Quantitative Dose-response Data Research Articles

Adverse outcome pathways and linkages to transcriptomic effects relevant to ionizing radiation injury

Background In the past three decades, a large body of data on the effects of exposure to ionizing radiation and the ensuing changes in gene expression has been generated. These data have allowed for an understanding of molecular-level events and shown a level of consistency in response despite the vast formats and experimental procedures being used across institutions. However, clarity on how this information may inform strategies for health risk assessment needs to be explored. An approach to bridge this gap is the adverse outcome pathway (AOP) framework. AOPs represent an illustrative framework characterizing a stressor associated with a sequential set of causally linked key events (KEs) at different levels of biological organization, beginning with a molecular initiating event (MIE) and culminating in an adverse outcome (AO). Here, we demonstrate the interpretation of transcriptomic datasets in the context of the AOP framework within the field of ionizing radiation by using a lung cancer AOP (AOP 272: https://www.aopwiki.org/aops/272) as a case example. Methods Through the mining of the literature, radiation exposure-related transcriptomic studies in line with AOP 272 related to lung cancer, DNA damage response, and repair were identified. The differentially expressed genes within relevant studies were collated and subjected to the pathway and network analysis using Reactome and GeneMANIA platforms. Identified pathways were filtered (p < .001, ≥3 genes) and categorized based on relevance to KEs in the AOP. Gene connectivities were identified and further grouped by gene expression-informed associated events (AEs). Relevant quantitative dose-response data were used to inform the directionality in the expression of the genes in the network across AEs. Results Reactome analyses identified 7 high-level biological processes with multiple pathways and associated genes that mapped to potential KEs in AOP 272. The gene connectivities were further represented as a network of AEs with associated expression profiles that highlighted patterns of gene expression levels. Conclusions This study demonstrates the application of transcriptomics data in AOP development and provides information on potential data gaps. Although the approach is new and anticipated to evolve, it shows promise for improving the understanding of underlying mechanisms of disease progression with a long-term vision to be predictive of adverse outcomes.

Mutation as a Toxicological Endpoint for Regulatory Decision-Making.

Mutations induced in somatic cells and germ cells are responsible for a variety of human diseases, and mutation per se has been considered an adverse health concern since the early part of the 20th Century. Although in vitro and in vivo somatic cell mutation data are most commonly used by regulatory agencies for hazard identification, that is, determining whether or not a substance is a potential mutagen and carcinogen, quantitative mutagenicity dose-response data are being used increasingly for risk assessments. Efforts are currently underway to both improve the measurement of mutations and to refine the computational methods used for evaluating mutation data. We recommend continuing the development of these approaches with the objective of establishing consensus regarding the value of including the quantitative analysis of mutation per se as a required endpoint for comprehensive assessments of toxicological risk. Environ. Mol. Mutagen. 61:34-41, 2020. © 2019 Wiley Periodicals, Inc.

Python BMDS: A Python interface library and web application for the canonical EPA dose-response modeling software

Several primary sources of publicly available, quantitative dose-response data from traditional toxicology study designs relevant to predictive toxicology applications are now available, including the redeveloped U.S. Environmental Protection Agency’s Toxicity Reference Database (ToxRefDB v2.0), the Health Assessment Workspace Collaborative (HAWC), and the National Toxicology Program’s Chemical Program’s Chemical Effects in Biological Systems (CEBS). These resources provide effect level information but modeling these data to a curve may be more informative for predictive toxicology applications. Benchmark Dose Software (BMDS) has been recognized broadly and used for regulatory applications at multiple agencies. However, the current BMDS software was not amenable to modeling large datasets. Herein we describe development and use of a Python package that implements a wrapper around BMDS, a software that requires manual input in the dose-response modeling process (i.e., best-fitting model-selection, reporting, and dose-dropping). In the Python BMDS, users can select the BMDS version, customize model recommendation logic, and export summaries of the resultant BMDS output. Further, using the Python interface, a web-based application programming interface (API) has been developed for easy integration into other software systems, pipelines, or databases. Software utility was demonstrated via modeling nearly 28,000 datasets in ToxRefDB v2.0, re-creation of an existing, published large-scale analysis, and demonstration of usage in software such as CEBS and HAWC. Python BMDS enables rapid-batch processing of dose-response datasets using a modeling software with broad acceptance in the toxicology community, thereby providing an important tool for leveraging the publicly available quantitative toxicology data in a reproducible manner.

Cumulative Dose Threshold for the Chemopreventive Effect of Aspirin Against Gastric Cancer.

Many studies have found evidence that aspirin has protective effects against certain cancers, but quantitative dose-response data have been available only on a limited basis. This study aimed to confirm the dose-response relationship of aspirin usage and gastric cancer and to estimate the cumulative dose threshold of aspirin to achieve protective effects against gastric cancer in the general population. A total of 461,489 individuals in a population-based longitudinal cohort provided by the National Health Insurance Services (NHIS) in the Republic of Korea were observed from 2007 to 2012 to identify gastric cancer incident cases. The pharmacy claims data of these individuals from 2002 to 2006 were reviewed to assess cumulative medication exposure using the defined daily dose (DDD) system. Hazard ratios (HRs) of aspirin use for gastric cancer were estimated using multivariate Cox Proportional Hazard regression. Sensitivity analyses, including propensity-score matching and a nested case-control design, were performed to evaluate the variability caused by study design. A total of 5674 incident gastric cancers were identified from 2,965,500 person-years of follow-up observation, giving an overall incidence rate of 191.00 gastric cancers per 100,000 person-years. Compared to non-users, those with aspirin use of ≥3 DDD-years showed a statistically significant protective effect of aspirin use against gastric cancer; the adjusted HR (95% confidence intervals) were 0.79 (0.63-0.98) and 0.63 (0.48-0.83) for those with aspirin use of 3-4 DDD-years and 4-5 DDD-years, respectively (P for trend < 0.001). Sensitivity analyses using propensity-score matching and a nested case-control design consistently showed a chemopreventive effect of aspirin. Long-term aspirin use was associated with reduced gastric cancer incidence in the general population of South Korea when the cumulative dose was >3 DDD-years.

Environmental surveillance and monitoring--The next frontiers for high-throughput toxicology.

High-throughput toxicity testing technologies along with the World Wide Web are revolutionizing both generation of and access to data regarding the biological activities that chemicals can elicit when they interact with specific proteins, genes, or other targets in the body of an organism. To date, however, most of the focus has been on the application of such data to assessment of individual chemicals. The authors suggest that environmental surveillance and monitoring represent the next frontiers for high-throughput toxicity testing. Resources already exist in curated databases of chemical-biological interactions, including highly standardized quantitative dose-response data generated from nascent high-throughput toxicity testing programs such as ToxCast and Tox21, to link chemicals detected through environmental analytical chemistry to known biological activities. The emergence of the adverse outcome pathway framework and the associated knowledge base for linking molecular-level or pathway-level perturbations of biological systems to adverse outcomes traditionally considered in risk assessment and regulatory decision-making through a series of measurable biological changes provides a critical link between activity and hazard. Furthermore, environmental samples can be directly analyzed via high-throughput toxicity testing platforms to provide an unprecedented breadth of biological activity characterization that integrates the effects of all compounds present in a mixture, whether known or not. Novel application of these chemical-biological interaction data provides an opportunity to transform scientific characterization of potential hazards associated with exposure to complex mixtures of environmental contaminants.

