2 research outputs found
DEEP Surveillance of Brain Cancer Using Self-Functionalized 3D Nanoprobes for Noninvasive Liquid Biopsy
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
Self-Functionalized Superlattice Nanosensor Enables Glioblastoma Diagnosis Using Liquid Biopsy
Glioblastoma (GBM), the most aggressive and lethal brain
cancer,
is detected only in the advanced stage, resulting in a median survival
rate of 15 months. Therefore, there is an urgent need to establish
GBM diagnosis tools to identify the tumor accurately. The clinical
relevance of the current liquid biopsy techniques for GBM diagnosis
remains mostly undetermined, owing to the challenges posed by the
blood-brain barrier (BBB) that restricts biomarkers entering the circulation,
resulting in the unavailability of clinically validated circulating
GBM markers. GBM-specific liquid biopsy for diagnosis and prognosis
of GBM has not yet been developed. Here, we introduce extracellular
vesicles of GBM cancer stem cells (GBM CSC-EVs) as a previously unattempted,
stand-alone GBM diagnosis modality. As GBM CSCs are fundamental building
blocks of tumor initiation and recurrence, it is desirable to investigate
these reliable signals of malignancy in circulation for accurate GBM
diagnosis. So far, there are no clinically validated circulating biomarkers
available for GBM. Therefore, a marker-free approach was essential
since conventional liquid biopsy relying on isolation methodology
was not viable. Additionally, a mechanism capable of trace-level detection
was crucial to detecting the rare GBM CSC-EVs from the complex environment
in circulation. To break these barriers, we applied an ultrasensitive
superlattice sensor, self-functionalized for surface-enhanced Raman
scattering (SERS), to obtain holistic molecular profiling of GBM CSC-EVs
with a marker-free approach. The superlattice sensor exhibited substantial
SERS enhancement and ultralow limit of detection (LOD of attomolar
10–18 M concentration) essential for trace-level
detection of invisible GBM CSC-EVs directly from patient serum (without
isolation). We detected as low as 5 EVs in 5 μL of solution,
achieving the lowest LOD compared to existing SERS-based studies.
We have experimentally demonstrated the crucial role of the signals
of GBM CSC-EVs in the precise detection of glioblastoma. This was
evident from the unique molecular profiles of GBM CSC-EVs demonstrating
significant variation compared to noncancer EVs and EVs of GBM cancer
cells, thus adding more clarity to the current understanding of GBM
CSC-EVs. Preliminary validation of our approach was undertaken with
a small amount of peripheral blood (5 μL) derived from GBM patients
with 100% sensitivity and 97% specificity. Identification of the signals
of GBM CSC-EV in clinical sera specimens demonstrated that our technology
could be used for accurate GBM detection. Our technology has the potential
to improve GBM liquid biopsy, including real-time surveillance of
GBM evolution in patients upon clinical validation. This demonstration
of liquid biopsy with GBM CSC-EV provides an opportunity to introduce
a paradigm potentially impacting the current landscape of GBM diagnosis