免疫检查点抑制剂（ICIs）是治疗黑色素瘤的有希望的药物。鉴于自身免疫性皮肤疾病表现出免疫反应过度，对自身免疫性皮肤疾病的免疫细胞进行调查对于验证ICIs在黑色素瘤治疗中的有效性至关重要。我们采用多面板标记物，通过表征系统性红斑狼疮（SLE）、特应性皮炎（AD）和银屑病（PS）中皮肤免疫细胞的基因表达特征来预测免疫检查点抑制剂的反应。通过分析每个数据集的单细胞RNA测序数据，我们发现自身免疫性皮肤疾病的T细胞基因表达特征在对免疫治疗作出反应的肿瘤中展现出复杂的免疫反应。基于CD86和CD80为T细胞活化提供必要的共刺激信号的事实，我们观察到CD86信号的相互作用在SLE、AD和PS患者的T细胞中被增强。我们的分析揭示了在SLE、AD和PS患者中，树突状细胞（DCs）向T细胞传递CD86信号的共同增加，证实树突状细胞产生促炎性细胞因子以激活T细胞。因此，我们假设自身免疫性皮肤疾病的T细胞基因表达特征表现出促炎性反应，并具有预测癌症免疫治疗的潜力。我们的研究证明，来源于炎症性皮肤疾病（特别是SLE和PS）的T细胞基因表达特征在预测黑色素瘤免疫检查点阻滞治疗的反应方面具有潜在的生物标记物价值。我们的数据提供了自身免疫性皮肤疾病的免疫相关特征和差异基因表达模式的理解，这可能代表了黑色素瘤免疫疗法的有希望的靶点。© 2023 Springer Nature Limited.

Immune checkpoint inhibitors (ICIs) are promising agents for treating melanoma. Given that autoimmune skin diseases exhibit hyper immune reaction, investigation of immune cells from autoimmune skin disease is crucial to validate the effectiveness of ICIs in melanoma treatment. We employed multipanel markers to predict the response to immune checkpoint inhibitors by characterizing the gene expression signatures of skin immune cells in systemic lupus erythematosus (SLE), atopic dermatitis (AD), and psoriasis (PS). By analyzing single-cell RNA sequencing data from each dataset, T cell gene signatures from autoimmune skin diseases exhibit a complex immune response in tumors that responded to immunotherapy. Based on that CD86 and CD80 provide essential costimulatory signals for T cell activation, we observed that interaction of CD86 signaling has been enhanced in the T cells of patients with SLE, AD, and PS. Our analysis revealed a common increase in CD86 signals from dendritic cells (DCs) to T cells in patients with SLE, AD, and PS, confirming that dendritic cells produce pro-inflammatory cytokines to activate T cells. Thus, we hypothesize that T cell gene signatures from autoimmune skin diseases exhibit a pro-inflammatory response and have the potential to predict cancer immunotherapy. Our study demonstrated that T cell gene signatures derived from inflammatory skin diseases, particularly SLE and PS, hold promise as potential biomarkers for predicting the response to immune checkpoint blockade therapy in patients with melanoma. Our data provide an understanding of the immune-related characteristics and differential gene expression patterns in autoimmune skin diseases, which may represent promising targets for melanoma immunotherapy.© 2023. Springer Nature Limited.