Benchmarking B-Cell Epitope Prediction with Quantitative Dose-Response Data on Antipeptide Antibodies: Towards Novel Pharmaceutical Product Development

B-cell epitope prediction can enable novel pharmaceutical product development. However, a mechanistically framed consensus has yet to emerge on benchmarking such prediction, thus presenting an opportunity to establish standards of practice that circumvent epistemic inconsistencies of casting the epitope prediction task as a binary-classification problem. As an alternative to conventional dichotomous qualitative benchmark data, quantitative dose-response data on antibody-mediated biological effects are more meaningful from an information-theoretic perspective in the sense that such effects may be expressed as probabilities (e.g., of functional inhibition by antibody) for which the Shannon information entropy (SIE) can be evaluated as a measure of informativeness. Accordingly, half-maximal biological effects (e.g., at median inhibitory concentrations of antibody) correspond to maximally informative data while undetectable and maximal biological effects correspond to minimally informative data. This applies to benchmarking B-cell epitope prediction for the design of peptide-based immunogens that elicit antipeptide antibodies with functionally relevant cross-reactivity. Presently, the Immune Epitope Database (IEDB) contains relatively few quantitative dose-response data on such cross-reactivity. Only a small fraction of these IEDB data is maximally informative, and many more of them are minimally informative (i.e., with zero SIE). Nevertheless, the numerous qualitative data in IEDB suggest how to overcome the paucity of informative benchmark data.

Abstract 895: Quantitative drug sensitivity and resistance testing (DSRT) of primary ex vivo AML blasts highlights mTOR and MEK as potential key molecular driver signals of therapeutic significance

Abstract Identification of signaling pathways that are required for the growth and differentiation block of cells from adult acute myeloid leukemia (AML) is urgently required to facilitate development of novel therapies. Here, we describe an approach to functionally determine molecular drivers of AML by quantitative drug sensitivity and resistance testing (DSRT) of AML blast cells in primary culture ex vivo. The selection of drugs covered the entire cancer pharmacopeia and much of the pipeline of drugs under development in the industry: 120 FDA approved small molecular cancer drugs and 120 emerging drugs, investigational compounds and signal transduction inhibitors. All compounds were tested over a 10,000-fold concentration range to generate quantitative and reliable dose-response data. In addition, whole exome and transcriptome sequencing and phophoproteomic profiling were also performed to derive a comprehensive understanding of the molecular AML-related aberrations on an individual basis. Comparison of 17 AML patient samples and 3 healthy bone marrow control samples based on ex vivo drug responses identified several classes of approved and investigational drugs that showed selective anti-AML activities: mTOR inhibitors (e.g. temsirolomus, everolimus, sirolimus), MEK inhibitors (e.g. AS703026, GSK1120212, RDEA119, selumetinib), tyrosine kinase inhibitors (e.g. dasatinib, ponatinib, sunitinib), Bcl-2 inhibitors (navitoclax) and HSP90 inhibitors (e.g. BIIB021, NVP-AUY922, tanespimycin). In particular, the rapamycin class of mTOR inhibitors and allosteric MEK inhibitors stood out as effective and selective inhibitors in 8/17 (47%) and 9/17 (52%) of the patients, respectively. Simultaneous data from other targeted inhibitors made it possible to dissect the critical steps in signaling and therapeutic efficacy. For example, PI3K and Akt inhibitors were not effective in these patients, suggesting that the mTOR dependency is mediated through a PI3K-Akt-independent pathway. Similarly, the dependency of MEK signaling appears to be through a Ras-Raf-independent pathway since Raf inhibitors were not effective. In conclusion, the DSRT platform allows us to derive quantitative data on the ex vivo drug response profiles of AML cells from individual patients. This information could be used as a diagnostic tool to optimize personalized therapies in the future. Our data demonstrate that mTOR and MEK signaling and the associated inhibitors are the most promising leads for improved AML therapeutics. This analysis also demonstrates gaps in our current understanding of the redundancy of key cancer cell signaling pathways and proves the significant value of data from experimental drug response testing ex vivo. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 895. doi:1538-7445.AM2012-895

High-throughput, high-sensitivity analysis of gene expression in Arabidopsis.

