Evidence map›Paper›PMID 40348923›Full record

ArticleDiscover oncology2025

Blood metabolites, protein regulatory networks and their roles in pan-cancer: a mendelian randomisation study.

Shenglong Xia, Zhengyang Xu, Cheng Cheng, Rui An, Wenci Chen, Daopo Lin, Yuzhen Gao, Liangjing Wang, Xinyou Xie, Jun Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

10 authors.

Shenglong Xia *Department of Clinical Laboratory, Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China.
Zhengyang Xu *Department of Gastroenterology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China.
Cheng ChengDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China.
Rui AnDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China.
Wenci ChenDepartment of Rehabilitation, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine, Wenzhou, 325000, China.
Daopo LinDepartment of Gastroenterology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Yuzhen GaoDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China.
Liangjing WangDepartment of Gastroenterology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China. wangljzju@zju.edu.cn.
Xinyou XieDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China. scottxie@zju.edu.cn.
Jun ZhangDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital of Zhejiang University School of Medicine, Hangzhou, 310016, Zhejiang, China. jameszhang2000@zju.edu.cn.

Funding

Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province 2022E10018Key Research and Development Program of Zhejiang Province 2019C03021National Natural Science Foundation of China 82172362Zhejiang Provincial Natural Science Foundation of China LQ24H270001Zhejiang Provincial Natural Science Foundation of China LQN25H160028
6 · The paper itself

Abstract

backgroundMetabolic dysregulation was closely associated with cancers. However, there is a lack of studies to explore the relationship between blood metabolites, related proteins, and different types of cancer.

methodsTwo-sample Mendelian randomization (MR) analysis was used to assess the causal effects of genetically determined metabolites and metabolite ratios on solid cancers. we analyzed 1400 metabolites/metabolite ratios as exposures and 16 cancers from UK Biobank/FinnGen as outcomes. Protein-metabolite interactions were mapped via MR and visualized with Cytoscape, followed by Gene Ontology enrichment. Clinical validation included metabolomic profiling of 75 breast cancer patients and 20 controls.

resultsMR analysis identified 11 metabolites or metabolite ratios causally associated with cancer risk. Moreover, 48 proteins were demonstrated to be involved in the regulation of these metabolites, which are predominantly enriched in 5 significant metabolic pathways in cancers. Clinically, elevated lignoceroylcarnitine (C24) reduced breast cancer risk, while high glucose-to-mannose and alanine-to-asparagine ratios increased risk.

conclusionsOur study revealed a causal effects of metabolites and its related proteins/pathways on various types of cancers.

Indexed as

Mendelian randomizationMetabolic pathwaysMetabolitesPan-cancerProtein

Identifiers

PMID40348923
PMCPMC12065688

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.