Thrombosis And High Cellular Density Impact On Glioma Growth: A Revised Mathematical Model

Author: Omar Emam

Abstract

A glioma is a tumor that forms when glial cells grow out of control. All its treatments typically merely prolong the patient's life by a few weeks. Helping to solve this problem, several studies were made to predict glioma growth, including Sturrock et al. In 2015, Sturrock et al. utilized the several literatures that exhibited a relation between pre-diagnostic serum glucose levels and the hazard ratio of the glioma occurrence. Four differential equations are used to describe pre-diagnostic glioma interactions. In this paper, Sturrock et al.'s work is revised, including the effect of microenvironmental factors, thrombosis and high cellular density, on glioma growth, showing how they lead to further complications. Further data of the effects of more microenvironmental phenomena is also shown, helping in better diagnosis of glioma. To overcome the lack of data of pre-diagnostic glioma, further work is needed, advancing our understanding of tumor-microenvironment interactions.

Read online

Please click here to read this article online.

Download PDF

Thrombosis and High Cellular Density Impact on Glioma Growth A revised Mathematical Model

Download • 1.24MB

References

Sturrock, Marc, et al. “A Mathematical Model of Pre-Diagnostic Glioma Growth.” Journal of Theoretical Biology, vol. 380, Sept. 2015, pp. 299–308, https://doi.org/10.1016/j.jtbi.2015.06.003.

IJzerman-Korevaar, Margriet, et al. “Prevalence of Symptoms in Glioma Patients throughout the Disease Trajectory: A Systematic Review.” Journal of Neuro- Oncology, vol. 140, no. 3, 30 Oct. 2018, pp. 485–496, https://doi.org/10.1007/s11060-018-03015-9.

M. Y. Zaky, N. S. Lamloum, N. Y. S. Yassin, and O. M. Ahmed, “Brain tumors: types, diagnostic biomarkers, and new therapeutic approaches,” in Handbook of Oncobiology: From Basic to Clinical Sciences, 2023, pp. 1–21. doi: 10.1007/978-981-99-2196-6_21-1.

Flavahan, William A, et al. “Brain Tumor Initiating Cells Adapt to Restricted Nutrition through Preferential Glucose Uptake.” Nature Neuroscience, vol. 16, no. 10, 1 Sept. 2013, pp. 1373–1382, https://doi.org/10.1038/nn.3510.

Edlinger, Michael, et al. “Blood Pressure and Other Metabolic Syndrome Factors and Risk of Brain Tumour in the Large Population-Based Me-Can Cohort Study.” Journal of Hypertension, vol. 30, no. 2, 1 Feb. 2012, pp. 290–296, journals.lww.com/jhypertension/Abstract/2012/02000/Blood_pressure_and_ other_metabolic_syndrome.9.aspx,https://doi.org/10.1097/HJH.0b013e3283 4e9176.

Spill, Fabian, et al. “Impact of the Physical Microenvironment on Tumor Progression and Metastasis.” Current Opinion in Biotechnology, vol. 40, Aug. 2016, pp. 41–48, https://doi.org/10.1016/j.copbio.2016.02.007.

Lin, Hao, et al. “Understanding the Immunosuppressive Microenvironment of Glioma: Mechanistic Insights and Clinical Perspectives.” Journal of Hematology & Oncology, vol. 17, no. 1, 8 May 2024, https://doi.org/10.1186/s13045-024-01544-7.

V. E. Mikkelsen et al., “Histopathologic Features in Relation to Pretreatment Tumor Growth in Patients with Glioblastoma,” World Neurosurgery, vol. 109, pp. e50–e58, Jan. 2018, doi: 10.1016/j.wneu.2017.09.102.

Zhang, Ian Y., et al. “Local and Systemic Immune Dysregulation Alters Glioma Growth in Hyperglycemic Mice.” Clinical Cancer Research, vol. 26, no. 11, 1 June 2020, pp. 2740–2753, https://doi.org/10.1158/1078-0432.ccr-19-2520.

