Modeling cancer-immune responses to therapy
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Bray F, Jemal A, Grey N, Ferlay J, Forman D (2012) Global cancer transitions according to the Human Development Index (20082030): a population-based study. Lancet Oncol 13:790–801
Biemar F, Foti M (2013) Global progress against cancer-challenges and opportunities. Cancer Biol Med 10:183–6
Topalian SL, Weiner GJ, Pardoll DM (2011) Cancer Immunotherapy Comes of Age. J Clin Oncol 29:4828–4836
Gorelik B, Ziv I, Shohat R, Wick M, Hankins WD, Sidransky D et al (2008) Efficacy of weekly docetaxel and bevacizumab in mesenchymal chondrosarcoma: a new theranostic method combining xenografted biopsies with a mathematical model. Cancer Res 68(21):9033–9040
Besse IM, Madsen MT, Bushnell DL, Juweid ME (2009) Modeling combined radiopharmaceutical therapy: a linear optimization framework. Technol Cancer Res Treat 8(1):51–60
Marqa MF, Mordon S, Betrouni N (2012) Laser interstitial thermotherapy of small breast fibroadenomas: numerical simulations. Lasers Surg Med 44(10):832–839
Berris T, Mazonakis M, Stratakis J, Tzedakis A, Fasoulaki A, Damilakis J (2013) Calculation of organ doses from breast cancer radiotherapy: a Monte Carlo study. J Appl Clin Med Phys 14(1):133–146
Traina TA, Theodoulou M, Feigin K, Patil S, Tan KL, Edwards C et al (2008) Phase I study of a novel capecitabine schedule based on the Norton-Simon mathematical model in patients with metastatic breast cancer. J Clin Oncol 26(11):1797–1802
Comen E, Morris PG, Norton L (2012) Translating mathematical modeling of tumor growth patterns into novel therapeutic approaches for breast cancer. J Mammary Gland Biol Neoplasia 17(3—-4, SI):241–249
Newton PK, Mason J, Bethel K, Bazhenova L, Nieva J, Norton L et al (2013) Spreaders and sponges define metastasis in lung cancer: a Markov Chain Monte Carlo mathematical model. Cancer Res 73(9):2760–2769
The annual 2013 Pharmaceutical Industry Profile. http://www.phrma.org/industryprofile2013 ; 2013. Accessed March 23, 2014
Agur Z, Vuk-Pavlovic S (2012) Mathematical modeling in immunotherapy of cancer: personalizing clinical trials. Mol Ther 20(1):1
Eftimie R, Bramson JL, Earn DJ (2011) Interactions between the immune system and cancer: a brief review of non-spatial mathematical models. Bull Math Biol 73:2–32
Ledzewicz U, Faraji M, Schaettler H (2012) On Optimal Protocols for Combinations of Chemo- and Immunotherapy. Proceedings of 51st IEEE Conference on Decision and Control, Maui 2012;pp. 7492–7497
d’Onofrio A, Ledzewicz U, Schaettler H (2012) New challenges for cancer systems biology. Springer Verlag, New York
d’Onofrio A (2008) Metamodeling tumor-immune system interaction, tumor evasion and immunotherapy. Math Comput Model 47(5):614–637
d’Onofrio A (2005) A general framework for modeling tumor-immune system competition and immunotherapy: mathematical analysis and biomedical inferences. Physica D 208(3):220–235
Agur Z, Arakelyan L, Merbl Y, Daugulis P, Ginosar Y, Vainstein V, et al. (2003) Cancer Modeling and Simulation. CRC Press/Chapman & Hall, ed: Luigi Preziosi; 2003. p. 185–219
Bar-Or R (2000) Feedback mechanisms between T helper cells and macrophages in the determination of the immune response. Math Biosci 163(1):35–58
Castiglione FF, Piccoli B (2006) Optimal control in a model of dendritic cell transfection cancer immunotherapy. Bull Math Biol 68(2):255–274
De Boer RJ, Hogeweg P, Dullens HF, De Weger RA, Den Otter W (1985) Macrophage T lymphocyte interactions in the anti-tumor immune response: a mathematical model. J Immunol 134(4):2748–2758
Rihan F, Abdel Rahman D, Lakshmanan S, Alkhajeh A (2014) A time delay model of tumourimmune system interactions:Global dynamics, parameter estimation, sensitivity analysis. Appl Math Comput 232:606–623
Kronik N, Kogan Y, Vainstein V, Agur Z (2008) Improving alloreactive CTL immunotherapy for malignant gliomas using a simulation model of their interactive dynamics. Cancer Immunol Immunother 57(3):425–439
