Blood plasma lipid profile in glial tumors

Introduction. In glial tumors, lipid metabolism becomes abnormal. Analysis of lipid metabolism components can be an important characteristic of molecular and genetic profile of gliomas.
Aim. To determine the correlation between plasma lipidome profile and immunohistochemical characteristics of glial tumors and to evaluate clinical significance of blood lipid spectrum analysis in preoperative assessment of molecular profile of gliomas.
Materials and methods. Immunohistochemical measurement of O-6-methylguanine-DNA-methyl transferase (MGMT), Ki-67, p53, IDH1 tumor markers was performed using the corresponding antibody clones. Composition of plasma lipids was assessed using thin layer chromatography.
Results. Even at the early stages of gliomagenesis, significant differences in cholesterol ethers, lysophosphatidylcholines, phosphatidylcholine (PC)/ lysophosphatidylcholine (LPC) ratio, neutral lipids (NL)/phospholipids (PL) in the blood were observed. Significant correlations between Ki-67, MGMT tumor markers and the above-mentioned lipidome parameters were found. The PC/LPC, NL/PL ratios in the blood of the patients from the groups with higher (above 10 %) and lower (below 10 %) Ki-67 mitotic indexes compared to healthy individuals were significantly lower. Therefore, the values of lipidome parameters allow to indirectly assess proliferative activity of gliomas which can be used for preoperative diagnosis of these tumors. No significant differences in the plasma PC/LPC and NL/PL ratios were found between the groups with MGMT promoter methylation and without it. No indirect predictor criteria for MGMT were found.
Conclusion. It is impossible to determine decreased epigenetic activity of corresponding transcripts and preoperative prognosis for alkylating agent therapy based on the parameters of plasma lipid metabolism.

1. Louis D.N., Perry A., Wesseling P. et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol 2021;23(8):1231–51. DOI: 10.1093/neuonc/noab190

2. Marien E., Meister M., Muley T. et al. Non-small cell lung cancer is characterized by dramatic changes in phospholipid profiles. Int J Cancer 2015;137(7):1539–48. DOI: 10.1002/ijc.29517

3. Bensaad K., Favaro E., Lewis C.A. et al. Fatty acid uptake and lipid storage induced by HIF-1α contribute to cell growth and survival after hypoxia-reoxygenation. Cell Rep 2014;9(1):349–65. DOI: 10.1016/j.celrep.2014.08.056

4. Guo D., Bell E.H., Chakravarti A. Lipid metabolism emerges as a promising target for malignant glioma therapy. CNS Oncol 2013;2(3):289–99. DOI: 10.2217/cns.13.20

5. El Khayari A., Bouchmaa N., Taib B. et al. Metabolic rewiring in glioblastoma cancer: EGFR, IDH and beyond. Front Oncol 2022;12:901–51. DOI: 10.3389/fonc.2022.901951

6. Zhou J., Ji N., Wang G. et al. Metabolic detection of malignant brain gliomas through plasma lipidomic analysis and support vector machine-based machine learning. BioMedicine 2022;81:104097. DOI: 10.1016/j.ebiom.2022.104097

7. Wu X., Geng F., Cheng X. et al. Lipid droplets maintain energy homeostasis and glioblastoma growth via autophagic release of stored fatty acids. iScience 2020;23(10):1–11. DOI: 10.1016/j.isci.2020.101569

8. Sharshunova M., Schwarz V., Michalec C. Thin-layer chromatography in pharmacy and clinical biochemistry: in 2 vol. Moscow: Mir; 1980. 295 p. (In Russ.).

9. Kuzmina E.I., Nelyubin A.S., Shchennikova M.K. The use of induced chemiluminescence for the assessment of free radical reactions in biological substrates. In: Interuniversity collection of biochemistry and biophysics of microorganisms. Gor`kiy: Volgo-Vyatskoe izdatel`stvo, 1983. Pp. 179–183. (In Russ.).

10. Goryainova E.R., Pankov A.R., Platonova E.N. Applied methods for analyzing statistical data: textbook for universities. Moscow: Izdatel’skiy dom Vysshej shkoly ekonomiki, 2012. Pp. 113–151. (In Russ.).

11. Eibinger G., Fauler G., Bernhart E. et al. On the role of 25-hydroxycholesterol synthesis by glioblastoma cell lines. Implications for chemo-tactic monocyte recruitment. Exp Cell Res 2013;319:1828–38. DOI: 10.1016/j.yexcr.2013.03.025

12. Cigliano L., Spagnuolo M.S., Napolitano G. et al. 24S-hydroxychole-sterol affects redox homeostasis in human glial U-87 MG cells. Mol Cell Endocrinol 2019; 486:25–33. DOI: 10.1016/j.mce.2019.02.013

13. Ríos-Marco P., Martín-Fernández M., Soria-Bretones I. et al. Alkylphospholipids deregulate cholesterol metabolism and induce cell-cycle arrest and autophagy in U-87 MG glioblastoma cells. Biochim Biophys Acta 2013;1831(8):1322–34. DOI: 10.1016/j.bbalip.2013.05.004

14. Chang T.Y., Li B.L., Chang C.C., Urano Y. Acyl-coenzyme A: cholesterol acyltransferases. Am J Physiol Endocrinol Metab 2009;297:E1–9. DOI: 10.1152/ajpendo.90926.2008

15. Geng F., Cheng X., Wu X. et al. Inhibition of SOAT1 suppresses glioblastoma growth via blocking SREBP-1-mediated lipogenesis. Clin Cancer Res 2016;22(21):5337–48. DOI: 10.1158/1078-0432.ccr-17-0063

