Artificial Intelligence for Computer-Aided Detection in Biomedical Applications

人工智能在生物医学应用中的计算机辅助检测

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Abstract

BACKGROUND: Bacterial cancer therapies have regained attention as a strategy to remodel the immunosuppressive tumor microenvironment (TME). Engineered bacteria equipped with tumor-targeting moieties can enhance intratumoral specificity; however, safety concerns and the need for repeat dosing limit their translational potential. METHODS: Here, we developed an aptamer-conjugated engineered bacterial strain (ApCB) carrying CXCL9, and evaluated its tumor-targeting colonization and immunomodulatory effects in a subcutaneous LLC tumor model. After determining the in vitro minimum inhibitory concentration (MIC) of kanamycin and extrapolating an equivalent in vivo dose based on mouse blood volume, we implemented a tail-vein antibiotic administration strategy to precisely regulate intratumoral bacterial burden. RESULTS: Antibiotic treatment substantially lowered peak bacterial abundance in tumors while retaining a viable intratumoral bacterial reservoir, allowing sustained bacterial proliferation and periodic CXCL9 release without repeated re-administration of engineered bacteria. In vivo, ApCB–CXCL9 treatment significantly inhibited tumor growth, induced extensive tumor necrosis, decreased Ki67 expression, and increased intratumoral CD8⁺ T-cell infiltration together with elevated effector cytokines (IFN-γ, TNF-α). CONCLUSION: These findings indicate that aptamer-guided engineered bacteria combined with antibiotic-mediated population control can safely and controllably remodel the tumor immune microenvironment, offering a practicable approach for sustained delivery and clinical translation of bacterial immunotherapies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-026-08194-y.

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