Chemically Induced Brain Cancer in Sprague-Dawley Rats: Changed Lipidomics Mimics the Human Conditions

• A. Leskanicova

  Institute of Biology and Ecology, Faculty of Sciences, Pavol Jozef Safarik University, Kosice, Slovakia

• P. Simko

  Institute of Biology and Ecology, Faculty of Sciences, Pavol Jozef Safarik University, Kosice, Slovakia

• N. Zidekova

  Department of Pharmacology, Jessenius Faculty of Medicine in Martin, Comenius University, Slovakia

• M. Babincak

  Institute of Biology and Ecology, Faculty of Sciences, Pavol Jozef Safarik University, Kosice, Slovakia

• A. Blicharova

  Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia

• M. Kertys

  Department of Pharmacology, Jessenius Faculty of Medicine in Martin, Comenius University, Slovakia

• J. Kostolný

  Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia

• D. Maceková

  Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia

• T. Kiskova

  Institute of Biology and Ecology, Faculty of Sciences, Pavol Jozef Safarik University, Kosice, Slovakia

Malignant gliomas are one of the most treatment-refractory cancers. Development of resistance to chemo- and radiotherapies contributes to these tumors’ aggressive phenotypes. Elevated lipid levels in gliomas have been reported for the last 50 years. However, the molecular mechanisms of how tumor tissues obtain lipids and utilize them are not well understood.In our study, 48.6% of phosphatidylcholines were significantly changed during an early stage of brain cancer in females, and 66.2% in males. As for lysophosphatidylcholines 57.1% metabolites were significantly changed in female, and 64.3% in male rats. We observed the most interesting results in the group of sphingomyelins, where 85.8% metabolites were significantly elevated during brain cancer. According to VIP projection, the most important metabolites were: PC ae C40:3, PC ae C38:1, PC ae C30:1, PC ae C38:3, PC ae C44:3, PC aa C40:2, PC aa C42:0, PC ae C30:2, SM C20:2, PC aa C42:1 in females, and PC ae C38:1, PC ae C40:3, PC ae C30:1, PC ae C42:1, SM C20:2, PC aa C34:4, PC ae C38:4, PC aa C32:2, PC aa C38:5, lysoPC a C14:0. The identification of lipid biomarkers during the early stage of cancer could improve patient prognosis.

Miller KD, et al. Brain and other central nervous system tumor statistics 2021. CA Cancer J Clin 2021; 71(5): 381-406. https://doi.org/10.3322/caac.21693

Siegel RL, et al. Cancer Statistics 2021. CA Cancer J Clin 2021; 71(1): 7-33. https://doi.org/10.3322/caac.21654

Silantyev AS, et al. Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics. Cells 2019; 8(8). https://doi.org/10.3390/cells8080863

Liu B, et al. RND3 promotes Snail 1 protein degradation and inhibits glioblastoma cell migration and invasion. Oncotarget 2016; 7(50): 82411-82423. https://doi.org/10.18632/oncotarget.12396

Olar A, Aldape KD. Using the molecular classification of glioblastoma to inform personalized treatment. J Pathol 2014; 232(2): 165-77. https://doi.org/10.1002/path.4282

Johnson BE, et al. Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science 2014; 343(6167): 189-193.

Koh I, et al. The mode and dynamics of glioblastoma cell invasion into a decellularized tissue-derived extracellular matrix-based three-dimensional tumor model. Sci Rep 2018; 8(1): 4608. https://doi.org/10.1038/s41598-018-22681-3

Hawkins CC, et al. Sphingolipid Metabolism in Glioblastoma and Metastatic Brain Tumors: A Review of Sphingomyelinases and Sphingosine-1-Phosphate. Biomolecules 2020; 10(10). https://doi.org/10.3390/biom10101357

Longuespée R, et al. Rapid detection of 2-hydroxyglutarate in frozen sections of IDH mutant tumors by MALDI-TOF mass spectrometry. Acta neuropathologica communications 2018; 6(1): 21-21. https://doi.org/10.1186/s40478-018-0523-3

