PubMed · 12428379
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Youichi Nakayama. 2002. [Developing computer models of cellular processes].. https://pubmed.ncbi.nlm.nih.gov/12428379/
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In this paper, we derive analytic solutions of stochastic mutation-selection networks that describe early events of cancer formation. A main assumption is that cancer is initiated in tissue compartments, where only a relatively small number of cells are at risk of mutating into cells that escape from homeostatic regulation. In this case, the evolutionary dynamics can be approximated by a low-dimensional stochastic process with a linear Kolmogorov forward equation that can be solved analytically. Most of the time, the cell population is homogeneous with respect to relevant mutations. Occasionally, such homogeneous states are connected by 'stochastic tunnels'. We give a precise analysis of the existence of tunnels and calculate the rate of tunneling. Finally, we calculate the conditions for chromosomal instability (CIN) to precede inactivation of the first tumor suppressor gene. In this case, CIN is an early event and a driving force of cancer progression. The techniques developed in this paper can be used to study arbitrarily complex mutation-selection networks of the somatic evolution of cancer.
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Cells are organized through the interactions of proteins with one another, and with phospholipids, nucleic acids and small molecules, suggesting a molecular recognition code for cell assembly. These interactions are mediated by a set of conserved protein interaction domains, which regulate the dynamic behaviour of the cell, and are used to build protein complexes and networks with emergent properties. Cell regulatory proteins have a modular architecture, which may have facilitated the evolution of new signalling pathways, and is exploited by pathogenic micro-organisms and chimeric oncoproteins to re-specify cellular function.