Lung cancer remains the leading cause of cancer-related deaths worldwide, with brain metastasis being one of the most common complications in advanced-stage disease. The development of noninvasive and efficient early diagnostic methods is therefore of critical clinical importance. In this study, untargeted liquid chromatography-mass spectrometry (LC-MS) was employed to perform metabolomic profiling of 66 serum samples from patients with lung cancer brain metastasis, early-stage lung cancer, and healthy controls. A total of 719 metabolites were identified with high data reliability. Comparative analysis revealed 20 significantly upregulated and 12 significantly downregulated metabolites in the lung cancer brain metastasis group. These differentially expressed metabolites were primarily enriched in amino acid and energy metabolism pathways. This specific metabolic signature was highly associated with the brain metastatic state. Although not yet validated for clinical application, this profile demonstrated robust discriminatory power within the current cohort and serves as a potential set of risk-stratification biomarkers. These findings identify a distinct metabolic phenotype associated with brain metastasis, laying the critical groundwork for future research into noninvasive diagnostic strategies. Nevertheless, further validation within independent, longitudinal cohorts is required.
Zhu et al. (2026) studied this question.