Genetic toxicology in silico protocol

In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

Considerations for Strategic Use of High-Throughput Transcriptomics Chemical Screening Data in Regulatory Decisions

Recently, numerous organizations, including governmental regulatory agencies in the U.S. and abroad, have proposed using data from New Approach Methodologies (NAMs) for augmenting and increasing the pace of chemical assessments. NAMs are broadly defined as any technology, methodology, approach or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. High-throughput transcriptomics (HTTr) is a type of NAM that uses gene expression profiling as an endpoint for rapidly evaluating the effects of large numbers of chemicals on in vitro cell culture systems. As compared to targeted high-throughput screening (HTS) approaches that measure the effect of chemical X on target Y, HTTr is a non-targeted approach that allows researchers to more broadly characterize the integrated response of an intact biological system to chemicals that may affect a specific biological target or many biological targets under a defined set of treatment conditions (time, concentration, etc.). HTTr screening performed in concentration-response mode can provide potency estimates for the concentrations of chemicals that produce perturbations in cellular response pathways. Here, we discuss study design considerations for HTTr concentration-response screening and present a framework for the use of HTTr-based biological pathway-altering concentrations (BPACs) in a screening-level, risk-based chemical prioritization approach. The framework involves concentration-response modeling of HTTr data, mapping gene level responses to biological pathways, determination of BPACs, in vitro-to-in vivo extrapolation (IVIVE) and comparison to human exposure predictions.

The Carcinogenome Project: In Vitro Gene Expression Profiling of Chemical Perturbations to Predict Long-Term Carcinogenicity

BACKGROUND

Most chemicals in commerce have not been evaluated for their carcinogenic potential. The de facto gold-standard approach to carcinogen testing adopts the 2-y rodent bioassay, a time-consuming and costly procedure. High-throughput in vitro assays are a promising alternative for addressing the limitations in carcinogen screening.

OBJECTIVES

We developed a screening process for predicting chemical carcinogenicity and genotoxicity and characterizing modes of actions (MoAs) using in vitro gene expression assays.

METHODS

We generated a large toxicogenomics resource comprising [Formula: see text] expression profiles corresponding to 330 chemicals profiled in HepG2 (human hepatocellular carcinoma cell line) at multiple doses and replicates. Predictive models of carcinogenicity and genotoxicity were built using a random forest classifier. Differential pathway enrichment analysis was performed to identify pathways associated with carcinogen exposure. Signatures of carcinogenicity and genotoxicity were compared with external sources, including Drugmatrix and the Connectivity Map.

RESULTS

Among profiles with sufficient bioactivity, our classifiers achieved 72.2% Area Under the ROC Curve (AUC) for predicting carcinogenicity and 82.3% AUC for predicting genotoxicity. Chemical bioactivity, as measured by the strength and reproducibility of the transcriptional response, was not significantly associated with long-term carcinogenicity in doses up to [Formula: see text]. However, sufficient bioactivity was necessary for a chemical to be used for prediction of carcinogenicity. Pathway enrichment analysis revealed pathways consistent with known pathways that drive cancer, including DNA damage and repair. The data is available at https://clue.io/CRCGN_ABC , and a portal for query and visualization of the results is accessible at https://carcinogenome.org .

DISCUSSION

We demonstrated an in vitro screening approach using gene expression profiling to predict carcinogenicity and infer MoAs of chemical perturbations. https://doi.org/10.1289/EHP3986.

In silico toxicology protocols

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information.

The impact of flow PRA on outcome in pediatric heart recipients in modern era: An analysis of the Pediatric Heart Transplant Study database

Data from patients in the Pediatric Heart Transplant Study (PHTS) registry transplanted between 2010 and 2014 were analyzed to determine the association between HLA antibody (PRA) determined by SPA using Luminex or flow cytometry with a positive retrospective cross-match and the post-transplant outcomes of acute rejection and graft survival. A total of 1459 of 1596 (91%) recipients had a PRA reported pretransplant; 26% had a PRA > 20%. Patients with a PRA > 20% were more likely to have CHD, prior cardiac surgery, ECMO support at listing, and waited longer for transplantation than patients with a PRA <20%. Patients with higher PRA% determined by SPA were predictive of a positive retrospective cross-match determined by flow cytometric method (P < .001). A PRA > 50% determined by SPA was independently associated with worse overall graft survival after first month of transplant in both unadjusted and adjusted for all other risk factors. In this large multicenter series of pediatric heart transplant recipients, an elevated PRA determined by SPA remains a significant risk factor in the modern era.

Tox21 Enricher: Web-based Chemical/Biological Functional Annotation Analysis Tool Based on Tox21 Toxicity Screening Platform

The US Toxicology Testing in the 21st Century (Tox21) program was established to develop more efficient and human-relevant toxicity assessment methods. The Tox21 program screens >10,000 chemicals using quantitative high-throughput screening (qHTS) of assays that measure effects on toxicity pathways. To date, more than 70 assays have yielded >12 million concentration-response curves. The patterns of activity across assays can be used to define similarity between chemicals. Assuming chemicals with similar activity profiles have similar toxicological properties, we may infer toxicological properties based on its neighbourhood. One approach to inference is chemical/biological annotation enrichment analysis. Here, we present Tox21 Enricher, a web-based chemical annotation enrichment tool for the Tox21 toxicity screening platform. Tox21 Enricher identifies over-represented chemical/biological annotations among lists of chemicals (neighbourhoods), facilitating the identification of the toxicological properties and mechanisms in the chemical set.

