Detection of brain metastases from blood using Brain nanoMET sensor: Extracellular vesicles as a dynamic marker for metastatic brain tumors

Abstract

Brain metastases account for a significant number of cancer-related deaths with poor prognosis and limited treatment options. Current diagnostic methods have limitations in resolution, sensitivity, inability to differentiate between primary and metastatic brain tumors, and invasiveness. Liquid biopsy is a promising non-invasive alternative; however, current approaches have shown limited efficacy for diagnosing brain metastases due to biomarker instability and low levels of detectable tumor-specific biomarkers. This study introduces an innovative liquid biopsy technique using extracellular vesicles (EVs) as a biomarker for brain metastases, employing the Brain nanoMET sensor. The sensor was fabricated through an ultrashort femtosecond laser ablation process and provides excellent surface-enhanced Raman Scattering functionality. We developed an in vitro model of metastatic tumors to understand the tumor microenvironment and secretomes influencing brain metastases from breast and lung cancers. Molecular profiling of EVs derived from brain-seeking metastatic tumors revealed unique, brain-specific signatures, which were also validated in the peripheral circulation of brain metastasis patients. Compared to primary brain tumor EVs, we also observed an upregulation of PD-L1 marker in the metastatic EVs. A machine learning model trained on these EV molecular profiles achieved 97% sensitivity in differentiating metastatic brain cancer from primary brain cancer, with 94% accuracy in predicting the primary tissue of origin for breast metastasis and 100% accuracy for lung metastasis. The results from this pilot validation suggest that this technique holds significant potential for improving metastasis diagnosis and targeted treatment strategies for brain metastases, addressing a critical unmet need in neuro-oncology.