Evidence map›Paper›PMID 32369664›Full record

ArticleCancer science2020

Nuclear magnetic resonance-based tissue metabolomic analysis clarifies molecular mechanisms of gastric carcinogenesis.

Jinping Gu, Caihua Huang, Xiaomin Hu, Jinmei Xia, Wei Shao, Donghai Lin

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

24 citing papers in PubMed, 51 citations in OpenAlex.

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  12. HAntioxidants (Basel, Switzerland) · 2023
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  19. Pharmacometabolomics by NMR in Oncology: A Systematic Review.Pharmaceuticals (Basel, Switzerland) · 2021
    Review
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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

6 authors at 4 institutions in 1 country.

Jinping GuCollege of Chemistry and Chemical Engineering, Key Laboratory for Chemical Biology of Fujian Province, High-field NMR Center, Xiamen University, Xiamen, China.ORCID https://orcid.org/0000-0001-5800-3624
Caihua HuangResearch and Communication Center of Exercise and Health, Xiamen University of Technology, Xiamen, China.ORCID https://orcid.org/0000-0001-5134-0169
Xiaomin HuCollege of Chemistry and Chemical Engineering, Key Laboratory for Chemical Biology of Fujian Province, High-field NMR Center, Xiamen University, Xiamen, China.ORCID https://orcid.org/0000-0002-5921-1051
Jinmei XiaKey Laboratory of Marine Biogenetic Resources, Third Institute of Oceanography, State Oceanic Administration, Xiamen, China.ORCID https://orcid.org/0000-0001-9499-5560
Wei ShaoAffiliated Cardiovascular Hospital of Xiamen University, Medical College of Xiamen University, Xiamen, China.ORCID https://orcid.org/0000-0002-9555-3091
Donghai LinCollege of Chemistry and Chemical Engineering, Key Laboratory for Chemical Biology of Fujian Province, High-field NMR Center, Xiamen University, Xiamen, China.ORCID https://orcid.org/0000-0002-2318-2033
Xiamen University · CNFirst Affiliated Hospital of Xiamen University · CNFujian Institute of Oceanography · CNXiamen University of Technology · CN

Funding

Foundation for Innovative Research Groups of the National Natural Science Foundation of China 21521004National Natural Science Foundation of China 31971357National Natural Science Foundation of China 81574080Natural Science Foundation of Zhejiang Province LQ18B050003Xiamen Ocean Economic Innovation and Development Demonstration Project 16PZP001SF16
6 · The paper itself

Abstract

Gastric cancer (GC) is one of the deadliest cancers worldwide, and the progression of gastric carcinogenesis (GCG) covers multiple complicated pathological stages. Molecular mechanisms of GCG are still unclear. Here, we undertook NMR-based metabolomic analysis of aqueous metabolites extracted from gastric tissues in an established rat model of GCG. We showed that the metabolic profiles were clearly distinguished among 5 histologically classified groups: control, gastritis, low-grade gastric dysplasia, high-grade gastric dysplasia (HGD), and GC. Furthermore, we carried out metabolic pathway analysis based on identified significant metabolites and revealed significantly disturbed metabolic pathways closely associated with the 4 pathological stages, including oxidation stress, choline phosphorylation, amino acid metabolism, Krebs cycle, and glycolysis. Three metabolic pathways were continually disturbed during the progression of GCG, including taurine and hypotaurine metabolism, glutamine and glutamate metabolism, alanine, aspartate, and glutamate metabolism. Both the Krebs cycle and glycine, serine, and threonine metabolism were profoundly impaired in both the HGD and GC stages, potentially due to abnormal energy supply for tumor cell proliferation and growth. Furthermore, valine, leucine, and isoleucine biosynthesis and glycolysis were significantly disturbed in the GC stage for higher energy requirement of the rapid growth of tumor cells. Additionally, we identified potential gastric tissue biomarkers for metabolically discriminating the 4 pathological stages, which also showed good discriminant capabilities for their serum counterparts. This work sheds light on the molecular mechanisms of GCG and is of benefit to the exploration of potential biomarkers for clinically diagnosing and monitoring the progression of GCG.

Indexed as

Magnetic Resonance SpectroscopyMetabolomicsAnimalsCell Line, TumorCell Transformation, NeoplasticDisease Models, AnimalDisease SusceptibilityEnergy MetabolismHumansMetabolic Networks and PathwaysMetabolomeRatsStomach NeoplasmsXenograft Model Antitumor Assaysgastric carcinogenesismetabolic pathwaynuclear magnetic resonancerat modeltissue metabolomics

Identifiers

PMID32369664
PMCPMC7469815
OpenAlexW3023767262

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.