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<p>Adeno-associated virus (AAV) has emerged as a pivotal vector for cancer gene therapy due to its low immunogenicity, non-pathogenicity, and sustained transgene expression capacity. However, the heterogeneity and complexity of the tumor microenvironment (TME) significantly constrain the delivery efficiency and targeting precision of AAV in solid tumors. Dense extracellular matrix, acidic and hypoxic conditions, and immunosuppressive signaling networks collectively impede effective AAV transduction while increasing off-target risks. To overcome these barriers, recent advances have introduced interdisciplinary optimization strategies, including dynamic engineering of AAV capsids, TME-responsive gene expression systems, and biomimetic camouflage technologies to enhance immune evasion and tumor targeting. Furthermore, data-driven AAV engineering, integrating machine learning and high-throughput screening, has significantly accelerated the development of next-generation vectors. This review systematically summarizes intelligent design strategies for TME-responsive AAV vectors and their progress in precision oncology, with a focus on overcoming key delivery barriers to achieve highly efficient and low-toxicity cancer therapy.</p>

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Intelligent design of tumor microenvironment-responsive Adeno-associated virus vectors: overcoming delivery barriers and enabling precision therapy

  • 期刊论文

  • 发表日期：

    2025年12月26日

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  • Ziyi Wu,
  • Hongmei Liu,
  • Decheng Wu

摘要

Adeno-associated virus (AAV) has emerged as a pivotal vector for cancer gene therapy due to its low immunogenicity, non-pathogenicity, and sustained transgene expression capacity. However, the heterogeneity and complexity of the tumor microenvironment (TME) significantly constrain the delivery efficiency and targeting precision of AAV in solid tumors. Dense extracellular matrix, acidic and hypoxic conditions, and immunosuppressive signaling networks collectively impede effective AAV transduction while increasing off-target risks. To overcome these barriers, recent advances have introduced interdisciplinary optimization strategies, including dynamic engineering of AAV capsids, TME-responsive gene expression systems, and biomimetic camouflage technologies to enhance immune evasion and tumor targeting. Furthermore, data-driven AAV engineering, integrating machine learning and high-throughput screening, has significantly accelerated the development of next-generation vectors. This review systematically summarizes intelligent design strategies for TME-responsive AAV vectors and their progress in precision oncology, with a focus on overcoming key delivery barriers to achieve highly efficient and low-toxicity cancer therapy.