Multiplexed RNA profiling by regenerative catalysis enables blood-based subtyping of brain tumors

Current technologies to subtype glioblastoma (GBM), the most lethal brain tumor, require highly invasive brain biopsies. Here, we develop a dedicated analytical platform to achieve direct and multiplexed profiling of circulating RNAs in extracellular vesicles for blood-based GBM characterization. The technology, termed 'enzyme ZIF-8 complexes for regenerative and catalytic digital detection of RNA' (EZ-READ), leverages an RNA-responsive transducer to regeneratively convert and catalytically enhance signals from rare RNA targets. Each transducer comprises hybrid complexes - protein enzymes encapsulated within metal organic frameworks - to configure strong catalytic activity and robust protection. Upon target RNA hybridization, the transducer activates directly to liberate catalytic complexes, in a target-recyclable manner; when partitioned within a microfluidic device, these complexes can individually catalyze strong chemifluorescence reactions for digital RNA quantification. The EZ-READ platform thus enables programmable and reliable RNA detection, across different-sized RNA subtypes (miRNA and mRNA), directly in sample lysates. When clinically evaluated, the EZ-READ platform established composite signatures for accurate blood-based GBM diagnosis and subtyping. Current methods to subtype brain tumors rely on invasive biopsies. Here, the authors develop a digital platform to regeneratively convert and catalytically enhance signals from rare circulating RNAs for blood-based characterization of brain tumors.

Automated summary

Current technologies to subtype glioblastoma (GBM) rely on invasive brain biopsies. In this study, the authors develop a digital platform called EZ-READ to detect and characterize GBM using circulating RNAs in extracellular vesicles. The platform utilizes an RNA-responsive transducer to convert and enhance signals from rare RNA targets, allowing for programmable and reliable RNA detection directly in blood samples. When evaluated clinically, the EZ-READ platform shows promising results for accurate blood-based diagnosis and subtyping of GBM.