Computer Simulation of Tumour Response to Therapy

Cancer Bioinformatics: From Therapy Design to Treatment

Volumn , Issue , 2006, Pages 109-125

  Stamatakos, Georgios S ^a,b   Uzunoglu, Nikolaos ^a,b  

^a INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Chemotherapy response simulation; Computer simulation efforts; DNA and protein microarrays; Efficacy toxicity mathematical model; Finite difference time domain (FDTD) technique; Mathematical analysis and discrete mathematics; Radiotherapy response simulation; Tumour simulation models; Tumour vulnerability identification

Indexed keywords

EID: 84890003708     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/0470032898.ch6     Document Type: Chapter

References (65)

1. Adam, J. A. and Maggelakis, S. A. 1990. Diffusion regulated growth characteristics of a spherical prevascular carcinoma. Bull. Math. Biol. 52: 549-582.
2. Alcalay, M., Orleth, A., Sebastiani, C., Meani, N., Chiaradonna, F., Casciari, C., Sciurpi, M. T., Gelmetti, V., Riganelli, D., Minucci, S., Fagioli, M. and Pelicci, P.G. 2001. Common themes in the pathogenesis of acute myeloid leukaemia. Oncogene 20: 5680-5694.
3. Antipas, V. P., Stamatakos, G. S., Uzunoglu, N. K., Dionysiou, D. D. and Dale, R. G. 2004a. A spatio-temporal simulation model of the response of solid tumours to radiotherapy in vivo: parametric validation concerning oxygen enhancement ratio and cell cycle duration. Phys. Med. Biol. 49: 1485-1504.
4. Antipas, V. P., Stamatakos, G. S., Uzunoglu, N. K. and Kouloulias, V. E. 2004b. Towards a spatiotemporal simulation of the in vivo response of normal tissues to radiotherapy. In Book of Short Communications, First International Advanced Research Workshop on In Silico Oncology: Advances and Challenges, Sparta, Greece, September 9-10, 2004 (eds N. Uzunoglu, G. Stamatakos, D. Givol). Institute of Communications and Computer Systems, National Technical University of Athens: Athens, Greece; 65-67.
5. Balding, D. and McElwain, D. L. S. 1985. A mathematical model of tumor-induced capillary growth. J. Theor. Biol. 114: 53-73.
6. Barbolosi, D. and Iliadis A. 2001. Optimizing drug regimens in cancer chemotherapy: a simulation study using a PK-PD model. Comput. Biol. Med. 31: 157-172.
7. Bode, A. and Dong, Z. 2004. Post-translational modification of p53 in tumorigenesis. Nature Rev. Cancer 4: 793-805.
8. Chen I. I. H. and Prewitt, R. L. 1982. A mathematical representation for vessel network. J. Theor. Biol. 97: 211-219.
9. Chuang, S. 1975. Mathematic models for cancer chemotherapy: pharmacokinetic and cell kinetic considerations. Cancer Chemother. Rep. 59: 827-842.
10. Cohen, L. 1983. Biophysical Models in Radiation Oncology. CRC Press: Boca Raton, FL.
11. Davis, J. and Tannock, I. F. 2000. Repopulation of tumour cells between cycles of chemotherapy: a neglected factor. Lancet Oncol. 1: 86-93.
12. Deisboeck, T. S., Berens, M. E., Kansal, A. R., Torquato, S., Stemmer-Rachamimov, A. O., and Chiocca, E. A. 2001. Pattern of self-organization in tumor systems: complex growth dynamics in a novel brain tumor spheroid model. Cell Prolif. 34: 115-134.
13. Dionysiou, D. 2004. Computer simulation of in vivo tumour growth and response to radiotherapeutic schemes. Biological optimization of radiation therapy by "in silico" experimentation. PhD thesis (in Greek). Dept. of Electrical and Computer Engineering: National Technical University of Athens.
14. Dionysiou, D. D. Stamatakos, G. S., Uzunoglu, N. K., Nikita, K. S. and Marioli, A. A. 2004. Four dimensional in vivo model of tumour response to radiotherapy: parametric validation considering radiosensitivity, genetic profile and fractionation. J. Theor. Biol. 230: 1-20.
15. Düchting, W. 1968. Krebs, ein instabiler Regelkreis, Versuch einer Systemanalyse. Kybernetik 5: 70-77.
16. Düchting, W. and Vogelsaenger, T. 1981. Three-dimensional pattern generation applied to spheroidal tumor growth in a nutrient medium. Int. J. Biomed. Comput. 12: 377-392.
17. Düchting, W., Ulmer, W., Ginsberg, T., Kikhounga-N Got, O. and Saile, C. 1995. Radiogenic responses of normal cells induced by fractionated irradiation-a simulation study. Strahlenther. Onkol. 171: 460-467.
18. Fowler, J. F. 1997. Review of radiobiological models for improving cancer treatment. In Modelling in Clinical Radiobiology (eds K. Baier and D. Baltas) Freiburg Oncology Series Monograph 2. Albert-Ludwigs-University: Freiburg, Germany, 1-14.
19. Gardner, S. N. 2002. Modeling multi-drug chemotherapy: tailoring treatment to individuals. J. Theor. Biol. 214: 181-207.
20. Gatenby, R. A. 1995. Models of tumor-host interaction as competing populations: implications for tumor biology and treatment. J. Theor. Biol. 176: 447-455.
21. Gödde, R., Düchting, W. and Kurz, H. 2000. Simulation of angiogenesis, vascular remodelling and haemodynamics in normal and neoplastic microcirculatory networks. Ann. Anat. Suppl. 182: 9-10.
22. Greenspan, H. P. 1976. On the growth and stability of cell cultures and solid tumors. J. Theor. Biol. 56: 229-242.
23. Haney, S., Thompson, P. M., Cloughesy, T. F., Alger, J. R. and Toga, A. W. 2001a. Tracking tumor growth rates in patients with malignant gliomas. A test of two algorithms. Am. J. Neuroradiol. 22: 73-82.
24. Haney, S., Thompson, P. M., Cloughesy, T. F., Alger, J. R., Frew, A., Torres-Trejo, A., Mazziotta, J. C. and Toga, A. W. 2001b. Mapping therapeutic response in a patient with malignant glioma. J. Comput. Assist. Tomogr. 25: 529-536.
25. Iliadis, A. and Barbolosi, D. 2000. Optimizing drug resistance in cancer chemotherapy by an efficacy-toxicity mathematical model. Comput. Biomed. Res. 33: 211-226.
26. Iwata, K., Kawasaki, K. and Shigesada, N. 2000. A dynamical model for the growth and size distribution of multiple metastatic tumors. J. Theor. Biol. 201: 177-186.
27. Jean, Y., De Traversay, J. and Lemieux, P. 1994. Teaching cancer chemotherapy by means of a computer simulation. Int. J. Biomed. Comput. 36: 273-280.
28. Jones, B. and Bleasdale, C. 1997. Influence of tumour regression and clonogen repopulation on tumour control by brachytherapy. In Modelling in Clinical Radiobiology (eds K. Baier and D. Baltas), Freiburg Oncology Series Monograph 2. Albert-Ludwigs-University: Freiburg, Germany, 116-126.
29. Kansal, A. R., Torquato, S., Harsh, G. R., Chiocca, E. A. and Deisboeck, T. S. 2000a. Cellular automaton of idealized brain tumor growth dynamics. BioSystems 55: 119-127.
30. Kansal, A. R., Torquato, S., Harsh, G. R., Chiocca, E. A. and Deisboeck, T.S. 2000b. Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. J. Theor. Biol. 203: 367-382.
31. Kocher, M. and Treuer, H. 1995. Reoxygenation of hypoxic cells by tumor shrinkage during irradiation. A computer simulation. Strahlenther. Onkol. 171: 219-230.
32. Kocher, M. Treuer, H., Voges, J., Hoevels, M., Sturm, V. and Mueller, R. P. 2000. Computer simulation of cytotoxic and vascular effects of radiosurgery in solid and necrotic brain metastases. Radiother. Oncol. 54: 149-156.
33. Levin, V. A., Patlak, C. S. and Landahl, H. D. 1980. Heuristic modeling of drug delivery to malignant brain tumors. J. Pharmacokinet. Biopharm. 8: 257-296.
34. Mansury, Y. and Deisboeck, T. S. 2003. The impact of 'search precision' in an agent-based tumor model. J. Theor. Biol. 224: 325-337.
35. Mansury, Y. and Deisboeck, T. S. 2004. Simulating 'structure-function' patterns of malignant brain tumors. Phys. A 331: 219-232.
36. Mansury, Y., Kimura, M., Lobo, J. and Deisboeck, T.S. 2002. Emerging patterns in tumor systems: simulating the dynamics of multicellular clusters with an agent-based spatial agglomeration model. J. Theor. Biol. 219: 343-370.
