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Evaluating cancer etiology and risk with a mathematical model of tumor evolution
Medicine and HealthNature Communications

Evaluating cancer etiology and risk with a mathematical model of tumor evolution

S. Pénisson, A. Lambert, et al.

This research by Sophie Pénisson, Amaury Lambert, and Cristian Tomasetti unveils a groundbreaking mathematical model that predicts the expected number of innate somatic mutations in tissues as we age. By correlating these predictions with actual observations, the study reveals that these mutational processes account for a staggering 80% of the variability in cancer risk, underscoring their critical role in understanding cancer development.... show more
Abstract
Recent evidence arising from DNA sequencing of healthy human tissues has clearly indicated that our organs accumulate a relevant number of somatic mutations due to normal endogenous mutational processes, in addition to those caused by environmental factors. A deeper understanding of the evolution of this endogenous mutational load is critical for understanding what causes cancer. Here we present a mathematical model of tumor evolution that is able to predict the expected number of endogenous somatic mutations present in various tissue types of a patient at a given age. These predictions are then compared to those observed in patients. We also obtain an improved fitting of the variation in cancer incidence across cancer types, showing that the endogenous mutational processes can explain 4/5 of the variation in cancer risk. Overall, these results offer key insights into cancer etiology, by providing further evidence for the major role these endogenous processes play in cancer.
Publisher
Nature Communications
Published On
Nov 24, 2022
Authors
Sophie Pénisson, Amaury Lambert, Cristian Tomasetti
Tags
tumor evolutionsomatic mutationscancer riskmutational processescancer etiology
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