Research progress in AI-driven nanodelivery systems targeting the cGAS-STING signal pathway for tumor therapy

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

Abstract

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

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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