October 18, 2021
Our first speaker, Stephen Ferguson, Ph.D., will discuss efforts by the Division of the National Toxicology Program (DNTP) to develop and qualify in vitro toxicology screening models using 3D spheroid cultures of human hepatocytes entitled: “High-throughput transcriptomics with physiologically-relevant in vitro models to predict human hepatotoxicity with environmental chemicals.” This presentation will be followed by a presentation from Ella Atlas, Ph.D. from Health Canada who will describe evaluations of 28 PFAS using spheroid hepatocyte culture models and high-throughput transcriptomics entitled: “Primary human liver cell spheroids as a platform for evaluating liver toxicity and potency of per- and polyfluoroalkyl substances (PFAS).”
What you’ll learn:
- 3D spheroid in vitro liver models highly proficient for xenobiotic metabolism and bioactivation
- Hallmarks of human and rodent hepatocellular function effectively modeled with hepatocyte 3D spheroid cultures
- High-throughput transcriptomics paired with 3D spheroid exposures an effective tool for quantitatively identifying human liver injury compounds
- PFAS screening with 3D spheroid cultures successful, revealing:
- Potency estimates for PFAS-associated hepatic receptor pathways (PPARα, CAR/PXR)
- Effective modeling of established chain-length dependences of biological activity across PFAS structures
- Extrapolation from in vitro assay data to human toxicokinetic models enabling translation of observed findings to human hazard contextualization
About our Speakers:
Dr. Stephen Ferguson:
Dr. Ferguson is an Investigator within the National Toxicology Program Division (DNTP) of the National Institute of Environmental Health Sciences (NIEHS). Ferguson serves multiple roles within DNTP that include: 1) leading research efforts to develop, qualify, and apply complex in vitro model systems, 2) integrating informative assay platforms (e.g., high throughput transcriptomics, imaging, cellular health/toxicity), and 3) applying innovative strategies to assess the human toxicity potential of DNTP test chemicals (e.g., PFAS, botanicals, polycyclic aromatic hydrocarbons, and other environmental chemicals). Prior to joining the NTP, Ferguson led the ADME/Tox R&D program of Life Technologies (now Thermo-Fisher) where he and his team developed predictive in vitro liver models and assay approaches for estimation of human drug metabolism, transport, liver toxicity, and drug-drug interactions. Steve received his BS and PhD in chemistry from NC State University with a focus on molecular biology and the roles of transition metals within biological systems, and currently serves as adjunct faculty to the Curriculum in Toxicology at the UNC-CH.
Dr. Ella Atlas:
The research conducted in Dr. Atlas’ laboratory comprises two major projects. To develop in vitro models to investigate the effects of chemicals on fat cell formation, adipogenesis, and to investigate the effects of these chemicals on the phenotype of the mature fat cells. The second project is focused on the carcinogenic effect of chemicals on the mammary gland in 3D models, using mammary epithelial cells.
Ella Atlas did her studies and postdoctoral training at Queen’s University and Lawrence Berkeley National Laboratories, UC Berkeley prior to her joining Health Canada as a research scientist. Her research focuses the development of in vitro models to investigate metabolic disruption of chemicals. In addition, she investigates the possible role of environmental pollutants on breast cancer initiation and progression.
Abstract:
Advances in biomedical sciences are rapidly evolving the available suite of tools and approaches for toxicology research. Recent progress with three-dimensional (3D) culture systems in 96- and 384-well formats now enable toxicology screening with superior modeling of tissue functionality hallmarks and pathophysiological action for specific phenotypes. In this presentation, we describe recent progress in the development, qualification, and application of 3D spheroid screening models for human and rodent liver. These models rival the metabolic proficiency of human liver while maintaining their dynamic sensitivity to liver enzyme inducers for major hepatic receptor signaling pathways (e.g., AhR, CAR, PXR, PPAR). Integration of these models with high-throughput transcriptomics has revealed superior capacity for modeling metabolically-activated human hepatotoxicity (e.g., valproic acid, cyclophosphamide) relative to differentiated 2D hepatocyte culture models. This transcriptomics platform has been used in combination with benchmark dose analysis to quantitatively estimate the human internal exposure levels of liver injury in an unsupervised screening approach that enables mechanistic resolution of the firing sequences of biological response along a potency-aligned framework. These models are now beginning to be deployed for environmental chemicals, and Ella Atlas will describe 2 recent publications assessing PFAS with these types of model systems. In these studies, primary human hepatocyte spheroids were used to evaluate 28 PFAS over time and concentration-response using gene expression profiling to estimate the potential for human liver toxicity. Further, using benchmark concentration analysis of evaluated transcriptomic points of departures, rankings for PFAS potencies were revealed for human health risk assessment.
About ScitoVation:
ScitoVation helps clients assess chemical compound safety using innovative science, next-generation technology, and professional expertise. ScitoVation is known for partnership, flexibility, and proven success in its work to develop safer and more effective pharmaceuticals, food ingredients, agricultural chemicals, commodity chemicals and consumer products. A spin-off of the former The CIIT and The Hammer Institutes for Chemical & Drug Safety Sciences, ScitoVation is an industry leader of New Approach Methods (NAMS) for chemical/drug discovery & development in the rapidly evolving global regulatory landscape.
Tags: Hepatocytes, PFAS, PHH, spheroids, toxicogenomics, toxicokinetic models, transcriptomics