Evidence map›Paper›PMID 39171464›Full record

ArticleCurrent medicinal chemistry2025

Prediction of Prognosis and Immunotherapy Response of Gastric Cancer Based on Glutamine Metabolism-related Genes.

Saisai Gong, Sheng Yang, Tianyi Zhang, Jie Li, Xin Wan, Yifei Fang, Tong Liu, Chengyun Li, Yun Zhou, Geyu Liang

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Article in Current medicinal chemistry, 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
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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

10 authors.

Saisai GongKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.
Sheng YangKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.
Tianyi ZhangKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.
Jie LiKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.
Xin WanKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.
Yifei FangKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.
Tong LiuSchool of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China.
Chengyun LiSchool of Public Health, Lanzhou University, Lanzhou, Gansu, 730000, China.
Yun ZhouDepartment of Medicine, Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, Jiangsu, 210009, China.
Geyu LiangKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu, 210009, China.

Funding

Postgraduate Research & Practice Innovation Program of Jiangsu Province KYCX24_0483
6 · The paper itself

Abstract

backgroundReprogramming of glutamine metabolism in Gastric Cancer (GC) can significantly affect the tumor immune microenvironment and immunotherapy. This study examines the role of glutamine metabolism in the microenvironment and prognosis of gastric cancer.

methodsWe obtained gene expression data and clinical information of patients from the TCGA database. The patients were divided into two metabolic subtypes based on consistent clustering. A prognostic risk model containing three glutamine metabolism-related genes (GMRGs) was developed using Lasso-Cox. It was validated by the GEO validation cohort. Additionally, the immune microenvironment composition of the highand low-risk groups was assessed using ESTIMATE, CIBERSORT, and ssGSEA. Drug sensitivity analysis was conducted using the "oncoPredict" R package.

resultsWe outlined the distinct clinical characteristics of two subtypes and developed a prognostic risk model. The high-risk group has a poorer prognosis due to an increased expression of immune checkpoints and immunosuppressive cellular infiltration. Our analysis, which included Cox risk regression, ROC curves, and nomogram, demonstrated that this risk model is an independent prognostic factor. The TIDE score was higher in the high-risk group than in the low-risk group. Additionally, the high-risk group did not respond well to chemotherapeutic drug treatment.

conclusionThis study shows that modelling glutamine metabolism is a good predictor of prognosis and immunotherapy efficacy in gastric cancer. Thus, we can better understand the role of glutamine metabolism in the development of cancer and use these insights to develop more targeted and effective treatments.

Indexed as

GlutamineImmunotherapyStomach NeoplasmsFemaleHumansMalePrognosisTumor MicroenvironmentGlutamineGastric cancerglutamine metabolismimmunotherapyprognostic modeltargeted drug.tumor microenvironment

Identifiers

PMID39171464

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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 Socratic graph.