A novel optimized orthotopic mouse model for brain metastasis with sustained cerebral blood circulation and capability of multiple delivery

作者：Zihao Liu, Huisheng Song, Zhenning Wang, Yang Hu, Xiaoxuan Zhong, Huiling Liu, Jianhao Zeng, Zhiming Ye, Wenfeng Ning, Yizhi Liang, Shengfang Yuan, Zijun Deng, Long Jin, Jeremy Mo, Jiaoyan Ren, Maojin Yao · 发表于：Clinical & Experimental Metastasis · 年份：2025 · DOI：10.1007/s10585-025-10336-3 · 被引用次数：2 · 研究领域：Brain Metastases and Treatment、Glioma Diagnosis and Treatment、Cancer, Stress, Anesthesia, and Immune Response

Brain metastasis is thought to be related to the high mortality and poor prognosis of lung cancer. Despite significant advances in the treatment of primary lung cancer, the unique microenvironment of the brain renders current therapeutic strategies largely ineffective against brain metastasis. The lack of effective drugs for brain metastasis treatment is primarily due to the incomplete understanding of the mechanisms underlying its initiation and progression. Currently, our understanding of brain metastasis remains limited, primarily due to the absence of appropriate models that can realistically simulate the entire process of tumor cell detachment from the primary site, circulation through the bloodstream, and eventual colonization of the brain. Therefore, there is a pressing need to develop more suitable lung cancer brain metastasis models that can effectively replicate these critical stages of metastasis. Here, based on the traditional carotid artery injection model, we established a novel orthotopic mouse model by using a light-controlled hydrogel to repair the puncture site on the carotid artery, with sustained cerebral blood circulation and the capability of multiple delivery cancer cell to mimic lung cancer brain metastasis. The optimized orthotopic mouse model significantly reduced cerebral ischemia and improved cerebral oxygenation by 60% compared to the traditional orthotopic mouse model, enhancing post-operative survival rates. It also showed a reduction in pro-inf...