Challenges integrating skin sensitization data for assessment of difficult to test substances

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Allison Greminger , Joseph Frasca, Katy Goyak, Colin North
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Abstract

Difficult to test substances, including poorly soluble, mildly irritating, or UVCBs (unknown or variable composition complex reaction products or biological materials), producing weak or borderline in vivo results, face additional challenges in in vitro assays that often necessitate data integration in a weight of evidence (WOE) approach to inform skin sensitization potential. Here we present several case studies on difficult to test substances and highlight the utility of the toxicological priority index (ToxPi) as a data visualization tool to compare skin sensitization biological activity. The case study test substances represent two poorly soluble substances, tetrakis (2-ethylbutyl) orthosilicate and decyl palmitate, and two UVCB substances, alkylated anisole and hydrazinecarboximidamide, 2-[(2-hydroxyphenyl)methylene]-, reaction products with 2 undecanone. Data from key events within the skin sensitization adverse outcome pathway were gathered from publicly available sources or specifically generated. Incorporating the data for these case study test substances as well as data on chemicals of a known sensitization class (sensitizer, irritating non-sensitizer, and non-sensitizer) into ToxPi produced biological activity profiles which were grouped using unsupervised hierarchical clustering. Three of the case study test substances concluded to lack skin sensitization potential by traditional WOE produced biological activity profiles most consistent with non-sensi­tizing substances, whereas the prediction was less definitive for a substance considered positive by traditional WOE. Visualizing the data using bioactivity profiles can provide further support for WOE conclusions in certain circumstances but is unlikely to replace WOE as a stand-alone prediction due to limitations of the method including the impact of missing data points.


Plain language summary
Non-animal test methods to detect chemicals that cause skin allergies are accepted alternatives to animal testing for this purpose. However, some chemicals are difficult to test using these methods, e.g., substances that cause skin irritation, are not water soluble or are mixtures of different compo­nents. We compiled existing and new data on how four such chemicals activate key elements of the biological pathway leading to allergic skin reactions and compared the resulting patterns with respective patterns of many chemicals confirmed to cause skin allergy, skin irritation or neither. The patterns were visualized and analyzed with a computer software tool. The tool confirmed that three substances were non-sensitizers but did not confirm that the fourth substance was a skin sensitizer as predicted by the standard assessment. This approach, which incorporates all available data types into the assessment of difficult to test chemicals, may further reduce unnecessary animal testing.

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How to Cite
Greminger, A., Frasca, J., Goyak, K. and North, C. (2024) “Challenges integrating skin sensitization data for assessment of difficult to test substances”, ALTEX - Alternatives to animal experimentation, 41(1), pp. 104–118. doi: 10.14573/altex.2201122.
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References

Adenuga, D., Woolhiser, M. R., Gollapudi, B. B. et al. (2012). Differential gene expression responses distinguish contact and respiratory sensitizers and nonsensitizing irritants in the local lymph node assay. Toxicol Sci 126, 413-425. doi:10.1093/toxsci/kfs071

Anderson, S. E., Siegel, P. D. and Meade, B. J. (2011). The LLNA: A brief review of recent advances and limitations. J Allergy 2011, 424203. doi:10.1155/2011/424203

Ashikaga, T., Yoshida, Y., Hirota, M. et al. (2006). Development of an in vitro skin sensitization test using human cell lines: The human cell line activation test (h-CLAT): I. Optimization of the h-CLAT protocol. Toxicol In Vitro 20, 767-773. doi:10.1016/j.tiv.2005.10.012

Basketter, D. A., Gerberick, G. F. and Kimber, I. (1998). Strategies for identifying false positive responses in predictive skin sensitization tests. Food Chem Toxicol 36, 327-333. doi:10.1016/s0278-6915(97)00158-0

Bergal, M., Puginier, M., Gerbeix, C. et al. (2020). In vitro testing strategy for assessing the skin sensitizing potential of “difficult to test” cosmetic ingredients. Toxicol In Vitro 65, 104781. doi:10.1016/j.tiv.2020.104781

Buehler, E. V. (1965). Delayed contact hypersensitivity in the guinea pig. Arch Dermatol 91, 171-177. doi:10.1001/archderm.1965.01600080079017

Cortes, C. and Vapnik, V. (1995). Support-vector networks. Machine Learning 20, 273-297. doi:10.1007/BF00994018

Dimitrov, S., Detroyer, A., Piroird, C. et al. (2016a). Accounting for data variability, a key factor in in vivo/in vitro relationships: Application to the skin sensitization potency (in vivo LLNA versus in vitro DPRA) example. J Appl Toxicol 36, 1568-1578. doi:10.1002/jat.3318

Dimitrov, S. D., Diderich, R., Sobanski, T. et al. (2016b). QSAR toolbox – Workflow and major functionalities. SAR QSAR Environ Res 27, 203-219. doi:10.1080/1062936X.2015.1136680

EC – European Commission (2022). Proposal for a regulation amending regulation (EC) No 1272/2008 on classification, labelling and packaging of substances and mixtures. D. Environment.

