The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - January/February (2012 vol.9)
pp: 169-184
A. W. Mahoney , Comput. Sci. Dept., Utah State Univ., Logan, UT, USA
G. J. Podgorski , Biol. Dept. & Center for Integrated Biosyst., Utah State Univ., Logan, UT, USA
N. S. Flann , Comput. Sci. Dept., Utah State Univ., Logan, UT, USA
ABSTRACT
Solid tumors must recruit new blood vessels for growth and maintenance. Discovering drugs that block tumor-induced development of new blood vessels (angiogenesis) is an important approach in cancer treatment. The complexity of angiogenesis presents both challenges and opportunities for cancer therapies. Intuitive approaches, such as blocking VegF activity, have yielded important therapies. But there maybe opportunities to alter nonintuitive targets either alone or in combination. This paper describes the development of a high-fidelity simulation of angiogenesis and uses this as the basis for a parallel search-based approach for the discovery of novel potential cancer treatments that inhibit blood vessel growth. Discovering new therapies is viewed as a multiobjective combinatorial optimization over two competing objectives: minimizing the estimated cost of practically developing the intervention while minimizing the simulated oxygen provided to the tumor by angiogenesis. Results show the effectiveness of the search process by finding interventions that are currently in use, and more interestingly, discovering potential new approaches that are nonintuitive yet effective.
INDEX TERMS
Cancer, Medical treatment, Neoplasms, Blood vessels, Computational modeling, Biology computing, Drugs, High performance computing, Recruitment, Pipelines,VegF., Cancer therapy, cellular Potts model, CPM, Glazier-Graner-Hogeweg model, GGH, multiobjective optimization, parallel search, computational discovery, angiogenesis
CITATION
A. W. Mahoney, G. J. Podgorski, N. S. Flann, "Multiobjective Optimization Based-Approach for Discovering Novel Cancer Therapies", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.9, no. 1, pp. 169-184, January/February 2012, doi:10.1109/TCBB.2010.39
REFERENCES
[1] M.A. Abo-Sinnaa and M.L. Husseinb, “An Algorithm for Generating Efficient Solutions of Multiobjective Dynamic Programming Problems,” European J. Operational Research, vol. 80, no. 1, pp. 156-165, Jan. 1995.
[2] T. Alarcón, “A Cellular Automaton Model for Tumour Growth in Inhomogeneous Environment,” J. Theoretical Biology, vol. 225, no. 2, pp. 257-274, Nov. 2003.
[3] F. Amyot, A. Small, and A.H. Gandjbakhche, “Stochastic Modeling of Tumor Induced Angiogenesis in a Heterogeneous Medium, the Extracellular Matrix,” Proc. 28th Ann. IEEE Int'l Conf. Eng. in Medicine and Biology Soc. (EMBS '06) pp. 3146-3149, 2006.
[4] L. Arakelyan, V. Vainstein, and Z. Agur, “A Computer Algorithm Describing the Process of Vessel Formation and Maturation, and Its Use for Predicting the Effects of Anti-Angiogenic and Anti-Maturation Therapy on Vascular Tumor Growth,” Angiogenesis, vol. 5, no. 3, pp. 203-214, 2002.
[5] R. Auerbacha, R. Lewis, B. Shinners, L. Kubai, and N. Akhtar, “Angiogenesis Assays: A Critical Overview,” Clinical Chemistry, vol. 49, no. 1, pp. 32-40, 2003.
[6] S. Bandyopadhyay, S. Saha, U. Maulik, and K. Deb, “A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA,” IEEE Trans. Evolutionary Computation, vol. 12, no. 3, pp. 269-283, June 2008.
[7] A.L. Bauer, T.L. Jackson, and Y. Jiang, “A Cell-Based Model Exhibiting Branching and Anastomosis during Tumor-Induced Angiogenesis,” Biophysical J., vol. 92, no. 9, pp. 3105-3121, May 2007.
[8] A.L. Bauer, T.L. Jackson, and Y. Jiang, “Topography of Extracellular Matrix Mediates Vascular Morphogenesis and Migration Speeds in Angiogenesis,” PLoS Computational Biology, vol. 5, no. 7: e1000445, 2009, doi:10.1371/journal.pcbi.1000445.
[9] P. Boyle and B. Levin, eds., World Cancer Report 2008, IARC Nonserial, ISBN-13 9789283204237, ISBN-10 9283204239, 2008.
[10] H.M. Byrne, T. Alarcon, M.R. Owen, S.D. Webb, and P.K. Maini, “Modelling Aspects of Cancer Dynamics: A Review,” Philosophical Transactions, Series A, Math., Physical, and Eng. Sciences, vol. 364, no. 1843, pp. 1563-1578, June 2006.