Powathil, Gibin G, et al. Mathematical Modeling of Brain Tumors: Effects of Radiotherapy and Chemotherapy. Vol. 52, no. 11, 7 June 2007, pp. 3291–

3306, https://doi.org/10.1088/0031-9155/52/11/023.

K. R. Swanson, C. Bridge, J. D. Murray, and E. C. Alvord, “Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion,” Journal of the Neurological Sciences, vol. 216, no. 1, pp. 1–10, Dec. 2003, doi: 10.1016/j.jns.2003.06.001.

Toma, A., Holl-Ulrich, K., Becker, S., Mang, A., Schütz, T.A., Bonsanto, M.M., Tronnier, V., Buzug, T.M., 2012. A mathematical model to simulate glioma growth and radiotherapy at the microscopic level. Biomed. Technol. 57, 218– 221.

Y. Kim, “Regulation of cell proliferation and migration in glioblastoma: new therapeutic approach,” Frontiers in Oncology, vol. 3, Jan. 2013, doi: 10.3389/fonc.2013.00053.

Matzavinos, A. “Mathematical Modelling of the Spatio-Temporal Response of Cytotoxic T-Lymphocytes to a Solid Tumour.” Mathematical Medicine and Biology, vol. 21, no. 1, 1 Mar. 2004, pp. 1–34, https://doi.org/10.1093/imammb/21.1.1.

Man, C.D., Rizza, R.A., Cobelli, C., 2007. Meal simulation model of glucose-insulin system. IEEE Trans. Biomed. Eng. 54, 1740–1749.

L. E. Ayala-Hernández, A. Gallegos, J. E. Macías-Díaz, M. L. Miranda-Beltrán, and

H. Vargas-Rodríguez, “A mathematical model for the pre-diagnostic of glioma growth based on blood glucose levels,” Journal of Mathematical Chemistry, vol. 56, no. 3, pp. 687–699, Oct. 2017, doi: 10.1007/s10910-017-0821-1.

H. Lin, C. Liu, A. Hu, D. Zhang, H. Yang, and Y. Mao, “Understanding the immunosuppressive microenvironment of glioma: mechanistic insights and clinical perspectives,” Journal of Hematology & Oncology, vol. 17, no. 1, May 2024, doi: 10.1186/s13045-024-01544-7.

M. Regmi et al., “From glioma gloom to immune bloom: unveiling novel immunotherapeutic paradigms-a review,” Journal of Experimental & Clinical Cancer Research, vol. 43, no. 1, Feb. 2024, doi: 10.1186/s13046-024-02973- 5.

Q. Liu and P. Cao, “Clinical and prognostic significance of HIF-1α in glioma patients: a meta-analysis,” PubMed Central (PMC), 2015. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729968/

C. Chen et al., “Allergy and risk of glioma: a meta-analysis,” European Journal of Neurology, vol. 18, no. 3, pp. 387–395, Aug. 2010, doi: 10.1111/j.1468- 1331.2010.03187.x.

J. Schwartzbaum et al., “Association between prediagnostic IGE levels and risk of glioma,” JNCI Journal of the National Cancer Institute, vol. 104, no. 16, pp. 1251–1259, Aug. 2012, doi: 10.1093/jnci/djs315.

L. Disney-Hogg et al., “Influence of obesity-related risk factors in the aetiology of glioma,” British Journal of Cancer, vol. 118, no. 7, pp. 1020–1027, Mar. 2018, doi: 10.1038/s41416-018-0009-x.

J. Anjom-Shoae et al., “Dietary insulin index and insulin load in relation to glioma: findings from a case–control study,” Nutritional Neuroscience, vol. 24, no. 5,

pp. 354–362, Jun. 2019, doi: 10.1080/1028415x.2019.1631594.

