A Mathematical Model of the Enhancement of Tumor Vaccine Efficacy by Immunotherapy

Bulletin of Mathematical Biology

Volumn 74, Issue 7, 2012, Pages 1485-1500

  Wilson, Shelby ^a   Levy, Doron ^a  

^a Bldg 142   (United States)

Author keywords

Cancer; Immunotherapy

Indexed keywords

CANCER VACCINE; TRANSFORMING GROWTH FACTOR BETA;

ANIMAL; ARTICLE; BIOLOGICAL MODEL; COMPUTER SIMULATION; CYTOTOXIC T LYMPHOCYTE; DENDRITIC CELL; DRUG ANTAGONISM; HUMAN; IMMUNOLOGY; IMMUNOTHERAPY; MOUSE; NEOPLASM; REGULATORY T LYMPHOCYTE;

ANIMALS; CANCER VACCINES; COMPUTER SIMULATION; DENDRITIC CELLS; HUMANS; IMMUNOTHERAPY; MICE; MODELS, BIOLOGICAL; NEOPLASMS; T-LYMPHOCYTES, CYTOTOXIC; T-LYMPHOCYTES, REGULATORY; TRANSFORMING GROWTH FACTOR BETA;

EID: 84861760879     PISSN: 00928240     EISSN: 15229602     Source Type: Journal    
DOI: 10.1007/s11538-012-9722-4     Document Type: Article

References (40)

