Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Amplifying mutational profiling of extracellular vesicle mRNA with SCOPE

Nature Biotechnology volume 43, pages 1485–1495 (2025)Cite this article

Subjects

Abstract

Sequencing of messenger RNA (mRNA) found in extracellular vesicles (EVs) in liquid biopsies can provide clinical information such as somatic mutations, resistance profiles and tumor recurrence. Despite this, EV mRNA remains underused due to its low abundance in liquid biopsies, and large sample volumes or specialized techniques for analysis are required. Here we introduce Self-amplified and CRISPR-aided Operation to Profile EVs (SCOPE), a platform for EV mRNA detection. SCOPE leverages CRISPR-mediated recognition of target RNA using Cas13 to initiate replication and signal amplification, achieving a sub-attomolar detection limit while maintaining single-nucleotide resolution. As a proof of concept, we designed probes for key mutations in KRAS, BRAF, EGFR and IDH1 genes, optimized protocols for single-pot assays and implemented an automated device for multi-sample detection. We validated SCOPE’s ability to detect early-stage lung cancer in animal models, monitored tumor mutational burden in patients with colorectal cancer and stratified patients with glioblastoma. SCOPE can expedite readouts, augmenting the clinical use of EVs in precision oncology.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: SCOPE.
Fig. 2: SCOPE device engineering.
Fig. 3: SCOPE assay kinetics.
Fig. 4: SCOPE assay characterization.
Fig. 5: Early cancer detection with SCOPE.
Fig. 6: Monitoring patients with CRC.

Similar content being viewed by others

Data availability

The mRNA target sequences were obtained from the National Center for Biotechnology Informationʼs Reference Sequence database (accession codes: NC_000002.12, NC_00007.14 and NC_000012.12). The primary data supporting assay characterization are accessible in a source data file and in Supplementary Information. Raw patient datasets generated and analyzed during this study are available from the corresponding authors upon reasonable request, subject to approval from the institutional review board of Massachusetts General Hospital (MGH) and the MGH Innovation Office. Data access requests will be considered from academic investigators without relevant conflicts of interest, for non-commercial use, who agree to non-distribution terms. Source data are provided with this paper.

References

  1. Ignatiadis, M., Sledge, G. W. & Jeffrey, S. S. Liquid biopsy enters the clinic—implementation issues and future challenges. Nat. Rev. Clin. Oncol. 18, 297–312 (2021).

    Article  PubMed  Google Scholar 

  2. Heitzer, E., Haque, I. S., Roberts, C. E. S. & Speicher, M. R. Current and future perspectives of liquid biopsies in genomics-driven oncology. Nat. Rev. Genet. 20, 71–88 (2019).

    Article  PubMed  CAS  Google Scholar 

  3. Killingsworth, B., Welsh, J. A. & Jones, J. C. EV translational horizons as viewed across the complex landscape of liquid biopsies. Front. Cell Dev. Biol. 9, 556837 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Parikh, A. R. et al. Liquid versus tissue biopsy for detecting acquired resistance and tumor heterogeneity in gastrointestinal cancers. Nat. Med. 25, 1415–1421 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Pantel, K. & Alix-Panabières, C. Liquid biopsy and minimal residual disease—latest advances and implications for cure. Nat. Rev. Clin. Oncol. 16, 409–424 (2019).

    Article  PubMed  CAS  Google Scholar 

  6. Siravegna, G., Marsoni, S., Siena, S. & Bardelli, A. Integrating liquid biopsies into the management of cancer. Nat. Rev. Clin. Oncol. 14, 531–548 (2017).

    Article  PubMed  CAS  Google Scholar 

  7. Shao, H. et al. New technologies for analysis of extracellular vesicles. Chem. Rev. 118, 1917–1950 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Im, H. et al. Label-free detection and molecular profiling of exosomes with a nano-plasmonic sensor. Nat. Biotechnol. 32, 490–495 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Jo, A. et al. Inaugurating high-throughput profiling of extracellular vesicles for earlier ovarian cancer detection. Adv. Sci. 10, e2301930 (2023).

