Evidence map›Paper›PMID 39487820›Full record

ArticleUnited European gastroenterology journal2025

Early colorectal cancer diagnosis: A novel methylated stool DNA model enhanced the diagnostic efficiency.

Peng Yun, Kamila Kulaixijiang, Jiang Pan, Luping Yang, Nengzhuang Wang, Zheng Xu, Yaodong Zhang, Haifang Cai, Zi-Ye Zhao, Min Zhu and 1 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in United European gastroenterology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. PRDM Proteins Orchestrate Colorectal Cancer Tumorigenesis.International journal of molecular sciences · 2026
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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

11 authors.

Peng YunReproductive Medicine Center, The First Affiliated Hospital of Naval Medical University, Shanghai, China.ORCID 0009-0006-3489-2205
Kamila KulaixijiangDepartment of Pathology, Karamay Central Hospital of Xinjiang, Karamay, China.
Jiang PanReproductive Medicine Center, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Luping YangReagent R&D Department, Xiamen Sciendox Biotechnology Co., Ltd., Xiamen, China.
Nengzhuang WangReproductive Medicine Center, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Zheng XuCentral Laboratory, Seventh People's Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yaodong ZhangReproductive Medicine Center, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
Haifang CaiReagent R&D Department, Xiamen Sciendox Biotechnology Co., Ltd., Xiamen, China.
Zi-Ye ZhaoDepartment of Colorectal Surgery and Hereditary Colorectal Cancer Registry, The First Affiliated Hospital of Naval Medical University, Shanghai, China.ORCID 0000-0002-0243-2873
Min ZhuDepartment of Pathology, Karamay Central Hospital of Xinjiang, Karamay, China.
Hongli YanReproductive Medicine Center, The First Affiliated Hospital of Naval Medical University, Shanghai, China.

Funding

National Natural Science Foundation of China 81872225National Natural Science Foundation of China 82260322National Natural Science Foundation of China 82273465Natural Science Foundation of Xinjiang Uygur Autonomous RegionNatural Science Foundation of Xinjiang Uygur Autonomous Region for Outstanding Young Scientists 2021D01E34
6 · The paper itself

Abstract

backgroundMethylated stool DNA (sDNA) is a reliable noninvasive biomarker for early colorectal cancer (CRC) diagnosis. However, there are barely any diagnostic panels that can achieve both a sensitivity and specificity exceeding 90% simultaneously.

objectiveWe aimed to identify a novel methylated sDNA panel and model for the early diagnosis of CRC.

methodsWe conducted methyl-CpG binding domain isolated genome sequencing (MiGS) on CpG island methylation phenotype (CIMP)-positive (n = 3) and CIMP-negative CRC tissues (n = 3) and their corresponding normal adjacent tissues. Subsequently, by utilizing both the aforementioned data and public datasets, we identified a set of promising methylated sDNA markers for CRC. Next, we validated 5 of these genes using pyrosequencing in CRC patients (n = 31). Then, we developed a combined diagnostic model (CDM) for CRC based on the methylation status of PRDM12, FOXE1, and SDC2 by a Training cohort (n = 231). Finally, the performance of CDM was evaluated in an independent multicenter Validation cohort (n = 800).

resultsA total of 1062 participants were included in this study. The area under the curve (AUC) of the CDM was 0.979 (95% CI: 0.960-0.997), and the optimal sensitivity and specificity were 97.35% and 99.05%, respectively, in the training cohort (n = 231). In the independent validation cohort (n = 800), the AUC was 0.950 (95% CI: 0.927-0.973), along with the optimal sensitivity of 92.75% and specificity of 97.21%. When CRC and advanced adenoma (AAD) were used as diagnostic targets, the model AUC was 0.945 (95% CI: 0.922-0.969), with an optimal sensitivity of 91.89% and a specificity of 95.21%. The model sensitivity for nonadvanced adenoma patients was 68.66%.

conclusionThe sDNA diagnostic model CDM, developed from both CIMP-P and CIMP-N, exhibited exceptional performance in CRC and could serve as a potential alternative strategy for CRC screening.

Indexed as

Biomarkers, TumorColorectal NeoplasmsDNA MethylationEarly Detection of CancerFecesAgedCpG IslandsDNA-Binding ProteinsFemaleHumansMaleMiddle AgedROC CurveSensitivity and SpecificitySyndecan-2Transcription FactorsBiomarkers, TumorDNA-Binding ProteinsSDC2 protein, humanSyndecan-2Transcription FactorsbiomarkerscarcinomaCRCearly diagnosisepigeneticsgenesgeneticsneoplasiaPRDM12screening

Identifiers

PMID39487820
PMCPMC11999042

What OpenQuestion holds

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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.