Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.

Utility of in vivo metabolomics to support read-across for UVCB substances under REACH

Structure-based grouping of chemicals for targeted testing and read-across is an efficient way to reduce resources and animal usage. For substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs), structure-based grouping is virtually impossible. Biology-based approaches such as metabolomics could provide a solution. Here, 15 steam-cracked distillates, registered in the EU through the Lower Olefins Aromatics Reach Consortium (LOA), as well as six of the major substance constituents, were tested in a 14-day rat oral gavage study, in line with the fundamental elements of the OECD 407 guideline, in combination with plasma metabolomics. Beyond signs of clinical toxicity, reduced body weight (gain), and food consumption, pathological investigations demonstrated the liver, thyroid, kidneys (males only), and hematological system to be the target organs. These targets were confirmed by metabolome pattern recognition, with no additional targets being identified. While classical toxicological parameters did not allow for a clear distinction between the substances, univariate and multivariate statistical analysis of the respective metabolomes allowed for the identification of several subclusters of biologically most similar substances. These groups were partly associated with the dominant (> 50%) constituents of these UVCBs, i.e., indene and dicyclopentadiene. Despite minor differences in clustering results based on the two statistical analyses, a proposal can be made for the grouping of these UVCBs. Both analyses correctly clustered the chemically most similar compounds, increasing the confidence that this biological approach may provide a solution for the grouping of UVCBs.

Influence of pregnancy and non-fasting conditions on the plasma metabolome in a rat prenatal toxicity study

The current parameters for determining maternal toxicity (e.g. clinical signs, food consumption, body weight development) lack specificity and may underestimate the extent of effects of test compounds on the dams. Previous reports have highlighted the use of plasma metabolomics for an improved and mechanism-based identification of maternal toxicity. To establish metabolite profiles of healthy pregnancies and evaluate the influence of food consumption as a confounding factor, metabolite profiling of rat plasma was performed by gas- and liquid-chromatography-tandem mass spectrometry techniques. Metabolite changes in response to pregnancy, food consumption prior to blood sampling (non-fasting) as well as the interaction of both conditions were studied. In dams, both conditions, non-fasting and pregnancy, had a marked influence on the plasma metabolome and resulted in distinct individual patterns of changed metabolites. Non-fasting was characterized by increased plasma concentrations of amino acids and diet related compounds and lower levels of ketone bodies. The metabolic profile of pregnant rats was characterized by lower amino acids and glucose levels and higher concentrations of plasma fatty acids, triglycerides and hormones, capturing the normal biochemical changes undergone during pregnancy. The establishment of metabolic profiles of pregnant non-fasted rats serves as a baseline to create metabolic fingerprints for prenatal and maternal toxicity studies.

Notch signaling in CD66+ cells drives the progression of human cervical cancers

Human epithelial tumor progression and metastasis involve cellular invasion, dissemination in the vasculature, and regrowth at metastatic sites. Notch signaling has been implicated in metastatic progression but its roles have yet to be fully understood. Here we report the important role of Notch signaling in maintaining cells expressing the carcinoembryonic antigen cell adhesion molecule CEACAM (CD66), a known mediator of metastasis. CD66 and Notch1 were studied in clinical specimens and explants of human cervical cancer, including specimens grown in a pathophysiologically relevant murine model. Gene expression profiling of CD66(+) cells from primary tumors showed enhanced features of Notch signaling, metastasis, and stemness. Significant differences were also seen in invasion, colony formation, and tumor forming efficiency between CD66(+) and CD66(-) cancer cells. Notably, CD66(+) cells showed a marked sensitivity to a Notch small molecule inhibitor. In support of studies in established cell lines, we documented the emergence of a tumorigenic CD66(+) cell subset within a metastatic lesion-derived cervical-cancer cell line. Similar to primary cancers, CD66 expression in the cell line was blocked by chemical and genetic inhibitors of ligand-dependent nuclear Notch signaling. Collectively, our work on the oncogenic properties of CD66(+) cells in epithelial cancers provides insights into the nature of tumor progression and offers a mechanistic rationale to inhibit the Notch signaling pathway as a generalized therapeutic strategy to treat metastatic cancers.

The role of Notch signaling in human cervical cancer: implications for solid tumors

The detection of intracellular forms of Notch1 in human cervical cancers more than a decade ago prompted an investigation into the possible role of this pathway in driving these cancers. These tumors are consistently characterized by features of deregulated ligand-dependent signaling. Although Notch signaling complements the function of papillomavirus oncogenes in transformation assays of human keratinocytes, there are dose-dependent effects, which inhibit growth of established cervical cancer cell lines. Two pro-oncogenic effector mechanisms that have been suggested to operate in this context by Notch signaling are the activation of PI3K/Akt pathway and the upregulation of c-Myc. Collectively, there is a complex interplay between Notch signaling and papillomaviruses in the context of cervical carcinogenesis. Better animal model systems and identification of human cervical cancer stem cells should help clarify the possible stage specific and pleiotropic effects and regulation of Notch signaling.