Nonlinear cancer response at ultralow dose: a 40800-animal ED(001) tumor and biomarker study

Assessment of human cancer risk from animal carcinogen studies is severely limited by inadequate experimental data at environmentally relevant exposures and by procedures requiring modeled extrapolations many orders of magnitude below observable data. We used rainbow trout, an animal model well-suited to ultralow-dose carcinogenesis research, to explore dose-response down to a targeted 10 excess liver tumors per 10000 animals (ED(001)). A total of 40800 trout were fed 0-225 ppm dibenzo[a,l]pyrene (DBP) for 4 weeks, sampled for biomarker analyses, and returned to control diet for 9 months prior to gross and histologic examination. Suspect tumors were confirmed by pathology, and resulting incidences were modeled and compared to the default EPA LED(10) linear extrapolation method. The study provided observed incidence data down to two above-background liver tumors per 10000 animals at the lowest dose (that is, an unmodeled ED(0002) measurement). Among nine statistical models explored, three were determined to fit the liver data well-linear probit, quadratic logit, and Ryzin-Rai. None of these fitted models is compatible with the LED(10) default assumption, and all fell increasingly below the default extrapolation with decreasing DBP dose. Low-dose tumor response was also not predictable from hepatic DBP-DNA adduct biomarkers, which accumulated as a power function of dose (adducts = 100 x DBP(1.31)). Two-order extrapolations below the modeled tumor data predicted DBP doses producing one excess cancer per million individuals (ED(10)(-6)) that were 500-1500-fold higher than that predicted by the five-order LED(10) extrapolation. These results are considered specific to the animal model, carcinogen, and protocol used. They provide the first experimental estimation in any model of the degree of conservatism that may exist for the EPA default linear assumption for a genotoxic carcinogen.