37. Mansury, Y., Athale, C., Gregor, B. F. and Deisboeck, T. S. 2004. Modeling malignant brain tumors with a novel spatio-temporal agent-based simulation framework. In Book of Short Communications, First International Advanced Research Workshop on In Silico Oncology: Advances and Challenges, Sparta, Greece, September 9-10, 2004 (eds N. Uzunoglu, G. Stamatakos, D. Givol). Institute of Communications and Computer Systems, National Technical University of Athens: Athens, Greece; 45-47.
38. Maxim, P. G., Carson, J. J. L., Ning, S., Knox, S. J., Boyer, A. L., P. Hsu, C. P., Benaron, D. A. and Walleczek, J. 2004. Enhanced effectiveness of radiochemotherapy with tirapazamine by local application of electric pulses to tumors. Radiat. Res. 162: 185-193.
39. Michelson, S. and Leith, J. T. 1997. Possible feedback and angiogenesis in tumor growth control. Bull. Math. Biol. 59: 233-254.
40. Nagl, S. 2004. Modelling of cancer gene-signal systems. In Book of Short Communications, First International Advanced Research Workshop on In Silico Oncology: Advances and Challenges, Sparta, Greece, September 9-10, 2004 (eds N. Uzunoglu, G. Stamatakos, D. Givol). Institute of Communications and Computer Systems, National Technical University of Athens: Athens, Greece; 23-24.
41. Nagl, S. B. and Patel, M. 2004. MicroCore: mapping genome expression to cell pathways and networks. Comp. Funct. Genom. 5: 75-78.
42. Nagl, S., Parish, J. H., Paton, R. and Warner, G. 2005. Macromolecules, genomes and ourselves. In Computation in Cells and Tissues-Perspectives and Tools of thought (eds R. Paton, H. Bolouri, M. Holcombe, H. Parish and R. Tateson). Springer-Verlag: Heidelberg; in press.
43. Nahum, A. and Sanchez-Nieto, B. 2001. Tumour control probability modelling: basic principles and applications in treatment planning. Phys. Med. 17 (Suppl. 2): 13-23.
44. Nani, F. K. and Oguztereli, M. N. 1999. Modelling and simulation of chemotherapy of haematological and gynaecological cancers. IMA J. Math. Appl. Med. Biol. 16: 39-91.
45. Ozawa, S., Sugiyama, Y., Mitsuhashi, J. and Inaba, M. 1989. Kinetic analysis of cell killing effect induced by cytosine arabinoside and cisplatin in relation to cell cycle phase specificity in human colon cancer and chinese hamster cells. Cancer Res. 49: 3823-3828.
46. Panetta, J. C. 1996. A mathematical model of periodically pulsed chemotherapy: tumor recurrence and metastasis in a competitive environment. Bull. Mater. Biol. 58: 425-447.
47. Pirogova, E., Fang, Q., Akay, M. and Cosic, I. 2002. Investigation of the structural and functional relationships of oncogene proteins. Proc. IEEE 90: 1859-1867.
48. Retsky, M. W., Demicheli, R., Swartzendruber, D. E., Bame, P. D., Wardwell, R.H., Bonadonna, G., Speer, J. F. and Valagussa, P. 1997. Computer simulation of a breast cancer metastasis model. Breast Cancer Res. Treat. 45: 193-202.
49. Simpson, M., Cox, C., Peterson, G. and Slayer, G. 2004. Engineering in the biological substrate: information processing in genetic circuits. Proc. IEEE 92: 848-863.
50. Stamatakos, G. S. 2004. The ISOG/ICCS/NTUA in silico model of in vivo tumour and normal tissue response to radiation therapy and chemotherapy: the modules of the model. In Book of Short Communications, First International Advanced Research Workshop on In Silico Oncology: Advances and Challenges, Sparta, Greece, September 9-10, 2004 (eds N. Uzunoglu, G. Stamatakos, D. Givol). Institute of Communications and Computer Systems, National Technical University of Athens: Athens, Greece; 51-53.
51. Stamatakos, G. S., Antipas, V. P. and Uzunoglu, N. K. 2004. A spatiotemporal, patient individualized simulation model of solid tumor response to chemotherapy in vivo: the paradigm of glioblastoma multiforme treated by temozolomide. In Book of Short Communications, First International Advanced Research Workshop on In Silico Oncology: Advances and Challenges, Sparta, Greece, September 9-10, 2004 (eds N. Uzunoglu, G. Stamatakos, D. Givol). Institute of Communications and Computer Systems, National Technical University of Athens: Athens, Greece; 62-64.
