Cross-Comparison of Inflammatory Skin Disease Transcriptomics Identifies PTEN as a Pathogenic Disease Classifier in Cutaneous

Brian D. Aevermann,Jeremy Di Domizio, Peter Olah, Fanny Saidoune, John M. Armstrong, Herve Bachelez,Jonathan Barker, Muzlifah Haniffa,Valerie Julia, Kasper Juul, Jayendra Kumar Krishnaswamy, Thomas Litman, Ian Parsons, Kavita Y. Sarin,Matthias Schmuth, Michael Sierra,Michael Simpson,Bernhard Homey,Christopher E. M. Griffiths,Richard H. Scheuermann,Michel Gilliet

JOURNAL OF INVESTIGATIVE DERMATOLOGY(2024)

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摘要
transcriptomics dysregulations underlying However, majority of transcriptomics studies focus on single diseases with limited relevance for understanding the molecular relationship between diseases or for identifying disease -specific markers. In this study, we used a normalization approach to compare gene expression across nine inflammatory skin diseases. The normalized datasets were found to retain differential expression signals that allowed unsupervised disease clustering and identification of disease -specific gene signatures. Using the NS -Forest algorithm, we identified a minimal set of biomarkers and validated their use as diagnostic disease classifier. Among them, PTEN was identified as being a specific marker for cutaneous lupus erythematosus and found to be strongly expressed by lesional keratinocytes in association with pathogenic type I IFNs. In fact, PTEN facilitated the expression of IFN-b and IFN-k in keratinocytes by promoting activation and nuclear translocation of IRF3. Thus, cross -comparison of tissue transcriptomics is a valid strategy to establish a molecular disease classification and to identify pathogenic disease biomarkers.
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AA,AD,Akt,CLE,DE,HS,KC,LE,LP,pDC,PI3K,PIP3,RMA,siRNA
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