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Data files for simulated advanced adenoma age incidence, under aspirin treatment

Citation

Komarova, Natalia (2022), Data files for simulated advanced adenoma age incidence, under aspirin treatment, Dryad, Dataset, https://doi.org/10.7280/D1M11M

Abstract

Aspirin intake has been shown to lead to significant protection against colorectal cancer, e.g. with an up to two-fold reduction in colorectal adenoma incidence rates at higher doses. The mechanisms contributing to protection are not yet fully understood. While aspirin is an anti-inflammatory drug and can thus influence the tumor microenvironment, in vitro and in vivo experiments have recently shown that aspirin can also have a direct effect on cellular kinetics and fitness. It reduces the rate of tumor cell division and increases the rate of cell death. The question arises whether such changes in cellular fitness are sufficient to significantly contribute to the epidemiologically observed protection.

To investigate this, we constructed a class of mathematical models of in vivo evolution of advanced adenomas, parameterized it with available estimates, and calculated population level incidence. Fitting the predictions to age incidence data revealed that only a model that included colonic crypt competition can account for the observed age-incidence curve. This model was then used to predict modified incidence patterns if cellular kinetics were altered as a result of aspirin treatment. We found that changes in cellular fitness that were within the experimentally observed ranges could reduce advanced adenoma incidence by a sufficient amount to account for age incidence data in aspirin-treated patient cohorts. While the mechanisms that contribute to the protective effect of aspirin are likely complex and multi-factorial, our study demonstrates that direct aspirin-induced changes of tumor cell fitness can significantly contribute to epidemiologically observed reduced incidence patterns.

Data files that were generated to create predicted advanced adenoma age incidence curves for virtual patients that received different doses of aspirin for different decades of their lives. These data files are then processed by using Mathematica code (Code_Fig4.nb) that is included.

Funding