Identifying candidate reference chemicals for in vitro testing of the retinoid pathway for predictive developmental toxicity

Baker, Nancy C.; Pierro, Jocylin D.; Taylor, Laura W.; Knudsen, Thomas B.

doi:10.14573/altex.2202231

Cited by 3 publications

(10 citation statements)

References 144 publications

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“…To further support the formation of pAOPs, publicly available databases that describe in vitro assay results of a chemical’s activity against one of the ATRA pathway targets of interest were mined ( Baker et al, 2022 ). Databases mined included Protein Data Bank (PDB) ( Berman et al, 2003 ), ChEMBL ( Gaulton et al, 2017 ), and ToxCast/Tox21 ( Judson et al, 2016 ; Richard et al, 2016 ).…”

Section: Resultsmentioning

confidence: 99%

“…Databases mined included Protein Data Bank (PDB) ( Berman et al, 2003 ), ChEMBL ( Gaulton et al, 2017 ), and ToxCast/Tox21 ( Judson et al, 2016 ; Richard et al, 2016 ). Chemicals with inactivity in the ToxCast and Tox21 assays were excluded from the developed ATRA pathway candidate chemicals ( Baker et al, 2022 ) selected from assays and literature. There were 1188 candidate chemicals ( Baker et al, 2022 ) with activity in one or more ToxCast or Tox21 assays of interest.…”

Section: Resultsmentioning

confidence: 99%

“…Chemicals with inactivity in the ToxCast and Tox21 assays were excluded from the developed ATRA pathway candidate chemicals ( Baker et al, 2022 ) selected from assays and literature. There were 1188 candidate chemicals ( Baker et al, 2022 ) with activity in one or more ToxCast or Tox21 assays of interest. Furthermore, a multi-rule filter was set to limit chemicals with the following qualifying features: DR5 < 20 μM, CYP <10 μM, RAR <10 μM, RXR <10 μM, RSP (Tox21) < 10 μM, and prevalent RDH10 literature.…”

Section: Resultsmentioning

confidence: 99%

“…Twenty-eight of the 48 chemicals found both in ToxRefDB and Tox21 and/or ToxCast were candidate reference chemicals ( Baker et al, 2022 ), but had not previously been noted. This finding provides reason for further exploration of the impact of the other 20 chemicals on the ATRA signaling pathway and skeletal defects.…”

Section: Discussionmentioning

confidence: 99%

“…Our project mined a combined 10 assays ( Table 1 ) from ToxCast and Tox21 ( Chen et al, 2016 ) for chemicals that demonstrated bioactivity for relevant ATRA nodes (RARs, DR5, RXRs, and CYP surrogate biomarker). CYP1A1 and CYP2C8 were selected as CYP surrogate biomarker, due to the absence of CYP26 assays in ToxCast and Tox 21 ( Baker et al, 2022 ). Importantly, both CYP surrogate biomarker’ assays are biochemical.…”

Section: Methodsmentioning

confidence: 99%

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Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

et al. 2022

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All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively. This data model provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

et al. 2022

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Development and validation of CYP26A1 inhibition assay for high‐throughput screening

Sakamuru,

Ma,

Pierro

et al. 2024

Biotechnology Journal

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All‐trans retinoic acid (atRA) is an endogenous ligand of the retinoic acid receptors, which heterodimerize with retinoid X receptors. AtRA is generated in tissues from vitamin A (retinol) metabolism to form a paracrine signal and is locally degraded by cytochrome P450 family 26 (CYP26) enzymes. The CYP26 family consists of three subtypes: A1, B1, and C1, which are differentially expressed during development. This study aims to develop and validate a high throughput screening assay to identify CYP26A1 inhibitors in a cell‐free system using a luminescent P450‐Glo assay technology. The assay performed well with a signal to background ratio of 25.7, a coefficient of variation of 8.9%, and a Z‐factor of 0.7. To validate the assay, we tested a subset of 39 compounds that included known CYP26 inhibitors and retinoids, as well as positive and negative control compounds selected from the literature and/or the ToxCast/Tox21 portfolio. Known CYP26A1 inhibitors were confirmed, and predicted CYP26A1 inhibitors, such as chlorothalonil, prochloraz, and SSR126768, were identified, demonstrating the reliability and robustness of the assay. Given the general importance of atRA as a morphogenetic signal and the localized expression of Cyp26a1 in embryonic tissues, a validated CYP26A1 assay has important implications for evaluating the potential developmental toxicity of chemicals.

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Searching for LINCS to Stress: Using Text Mining to Automate Reference Chemical Curation

Chambers,

Basili,

Word

et al. 2024

Chem. Res. Toxicol.

Self Cite

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Adaptive stress response pathways (SRPs) restore cellular homeostasis following perturbation but may activate terminal outcomes like apoptosis, autophagy, or cellular senescence if disruption exceeds critical thresholds. Because SRPs hold the key to vital cellular tipping points, they are targeted for therapeutic interventions and assessed as biomarkers of toxicity. Hence, we are developing a public database of chemicals that perturb SRPs to enable new data-driven tools to improve public health. Here, we report on the automated text-mining pipeline we used to build and curate the first version of this database. We started with 100 reference SRP chemicals gathered from published biomarker studies to bootstrap the database. Second, we used information retrieval to find co-occurrences of reference chemicals with SRP terms in PubMed abstracts and determined pairwise mutual information thresholds to filter biologically relevant relationships. Third, we applied these thresholds to find 1206 putative SRP perturbagens within thousands of substances in the Library of Integrated Network-Based Cellular Signatures (LINCS). To assign SRP activity to LINCS chemicals, domain experts had to manually review at least three publications for each of 1206 chemicals out of 181,805 total abstracts. To accomplish this efficiently, we implemented a machine learning approach to predict SRP classifications from texts to prioritize abstracts. In 5-fold cross-validation testing with a corpus derived from the 100 reference chemicals, artificial neural networks performed the best (F1-macro = 0.678) and prioritized 2479/181,805 abstracts for expert review, which resulted in 457 chemicals annotated with SRP activities. An independent analysis of enriched mechanisms of action and chemical use class supported the text-mined chemical associations (p < 0.05): heat shock inducers were linked with HSP90 and DNA damage inducers to topoisomerase inhibition. This database will enable novel applications of LINCS data to evaluate SRP activities and to further develop tools for biomedical information extraction from the literature.

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Identifying candidate reference chemicals for in vitro testing of the retinoid pathway for predictive developmental toxicity

Cited by 3 publications

References 144 publications

Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling

Development and validation of CYP26A1 inhibition assay for high‐throughput screening

Searching for LINCS to Stress: Using Text Mining to Automate Reference Chemical Curation

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