High-throughput gene expression analysis of genes expressed during salt stress was performed using a novel multiplexed quantitative nuclease protection assay that involves customized DNA microarrays printed within the individual wells of 96-well plates. The levels of expression of the transcripts from 16 different genes were quantified within crude homogenates prepared from Arabidopsis (Arabidopsis thaliana) plants also grown in a 96-well plate format. Examples are provided of the high degree of reproducibility of quantitative dose-response data and of the sensitivity of detection of changes in gene expression within limiting amounts of tissue. The lack of requirement for RNA purification renders the assay particularly suited for high-throughput gene expression analysis and for the discovery of novel chemical compounds that specifically modulate the expression of endogenous target genes.

Suppression of Neoplastic Transformation in vitro by Low Doses of Low Let Radiation

A major concern of exposure to low doses of radiation is the risk of cancer induction. Epidemiologic data are rarely powerful enough to accurately discriminate this risk at doses <10 cGy. In order to gain insight into events at these low doses, laboratory-based studies of relevant endpoints are required. One such endpoint is radiation-induced neoplastic transformation in vitro. Such studies can provide quantitative dose-response data, as well as insights into underlying cellular and molecular mechanisms. Data are presented that indicate that low doses of low LET radiation can suppress neoplastic transformation in vitro to levels below those seen spontaneously. Mechanisms involved include both the death of a subpopulation of cells prone to spontaneous neoplastic transformation and the induction of DNA repair. The relative contributions of these mechanisms is dose-dependent. The relevance of these observations to radiation risk estimation is discussed.

Radiation-induced neoplastic transformation in vitro: evidence for a protective effect at low doses of low LET radiation.

The study of radiation-induced transformation in vitro has long been an experimental approach to examine mechanisms underlying radiation carcinogenesis. Even though the major concern of exposure to radiation is the risk of cancer induction at low radiation doses, most laboratory mechanistic studies have focused on high dose effects. This, coupled with the fact that epidemiologic data are rarely powerful enough to accurately discriminate this risk at doses <5 cGy, has led in recent years to an increased effort to study low dose effects using the endpoint of neoplastic transformation in vitro. Since transformation frequencies at low doses are typically low (< 10(-4)), such studies are, by necessity, large and labor intensive. However, they have yielded quantitative dose-response data, as well as insights into underlying cellular and molecular mechanisms. An interesting, and potentially important, finding is that low doses of low LET radiation can suppress neoplastic transformation in vitro to levels below that seen spontaneously. Mechanistic studies have revealed that multiple mechanisms are likely to be involved, and these include both the death of a subpopulation of cells prone to spontaneous neoplastic transformation and the induction of DNA repair. The relative contribution of these mechanisms appears to be dose-dependent. The relevance of in vitro studies to carcinogenesis in vivo is discussed.

A quantitative characterization of the yeast heterotrimeric G protein cycle.

The yeast mating response is one of the best understood heterotrimeric G protein signaling pathways. Yet, most descriptions of this system have been qualitative. We have quantitatively characterized the heterotrimeric G protein cycle in yeast based on direct in vivo measurements. We used fluorescence resonance energy transfer to monitor the association state of cyan fluorescent protein (CFP)-Galpha and Gbetagamma-yellow fluorescent protein (YFP), and we found that receptor-mediated G protein activation produced a loss of fluorescence resonance energy transfer. Quantitative time course and dose-response data were obtained for both wild-type and mutant cells possessing an altered pheromone response. These results paint a quantitative portrait of how regulators such as Sst2p and the C-terminal tail of alpha-factor receptor modulate the kinetics and sensitivity of G protein signaling. We have explored critical features of the dynamics including the rapid rise and subsequent decline of active G proteins during the early response, and the relationship between the G protein activation dose-response curve and the downstream dose-response curves for cell-cycle arrest and transcriptional induction. Fitting the data to a mathematical model produced estimates of the in vivo rates of heterotrimeric G protein activation and deactivation in yeast.

