/* * Evolutionary dynamics of mutator phenotypes in cancer: implications * for chemotherapy * * Model Status * * This is the CellML description of the simple version of the * model detailed in the paper. The model runs in both OpenCell * and COR and the units are consistent, however it does not reproduce * the correct published results as some of the parameter values * are unknown. * * Model Structure * * ABSTRACT: Genetic instability is a central characteristic of * cancers. However, the selective forces responsible for the emergence * of genetic instability are not clear. We use mathematical models * to determine the conditions under which selection favors instability, * and when stable cells are advantageous. We take into account * the processes of DNA damage, repair, cell cycle arrest, mutation, * and death. We find that the rate of DNA damage can play a major * role in this context. In particular, an increase in the rate * of DNA damage can reverse the relative fitness of stable and * unstable cells. In terms of cancer progression, we find the * following results. If cells have intact apoptotic responses, * stable cells prevail if the DNA hit rate is low. A high DNA * hit rate can result in the selection of genetically unstable * cells. This has implications for the induction of tumors by * carcinogens. On the other hand, if cells are characterized by * impaired apoptosis, we observe the opposite. Genetic instability * is selected for if the DNA hit rate is low. A high DNA hit rate * can select against instability and result in the persistence * of stable cells. We propose that chemotherapy can be used to * reverse the relative fitness of stable and unstable cells, such * that unstable cells are the inferior competitors. This could * result in the competitive exclusion of progressing cancer cells. * * The original paper reference is cited below: * * Evolutionary dynamics of mutator phenotypes in cancer: implications * for chemotherapy, Natalia L. Komarova and Dominik Wodarz, 2003,Cancer * Research, 63, 6635-6642. PubMed ID: 14583456 * * cell diagram * * [[Image file: komarova_2003.png]] * * Schematic diagram of the model, showing the processes of cell * reproduction, DNA damage, repair, cell cycle arrest, mutation * and death. */ import nsrunit; unit conversion on; unit hour=3600 second^1; unit first_order_rate_constant=2.7777778E-4 second^(-1); unit per_time2=7.7160494E-8 second^(-2); unit per_time3=2.1433471E-11 second^(-3); math main { realDomain time hour; time.min=0; extern time.max; extern time.delta; real S(time) dimensionless; when(time=time.min) S=0.5; real rs first_order_rate_constant; rs=1; real epsilon_s first_order_rate_constant; epsilon_s=0.99; real alpha first_order_rate_constant; alpha=0.1; real u first_order_rate_constant; u=0.07; real beta first_order_rate_constant; beta=0.2; real phi(time) dimensionless; real M(time) dimensionless; when(time=time.min) M=0.5; real rm first_order_rate_constant; rm=1.3; real epsilon_m first_order_rate_constant; epsilon_m=0.1; real growth_rate first_order_rate_constant; real a first_order_rate_constant; a=0.5; // // S:time=(rs*S*(1-u*(1 hour)+beta*epsilon_s*u/(1 per_time3))+alpha*u*rs*S/(1 per_time3)*((1 first_order_rate_constant)-epsilon_s)-phi*S*(1 first_order_rate_constant)); // M:time=(rm*M*(1-u/(1 first_order_rate_constant)+beta*epsilon_m*u/(1 per_time3))+alpha*u*rm*M/(1 per_time3)*((1 first_order_rate_constant)-epsilon_m)-phi*M*(1 first_order_rate_constant)); // phi=(S*rs/(1 first_order_rate_constant)*(1-u/(1 first_order_rate_constant)*(1-beta*epsilon_s/(1 per_time2)-alpha/(1 first_order_rate_constant)*(1-epsilon_s/(1 first_order_rate_constant))))+M*rm/(1 first_order_rate_constant)*(1-u/(1 first_order_rate_constant)*(1-beta*epsilon_m/(1 per_time2)-alpha/(1 first_order_rate_constant)*(1-epsilon_m/(1 first_order_rate_constant))))); growth_rate=((rs+rm)*(1-a/(1 first_order_rate_constant))); // }