Abstract The research on cancer cells has proposed many hypotheses as a basic conceptual framework for understanding how normal cells transform into cancer cells. Cancer cells are assumed to undergo a multilevel mutation process from normal cells to cancer cells. A kinetics model of the multistep transformation of normal cells into cancer cells was developed to provide insight into the fundamental aspects of cancer cell evolution. The kinetic model is composed of coupled ordinary differential equations to describe the mutation process. This combination of equations can describe how mutational processes, such as angiogenesis, cell death rates, genetic instability, and replication rates. The main predictions of the multistep mutation model are based on the fastest-growing cancer cells. The new estimation method was used in this study to estimate the parameters in the kinetics model. Parameters were estimated using the particle swarm optimization algorithm. A new technique in this study, parameters are estimated to obtain the possible contribution of each parameter to the fastest-growing cancer cells. The results of this study present a new estimate of the multilevel mutation process based on parameters from breast cancer data.
Kartono et al. (Thu,) studied this question.
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