52. Stamatakos, G., Uzunoglu, N., Delibasis, K., Makropoulou M., Mouravliansky, N. and Marsh, A. 1998a. A simplified simulation model and virtual reality visualization of tumor growth in vitro. Future Gen. Comput. Syst. 14: 79-89.
53. Stamatakos, G. S., Uzunoglu, N. K., Delibasis, K., Makropoulou, M., Mouravliansky, N. and Marsh, A. 1998b. Coupling parallel computing and the WWW to visualize a simplified simulation of tumor growth in vitro. In Proc. International Conference on Parallel and distributed Processing Techniques and Applications, PDTA'98, Las Vegas, USA (ed. H. R. Arabnia). CSREA Press: Las Vegas, NV; 526-533.
54. Stamatakos, G., Zacharaki, E., Mouravliansky, N., Delibasis, K., Nikita, K., Uzunoglu, N. and Marsh, A. 1999. Using Web technologies and meta-computing to visualize a simplified simulation model of tumor growth in vitro. In High-Performance Computing and Networking (eds P. Sloot, M. Bubak, A. Hoekstra, B. Hertzberger), Lecture Notes in Computer Science 1593. Springer: Berlin; 973-982.
55. Stamatakos, G., Dionysiou, D., Nikita, K., Zamboglou, N., Baltas, D., Pissakas, G. and Uzunoglu, N. 2001a. In vivo tumor growth and response to radiation therapy: a novel algorithmic description. Int. J. Radiat. Oncol. Biol. Phys. 51 (Suppl. 1): 240.
56. Stamatakos, G., Zacharaki, E., Makropoulou, M., Mouravliansky, N. Marsh, A., Nikita, K. and Uzunoglu, N. 2001b. Modeling tumor growth and irradiation response in vitro-a combination of high-performance computing and web-based technologies including VRML visualization. IEEE Trans. Inform. Technol. Biomed. 5: 279-289.
57. Stamatakos, G., Dionysiou, D., Zacharaki, E., Mouravliansky, N., Nikita, K. and Uzunoglu, N. 2002. In silico radiation oncology: combining novel simulation algorithms with current visualization techniques. Proc. IEEE (Special Issue on Bioinformatics: Advances and Challenges) 90: 1764-1777.
58. Terz, J. J., Lawrence Jr, W. and Cox, B. 1977. Analysis of the cycling and noncycling cell population of human solid tumors. Cancer 40: 1462-1470.
59. Uzunoglu, N. K. 2004. The ISOG/ICCS/NTUA in silico model of in vivo tumour and normal tissue response to radiation therapy and chemotherapy: the principles. In Book of Short Communications, First International Advanced Research Workshop on In Silico Oncology: Advances and Challenges, Sparta, Greece, September 9-10, 2004, (eds N. Uzunoglu, G. Stamatakos, D. Givol). Institute of Communications and Computer Systems, National Technical University of Athens: Athens, Greece; 48-50.
60. von Eschenbach, A. C. 2004. A vision for the National Cancer Program in the United States. Nature Rev. Cancer 4: 820-828.
61. Ward, J. P. and King, J. R. 2003. Mathematical modeling of drug transport in tumour multicell spheroids and monolayer cultures. Mater. Biosci. 181: 177-207.
62. Williams, T. and Bjerknes, R. 1972. Stochastic model for abnormal clone spread through epithelial basal layer. Nature 236: 19-21.
63. Wojtowicz, A., Selman, S. and Jankun, J. 2003. Computer simulation of prostate cryoablation-fast and accurate approximation of the exact solution. Comput. Aided Surg. 8: 91-97.
64. Zacharaki, E. 2004. Development of imaging data registration algorithms and computer simulation models of malignant tumour behaviour aiming at supporting clinical decisions in radio-oncology. PhD thesis (in Greek). Dept. of Electrical and Computer Engineering: National Technical University of Athens.
65. Zacharaki, E. I., Stamatakos, G. S., Nikita, K. S. and Uzunoglu, N. K. 2004. Simulating growth dynamics and radiation response of avascular tumour spheroids-model validation in the case of an EMT6/Ro multicellular spheroid. Comput. Meth. Prog. Biomed. 76: 193-206.