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

Abstract 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 characteriz...

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Bibliographic Details
Main Authors: Yan Zhang, Chi Yan Wong, Carine Z. J. Lim, Qingchang Chen, Zhonglang Yu, Auginia Natalia, Zhigang Wang, Qing You Pang, See Wee Lim, Tze Ping Loh, Beng Ti Ang, Carol Tang, Huilin Shao
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-023-39844-0
Description
Summary:Abstract 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.
ISSN:2041-1723