Evidence map›Paper›PMID 40130819›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Identification of Tumor-Specific Surface Proteins Enables Quantification of Extracellular Vesicle Subtypes for Early Detection of Pancreatic Ductal Adenocarcinoma.

Chen Zhao, Zhili Wang, Hyoyong Kim, Hui Kong, Junseok Lee, Jacqueline Ziqian Yang, Anmin Wang, Ryan Y Zhang, Yong Ju, Jina Kim and 18 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

28 authors.

Chen ZhaoDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.ORCID https://orcid.org/0000-0003-1324-1375
Zhili WangCAS Key Laboratory for Nano-Bio Interface, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China.
Hyoyong KimCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Hui KongDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Junseok LeeCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Jacqueline Ziqian YangCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Anmin WangDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Ryan Y ZhangCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Yong JuCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Jina KimDepartment of Urology and Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Bing FengCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Dejun LiuDepartment of Biliary-Pancreatic Surgery, Renji Hospital, Shanghai Jiaotong University, Shanghai, 200217, China.
Yating ZhangDepartment of Anesthesiology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Zhenfang WangDepartment of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
Yandong ZhangDepartment of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
Shujing GuoDepartment of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
Dekang GaoDepartment of General Surgery, Second Affiliated Hospital of Soochow University, Suzhou, 215004, China.
James S TomlinsonDepartment of Surgery, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Renjun PeiCAS Key Laboratory for Nano-Bio Interface, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China.
Jipeng WanCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
Stephen J PandolDivision of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Myung-Shin SimDepartment of Urology and Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Sungyong YouDepartment of Urology and Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Ding MaDepartment of Biliary-Pancreatic Surgery, Renji Hospital, Shanghai Jiaotong University, Shanghai, 200217, China.
Shaohua LuDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Na SunCAS Key Laboratory for Nano-Bio Interface, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, 215123, China.
Hsian-Rong TsengCalifornia NanoSystems Institute, Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.ORCID https://orcid.org/0000-0003-0942-5905
Yazhen ZhuDepartment of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.

Funding

The UCLA Center in Early Detection of Liver CancerU01CA230705 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Vatche Agopian, Samuel Wheeler French · 2018 to 2026
$6.6M
Clinical Validation Center for Hepatocellular CarcinomaU01CA271887 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI FASIHA KANWAL, JORGE A MARRERO · 2022 to 2026
$4.7M
Non-Invasive Prenatal Diagnostics Based on Circulating TrophoblastsU01EB026421 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PISARSKA, MARGARETA, TSENG, HSIAN-RONG · 2019 to 2023
$4.0M
HCC EV Digital Scoring Assay for assessing treatment response in HCC patientsR01CA253651 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AGOPIAN, VATCHE, TSENG, HSIAN-RONG · 2020 to 2024
$3.3M
Extracellular Vesicle-Based Digital Scoring Assay for Detecting Early-stage Hepatocellular CarcinomaR01CA255727 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ZHU, YAZHEN · 2021 to 2025
$3.2M
Integrated analysis of HCC CTCs for Liver Transplant Candidate SelectionR01CA246304 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AGOPIAN, VATCHE, TSENG, HSIAN-RONG · 2020 to 2024
$2.8M
Click Chemistry-Mediated Surface Protein Assay for Quantifying Subpopulations of Hepatocellular Carcinoma-associated Extracellular VesiclesR01CA277530 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Vatche Agopian, HSIAN-RONG TSENG · 2023 to 2026
$2.6M
Developing and Automating an Extracellular Vesicle-Based Test for Early Detection of Hepatocellular CarcinomaR44CA288163 · NCI · EXIMIUS DIAGNOSTICS CORP · PI CHUANG, HAN-YU, LIU, SEAN XIAO · 2023 to 2025
$2.0M
Novel circulating biomarker digital scores for assessing treatment response in liver cancerK08CA259534 · NCI · CEDARS-SINAI MEDICAL CENTER · PI YANG, JU DONG · 2022 to 2024
$807k
Novel circulating biomarker digital scores for assessing treatment response in liver cancerR21CA280444 · NCI · CEDARS-SINAI MEDICAL CENTER · PI YANG, JU DONG, ZHU, YAZHEN · 2023 to 2023
$436k
Natural Science Foundation of Hubei Province 2023AFB165NCI NIH HHS K08 CA259534NCI NIH HHS K08CA259534NCI NIH HHS R01 CA246304NCI NIH HHS R01CA246304NCI NIH HHS R01 CA253651NCI NIH HHS R01CA253651NCI NIH HHS R01CA253651-04S1NCI NIH HHS R01 CA255727NCI NIH HHS R01CA255727NCI NIH HHS R01 CA277530NCI NIH HHS R01CA277530NCI NIH HHS R21 CA280444NCI NIH HHS R21CA280444NCI NIH HHS R44 CA288163NCI NIH HHS R44CA288163NCI NIH HHS U01 CA230705NCI NIH HHS U01CA230705NCI NIH HHS U01 CA271887NCI NIH HHS U01CA271887NCI NIH HHS U01EB026421NIBIB NIH HHS U01 EB026421Science and Technology Foundation of Jiangsu Province BK20220099Youth Innovation Promotion Association CAS 2023335
6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related mortality, largely due to late-stage diagnosis. Reliable early detection methods are critically needed. PDAC-derived extracellular vesicles (EVs) carry molecules that reflect their parental tumor cells and are detectable in early disease stages, offering a promising noninvasive diagnostic approach. Here, a streamlined PDAC EV Surface Protein Assay for quantifying PDAC EV subpopulations in 300-µL plasma through a two-step workflow is presented: i) click chemistry-mediated EV enrichment using EV Click Beads and trans-cyclooctene-grafted antibodies targeting three PDAC EV-specific surface proteins (MUC1, EGFR, and TROP2), and ii) quantification of enriched PDAC EVs through reverse transcription-quantitative polymerase chain reaction. The three PDAC EV-specific surface proteins are identified using a bioinformatics framework and validated on PDAC cell lines and tissue microarrays. The resultant PDAC EV Score, derived from signals of the three PDAC EV subpopulations, demonstrates robust differentiation of PDAC patients from noncancer controls, with area under the receiver operating characteristic curves of 0.94 in the training (n = 124) and 0.93 in the validation (n = 136) cohorts. This EV-based diagnostic approach successfully exploits PDAC EV subpopulations as novel biomarkers for PDAC early detection, translating PDAC surface proteins into an EV-based liquid biopsy platform.

Indexed as

Biomarkers, TumorCarcinoma, Pancreatic DuctalEarly Detection of CancerExtracellular VesiclesMembrane ProteinsPancreatic NeoplasmsCell Line, TumorFemaleHumansMaleBiomarkers, TumorMembrane Proteinscancer diagnosisextracellular vesiclesliquid biopsypancreatic ductal adenocarcinoma

Identifiers

PMID40130819
PMCPMC12140334

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Registered trials

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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.