16. Geng F., Guo D. Lipid droplets, potential biomarker and metabolic target in glioblastoma. Intern Med Rev (Wash D C) 2017;3(5):10.18103. DOI: 10.18103/imr.v3i5.443

17. Kou Y., Geng F., Guo D. Lipid metabolism in glioblastoma: from de novo synthesis to storage. Biomedicines 2022;10(8):1943–25. DOI: 10.3390/biomedicines10081943

18. Deligne C., Hachani J., Duban-Deweer S. et al. Development of a human in vitro blood–brain tumor barrier model of diffuse intrinsic pontine glioma to better understand the chemoresistance. Fluids Barriers CNS 2020;17(1):37. DOI: 10.1186/s12987-020-00198-0

19. Abbott N.J. Blood-brain barrier structure and function and the challenges for CNS drug delivery. J Inherit Metab Dis 2013;36(3):437–49. DOI: 10.1007/s10545-013-9608-0

20. Sarkaria J.N., Hu L.S., Parney I.F. et al. Is the blood–brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data. Neuro-Oncology 2018;20(2):184–91. DOI: 10.1093/neuonc/nox175

21. Krasnikova O.V., Kondrat’eva A.R., Badu S.K. et al. Potential diagnostic biomarkers of glioma in the liquid media of the body. Zhurnal mediko-biologicheskikh issledovaniy = Journal of Medical and Biological Research 2022;10(1):52–63. DOI: 10.37482/2687-1491-z090

22. Zhou J., Ji N., Wang G. et al. Metabolic detection of malignant brain gliomas through plasma lipidomic analysis and support vector machine-based machine learning. Articles 2022;81:1–13. DOI: 10.1016/j.ebiom.2022.104097

23. Kao T.-J., Lin Ch.-L., Yang W.-B. et al. Dysregulated lipid metabolism in TMZ-resistant glioblastoma: pathways, proteins, metabolites and therapeutic opportunities. Lipids Health Dis 2023;22(114):1–13. DOI: 10.1186/s12944-023-01881-5

24. Bullwinkel J., Baron-Luehr B., Ludemann A. et al. Ki-67 protein is associated with ribosomal RNA transcription in quiescent and proliferating cells. J Cell Physiol 2006;206(3):624–35. DOI: 10.1002/jcp.20494

25. Theresia E., Malueka R.G., Pranacipta S. et al. Association between Ki-67 labeling index and histopathological grading of glioma in Indonesian population. Asian Pac J Cancer Prev 2020;21(4):1063–8. DOI: 10.31557/apjcp.2020.21.4.1063

26. Yoda R.A., Marxen T., Longo L. et al. Mitotic index thresholds do not predict clinical outcome for IDH-mutant astrocytoma. J Neuropathol Exp Neurol 2019;78(11):1002–10. DOI: 10.1093/jnen/nlz082

27. Dahlrot R.H., Bangsø J.A., Petersen J.K. et al. Prognostic role of Ki-67 in glioblastomas excluding contribution from nonneoplastic cells. Sci Rep 2021;11(1):17918. DOI: 10.1038/s41598-021-95958-9

28. Chen W.J., He D.S., TangR.X. et al. Ki-67 is a valuable prognostic factor in gliomas: evidence from a systematic review and metaanalysis. Asian Pac J Cancer Prev 2015;16(2):411–20. DOI: 10.7314/apjcp.2015.16.2.411

29. Abdul Rashid K., Ibrahim K., Wong J.H.D., Mohd Ramli N. Lipid alterations in glioma: a systematic review. Metabolites 2022;12(12):1280. DOI: 10.3390/metabo12121280

30. Morash S.C., Cook H.W., Spence M.W. Lysophosphatidylcholine as an intermediate in phosphatidylcholine metabolism and glycerophosphocholine synthesis in cultured cells: an evaluation of the roles of 1-acyl- and 2-acyl-lysophosphatidylcholine. Biochim Biophys Acta 1989;1004(2):221–9. DOI: 10.1016/0005-2760(89)90271-3

31. Butler M., Pongor L., Su Y.T. et al. MGMT status as a clinical biomarker in glioblastoma. Trends Cancer 2020;6(5):380–91. DOI: 10.1016/j.trecan.2020.02.010

32. Tano K., Shiota S., Collier J et al. Isolation and structural characterization of a cDNA clone encoding the human DNA repair protein for O6-alkylguanine. Proc Nat Acad Sci USA 1990;87(2):686–90. DOI: 10.1073/pnas.87.2.686

33. Chen X., Zhang M., Gan H. et al. A novel enhancer regulates MGMT expression and promotes temozolomide resistance in glioblastoma. Nat Commun 2018;9(1):2949. DOI: 10.1038/s41467-018-05373-4

34. Pandith A.A., Qasim I., Zahoor W. et al. Concordant association validates MGMT methylation and protein expression as favorable prognostic factors in glioma patients on alkylating chemotherapy (temozolo-mide). Sci Rep 2018;8(1):6704. DOI: 10.1038/s41598-018-25169-2

35. Dahlrot R.H., Larsen P., Boldt H.B. et al. Posttreatment effect of MGMT methylation level on glioblastoma survival. J Neuropathol Exp Neurol 2019;8(7):633–40. DOI: 10.1093/jnen/nlz032

36. Aoki K., Natsume A. Overview of DNA methylation in adult diffuse gliomas. Brain Tumor Pathol 2019;36(2):8491. DOI: 10.1007/s10014-019-00339-w

37. Huang F., Li S., Wang X. et al. Serum lipids concentration on prognosis of high-gradeglioma. Cancer Causes Control 2023;34(9):801–11. DOI: 10.1007/s10552-023-01710-1