Aspirin and the chemoprevention of cancers: A mathematical and evolutionary dynamics perspective.
Natalia L KomarovaC Richard BolandAjay GoelDominik WodarzPublished in: Wiley interdisciplinary reviews. Systems biology and medicine (2020)
Epidemiological data indicate that long-term low dose aspirin administration has a protective effect against the occurrence of colorectal cancer, both in sporadic and in hereditary forms of the disease. The mechanisms underlying this protective effect, however, are incompletely understood. The molecular events that lead to protection have been partly defined, but remain to be fully characterized. So far, however, approaches based on evolutionary dynamics have not been discussed much, but can potentially offer important insights. The aim of this review is to highlight this line of investigation and the results that have been obtained. A core observation in this respect is that aspirin has a direct negative impact on the growth dynamics of the cells, by influencing the kinetics of tumor cell division and death. We discuss the application of mathematical models to experimental data to quantify these parameter changes. We then describe further mathematical models that have been used to explore how these aspirin-mediated changes in kinetic parameters influence the probability of successful colony growth versus extinction, and how they affect the evolution of the tumor during aspirin administration. Finally, we discuss mathematical models that have been used to investigate the selective forces that can lead to the rise of mismatch-repair deficient cells in an inflammatory environment, and how this selection can be potentially altered through aspirin-mediated interventions. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.
Keyphrases
- low dose
- cardiovascular events
- antiplatelet therapy
- high dose
- induced apoptosis
- cell cycle arrest
- electronic health record
- signaling pathway
- oxidative stress
- liquid chromatography
- stem cells
- anti inflammatory drugs
- coronary artery disease
- cell death
- endoplasmic reticulum stress
- gene expression
- mass spectrometry
- single cell
- mesenchymal stem cells
- percutaneous coronary intervention
- machine learning
- single molecule
- cell therapy
- dna methylation
- amyotrophic lateral sclerosis