Stepwise Evolution and Epistatic Interaction of Driver Mutations from Endometrial Hyperplasia to Carcinoma
Mary F Summers, Kira A. GlasmacheriD, Sem AsmelashiD, Jeffrey D. MandelliD, Jeffrey Nicholas FiskiD, Jeffrey P. TownsendiD, Vincent L. CannataroiD
Abstract
To characterize early oncogenesis, pathologically identified pre-cancerous tissue can be analyzed for the presence of cancer drivers. Here, we argue that in such studies, analyses of the driver status of variants, of the association between step-specific prevalence and progression through tumorigenesis, and of driver co-occurrence and mutual exclusivity should be accompanied by estimates of inherent mutation rate of variants and presented within an evolutionary framework of selective epistasis. To illustrate this point, we examine the transition of endometrial tissue from atypical hyperplasia to carcinoma. We apply a step-specific analysis, demonstrating that the strength of selection on somatic driver mutations promoting cell division and survival differs between hyperplasia to carcinoma. We demonstrate that mutations of PTEN, which are highly prevalent in carcinomas and have been argued to exert substantial driver effects, exhibit an even larger effect of increasing cellular division and survival within developing hyperplasias. A determination of cooccurrence or mutual exclusivity may be a product of genes sharing or differing in underlying sources of mutation, as opposed to a product of biological interaction and selection. By accounting for tumor-specific mutational processes that influence co-occurrence, we calculate epistatic selective intensities between pairs of drivers. Mutations of KRAS and FGFR2 are often mutually exclusive and were indeed found to exhibit significant antagonistic selective epistasis. However, mutations of PIK3CA and PIK3R1, which also have been identified as showing mutual exclusivity, do not demonstrate significant antagonistic selective epistasis. Thus, evidence of mutually exclusivity is insufficient to determine epistasis. Accordingly, the application of quantitative approaches that distinctly analyze mutation and selection on cancer variants has the potential to substantially illuminate the trajectory of tumorigenesis and cancer progression.
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