    Article  Google Scholar 

  10. Dixson, A. C., Dawson, T. R., Di Vizio, D. & Weaver, A. M. Context-specific regulation of extracellular vesicle biogenesis and cargo selection. Nat. Rev. Mol. Cell Biol. 24, 454–476 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Skog, J. et al. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat. Cell Biol. 10, 1470–1476 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Vitale, S. R. et al. Detection of tumor-derived extracellular vesicles in plasma from patients with solid cancer. BMC Cancer 21, 315 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. van de Haar, J. et al. Codon-specific KRAS mutations predict survival benefit of trifluridine/tipiracil in metastatic colorectal cancer. Nat. Med. 29, 605–614 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Shao, H. et al. Chip-based analysis of exosomal mRNA mediating drug resistance in glioblastoma. Nat. Commun. 6, 6999 (2015).

    Article  PubMed  CAS  Google Scholar 

  15. Park, J. et al. An integrated magneto-electrochemical device for the rapid profiling of tumour extracellular vesicles from blood plasma. Nat. Biomed. Eng. 5, 678–689 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Noerholm, M. et al. RNA expression patterns in serum microvesicles from patients with glioblastoma multiforme and controls. BMC Cancer 12, 22 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Wei, Z. et al. Coding and noncoding landscape of extracellular RNA released by human glioma stem cells. Nat. Commun. 8, 1145 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Hong, J. S., Son, T., Castro, C. M. & Im, H. CRISPR/Cas13a-based microRNA detection in tumor-derived extracellular vesicles. Adv. Sci. 10, e2301766 (2023).

    Article  Google Scholar 

  19. Yan, H. et al. A one-pot isothermal Cas12-based assay for the sensitive detection of microRNAs. Nat. Biomed. Eng. 7, 1583–1601 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Ramshani, Z. et al. Extracellular vesicle microRNA quantification from plasma using an integrated microfluidic device. Commun. Biol. 2, 189 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Li, Y. et al. EV-origin: enumerating the tissue-cellular origin of circulating extracellular vesicles using exLR profile. Comput. Struct. Biotechnol. J. 18, 2851–2859 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Pickar-Oliver, A. & Gersbach, C. A. The next generation of CRISPR–Cas technologies and applications. Nat. Rev. Mol. Cell Biol. 20, 490–507 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Kaminski, M. M., Abudayyeh, O. O., Gootenberg, J. S., Zhang, F. & Collins, J. J. CRISPR-based diagnostics. Nat. Biomed. Eng. 5, 643–656 (2021).

    Article  PubMed  CAS  Google Scholar 

  24. Abudayyeh, O. O. & Gootenberg, J. S. CRISPR diagnostics. Science 372, 914–915 (2021).

    Article  PubMed  CAS  Google Scholar 

  25. Potapov, V. & Ong, J. L. Examining sources of error in PCR by single-molecule sequencing. PLoS ONE 12, e0169774 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Kebschull, J. M. & Zador, A. M. Sources of PCR-induced distortions in high-throughput sequencing data sets. Nucleic Acids Res. 43, e143 (2015).

    PubMed  PubMed Central  Google Scholar 

  27. Gootenberg, J. S. et al. Nucleic acid detection with CRISPR–Cas13a/C2c2. Science 356, 438–442 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Truong, N. P., Jia, Z., Burges, M., McMillan, N. A. & Monteiro, M. J. Self-catalyzed degradation of linear cationic poly(2-dimethylaminoethyl acrylate) in water. Biomacromolecules 12, 1876–1882 (2011).

    Article  PubMed  CAS  Google Scholar 

  29. Maslak, M. & Martin, C. T. Kinetic analysis of T7 RNA polymerase transcription initiation from promoters containing single-stranded regions. Biochemistry 32, 4281–4285 (1993).

    Article  PubMed  CAS  Google Scholar 

  30. Avaro, A. S. & Santiago, J. G. Uncertainty quantification of Michaelis-Menten kinetic rates and its application to the analysis of CRISPR-based diagnostics. Angew. Chem. Int. Ed. Engl. 61, e202209527 (2022).

