Machine perception liquid biopsy identifies brain tumours via systemic immune and tumour microenvironment signature.

ABSTRACT: The detection and identification of intracranial tumours is limited by the lack of accurate biomarkers and requires invasive biopsy procedures. We investigated a machine perception liquid biopsy approach to detect and identify intracranial tumours from peripheral blood and to discover biomarkers responsible for the predictions. Quantum well defect-modified single-walled carbon nanotubes stabilized with single-stranded DNA, interrogating 739 plasma samples from brain tumour patients, were used to train and validate machine-learning models to detect intracranial tumours with 98% accuracy and identify tumour type. The protein corona of the top model-contributing nanosensor was interrogated using quantitative proteomics, resulting in the identification of tumour ecosystem-secreted factors, bot

SUBMITTER: Goerzen D 

PROVIDER: S-EPMC12916486 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature