Brain cancers, one of the most fatal
malignancies, require
accurate
diagnosis for guided therapeutic intervention. However, conventional
methods for brain cancer prognosis (imaging and tissue biopsy) face
challenges due to the complex nature and inaccessible anatomy of the
brain. Therefore, deep analysis of brain cancer is necessary to (i)
detect the presence of a malignant tumor, (ii) identify primary or
secondary origin, and (iii) find where the tumor is housed. In order
to provide a diagnostic technique with such exhaustive information
here, we attempted a liquid biopsy-based deep surveillance of brain
cancer using a very minimal amount of blood serum (5 μL) in
real time. We hypothesize that holistic analysis of serum can act
as a reliable source for deep brain cancer surveillance. To identify
minute amounts of tumor-derived material in circulation, we synthesized
an ultrasensitive 3D nanosensor, adopted SERS as a diagnostic methodology,
and undertook a DEEP neural network-based brain cancer surveillance.
Detection of primary and secondary tumor achieved 100% accuracy. Prediction
of intracranial tumor location achieved 96% accuracy. This modality
of using patient sera for deep surveillance is a promising noninvasive
liquid biopsy tool with the potential to complement current brain
cancer diagnostic methodologies.