Chen Ying, Zhang Ao, Wang Jingrong, Pan Hudan, Liu Liang, Li Runze
Chinese Medicine Guangdong Laboratory, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 511430, China.
Cancers (Basel). 2025 May 7;17(9):1588. doi: 10.3390/cancers17091588.
Lung cancer brain metastasis (LCBM) is a major contributor to cancer-related mortality, with a median survival of 8-16 months following diagnosis, despite advances in therapeutic strategies. The development of clinically relevant animal models is crucial for understanding the metastatic cascade and assessing therapies that can penetrate the blood-brain barrier (BBB). This review critically evaluates five primary LCBM modeling approaches-orthotopic implantation, intracardiac injection, stereotactic intracranial injection, carotid artery injection, and tail vein injection-focusing on their clinical applicability. We systematically compare their ability to replicate human metastatic pathophysiology and highlight emerging technologies for personalized therapy screening. Additionally, we analyze breakthrough strategies in central nervous system (CNS)-targeted drug delivery, including microparticle targeted delivery systems designed to enhance brain accumulation. By incorporating advances in single-cell omics and AI-driven metastasis prediction, this work provides a roadmap for the next generation of LCBM models, aimed at bridging preclinical and clinical research.
肺癌脑转移(LCBM)是癌症相关死亡的主要原因,尽管治疗策略有所进步,但诊断后的中位生存期仍为8至16个月。开发具有临床相关性的动物模型对于理解转移级联反应和评估能够穿透血脑屏障(BBB)的治疗方法至关重要。本综述批判性地评估了五种主要的LCBM建模方法——原位植入、心内注射、立体定向颅内注射、颈动脉注射和尾静脉注射——重点关注它们的临床适用性。我们系统地比较了它们复制人类转移病理生理学的能力,并强调了用于个性化治疗筛选的新兴技术。此外,我们分析了中枢神经系统(CNS)靶向药物递送的突破性策略,包括旨在增强脑内蓄积的微粒靶向递送系统。通过纳入单细胞组学和人工智能驱动的转移预测方面的进展,这项工作为下一代LCBM模型提供了路线图,旨在弥合临床前研究和临床研究之间的差距。