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癌症核酸疫苗的研究进展:从技术创新到临床转化

Research Progress of Cancer Nucleic Acid Vaccines: From Technological Innovation to Clinical Translation

  • 摘要: 癌症核酸疫苗通过递送编码肿瘤抗原的核酸序列激活特异性抗肿瘤免疫,是精准肿瘤免疫治疗的重要方向之一。与传统蛋白及细胞疫苗相比,核酸疫苗具有设计灵活、制备周期短和易于个体化开发等优势。COVID-19 mRNA疫苗的应用促进了核苷修饰技术和脂质纳米颗粒递送平台的发展,为治疗性癌症疫苗的转化提供了支持。基于高通量测序与人工智能算法的新抗原疫苗策略正推动癌症疫苗由经验性设计向精准个体化治疗转变。目前,多种癌症核酸疫苗已在黑色素瘤、胰腺癌和非小细胞肺癌等肿瘤中开展临床研究,并显示出良好的免疫原性和治疗潜力。个体化mRNA疫苗联合免疫检查点抑制剂的治疗模式正在由晚期疾病治疗向术后辅助治疗及微小残留病灶干预阶段拓展。本文系统总结了癌症核酸疫苗的关键技术基础与临床研究进展,分析了新抗原预测准确性、递送效率及免疫抑制微环境等挑战,并讨论了人工智能辅助抗原预测及联合治疗策略的发展方向。

     

    Abstract: Cancer nucleic acid vaccines activate specific antitumor immunity by delivering nucleic acid sequences encoding tumor antigens and have emerged as a promising approach in precision cancer immunotherapy. Compared with conventional protein-based and cell-based vaccines, nucleic acid vaccines offer advantages including flexible design, rapid manufacturing, and feasibility for personalized development. The clinical application of COVID-19 mRNA vaccines has facilitated advances in nucleoside modification technologies and lipid nanoparticle delivery platforms, supporting the translation of therapeutic cancer vaccines. Integration of high-throughput sequencing with artificial intelligence-based neoantigen identification has promoted the transition of cancer vaccines from empirical design toward precision personalized immunotherapy. Currently, multiple cancer nucleic acid vaccines have entered clinical studies in melanoma, pancreatic cancer, non-small cell lung cancer, and other malignancies, demonstrating favorable immunogenicity and therapeutic potential. Personalized mRNA vaccines combined with immune checkpoint inhibitors are being investigated in clinical settings, with application strategies expanding from treatment of advanced disease toward adjuvant therapy and minimal residual disease intervention. This review summarizes the key technological advances and clinical progress of cancer nucleic acid vaccines, discusses current challenges including neoantigen prediction accuracy, delivery efficiency, and immunosuppressive tumor microenvironment, and highlights future directions involving artificial intelligence-assisted antigen design and combination therapeutic strategies.

     

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