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基于 GEO 数据库的瘢痕疙瘩新型诊断生物标志物的鉴定与验证
Authors Nurzati Y , Zhu Z, Xu H, Zhang Y
Received 30 September 2021
Accepted for publication 15 December 2021
Published 26 January 2022 Volume 2022:15 Pages 897—912
DOI https://doi.org/10.2147/IJGM.S337951
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Scott Fraser
Introduction: Keloid is a pathological scar type, which invades normal surrounding tissue without self-limiting to cause pain, itching, cosmetic disfigurement, etc. Knowledge of the molecular mechanisms underlying keloid remains unclear. This dilemma leads to no biomarker available for diagnosis. Thus, to seek accurate diagnosis, biomarkers are necessary for keloid diagnosis to help control its incidence.
Methods: Gene Expression Omnibus (GEO) database was used to select differentially expressed miRNAs (DE-miRNAs) in GSE113620. miRTarBase miRNA–target tools were used to predict the interactions between miRNAs and their target mRNAs. Target mRNAs that were differentially expressed in keloid were selected by analyzing differentially expressed genes (DEGs) in GSE44270 and GSE92566. PPI network analysis, gene enrichment analysis, cell-specific and tissue-specific expression analyses of DE-target mRNAs were conducted. RT-PCR analysis was conducted to validate our results.
Results: Three novel miRNAs (miR-30b-5p, miR-212-3p, miR-149-5p) and five target mRNAs (SIX1, CCNA2, CCNB1, FOXM1, RUNX2 ) were identified as potential biomarkers for keloid patients. Additionally, the potential functions of those miRNAs-mRNAs pathways were analyzed.
Discussion: These findings of keloid-related miRNAs, mRNAs, and miRNA–mRNAs regulatory networks may provide insights into the underlying pathogenesis of keloid and serve as potential biomarkers for keloid diagnosis.
Keywords: diagnostic biomarkers, miRNA–mRNA network, keloids, differentially expressed genes