Identifying restrictions in the order of accumulation of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

Table 2 Main parameters for each of the tumor progression models

Model	Birth rate	Death rate	Mutation	Cancer
			rate (per	reached if
			gene per
			unit time)
Bozic	1	(1−s)^j(1+s _h)^p	10⁻⁶	>10⁹ cells
exp	(1+s)^j(1−s _h)^p(+)	1	b _j∗10⁻⁷	>10⁹ cells
McF_4	(1+s)^j/(1+s _h)^p	log(1+N/K)	5∗10⁻⁷	Number of
				drivers ≥4
McF_6	(1+s)^j/(1+s _h)^p	log(1+N/K)	5∗10⁻⁷	Number of
				drivers ≥6

j is the number of drivers with their dependencies met, and p the number of drivers with dependencies not met. In all cases s = 0.1. s _h is set to either 0 (so it has no effect) or ∞ (so fitness of that clone is 0). N: population size. K = 2000. ⁺:Strictly, birth rate = max(0, (1 + s)^j (1 −s ^h)^p).

ISSN: 1471-2105