Mörén L, et al. Metabolomic profiling identifies distinct phenotypes for ASS1 positive and negative GBM. BMC Cancer 2018; 18(1): 167. https://doi.org/10.1186/s12885-018-4040-3

Spalding K, et al. A review of novel analytical diagnostics for liquid biopsies: spectroscopic and spectrometric serum profiling of primary and secondary brain tumors. Brain and behavior 2016; 6(9): e00502-e00502. https://doi.org/10.1002/brb3.502

Huszthy PC, et al. In vivo models of primary brain tumors: pitfalls and perspectives. Neuro Oncol 2012; 14(8): 979-93. https://doi.org/10.1093/neuonc/nos135

Kerbel RS. What is the optimal rodent model for anti-tumor drug testing? Cancer Metastasis Rev 1998, 17(3): 301-4. https://doi.org/10.1023/A:1006152915959

Bulnes-Sesma S, Ullibarri-Ortiz de Zárate N, Lafuente-Sánchez JV. [Tumour induction by ethylnitrosourea in the central nervous system]. Rev Neurol 2006, 43(12): 733-8. https://doi.org/10.33588/rn.4312.2006174

Koestner A, Swenberg JA, Wechsler W. Transplacental pro-duction with ethylnitrosourea of neoplasms of the nervous sys-tem in Sprague-Dawley rats. Am J Pathol 1971, 63(1): 37-56.

Bulnes S, et al. Angiogenic Signalling Pathways Altered in Gliomas: Selection Mechanisms for More Aggressive Neoplastic Subpopulations with Invasive Phenotype. Journal of Signal Transduction 2012; 2012: 597915. https://doi.org/10.1155/2012/597915

Pena M, et al. Serum metabolites predict response to angiotensin II receptor blockers in patients with diabetes mellitus. Journal of Translational Medicine 2016; 14: 203. https://doi.org/10.1186/s12967-016-0960-3

Chhabda S, et al. The 2016 World Health Organization Clas-sification of tumours of the Central Nervous System: what the paediatric neuroradiologist needs to know. Quantitative Imaging in Medicine and Surgery 2016; 6(5): 486-489. https://doi.org/10.21037/qims.2016.10.01

Cavazos DA, Brenner AJ. Hypoxia in astrocytic tumors and implications for therapy. Neurobiol Dis 2016; 85: 227-233. https://doi.org/10.1016/j.nbd.2015.06.007

Jaroch K, Modrakowska P, Bojko B. Glioblastoma Metabolomics-In vitro Studies. Metabolites 2021; 11(5). https://doi.org/10.3390/metabo11050315

Leskanicova A, et al. Sex-dependent differences in stress-induced depression in Wistar rats are accompanied predominantly by changes in phosphatidylcholines and sphingomyelins. J Physiol Pharmacol 2021; 72(4).

Guo D, Bell EH, Chakravarti A. Lipid metabolism emerges as a promising target for malignant glioma therapy. CNS Oncol 2013; 2(3): 289-99. https://doi.org/10.2217/cns.13.20

Ralhan I, et al. Lipid droplets in the nervous system. J Cell Biol 2021; 220(7). https://doi.org/10.1083/jcb.202102136

Petrelli F, Knobloch M, Amati F. Brain lipid metabolism: the emerging role of lipid droplets in glial cells. Curr Opin Lipidol 2022; 33(1): 86-87. https://doi.org/10.1097/MOL.0000000000000812

Warburg O. On the origin of cancer cells. Science 1956; 123(3191): 309-14. https://doi.org/10.1126/science.123.3191.309

He H, et al. Method for lipidomic analysis: p53 expression modulation of sulfatide, ganglioside, and phospholipid composition of U87 MG glioblastoma cells. Analytical Chemistry 2007; 79(22): 8423-8430. https://doi.org/10.1021/ac071413m

Campanella R. Membrane lipids modifications in human gliomas of different degree of malignancy. J Neurosurg Sci 1992; 36(1): 11-25.

