3Rs-friendly approach to exogenous metabolic activation that supports high-throughput genetic toxicology testing

Identification of environmental chemicals that activate p53 signaling after in vitro metabolic activation

Currently, approximately 80,000 chemicals are used in commerce. Most have little-to-no toxicity information. The U.S. Toxicology in the 21st Century (Tox21) program has conducted a battery of in vitro assays using a quantitative high-throughput screening (qHTS) platform to gain toxicity information on environmental chemicals. Due to technical challenges, standard methods for providing xenobiotic metabolism could not be applied to qHTS assays. To address this limitation, we screened the Tox21 10,000-compound (10K) library, with concentrations ranging from 2.8 nM to 92 µM, using a p53 beta-lactamase reporter gene assay (p53-bla) alone or with rat liver microsomes (RLM) or human liver microsomes (HLM) supplemented with NADPH, to identify compounds that induce p53 signaling after biotransformation. Two hundred and seventy-eight compounds were identified as active under any of these three conditions. Of these 278 compounds, 73 gave more potent responses in the p53-bla assay with RLM, and 2 were more potent in the p53-bla assay with HLM compared with the responses they generated in the p53-bla assay without microsomes. To confirm the role of metabolism in the differential responses, we re-tested these 75 compounds in the absence of NADPH or with heat-attenuated microsomes. Forty-four compounds treated with RLM, but none with HLM, became less potent under these conditions, confirming the role of RLM in metabolic activation. Further evidence of biotransformation was obtained by measuring the half-life of the parent compounds in the presence of microsomes. Together, the data support the use of RLM in qHTS for identifying chemicals requiring biotransformation to induce biological responses.

Biomarkers of DNA damage response improve in vitro micronucleus assays by revealing genotoxic mode of action and reducing the occurrence of irrelevant positive results

We have previously described two flow cytometry-based in vitro genotoxicity tests: micronucleus (MN) scoring (MicroFlow®) and a multiplexed DNA damage response biomarker assay (MultiFlow®). Here, we describe a strategy for combining the assays in order to efficiently supplement MN analyses with a panel of biomarkers that comment on cytotoxicity (i.e. relative nuclei count, relative increased nuclei count, cleaved PARP-positive chromatin and ethidium monoazide-positive chromatin) and genotoxic mode of action (MoA; i.e. γH2AX, phospho-histone H3, p53 activation and polyploidy). For these experiments, human TK6 cells were exposed to each of 32 well-studied reference chemicals in 96-well plates for 24 continuous hours. The test chemicals were evaluated over a range of concentrations in the presence and absence of a rat liver S9-based metabolic activation system. MultiFlow assay data were acquired at 4 and 24 h, and micronuclei were scored at 24 h. Testing 32 chemicals in two metabolic activation arms translated into 64 a priori calls: 42 genotoxicants and 22 non-genotoxicants. The MN assay showed high sensitivity and moderate specificity (90% and 68%, respectively). When a genotoxic call required significant MN and MultiFlow responses, specificity increased to 95% without adversely affecting sensitivity. The dose-response data were analysed with PROAST Benchmark Dose (BMD) software in order to calculate potency metrics for each endpoint, and ToxPi software was used to synthesise the resulting lower and upper bound 90% confidence intervals into visual profiles. The BMD/ToxPi combination was found to represent a powerful strategy for synthesising multiple BMD confidence intervals, as the software output provided MoA information as well as insights into genotoxic potency.

Oncoimmunology Meets Organs-on-Chip

Oncoimmunology represents a biomedical research discipline coined to study the roles of immune system in cancer progression with the aim of discovering novel strategies to arm it against the malignancy. Infiltration of immune cells within the tumor microenvironment is an early event that results in the establishment of a dynamic cross-talk. Here, immune cells sense antigenic cues to mount a specific anti-tumor response while cancer cells emanate inhibitory signals to dampen it. Animals models have led to giant steps in this research context, and several tools to investigate the effect of immune infiltration in the tumor microenvironment are currently available. However, the use of animals represents a challenge due to ethical issues and long duration of experiments. Organs-on-chip are innovative tools not only to study how cells derived from different organs interact with each other, but also to investigate on the crosstalk between immune cells and different types of cancer cells. In this review, we describe the state-of-the-art of microfluidics and the impact of OOC in the field of oncoimmunology underlining the importance of this system in the advancements on the complexity of tumor microenvironment.

The use of benchmark dose uncertainty measurements for robust comparative potency analyses

The Benchmark Dose (BMD) method is the favored approach for quantitative dose-response analysis where uncertainty measurements are delineated between the upper (BMDU) and lower (BMDL) confidence bounds, or confidence intervals (CIs). Little has been published on the accurate interpretation of uncertainty measurements for potency comparative analyses between different test conditions. We highlight this by revisiting a previously published comparative in vitro genotoxicity dataset for human lymphoblastoid TK6 cells that were exposed to each of 10 clastogens in the presence and absence (+/-) of low concentration (0.25%) S9, and scored for p53, γH2AX and Relative Nuclei Count (RNC) responses at two timepoints (Tian et al., 2020). The researchers utilized BMD point estimates in potency comparative analysis between S9 treatment conditions. Here we highlight a shortcoming that the use of BMD point estimates can mischaracterize potency differences between systems. We reanalyzed the dose responses by BMD modeling using PROAST v69.1. We used the resulting BMDL and BMDU metrics to calculate "S9 potency ratio confidence intervals" that compare the relative potency of compounds +/- S9 as more statistically robust metrics for comparative potency measurements compared to BMD point estimate ratios. We performed unsupervised hierarchical clustering that identified four S9-dependent groupings: high and low-level potentiation, no effect, and diminution. This work demonstrates the importance of using BMD uncertainty measurements in potency comparative analyses between test conditions. Irrespective of the source of the data, we propose a stepwise approach when performing BMD modeling in comparative potency analyses between test conditions.