Accumulation of driver and passenger mutations during tumor progression

TL;DR

This paper introduces a mathematical model of tumor progression that explains heterogeneity in tumor development and estimates the small selective advantage of typical somatic mutations in human cancers.

Contribution

The study presents a novel discrete time branching process model that links driver mutations to tumor growth and provides a formula for mutation accumulation.

Findings

Tumor development rates vary widely, explaining observed heterogeneity.

The model estimates the selective advantage of somatic mutations as approximately 0.005.

Provides a new method to quantify mutation benefits in cancer progression.

Abstract

Major efforts to sequence cancer genomes are now occurring throughout the world. Though the emerging data from these studies are illuminating, their reconciliation with epidemiologic and clinical observations poses a major challenge. In the current study, we provide a novel mathematical model that begins to address this challenge. We model tumors as a discrete time branching process that starts with a single driver mutation and proceeds as each new driver mutation leads to a slightly increased rate of clonal expansion. Using the model, we observe tremendous variation in the rate of tumor development - providing an understanding of the heterogeneity in tumor sizes and development times that have been observed by epidemiologists and clinicians. Furthermore, the model provides a simple formula for the number of driver mutations as a function of the total number of mutations in the tumor. Finally, when applied to recent experimental data, the model allows us to calculate, for the first time, the actual selective advantage provided by typical somatic mutations in human tumors in situ. This selective advantage is surprisingly small, 0.005 +- 0.0005, and has major implications for experimental cancer research.