    Article  PubMed  CAS  Google Scholar 

  31. Newman, A. M. et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat. Med. 20, 548–554 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Diehl, F. et al. Detection and quantification of mutations in the plasma of patients with colorectal tumors. Proc. Natl Acad. Sci. USA 102, 16368–16373 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Li, R. et al. Therapeutically reprogrammed nutrient signalling enhances nanoparticulate albumin bound drug uptake and efficacy in KRAS-mutant cancer. Nat. Nanotechnol. 16, 830–839 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Pfirschke, C. et al. Immunogenic chemotherapy sensitizes tumors to checkpoint blockade therapy. Immunity 44, 343–354 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. DuPage, M., Dooley, A. L. & Jacks, T. Conditional mouse lung cancer models using adenoviral or lentiviral delivery of Cre recombinase. Nat. Protoc. 4, 1064–1072 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Mendiratta, G. et al. Cancer gene mutation frequencies for the U.S. population. Nat. Commun. 12, 5961 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Welsh, J. A. et al. Minimal information for studies of extracellular vesicles (MISEV2023): from basic to advanced approaches. J. Extracell. Vesicles 13, e12404 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Weller, M. et al. EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat. Rev. Clin. Oncol. 18, 170–186 (2021).

    Article  PubMed  Google Scholar 

  39. Guo, G. et al. Ligand-independent EGFR signaling. Cancer Res. 75, 3436–3441 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  40. Chen, W. W. et al. BEAMing and droplet digital PCR analysis of mutant IDH1 mRNA in glioma patient serum and cerebrospinal fluid extracellular vesicles. Mol. Ther. Nucleic Acids 2, e109 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  41. SongTao, Q. et al. IDH mutations predict longer survival and response to temozolomide in secondary glioblastoma. Cancer Sci. 103, 269–273 (2012).

    Article  PubMed  Google Scholar 

  42. Batool, S. M. et al. Highly sensitive EGFRvIII detection in circulating extracellular vesicle RNA of glioma patients. Clin. Cancer Res. 28, 4070–4082 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Krug, A. K. et al. Improved EGFR mutation detection using combined exosomal RNA and circulating tumor DNA in NSCLC patient plasma. Ann. Oncol. 29, 700–706 (2018).

    Article  PubMed  CAS  Google Scholar 

  44. Srivastava, P. & Prasad, D. Isothermal nucleic acid amplification and its uses in modern diagnostic technologies. 3 Biotech 13, 200 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Ueda, T., Tohda, H., Chikazumi, N., Eckstein, F. & Watanabe, K. Phosphorothioate-containing RNAs show mRNA activity in the prokaryotic translation systems in vitro. Nucleic Acids Res. 19, 547–552 (1991).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Lane, R. E., Korbie, D., Trau, M. & Hill, M. M. Optimizing size exclusion chromatography for extracellular vesicle enrichment and proteomic analysis from clinically relevant samples. Proteomics 19, e1800156 (2019).

    Article  PubMed  Google Scholar 

  47. Lee, K. et al. Multiplexed profiling of single extracellular vesicles. ACS Nano 12, 494–503 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Zhang, J. et al. Engineering a tunable micropattern-array assay to sort single extracellular vesicles and particles to detect RNA and protein in situ. J. Extracell. Vesicles 12, e12369 (2023).

    Article  PubMed  Google Scholar 

  49. Schraa, S. J. et al. Circulating tumor DNA guided adjuvant chemotherapy in stage II colon cancer (MEDOCC-CrEATE): study protocol for a trial within a cohort study. BMC Cancer 20, 790 (2020).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Koga, T. et al. Mapping of genomic EGFRvIII deletions in glioblastoma: insight into rearrangement mechanisms and biomarker development. Neuro Oncol. 20, 1310–1320 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Muralidharan, K. et al. TERT promoter mutation analysis for blood-based diagnosis and monitoring of gliomas. Clin. Cancer Res. 27, 169–178 (2021).

    Article  PubMed  CAS  Google Scholar 

  52. Shen, S. Y. et al. Sensitive tumour detection and classification using plasma cell-free DNA methylomes. Nature 563, 579–583 (2018).

    Article  PubMed  CAS  Google Scholar 

  53. Chang, M. T. et al. Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity. Nat. Biotechnol. 34, 155–163 (2016).

    Article  PubMed  CAS  Google Scholar 

  54. Miller, M. L. et al. Pan-cancer analysis of mutation hotspots in protein domains. Cell Syst. 1, 197–209 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Sequist, L. V. et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci. Transl. Med. 3, 75ra26 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Krook, M. A. et al. Fibroblast growth factor receptors in cancer: genetic alterations, diagnostics, therapeutic targets and mechanisms of resistance. Br. J. Cancer 124, 880–892 (2021).