Vehicle effects on skin sensitizing potency of four chemicals: assessment using the local lymph node assay

The murine local lymph node assay (LLNA) can be used to determine the relative skin sensitizing potency of chemicals via interpolation of the quantitative dose response data generated. Using this approach we have demonstrated previously that the vehicle matrix in which a chemical allergen is encountered on the skin can have a significant influence on sensitizing potency. Estimates of relative potency are calculated from LLNA dose responses as a function of the mathematically derived EC3 value, this being the concentration estimated to induce a stimulation index (SI) of 3. To investigate further the influence of application vehicle on sensitizing potency, the LLNA has been used to examine the activity of four recognized human contact allergens: isoeugenol and cinnamic aldehyde, two fragrance chemicals; 3-dimethylaminopropylamine (a sensitizing impurity of cocamidopropyl betaine, a surfactant used in shower gel) and dibromodicyanobutane (the sensitizing component of Euxyl K 400, a preservative used in cosmetics). The four chemicals were applied in each of seven different vehicles (acetone: olive oil [4 : 1]; dimethylsulphoxide; methylethylketone; dimethyl formamide; propylene glycol; and both 50 : 50 and 90 : 10 mixtures of ethanol and water). It was found that the vehicle in which a chemical is presented to the epidermis can have a marked effect on sensitizing activity. EC3 values ranged from 0.9 to 4.9% for isoeugenol, from 0.5 to 1.7% for cinnamic aldehyde, from 1.7 to > 10% for dimethylaminopropylamine and from 0.4 to 6.4% for dibromodicyanobutane. These data confirm that the vehicle in which a chemical is encountered on the skin has an important influence on the relative skin sensitizing potency of chemicals and may have a significant impact on the acquisition of allergic contact dermatitis. The data also demonstrate the utility of the LLNA as a method for the prediction of these effects and thus for the development of more accurate risk assessments.

A spore counting method and cell culture model for chlorine disinfection studies of Encephalitozoon syn. Septata intestinalis.

The microsporidia have recently been recognized as a group of pathogens that have potential for waterborne transmission; however, little is known about the effects of routine disinfection on microsporidian spore viability. In this study, in vitro growth of Encephalitozoon syn. Septata intestinalis, a microsporidium found in the human gut, was used as a model to assess the effect of chlorine on the infectivity and viability of microsporidian spores. Spore inoculum concentrations were determined by using spectrophotometric measurements (percent transmittance at 625 nm) and by traditional hemacytometer counting. To determine quantitative dose-response data for spore infectivity, we optimized a rabbit kidney cell culture system in 24-well plates, which facilitated calculation of a 50% tissue culture infective dose (TCID(50)) and a minimal infective dose (MID) for E. intestinalis. The TCID(50) is a quantitative measure of infectivity and growth and is the number of organisms that must be present to infect 50% of the cell culture wells tested. The MID is as a measure of a system's permissiveness to infection and a measure of spore infectivity. A standardized MID and a standardized TCID(50) have not been reported previously for any microsporidian species. Both types of doses are reported in this paper, and the values were used to evaluate the effects of chlorine disinfection on the in vitro growth of microsporidia. Spores were treated with chlorine at concentrations of 0, 1, 2, 5, and 10 mg/liter. The exposure times ranged from 0 to 80 min at 25 degrees C and pH 7. MID data for E. intestinalis were compared before and after chlorine disinfection. A 3-log reduction (99.9% inhibition) in the E. intestinalis MID was observed at a chlorine concentration of 2 mg/liter after a minimum exposure time of 16 min. The log(10) reduction results based on percent transmittance-derived spore counts were equivalent to the results based on hemacytometer-derived spore counts. Our data suggest that chlorine treatment may be an effective water treatment for E. intestinalis and that spectrophotometric methods may be substituted for labor-intensive hemacytometer methods when spores are counted in laboratory-based chlorine disinfection studies.

