ArticleNature communications2022
Evaluating cancer etiology and risk with a mathematical model of tumor evolution.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Comprehensive Genomic Analysis of Normal and Cancer Cells Elucidates the Elevated Mutational Burden in Cancer.Cancer research · 2026Article
- Tumor evolution: signaling pathways, molecular mechanisms and therapeutic targets.Signal transduction and targeted therapy · 2026Review
- An investigative network analysis mapping global cancer epidemiology.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- Article
- Computational analysis of 3D biopolymeric porous scaffolds for the in vitro development of neural networks.PloS one · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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