Beyond two-stage models for lung carcinogenesis in the Mayak workers: implications for plutonium risk.

Sascha Zöllner,Markus Eidemüller,Mikhail E Sokolnikov,Olga Y Gorlova

doi:10.1371/journal.pone.0126238

Sascha Zöllner, Markus Eidemüller + Show 2 more

Open Access

https://doi.org/10.1371/journal.pone.0126238

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Journal: PloS one	Publication Date: May 22, 2015
Citations: 58	License type: CC BY 4.0

Affiliation: Helmholtz Zentrum München, Institute of Biophysics

Abstract

Mechanistic multi-stage models are used to analyze lung-cancer mortality after Plutonium exposure in the Mayak-workers cohort, with follow-up until 2008. Besides the established two-stage model with clonal expansion, models with three mutation stages as well as a model with two distinct pathways to cancer are studied. The results suggest that three-stage models offer an improved description of the data. The best-fitting models point to a mechanism where radiation increases the rate of clonal expansion. This is interpreted in terms of changes in cell-cycle control mediated by bystander signaling or repopulation following cell killing. No statistical evidence for a two-pathway model is found. To elucidate the implications of the different models for radiation risk, several exposure scenarios are studied. Models with a radiation effect at an early stage show a delayed response and a pronounced drop-off with older ages at exposure. Moreover, the dose-response relationship is strongly nonlinear for all three-stage models, revealing a marked increase above a critical dose.

Highlights

Beginning with the seminal multi-step models by Armitage/Doll and Nordling [3, 4], this eventually led to the stochastic two-stage model with clonal expansion due to Moolgavkar, Venzon, and Knudson [5, 6], which has become an established tool to understand and predict cancer risk [7,8,9]
All highest-ranked multi-stage models share a Plutonium-induced enhancement of proliferation rates
The fits suggest that 3-stage models with a radiation effect on an early stage of proliferation may yield an improved description of the Mayak data, compared with an effect on the penultimate stage (C)

Summary

Introduction

In the widely held theory of somatic evolution [1], a cell’s path toward the malignant state is portrayed as a series of mutations or epigenetic events, lending it successive selective advantages These advantages, as summarized in the “hallmarks of cancer” [2], essentially amount to an increasingly uncontrolled proliferation. Beginning with the seminal multi-step models by Armitage/Doll and Nordling [3, 4], this eventually led to the stochastic two-stage model with clonal expansion due to Moolgavkar, Venzon, and Knudson [5, 6], which has become an established tool to understand and predict cancer risk [7,8,9].

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