    Article  PubMed  CAS  Google Scholar 

  57. Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359, 926–930 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Gootenberg, J. S. et al. Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science 360, 439–444 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

We thank X. O. Breakefield (Massachusetts General Hospital (MGH)) for helpful discussions. This work was supported, in part, by National Institutes of Health (NIH) grants 1U01CA279858 (C.M.C. and H.L.), U01CA284982 (H.L. and C.M.C.), R01CA229777 (H.L.), R01CA239078 (H.L.), R01HL163513 (H.L.), R01CA237500 (H.L.), R21CA267222 (H.L.), R01CA264363 (C.M.C., H.L.), R01GM138790 (M.A.M.) and DP2CA259675 (M.A.M.); the MGH Scholar Fund (H.L.); National Research Foundation (NRF) of Korea grants 2021R1A2C1005342 (S.Y.P.), 2021R1A2B5B03001416 (S.G.I.), 2021M3H4A1A02051048 (T.K.), 2023R1A2C2005185 (T.K.) and RS-2024-00438316 (T.K.); Korea Environmental Industry & Technology Institute (KEITI) grants 2021003370003 (T.K.), RS-2022-00154853 (T.K.) and RS-2024-00432382 (T.K.); the Nanomedical Devices Development Program of the National NanoFab Center (NNFC) (T.K.); Korea Research Institute of Bioscience and Biotechnology (KRIBB) Research Initiative Program KGM5472413 (T.K.); and Korea Health Industry Development Institute (KHIDI) grant HR22C1832 (J.S.P.).

Author information

Authors and Affiliations

  1. Center for Systems Biology, Massachusetts General Hospital Research Institute, Boston, MA, USA

    Jayeon Song, Mi Hyeon Cho, Hayoung Cho, Jae-Sang Hong, Jueun Jeon, Dong Gil You, Miles A. Miller, Cesar M. Castro & Hakho Lee

  2. Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Jayeon Song, Mi Hyeon Cho, Jae-Sang Hong, Jueun Jeon, Miles A. Miller & Hakho Lee

  3. Department of Forensic Sciences, Sungkyunkwan University, Suwon, Republic of Korea

    Jayeon Song

  4. School of Pharmacy, Sungkyunkwan University, Suwon, Republic of Korea

    Jayeon Song & Taejoon Kang

  5. Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

    Younseong Song & Sung Gap Im

  6. RevoSketch, Inc., Daejeon, Republic of Korea

    Sung Woon Lee, Ho Chul Nam, Tae Ho Yoon & Jong Cheol Shin

  7. Research Institute of Aging and Metabolism, Kyungpook National University, Daegu, Republic of Korea

    Yejin Kim

  8. Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA

    Emil Ekanayake, Dong Gil You, Bob C. Carter & Leonora Balaj

  9. Colorectal Cancer Center, Kyungpook National University Chilgok Hospital, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

