Evidence map›Paper›PMID 38551775›Full record

ArticleDiscover oncology2024

High-throughput metabolomics identifies new biomarkers for cervical cancer.

Xue Li, Liyi Zhang, Xuan Huang, Qi Peng, Shoutao Zhang, Jiangming Tang, Jing Wang, Dingqing Gui, Fanxin Zeng

Open access · goldAbstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 2 institutions in 1 country.

Xue Li *Department of Clinical Research Center, Dazhou Central Hospital, Dazhou, 635000, Sichuan, China.
Liyi Zhang *Department of Gynaecology and Obstetrics, Dazhou Central Hospital, Dazhou, Sichuan, China.
Xuan Huang *Department of Medical Research Center, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Qi PengDepartment of Gynaecology and Obstetrics, Dazhou Central Hospital, Dazhou, Sichuan, China.
Shoutao ZhangDepartment of Gynaecology and Obstetrics, Dazhou Central Hospital, Dazhou, Sichuan, China.
Jiangming TangDepartment of Gynaecology and Obstetrics, Dazhou Central Hospital, Dazhou, Sichuan, China.
Jing WangDepartment of Clinical Laboratory, Beijing Anding Hospital, Capital Medical University, Beijing, China. ycwangjing@mail.ccmu.edu.cn.
Dingqing GuiDepartment of Gynaecology and Obstetrics, Dazhou Central Hospital, Dazhou, Sichuan, China. 28459897@qq.com.
Fanxin ZengDepartment of Clinical Research Center, Dazhou Central Hospital, Dazhou, 635000, Sichuan, China. zengfx@pku.edu.cn.
Dazhou Central Hospital · CNCapital Medical University · CN

Funding

Innovative Scientific Research Project of Medical Youth in Sichuan Province Q20073Scientific Research Fund of Sichuan health and Health Committee No. 21PJ085the Dazhou-Sichuan University Intelligent Medical Laboratory in Dazhou 2021CDDZ-26the Dazhou-Sichuan University Intelligent Medical Laboratory in Dazhou 21ZDYF0029The Key Projects fund of Science & Technology Department of Sichuan Province 2022JDRC0069The Key Projects fund of Science & Technology Department of Sichuan Province 2022YFS0588
6 · The paper itself

Abstract

backgroundCervical cancer (CC) is a danger to women's health, especially in many developing countries. Metabolomics can make the connection between genotypes and phenotypes. It provides a wide spectrum profile of biological processes under pathological or physiological conditions.

methodIn this study, we conducted plasma metabolomics of healthy volunteers and CC patients and integratively analyzed them with public CC tissue transcriptomics from Gene Expression Omnibus (GEO).

resultHere, we screened out a panel of 5 metabolites to precisely distinguish CC patients from healthy volunteers. Furthermore, we utilized multi-omics approaches to explore patients with stage I-IIA1 and IIA2-IV4 CC and comprehensively analyzed the dysregulation of genes and metabolites in CC progression. We identified that plasma levels of trimethylamine N-oxide (TMAO) were associated with tumor size and regarded as a risk factor for CC. Moreover, we demonstrated that TMAO could promote HeLa cell proliferation in vitro. In this study, we delineated metabolic profiling in healthy volunteers and CC patients and revealed that TMAO was a potential biomarker to discriminate between I-IIA1 and IIA2-IV patients to indicate CC deterioration.

conclusionOur study identified a diagnostic model consisting of five metabolites in plasma that can effectively distinguish CC from healthy volunteers. Furthermore, we proposed that TMAO was associated with CC progression and might serve as a potential non-invasive biomarker to predict CC substage. IMPACT: These findings provided evidence of the important role of metabolic molecules in the progression of cervical cancer disease, as well as their ability as potential biomarkers.

Indexed as

Cervical cancerMetabolitesPrognosisTrimethylamine N-oxide

Identifiers

PMID38551775
PMCPMC10980666
OpenAlexW4393317832

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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.