Computer machine‐learning tools help identify how different anti‐inflammatory treatments affect skin cells

Abstract

British Journal of DermatologyVolume 184, Issue 5 p. e167-e167 Plain Language Summary Computer machine-learning tools help identify how different anti-inflammatory treatments affect skin cells First published: 04 May 2021 https://doi.org/10.1111/bjd.19902AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Linked Article: Clayton et al. Br J Dermatol 2021; 184:913–922. Eczema and psoriasis affect up to one in 10 adults and as many as one in five children. These conditions are caused by skin cells not communicating properly, leading to a state known as inflammation, which changes how the skin works. Following recent research advances we have a good understanding of the type of inflammation involved in eczema and psoriasis, and this has led to the development and use of targeted therapies. However, we do not fully understand how targeted and less targeted treatments affect different skin cell types, and the communication between them. Skin cells called keratinocytes that are not functioning normally contribute significantly to the symptoms of many skin diseases. Although it is known that inflammatory signalling can affect these keratinocytes, little is known about the molecular mechanisms involved in this process. Investigations of gene expression in whole tissue biopsy (where skin is removed and tested) provide comprehensive, but very complex, information about skin inflammation. To understand more about keratinocyte biology in skin disease and during treatment, we used computer machine-learning tools and a program called CIBERSORT. This approach helped us to find out more specific, detailed information about keratinocytes in different skin diseases that involve inflammation and has helped reveal the effect of different treatments on keratinocytes. We found that eczema keratinocytes are different to healthy cells even when there is no active disease, and they respond differently to available therapies. We show that treatment with a drug called ciclosporin may treat active eczema but not the underlying condition, whereas targeted treatment using dupilumab (which is injected just under the skin) corrects keratinocyte abnormalities. Volume184, Issue5May 2021Pages e167-e167 RelatedInformation