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.
Keywords: Glioblastoma; SERS; cancer diagnosis; extracellular vesicles; nanosensor.