Kuznetsov V (1997) Basic models of tumor-immune system interactions - identification, analysis and predictions. In: Adam J, Bellomo N (eds) A survey of models for tumor-immune system dynamics. Springer, New York, pp 237–294
Lin A (2004) A model of tumor and lymphocyte interactions. Discrete Contin Dyn Syst Ser B 4(1):241–266
Mallet DG, de Pillis LG (2006) A cellular automata model of tumor-immune system interactions. J Theor Biol 239(3):334–350
Nazari S, Basirzadeh H (2014) Natural Killer or T-lymphocyte cells: which is the best immune therapeutic agent for cancer? an optimal control approach. Int J Control Autom Syst 12:84–92
Takayanagi T, Ohuchi A (2001) A mathematical analysis of the interactions between immunogenic tumor cells and cytotoxic T lymphocytes. Microbiol Immunol 45(10):709–715
de Vladar HP, Gonzalez JA (2004) Dynamic response of cancer under the influence of immunological activity and therapy. J Theor Biol 227(3):335–348
Wein LM, Wu JT, Kirn DH (2003) Validation and analysis of a mathematical model of a replication-competent oncolytic virus for cancer treatment: implications for virus design and delivery. Cancer Res 63(6):1317–1324
Yueping Dong Rinko Miyazaki YT (2014) Mathematical modeling on helper T cells in a tumor immune system. Discret Contin Dyn Syst Ser B 19:55–72
Kuznetsov V, Makalkin I, Taylor M, Perelson A (1994) Nonlinear dynamics of immunogenic tumors: Parameter estimation and global bifurcation analysis. Bull Math Biol 56(2):295–321
de Pillis L, Radunskaya AE (2014) Modeling of tumor-immune dynamics. In: Eladdadi A, Kim P (eds) Mathematical modeling of tumor-immune dynamics. Springer, New York, pp 67–115
Roesch K, Hasenclever D, Scholz M (2014) Modelling Lymphoma Therapy and Outcome. Bull Math Biol 76(2):401–430
Pfreundschuh M, Trmper L, Kloess M, Schmits R, Feller AC, Rudolph C et al (2004) Two-weekly or 3-weekly CHOP chemotherapy with or without etoposide for the treatment of young patients with good-prognosis (normal LDH) aggressive lymphomas: results of the NHL-B1 trial of the DSHNHL. Blood 104(3):626–633
Pfreundschuh M, Trmper L, Kloess M, Schmits R, Feller AC, Rbe C et al (2004) Two-weekly or 3-weekly CHOP chemotherapy with or without etoposide for the treatment of elderly patients with aggressive lymphomas: results of the NHL-B2 trial of the DSHNHL. Blood 104(3):634–641
Pfreundschuh M, Schubert J, Ziepert M, Schmits R, Mohren M, Lengfelder E et al (2008) Six versus eight cycles of bi-weekly CHOP-14 with or without rituximab in elderly patients with aggressive $$\text{ CD20 }^+$$ CD20 + B-cell lymphomas: a randomised controlled trial (RICOVER-60). Lancet Oncol 9:105–116
Thomlinson R (1982) Measurement and management of carcinoma of the breast. Clin Radiol 33(5):481–493
de Pillis L, Radunskaya A (2001) A mathematical tumor model with immune resistance and drug therapy: an optimal control approach. J Theor Med 3:79–100
de Pillis L, Radunskaya A (2003) The dynamics of an optimally controlled tumor model: a case study. Math Comput Model (Special Issue) 37:1221–1244
de Pillis L, Gu W, Fister K, Head T, Maples K, Murugan A et al (2007) Chemotherapy for tumors: an analysis of the dynamics and a study of quadratic and linear optimal controls. Math Biosci 209:292–315
de Pillis L, Radunskaya A (2012) Best practices in mathematical modeling. In: Mayeno A, Reisfeld B (eds) Computational toxicology, methods in molecular biology, part 2. Springer, New York, pp 51–74
dePillis LG, Radunskaya AE, Wiseman CL (2005) A validated mathematical model of cell-mediated immune response to tumor growth. Cancer Res 65(1):7950–7958
Lai R, Jackson T (2004) A mathematical model of receptor-mediated apoptosis: dying to know why FasL is a trimer. Math Biosci Eng 1(2):325–338
Diefenbach A, Jensen E, Jamieson A, Raulet D (2001) Rae1 and H60 ligands of the NKG2D receptor stimulate tumor immunity. Nature 413:165–171
Dudley ME, Wunderlich JR, Robbins PF, Yang JC, Hwu P, Schwartzentruber DJ et al (2002) Cancer regression and autoimmunity in patients after Clonal repopulation with antitumor lymphocytes. Science 298(5594):850–854