Flavin R, et al. Fatty acid synthase as a potential therapeutic target in cancer. Future Oncol 2010; 6(4): 551-62. https://doi.org/10.2217/fon.10.11

Simons K, Toomre D. Lipid rafts and signal transduction. Nat Rev Mol Cell Biol 2000; 1(1): 31-9. https://doi.org/10.1038/35036052

de Almeida RFM, Fedorov A, Prieto M. Sphingomyelin/phosphatidylcholine/cholesterol phase diagram: boundaries and composition of lipid rafts. Biophysical Journal 2003; 85(4): 2406-2416. https://doi.org/10.1016/S0006-3495(03)74664-5

de Almeida RF, et al. Lipid rafts have different sizes depending on membrane composition: a time-resolved fluorescence resonance energy transfer study. J Mol Biol 2005; 346(4): 1109-20. https://doi.org/10.1016/j.jmb.2004.12.026

Huitema K, et al. Identification of a family of animal sphingomyelin synthases. Embo J 2004; 23(1): 33-44. https://doi.org/10.1038/sj.emboj.7600034

Zhai XH, et al. Novel sphingomyelin biomarkers for brain glioma and associated regulation research on the PI3K/Akt signaling pathway. Oncol Lett 2019; 18(6): 6207-6213. https://doi.org/10.3892/ol.2019.10946

Maceyka M, Spiegel S. Sphingolipid metabolites in inflammatory disease. Nature 2014; 510(7503): 58-67. https://doi.org/10.1038/nature13475

Hadi LA, et al. The Role and Function of Sphingolipids in Glioblastoma Multiforme 2015.

Vit JP, Rosselli F. Role of the ceramide-signaling pathways in ionizing radiation-induced apoptosis. Oncogene 2003; 22(54): 8645-52. https://doi.org/10.1038/sj.onc.1207087

Mirzayans R, et al. Ionizing radiation-induced responses in human cells with differing TP53 status. Int J Mol Sci 2013; 14(11): 22409-35. https://doi.org/10.3390/ijms141122409

Grassmé H, Riethmüller J, Gulbins E. Biological aspects of ceramide-enriched membrane domains. Prog Lipid Res 2007; 46(3-4): 161-70. https://doi.org/10.1016/j.plipres.2007.03.002

Ekiz HA, Baran Y. Bioactive sphingolipids in response to chemotherapy: a scope on leukemias. Anticancer Agents Med Chem 2011; 11(4): 385-97. https://doi.org/10.2174/187152011795677571

Truman JP, et al. Evolving concepts in cancer therapy through targeting sphingolipid metabolism. Biochim Biophys Acta 2014; 1841(8): 1174-88. https://doi.org/10.1016/j.bbalip.2013.12.013

Oskouian B, Saba JD. Cancer treatment strategies targeting sphingolipid metabolism. Adv Exp Med Biol 2010; 688: 185-205. https://doi.org/10.1007/978-1-4419-6741-1_13

Buentzel J, et al. Metabolomic Profiling of Blood-Derived Microvesicles in Breast Cancer Patients. Int J Mol Sci 2021; 22(24). https://doi.org/10.3390/ijms222413540

Guo Y, et al. Probing gender-specific lipid metabolites and diagnostic biomarkers for lung cancer using Fourier transform ion cyclotron resonance mass spectrometry. Clin Chim Acta 2012; 414: 135-41. https://doi.org/10.1016/j.cca.2012.08.010

Schmidt JA, et al. Pre-diagnostic metabolite concentrations and prostate cancer risk in 1077 cases and 1077 matched controls in the European Prospective Investigation into Cancer and Nutrition. BMC Med 2017; 15(1): 122. https://doi.org/10.1186/s12916-017-0885-6

• PDF

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.