Clinical practice patterns are relatively uniform between pediatric heart transplant centers: A survey-based assessment

Clinical practice variations are a barrier to the study of pediatric heart transplants and coordination of multicenter RCTs in this patient population. We surveyed centers to describe practice patterns, understand areas of variation, and willingness to modify protocol. Pediatric heart transplant centers were identified, and one survey was completed per center. Simple descriptive statistics were used. The response rate was 77% (40 responses from 52 contacted centers, 37 with complete responses). Median center volume of respondents was eight transplants/year (IQR 3-19). Most centers reported tacrolimus (36/38, 95%) and mycophenolate mofetil (36/38, 95%) as maintenance immunosuppression. Other immunosuppression agents reported were cyclosporine (7/38, 18%), everolimus or sirolimus (3/38, 8%), and azathioprine (2/38, 5%). Overall, respondents answered similarly for questions regarding clinical practices including induction therapy, maintenance immunosuppression, and rejection treatment threshold (>85% agreement for all). Additionally, willingness to change clinical practices was over 70% for all practices surveyed (35 total respondents), and 97% of centers (36/37) were willing to participate in a RCT of maintenance immunosuppression. In conclusion, we found many similar clinical practice protocols. Most centers are willing to collaborate on a common protocol in order to participate in a RCT and support a trial investigating maintenance immunosuppression.

Integrating Drug's Mode of Action into Quantitative Structure-Activity Relationships for Improved Prediction of Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is complex in mechanism. Different drugs could undergo different mechanisms but result in the same DILI type, while the same drug could lead to different DILI types via different mechanisms. Therefore, predicting a drug's potential for DILI should take its underlying mechanisms into consideration. To achieve that, we constructed a novel approach by incorporating the drug's Mode of Action (MOA) into Quantitative Structure-Activity Relationship (QSAR) modeling. This MOA-DILI approach was examined using a data set of 333 drugs. The drugs were first grouped according to their MOA profiles (positive or negative in each MOA) based on the Tox21 qHTS assays. QSAR models for individual MOA assays were developed and subsequently combined to obtain the MOA-DILI model. A hold-out testing strategy (222 drugs for training and 111 drugs as a test set) was employed, which yielded a predictive accuracy of 0.711. The MOA-DILI model was directly compared with the standard QSAR approach using the same hold-out strategy, and the QSAR model yielded an accuracy of 0.662. To minimize the random chance in splitting training/test sets, the hold-out testing process was repeated 1000 times, and the observed difference in prediction accuracy between MOA-DILI and QSARs was statistically significant (P value <0.0001). Out of 17 MOAs used, four assays (i.e., antioxidant response elements, PPAR-gamma, estrogen receptor, and thyroid receptor assays) contributed most to the improved prediction of the MOA-DILI model over QSARs. In conclusion, the MOA-DILI approach has the potential to significantly improve predictive outcomes and to reveal complex relationships between MOAs and DILI, all of which would be helpful in developing DILI predictive models in drug screening and for risk assessment of industrial chemicals.

Cardiac Failure in a Trisomy 9 Patient Undergoing Anesthesia: A Case Report

A 27-year-old female with Trisomy 9 mosaicism presented to Children's Hospital Colorado for outpatient dental surgery under general anesthesia. The patient's past medical history was also significant for premature birth, gastroesophageal reflux, scoliosis and kyphosis, obesity, and developmental delay. Per her mother's report, the patient had no cardiac issues. She had undergone multiple previous general anesthetics, some of which documented respiratory complications such as laryngospasm, bronchospasm, and possible aspiration. During this anesthetic, the patient became hypotensive on induction, with sluggish response to intravenous fluids, glycopyrrolate, and ephedrine. Her electrocardiogram demonstrated what appeared to be left bundle branch block at baseline, with possible ST segment changes after induction. Due to her abnormal reaction to the induction and subsequent treatment for hypotension, an echocardiogram was performed. The patient was found to have an ejection fraction of 25%-30%. The anesthetic was uneventful for the remainder of the procedure, and following recovery, the patient was admitted by the heart failure team for further care.

Prioritizing Environmental Chemicals for Obesity and Diabetes Outcomes Research: A Screening Approach Using ToxCast™ High-Throughput Data

BACKGROUND

Diabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program.

OBJECTIVES

Our aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data.

METHODS

We identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and β cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest.

DISCUSSION

The results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform.

CONCLUSIONS

More research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses.

CITATION

Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141-1154; http://dx.doi.org/10.1289/ehp.1510456.

Gender differences in cancer susceptibility: role of oxidative stress

Cancer is a leading cause of death worldwide and environmental factors, including chemicals, have been suggested as major etiological incitements. Cancer statistics indicates that men get more cancer than women. However, differences in the known risk factors including life style or occupational exposure only offer partial explanation. Using a text mining tool, we have investigated the scientific literature concerning male- and female-specific rat carcinogens that induced tumors only in one gender in NTP 2-year cancer bioassay. Our evaluation shows that oxidative stress, although frequently reported for both male- and female-specific rat carcinogens, was mentioned significantly more in literature concerning male-specific rat carcinogens. Literature analysis of testosterone and estradiol showed the same pattern. Tox21 high-throughput assay results, although showing only weak association of oxidative stress-related processes for male- and female-specific rat carcinogens, provide additional support. We also analyzed the literature concerning 26 established human carcinogens (IARC group 1). Oxidative stress was more frequently reported for the majority of these carcinogens, and the Tox21 data resembled that of male-specific rat carcinogens. Thus, our data, based on about 600000 scientific abstracts and Tox21 screening assays, suggest a link between male-specific carcinogens, testosterone and oxidative stress. This implies that a different cellular response to oxidative stress in men and women may be a critical factor in explaining the greater cancer susceptibility observed in men. Although the IARC carcinogens are classified as human carcinogens, their classification largely based on epidemiological evidence from male cohorts, which raises the question whether carcinogen classifications should be gender specific.