A Simple Technique for High-Throughput Screening of Drugs That Modulate Normal and Psoriasis-Like Differentiation in Cultured Human Keratinocytes

Abstract

Established treatments for psoriasis act ei-ther on hyperproliferation, inflammation, aberrant epidermal differentiation or a combination of these aspects of the disease. Potential new drugs for treatment of psoriasis or other disorders with abnormalities in epidermal differentiation can be identified by high-throughput screening of large compound libraries using surrogate markers for the disease. Here we describe a screening model to detect pharmacologically active drugs in two keratinocyte-based, 96-well culture models that use expression of cytokeratin 10 (CK10) and skin-derived antileucoprotease (SKALP)/elafin as markers for normal and psoriatic differentiation, respectively, and allow multiple parameters to be determined from a single well. In this model we tested a number of compounds in a pharmacological range from 10–7 to 10–5 M, including known antipsoriatic drugs, and experimental drugs that are potentially useful in the treatment of psoriasis. All-trans-retinoic acid, dithranol and the p38 mitogen-activated protein (MAP) kinase inhibitor SB220025 displayed a strong inhibitory effect on SKALP expression while cyclosporin A, dexamethasone, the vitamin D3 derivative calcipotriol and the p38 MAP kinase inhibitor SB203580 showed only moderate inhibition. Methotrexate and dimethylfumarate did not affect the expression of SKALP. With respect to CK10 expression, all-trans-retinoic acid, calcipotriol, SB203580 and SB220025 exhibited strong inhibition while dithranol showed only moderate suppression of this normal differentiation marker. Expression levels of CK10 were not significantly affected by dexamethasone, methotrexate, cyclosporin A or dimethylfumarate. This model system parallels most, but not all, findings on the in vitro effect of known antipsoriatic drugs on keratinocytes. In addition, the model identifies p38 MAP kinase inhibitors as potent suppressors of differentiation-associated gene expression. Although further delineation and validation of this model is required, we conclude that the system is amenable to down-scaling and application as a high-throughput screen for differentiation-modifying compounds.