1. Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow, Russia 2. Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow, Russia; 2V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Center of Chemical Physics, Moscow, Russia 3. Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang, China
Research of cancer progression mechanisms and their impact on metabolism of tumor cells and tumor microenvironment cells is an important element in drug development for cancer target therapy. In this study, changes in tumor tissue and margin tissue lipid profiles, were associated with the following clinical and morphological characteristics: tumor size, cancer stage, multifocalite, tumor grade, number of lymph node metastasis, Nottingham prognostic index, total malignancy score, level of Ki67 protein. Lipid profiling was performed by reverse-phase chromato-mass spectrometry analysis of lipid tissue extract with lipid identification by characteristic fragments. In the lipid profile of tumor tissue 13 characteristic lipids were selected. Their levels significantly correlated with at least 5 clinical and morphological features. Eight of 13 belonged to phosphatidylcholines. In lipid profile of tumor microenviroment tissue 13 lipid features were selected. Their levels significantly correlated with at least 5 clinical and morphological features. Four of 13 belonged to oxidized lipids, 4 lipid features belonged to sphingomyelins, four of 13 belonged to phosphatidylethanolamines. The tumor microenvironment tissue lipid profile correlated with tumor size, cancer stage, tumor grade, number of axillary metastases, Nottingham prognostic index. The tumor tissue lipid profile correlated with tumor size, tumor grade, total malignant score, and number of axillary metastases.
Download PDF:
Keywords: mass-spectrometry, lipidomics, breast cancer, tumor microenvironment, cancer progression
Supplementary materials:
Citation:
Tokareva A.O., Starodubtseva N.L., Chagovets V.V., Rodionov V.V., Kometova V.V., Chingin K.S., Frankevich V.E. (2022) Lipidomic markers of tumor progress in breast cancer patients. Biomeditsinskaya Khimiya, 68(2), 144-152.
Tokareva A.O. et al. Lipidomic markers of tumor progress in breast cancer patients // Biomeditsinskaya Khimiya. - 2022. - V. 68. -N 2. - P. 144-152.
Tokareva A.O. et al., "Lipidomic markers of tumor progress in breast cancer patients." Biomeditsinskaya Khimiya 68.2 (2022): 144-152.
Tokareva, A. O., Starodubtseva, N. L., Chagovets, V. V., Rodionov, V. V., Kometova, V. V., Chingin, K. S., Frankevich, V. E. (2022). Lipidomic markers of tumor progress in breast cancer patients. Biomeditsinskaya Khimiya, 68(2), 144-152.
Bray F., Ferlay J., Soerjomataram I., Siegel R.L., Torre L.A., Jemal A. (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: Cancer J. Clin., 68(6), 394-424. CrossRef Scholar google search
Kaprin A.D., Starinskiy V.V., Shakhzadova A.O. (2020) Zlokachestvennye novoobrazovaniya v Rossii v 2019 godu (Zabolevaemost' i smertnost'), MNIOI P.A. Herzcena — filial FGBU “NMITS radiologii” Minzdrava Rossii, Moskva, 250 p. Scholar google search
Annaratone L., Cascardi E., Vissio E., Sarotto I., Chmielik E., Sapino A., Berrino E., Marchiò C. (2020) The multifaceted nature of tumor microenvironment in breast carcinomas. Pathobiology, 87(2), 125-142. CrossRef Scholar google search
Renner K., Singer K., Koehl G.E., Geissler E.K., Peter K., Siska P.J., Kreutz M. (2017) Metabolic hallmarks of tumor and immune cells in the tumor microenvironment. Front. Immunol., 8, 1-11. CrossRef Scholar google search
Giallourou N., Urbaniak C., Puebla-Barragan S., Vorkas P.A., Swann J.R., Reid G. (2021) Characterizing the breast cancer lipidome and its interaction with the tissue microbiota. Communications Biology, 4(1), 1229. CrossRef Scholar google search
Huang H., Li S., Tang Q., Zhu G. (2021) Metabolic reprogramming and immune evasion in nasopharyngeal carcinoma. Front. Immunol., 12, 1-18. CrossRef Scholar google search
Cui M.Y., Yi X., Zhu D.X., Wu J. (2021) Aberrant lipid metabolism reprogramming and immune microenvironment for gastric cancer: A literature review. Transl. Cancer Res., 10(8), 3829-3842. CrossRef Scholar google search
Nguyen A., Rudge S.A., Zhang Q., Wakelam M.J. (2017) Using lipidomics analysis to determine signalling and metabolic changes in cells. Curr. Opin. Biotechnol., 43, 96-103. CrossRef Scholar google search
Preedy V.R., Patel V.B. (eds.) (2015) in: General Methods In Biomarker Research And Their Applications; Series Abbreviated Title Biomarkers in Disease: Methods, Discoveries and Applications; Springer Dordrecht Heidelberg New York London, 1-2, 1-1316. CrossRef