[11] H.M. Byrne, M.R. Owen, T.A. Alarcon, J. Murphy, and P.K. Maini, “Modelling the Response of Vascular Tumours to Chemotherapy: A Multiscale Approach,” Math. Models and Methods in Applied Sciences, vol. 16, no. 7S, pp. 1219-1241, 2006.
[12] P. Carmeliet and R.K. Jain, “Angiogenesis in Cancer and Other Diseases,” Nature, vol. 407, no. 6801, pp. 249-257, Sept. 2000.
[13] Carraway, “Generalized Dynamic Programming for Multicriteria Optimization,” European J. Operational Research, vol. 44, no. 1, pp. 95-104, 1990.
[14] M.A.J.A. Chaplain, S.R.R. McDougall, and A.R.A.R. Anderson, “Mathematical Modeling of Tumor-Induced Angiogenesis,” Ann. Rev. Biomedical Eng., vol. 8, pp. 233-257, Apr. 2006.
[15] A. Chattopadhyay and C. Seeley, “A Simulated Annealing Technique for Multiobjective Optimization of Intelligent Structures,” Smart Materials and Structures, vol. 3, pp. 98-106, 1994.
[16] K. Deb, Multi-objective Optimization Using Evolutionary Algorithms. John Wiley and Sons, 2001.
[17] N. Ferrara, K. Hillan, and W. Novotny, “Bevacizumab (Avastin), A Humanized Anti-VEGF Monoclonal Antibody for Cancer Therapy,” Biochemical and Biophysical Research Comm., vol. 333, no. 2, pp. 328-335, July. 2005.
[18] N. Ferrara and R.S. Kerbel, “Angiogenesis as a Therapeutic Target,” Nature, vol. 438, no. 7070, pp. 967-974, Dec. 2005.
[19] R.S. Finley, “New Directions in the Treatment of Cancer: Inhibition of Signal Transduction,” J. Pharmacy Practice, vol. 15, no. 1, pp. 5-16, Feb. 2002.
[20] C. Fonseca and P. Fleming, “An Overview of Evolutionary Algorithms in Multiobjective Optimization,” Evolutionary Computation, vol. 3, no. 1, pp. 1-16, 1995.
[21] F.M. Gabhann and A.S. Popel, “Targeting Neuropilin-1 to Inhibit VEGF Signaling in Cancer: Comparison of Therapeutic Approaches,” PLoS Computational Biology, vol. 2, no. 12: e180, Dec. 2006, doi:10.1371/journal.pcbi.0020180.
[22] H. Gerhardt, M. Golding, M. Fruttiger, C. Ruhrberg, A. Lundkvist, A. Abramsson, M. Jeltsch, C. Mitchell, K. Alitalo, D. Shima, and C. Betsholtz, “VEGF Guides Angiogenic Sprouting Utilizing Endothelial Tip Cell Filopodia,” The J. Cell Biology, vol. 161, no. 6, pp. 1163-1177, June 2003.
[23] J.L. Gevertz and S. Torquato, “Modeling the Effects of Vasculature Evolution on Early Brain Tumor Growth,” J. Theoretical Biology, vol. 243, no. 4, pp. 517-531, 2006.
[24] J.A. Glazier and F. Graner, “Simulation of the Differential Adhesion Driven Rearrangement of Biological Cells,” Physical Rev. E, vol. 47, no. 3, pp. 2128-2154, 1993.
[25] S.L. Gupton and F.B. Gertler, “Filopodia: The Fingers that Do the Walking,” Science Signaling, vol. 2007, no. 400,re5, Aug. 2007, doi: 10.1126/stke.4002007re5.
[26] J. Handl, D. Kell, and J. Knowles, “Multiobjective Optimization in Bioinformatics and Computational Biology,” IEEE/ACM Trans. Computational Biology and Bioinformatics, vol. 4, no. 2, pp. 279-292, Apr. 2007.
[27] A.J. Hayes, L.Y. Li, and M.E. Lippman, “Science, Medicine, and the Future: Antivascular Therapy: A New Approach to Cancer Treatment,” British Medical J., vol. 318, no. 7187, pp. 853-856, Mar. 1999.
[28] M. Hellstrom, L.-K. Phng, J.J. Hofmann, E. Wallgard, L. Coultas, P. Lindblom, J. Alva, A.-K. Nilsson, L. Karlsson, N. Gaiano, K. Yoon, J. Rossant, L.M. Iruela-Arispe, M. Kalén, H. Gerhardt, and C. Betsholtz, “Dll4 Signalling through Notch1 Regulates Formation of Tip Cells during Angiogenesis,” Nature, vol. 445, pp. 776-780, Jan. 2007.
