High Accuracy Classification of Developmental Toxicants by In Vitro Tests of Human Neuroepithelial and Cardiomyoblast Differentiation

Seidel Florian, Cherianidou Anna, Kappenberg Franziska, Marta Miriam, Dreser Nadine, Blum Jonathan, Waldmann Tanja, Blüthgen Nils, Meisig Johannes, Madjar Katrin, Henry Margit, Rotshteyn Tamara, Scholtz-Illigens Andreas, Marchan Rosemarie, Edlund Karolina, Leist Marcel, Rahnenführer Jörg, Sachinidis Agapios, Hengstler Jan G.
DOI: 10.3390/cells11213404
PMID: 36359802
Keyword: Alternative testing strategies · Developmental and reproductive toxicity · Drug screening · Gene expression · In vitro test · Induced pluripotent stem cells · Toxicogenomics · Transcriptomics


Human-relevant tests to predict developmental toxicity are urgently needed. A currently intensively studied approach makes use of differentiating human stem cells to measure chemically-induced deviations of the normal developmental program, as in a recent study based on cardiac differentiation (UKK2). Here, we (i) tested the performance of an assay modeling neuroepithelial differentiation (UKN1), and (ii) explored the benefit of combining assays (UKN1 and UKK2) that model different germ layers. Substance-induced cytotoxicity and genome-wide expression profiles of 23 teratogens and 16 non-teratogens at human-relevant concentrations were generated and used for statistical classification, resulting in accuracies of the UKN1 assay of 87-90%. A comparison to the UKK2 assay (accuracies of 90-92%) showed, in general, a high congruence in compound classification that may be explained by the fact that there was a high overlap of signaling pathways. Finally, the combination of both assays improved the prediction compared to each test alone, and reached accuracies of 92-95%. Although some compounds were misclassified by the individual tests, we conclude that UKN1 and UKK2 can be used for a reliable detection of teratogens in vitro, and that a combined analysis of tests that differentiate hiPSCs into different germ layers and cell types can even further improve the prediction of developmental toxicants.