ArticleCancer biomarkers : section A of Disease markers2025
Exploring lipid metabolism-associated gene biomarkers and their regulatory mechanisms in nasopharyngeal carcinoma.
Article in Cancer biomarkers : section A of Disease markers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma.Translational cancer research · 2025Article
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3 authors.
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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.
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