2017 Nov 6;216(11):3767�3783.

https://doi.org/10.1083/jcb.201612006

43.

Ramos AR, Elong Edimo W, Erneux C. Phosphoinositide 5-phosphatase activities control cell motility in glioblastoma: Two

phosphoinositides PI(4,5)P2

and PI(3,4)P2 are involved. Adv Biol Regul. 2018 Jan;67:40�48.

https://doi.org/10.1016/j.jbior.2017.09.001

44.

Sikalidis AK. Amino acids and immune response: a role for cysteine, glutamine, phenylalanine, tryptophan and arginine in

T-cell function and cancer? Pathol Oncol Res. 2015 Jan;21(1):9�17. https://doi.org/10.1007/s12253-014-9860-0

��-�� 2024. �. 5, � 3. �. 91-101

�� . �., �� . �. , �� .�., �� . �. ��

45.

Badawy AAB. Kynurenine Pathway of Tryptophan Metabolism: Regulatory and Functional Aspects. Int J Tryptophan Res.

2017;10:1178646917691938.

https://doi.org/10.1177/1178646917691938

46.

Wlodarska

M,

Luo

C,

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

Kolde

R,

d�Hennezel

E,

Annand

JW,

Heim

CE,

et

al.

Indoleacrylic

Acid

Produced

by

Commensal

Peptostreptococcus

Species Suppresses Inflammation. Cell Host Microbe. 2017 Jul 12;22(1):25�37.

https://doi.org/10.1016/j.chom.2017.06.007

47.

Tanaka M, Toth F, Polyak H, Szabo A, Mandi Y, Vecsei L. Immune Influencers in Action: Metabolites and Enzymes of the

Tryptophan-Kynurenine Metabolic Pathway. Biomedicines. 2021

Jun 25;9(7):734.

https://doi.org/10.3390/biomedicines9070734

48.

Kanova M, Kohout P. Tryptophan: A Unique Role in the Critically Ill. Int J Mol Sci. 2021

Oct 28;22(21):11714.

https://doi.org/10.3390/ijms222111714

49.

Cheng

HH,

Kuo

CC,

Yan

JL,

Chen

HL,

Lin

WC,

Wang

KH,

et

al.

Control

of

cyclooxygenase-2

expression

and

tumorigenesis

by endogenous 5-methoxytryptophan. Proc Natl Acad Sci U S A. 2012

Aug 14;109(33):13231�13236.

https://doi.org/10.1073/pnas.1209919109

50.

Neurauter G, Grahmann AV, Klieber M, Zeimet A, Ledochowski M, Sperner-Unterweger B, et al. Serum phenylalanine

concentrations in patients with ovarian carcinoma correlate with concentrations of immune activation markers and of isoprostane-

8. Cancer Lett. 2008 Dec 8;272(1):141�147. https://doi.org/10.1016/j.canlet.2008.07.002

51.

Ozawa H, Hirayama A, Shoji F, Maruyama M, Suzuki K, Yamanaka-Okumura H, et al. Comprehensive Dipeptide Analysis

Revealed Cancer-Specific Profile in the Liver of Patients with Hepatocellular Carcinoma and Hepatitis. Metabolites. 2020

Nov 1;10(11):442. https://doi.org/10.3390/metabo10110442

52.

Sass JO, Mohr V, Olbrich H, Engelke U, Horvath J, Fliegauf M, et al. Mutations in ACY1, the gene encoding aminoacylase 1,

cause a novel inborn error of metabolism. Am J Hum Genet. 2006 Mar;78(3):401�409. https://doi.org/10.1086/500563

53.

Lin Y, Ma C, Liu C, Wang Z, Yang J, Liu X, et al. NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis

in patients with colorectal cancer. Oncotarget. 2016 May 17;7(20):29454�29464.

https://doi.org/10.18632/oncotarget.8762

54.

Frankel AE, Coughlin LA, Kim J, Froehlich TW, Xie Y, Frenkel EP, et al. Metagenomic Shotgun Sequencing and Unbiased Metabolomic

Profiling Identify Specific Human Gut Microbiota and Metabolites Associated with Immune Checkpoint Therapy

Efficacy in Melanoma Patients. Neoplasia. 2017 Oct;19(10):848�855. https://doi.org/10.1016/j.neo.2017.08.004

55.

Shojaei-Zarghani S, Yari Khosroushahi A, Rafraf M, Asghari-Jafarabadi M, Azami-Aghdash S. Dietary natural methylxanthines

and colorectal cancer: a systematic review and meta-analysis. Food Funct. 2020 Dec 1;11(12):10290�10305.

https://doi.org/10.1039/d0fo02518f

56.

Liu H, Song J, Zhou Y, Cao L, Gong Y, Wei Y, et al. Methylxanthine derivatives promote autophagy in gastric cancer cells

targeting PTEN. Anticancer Drugs. 2019 Apr;30(4):347�355. https://doi.org/10.1097/CAD.0000000000000724

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Метаболомный профиль злокачественных опухолей яичника Текст научной статьи по специальности «Клиническая медицина»

Metabolomic profile of malignant ovarian tumors

Текст научной работы на тему «Метаболомный профиль злокачественных опухолей яичника»