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The Sphingolipids Metabolism Mechanism and Associated Molecular Biomarker Investigation in Keloid

鞘脂 瘢痕疙瘩 细胞外基质 信号转导 生物 细胞生物学 神经酰胺 基因 生物化学 化学 医学 外科 细胞凋亡
作者
Chengyu Zang,Yanxin Liu,Huaxia Chen
出处
期刊:Combinatorial Chemistry & High Throughput Screening [Bentham Science Publishers]
卷期号:26 (11): 2003-2012 被引量:4
标识
DOI:10.2174/1386207326666221031114305
摘要

Background: Sphingolipid metabolism plays important roles in maintaining cell growth and signal transduction. However, this pathway has not been investigated in keloid, a disease characterized by the excessive proliferation of fibroblasts. Methods: Based on the expression profiles of three datasets, the differentially expressed genes (DEGs) were explored between keloid fibroblasts and normal fibroblasts. Metabolism-related genes were obtained from a previous study. Then, enrichment analysis and protein-protein interaction (PPI) network analysis were performed for genes. Differences in metabolism-related pathways between keloid fibroblasts and normal fibroblasts were analyzed by the gene set variation analysis (GSVA). Quantitative PCR was used to confirm the expression of key genes in keloid fibroblast. Results: A total of 42 up-regulated co-DEGs and 77 down-regulated co-DEGs were revealed based on three datasets, and were involved in extracellular matrix structural constituent, collagencontaining extracellular matrix and sphingolipid metabolism pathway. A total of 15 metabolism- DEGs were screened, including serine palmitoyltransferase long chain base subunit (SPTLC) 3, UDP-glucose ceramide glucosyltransferase (UGCG) and sphingomyelin synthase 2 (SGMS2). All these three genes were enriched in the sphingolipid pathway. GSVA showed that the biosynthesis of glycosphingolipids (GSLs) in keloid fibroblasts was lower than that in normal fibroblasts. Quantitative PCR suggested SPTLC3, UGCG and SGMS2 were regulated in keloid fibroblasts. Conclusion: Sphingolipids metabolism pathway might take part in the disease progression of keloid by regulating keloid fibroblasts. SPTLC3, UGCG and SGMS2 might be key targets to investigate the underlying mechanism.
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