Abstract

Chemical-induced allergies at workplace represent a significant occupational health issue. These substances must be properly identified as sensitizers. In previous studies, an original model using mouse bone marrow-derived dendritic cells (BMDC) was developed for this purpose. The aim of this study was to evaluate the predictive capacity of the BMDC model with a large panel of sensitizers (including pre- and pro-haptens) and non-sensitizers. The readout from the BMDC model is based on expression levels of six phenotypic markers measured by flow cytometry. The results indicate that 29 of the 37 non-sensitizers, and 81 of the 86 sensitizers were correctly classified compared to the Local Lymph Node Assay (LLNA). Statistical analysis revealed the BMDC model to have a sensitivity of 94%, a specificity of 78%, and an accuracy of 89%. The EC2 (Effective Concentration) values calculated with this model allow sensitizers to be categorized into four classes: extreme, strong, moderate and weak. These excellent predictive performances show that the BMDC model discriminates between sensitizers and non-sensitizers with outstanding precision equal to or better than existing validated alternative models. Moreover, this model allows to predict sensitization potency of chemicals. The BMDC test could therefore be proposed as an additional tool to assess the sensitizing potential and potency of chemicals.

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