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<p>Cancer-causing mutations have been identified primarily from positive selection signals in cancer genomes. However, positive selection is also a ubiquitous feature of normal tissue aging. Here we develop a statistical framework to disentangle selection in normal tissue and causation of carcinogenesis. By comparing cancer and normal tissue genomes, we estimate the effects of mutations on cancer risk in the blood, esophagus and colon. We determine that stronger cancer-causing mutations are enriched at younger patient ages. This enables cancer-causing mutations to be identified from patient age distributions, even without normal tissue data. Moreover, we show for acute myeloid leukemia that the age-dependence of purported causal mutations can be explained largely by normal blood evolution, challenging the long-standing notion that childhood cancers require distinct mutations. Broadly, our framework delineates carcinogenesis from normal tissue aging, improving the assessment of cancer risk conferred by mutations.</p>

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Age distinguishes selection from causation in cancer genomes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月5日

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  • David Cheek,
  • Martin Blohmer,
  • Martin A. Nowak,
  • Tibor Antal,
  • Kamila Naxerova

摘要

Cancer-causing mutations have been identified primarily from positive selection signals in cancer genomes. However, positive selection is also a ubiquitous feature of normal tissue aging. Here we develop a statistical framework to disentangle selection in normal tissue and causation of carcinogenesis. By comparing cancer and normal tissue genomes, we estimate the effects of mutations on cancer risk in the blood, esophagus and colon. We determine that stronger cancer-causing mutations are enriched at younger patient ages. This enables cancer-causing mutations to be identified from patient age distributions, even without normal tissue data. Moreover, we show for acute myeloid leukemia that the age-dependence of purported causal mutations can be explained largely by normal blood evolution, challenging the long-standing notion that childhood cancers require distinct mutations. Broadly, our framework delineates carcinogenesis from normal tissue aging, improving the assessment of cancer risk conferred by mutations.