Evidence map›Paper›PMID 39696985›Full record

ArticleActa biochimica et biophysica Sinica2024

O-GlcNAcylation-related genes mediate tumor microenvironment characteristics and prediction of immunotherapy response in gastric cancer.

Wangwen Wang, Xi Lu, Chengjun Zhu, Jie Li, Yue Liu, Zhangchao Yao, Xiaolin Li

Abstract read
In one paragraph

Article in Acta biochimica et biophysica Sinica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Wangwen WangDepartment of Geriatric Gastroenterology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Xi LuDepartment of Geriatric Gastroenterology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Chengjun ZhuDepartment of General Surgery, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Jie LiDepartment of Geriatric Gastroenterology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Yue LiuDepartment of Geriatric Gastroenterology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Zhangchao YaoDepartment of Geriatric Gastroenterology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Xiaolin LiDepartment of Geriatric Gastroenterology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aim to identify molecular clusters related to O-GlcNAcylation and establish a novel scoring system for predicting prognosis and immunotherapy efficacy in patients with gastric cancer (GC). The transcriptomic and clinical data are obtained from XENA-UCSC and GEO databases. The O-GlcNAcylation-related genes are obtained from the GSEA database. Consensus clustering analysis is employed to identify O-GlcNAcylation-related molecular clusters, and principal component analysis (PCA) is utilized to develop a novel prognostic scoring system for predicting GC outcomes and immunotherapy efficacy. The prognostic accuracy of the scoring system is assessed across five real-world cohorts. The biological function of actin alpha 2, smooth muscle (ACTA2) in GC is determined through experimental verification. Using 34 O-GlcNAcylation-related genes associated with prognosis in GC patients, these individuals are divided into two distinct subgroups characterized by different outcomes, tumor microenvironment profiles, and clinical case characteristics. The DEGs between the two subgroups are subsequently used to further divide the GC patients into two subgroups by consensus cluster analysis. PCA is used to construct a prognostic scoring system, which reveal that patients in the low-score subgroup have a better prognosis and greater benefit from immunotherapy. The accuracy of the scoring system is confirmed through validation in a cohort of patients receiving immunotherapy in the real world. ACTA2 promotes proliferation and inhibits apoptosis in GC cells. These findings suggest that we successfully establish molecular clusters associated with O-GlcNAcylation and develop a scoring system that demonstrates strong performance in predicting the prognosis of patients with GC and the effect of immunotherapy interventions.

Indexed as

ImmunotherapyStomach NeoplasmsTumor MicroenvironmentActinsBiomarkers, TumorGene Expression Regulation, NeoplasticHumansMalePrognosisACTA2 protein, humanActinsBiomarkers, Tumorgastric cancerimmunotherapy efficacyO-GlcNAcylationprognosistumor immune microenvironment

Identifiers

PMID39696985
PMCPMC12053408

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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.