Effect of lipid metabolism genes expression on immunemicro environment and prognosis in endometrial carcinoma

ZHAO Lijuan; LIU Xiaoli; CHEN Fang; WENG Ling; ZENG Yongping; SHANG Qi; CHEN Huang

doi:10.14188/j.1671-8852.2024.0318

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Effect of lipid metabolism genes expression on immunemicro environment and prognosis in endometrial carcinoma

更新时间：2026-11-05

- Effect of lipid metabolism genes expression on immunemicro environment and prognosis in endometrial carcinoma
- Medical Journal of Wuhan University Vol. 46, Issue 11, Pages: 1422-1428(2025)
- 作者机构：
  
  武汉市第八医院妇产科湖北武汉 430012
- 作者简介：
- 基金信息：
- DOI：10.14188/j.1671-8852.2024.0318
  CLC： R737.6
- Received：28 April 2024，
  
  Published：25 November 2025
- 稿件说明：
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赵丽娟,刘晓丽,陈芳等.脂质代谢基因表达对子宫内膜癌免疫微环境及预后的影响[J].武汉大学学报（医学版）,2025,46(11):1422-1428.

ZHAO Lijuan,LIU Xiaoli,CHEN Fang,et al.Effect of lipid metabolism genes expression on immunemicro environment and prognosis in endometrial carcinoma[J].Medical Journal of Wuhan University,2025,46(11):1422-1428.
赵丽娟,刘晓丽,陈芳等.脂质代谢基因表达对子宫内膜癌免疫微环境及预后的影响[J].武汉大学学报（医学版）,2025,46(11):1422-1428. DOI： 10.14188/j.1671-8852.2024.0318.

ZHAO Lijuan,LIU Xiaoli,CHEN Fang,et al.Effect of lipid metabolism genes expression on immunemicro environment and prognosis in endometrial carcinoma[J].Medical Journal of Wuhan University,2025,46(11):1422-1428. DOI： 10.14188/j.1671-8852.2024.0318.

摘要

目的

探讨脂代谢相关基因在子宫内膜癌发生发展和诊断中的作用，为子宫内膜癌的治疗寻找潜在的治疗靶点并基于脂代谢基因并建立预后模型。

方法

从癌症基因组图谱（TCGA）的数据库下载子宫内膜癌患者的临床信息和相应的RNA数据，识别与子宫内膜癌患者预后显著相关的脂质代谢相关基因（LMRGs）。采用LASSO和Cox回归分析与子宫内膜癌患者预后显著相关的LMRGs，并基于此构建患者预后模型，进一步建立由LMRGs和临床变量组成的列线图估计子宫内膜癌患者的生存概率。

结果

发现ACOT11、CYP1A2、GDPD5、MOGAT3、OLAH、PIASS4、PIP5K1C、PLPP2和SRD5A1与子宫内膜癌患者的临床预后密切相关。由上述9

个LMRGs构建的预测模型能有效区分高低风险患者（

0.05），并预测子宫内膜癌患者的生存概率。

结论

LMRGs基因的表达与子宫内膜癌患者的免疫微环境相关，可用于准确预测子宫内膜癌患者的预后。

Abstract

Objective

To identify the lipid metabolism⁃related genes (LMRGs) in endometrial cancer

explore the role of lipid metabolism in the development and diagnosis of endometrial cancer

find potential therapeutic targets for endometrial cancer treatment

and establish a prognosis model.

Methods

Clinical information and corresponding RNA data of endometrial cancer patients were downloaded from the Cancer Genome Atlas (TCGA) database. Subsequently

LMRGs were identified using LASSO and Cox regression analysis to determine those significantly associated with patient prognosis. Based on these analyses

a model was developed to predict patient prognosis. Additionally

a nomogram incorporating risk models and clinical variables was constructed to estimate the survival probability in endometrial cancer patients.

Results

Nine LMRGs

ACOT11

CYP1A2

GDPD5

MOGAT3

OLAH

PIASS4

PIP5K1C

PLPP2

and SRD5A1 were found to be closely associated with the clinical prognosis of endometrial cancer patients. The prediction model constructed by the above 9 LMRGs can effectively distinguish high‑risk patients from low‑risk patients (

0.05)

and predict the survival probability of endometrial cancer patients.

Conclusion

The expression levels of LMRGs are associated with the immune microenvironment in endometrial cancer patients and can be utilized to accurately predict their prognosis.

关键词

Keywords

references

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Related Author

ZHAO Lijuan

LIU Xiaoli

CHEN Fang

WENG Ling

ZENG Yongping

SHANG Qi

CHEN Huang

YANG Shuang

Related Institution

Dept. of Obstetrics and Gynecology, The Eighth Hospital of Wuhan

Department of Respiratory and Critical Care Medicine， Zhongnan Hospital of Wuhan University

Intensive Care Unit, Renmin Hospital of Wuhan University

Intensive Care Unit, Luzhou Traditional Chinese Medicine Hospital

Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University

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