Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer

<b>Background/Objectives</b>: Lipid metabolism plays a crucial role in uterine corpus endometrial carcinoma (UCEC); however, its specific mechanisms remain to be fully elucidated. This study aimed to construct a lipid-metabolism-related prognostic model and explore its association with t...

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Main Authors: Zhangxin Wu, Yufei Nie, Deshui Kong, Lixiang Xue, Tianhui He, Kuaile Zhang, Jie Zhang, Chunliang Shang, Hongyan Guo
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Biomedicines
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Online Access:https://www.mdpi.com/2227-9059/13/5/1050
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author Zhangxin Wu
Yufei Nie
Deshui Kong
Lixiang Xue
Tianhui He
Kuaile Zhang
Jie Zhang
Chunliang Shang
Hongyan Guo
author_facet Zhangxin Wu
Yufei Nie
Deshui Kong
Lixiang Xue
Tianhui He
Kuaile Zhang
Jie Zhang
Chunliang Shang
Hongyan Guo
author_sort Zhangxin Wu
collection DOAJ
description <b>Background/Objectives</b>: Lipid metabolism plays a crucial role in uterine corpus endometrial carcinoma (UCEC); however, its specific mechanisms remain to be fully elucidated. This study aimed to construct a lipid-metabolism-related prognostic model and explore its association with the tumor immune microenvironment. <b>Methods</b>: A total of 552 UCEC and 35 normal tissue samples from The Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed lipid-metabolism-related genes (DE-LMRGs). A prognostic risk model was established using univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression, and its clinical utility was assessed through nomogram construction. Functional enrichment analysis was performed to explore the biological pathways involved. Tumor immune infiltration patterns were evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Results: Multivariate analysis indicated that the prognostic model had robust predictive value, with AUCs of 0.701, 0.746, and 0.790 for 1-, 3-, and 5-year overall survival predictions. High-risk patients exhibited a suppressed immune microenvironment characterized by reduced immune cell infiltration, lower tumor mutation burden (TMB), and elevated TIDE scores, suggesting potential resistance to immunotherapy. Furthermore, LIPG was identified as a key hub gene through the intersection of nine machine learning algorithms, demonstrating strong associations with both cancer progression and immune infiltration. Functional validation using Cell Counting Kit-8 (CCK-8), wound healing, and transwell migration assays following small interfering RNA (siRNA) transfection demonstrated that LIPG promotes UCEC cell proliferation and migration in vitro. <b>Conclusions</b>: These findings highlight the critical role of lipid metabolism in UCEC progression and immune modulation, with LIPG emerging as a potential prognostic biomarker. The identified lipid-metabolism-related gene signature may provide new insights into tumor microenvironment interactions.
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spelling doaj-art-d6a252d75e2a451e9a67d9df1cd9c4922025-08-20T03:14:32ZengMDPI AGBiomedicines2227-90592025-04-01135105010.3390/biomedicines13051050Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial CancerZhangxin Wu0Yufei Nie1Deshui Kong2Lixiang Xue3Tianhui He4Kuaile Zhang5Jie Zhang6Chunliang Shang7Hongyan Guo8Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, ChinaDepartment of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, ChinaDepartment of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, ChinaInstitute of Medical Innovation and Research, Peking University Third Hospital, Beijing 100191, ChinaDepartment of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, ChinaDepartment of Obstetrics and Gynecology, Beijing Huairou District Traditional Chinese Medicine Hospital, Beijing 101400, ChinaInstitute of Medical Innovation and Research, Peking University Third Hospital, Beijing 100191, ChinaDepartment of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, ChinaDepartment of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China<b>Background/Objectives</b>: Lipid metabolism plays a crucial role in uterine corpus endometrial carcinoma (UCEC); however, its specific mechanisms remain to be fully elucidated. This study aimed to construct a lipid-metabolism-related prognostic model and explore its association with the tumor immune microenvironment. <b>Methods</b>: A total of 552 UCEC and 35 normal tissue samples from The Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed lipid-metabolism-related genes (DE-LMRGs). A prognostic risk model was established using univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression, and its clinical utility was assessed through nomogram construction. Functional enrichment analysis was performed to explore the biological pathways involved. Tumor immune infiltration patterns were evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Results: Multivariate analysis indicated that the prognostic model had robust predictive value, with AUCs of 0.701, 0.746, and 0.790 for 1-, 3-, and 5-year overall survival predictions. High-risk patients exhibited a suppressed immune microenvironment characterized by reduced immune cell infiltration, lower tumor mutation burden (TMB), and elevated TIDE scores, suggesting potential resistance to immunotherapy. Furthermore, LIPG was identified as a key hub gene through the intersection of nine machine learning algorithms, demonstrating strong associations with both cancer progression and immune infiltration. Functional validation using Cell Counting Kit-8 (CCK-8), wound healing, and transwell migration assays following small interfering RNA (siRNA) transfection demonstrated that LIPG promotes UCEC cell proliferation and migration in vitro. <b>Conclusions</b>: These findings highlight the critical role of lipid metabolism in UCEC progression and immune modulation, with LIPG emerging as a potential prognostic biomarker. The identified lipid-metabolism-related gene signature may provide new insights into tumor microenvironment interactions.https://www.mdpi.com/2227-9059/13/5/1050endometrial cancerlipid metabolismbiomarkerstumor microenvironmentendothelial lipase
spellingShingle Zhangxin Wu
Yufei Nie
Deshui Kong
Lixiang Xue
Tianhui He
Kuaile Zhang
Jie Zhang
Chunliang Shang
Hongyan Guo
Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer
Biomedicines
endometrial cancer
lipid metabolism
biomarkers
tumor microenvironment
endothelial lipase
title Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer
title_full Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer
title_fullStr Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer
title_full_unstemmed Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer
title_short Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer
title_sort lipid metabolism related gene signature predicts prognosis and immune microenvironment alterations in endometrial cancer
topic endometrial cancer
lipid metabolism
biomarkers
tumor microenvironment
endothelial lipase
url https://www.mdpi.com/2227-9059/13/5/1050
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