Cell Dynamics is a Cancer Drive.

INTRODUCTION AND OBJECTIVES: Cancer is a multi-stage disease characterized by abnormal replication of somatic cells mainly due to genetic alterations. As cells divide, they accumulate mutations, which mostly are neutral or negative but few can increase fitness and provide selective advantage that leads to clonal expansion. Age, environmental exposition and tissue characteristics are factors that contribute to the number of accumulated mutations; in addition, lifetime cancer risk correlates with the number of stem cell division from different tissues due to mutation load. As most tissues are in homeostasis, more division implies more cell death, which corresponds to Cell Turnover Rate (CTOR) and impacts on population dynamics, leading to an increase in tissue clonality. Thus, to characterize CTOR as a cancer risk regardless of mutation load, we propose that, with high CTOR, mutated cells are more likely to be selected, a concept called ancestral selection (ANSEL). MATERIAL AND METHOD: For all simulations we used esiCancer, a software that stochastically models evolutionary story. The software receives an esiTable representing the genome of each cell, which was modified for each condition analyzed. RESULTS AND CONCLUSION: In our hypothesis, in a high CTOR scenario, a significant number of cells will divide and another will be eliminated, reducing the percentage of ancestral cells and increasing the dominant ancestral by clonal selection. Conversely, in a low CTOR scenario, only a few cells will divide or be eliminated. We define the ancestral selection profile as the ratio between the dominant ancestral and the percentage of ancestral cells in current population, which is positively related to CTOR as demonstrated in simulations. In simulations with mutations, high CTORs had a higher proportion of cells with multiple hits, suggesting that population dynamics may be responsible for the accumulation of multiple mutations that may increase the chance of tumors in a scenario with cancer driver genes. In a tumorigenic condition, high CTORs had earlier and more esiTumors, which was demonstrated by the relative incidence curve and by the total risk of esiTumor. We then built an esiTable for ESCC and set values based on literature data for a more realistic condition. ESCC was chosen due to previous demonstration of neutral clonal competition in normal esophageal epithelium, in which the number of clones decreased with time and the area of remained clones increased. Under this condition, CTOR and esiTumor risk were positively related; however, the number of mutations, which increases with CTOR, may be a possible explanation. We then adjusted the number of mutations per division so that each CTOR receives the same number of mutations. In this condition, we continue to see a positive relation between CTOR and esiTumor, suggesting that there is a CTOR-dependent risk, which corroborates our hypothesis.