Comprehensive Genomic Analysis of Normal and Cancer Cells Elucidates the Elevated Mutation Burden in Cancer.

Authors

Sophie Pénisson, Kameron Bates, Kunjur Manasa Upadhyaya, Kamel Lahouel, Mete Mülazımoğlu, Louka Monteiro de Sousa, Isaac Kohane, Jeffrey M Trent, Bert Vogelstein, Cristian Tomasetti

Published in

Cancer research. Jul 10, 2026. Epub Jul 10, 2026.

Abstract

Self-renewing normal tissues generate several somatic mutations at each division. Previous studies have reported that cancer cells have more mutations than their normal counterparts. It is not obvious why dramatic differences in mutation burdens between normal tissues and cancers should exist. To fully understand human tumorigenesis, the increase of mutation burden in cancers will have to be understood. Here, we provided a systematic comparison of mutational burdens in normal and cancer cells from five different organs, revealing a four-fold increase of mutation burdens in cancerous vs. non-cancerous cells. Three proposed hypotheses that could account for the increased mutation burdens in cancer are: the classical hypothesis, where driver gene mutations explain the higher mutational burden; the catastrophic hypothesis, where extreme mutational events lead to large-scale genomic alterations; and the tail hypothesis, where differences in baseline mutation rates among individuals account for the differences. Testing through orthogonal observations showed that the observed medians and distributions of mutation burdens in cancers could be explained by the hypotheses to various degrees of significance, and only the tail hypothesis could easily explain the increase in median mutation burdens in the normal tissues of cancer patients compared to the normal tissues of non-cancer patients. Overall, this study characterizes an increased mutation burden across multiple types of cancer compared to normal tissue and provides insights into the contributing factors. A tenable hypothesis proposed in this study involving fundamental differences in baseline mutation rates among individuals could have implications for cancer prevention strategies.

PMID:
42430563
Bibliographic data and abstract were imported from PubMed on 11 Jul 2026.

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