[29] P. Hogeweg, “Evolving Mechanisms of Morphogenesis: On the Interplay between Differential Adhesion and Cell Differentiation,” J. Theoretical Biology, vol. 203, no. 4, pp. 317-333, Apr. 2000.
[30] M.T. Holderfield and C.C.W. Hughes, “Crosstalk between Vascular Endothelial Growth Factor, Notch, and Transforming Growth Factor-Beta in Vascular Morphogenesis,” Circulation Research, vol. 102, pp. 637-652, Mar. 2008.
[31] J.A. Izaguirre, R. Chaturvedi, C. Huang, T. Cickovski, J. Coffland, G. Thomas, G. Forgacs, M. Alber, G. Hentschel, S.A. Newman, and J.A. Glazier, “Compucell, A Multi-Model Framework for Simulation of Morphogenesis,” Bioinformatics, vol. 20, no. 7, pp. 1129-1137, May 2004.
[32] T. Jackson, “A Mathematical Model to Study the Effects of Drug Resistance and Vasculature on the Response of Solid Tumors to Chemotherapy,” Math. Biosciences, vol. 164, no. 1, pp. 17-38, Mar. 2000.
[33] R.K. Jain, R.T. Tong, and L.L. Munn, “Effect of Vascular Normalization by Antiangiogenic Therapy on Interstitial Hypertension, Peritumor Edema, and Lymphatic Metastasis: Insights from a Mathematical Model,” Cancer Research, vol. 67, no. 6, pp. 2729-2735, Mar. 2007.
[34] A. Jemal, R. Siegel, E. Ward, Y. Hao, J. Xu, T. Murray, and M.J. Thun, “Cancer Statistics, 2008,” CA: A Cancer J. for Clinicians, vol. 58, no. 2, pp. 71-96, Mar. 2008.
[35] J.W. Ji, N.M. Tsoukias, D. Goldman, and A.S. Popel, “A Computational Model of Oxygen Transport in Skeletal Muscle for Sprouting and Splitting Modes of Angiogenesis,” J. Theoretical Biology, vol. 241, no. 1, pp. 94-108, July 2006.
[36] J. Kafer, P. Hogeweg, and A.F. Marée, “Moving Forward Moving Backward: Directional Sorting of Chemotactic Cells due to Size and Adhesion Differences,” PLoS Computational Biology, vol. 2, no. 6: e56, June 2006, doi:10.1371/journal.pcbi.0020056.
[37] Y. Lan and G.A. Papoian, “The Stochastic Dynamics of Filopodial Growth,” Biophysical J., vol. 94, no. 10, pp. 3839-3852, May 2008.
[38] W.B. Langdon and R. Poli, “Fitness Causes Bloat,” Soft Computing in Engineering Design and Manufacturing, pp. 23-27, Springer-Verlag, 1997.
[39] T.-C. Lee, R.L. Kashyap, and C.-N. Chu, “Building Skeleton Models via 3D Medial Surface/Axis Thinning Algorithms,” CVGIP: Grapical Models and Image Processing, vol. 56, no. 6, pp. 462-478, Nov. 1994.
[40] H. Levine, S. Pamuk, B. Sleeman, and M. Nilsen-Hamilton, “Mathematical Modeling of Capillary Formation and Development in Tumor Angiogenesis: Penetration into the Stroma,” Bull. of Math. Biology, vol. 63, no. 5, pp. 801-863, 2001.
[41] M. James Ji and A. Popel, “Multi-Scale Computational Models of Pro-Angiogenic Treatments in Peripheral Arterial Disease,” Annals of Biomedical Eng., vol. 35, no. 6, pp. 982-994, June 2007.
[42] J.D.B. Macdougall and M. Mccabe, “Diffusion Coefficient of Oxygen through Tissues,” Nature, vol. 215, no. 5106, pp. 1173-1174, 1967.
[43] T. Maciag, G.A. Hoover, M.B. Stemerman, and R. Weinstein, “Serial Propagation of Human Endothelial Cells In Vitro,” The J. Cell Biology, vol. 91, no. 2, pp. 420-426, Nov. 1981.
[44] J.L. Mauriz and J. González-Gallego, “Antiangiogenic Drugs: Current Knowledge and New Approaches to Cancer Therapy,” J. Pharmaceutical Sciences, vol. 97, no. 10, pp. 4129-4154, 2008.
[45] S.R. McDougall, A.R. Anderson, and M.A. Chaplain, “Mathematical Modelling of Dynamic Adaptive Tumour-Induced Angiogenesis: Clinical Implications and Therapeutic Targeting Strategies,” J. Theoretical Biology, vol. 241, no. 3, pp. 564-589, Aug. 2006.
