Using Short-term In Life Transcriptomic Studies to More Effectively Assess Dose Responses and Modes of Action

In the past, dose responses results from in life toxicology studies were used to estimate no observed effect levels (NOELs) and more recently benchmark doses (BMDs). These observational studies of apical endpoints were frequently followed up by mechanistic studies both in intact animals and in in vitro models to determine modes of action (MOAs) and lend support to using either linear or threshold-based low dose extrapolations.  Over the past two decades, gene expression analysis (transcriptomics) has provided new tools to assess no observed transcriptional effect levels – NOTELs [1], gene expression BMDs [2] and MOAs by examining the dose response of enrichment of various cellular/biochemical pathways among the differentially expressed genes [3-5]. 

Toxicology testing both for dose response assessment and to a lesser extent MOA is moving away from reliance on conventional in these life studies [6]. Transcriptomics, measuring the changes in expression of some or all transcribed genes, is expected to play an important role in this transition, due to its ability to capture molecular changes that relate to organism-level apical effects. There is a growing body of evidence showing the quantitative correspondence of the dose level at which transcriptomic changes are detected and the level at which apical effects occur [7, 8]. Importantly, studies have also found that apical effects—such as tumor incidence—observable in longer-term in life studies are preceded by transcriptomic changes at shorter-term exposures and the effect levels of the apical responses and the shorter-term gene expression changes were similar. As such, there is an opportunity for the toxicity testing community to embrace short term in vivo studies to approximate points-of-departure obtained with more traditional testing. 

Molecular endpoints, including gene expression, are becoming increasingly important for understanding toxicity.

In addition to determining effect levels, short-term in life transcriptomics will be valuable in informing MOA. With several compounds—formaldehyde [9, 10], isoprene [11] and styrene [12, 13]—transcriptional dose response behavior was examined at various time points – from as early as 2 days (with formaldehyde and  styrene) through 2 years (styrene).  For the earlier times, the dose responses for apical and transcriptional responses were similar and pathway enrichment was generally consistent with other information on compound MOA although there were some surprises.  In the lung styrene had enrichment for cell cycle pathways but not cytotoxicity [12] and methylene chloride had enrichment for organelle biogenesis, TCA cycle, and respiratory electron transport indicating primary effects through a metabolite, carbon monoxide [14].  With these two compounds, the transcriptional MOAs supported a threshold model rather than a linear low dose model.  

Moving to the future where we are much less reliant on detailed, multi-endpoint toxicity evaluations, these short-term in life transcriptomic studies will be an important linchpin allowing comparisons across MOA-oriented in life studies and emerging high throughput gene expression studies in cell lines and primary cells.  ScitoVation offers clients a one-stop shop for the conduct and interpretation of these short-term in life transcriptomic studies.  ScitoVation staff will analyze gene expression BMDs, conduct MOA analysis, and develop detailed sponsor reports. The studies will be based on the protocol developed by the National Toxicology Program (NTP) enabling comparisons with other studies conducted by third parties and possibly acceptance by stakeholders. ScitoVation offer a seamless collaboration to our clients and efficiency reflected by very competitive pricing.  

Contact Dr. Jean Orelien at jorelien@scitovation.com  for more information about these offerings. 

1. Thomas, R.S. et al. (2009) Use of short-term transcriptional profiles to assess the long-term cancer-related safety of environmental and industrial chemicals. Toxicol Sci 112 (2), 311-21. 

2. Thomas, R.S. et al. (2007) A method to integrate benchmark dose estimates with genomic data to assess the functional effects of chemical exposure. Toxicol Sci 98 (1), 240-8. 

3. Andersen, M.E. et al. (2018) Application of transcriptomic data, visualization tools and bioinformatics resources for informing mode of action. . Current Opinions in Toxicology 9, 21-27. 

4. McMullen, P.D. et al. (2014) A map of the PPARalpha transcription regulatory network for primary human hepatocytes. Chem Biol Interact 209, 14-24. 

5. McMullen, P.D. et al. (2020) Identifying qualitative differences in PPARalpha signaling networks in human and rat hepatocytes and their significance for next generation chemical risk assessment methods. Toxicol In Vitro 64, 104463. 

6. Andersen, M.E. et al. (2019) Developing context appropriate toxicity testing approaches using new alternative methods (NAMs). ALTEX 36 (4), 523-534. 

7. Thomas, R.S. et al. (2013) Temporal concordance between apical and transcriptional points of departure for chemical risk assessment. Toxicol Sci 134 (1), 180-94. 

8. National Toxicology Program (2018) NTP Research Report on National Toxicology Program Approach to Genomic Dose-Response Modeling. NTP RR 5. 

9. Andersen, M.E. et al. (2008) Genomic signatures and dose-dependent transitions in nasal epithelial responses to inhaled formaldehyde in the rat. Toxicol Sci 105 (2), 368-83. 

10. Andersen, M.E. et al. (2010) Formaldehyde: integrating dosimetry, cytotoxicity, and genomics to understand dose-dependent transitions for an endogenous compound. Toxicol Sci 118 (2), 716-31. 

11. Thomas, R.S. et al. (2013) Cross-species transcriptomic analysis of mouse and rat lung exposed to chloroprene. Toxicol Sci 131 (2), 629-40. 

12. Andersen, M.E. et al. (2017) Assessing molecular initiating events (MIEs), key events (KEs) and modulating factors (MFs) for styrene responses in mouse lungs using whole genome gene expression profiling following 1-day and multi-week exposures. Toxicol Appl Pharmacol 335, 28-40. 

13. Andersen, M.E. et al. (2018) Strain-related differences in mouse lung gene expression over a two-year period of inhalation exposure to styrene: Relevance to human risk assessment. Regul Toxicol Pharmacol 96, 153-166. 

14. Andersen, M.E. et al. (2017) Combining transcriptomics and PBPK modeling indicates a primary role of hypoxia and altered circadian signaling in dichloromethane carcinogenicity in mouse lung and liver. Toxicol Appl Pharmacol 332, 149-158. 

Featured image Courtesy: National Human Genome Research Institute. http://www.genome.gov