1. Akhurst, R., & Derynck, R. (2001). TGF-β signaling in cancer-a double-edged sword. Trends Cell Biol., 11(11), S44-S51.
2. Baylor College of Medicine. (2006). Safety study of injections of autologous/allogeneic TGFBeta-resistant LMP2A-specific cytotoxic T lymphocytes (CTL). Bethesda: National Library of Medicine. Available from http://clinicaltrials. gov/ct/show/NCT00368082.
3. Baylor College of Medicine. (2009). Her2 and TGFBeta in treatment of Her2 positive lung malignancy (HERCREEM). Bethesda: National Library of Medicine. Available from http://clinicaltrials. gov/ct/show/NCT00368082.
4. Beyer, M., & Schultze, J. L. (2006). Regulatory T cells in cancer. Blood, 108(3), 804-811.
5. Blattman, J. N., & Greenberg, P. D. (2004). Cancer immunotherapy: a treatment for the masses. Science, 305(5681), 200-205.
6. Blattman, J. N., Antia, R., Sourdive, D. J. D., Wang, X., Kaech, S. M., Murali-Krishna, K., Altman, J. D., & Ahmed, R. (2002). Estimating the precursor frequency of naive antigen-specific CD8 T cells. J. Exp. Med., 195(5), 657-664.
7. Byrne, H., & Gourley, S. (1997). The role of growth factors in avascular tumour growth. Math. Comput. Model., 26(4), 35-55.
8. Cappuccio, A., Elishmereni, M., & Agur, Z. (2006). Cancer immunotherapy by interleukin-21: potential treatment strategies evaluated in a mathematical model. Cancer Res., 66(14), 7293-7300.
9. Castiglione, F., & Piccoli, B. (2006). Optimal control in a model of dendritic cell transfection cancer immunotherapy. Bull. Math. Biol., 68(2), 255-274.
10. Cerwenka, A., & Swain, S. L. (1999). TGF-β1: immunosuppressant and viability factor for T lymphocytes. Microbes Infect., 1(15), 1291-1296.
11. Clarke, D. C., & Liu, X. (2008). Decoding the quantitative nature of TGF-beta/Smad signaling. Trends Cell Biol., 18(9), 430-442.
12. Currie, G. (1972). Eighty years of immunotherapy: a review of immunological methods used for the treatment of human cancer. Br. J. Cancer, 141-153.
13. de Pillis, L. G., Radunskaya, A., & Wiseman, C. L. (2005). A validated mathematical model of cell-mediated immune response to tumor growth. Cancer Res., 65(17), 7950-7958.
14. de Pillis, L. G., Gu, W., & Radunskaya, A. E. (2006). Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations. J. Theor. Biol., 238(4), 841-862.
15. Dermime, S., Armstrong, A., Hawkins, R. E., & Stern, P. L. (2002). Cancer vaccines and immunotherapy. Br. Med. Bull., 62, 149-162.
16. Derynck, R., Akhurst, R. J., & Balmain, A. (2001). TGF-β signaling in tumor suppression and cancer progression. Nat. Genet., 29(2), 117-129.
17. d'Onofrio, A. (2005). A general framework for modeling tumor-immune system competition and immunotherapy: mathematical analysis and biomedical inferences. Physica D, Nonlinear Phenom., 208(3-4), 220-235.
18. Eftimie, R., Bramson, J., & Earn, D. (2011). Interactions between the immune system and cancer: a brief review of non-spatial mathematical models. Bull. Math. Biol., 73, 2-32.
19. Flavell, R. A., Sanjabi, S., Wrzesinski, S. H., & Lixon-Limon, P. (2010). The polarization of immune cells in the tumour environment by TGFβ. Nat. Rev. Immunol., 10(8), 554-567.
20. Kim, P., Lee, P., & Levy, D. (2010). Emergent group dynamics governed by regulatory cells produce a robust primary t cell response. Bull. Math. Biol., 72, 611-644.
21. Kim, P. S., Lee, P. P., & Levy, D. (2007). Modeling regulation mechanisms in the immune system. J. Theor. Biol., 246(1), 33-69.
22. Kirschner, D., & Panetta, J. C. (1998). Modeling immunotherapy of the tumor-immune interaction. J. Math. Biol., 37(3), 235-252.
23. Kirschner, D., Jackson, T., & Arciero, J. (2003). A mathematical model of tumor-immune evasion and siRNA treatment. Discrete Contin. Dyn. Syst., Ser. B, 4(1), 39-58.
24. Kogan, Y., Forys, U., Shukron, O., Kronik, N., & Agur, Z. (2010). Cellular immunotherapy for high grade gliomas: mathematical analysis deriving efficacious infusion rates based on patient requirements. SIAM J. Appl. Math., 70(6), 1953-1976.
25. Kolev, M. (2005). A mathematical model for single cell cancer immune system dynamics. Math. Comput. Model., 41, 1083-1095.
26. Kuznetsov, V., Makalkin, I., Taylor, M., & Perelson, A. (1994). Nonlinear dynamics of immunogenic tumors: parameter estimation and global bifurcation analysis. Bull. Math. Biol.
27. Llopiz, D., Dotor, J., Casares, N., Bezunartea, J., Díaz-Valdés, N., Ruiz, M., Aranda, F., Berraondo, P., Prieto, J., Lasarte, J. J., Borrás-Cuesta, F., & Sarobe, P. (2009). Peptide inhibitors of transforming growth factor-β enhance the efficacy of antitumor immunotherapy. Int. J. Cancer, 125(11), 2614-2623.
28. Michelson, S., & Leith, J. (1991). Autocrine and paracrine growth factors in tumor growth: a mathematical model. Bull. Math. Biol., 53(4), 639-656.
29. Murphy, K., Travers, P., Walport, M., et al. (2008). Immunobiology. New York: Garland Science.
30. Paillard, F. (2000). Immunosuppression mediated by tumor cells: a challenge for immunotherapeutic approaches. Hum. Gene Ther., 11(5), 657-658.
31. Reiss, M. (1999). TGF-β and cancer. Microbes Infect., 1(15), 1327-1347.
32. Ribas, A., Butterfield, L. H., Glaspy, J. A., & Economou, J. S. (2003). Current developments in cancer vaccines and cellular immunotherapy. J. Clin. Oncol., 21(12), 2415-2432.
33. Ribba, B., Colin, T., & Schnell, S. (2006). A multiscale mathematical model of cancer, and its use in analyzing irradiation therapies. Theor. Biol. Med. Model., 3, 7.
34. Rosenberg, S. A. (2001). Progress in human tumour immunology and immunotherapy. Nature, 411(6835), 380-384.
35. Rosenberg, S. A., Yang, J. C., & Restifo, N. P. (2004). Cancer immunotherapy: moving beyond current vaccines. Nat. Med., 10(9), 909-915.
36. Sakaguchi, S., Yamaguchi, T., Nomura, T., & Ono, M. (2008). Regulatory T cells and immune tolerance. Cell, 133(5), 775-787.
37. Sakaguchi, S., Miyara, M., Costantino, C. M., & Hafler, D. A. (2010). FOXP3+ regulatory T cells in the human immune system. Nat. Rev. Immunol., 10(7), 490-500.
38. Terabe, M., Ambrosino, E., Takaku, S., O'Konek, J. J., Venzon, D., Lonning, S., McPherson, J. P., & Berzofsky, J. A. (2009). Synergistic enhancement of CD8+ T cell-mediated tumor vaccine efficacy by an anti-transforming growth factor-β monoclonal antibody. Clin. Cancer Res., 15(21), 6560-6569.
39. Wang, S. E., Hinow, P., Bryce, N., Weaver, A. M., Estrada, L., Arteaga, C. L., & Webb, G. F. (2009). A mathematical model quantifies proliferation and motility effects of TGF-β on cancer cells. Comput. Math. Methods Med., 10(1), 71-83.
40. Wilson, S. N., Lee, P., & Levy, D. (2010). A mathematical model of the primary T cell response with contraction governed by adaptive regulatory T cells. In K. E. Herold, W. E. Bentley, & J. Vossoughi (Eds.), Proceedings IFMBE (Vol. 32, pp. 209-212). Berlin: Springer.