[46] S.R. McDougall, A.R. Anderson, M.A. Chaplain, and J.A. Sherratt, “Mathematical Modelling of Flow through Vascular Networks: Implications for Tumour-Induced Angiogenesis and Chemotherapy Strategies,” Bull. of Math Biology, vol. 64, no. 4, pp. 673-702, July 2002.
[47] R.M. Merks, S.V. Brodsky, M.S. Goligorksy, S.A. Newman, and J.A. Glazier, “Cell Elongation is Key to in silico Replication of In Vitro Vasculogenesis and Subsequent Remodeling,” Developmental Biology, vol. 289, no. 1, pp. 44-54, Jan. 2006.
[48] R.M. Merks and J.A. Glazier, “A Cell-Centered Approach to Developmental Biology,” Physica A, vol. 352, pp. 113-130, 2005.
[49] R.M. Merks, E.D. Perryn, A. Shirinifard, and J.A. Glazier, “Contact-Inhibited Chemotaxis in De Novo and Sprouting Blood-Vessel Growth,” PLoS Computational Biology, vol. 4, no. 9: e1000163, 2008, doi:10.1371/journal.pcbi.1000163.
[50] R.M.H. Merks, S.A. Newman, and J.A. Glazier, “Cell-Oriented Modeling of In Vitro Capillary Development,” Cellular Automata, pp. 425-434, Springer, 2004.
[51] T. Morisada, Y. Kubota, T. Urano, T. Suda, and Y. Oike, “Angiopoietins and Angiopoietin-Like Proteins in Angiogenesis,” Endothelium, vol. 13, no. 2, pp. 71-79, Apr. 2006.
[52] S.M. Peirce, “Computational and Mathematical Modeling of Angiogenesis,” Microcirculation, vol. 15, no. 8, pp. 739-751, 2008.
[53] C. Ruegg and N. Mutter, “Anti-Angiogenic Therapies in Cancer : Achievements and Open Questions,” Bull. of Cancer, vol. 94, pp. 753-762, Sept. 2007.
[54] Shiba, Yuji, Takahashi, Masafumi, Ikeda, and Uichi, “Models for the Study of Angiogenesis,” Current Pharmaceutical Design, vol. 14, no. 4, pp. 371-377, Feb. 2008.
[55] S. Shinkaruk, M. Bayle, G. Laïn, and G. Déléris, “Vascular Endothelial Cell Growth Factor (VEGF), an Emerging Target for Cancer Chemotherapy,” Current Medicinal Chemistry—Anti-Cancer Agents, vol. 3, no. 2, pp. 95-117, Mar. 2003.
[56] F. Shojaei and N. Ferrara, “Antiangiogenic Therapy for Cancer: An Update,” The Cancer J., vol. 13, no. 6, pp. 345-348, Nov. 2007.
[57] W.G. Stetler-Stevenson, “Matrix Metalloproteinases in Angiogenesis: A Moving Target for Therapeutic Intervention,” The J. Clinical Investigation, vol. 103, no. 9, pp. 1237-1241, May 1999.
[58] S.F. Stewman and A.R. Dinner, “Lattice Model for Self-Assembly with Application to the Formation of Cytoskeletal-Like Structures,” Physical Rev. E (Statistical, Nonlinear, and Soft Matter Physics), vol. 76, no. 1, p. 016103, July 2007, doi:10.1103/PhysRevE.76.016103.
[59] B. Suman and P. Kumar, “A Survey of Simulated Annealing as a Tool for Single and Multiobjective Optimization,” J. Operational Research Soc., vol. 57, no. 18, pp. 1143-1160, 2006.
[60] A. Suppapitnarm, K. Seffen, G. Parks, and P. Clarkson, “A Simulated Annealing Algorithm for Multiobjective Optimization,” Eng. Optimization, vol. 33, no. 1, pp. 59-85, 2000.
[61] S. Turner and J.A. Sherratt, “Intercellular Adhesion and Cancer Invasion: A Discrete Simulation Using the Extended Potts Model,” J. Theoretical Biology, vol. 216, no. 1, pp. 85-100, May 2002.
[62] I. Walker and H. Newell, “Do Molecularly Targeted Agents in Oncology Have Reduced Attrition Rates?” Nature Rev. Drug Discovery, vol. 8, no. 1, pp. 15-16, Nov. 2008.
[63] L. Wolpert, J. Smith, T. Jessell, and P. Lawrence, Principles of Development, third ed., Oxford Univ. Press, 2007.
[64] E. Zitzler, K. Deb, and L. Thiele, “Comparison of Multiobjective Evolutionary Algorithms: Empirical Results,” Evolutionary Computation, vol. 8, no. 2, pp. 173-195, 2000.
[65] E. Zitzler and L. Thiele, “Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach,” IEEE Trans. Evolutionary Computation, vol. 3, no. 4, pp. 257-271, Nov. 1999.
45 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool