这项研究解决了恶性黑色素瘤（MM）和非黑色素瘤皮肤癌（NMSC）的诊断和治疗挑战。我们的目标是使用多中心孟德尔随机化 (MR) 框架来识别与 MM 和 NMSC 特征因果相关的循环蛋白。我们利用大规模 cis-MR 来评估多种血浆蛋白对 MM、NMSC、鳞状细胞癌 (SCC) 和基底细胞癌 (BCC) 的影响。为了确保稳健性，进行了 MR Steiger 和贝叶斯共定位等额外分析，然后通过荟萃分析方法进行复制。使用全转录组关联研究方法还可以在组织水平上验证已识别蛋白质和结果之间的关联。此外，还进行了蛋白质-蛋白质相互作用分析，以探索已识别蛋白质与现有癌症药物靶点之间的关系。 MR 分析已确定 13 种血浆蛋白与 BCC、2 种与 SCC 和 1 种与 MM 相关。具体来说，ASIP 和 KRT5 与 BCC 相关，ASIP 也可能针对 MM。 CTSS 和 TNFSF8 被认为是 BCC 的有前途的成药候选者。这种多维方法提名 ASIP、KRT5、CTSS 和 TNFSF8 作为皮肤癌的潜在诊断和治疗靶点。© 2024。作者。

This study addresses the diagnostic and therapeutic challenges in malignant melanoma (MM) and non-melanoma skin cancers (NMSC). We aim to identify circulating proteins causally linked to MM and NMSC traits using a multicenter Mendelian randomization (MR) framework. We utilized large-scale cis-MR to estimate the impact of numerous plasma proteins on MM, NMSC, squamous cell carcinoma (SCC), and basal cell carcinoma (BCC). To ensure robustness, additional analyses like MR Steiger and Bayesian colocalization are conducted, followed by replication through meta-analytical methods. The associations between identified proteins and outcomes are also validated at the tissue level using Transcriptome-Wide Association Study methods. Furthermore, a protein-protein interaction analysis is conducted to explore the relationship between identified proteins and existing cancer medication targets. The MR analysis has identified associations of 13 plasma proteins with BCC, 2 with SCC, and 1 with MM. Specifically, ASIP and KRT5 are associated with BCC, with ASIP also potentially targeting MM. CTSS and TNFSF8 are identified as promising druggability candidates for BCC. This multidimensional approach nominates ASIP, KRT5, CTSS, and TNFSF8 as potential diagnostic and therapeutic targets for skin cancers.© 2024. The Author(s).