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

TL;DR

This paper reviews lung cancer brain metastasis models and emerging therapies to improve preclinical research and treatment development.

Contribution

The study systematically compares five LCBM modeling approaches and proposes a roadmap integrating new technologies for better preclinical models.

Findings

Five LCBM modeling approaches are evaluated for their ability to replicate human metastatic pathophysiology.

Emerging technologies like CNS-targeted drug delivery and AI-driven prediction are highlighted for future models.

Robust models are needed to simulate the metastatic cascade and develop BBB-penetrating therapies.

Abstract

This study provides a comprehensive review of lung cancer brain metastasis (LCBM) models, evaluating their clinical relevance and ability to replicate human metastatic pathophysiology. The authors assess five primary modeling approaches—orthotopic implantation, intracardiac injection, stereotactic intracranial injection, carotid artery injection, and tail vein injection—highlighting their strengths and limitations. This review emphasizes the need for robust models that can accurately simulate the metastatic cascade and aid in developing therapies capable of penetrating the blood–brain barrier (BBB). This article also explores emerging technologies in personalized therapy screening and CNS-targeted drug delivery, aiming to bridge preclinical and clinical research.

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.

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