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

Journal: International journal of molecular sciences
Published Date:

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.

Authors

  • Dittman Lai-Shun Chung
    Department of Clinical Oncology, University of Hong Kong, Hong Kong SAR, China.
  • Geoffrey Ho Duen Leung
    Insilico Medicine Hong Kong Ltd., Hong Kong Science and Technology Park, New Territories, Hong Kong, China.
  • Songran Liu
    Department of Clinical Oncology, University of Hong Kong, Hong Kong SAR, China.
  • Sarah Wing Yan Lok
    Insilico Medicine Hong Kong Ltd., Unit 310, 3/F, Building 8W, Hong Kong Science and Technology Park, Hong Kong SAR, China.
  • Ying Xin
    Insilico Medicine Hong Kong Ltd., Unit 310, 3/F, Building 8W, Hong Kong Science and Technology Park, Hong Kong SAR, China.
  • Yunfei Xia
    Department of Radiation Oncology, Sun Yat-Sen University Cancer Centre, Guangzhou 510060, China.
  • Alex Zhavoronkov
    Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, Maryland, USA.
  • Frank W Pun
    Insilico Medicine Hong Kong Ltd., Hong Kong Science and Technology Park, New Territories, Hong Kong, China.
  • Wai-Tong Ng
    Department of Clinical Oncology, Pamela Youde Nethersole Eastern Hospital, Hong Kong.
  • Wei Dai
    Department of Intensive Care Unit, The First Affiliated Hospital of Jiangxi Medical College, Shangrao, Jiangxi, China.