Modelling malignant progression with a finite state machine supports a two checkpoint theory of cancer

Abstract

We postulate the two checkpoints theory of cancer, a model of cancer development suggesting that malignant transformation of cells requires loss of function of both the G1 checkpoint and the mitotic spindle checkpoint. Malignant progression can be described as a process analogous to a genetic algorithm, which we term the malignant progression algorithm. There are two prerequisites for this process: first, there must be competition for reproductive resources, and this is driven by loss of the G1 checkpoint; second, there must be a source of genetic variation, and this is provided by loss of the mitotic spindle checkpoint, resulting in aneuploidy. These two factors then trigger a process of Darwinian selection, driving the emergence of cells with the various abnormalities that have been termed the “hallmarks of cancer”. Malignant progression is iterative, autocatalytic, and irreversible. The process can be modelled mathematically by describing the system as a finite state machine. The model indicates that loss of the two checkpoints is necessary and sufficient for tumour progression. The order of loss of the two checkpoints appears to be important: loss of the G1 checkpoint results in premalignant cells that replicate independently of physiological growth signals, but which remain diploid. Loss of the mitotic spindle checkpoint then results in aneuploid, malignant cells with highly error-prone replication, which rapidly progress to invasive, metastatic, hypoxia-tolerant, immortalised cells. This model of malignant progression has implications for the selection of anticancer drug targets and for tumour prevention strategies.

Keywords

• cancer
• checkpoint
• finite state machine
• genetic