Hormesis without cell killing.
Stochastic two-stage clonal expansion (TSCE) models of carcinogenesis offer the following clear theoretical explanation for U-shaped cancer dose-response relations. Low doses that kill initiated (premalignant) cells thereby create a protective effect. At higher doses, this effect is overwhelmed by an increase in the net number of initiated cells. The sum of these two effects, from cell killing and cell proliferation, gives a U-shaped or J-shaped dose-response relation. This article shows that exposures that do not kill, repair, or decrease cell populations, but that only hasten transitions that lead to cancer, can also generate U-shaped and J-shaped dose-response relations in a competing-risk (modified TSCE) framework where exposures disproportionately hasten transitions into carcinogenic pathways with relatively long times to tumor. Quantitative modeling of the competing effects of more transitions toward carcinogenesis (risk increasing) and a higher proportion of transitions into the slower pathway (risk reducing) shows that a J-shaped dose-response relation can occur even if exposure increases the number of initiated cells at every positive dose level. This suggests a possible new explanation for hormetic dose-response relations in response to carcinogenic exposures that do not have protective (cell-killing) effects. In addition, the examples presented emphasize the role of time in hormesis: exposures that monotonically increase risks at younger ages may nonetheless produce a U-shaped or J-shaped dose-response relation for lifetime risk of cancer.
Cox
Louis Anthony Tony
LA
Cox Associates and University of Colorado, 503 Franklin St., Denver, CO 80218, USA. tcoxdenver@aol.com
D000818:Animals; D016923:Cell Death / Q000187:drug effects; D049109:Cell Proliferation / Q000187:drug effects; D002471:Cell Transformation, Neoplastic / Q000187:drug effects*; D004305:Dose-Response Relationship, Drug; D006801:Humans; D008175:Lung Neoplasms / Q000473:pathology*; D008954:Models, Biological; D016012:Poisson Distribution; D012306:Risk; D013269:Stochastic Processes