A computational SOX10 network-based selection strategy to identify new drug targets in uveal melanoma

作者：Anja Wessely, Christopher Lischer, Adrian Weich, Claudia Kammerbauer, Esther Güse, Elias A. T. Koch, Xin Lai, Jan Dörrie, Michael Erdmann, Caroline Voskens, Stefan Schliep, Jens Neumann, Markus Eckstein, Harald Knorr, Beatrice Schuler‐Thurner, Julio Vera, Carola Berking, Markus V. Heppt · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2025 · DOI：10.1101/2025.10.14.679939 · 被引用次数：2 · 研究领域：Ubiquitin and proteasome pathways、Neurobiology and Insect Physiology Research、Machine Learning in Bioinformatics

Abstract Uveal melanoma (UM) is the most common intraocular malignancy in adults. In contrast to cutaneous melanoma (CM), effective treatment options for metastatic UM are limited. The transcription factor SOX10 is crucial for CM initiation and survival, making it an interesting candidate for new targeted therapies, but its relevance in UM was unclear. We found that SOX10 was widely expressed in UM and essential for proliferation, cell cycle progression, and survival. The effects were partially mediated by SOX10-related genes including MITF , highlighting high addiction of UM to the SOX10-MITF axis. Additionally, SOX10 knockdown induced massive transcriptomic changes. Due to a lack of specific inhibitors of SOX10 and MITF, a computational approach was used to identify druggable targets by curating a UM-specific protein interaction network to search for candidates downregulated upon SOX10 inhibition. Thereby, the E2F transcription factor family was identified and their potential as druggable target candidates in UM was confirmed using the pan-E2F inhibitor HLM006474, resulting in cell cycle arrest and apoptosis. Taken together, SOX10 is crucial for UM survival and SOX10-associated proteins may serve as promising targets for developing new therapeutic strategies in UM.