ArticleLab on a chip2018
Ultrasensitive quantification of tumor mRNAs in extracellular vesicles with an integrated microfluidic digital analysis chip.
Article in Lab on a chip, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.
- Extracellular Vesicles: A New Source of Biomarkers in Pediatric Solid Tumors? A Systematic Review.Frontiers in oncology · 2022Pooled it
- Tumor Extracellular Vesicle Digital Scoring Assays for Cancer Detection and Monitoring.Precision chemistry · 2025Review
- Extracellular Vesicles for Clinical Diagnostics: From Bulk Measurements to Single-Vesicle Analysis.ACS nano · 2025Review
- Microfluidic Devices for Manufacture of Therapeutic Extracellular Vesicles: Advances and Opportunities.Journal of extracellular vesicles · 2025Review
- Partition-Less Digital Immunoassay Using Configurable Topographic Nanoarrays for Extracellular Vesicle Diagnosis of Ewing Sarcoma.ACS nano · 2025Article
- Microfluidic devices for on-chip quantification of extracellular vesicles and associated biomarkers.Extracellular vesicles and circulating nucleic acids · 2025Review
- Hydromechanical Modulation of Enzymatic Kinetics Using Microfluidically Configurable Nanoconfinement Arrays.ACS central science · 2024Article
- Metal-organic framework-interfaced ELISA probe enables ultrasensitive detection of extracellular vesicle biomarkers.Journal of materials chemistry. B · 2024Article
- Exosome-Based Liquid Biopsy Approaches in Bone and Soft Tissue Sarcomas: Review of the Literature, Prospectives, and Hopes for Clinical Application.International journal of molecular sciences · 2023Review
- Identification of small extracellular vesicle protein biomarkers for pediatric Ewing Sarcoma.Frontiers in molecular biosciences · 2023Article
- Microfluidic Strategies for Extracellular Vesicle Isolation: Towards Clinical Applications.Biosensors · 2022Review
- Cancer-Derived Extracellular Vesicles: Their Role in Sarcoma.Life (Basel, Switzerland) · 2022Review
- MicroRNA Content of Ewing Sarcoma Derived Extracellular Vesicles Leads to Biomarker Potential and Identification of a Previously Undocumented EWS-FLI1 Translocation.Biomarker insights · 2022Article
- Advances in microfluidic extracellular vesicle analysis for cancer diagnostics.Lab on a chip · 2021Review
- Emerging methods in biomarker identification for extracellular vesicle-based liquid biopsy.Journal of extracellular vesicles · 2021Review
- Ultrafast Detection of Exosomal RNAsACS applied nano materials · 2021Article
- Coupling Nanostructured Microchips with Covalent Chemistry Enables Purification of Sarcoma-Derived Extracellular Vesicles for Downstream Functional Studies.Advanced functional materials · 2020Article
- Ewing sarcoma family of tumors-derived small extracellular vesicle proteomics identify potential clinical biomarkers.Oncotarget · 2020Article
- Sensor-Integrated Microfluidic Approaches for Liquid Biopsies Applications in Early Detection of Cancer.Sensors (Basel, Switzerland) · 2020Review
- Latest advances in extracellular vesicles: from bench to bedside.Science and technology of advanced materials · 2019Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Extracellular vesicles (EVs) present a promising liquid biopsy for cancer diagnosis. However, it remains a daunting challenge to quantitatively measure molecular contents of EVs including tumor-associated mRNAs. Herein, we report a configurable microwell-patterned microfluidic digital analysis platform combined with a dual-probe hybridization assay for PCR-free, single-molecule detection of specific mRNAs in EVs. The microwell array in our device is configurable between the flow-through assay mode for enhanced hybridization capture and tagging of mRNAs and the digital detection mode based on femtoliter-scale enzymatic signal amplification for single-molecule counting of surface-bound targets. Furthermore, a dual-probe hybridization assay has been developed to enhance the sensitivity of the digital single-molecule detection of EV mRNAs. Combining the merits of the chip design and the dual-probe digital mRNA hybridization assay, the integrated microfluidic system has been demonstrated to afford quantitative detection of synthetic GAPDH mRNA with a LOD as low as 20 aM. Using this technology, we quantified the level of GAPDH and EWS-FLI1 mRNAs in EVs derived from two cell lines of peripheral primitive neuroectodermal tumor (PNET), CHLA-9 and CHLA-258. Our measurements detected 64.6 and 43.5 copies of GAPDH mRNA and 6.5 and 0.277 copies of EWS-FLI1 fusion transcripts per 105 EVs derived from CHLA-9 and CHLA-258 cells, respectively. To our knowledge, this is the first demonstration of quantitative measurement of EWS-FLI1 mRNA copy numbers in Ewing Sarcoma (EWS)-derived EVs. These results highlight the ultralow frequency of tumor-specific mRNA markers in EVs and the necessity of developing highly sensitive methods for analysis of EV mRNAs. The microfluidic digital mRNA analysis platform presented here would provide a useful tool to facilitate quantitative analysis of tumor-associated EV mRNAs for liquid biopsy-based cancer diagnosis and monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.