Evidence map›Paper›PMID 39068426›Full record

ArticleBMC women's health2024

Risk prediction model of uterine corpus endometrial carcinoma based on immune-related genes.

Qiu Sang, Linlin Yang, He Zhao, Lingfeng Zhao, Ruolan Xu, Hui Liu, Chunyan Ding, Yan Qin, Yanfei Zhao

Abstract read
In one paragraph

Article in BMC women's health, 2024. 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
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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

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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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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.

Qiu SangYunnan SangGu Zhizao Biotechnology Co., Ltd, Kunming, 650201, China.
Linlin YangDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China. yll194900@sina.com.ORCID http://orcid.org/0000-0003-2371-2951
He ZhaoDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.
Lingfeng ZhaoDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.
Ruolan XuDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.
Hui LiuDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.
Chunyan DingDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.
Yan QinDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.
Yanfei ZhaoDepartment of Gynaecology, Yunnan Cancer Hospital (The Third Affiliated Hospital of Kunming Medical University), Kunming, 650118, China.

Funding

Special fund project for training high-level health technical personnel in Yunnan Province D-2018053
6 · The paper itself

Abstract

backgroundGiven the significant role of immune-related genes in uterine corpus endometrial carcinoma (UCEC) and the long-term outcomes of patients, our objective was to develop a prognostic risk prediction model using immune-related genes to improve the accuracy of UCEC prognosis prediction.

methodsThe Limma, ESTIMATE, and CIBERSORT methods were used for cluster analysis, immune score calculation, and estimation of immune cell proportions. Univariate and multivariate analyses were utilized to develop a prognostic risk model for UCEC. Risk model scores and nomograms were used to evaluate the models. String constructs a protein-protein interaction (PPI) network of genes. The qRT-PCR, immunofluorescence, and immunohistochemistry (IHC) all confirmed the genes.

resultsCluster analysis divided the immune-related genes into four subtypes. 33 immune-related genes were used to independently predict the prognosis of UCEC and construct the prognosis model and risk score. The analysis of the survival nomogram indicated that the model has excellent predictive ability and strong reliability for predicting the survival of patients with UCEC. The protein-protein interaction network analysis of key genes indicates that four genes play a pivotal role in interactions: GZMK, IL7, GIMAP, and UBD. The quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence, and immunohistochemistry (IHC) all confirmed the expression of the aforementioned genes and their correlation with immune cell levels. This further revealed that GZMK, IL7, GIMAP, and UBD could potentially serve as biomarkers associated with immune levels in endometrial cancer.

conclusionThe study identified genes related to immune response in UCEC, including GZMK, IL7, GIMAP, and UBD, which may serve as new biomarkers and therapeutic targets for evaluating immune levels in the future.

Indexed as

Endometrial NeoplasmsNomogramsBiomarkers, TumorCluster AnalysisFemaleHumansMiddle AgedPrognosisProtein Interaction MapsRisk AssessmentBiomarkers, TumorKey genesPrognosis evaluationTCGA databaseTumor immunotherapyUCEC

Identifiers

PMID39068426
PMCPMC11282678

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