AI-Driven Drug Target Screening Platform Identified Oncogene CACNA2D1 Activated by Enhancer Infestation in Epstein-Barr Virus-Associated Nasopharyngeal Carcinoma

作者：Dittman Lai‐Shun Chung, Geoffrey Ho Duen Leung, Songran Liu, Sarah Wing Yan Lok, Ying Xin, Yunfei Xia, Alex Zhavoronkov, Frank W. Pun, Wai Tong Ng, Wei Dai · 发表于：International Journal of Molecular Sciences · 年份：2025 · DOI：10.3390/ijms26104697 · 被引用次数：4 · 研究领域：Protein Degradation and Inhibitors、Chromatin Remodeling and Cancer、Peptidase Inhibition and Analysis

The management of nasopharyngeal cancer (NPC) is rapidly evolving, with immune checkpoint inhibitors emerging as a prominent treatment approach. However, drug development targeting specific molecular and cellular abnormalities in NPC has slowed. Recent advancements in artificial intelligence (AI) and bioinformatics, particularly those integrating multi-omics data, offer a more effective alternative to traditional in vitro screening methods for identifying clinically actionable targets in NPC. Through a combination of multi-omics analyses and AI-driven screening, we identified CACNA2D1 as a novel cancer-cell-specific therapeutic target in NPC. Our research indicates that exploiting Epstein–Barr virus (EBV) tethering increases H3K27 acetylation near the CACNA2D1 promoter. Analysis of clinical specimens revealed significant upregulation of CACNA2D1 at both the transcriptional and translational levels (p-value < 0.01). Functional studies demonstrated that the mouse tumour size shrank by one-third upon the depletion of CACNA2D1, and there was an 85% reduction in cancer cell growth through the blockage of enhancers, while the presence of CACNA2D1 conferred a survival advantage during NPC tumour development. These findings highlight the potential of CACNA2D1 as a promising target for therapeutic intervention in NPC.