Grant: Project Grant

Glioblastoma (GBM) is a paradigm of intractable cancer with a dynamic cellular and molecular complexity that remains virtually inaccessible in real time with roughly 15 months median survival times. While chemoradiation therapy with temozolomide (TMZ) leads to short term relief, a resistant disease inevitably reoccurs with uniformly lethal consequences. Also, customized treatments require that the cancer's full molecular profile be monitored continuously, which is highly challenging. Extra-cellular vesicles (EV's) provide an alternative approach for comprehensive continuous time monitoring of the GBM molecular profile, as they carry molecular cargo reflective of their parental cells. Oncogenic EVs can be recovered non-invasively from blood of GBM bearing patients. Despite their promise, optimum therapeutic exploitation of EVs is challenging, due to their small-size, extreme heterogeneity and chemical complexity. Moreover, to exploit the single cell resolved information potentially contained in a single EV, truly single EV analysis approaches are required. The single EV approaches to date inevitably pre-select the biomarkers targeted from the pool of biomarkers for which reliable probes exist. We have developed a label-free single EV technology that exploits surface-enhanced Raman spectroscopy (SERS) to output a Raman spectrographic fingerprint from individual EVs captured in a nano plasmonic cavity array (MoSERS). When interpreted via a deep learning algorithm, the multiplexed biomarker status of the originating cell can be extracted from the fingerprint via a post-measurement data processing step. Here we propose to scale our proof-of-principle demonstration of MoSERS technology for continuous time monitoring of molecular status of patient's GBM at the level of single EVs. Ultimately, we will demonstrate the potential of MoSERS as a tool for monitoring the evolution of the GBM molecular profile in individual patients undergoing standard TMZ treatment.