    Gyu-Seog Choi, Jun Seok Park & Soo Yeun Park

  10. Department of Pathology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, Republic of Korea

    An Na Seo

  11. Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea

    Taejoon Kang

  12. Cancer Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Cesar M. Castro

  13. Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, Republic of Korea

    Hakho Lee

Authors
  1. Jayeon Song
    View author publications

    Search author on:PubMed Google Scholar

  2. Mi Hyeon Cho
    View author publications

    Search author on:PubMed Google Scholar

  3. Hayoung Cho
    View author publications

    Search author on:PubMed Google Scholar

  4. Younseong Song
    View author publications

    Search author on:PubMed Google Scholar

  5. Sung Woon Lee
    View author publications

    Search author on:PubMed Google Scholar

  6. Ho Chul Nam
    View author publications

    Search author on:PubMed Google Scholar

  7. Tae Ho Yoon
    View author publications

    Search author on:PubMed Google Scholar

  8. Jong Cheol Shin
    View author publications

    Search author on:PubMed Google Scholar

  9. Jae-Sang Hong
    View author publications

    Search author on:PubMed Google Scholar

  10. Yejin Kim
    View author publications

    Search author on:PubMed Google Scholar

  11. Emil Ekanayake
    View author publications

    Search author on:PubMed Google Scholar

  12. Jueun Jeon
    View author publications

    Search author on:PubMed Google Scholar

  13. Dong Gil You
    View author publications

    Search author on:PubMed Google Scholar

  14. Sung Gap Im
    View author publications

    Search author on:PubMed Google Scholar

  15. Gyu-Seog Choi
    View author publications

    Search author on:PubMed Google Scholar

  16. Jun Seok Park
    View author publications

    Search author on:PubMed Google Scholar

  17. Bob C. Carter
    View author publications

    Search author on:PubMed Google Scholar

  18. Leonora Balaj
    View author publications

    Search author on:PubMed Google Scholar

  19. An Na Seo
    View author publications

    Search author on:PubMed Google Scholar

  20. Miles A. Miller
    View author publications

    Search author on:PubMed Google Scholar

  21. Soo Yeun Park
    View author publications

    Search author on:PubMed Google Scholar

  22. Taejoon Kang
    View author publications

    Search author on:PubMed Google Scholar

  23. Cesar M. Castro
    View author publications

    Search author on:PubMed Google Scholar

  24. Hakho Lee
    View author publications

    Search author on:PubMed Google Scholar

Contributions

J.S., T.K., C.M.C. and H.L. developed the concept and designed the study. J.S., M.H.C., H.C., J.-S.H. and J.J. performed the experiments. M.H.C., H.L. and M.A.M. designed and analyzed the animal model studies. Y.S. and S.G.I. prepared the pDMAEA-coated tube. S.W.L., H.C.N., T.H.Y., J.C.S. and H.L. designed the SCOPE device. E.E., D.G.Y., B.C.B. and L.B. collected blood samples from patients with GBM and analyzed their tissue samples. Y.K., G.-S.C., J.S.P., A.N.S. and S.Y.P. collected blood samples from patients with CRC and analyzed their tissue samples. J.S., T.K., C.M.C. and H.L. wrote the paper, with input from all authors.

Corresponding authors

Correspondence to Taejoon Kang, Cesar M. Castro or Hakho Lee.

Ethics declarations

Competing interests

J.S., T.K., C.M.C. and H.L. declare the filing of a provisional patent that was assigned to and handled by Massachusetts General Hospital and the Korea Research Institute of Bioscience and Biotechnology. M.A.M. declares research support from Ionis Pharmaceuticals, Genentech and Pfizer, all of which are unrelated to the present paper. The other authors declare no competing interests.

Peer review

Peer review information

Nature Biotechnology thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Stratifying glioma patients.

(a) SCOPE analyzed plasma samples collected from radiologically confirmed glioma patients. Tissue samples were used for clinical pathology. (b) Target RNA sequences for glioma-SCOPE analyses. IDH1 probes were designed to detect wild-type (WT) and single nucleotide mutation (R132H), and EGFR probes to detect WT as well as the variant III (EGFRvIII) resulting from genomic deletion of exons 2–7 in the EGFR gene. (c) The specificity of glioma-SCOPE probes was evaluated. The designed probes achieved a high signal contrast (>30) between on-target and off-target samples. Synthetic RNA samples (1 nM) were used. The heatmap displays mean values from technical triplicate measurements. a.u., arbitrary unit. (d) Application of SCOPE to profile EVs for IDH1 (WT, R132H) and EGFR (WT, vIII). EVs were harvested from glioma cell lines. The results confirmed that EVs reflected the genotype of parent glioma cells. Data are shown as mean ± s.d. from biological triplicates. a.u., arbitrary unit. (e) Plasma EVs were analyzed via SCOPE for IDH1 (WT, R132H) and EGFR (WT, vIII). Control samples were from healthy donors (n = 15). Glioma samples were from patients with different genotypes: EGFR amplification (GBM-WT; n = 20), IDH1-R132H mutation (n = 20), and EGFRvIII mutation (n = 20). The SCOPE assay identified glioma patients and correctly stratified them according to their molecular genotypes. The heatmap shows mean values from technical triplicate measurements.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–25, Tables 1–5, Note and references.

Reporting Summary

Source data

Source Data Figs. 2–5 and Extended Data Fig. 1

Statistical source data (with a named tab).

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, J., Cho, M.H., Cho, H. et al. Amplifying mutational profiling of extracellular vesicle mRNA with SCOPE. Nat Biotechnol 43, 1485–1495 (2025). https://doi.org/10.1038/s41587-024-02426-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41587-024-02426-6

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing