Evidence map›Paper›PMID 42133180›Full record

ArticleGastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association2026

Plasma proteomic signatures improve risk stratification and personalized screening for gastric cancer.

Xue Li, Wen-Hao Shi, Juan Zhu, Ying Chen, Bin Liu, Nai-Ren Zheng, Le Wang, Li Yuan, Ying-Ying Mao, Xiang-Dong Cheng and 1 more

Abstract read
In one paragraph

Article in Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Xue Li *Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.
Wen-Hao Shi *Analysis Center, Chemistry Department, Tsinghua University, Beijing, 100084, China.
Juan Zhu *Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.
Ying Chen *Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.
Bin Liu *Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.
Nai-Ren ZhengBeijing Pineal Diagnostics Company Limited, Beijing, 102206, China.
Le WangDepartment of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.
Li YuanZhejiang Key Laboratory of Prevention, Diagnosis and Therapy for Gastrointestinal Cancer, Hangzhou, 310022, Zhejiang, China.
Ying-Ying MaoDepartment of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.
Xiang-Dong ChengDepartment of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.
Ling-Bin DuDepartment of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China. dulb@zjcc.org.cn.ORCID 0000-0002-1992-7784

Funding

Healthy Zhejiang One Million People Cohort K-20230085National Natural Science Foundation of China No. 32300974National Natural Science Foundation of China No. 82404341Zhejiang Key Laboratory of Prevention, Diagnosis and Therapy for Gastrointestinal Cancer Zhejiang Key Laboratory of Prevention, Diagnosis and Therapy for Gastrointestinal Cancer
6 · The paper itself

Abstract

backgroundAccurate identification of individuals at high risk of gastric cancer (GC) remains a major challenge for effective screening. We aimed to identify plasma proteomic signatures and develop a risk prediction model for GC risk stratification.

methodsPlasma proteomic profiling was performed using liquid chromatography-tandem mass spectrometry in a case-control discovery set (100 GC cases and 94 controls). Candidate proteins were evaluated in 52,552 UK Biobank participants with a median follow-up of 13.63 years, during which 92 incident GC cases were identified. Risk models integrating clinical, genetic, and proteomic factors were developed using LASSO-penalized Cox regression with stability selection and internally validated using bootstrap resampling.

resultsAmong 2306 differentially expressed proteins in discovery, 25 were replicated in validation at nominal significance (P < 0.05) with consistent directions. Two proteins (CTSD and GGH) remained significant after false discovery rate correction. A primary proteomic model (clinical factors plus five proteins) improved discrimination versus clinical model (optimism-corrected C-index: 0.745 vs. 0.732, P = 0.046). Risk stratification revealed a clear GC risk gradient: hazard ratios were 6.08 (95% CI 2.15-17.20) for moderate-risk and 23.88 (95% CI 8.66-65.87) for high-risk groups. The risk score was also associated with GC risk as continuous variable (HR per standard deviation: 1.09, 95% CI 1.08-1.11). The 15-year cumulative incidence ranged from 0.02 to 0.56% across risk groups. Decision curve analysis indicated improved clinical utility.

conclusionsPlasma proteomic signatures may improve GC risk stratification beyond traditional clinical factors and could support more targeted screening strategies. Further validation is warranted.

Indexed as

Biomarkers, TumorEarly Detection of CancerProteomicsStomach NeoplasmsAgedCase-Control StudiesFemaleFollow-Up StudiesHumansMaleMiddle AgedPrecision MedicineRisk AssessmentRisk FactorsBiomarkers, TumorBiomarkerCancer preventionCancer screeningGastric cancerProteomics

Identifiers

PMID42133180
PMCPMC13315260

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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.