竞争性内源性RNA
瘢痕疙瘩
小RNA
马拉特1
微阵列分析技术
长非编码RNA
微阵列
计算生物学
基因
生物
生物信息学
核糖核酸
基因表达
遗传学
医学
病理
作者
Ruxin Xie,Yun Jiao,Chenyu Li,Shiwei Zhang,Ai Zhong,Junliang Wu,Ying Cen,Junjie Chen
出处
期刊:Research Square - Research Square
日期:2023-11-06
标识
DOI:10.21203/rs.3.rs-3008440/v2
摘要
Abstract Objective To explore the complex mechanisms of keloid, new approaches have been developed by different strategies. However, conventional treatment did not significantly reduce the recurrence rate. This study aimed to identify new biomarkers and mechanisms for keloid progression through bioinformatics analyses. Methods In our study, microarray datasets for keloid were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by R software. Multiple bioinformatics tools were used to identify hub genes, and reverse predict upstream miRNAs and lncRNA molecules of target hub genes. Finally, the total RNA-sequencing technique and miRNA microarray were combined to validate the identified genes. Results Thirty-one DEGs were screened out and the upregulated hub gene SPP1 was finally identified, which was consistent with our RNA-sequencing analysis results and validation dataset. In addition, a ceRNA network of mRNA (SPP1)-miRNA (miR-181a-5p)-lncRNA (NEAT1, MALAT1, LINC00667, NORAD, XIST and MIR4458HG) was identified by the bioinformatics databases. The results of our miRNA microarray showed that miR-181a-5p was upregulated in keloid, also we found that the lncRNA NEAT1 could affect keloid progression by retrieving the relevant literature. Conclusions We speculate that SPP1 is a potential candidate biomarker and therapeutic target for patients with keloid, and NEAT1/miR-181a-5p/SPP1 might be the RNA regulatory pathway that regulates keloid formation.
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