AI驱动纳米递送系统靶向cGAS-STING信号通路在肿瘤治疗中的研究进展

doi:10.3760/cma.j.cn371439-20251112-00058

摘要/Abstract

摘要：

环鸟苷酸-腺苷酸合成酶（cGAS）-干扰素基因刺激因子（STING）信号通路是肿瘤免疫治疗的关键靶点，但其激动剂因全身毒性及递送效率低而应用受阻。纳米递送系统可精准靶向肿瘤并响应性释药，有效解决了这一难题。然而，纳米载体的设计与针对个体患者的精准适配，需更高维度的智能决策。人工智能（AI）技术可利用机器学习优化纳米载体理化参数以提升肿瘤富集、基于多组学数据解析患者亚群以实现精准分层、融合动态治疗数据以实时优化给药策略。深入分析AI驱动下纳米递送系统与cGAS-STING靶向治疗的深度融合，构建一个从载体设计、患者筛选到动态治疗的智能化闭环，可推动该领域从普适性给药迈向个体化精准治疗的新范式。

关键词: 肿瘤, 分子靶向治疗, 人工智能, 纳米递送系统, cGAS-STING信号通路

Abstract:

The cyclic GMP-AMP synthase（cGAS）-stimulator of interferon gene（STING）signal pathway is a key target in tumor immunotherapy，yet the clinical application of its agonists is hindered by systemic toxicity and poor delivery efficiency. Nanodelivery systems, with their ability to precisely target tumors and release drugs in a stimuli-responsive manner, provide an effective solution to this challenge. However，the design of nanocarriers and their precise adaptation to individual patients require higher-dimensional intelligent decision-making. Artificial intelligence（AI）technology can utilize machine learning to optimize the physicochemical parameters of nanocarriers to enhance tumor enrichment，analyze patient subgroups based on multi-omics data for precise stratification，and integrate dynamic treatment data to optimize drug administration strategies in real time. A thorough analysis of the deep integration of AI-driven nanodelivery systems and cGAS-STING-targeted therapy has established an intelligent closed loop encompassing carrier design，patient screening，and dynamic treatment，which can propel this field from universal drug administration towards a new paradigm of individualized precision therapy.

Key words: Neoplasms, Molecular targeted therapy, Artificial intelligence, Nanodelivery system, cGAS-STING signal pathway

澈根, 乌日汗, 李畅, 东丽. AI驱动纳米递送系统靶向cGAS-STING信号通路在肿瘤治疗中的研究进展[J]. 国际肿瘤学杂志, 2026, 53(6): 361-365.

Che Gen, Wu Rihan, Li Chang, Dong Li. Research progress in AI-driven nanodelivery systems targeting the cGAS-STING signal pathway for tumor therapy[J]. Journal of International Oncology, 2026, 53(6): 361-365.

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