W. Yang et al., “Association between psychiatric disorders and glioma risk: evidence from Mendelian randomization analysis,” BMC Cancer, vol. 24, no. 1, Jan. 2024, doi: 10.1186/s12885-024-11865-y.

V. E. Mikkelsen et al., “Angiogenesis and radiological tumor growth in patients with glioblastoma,” BMC Cancer, vol. 18, no. 1, Sep. 2018, doi: 10.1186/s12885- 018-4768-9.

H. Malmir, M. Shayanfar, M. Mohammad-Shirazi, H. Tabibi, G. Sharifi, and A. Esmaillzadeh, “Patterns of nutrients intakes in relation to glioma: A case- control study,” Clinical Nutrition, vol. 38, no. 3, pp. 1406–1413, Jun. 2019, doi: 10.1016/j.clnu.2018.06.961.

H. Ohgaki and P. Kleihues, “Epidemiology and etiology of gliomas,” Acta Neuropathologica, vol. 109, no. 1, pp. 93–108, Jan. 2005, doi: 10.1007/s00401-005-0991-y.

D. H. Lachance et al., “Associations of High-Grade glioma with glioma risk alleles and histories of allergy and smoking,” American Journal of Epidemiology, vol. 174, no. 5, pp. 574–581, Jul. 2011, doi: 10.1093/aje/kwr124.

X. Xu, L. Xi, J. Zeng, and Q. Yao, “A Functional +61G/A Polymorphism in Epidermal Growth Factor Is Associated with Glioma Risk among Asians,” PLoS ONE, vol. 7, no. 7, p. e41470, Jul. 2012, doi: 10.1371/journal.pone.0041470.

U. Andersson et al., “A comprehensive study of the association between the EGFR and ERBB2 genes and glioma risk,” Acta Oncologica, vol. 49, no. 6, pp. 767– 775, May 2010, doi: 10.3109/0284186x.2010.480980.

T. Harder, A. Plagemann, and A. Harder, “Birth Weight and subsequent Risk of childhood Primary Brain Tumors: A Meta-Analysis,” American Journal of Epidemiology, vol. 168, no. 4, pp. 366–373, Jun. 2008, doi: 10.1093/aje/kwn144.

G. Bao, M. Wang, S. Guo, Y. Han, and G. Xu, “Association between Epidermal Growth Factor +61 G/A Polymorphism and Glioma Risk in a Chinese Han Population,” Journal of International Medical Research, vol. 38, no. 5, pp. 1645–1652, Oct. 2010, doi: 10.1177/147323001003800509.

Y. Wang et al., “Does diabetes decrease the risk of glioma? A systematic review and meta-analysis of observational studies,” Annals of Epidemiology, vol. 30, pp. 22-29.e3, Feb. 2019, doi: 10.1016/j.annepidem.2018.11.010.

Ameer, Muhammad, et al. “Thrombosis.” PubMed, StatPearls Publishing, 2022, pubmed.ncbi.nlm.nih.gov/30860701/.

J. R. Perry, “Thromboembolic disease in patients with high-grade glioma,” Neuro- Oncology, vol. 14, no. suppl 4, pp. iv73–iv80, Sep. 2012, doi: 10.1093/neuonc/nos197.

M. Tehrani, T. M. Friedman, J. J. Olson, and D. J. Brat, “RESEARCH ARTICLE: Intravascular thrombosis in Central Nervous System Malignancies: A potential role in Astrocytoma Progression to Glioblastoma,” Brain Pathology, vol. 18, no. 2, pp. 164–171, Jan. 2008, doi: 10.1111/j.1750- 3639.2007.00108.x.

H. Katoh, I. Yamaguchi, and S. H. Yoshimura, “High cell density increases glioblastoma cell viability under glucose deprivation via degradation of the cystine/glutamate transporter XCT (SLC7A11),” JBC ARTICLE, Dec. 2019, doi: 10.1074/jbc.RA119.012213.