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Updated: Sep 26, 2026

Methods for Evaluating the Role of c-Fos and Dusp1 in Oncogene Dependence
Published on: January 7, 2019
Evolutionary dynamics of oncogenes and tumor suppressor genes: higher intensities of purifying selection than other
Michael A Thomas1, Benjamin Weston, Moltu Joseph
1Bioinformatics Research Center, Medical College of Wisconsin, Milwaukee, WI, USA. mthomas@mcw.edu
Abstract:
Oncogenes and tumor suppressor genes (hereafter referred to as "cancer genes") result in cancer when they experience substitutions that prevent or distort their normal function. We examined evolutionary pressures acting on cancer genes and other classes of disease-related genes and compared our results to analyses of genes without known association to disease. We compared synonymous and nonsynonymous substitution rates in 3,035 human genes-approximately 10% of the genome-measuring the intensity of purifying selection on 311 human disease genes, including 122 cancer-related genes. Although the genes examined are similar to nondisease genes in product, expression, function, and pathway affiliation, we found intriguing differences in the selective pressures experienced by cancer genes relative to other (noncancer) disease-related and non-disease-related genes. We found a statistically significant increase in the intensity of purifying selection exerted on cancer genes (the average ratio of nonsynonymous to synonymous substitutions, omega, was 0.079) relative to all other disease-related genes groups (omega = 0.101) and non-disease-related genes (omega = 0.100). This difference indicates a striking increase in selection against nonsynonymous substitutions in oncogenes and tumor suppressor genes. This finding provides insight into the etiology of cancer and the differences between genes involved in cancer and those implicated in other human diseases. Specifically, we found a significant overlap between human oncogenes and tumor suppressor genes and "essential genes," human homologs of mouse lethal genes identified by knockout experiments. This insight may improve our ability to identify cancer-related genes and enhances our understanding of the nature of these genes.
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