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Abstract:
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To estimate the number of cell divisions (mitotic age) of a given tissue type between individuals is of interest as that allows their stratification of prospective cancer risk. Here we develop a DNA methylation-based statistical method MiAge, designed to quantitatively estimate mitotic ages of a tissue of an individual. With MiAge, we build the MiAge Calculator, a true mitotic clock, using the training data of eight TCGA cancers. We test the MiAge Calculator using the testing data of five other cancers. We show that the mitotic clock is universally accelerated in tumor tissues than in adjacent normal tissues across tissue types. We further show that accelerated mitotic clock negatively correlates with survival across multiple cancers. Finally, we demonstrate the utility of this mitotic clock by showing that the integration of clinical information and mitotic clock leads to a much improved survival prediction in multiple cancers.
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