Log in

Analytical and numerical solutions for glial cells interactions between ’chemo-immunotherapy and cancer’

  • Application Article
  • Published:
OPSEARCH Aims and scope Submit manuscript

Abstract

Cancer continues to be one of the most daunting obstacles to human health, which is why there is a never-ending attempt to create therapies that are particularly successful. For the purpose of improving treatment options and actively combating brain tumours, it is critical to have a complete comprehension of the intricate interactions that occur between cancer cells, the immune system, and therapeutic treatments. So, we suggest a model that shows how healthy cells (glial) and glioma cells (cancer cells), neurons, CD8+ T cells, macrophages, immunotherapy, and chemotherapy interact with each other by using differential equations. Positivity and boundedness are investigated. A further investigation of the analytical procedure has been carried out. Additionally, stability analysis is evaluated, and numerical simulations are provided in three different categories for the model that we have presented. A graph comparison is made between the numerical and the analytical in order to figure out the model’s quality in the discussion and conclusion. Among them, chemo-immunotherapy has emerged as a promising strategy that allows for the use of the synergistic effects of immunotherapy and chemotherapy in order to battle the development of tumours and the spread of diseases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. DeAngelis, L.M.: Brain tumors. N. Engl. J. Med. 344, 114–123 (2001). https://doi.org/10.1056/nejm200101113440207

    Article  Google Scholar 

  2. Dunn, G.P., Lloyd, J.O., Robert, D.S.: The three Es of cancer immunoediting. Annu. Rev. Immunol. 22, 329–360 (2004). https://doi.org/10.1146/annurev.immunol.22.012703.104803

    Article  Google Scholar 

  3. Khajanchi, S.: Bifurcation analysis of a delayed mathematical model for tumor growth. Chaos Solitons Fract. 77, 264–276 (2015). https://doi.org/10.1016/j.chaos.2015.06.001

    Article  Google Scholar 

  4. Philip, G., Sven, N.: The impact of phenotypic switching on glioblastoma growth and invasion. PLoS Comput. Biol. 8, 1002556 (2012). https://doi.org/10.1371/journal.pcbi.1002556

    Article  Google Scholar 

  5. Kronik, N., Yuri, K., Vladimir, V., Zvia, A.: Improving alloreactive CTL immunotherapy for malignant gliomas using a simulation model of their interactive dynamics. Cancer Immunol. Immunother. 57, 441 (2008). https://doi.org/10.1007/s00262-007-0432-y

    Article  Google Scholar 

  6. Nandi, S., Khajanchi, S., Chatterjee, A.N., Roy, P.K.: Insight of viral infection of Jatropha curcas plant (future fuel): a control based mathematical study. Acta Anal. Funct. Appl. 13, 366–374 (2011). https://doi.org/10.3724/SP.J.1160.2011.00366

    Article  Google Scholar 

  7. Khajanchi, S.: Modeling the dynamics of glioma-immune surveillance. Chaos Solitons Fract. 114, 108–118 (2018). https://doi.org/10.1016/j.chaos.2018.06.028

    Article  Google Scholar 

  8. Gosak, M., Markovic, R., Jurij, D.: Network science of biological systems at different scales: A review. Phys. Life Rev. 24, 118–135 (2018). https://doi.org/10.1016/j.plrev.2017.11.003

    Article  Google Scholar 

  9. Banerjee, S., Khajanchi, S., Chaudhuri, S.: A mathematical model to elucidate brain tumor abrogation by immunotherapy with t11 target structure. PLoS ONE 10, 0123611 (2015). https://doi.org/10.1371/journal.pone.0123611

    Article  Google Scholar 

  10. Swanson, K., Carly, B., Murray, J.D.: Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion. J. Neurol. Sci. 216, 1–10 (2003). https://doi.org/10.1016/j.jns.2003.06.001

    Article  Google Scholar 

  11. Mokhtari, R.B., Homayouni, T.S., Baluch, N.: Combination therapy in combating cancer. Oncotarget 8, 38022–38043 (2017). https://doi.org/10.18632/oncotarget.16723

    Article  Google Scholar 

  12. Schreiber, R.D., Old, L.J., Smyth, M.J.: Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science 331, 1565–1570 (2011). https://doi.org/10.1126/science.1203486

    Article  Google Scholar 

  13. Hickey, W.F.: Basic principles of immunological surveillance of the normal central nervous system. Glia 36, 118–124 (2001). https://doi.org/10.1002/glia.1101

    Article  Google Scholar 

  14. Iarosz, K.C., Fernando, S.B., Antonio, M.B.: Mathematical model of brain tumour with glia-neuron interactions and chemotherapy treatment. J. Theor. Biol. 368, 113–121 (2015). https://doi.org/10.1016/j.jtbi.2015.01.006

    Article  Google Scholar 

  15. Khajanchi, S.: Stability analysis of a mathematical model for glioma–immune interaction under optimal therapy. Int. J. Nonlinear Sci. Numer. Simul. 20, 269–285 (2019). https://doi.org/10.1515/ijnsns-2017-0206

    Article  Google Scholar 

  16. Pinho, S.T.R., Bacelar, F.S., Andrade, R.F.S.: A mathematical model for the effect of anti-angiogenic therapy in the treatment of cancer tumours by chemotherapy. Nonlinear Anal. Real World Appl. 14, 815–828 (2013). https://doi.org/10.1016/j.nonrwa.2012.07.034

    Article  Google Scholar 

  17. Spratt, J.S., Spratt, T.L.: Rates of growth of pulmonary metastases and host survival. Ann. Surg. 159, 161–171 (1964). https://doi.org/10.1097/00000658-196402000-00001

    Article  Google Scholar 

  18. Rzeski, W., Pruskil, S., Alexander, M.: Anticancer agents are potent neurotoxins in vitro and in vivo. Ann. Neurol. 56, 351–360 (2004). https://doi.org/10.1002/ana.20185

    Article  Google Scholar 

  19. Stupp, R., et al.: Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 352, 987–996 (2005). https://doi.org/10.1056/nejmoa043330

    Article  Google Scholar 

  20. Borges, F.S., Iarosz, K.C., Ren, H.P.: Model for tumour growth with treatment by continuous and pulsed chemotherapy. Biosystems 116, 43–48 (2014). https://doi.org/10.1016/j.biosystems.2013.12.001

    Article  Google Scholar 

  21. Frederico, A.C.A., Ludmila, R.B., Lea, T.G.: Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J. Comp. Neurol. 513, 532–541 (2009). https://doi.org/10.1002/cne.21974

    Article  Google Scholar 

  22. Kuznetsov, V., Makalkin, I., Taylor, M., Perelson, A.: Nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis. Bull. Math. Biol. 56, 295–321 (1994). https://doi.org/10.1016/s0092-8240(05)80260-5

    Article  Google Scholar 

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

Authors

Contributions

Each contributor made an equal contribution to the paper. The article was reviewed and approved by all writers.

Corresponding author

Correspondence to E. Vargees Kaviyan.

Ethics declarations

Conflict of interest

There is no conflict of interest declared by the authors.

Code availability

Not applicable.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kaviyan, E.V., Jayakumar, T., Sujitha, S. et al. Analytical and numerical solutions for glial cells interactions between ’chemo-immunotherapy and cancer’. OPSEARCH (2024). https://doi.org/10.1007/s12597-024-00812-x

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12597-024-00812-x

Keywords

Navigation