Abstract
Based on an innovative endogenous network hypothesis on cancer genesis and progression we have been working towards a quantitative cancer theory along the systems biology perspective. Here we give a brief report on our progress and illustrate that combing ideas from evolutionary and molecular biology, mathematics, engineering, and physics, such quantitative approach is feasible.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Abedelrazeq, A.S. 2007. Spontaneous regression of colorectal cancer: A review of cases from 1900 to 2005. Int J Colorectal Disease 22, 727–736.
Ao, P. 2004. Potential in stochastic differential equations: novel construction. J Phys 37, L25–L30.
Ao, P. 2009. Global view of bionetwork dynamics: Adaptive landscape. J Genetics and Genomics 36, 1–11.
Ao, P., Kwon, C., Qian, H. 2007. On the existence of potential landscape in the evolution of complex systems. Complexity 12, 19–27.
Ao, P., Galas, D., Hood, L., Zhu, X.-M. 2008. Cancer as Robust Intrinsic State of Endogenous Molecular-Cellular Network Shaped by Evolution. Medical Hypotheses 70, 678–684.
Auffray, C., Chen, Z., Hood, L. 2009. Systems medicine: The future of medical genomics and healthcare. Genome Medicine 1, article No. 2.
Bar-Yam, Y., Harmon, D., de Bivort, B. 2009. Systems biology: Attractors and democratic dynamics. Science 323, 1016–1017.
Cao, Y.F., Liang, J. 2008. Optimal enumeration of state space of finitely buffered stochastic molecular networks and exact computation of steady state landscape probability. BMC Syst Biol 2, article No. 30.
Dinulos, J.G., Hawkins, D.S., Clark, B.S., Francis, J.S. 1997. Spontaneous remission of congenital leukemia. J Pediatrics 131, 300–303.
Greaves, M. 2001. Cancer: The Evolutionary Legacy. Oxford University Press, Oxford.
Heng, H.H.Q., Bremer, S.W., Stevens, J.B., Ye, K.J., Liu, G., Ye, C.J. 2009. Genetic and epigenetic heterogeneity in cancer: A genome-centric perspective. J Cellular Physiology 220, 538–547.
Karmakar, R., Bose, I. 2007. Positive feedback, stochasticity and genetic competence. Physical Biology 4, 29–37.
Kosko, B. 1997. Fuzzy Engineering. Prentice-Hall, Upper Saddle River.
Kwon, C., Ao, P., Thouless, D.J. 2005. Structure of stochastic dynamics near fixed points. Proc Natl Acad Sci (USA) 102, 13029–13033.
Miao, Y., Liu, Z.Q., Siew, C.K., Miao, C.Y. 2001. Dynamical cognitive network — an extension of fuzzy cognitive map. IEEE T Fuzzy Systems 9, 760–770.
Morelli, M.J., Tanase-Nicola, S., Allen, R.J., ten Wolde, P.R. 2008. Reaction coordinates for the flipping of genetic switches. Biophys J 94, 3413–3423.
Onuchic, J.N., Wang, J., Wolynes, P.G. 1999. Analyzing single molecule trajectories on complex energy landscapes using replica correlation functions. Chem Phys 247, 175–184.
Qian, H., Shi, P.Z., Xing, J.H. 2009. Stochastic bifurcation, slow fluctuations, and bistability as an origin of biochemical complexity. Phys Chem Chem Phys 11, 4861–4870.
Reynolds, C.P. 2002. Ras and Seppuku in neuroibalstorma. J Natl Cancer Inst 94, 319–321.
Wang, J., Huang, B., Xia, X.F., Sun, Z.R. 2006. Funneled landscape leads to robustness of cell networks: Yeast cell cycle. PLoS Comput Biol 2, 1385–1394.
Weinberg, R.A. 2007. The Biology of Cancer. Taylor and Francis, New York.
Weinreb, G.E., Elston, T.C., Jacobson, K. 2006. Causal mapping as a tool to mechanistically interpret phenomena in cell motility: Application to cortical oscillations in spreading cells. Cell Mot Cytosk 63, 523–532.
Yin, L., Ao, P. 2006. Existence and construction of dynamical potential in nonequilibrium processes without detailed balance. J Phy A39, 8593–8601.
Zhang, Y.P., Qian, M.P., Ouyang, Q., Deng, M.H., Li, F.T., Tang, C. 2006. Stochastic model of yeast cellcycle network. Physica D219, 35–39.
Zhu, X.M., Yin, L., Hood, L., Ao, P. 2004. Calculating robustness of epigenetic states in phage lambda life cycle. Funct Integr Genom 4, 188–195.
Zhu, X.M., Hood, L., Galas, D., Ao, P. 2010. Construction of a molecular-cellular endogenous network prostate cancer model. To be published.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ao, P., Galas, D., Hood, L. et al. Towards predictive stochastic dynamical modeling of cancer genesis and progression. Interdiscip Sci Comput Life Sci 2, 140–144 (2010). https://doi.org/10.1007/s12539-010-0072-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12539-010-0072-3