ECETOC – European Centre for Ecotoxicology and Toxicology of Chemicals (2003). Technical Report No. 87: Contact sensitisation: Classification according to potency. https://www.ecetoc.org/wp-content/uploads/2014/08/ecetoc-tr-087.pdf

ECHA – European Chemicals Agency (2017a). Guidance on information requirements and chemical safety assessment – Chapter R.7A – Endpoint specific guidance. Version 6.0. doi:10.2823/337352

ECHA (2017b). Guidance on the application of the CLP criteria. Guidance to Regulation (EC) No 1272/2008 on classification, labelling, and packaging (CLP) of substances and mixtures. Version 5.0. ECHA-17-g-21-en. doi:10.2823/124801

EURL-ECVAM (2012). Direct peptide reactivity assay (DPRA) ECVAM validation study report. https://tsar.jrc.ec.europa.eu/system/files/published/dpra%20validation%20study%20report.pdf (accessed 13.08.2021)

EURL ECVAM Scientific Advisory Committee (2021). ESAC opinion on the scientific validity of the GARDskin and GARDpotency test methods. Publications Office of the European Union, Luxembourg, 2021. ISBN 978-92-76-40345-6. doi:10.2760/626728

Forreryd, A., Zeller, K. S., Lindberg, T. et al. (2016). From genome-wide arrays to tailor-made biomarker readout-progress towards routine analysis of skin sensitizing chemicals with GARD. Toxicol In Vitro 37, 178-188. doi:10.1016/j.tiv.2016.09.013

Gerberick, G. F. (2016). The use of peptide reactivity assays for skin sensitisation hazard identification and risk assessment. Altern Lab Anim 44, 437-442. doi:10.1177/026119291604400506

Gilmour, N., Kimber, I., Williams, J. et al. (2019). Skin sensitization: Uncertainties, challenges, and opportunities for improved risk assessment. Contact Dermatitis 80, 195-200. doi:10.1111/cod.13167

Grimm, F. A., Iwata, Y., Sirenko, O. et al. (2016). A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives. Green Chem 18, 4407-4419. doi:10.1039/c6gc01147k

Grimm, F. A., House, J. S., Wilson, M. R. et al. (2019). Multi-dimensional in vitro bioactivity profiling for grouping of glycol ethers. Regul Toxicol Pharmacol 101, 91-102. doi:10.1016/j.yrtph.2018.11.011

Hoffmann, S. (2015). LLNA variability: An essential ingredient for a comprehensive assessment of non-animal skin sensitization test methods and strategies. ALTEX 32, 379-383. doi:10.14573/altex.1505051

Hoffmann, S., Kleinstreuer, N., Alépée, N. et al. (2018). Non-animal methods to predict skin sensitization (I): The cosmetics Europe database. Crit Rev Toxicol 48, 344-358. doi:10.1080/10408444.2018.1429385

Ivanova, H., Dimitrova, G., Kuseva, C. et al. (2020). Modeling hazard assessment of chemicals based on adducts formation. I. A basis for inclusion of kinetic factors in simulating skin sensitization. Comput Toxicol 15, 100130. doi:10.1016/j.comtox.2020.100130

Johansson, H., Lindstedt, M., Albrekt, A. S. et al. (2011). A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests. BMC Genomics 12, 399. doi:10.1186/1471-2164-12-399

Johansson, H., Albrekt, A.-S., Borrebaeck, C. A. et al. (2013). The GARD assay for assessment of chemical skin sensitizers. Toxicol In Vitro 27, 1163-1169. doi:10.1016/j.tiv.2012.05.019

Johansson, H., Rydnert, F., Kühnl, J. et al. (2014). Genomic allergen rapid detection in-house validation – A proof of concept. Toxicol Sci 139, 362-370. doi:10.1093/toxsci/kfu046

Johansson, H., Gradin, R., Forreryd, A. et al. (2017). Evaluation of the GARD assay in a blind cosmetics Europe study. ALTEX 34, 515-523. doi:10.14573/altex.1701121

