Abstract
Recently available cancer sequencing data have revealed a complex view of the cancer genome containing a multitude of mutations, including drivers responsible for cancer progression and neutral passengers. Measuring selection in cancer and distinguishing drivers from passengers have important implications for development of novel treatment strategies. It has recently been argued that a third of cancers are evolving neutrally, as their mutational frequency spectrum follows a 1/f power law expected from neutral evolution in a particular intermediate frequency range. We study a stochastic model of cancer evolution and derive a formula for the probability distribution of the cancer cell frequency of a subclonal driver, demonstrating that driver frequency is biased towards 0 and 1. We show that it is difficult to capture a driver mutation at an intermediate frequency, and thus the calling of neutrality due to a lack of such driver will significantly overestimate the number of neutrally evolving tumors. Our approach provides quantification of the validity of the 1/f statistic across the entire range of relevant parameter values. We also show that our conclusions remain valid for non-exponential models: spatial 3d model and sigmoidal growth, relevant for early- and late stages of cancer growth.
Highlights
Darwinian evolution in cancer has been the subject of intense research in the past decade
It has recently been argued that the presence or absence of selection in cancer can be deduced from deviation of mutant allele frequencies from 1/f power law in an intermediate frequency range
Using a stochastic mathematical model of cancer evolution we derive a formula for the frequency of a subclonal driver and show that frequencies of cancer drivers are biased towards 0 and 1; most mutations will inevitably appear to be either neutral or clonal despite very different levels of selection
Summary
Darwinian evolution in cancer has been the subject of intense research in the past decade. Numerous methods for classifying driver and passenger mutations and measuring selection in cancer have been developed, including those that identify driver genes based on how frequently they are mutated [2], specific mutation patterns [9,10], and dN/dS ratios [1,11]. Subsequent studies focused on quantifying the strength of selection and distinguishing it from “effectively neutral” cancer evolution [14,15] These works [13,15] are based upon the assumption that drivers that arose after cancer initiation will be present at a macroscopic but clearly subclonal frequency We use a branching process model of cancer evolution to derive a formula for the probability of detection of a subclonal driver, and test the validity of the proposed 1/f statistic across all relevant parameter combinations
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.