Castiglione FF, Castiglione V, Agur Z (2003) Cancer Modelling and Simulation. Chapman & Hall/CRC Mathematical and Computational Biology, Luigi Preziosi, ed.; 2003. p. 333–366
Roeder I, Horn M, Glauche I, Hochhaus A, Mueller M, Loeffler M (2006) Dynamic modeling of imatinib-treated chronic myeloid leukemia: functional insights and clinical implications. Nat Med 12:11811184
Michor F, Hughes T, Iwasa Y, Branford S, Shah N, Sawyers C et al (2005) Dynamics of chronic myeloid leukemia. Nature 435:1267–1270
Kim PS, Lee PP, Levy D (2008) Modeling imatinib-treated chronic myelogenous leukemia: reducing the complexity of agent-based models. Bull Math Biol 70(3):728–744
Kim PS, Lee PP, Levy D (2008) A PDE model for imatinib-treated chronic myelogenous leukemia. Bull Math Biol 70(7):1994–2016
Paquin D, Kim PS, Lee PP, Levy D (2011) Strategic treatment interruptions during imatinib treatment of chronic myelogenous leukemia. Bull Math Biol 73(5):1082–1100
Rosenberg SA (2004) Development of effective immunotherapy for the treatment of patients with cancer. J Am Coll Surg 198(5):685
Wainwright DA, Nigam P, Thaci B, Dey M, Lesniak MS (2012) Recent developments on immunotherapy for brain cancer. Expert Opin Emerg Drugs 17:181–201
Kirschner DD, Panetta JC (1998) Modeling immunotherapy of the tumor - immune interaction. J Math Biol 37(3):235–252
Goldsby RA, Kindt TJ, Osborne BA, Kuby J (2003) Immunology, 5th edn. W. H. Freeman, New York
Rosenberg S, Yang J, Schwartzentruber D, Hwu P, Marincola F, Topalian S et al (1999) Prospective randomized trial of the treatment of patients with metastatic melanoma using chemotherapy with cisplatin, dacarbazine, and tamoxifen alone or in combination with interleukin-2 and interferon alfa-2b. J Clin Oncol 17(3):968–975
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
Bellomo N, Bellouquid A, Delitala M (2004) Mathematical topics on the modelling complex multicellular systems and tumor immune cells competition. Math Models Methods Appl Sci 14(11):1683–1733
Bellomo N, Preziosi L (2000) Modelling and mathematical problems related to tumor evolution and its interaction with the immune system. Math Comput Model 32(3):413–452
Bellomo N, Bellouquid A, DeAngelis E (2003) The modelling of the immune competition by generalized Kinetic (Boltzmann) MModel: review and research Perspectives. Math Comput Model 37:65–86
Bellomo N, Bertotti ML, Motta S (2003) Cancer Modelling and Simulation. Chapman & Hall/CRC Mathematical and Computational Biology, Luigi Preziosi, ed.; 2003. p. 299–332
Bellomo N, Forni G (2006) Looking for new paradigms towards a biological-mathematical theory of complex multicellular systems. Math Model Methods Appl Sci 16:1001–1029
Antony P, Restifo N (2005) CD4+CD25+ T regulatory cells, immunotherapy of cancer, and interleukin-2. J Immunother 28(2):120–128
Radunskaya A, Hook S (2012) Modeling the Kinetics of the immune response. In: d’Onofrio A, Cerrai P, Gandolfi A (eds) New challenges for cancer systems biomedicine. Springer-Verlag, New York, pp 267–282
Cheever MA (2011) PROVENGE (Sipuleucel-T) in Prostate Cancer: The first FDA-Approved Therapeutic Cancer Vaccine. Clin Cancer Res 17(11):3520–3526
de Pillis L, Gallegos A, Radunskaya A (2013) A model of dendritic cell therapy for melanoma. Front Oncol 3(56):1–14
Ludewig BB, Krebs P, Junt T, Metters H, Ford NJ, Anderson RM et al (2004) Determining control parameters for dendritic cell-cytotoxic T lymphocyte interaction. Eur J Immunol 34(9):2407–2418. doi: 10.1002/eji.200425085
Lee TH, Cho YH, Lee MG (2007) Larger numbers of immature dendritic cells augment an anti-tumor effect against established murine melanoma cells. Biotechnol Lett 29(3):351–357
Preynat-Seauve O, Contassot E, Schuler P, French LE, Huard B (2007) Melanoma-infiltrating dendritic cells induce protective antitumor responses mediated by T cells. Melanoma Res 17:169–176