Johansson, H., Gradin, R., Johansson, A. et al. (2019). Validation of the GARD™skin assay for assessment of chemical skin sensitizers: Ring trial results of predictive performance and reproducibility. Toxicol Sci 170, 374-381. doi:10.1093/toxsci/kfz108

Johnson, W., Heldreth, B., Bergfeld, W. F. et al. (2011). Final report of the cosmetic ingredient review expert panel on the safety assessment of pelargonic acid (nonanoic acid) and nonanoate esters. Int J Toxicol 30, Suppl, 228S-269S. doi:10.1177/1091581811428980

Kimber, I., Dearman, R. J., Scholes, E. W. et al. (1994). The local lymph node assay: Developments and applications. Toxicology 93, 13-31. doi:10.1016/0300-483x(94)90193-7

Kimber, I., Hilton, J., Dearman, R. J. et al. (1995). An international evaluation of the murine local lymph node assay and comparison of modified procedures. Toxicology 103, 63-73. doi:10.1016/0300-483x(95)03114-u

Kleinstreuer, N. C., Hoffmann, S., Alépée, N. et al. (2018). Non-animal methods to predict skin sensitization (II): An assessment of defined approaches*. Crit Rev Toxicol 48, 359-374. doi:10.1080/10408444.2018.1429386

Kolle, S. N., Basketter, D. A., Casati, S. et al. (2013). Performance standards and alternative assays: Practical insights from skin sensitization. Regul Toxicol Pharmacol 65, 278-285. doi:10.1016/j.yrtph.2012.12.006

LoPachin, R. M., Gavin, T., DeCaprio, A. et al. (2012). Application of the hard and soft, acids and bases (HSAB) theory to toxicant-target interactions. Chem Res Toxicol 25, 239-251. doi:10.1021/tx2003257

LoPachin, R. M., Geohagen, B. C. and Nordstroem, L. U. (2019). Mechanisms of soft and hard electrophile toxicities. Toxicology 418, 62-69. doi:10.1016/j.tox.2019.02.005

Maeda, Y. and Takeyoshi, M. (2019). Proposal of GHS sub-categorization criteria for LLNA: BrdU-ELISA (OECD TG442B). Regul Toxicol Pharmacol 107, 104409. doi:10.1016/j.yrtph.2019.104409

Magnusson, B. and Kligman, A. M. (1969). The identification of contact allergens by animal assay. The guinea pig maximization test. J Invest Dermatol 52, 268-276. doi:10.1038/jid.1969.42

Marvel, S. W., To, K., Grimm, F. A. et al. (2018). ToxPi graphical user interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models. BMC Bioinformatics 19, 80. doi:10.1186/s12859-018-2089-2

McEwen-Smith, R. M., Salio, M. and Cerundolo, V. (2015). CD1d-dependent endogenous and exogenous lipid antigen presentation. Curr Op Immunol 34, 116-125. doi:10.1016/j.coi.2015.03.004

McNamee, P. M., Api, A. M., Basketter, D. A. et al. (2008). A review of critical factors in the conduct and interpretation of the human repeat insult patch test. Regul Toxicol Pharmacol 52, 24-34. doi:10.1016/j.yrtph.2007.10.019

Mekenyan, O., Roberts, D. W. and Karcher, W. (1997). Molecular orbital parameters as predictors of skin sensitization potential of halo- and pseudohalobenzenes acting as SNAr electrophiles. Chem Res Toxicol 10, 994-1000. doi:10.1021/tx960104g

Montelius, J., Wahlkvist, H., Boman, A. et al. (1998). Murine local lymph node assay for predictive testing of allergenicity: Two irritants caused significant proliferation. Acta Derm Venereol 78, 433-437. doi:10.1080/000155598442728

Natsch, A., Bauch, C., Foertsch, L. et al. (2011). The intra- and inter-laboratory reproducibility and predictivity of the Keratinosens assay to predict skin sensitizers in vitro: Results of a ring-study in five laboratories. Toxicol In Vitro 25, 733-744. doi:10.1016/j.tiv.2010.12.014

Natsch, A., Kleinstreuer, N. and Asturiol, D. (2023). Reduced specificity for the local lymph node assay for lipophilic chemicals: Implications for the validation of new approach methods for skin sensitization. Regul Toxicol Pharmacol 138, 105333. doi:10.1016/j.yrtph.2023.105333

NRC – National Research Council (2011). Guide for Care and Use of Laboratory Animals. 8th edition. National Academies Press. https://grants.nih.gov/grants/olaw/guide-for-the-care-and-use-of-laboratory-animals.pdf

