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人工智能驱动的药物靶点筛选平台鉴定出在爱泼斯坦-巴尔病毒相关鼻咽癌中因增强子侵扰而激活的致癌基因CACNA2D1。

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

作者信息

Chung Dittman Lai-Shun, Leung Geoffrey Ho Duen, Liu Songran, Lok Sarah Wing Yan, Xin Ying, Xia Yunfei, Zhavoronkov Alex, Pun Frank W, Ng Wai-Tong, Dai Wei

机构信息

Department of Clinical Oncology, University of Hong Kong, Hong Kong SAR, China.

Insilico Medicine Hong Kong Ltd., Unit 310, 3/F, Building 8W, Hong Kong Science and Technology Park, Hong Kong SAR, China.

出版信息

Int J Mol Sci. 2025 May 14;26(10):4697. doi: 10.3390/ijms26104697.

DOI:10.3390/ijms26104697
PMID:40429844
Abstract

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 promoter. Analysis of clinical specimens revealed significant upregulation of CACNA2D1 at both the transcriptional and translational levels (-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.

摘要

鼻咽癌(NPC)的治疗方法正在迅速发展,免疫检查点抑制剂已成为一种重要的治疗手段。然而,针对NPC中特定分子和细胞异常的药物研发进展缓慢。人工智能(AI)和生物信息学的最新进展,特别是那些整合多组学数据的进展,为传统的体外筛选方法提供了一种更有效的替代方案,用于识别NPC中具有临床可操作性的靶点。通过多组学分析和AI驱动的筛选相结合,我们确定了CACNA2D1是NPC中一种新的癌细胞特异性治疗靶点。我们的研究表明,利用爱泼斯坦-巴尔病毒(EBV)的束缚作用可增加启动子附近的H3K27乙酰化。对临床标本的分析显示,CACNA2D1在转录和翻译水平均显著上调(P值<0.01)。功能研究表明,CACNA2D1缺失后小鼠肿瘤大小缩小了三分之一,通过阻断增强子癌细胞生长减少了85%,而CACNA2D1的存在在NPC肿瘤发生过程中赋予了生存优势。这些发现凸显了CACNA2D1作为NPC治疗干预潜在靶点的潜力。

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本文引用的文献

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Establishment and Characterization of an Epstein-Barr Virus-positive Cell Line from a Non-keratinizing Differentiated Primary Nasopharyngeal Carcinoma.建立并鉴定一个源自非角化分化型鼻咽原发癌的 Epstein-Barr 病毒阳性细胞株。
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A comprehensive AI-driven analysis of large-scale omic datasets reveals novel dual-purpose targets for the treatment of cancer and aging.大规模组学数据集的综合人工智能分析揭示了治疗癌症和衰老的新型两用靶点。
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