Evidence map›Paper›PMID 40115997›Full record

ArticleACS nano2025

Partition-Less Digital Immunoassay Using Configurable Topographic Nanoarrays for Extracellular Vesicle Diagnosis of Ewing Sarcoma.

Yunjie Wen, Yutao Li, Shibo Cheng, Jennifer Crow, Glenson Samuel, Vikalp Vishwakarma, Soumya M Turaga, Leonidas Bantis, Andrew K Godwin, Yong Zeng

Abstract read
In one paragraph

Article in ACS nano, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yunjie WenDepartment of Chemistry, University of Florida, Gainesville, Florida 32611, United States.ORCID 0009-0006-4319-9883
Yutao LiDepartment of Chemistry, University of Florida, Gainesville, Florida 32611, United States.
Shibo ChengDepartment of Chemistry, University of Florida, Gainesville, Florida 32611, United States.
Jennifer CrowDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas 66103, United States.
Glenson SamuelChildren's Mercy─Kansas City, Kansas City, Missouri 64108, United States.
Vikalp VishwakarmaDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas 66103, United States.
Soumya M TuragaDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas 66103, United States.ORCID 0000-0002-1933-2764
Leonidas BantisDepartment of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas 66160, United States.
Andrew K GodwinDepartment of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas 66103, United States.ORCID 0000-0002-3987-9580
Yong ZengDepartment of Chemistry, University of Florida, Gainesville, Florida 32611, United States.ORCID 0000-0003-0537-109X

Funding

Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
Using Integrated Omics to Identify Dysfunctional Genetic Mechanisms Influencing Schizophrenia and Sleep DisturbancesP20GM130423 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI Kalyani Pyaram, Steven Allan Soper · 2019 to 2026
$21.5M
Extracellular Vesicle Proteomic Fingerprinting of Ovarian Cancer for Early Detection with a Nanoengineered MicrosystemR01CA260132 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI GODWIN, ANDREW K., ZENG, YONG · 2021 to 2025
$3.4M
Nano-Engineered Lab-on-a-Chip for Assessing HuR-Regulated Exosomes for Cancer Monitoring and Targeted TherapyR01CA243445 · NCI · UNIVERSITY OF KANSAS LAWRENCE · PI DIXON, DAN ALAN, XU, LIANG · 2019 to 2023
$3.0M
Integrated exosomes profiling for minimally invasive diagnosis and monitoring of cancerR33CA214333 · NCI · UNIVERSITY OF KANSAS LAWRENCE · PI GODWIN, ANDREW K., ZENG, YONG · 2017 to 2019
$1.2M
Integrative Functional Profiling of Tumor-Derived Extracellular VesiclesR33CA252158 · NCI · UNIVERSITY OF FLORIDA · PI XU, LIANG, ZENG, YONG · 2021 to 2024
$1.0M
NCI NIH HHS P30 CA168524NCI NIH HHS R01 CA243445NCI NIH HHS R01 CA260132NCI NIH HHS R33 CA214333NCI NIH HHS R33 CA252158NIGMS NIH HHS P20 GM130423
6 · The paper itself

Abstract

Emerging digital bioassays provide opportunities for bioanalysis and clinical diagnostics due to their improved analytical performance. Prevailing digitization strategies rely on partitioning single molecules into discrete compartments for which bead-based capture may be used. Herein we report a partition-free digital enzyme-linked immunosorbent assay (dELISA) named microfluidic Topographically Intensified, Partition-less dELISA (μTIP-dELISA). Our method builds on a single-molecule signal amplification technique that employs a simple micropost device to generate a topographic nanogap array to significantly enhance surface-bound enzymatic reactions. Compared to existing dELISA methods, our approach features appreciable simplicity and enhanced adaptability as it obviates the needs for sophisticated device fabrication, complicated workflow for off-line immunomagnetic capture, and ultralow-volume compartmentalization. Moreover, μTIP-dELISA integrates the inherent advantages of microfluidics in improving the assay performance and throughput and enhancing the scalability and automation. As a proof-of-concept for potential biomedical applications, we adapted μTIP-dELISA to extracellular vesicle (EV)-based liquid biopsy diagnosis of a pediatric cancer, Ewing sarcoma (EWS). Our technology confers >300-fold improvement over the conventional ELISA in detecting four EWS protein biomarkers. We demonstrated highly sensitive and specific detection of EWS cases with a machine-learning-defined four-marker EV signature. The four EV markers were further tested to assess age as a prognostic factor, resulting in an overall accuracy of 97% for classifying the control, pediatric and adult subjects. Overall, we envision that our μTIP single-molecule signal amplification strategy could promote the development and adaptation of digital bioassays and that the μTIP-dELISA could provide a useful tool for clinical diagnostics for many malignancies.

Indexed as

Extracellular VesiclesSarcoma, EwingChildEnzyme-Linked Immunosorbent AssayHumansImmunoassaydigital bioassaysEwing sarcoma diagnosisextracellular vesiclepartition-less dELISAsingle-molecule signal amplification

Identifiers

PMID40115997
PMCPMC13632777

What OpenQuestion holds

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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.