Evidence map›Paper›PMID 40311616›Full record

ArticleCell reports. Medicine2025

Integrative proteomic profiling of tumor and plasma extracellular vesicles identifies a diagnostic biomarker panel for colorectal cancer.

Jun Wang, Chen-Zheng Gu, Peng-Xiang Wang, Jing-Rong Xian, Hao Wang, An-Quan Shang, Yu-Chen Zhong, Wen-Jing Zheng, Jian-Wen Cheng, Wen-Jing Yang and 5 more

Abstract read
In one paragraph

Article in Cell reports. Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  6. [The Clinical Application and Development of Tumor Biomarkers in China].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026
    Review
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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

15 authors.

Jun WangDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China; Department of Chemistry, Institutes of Biomedical Sciences and Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, P.R. China.
Chen-Zheng GuDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
Peng-Xiang WangDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
Jing-Rong XianDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
Hao WangDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
An-Quan ShangDepartment of Laboratory Medicine, Lianyungang Clinical College of Jiangsu University, Lianyungang, 222006, P.R. China.
Yu-Chen ZhongDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
Wen-Jing ZhengDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
Jian-Wen ChengDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
Wen-Jing YangDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China.
Jian ZhouDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
Jia FanDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China.
Wei GuoDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China; Department of Laboratory Medicine, Shanghai Geriatric Medical Center, Shanghai 200032, P.R. China; Department of Laboratory Medicine, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, P.R. China; Department of Laboratory Medicine, Wusong Branch, Zhongshan Hospital, Fudan University, Shanghai 200032, P.R. China. Electronic address: guo.wei@zs-hospital.sh.cn.
Xin-Rong YangDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China. Electronic address: yang.xinrong@zs-hospital.sh.cn.
Hao-Jie LuDepartment of Liver Surgery & Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Shanghai 200032, P.R. China; Department of Chemistry, Institutes of Biomedical Sciences and Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200032, P.R. China. Electronic address: luhaojie@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lack of reliable non-invasive biomarkers for early colorectal cancer (CRC) diagnosis underscores the need for improved diagnostic tools. Extracellular vesicles (EVs) have emerged as promising candidates for liquid-biopsy-based cancer monitoring. Here, we propose a comprehensive workflow that integrates staged mass spectrometry (MS)-based discovery and verification with ELISA-based validation to identify EV protein biomarkers for CRC. Our approach, applied to 1,272 individuals, yields a machine learning model, ColonTrack, incorporating EV proteins HNRNPK, CTTN, and PSMC6. ColonTrack effectively distinguishes CRC from non-CRC cases and identifies early-stage CRC with high accuracy (combined area under the curve [AUC] >0.97, sensitivity ∼0.94, specificity ∼0.93). Our analysis of EV protein profiles from tissue and plasma demonstrates ColonTrack's potential as a robust non-invasive biomarker panel for CRC diagnosis and early detection.

Indexed as

Biomarkers, TumorColorectal NeoplasmsExtracellular VesiclesProteomicsAgedEarly Detection of CancerFemaleHumansMaleMass SpectrometryMiddle AgedBiomarkers, Tumordiagnostic biomarker panelearly diagnosis of colorectal cancermachine learningproteomicstissue extracellular vesicles

Identifiers

PMID40311616
PMCPMC12147850

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.