Summary of the Workshop on Issues in Risk Assessment: Quantitative Methods for Developmental Toxicology

This report summarizes the proceedings of a conference on quantitative methods for assessing the risks of developmental toxicants. The conference was planned by a subcommittee of the National Research Council's Committee on Risk Assessment Methodology in conjunction with staff from several federal agencies, including the U.S. Environmental Protection Agency, U.S. Food and Drug Administration, U.S. Consumer Products Safety Commission, and Health and Welfare Canada. Issues discussed at the workshop included computerized techniques for hazard identification, use of human and animal data for defining risks in a clinical setting, relationships between end points in developmental toxicity testing, reference dose calculations for developmental toxicology, analysis of quantitative dose-response data, mechanisms of developmental toxicity, physiologically based pharmacokinetic models, and structure-activity relationships. Although a formal consensus was not sought, many participants favored the evolution of quantitative techniques for developmental toxicology risk assessment, including the replacement of lowest observed adverse effect levels (LOAELs) and no observed adverse effect levels (NOAELs) with the benchmark dose methodology.

Intact chemoreceptor biosensors based on Hawaiian aquatic species

Two species of Hawaiian crustaceans, Portunis sanguinolentus and Podophthalmis vigil, are shown to be effective for the construction of antennular receptrodes. The resulting chemoreceptor-based biosensors respond to stimulant compounds at levels below 10 −15 M with very short response times. Experimental studies focused on trimethylamine oxide as a novel test compound, combined with chemometric techniques for data analysis, yield quantitative dose-response data over a wide concentration range.

α-Factor inhibition of the rate of cell passage through the “start” step of cell division in Saccharomyces cerevisiae yeast: Estimation of the division delay per α-factor·receptor complex

A highly sensitive, kinetically unambiguous assay for α-factor-induced delay of cell passage through the “start” step of cell division in yeast is presented. The assay employs perfusion with periodic microscopy to monitor the bud emergence kinetics on the 20% of cells within an exponentially growing population which exist prior to the α-factor execution point of start. The t 1 2 for cell passage through start by this population of cells is 31 min in the absence of α-factor. The inhibition constant, K I , represents the α-factor concentration which produces a 50% inhibition of this rate and is equal to 2×10 −10 M. A second assay for maximal cell division arrest by α-factor on whole populations of cells is presented. This assay shows a maximum cell division arrest time of 125±5 h at saturating α-factor, and a K 50 (that is, an α-factor concentration which produces a half-maximal response) of 2.5×10 −8 M. Both assays were performed in the effective absence of α-factor inactivation. Values of the dissociation constant K D and total number of receptors per cell which specifically mediate cell division arrest or delay were estimated to be 2.5×10 −8 M and 10 4, respectively. These estimates, along with the quantitative dose-response data for division arrest which are presented here, are consistent with each receptor·α-factor complex which is present on the cell at equilibrium producing a 43±10 s delay of cell passage through start. Surprisingly, this number is constant within twofold over the entire range of cellular division arrest responses to α-factor, that is, from a 1.9-fold inhibition of the rate of cell passage through start at 0.17 n M α-factor to a 125±5 h maximum arrest at saturating α-factor concentrations of >170 n M. The possible significance of this observation toward the mechanism of α-factor-induced cell division arrest is discussed.

Quantitative aspects of lipoprotein lipase release by heparin in mice.

Although heparin has been known to release lipoprotein lipase (diacylglycerol acylhydrolase, EC 3.1.1.34) since 1943 (1), the quantitative aspects related to dosage have never been fully determined. Furthermore, only the data of Robinson et al. (2) are available concerning the half-life of enzyme action, once released into the blood. Olsson et al. (3) and Estes et al. (4) published data on the volume of distribution of heparin and kinetic data on heparin's anticoagulant action in man. More recently, McAvoy (5) determined the biologic half-life of heparin. In this paper, we present quantitative dose-response data on the release of lipoprotein lipase by heparin in mice, as well as information on time-duration action of released lipoprotein lipase in serum.Materials and Methods. Seventy male Swiss-Webster mice (weighing 20–30 g) were used in this investigation. Heparin sodium was injected intravenously in the tail vein in a volume of 0.1 ml. Axillary blood was obtained from etherized mice, allowed to clot, a...