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基于生物信息学方法的子宫内膜癌和多囊卵巢综合征相关潜在标志物的筛选与验证

Screening and validation of potential markers associated with uterine corpus endometrial carcinoma and polycystic ovary syndrome based on bioinformatics methods.

作者信息

Wu Ruishan, Wu Cailin, Zhu Bingming, Li Jin, Zhao Wenzhong

机构信息

NHC Key Laboratory of Male Reproduction and Genetics, Guangdong Provincial Reproductive Science Institute (Guangdong Provincial Fertility Hospital), Guangzhou, China.

Department of Gynecology, The University of HongKong-Shenzhen Hospital, Shenzhen, China.

出版信息

Front Mol Biosci. 2023 Jun 9;10:1192313. doi: 10.3389/fmolb.2023.1192313. eCollection 2023.

Abstract

Endometrial cancer (UCEC) is a commonly occurring tumor in females, and polycystic ovary syndrome (PCOS) is closely related to UCEC, but the molecular mechanisms remain unclear. This article aims to explore potential molecular mechanisms in UCEC and PCOS, as well as identify prognostic genes for UCEC. Bioinformatics methods were employed to screen for DEGs in UCEC and PCOS. The shared DEGs were analyzed by constructing a protein-protein interaction (PPI) network using the String database and Cytoscape software. The enrichment analysis was performed using Metascape. The shared DEGs associated with the prognosis of UCEC were identified through univariate and lasso Cox regression methods. A multivariate Cox regression model was constructed and internally validated. The expression and test efficiency of the key prognostic genes were verified using external datasets for UCEC and PCOS. Furthermore, the Gepia database was utilized to analyze the expression of key prognostic genes and their correlation with the disease-free survival (RFS) of UCEC. Tumor mutation burden (TMB), immune infiltration, and the correlation of immune cells were assessed for the prognostic genes of UCEC. There were 151 shared DEGs identified between UCEC and PCOS through bioinformatics screening. These shared DEGs were primarily enriched in leukocyte activation. Following model construction and verification, nine genes were determined to be prognostic for UCEC from the shared DEGs. Among them, TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 were confirmed as prognostic genes in UCEC through external validation. Additionally, RTN1 was identified as a key gene in both UCEC and PCOS. Gepia analysis revealed that higher expression of RTN1 was associated with RFS in UCEC. Immune infiltration analysis of the shared DEGs demonstrated significant differences in the expression of various immune cells between UCEC high and low TMB groups. The seven key prognostic genes in UCEC exhibited regulatory relationships with immune cells. This study identified TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 as the key prognostic DEGs of UCEC. These genes are associated with UCEC survival, TMB, immune cell infiltration, and immune cell regulation. Among them, RTN1 may serve as a potential biomarker for both UCEC and PCOS.

摘要

子宫内膜癌(UCEC)是女性常见的肿瘤,多囊卵巢综合征(PCOS)与UCEC密切相关,但其分子机制仍不清楚。本文旨在探讨UCEC和PCOS潜在的分子机制,并确定UCEC的预后基因。采用生物信息学方法筛选UCEC和PCOS中的差异表达基因(DEGs)。通过使用String数据库和Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络,对共享的DEGs进行分析。使用Metascape进行富集分析。通过单变量和套索Cox回归方法确定与UCEC预后相关的共享DEGs。构建多变量Cox回归模型并进行内部验证。使用UCEC和PCOS的外部数据集验证关键预后基因的表达和检测效率。此外,利用Gepia数据库分析关键预后基因的表达及其与UCEC无病生存期(RFS)的相关性。对UCEC的预后基因评估肿瘤突变负荷(TMB)、免疫浸润以及免疫细胞的相关性。通过生物信息学筛选,在UCEC和PCOS之间鉴定出151个共享的DEGs。这些共享的DEGs主要富集于白细胞激活。经过模型构建和验证,从共享的DEGs中确定了9个对UCEC有预后意义的基因。其中,TSPYL5、KCNJ15、RTN1、HMOX1、DCAF12L1、VNN2和ANXA1通过外部验证被确认为UCEC的预后基因。此外,RTN1被确定为UCEC和PCOS中的关键基因。Gepia分析显示,RTN1的高表达与UCEC的RFS相关。对共享DEGs的免疫浸润分析表明,UCEC高TMB组和低TMB组之间各种免疫细胞的表达存在显著差异。UCEC中的7个关键预后基因与免疫细胞表现出调控关系。本研究确定TSPYL5、KCNJ15、RTN1、HMOX1、DCAF12L1、VNN2和ANXA1为UCEC的关键预后DEGs。这些基因与UCEC的生存、TMB、免疫细胞浸润和免疫细胞调控相关。其中,RTN1可能是UCEC和PCOS的潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f7f/10288877/0b3065b2c410/fmolb-10-1192313-g001.jpg

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