Engineering oncolytic bacteria as precision cancer therapeutics: design principles, therapeutic strategies, and translational perspectives
Lingxue Niu, Zhenqiang Deng, Yiyu Jin, Ningzi Guan, Haifeng Ye
East China Normal University Shanghai CASB Biotechnology (China)
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Engineered oncolytic bacteria are emerging as a promising platform for precision cancer therapy, combining inherent tumor tropism, immunogenicity, and programmable gene control. Advances in synthetic biology now enable inducible and autonomous circuits that sense exogenous inputs (chemical signals or physical signals), bacterial self-cues (quorum sensing, bacterial invasion switches, or nitric oxide-responsive promoters), and tumor-specific pathophysiology (hypoxia, low pH, or lactate). These designs regulate colonization, lysis, and the spatiotemporally confined release of therapeutic cargos-including prodrug-converting enzymes, cytokines, and antibody/nanobody fragments-thereby enhancing antitumor efficacy while limiting off-target toxicity. Beyond monotherapy, oncolytic bacteria integrate with complementary modalities-including immune checkpoint blockade, adoptive cell therapies (CAR-T/NK), radiotherapy/chemotherapy, nanomedicine, and oncolytic viruses-to amplify immune activation and to enable multimodal, synergistic regimens. Concurrently, biosensor modules transform bacterial chassis into programmable "microbial factories" that couple therapy with real-time imaging and adaptive responses within the tumor microenvironment. This review synthesizes design principles for bacterial gene regulation, surveys recent preclinical advances, and highlights emerging combination strategies, while outlining translational considerations for safety, manufacturability, dosing, and patient selection. Together, these developments position engineered oncolytic bacteria as a promising route toward safe, effective, and ultimately personalized bacteria-based cancer therapeutics.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
生物医学Cancer Research and Treatments
Virus-based gene therapy research · Biomedical and Engineering Education
参考文献 186
此处列出前 3 条
引用本文 14
按被引量排序,此处列出前 3 条