Robinson et al. challenge the reliance on neurosurgery for glioma diagnosis by integrating multi-omic profiling of plasma extracellular vesicles with machine learning. Across independent cohorts, these biomarkers discriminate between glioma and controls and enable longitudinal tracking of tumor burden, establishing a clinically relevant foundation for minimally invasive diagnosis, monitoring, and stratification.
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Szydlik et al. (2026) studied this question.
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