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

Author

Listed:
  • Yan Zhang

    (National University of Singapore
    National University of Singapore)

  • Chi Yan Wong

    (National University of Singapore
    National University of Singapore)

  • Carine Z. J. Lim

    (National University of Singapore
    National University of Singapore)

  • Qingchang Chen

    (National University of Singapore
    National University of Singapore)

  • Zhonglang Yu

    (National University of Singapore
    National University of Singapore)

  • Auginia Natalia

    (National University of Singapore
    National University of Singapore)

  • Zhigang Wang

    (National University of Singapore)

  • Qing You Pang

    (National Neuroscience Institute)

  • See Wee Lim

    (National Neuroscience Institute)

  • Tze Ping Loh

    (National University of Singapore
    National University Hospital)

  • Beng Ti Ang

    (National Neuroscience Institute
    Duke-National University of Singapore Medical School)

  • Carol Tang

    (National Neuroscience Institute
    Duke-National University of Singapore Medical School
    Nanyang Technological University Singapore)

  • Huilin Shao

    (National University of Singapore
    National University of Singapore
    National Neuroscience Institute
    National University of Singapore)

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.

Suggested Citation

  • 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, 2023. "Multiplexed RNA profiling by regenerative catalysis enables blood-based subtyping of brain tumors," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39844-0
    DOI: 10.1038/s41467-023-39844-0
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    References listed on IDEAS

    as
    1. Melanie Si Yan Tan & Edwin Sandanaraj & Yuk Kien Chong & See Wee Lim & Lynnette Wei Hsien Koh & Wai Hoe Ng & Nguan Soon Tan & Patrick Tan & Beng Ti Ang & Carol Tang, 2019. "A STAT3-based gene signature stratifies glioma patients for targeted therapy," Nature Communications, Nature, vol. 10(1), pages 1-15, December.
    2. Huilin Shao & Jaehoon Chung & Kyungheon Lee & Leonora Balaj & Changwook Min & Bob S. Carter & Fred H. Hochberg & Xandra O. Breakefield & Hakho Lee & Ralph Weissleder, 2015. "Chip-based analysis of exosomal mRNA mediating drug resistance in glioblastoma," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
    3. Xiaoyang Lan & David J. Jörg & Florence M. G. Cavalli & Laura M. Richards & Long V. Nguyen & Robert J. Vanner & Paul Guilhamon & Lilian Lee & Michelle M. Kushida & Davide Pellacani & Nicole I. Park & , 2017. "Fate mapping of human glioblastoma reveals an invariant stem cell hierarchy," Nature, Nature, vol. 549(7671), pages 227-232, September.
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