Refining Lung Cancer Brain Metastasis Models for Spatiotemporal Dynamic Research and Personalized Therapy.

Abstract

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.