Toxicity and occupational exposure assessment for Fischer-Tropsch synthetic paraffinic kerosene.

Fischer-Tropsch (FT) Synthetic Paraffinic Kerosene (SPK) jet fuel is a synthetic organic mixture intended to augment petroleum-derived JP-8 jet fuel use by the U.S. armed forces. The FT SPK testing program goal was to develop a comparative toxicity database with petroleum-derived jet fuels that may be used to calculate an occupational exposure limit (OEL). Toxicity investigations included the dermal irritation test (FT vs. JP-8 vs. 50:50 blend), 2 in vitro genotoxicity tests, acute inhalation study, short-term (2-week) inhalation range finder study with measurement of bone marrow micronuclei, 90-day inhalation toxicity, and sensory irritation assay. Dermal irritation was slight to moderate. All genotoxicity studies were negative. An acute inhalation study with F344 rats exposed at 2000 mg/m3 for 4 hr resulted in no abnormal clinical observations. Based on a 2-week range-finder, F344 rats were exposed for 6 hr per day, 5 days per week, for 90 days to an aerosol-vapor mixture of FT SPK jet fuel (0, 200, 700 or 2000 mg/m3). Effects on the nasal cavities were minimal (700 mg/m3) to mild (2000 mg/m3); only high exposure produced multifocal inflammatory cell infiltration in rat lungs (both genders). The RD50 (50% respiratory rate depression) value for the sensory irritation assay, calculated to be 10,939 mg/m3, indicated the FT SPK fuel is less irritating than JP-8. Based upon the proposed use as a 50:50 blend with JP-8, a FT SPK jet fuel OEL is recommended at 200 mg/m3 vapor and 5 mg/m3 aerosol, in concurrence with the current JP-8 OEL.

Next generation testing strategy for assessment of genomic damage: A conceptual framework and considerations.

For several decades, regulatory testing schemes for genetic damage have been standardized where the tests being utilized examined mutations and structural and numerical chromosomal damage. This has served the genetic toxicity community well when most of the substances being tested were amenable to such assays. The outcome from this testing is usually a dichotomous (yes/no) evaluation of test results, and in many instances, the information is only used to determine whether a substance has carcinogenic potential or not. Over the same time period, mechanisms and modes of action (MOAs) that elucidate a wider range of genomic damage involved in many adverse health outcomes have been recognized. In addition, a paradigm shift in applied genetic toxicology is moving the field toward a more quantitative dose-response analysis and point-of-departure (PoD) determination with a focus on risks to exposed humans. This is directing emphasis on genomic damage that is likely to induce changes associated with a variety of adverse health outcomes. This paradigm shift is moving the testing emphasis for genetic damage from a hazard identification only evaluation to a more comprehensive risk assessment approach that provides more insightful information for decision makers regarding the potential risk of genetic damage to exposed humans. To enable this broader context for examining genetic damage, a next generation testing strategy needs to take into account a broader, more flexible approach to testing, and ultimately modeling, of genomic damage as it relates to human exposure. This is consistent with the larger risk assessment context being used in regulatory decision making. As presented here, this flexible approach for examining genomic damage focuses on testing for relevant genomic effects that can be, as best as possible, associated with an adverse health effect. The most desired linkage for risk to humans would be changes in loci associated with human diseases, whether in somatic or germ cells. The outline of a flexible approach and associated considerations are presented in a series of nine steps, some of which can occur in parallel, which was developed through a collaborative effort by leading genetic toxicologists from academia, government, and industry through the International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC). The ultimate goal is to provide quantitative data to model the potential risk levels of substances, which induce genomic damage contributing to human adverse health outcomes. Any good risk assessment begins with asking the appropriate risk management questions in a planning and scoping effort. This step sets up the problem to be addressed (e.g., broadly, does genomic damage need to be addressed, and if so, how to proceed). The next two steps assemble what is known about the problem by building a knowledge base about the substance of concern and developing a rational biological argument for why testing for genomic damage is needed or not. By focusing on the risk management problem and potential genomic damage of concern, the next step of assay(s) selection takes place. The work-up of the problem during the earlier steps provides the insight to which assays would most likely produce the most meaningful data. This discussion does not detail the wide range of genomic damage tests available, but points to types of testing systems that can be very useful. Once the assays are performed and analyzed, the relevant data sets are selected for modeling potential risk. From this point on, the data are evaluated and modeled as they are for any other toxicology endpoint. Any observed genomic damage/effects (or genetic event(s)) can be modeled via a dose-response analysis and determination of an estimated PoD. When a quantitative risk analysis is needed for decision making, a parallel exposure assessment effort is performed (exposure assessment is not detailed here as this is not the focus of this discussion; guidelines for this assessment exist elsewhere). Then the PoD for genomic damage is used with the exposure information to develop risk estimations (e.g., using reference dose (RfD), margin of exposure (MOE) approaches) in a risk characterization and presented to risk managers for informing decision making. This approach is applicable now for incorporating genomic damage results into the decision-making process for assessing potential adverse outcomes in chemically exposed humans and is consistent with the ILSI HESI Risk Assessment in the 21st Century (RISK21) roadmap. This applies to any substance to which humans are exposed, including pharmaceuticals, agricultural products, food additives, and other chemicals. It is time for regulatory bodies to incorporate the broader knowledge and insights provided by genomic damage results into the assessments of risk to more fully understand the potential of adverse outcomes in chemically exposed humans, thus improving the assessment of risk due to genomic damage. The historical use of genomic damage data as a yes/no gateway for possible cancer risk has been too narrowly focused in risk assessment. The recent advances in assaying for and understanding genomic damage, including eventually epigenetic alterations, obviously add a greater wealth of information for determining potential risk to humans. Regulatory bodies need to embrace this paradigm shift from hazard identification to quantitative analysis and to incorporate the wider range of genomic damage in their assessments of risk to humans. The quantitative analyses and methodologies discussed here can be readily applied to genomic damage testing results now. Indeed, with the passage of the recent update to the Toxic Substances Control Act (TSCA) in the US, the new generation testing strategy for genomic damage described here provides a regulatory agency (here the US Environmental Protection Agency (EPA), but suitable for others) a golden opportunity to reexamine the way it addresses risk-based genomic damage testing (including hazard identification and exposure). Environ. Mol. Mutagen. 58:264-283, 2017. © 2016 The Authors. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc.

