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A Bayesian network model was developed to integrate diverse types of data to conduct an exposure-dose-response assessment for benzene-induced acute myeloid leukemia (AML). The network approach was used to evaluate and compare individual biomarkers and quantitatively link the biomarkers along the exposure-disease continuum. The network was used to perform the biomarker-based dose-response analysis, and various other approaches to the dose-response analysis were conducted for comparison. The network-derived benchmark concentration was approximately an order of magnitude lower than that from the usual exposure concentration versus response approach, which suggests that the presence of more information in the low-dose region (where changes in biomarkers are detectable but effects on AML mortality are not) helps inform the description of the AML response at lower exposures. This work provides a quantitative approach for linking changes in biomarkers of effect both to exposure information and to changes in disease response. Such linkage can provide a scientifically valid point of departure that incorporates precursor dose-response information without being dependent on the difficult issue of a definition of adversity for precursors. [ABSTRACT FROM AUTHOR]

Advances in molecular epidemiology and mechanistic toxicology have provided increased opportunities for incorporating biomarkers in the human health risk assessment process. For years, the published literature has lauded the concept of incorporating biomarkers into risk assessments as a means to reduce uncertainty in estimating health risk. For all the potential benefits, one would think that markers of effective dose, markers of early biological effects, and markers of human susceptibility are frequently selected as the basis for quantitative human health risk assessments. For this article, we sought to determine the degree to which this evolution in risk assessment has come to pass. The extent to which biomarkers are being used in current human health risk assessment was determined through an informal survey of leading risk assessment practitioners. Case studies highlighting the evolution of risk assessment methods to include biomarkers are also described. The goal of this review was to enhance the implementation of biomarker technology in risk assessment by (1) highlighting successes in biomarker implementation, (2) identifying key barriers to overcome, and (3) describing evolutions in risk assessment methods. [ABSTRACT FROM AUTHOR]

Protein biomarkers to occupational carcinogens were investigated using a transformable human uroepithelial cell system, SV-HUC.PC. SV-HUC.PC was treated with N-hydroxy-4,4′-methylene bis (2-chloroaniline) (N-OH-MOCA) or N-hydroxy-4 aminobiphenyl (N-OH-ABP). Two-dimensional gel electrophoresis of cell lysates compared protein changes across treatments. Increasing N-OH-MOCA resulted in a dose-related increase in protein spots altered. Comparing cell profiles treated with either carcinogen revealed alterations in the expression of nine proteins, identified using the TagIdent database. These demonstrated isoelectric point shift (1) or quantity change (8). Our investigation may be useful in identifying biomarkers of effects of exposure to bladder carcinogens. [Copyright &y& Elsevier]