de Pillis L, Caldwell T, Sarapata E, Williams H (2013) Mathematical modeling of the regulatory T cell effects on renal cell carcinoma treatment. Discret Contin Dyn Syst Ser B 18(4):915–943
Meropol N, Barresi G, Fehniger T, Hitt J, Franklin M, Caligiuri M (1998) Evaluation of natural killer cell expansion and activation in vivo with daily subcutaneous low-dose interleukin-2 plus periodic intermediate-dose pulsing. Cancer Immunol Immunother 46:318326
Jea Ko (2009) Sunitinib mediates reversal of myeloid-derived suppressor cell accumulation in renal cell carcinoma patients. Clin Cancer Res 6:2148–2157
Nanda S, dePillis LG, Radunskaya AE (2013) B cell chronic lymphocytic leukemia — a model with immune response. Discret Contin Dyn Syst Ser B 18(4):1053–1076
Messmer BT, Messmer D, Allen SL, Kolitz JE, Kudalkar P, Cesar D et al (2005) In vivo measurements document the dynamic cellular kinetics of chronic lymphocytic leukemia B cells. J Clin Invest 115:755–764
Ramos RA, Zapata J, Condat CA, Deisboeck TS (2013) Modeling cancer immunotherapy: assessing the effects of lymphocytes on cancer cell growth and motility. Physica A 392:2415–2425
Kang-Ling Liao Xue-Feng Bai AF (2014) Mathematical modeling of Interleukin-27 induction of anti-tumor T cells response. PLoS ONE 9(3):e91844
Dong Y, Miyazaki R, Takeuchi Y (2014) Mathematical modeling on helper T cells in a tumor immune system. Discret Contin Dyn Syst Ser B 19:55–72
Galach M (2003) Dynamics of the tumor-immune system competition - the effect of time delay. Int J Appl Math Comput Sci 13:395–406
de Pillis L, Gu W, Radunskaya A (2006) Mixed immunotherapy and chemotherapy of tumors: modeling applications and biological interpretations. J Theor Biol 238(4):841–862
Yee C, Thompson JA, Byrd D, Riddell SR, Roche P, Celis E et al (2002) Adoptive T cell therapy using antigen-specific CD8+ T cell clones for the treatment of patients with metastatic melanoma: In vivo persistence, migration, and antitumor effect of transferred T cells. Proc Natl Acad Sci USA 99(25):16168–16173
Dillman RO, DePriest C, McClure SE (2014) High-Dose IL2 in metastatic melanoma: better survival in patients immunized with antigens from autologous tumor cell lines. Cancer Biother Radiopharm 29(2):53–57
Machiels J, Reilly R, Emens L, Ercolini A, Lei R, Weintraub D et al (2001) Cyclophosphamide, doxorubicin, and paclitaxel enhance the antitumor immune response of granulocyte/macrophage-colony stimulating factor-secreting whole-cell vaccines in HER-2/neu tolerized mice. Cancer Res 61(9):3689–3697
de Pillis L, Fister KR, Gu W, Collins C, Daub M, Gross D et al (2009) Mathematical model creation for cancer chemo-immunotherapy. Comput Mat Methods Med 10(3):165–184
de Pillis LG, Fister KR, Gu W, Collins C, Daub M, Gross D et al (2007) Seeking bang-bang solutions of mixed immuno-chemotherapy of tumors. Electron J Diff Eqns 171:1–24
de Pillis LG, Fister KR, Gu W, Head T, Maples K, Neal T et al (2008) Optimal control of mixed immunotherapy and chemotherapy of tumors. J Biol Syst 16(1):51–80
de Pillis LG, Radunskaya AE, Savage H (2014) Mathematical model of colorectal cancer with monoclonal antibody treatments. Br J Med Med Res 4(16):3101–3131
Lenz HJ (2007) Cetuximab in the management of colorectal cancer. Biol: Targ Ther 2:77–91
Grothey AM (2006) Defining the role of panitumumab in colorectal cancer. Commun Oncol 3:10–16
Gravalos C, Cassinello J, Garcia-Alfonso P, Jimeno A (2010) Integration of panitumumab into the treatment of colorectal cancer. Crit Rev Oncol/Hematol 74(1):16–26
De Vita VJ, Hellman S, Rosenberg S (2000) Cancer: principles and practice of oncology, 7th edn. Lippincott Wiliams & Wilkins, Philadelphia
Kim PS, Lee PP, Levy D (2008) Dynamics and potential impact of the immune response to chronic myelogenous leukemia. PLoS Comput Biol 4(6):e1000095
Peet MM, Kim PS, Niculescu SI, Levy D (2009) New computational tools for modeling chronic myelogenous leukemia. Math Model Nat Phenom 4:119–139
Radunskaya A, de Pillis L, Gallegos A (2013) A model of dendritic cell therapy for melanoma. Front Oncol 3:56