An organizational approach for the assessment of DNA adduct data in risk assessment: case studies for aflatoxin B1, tamoxifen and vinyl chloride.

The framework analysis previously presented for using DNA adduct information in the risk assessment of chemical carcinogens was applied in a series of case studies which place the adduct information into context with the key events in carcinogenesis to determine whether they could be used to support a mutagenic mode of action (MOA) for the examined chemicals. Three data-rich chemicals, aflatoxin B1 (AFB1), tamoxifen (Tam) and vinyl chloride (VCl) were selected for this exercise. These chemicals were selected because they are known human carcinogens and have different characteristics: AFB1 forms a unique adduct and human exposure is through contaminated foods; Tam is a pharmaceutical given to women so that the dose and duration of exposure are known, forms unique adducts in rodents, and has both estrogenic and genotoxic properties; and VCl, to which there is industrial exposure, forms a number of adducts that are identical to endogenous adducts found in unexposed people. All three chemicals produce liver tumors in rats. AFB1 and VCl also produce liver tumors in humans, but Tam induces human uterine tumors, only. To support a mutagenic MOA, the chemical-induced adducts must be characterized, shown to be pro-mutagenic, be present in the tumor target tissue, and produce mutations of the class found in the tumor. The adducts formed by AFB1 and VCl support a mutagenic MOA for their carcinogenicity. However, the data available for Tam shows a mutagenic MOA for liver tumors in rats, but its carcinogenicity in humans is most likely via a different MOA.

Creating context for the use of DNA adduct data in cancer risk assessment: I. Data organization.

The assessment of human cancer risk from chemical exposure requires the integration of diverse types of data. Such data involve effects at the cell and tissue levels. This report focuses on the specific utility of one type of data, namely DNA adducts. Emphasis is placed on the appreciation that such DNA adduct data cannot be used in isolation in the risk assessment process but must be used in an integrated fashion with other information. As emerging technologies provide even more sensitive quantitative measurements of DNA adducts, integration that establishes links between DNA adducts and accepted outcome measures becomes critical for risk assessment. The present report proposes an organizational approach for the assessment of DNA adduct data (e.g., type of adduct, frequency, persistence, type of repair process) in concert with other relevant data, such as dosimetry, toxicity, mutagenicity, genotoxicity, and tumor incidence, to inform characterization of the mode of action. DNA adducts are considered biomarkers of exposure, whereas gene mutations and chromosomal alterations are often biomarkers of early biological effects and also can be bioindicators of the carcinogenic process.

Dose-response modeling of in vivo genotoxicity data for use in risk assessment: some approaches illustrated by an analysis of acrylamide.

Methods for dose-response modeling of in vivo genotoxicity data are introduced and applied to a case study of acrylamide. Genetic toxicity results are typically summarized as being either positive or negative, with no further consideration of the dose-response patterns that can be estimated from such studies. This analysis explores the use of three modeling approaches: Poisson regression of counts of genetic effects per cell; dynamic modeling of the time-course of micronucleus production and loss as a function of exposure; and categorical regression of sets of genetic toxicity experiments, the results of which are recoded in terms of severities of response. Estimates derived from these models (benchmark doses and predictions of response rates for predetermined doses of interest) are then used to assess the relevance and role of the genetic toxicity results in a risk assessment. With respect to the acrylamide data base, the results suggest that the genetic damage studies do not appear to be consistent or congruent with the thyroid tumor endpoints observed in two long-term bioassays in rats. This suggests that acrylamide's mechanism of action with respect to production of such tumors may not be genotoxic, and that a cancer risk assessment that applied a linear, no-threshold approach to such endpoints might be inappropriate. Benchmark doses derived from the genetic toxicity data base do not appear to be the critical ones for acrylamide risk assessment. Dose metric and modeling issues associated with the proposed dose-response approach to evaluation of genetic toxicity data are explored, and it is recommended that further advancements of the methodology be developed and employed for optimal use of such data for risk assessment purposes.