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Evaluating liquid biopsy biomarkers for early detection of brain metastasis: A systematic review
Jinyue Yu1,2, Craig Paterson1,2, Phillippa Davies1,2
1Cancer Research Integrative Cancer Epidemiology Programme, University of Bristol, Bristol, UK.
Background:
Brain metastases (BMs) are the most common intracranial malignancy in adults, contributing significantly to cancer-related morbidity and mortality. Early detection is critical for optimizing treatment and improving survival. This systematic review evaluates the diagnostic potential of liquid biopsy biomarkers for detecting BM from lung, breast, and other cancers.
Methods:
A comprehensive search was conducted in MEDLINE, Embase, and BIOSIS databases using keywords related to liquid biopsy, biomarkers, and BMs. Data on participant characteristics, diagnostic reference standards, types of biomarkers, primary cancer origins, and diagnostic outcomes were independently extracted. Diagnostic performance was evaluated using sensitivity, specificity, and area under the curve (AUC). Risk of bias was assessed using the QUADAS-2 tool.
Results:
Thirty-one studies involving 5676 participants were included, assessing biomarkers such as cfDNA, miRNAs, proteins (eg, neurofilament light [NfL], glial fibrillary acidic protein [GFAP], S100B), metabolomic profiles, and multi-marker models. NfL and GFAP emerged as the most promising biomarkers, demonstrating moderate to strong diagnostic performance across multiple cancer types. Multi-marker models combining NfL and GFAP achieved sensitivity and specificity exceeding 90%. S100B showed variable performance due to differences in study designs and thresholds. Emerging biomarkers like cfDNA and metabolomic profiles showed potential but require further validation.
Conclusions:
Liquid biopsy biomarkers, particularly NfL and GFAP, hold promise for non-invasive BM detection. Clinical utility may be in the initial cancer workup for localized tumor to prompt brain imaging. Future research is required to validate biomarkers in larger, diverse populations across different cancer types.