OECD (2002). Guidance Document on Aquatic Toxicity Testing of Difficult Substances and Mixtures. OECD Publishing, Paris: doi:10.1787/9789264078406-en

OECD (2010). Test N. 429: Skin Sensitisation: Local Lymph Node Assay. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi:10.1787/9789264071100-en

OECD (2018). Test No. 442B: Skin Sensitization: Local Lymph Node Assay: BrdU-ELISA or –FCM. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi:10.1787/9789264090996-en

OECD (2021). Guideline No. 497: Defined Approaches on Skin Sensitisation. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi:10.1787/b92879a4-en

OECD (2022). Test no. 442D: In Vitro Skin Sensitisation: ARE-Nrf2 Luciferase Test Method. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi:10.1787/9789264229822-en

OECD (2023a). Test No. 442C: In Chemico Skin Sensitisation: Assays addressing the Adverse Outcome Pathway key event on covalent binding to proteins. OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi:10.1787/9789264229709-en

OECD (2023b). Test No. 442E: In Vitro Skin Sensitisation: In Vitro Skin Sensitisation assays addressing the Key Event on activation of dendritic cells on the Adverse Outcome Pathway for Skin Sensitisation: OECD Guidelines for the Testing of Chemicals, Section 4. OECD Publishing, Paris. doi:10.1787/9789264264359-en

Ouyang, Q., Wang, L., Mu, Y. et al. (2014). Modeling skin sensitization potential of mechanistically hard-to-be-classified aniline and phenol compounds with quantum mechanistic properties. BMC Pharmacol Toxicol 15, 76. doi:10.1186/2050-6511-15-76

Patlewicz, G., Kuseva, C., Mehmed, A. et al. (2014). Times-SS – Recent refinements resulting from an industrial skin sensitisation consortium. SAR QSAR Environ Res 25, 367-391. doi:10.1080/1062936X.2014.900520

Ramirez, T., Mehling, A., Kolle, S. N. et al. (2014). Lusens: A keratinocyte based ARE reporter gene assay for use in integrated testing strategies for skin sensitization hazard identification. Toxicol In Vitro 28, 1482-1497. doi:10.1016/j.tiv.2014.08.002

Reif, D. M., Martin, M. T., Tan, S. W. et al. (2010). Endocrine profiling and prioritization of environmental chemicals using toxcast data. Environ Health Perspect 118, 1714-1720. doi:10.1289/ehp.1002180

Roberts, D. W. (2018). Is a combination of assays really needed for non-animal prediction of skin sensitization potential? Performance of the GARD™ (genomic allergen rapid detection) assay in comparison with OECD guideline assays alone and in combination. Regul Toxicol Pharmacol 98, 155-160. doi:10.1016/j.yrtph.2018.07.014

Strickland, J., Zang, Q., Kleinstreuer, N. et al. (2016). Integrated decision strategies for skin sensitization hazard. J Appl Toxicol 36, 1150-1162. doi:10.1002/jat.3281

Takenouchi, O., Miyazawa, M., Saito, K. et al. (2013). Predictive performance of the human cell line activation test (h-CLAT) for lipophilic chemicals with high octanol-water partition coefficients. J Toxicol Sci 38, 599-609. doi:10.2131/jts.38.599

Tilley, S. K., Reif, D. M. and Fry, R. C. (2017). Incorporating ToxCast and Tox21 datasets to rank biological activity of chemicals at superfund sites in North Carolina. Environ Int 101, 19-26. doi:10.1016/j.envint.2016.10.006

To, K. T., Fry, R. C. and Reif, D. M. (2018). Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi. BioData Min 11, 10. doi:10.1186/s13040-018-0169-5

Tojo, K., Chiang, C. C., Doshi, U. et al. (1988). Stratum corneum reservoir capacity affecting dynamics of transdermal drug delivery. Drug Dev Ind Pharm 14, 561-572. doi:10.3109/03639048809151884

United Nations (2019). Globally Harmonized System of Classification and Labelling of Chemicals (GHS). 8th revised edition. New York and Geneva: United Nations Publications. https://unece.org/ghs-rev8-2019

USEPA – U.S. Environmental Protection Agency (2021). New Approach Methods Work Plan (V2).

van der Zalm, A. J., Barroso, J., Browne, P. et al. (2022). A framework for establishing scientific confidence in new approach methodologies. Arch Toxicol 96, 2865-2879. doi:10.1007/s00204-022-03365-4

Wang, C.-C., Lin, Y.-C., Wang, S.-S. et al. (2017). SkinSensDB: A curated database for skin sensitization assays. J Cheminform 9, 5. doi:10.1186/s13321-017-0194-2

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