The constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are important nuclear receptors involved in the regulation of cellular responses from exposure to many xenobiotics and various physiological processes. Phenobarbital (PB) is a non-genotoxic indirect CAR activator, which induces cytochrome P450 (CYP) and other xenobiotic metabolizing enzymes and is known to produce liver foci/tumors in mice and rats. From literature data, a mode of action (MOA) for PB-induced rodent liver tumor formation was developed. A MOA for PXR activators was not established owing to a lack of suitable data. The key events in the PB-induced liver tumor MOA comprise activation of CAR followed by altered gene expression specific to CAR activation, increased cell proliferation, formation of altered hepatic foci and ultimately the development of liver tumors. Associative events in the MOA include altered epigenetic changes, induction of hepatic CYP2B enzymes, liver hypertrophy and decreased apoptosis; with inhibition of gap junctional intercellular communication being an associative event or modulating factor. The MOA was evaluated using the modified Bradford Hill criteria for causality and other possible MOAs were excluded. While PB produces liver tumors in rodents, important species differences were identified including a lack of cell proliferation in cultured human hepatocytes. The MOA for PB-induced rodent liver tumor formation was considered to be qualitatively not plausible for humans. This conclusion is supported by data from a number of epidemiological studies conducted in human populations chronically exposed to PB in which there is no clear evidence for increased liver tumor risk.

The nuclear receptor family member constitutive activated receptor (CAR) is activated by structurally diverse drugs and environmentally-relevant chemicals leading to transcriptional regulation of genes involved in xenobiotic metabolism and transport. Chronic activation of CAR increases liver cancer incidence in rodents, whereas suppression of CAR can lead to steatosis and insulin insensitivity. Here, analytical methods were developed to screen for chemical treatments in a gene expression compendium that lead to alteration of CAR activity. A gene expression biomarker signature of 83 CAR-dependent genes was identified using microarray profiles from the livers of wild-type and CAR-null mice after exposure to three structurally-diverse CAR activators (CITCO, phenobarbital, TCPOBOP). A rank-based algorithm (Running Fisher’s algorithm (p-value ≤ 10-4)) was used to evaluate the similarity between the CAR biomarker signature and a test set of 28 and 32 comparisons positive or negative, respectively, for CAR activation; the test resulted in a balanced accuracy of 97%. The biomarker signature was used to identify chemicals that activate or suppress CAR in an annotated mouse liver/primary hepatocyte gene expression database of ~1850 comparisons. CAR was activated by 1) activators of the aryl hydrocarbon receptor (AhR) in wild-type but not AhR-null mice, 2) pregnane X receptor (PXR) activators in wild-type and to lesser extents in PXR-null mice, and 3) activators of PPARα in wild-type and PPARα-null mice. CAR was consistently activated by five conazole fungicides and four perfluorinated compounds. Comparison of effects in wild-type and CAR-null mice showed that the fungicide propiconazole increased liver weight and hepatocyte proliferation in a CAR-dependent manner, whereas the perfluorinated compound perfluorooctanoic acid (PFOA) increased these endpoints in a CAR-independent manner. A number of compounds suppressed CAR coincident with increases in markers of inflammation including acetaminophen, concanavalin A, lipopolysaccharide, and 300 nm silica particles. In conclusion, we have shown that a CAR biomarker signature coupled with a rank-based similarity method accurately predicts CAR activation. This analytical approach, when applied to a gene expression compendium, increased the universe of known chemicals that directly or indirectly activate CAR, highlighting the promiscuous nature of CAR activation and signaling through activation of other xenobiotic-activated receptors.

Weight of evidence (WoE) approaches are recommended for interpreting various toxicological data, but few systematic and transparent procedures exist. A hypothesis-based WoE framework was recently published focusing on the U.S. EPA's Tier 1 Endocrine Screening Battery (ESB) as an example. The framework recommends weighting each experimental endpoint according to its relevance for deciding eight hypotheses addressed by the ESB. Here we present detailed rationale for weighting the ESB endpoints according to three rank ordered categories and an interpretive process for using the rankings to reach WoE determinations. Rank 1 was assigned to in vivo endpoints that characterize the fundamental physiological actions for androgen, estrogen, and thyroid activities. Rank 1 endpoints are specific and sensitive for the hypothesis, interpretable without ancillary data, and rarely confounded by artifacts or nonspecific activity. Rank 2 endpoints are specific and interpretable for the hypothesis but less informative than Rank 1, often due to oversensitivity, inclusion of narrowly context-dependent components of the hormonal system (e.g., in vitro endpoints), or confounding by nonspecific activity. Rank 3 endpoints are relevant for the hypothesis but only corroborative of Ranks 1 and 2 endpoints. Rank 3 includes many apical in vivo endpoints that can be affected by systemic toxicity and nonhormonal activity. Although these relevance weight rankings (W REL ) necessarily involve professional judgment, their a priori derivation enhances transparency and renders WoE determinations amenable to methodological scrutiny according to basic scientific premises, characteristics that cannot be assured by processes in which the rationale for decisions is provided post hoc.