Evidence map›Paper›PMID 34156450›Full record

ArticleJAMA network open2021

Identification and Validation of Plasma Metabolomic Signatures in Precancerous Gastric Lesions That Progress to Cancer.

Sha Huang, Yang Guo, Zhong-Wu Li, Guanghou Shui, He Tian, Bo-Wen Li, Gaohaer Kadeerhan, Zhe-Xuan Li, Xue Li, Yang Zhang and 4 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 4% of its field
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

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 citations in OpenAlex.

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  6. Targeted metabolomic profiling of gastric cancer biopsies.The Indian journal of medical research · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 1 country.

Sha HuangKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Yang GuoKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Zhong-Wu LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Guanghou ShuiState Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.
He TianState Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.
Bo-Wen LiLipidALL Technologies Company Limited, Changzhou, Jiangsu Province, China.
Gaohaer KadeerhanKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Zhe-Xuan LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Xue LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Yang ZhangKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Tong ZhouKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Wei-Cheng YouKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Kai-Feng PanKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Wen-Qing LiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing, China.
Peking University · CNPeking University Cancer Hospital · CNChinese Academy of Sciences · CNInstitute of Genetics and Developmental Biology · CNLipidALL Technologies (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Metabolic deregulation plays an important role in gastric cancer (GC) development. To date, no studies have comprehensively explored the metabolomic profiles along the cascade of gastric lesions toward GC. Objective: To draw a metabolic landscape and define metabolomic signatures associated with the progression of gastric lesions and risk of early GC. Design, Setting, and Participants: A 2-stage, population-based cohort study was initiated in 2017 in Linqu County, Shandong Province, China, a high-risk area for GC. Prospective follow-up was conducted during the validation stage (June 20, 2017, to May 27, 2020). A total of 400 individuals were included based on the National Upper Gastrointestinal Cancer Early Detection Program in China. The discovery stage involved 200 individuals with different gastric lesions or GC (high-grade intraepithelial neoplasia or invasive GC). The validation stage prospectively enrolled 152 individuals with gastric lesions who were followed up for 118 to 1063 days and 48 individuals with GC. Exposures: Metabolomic profiles and metabolite signatures were examined based on untargeted plasma metabolomics assay. Main Outcomes and Measures: The risk of GC overall and early GC (high-grade intraepithelial neoplasia), and progression of gastric lesions. Results: Of the 400 participants, 124 of 200 (62.0%) in the discovery set were men; mean (SD) age was 56.8 (7.5) years. In the validation set, 136 of 200 (68.0%) were men; mean (SD) age was 57.5 (8.1) years. Distinct metabolomic profiles were noted for gastric lesions and GC. Six metabolites, including α-linolenic acid, linoleic acid, palmitic acid, arachidonic acid, sn-1 lysophosphatidylcholine (LysoPC)(18:3), and sn-2 LysoPC(20:3) were significantly inversely associated with risk of GC overall and early GC (high-grade intraepithelial neoplasia). Among these metabolites, the first 3 were significantly inversely associated with gastric lesion progression, especially for the progression of intestinal metaplasia (α-linolenic acid: OR, 0.42; 95% CI, 0.18-0.98; linoleic acid: OR, 0.43; 95% CI, 0.19-1.00; and palmitic acid: OR, 0.32; 95% CI, 0.13-0.78). Compared with models including only age, sex, Helicobacter pylori infection, and gastric histopathologic findings, integrating these metabolites significantly improved the performance for predicting the progression of gastric lesions (area under the curve [AUC], 0.86; 95% CI, 0.70-1.00 vs AUC, 0.69; 95% CI, 0.50-0.88; P = .02) and risk of early GC (AUC, 0.83; 95% CI, 0.58-1.00 vs AUC, 0.61; 95% CI, 0.31-0.91; P = .03). Conclusions and Relevance: This study defined metabolite signatures that might serve as meaningful biomarkers for assessing high-risk populations and early diagnosis of GC, possibly advancing targeted GC prevention and control.

Indexed as

AgedChinaCohort StudiesFemaleHelicobacter InfectionsHelicobacter pyloriHumansMaleMetabolomicsMiddle AgedPrecancerous ConditionsProspective StudiesStomach Neoplasms

Identifiers

PMID34156450
PMCPMC8220475
OpenAlexW3174246204

What OpenQuestion holds

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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.