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探索鼻咽癌中脂质代谢相关基因生物标志物及其调控机制。

Exploring lipid metabolism-associated gene biomarkers and their regulatory mechanisms in nasopharyngeal carcinoma.

作者信息

Liu Yiyi, Xie Yingying, Wang Yong

机构信息

Department of Pharmacy, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.

出版信息

Cancer Biomark. 2025 Apr;42(4):18758592241301683. doi: 10.1177/18758592241301683. Epub 2025 Apr 28.

Abstract

BackgroundNasopharyngeal carcinoma (NPC) is a neoplasm that arises from the mucosal lining of the nasopharynx. Recent investigations have underscored that reprogramming of lipid metabolism is a salient metabolic alteration in neoplastic cells. Consequently, identifying lipid metabolism-associated biomarkers in NPC is of paramount importance.MethodsUtilizing transcriptomic datasets, differentially expressed genes (DEGs) were identified from GSE12452, contrasting NPC specimens with normal controls. The Weighted Gene Co-expression Network Analysis (WGCNA) was employed to discern key module genes pertinent to NPC. Lipid metabolism-related differentially expressed genes (LMR-DEGs) were ascertained by intersecting DEGs, key module genes linked to NPC, and lipid metabolism-related genes (LMRGs) using a Venn diagram approach. Subsequently, the MCODE algorithm was applied within the protein-protein interaction (PPI) framework to pinpoint lipid metabolism-centric biomarkers for NPC. The diagnostic potential of these biomarkers was assessed through ROC analysis. In the concluding phase, a 'TF-mRNA-miRNA' interaction network was delineated using Cytoscape.ResultsIn our analysis, a total of 5026 DEGs were discerned when contrasting NPC specimens with normal controls. From this pool, 1835 genes were pinpointed as key module genes pertinent to NPC. Through a Venn diagram approach, 64 LMR-DEGs were isolated. Further analysis led to the identification of six lipid metabolism-centric biomarkers for NPC, namely GALC, SPTLC2, SMPD2, DEGS2, DEGS1, and SMPD3. Notably, these biomarkers demonstrated robust diagnostic efficacy. We found that DEGS1 was negatively correlated with SMPD2 and DEGS2. A comparative expression analysis revealed diminished expression levels of GALC, SPTLC2, SMPD2, DEGS2, and SMPD3 in the NPC cohort relative to the control group. In the terminal phase of our study, the 'TF-mRNA-miRNA' regulatory network was delineated, comprising 309 nodes and 360 interaction pairs.ConclusionIn summary, our investigation identified six lipid metabolism-associated biomarkers (GALC, SPTLC2, SMPD2, DEGS2, DEGS1, and SMPD3) linked to NPC, providing a foundational framework for potential therapeutic interventions for NPC.

摘要

背景

鼻咽癌(NPC)是一种起源于鼻咽部黏膜的肿瘤。最近的研究强调,脂质代谢重编程是肿瘤细胞中显著的代谢改变。因此,鉴定鼻咽癌中与脂质代谢相关的生物标志物至关重要。

方法

利用转录组数据集,从GSE12452中鉴定出差异表达基因(DEG),将鼻咽癌标本与正常对照进行对比。采用加权基因共表达网络分析(WGCNA)来识别与鼻咽癌相关的关键模块基因。通过使用维恩图方法,将DEG、与鼻咽癌相关的关键模块基因以及脂质代谢相关基因(LMRG)进行交叉,确定脂质代谢相关差异表达基因(LMR-DEG)。随后,在蛋白质-蛋白质相互作用(PPI)框架内应用MCODE算法,以确定鼻咽癌以脂质代谢为中心的生物标志物。通过ROC分析评估这些生物标志物的诊断潜力。在最后阶段,使用Cytoscape绘制“转录因子-mRNA- miRNA”相互作用网络。

结果

在我们的分析中,将鼻咽癌标本与正常对照对比时,共识别出5026个DEG。从中确定了1835个基因作为与鼻咽癌相关的关键模块基因。通过维恩图方法,分离出64个LMR-DEG。进一步分析导致鉴定出6个鼻咽癌以脂质代谢为中心的生物标志物,即半乳糖脑苷脂酶(GALC)、丝氨酸棕榈酰转移酶长链亚基2(SPTLC2)、鞘磷脂磷酸二酯酶2(SMPD2)、二氢神经酰胺Δ4-去饱和酶2(DEGS2)、二氢神经酰胺Δ4-去饱和酶1(DEGS1)和鞘磷脂磷酸二酯酶3(SMPD3)。值得注意的是,这些生物标志物显示出强大的诊断效能。我们发现DEGS1与SMPD2和DEGS2呈负相关。比较表达分析显示,相对于对照组,鼻咽癌队列中GALC、SPTLC2、SMPD2、DEGS2和SMPD3的表达水平降低。在我们研究的最后阶段,绘制了“转录因子-mRNA- miRNA”调控网络,其包含309个节点和360个相互作用对。

结论

总之,我们的研究鉴定出6个与鼻咽癌相关的脂质代谢相关生物标志物(GALC、SPTLC2、SMPD2、DEGS2、DEGS1和SMPD3),为鼻咽癌潜在的治疗干预提供了基础框架。

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