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Clonal Expansion (CE) Models in Cancer Risk Assessment
Citation:
CONOLLY, R. Clonal Expansion (CE) Models in Cancer Risk Assessment. Presented at Society for Risk Analysis Annual Meeting, Salt Lake City, UT, December 05 - 08, 2010.
Impact/Purpose:
The main thesis of this presentation is that uncertainty in low dose extrapolation can be reduced though judicious use of relevant mechanistic data.
Description:
Cancer arises when cells accumulate sufficient critical mutations. Carcinogens increase the probability of mutation during cell division or promote clonal expansion within stages. Multistage CE models recapitulate this process and provide a framework for incorporating relevant data. CE models fit naturally within biologically based dose response (BBDR) models linking carcinogen exposure with tumor response. A recent BBDR model for formaldehyde (F) consists of submodels for dosimetry, for a mode of action characterized by regenerative cellular proliferation and DNA damage, and for CE, with the latter taking mode of action effects as inputs and describing resultant tumor incidence. BBDR modeling has recently been criticized, particularly for its use in low dose extrapolation. It was specifically suggested that F might exert a low dose mitogenic effect on cells with one mutation, something that would be difficult to measure but that would significantly affect risk. Data gaps are not unique to BBDR/CE models, and do not present an insurmountable obstacle to the use of mechanistic data for low dose extrapolation. A BBDR/CE model that lacks data on cells with one mutation brings the gap to our attention, but no new uncertainty is introduced. If data on this component of the overall relationship is lacking, the uncertainty exists regardless of the model used to describe the relationship. Suggesting that the BBDR model increases uncertainty because it helps to identify a data gap is equivalent to shooting the messenger! Moreover, numerous studies of preneoplastic lesions provide substantial prior knowledge that should beconsidered when parameterizing this part of the CE model. The main thesis of this presentation is that uncertainty in low dose extrapolation can be reduced though judicious use of relevant mechanistic data. Uncertainties in the BBDR model for F will be compared to the uncertainties, explicit or not, in models with less biologically detailed structures. (This work was reviewed by the USEPA and approved for publication but may not reflect Agency policy.)