(Invited) liquid Biopsy Tool: Integrated Aiot Digital Bead-Based Sensor for Molecular-Fingerprint Profiling of Extracellular Vesicles

Abstract

Development of liquid biopsies for non-invasive tumor characterization techniques shows great promise for real-time monitoring of tumor recurrence, progression, and treatment response. To better assess the various tumor evolution, cellular heterogeneity, consequent drug-resistance mechanisms, it is critical to screen proteins and nucleic acids of extracellular vesicles (EVs) in biofluids. We are developing an integrated sensitive digital bead-based sensor enabling evaluation of molecular profiling of extracellular vesicles in glioblastoma. The tumor relevant genetic information in EVs is enriched by antibody-specific magnetic beads and amplified by reverse transcription recombinase polymerase amplification with CRISPR/Cas13a system in twenty-five thousand droplets, and results are analyzed by a miniaturized imaging device. The niches of our developing technique include a) the streamlined sample preparation process and miniaturized detection system enable the ultrasensitive detection of mRNA in extracellular vesicles within one and half hour, b) the fluorescent signal-to-noise ratio in each 40-µm sized droplet is significantly enhanced via using a simple Cas13a assay and triggering greater than 104 turnovers of fluorescent reporters on a chip, c) real-time image data are transferred to a cloud-based server to be classified with trained YOLOv5 models and RNAomic results are displayed on the Raspberry Pi touchscreen. This system allows use by lower skill health care workers. This approach can provide inexpensive, rapid, and treatment-informative diagnostics for underserved regions, and underfunded health care systems. It could be further developed for other cancers, leading up the speed of diagnosis and treatment decision-making in using liquid biopsy, thus find widespread use in global health. Figure 1