Identification of DYRK2 and TRIM32 as keloids programmed cell death-related biomarkers: insights from bioinformatics and machine learning in multiple cohorts.

IF 1.7 4区 医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xi Yang, Yao Yang, Mingjian Zhao, He Bai, Chongyang Fu
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引用次数: 0

Abstract

This study aims to explore the expression patterns and mechanisms of programmed cell death-related genes in keloids and identify molecular targets for early diagnosis and treatment. We first explored the expression, immune, and biological function profiles of keloids. Using various machine learning methods, two key genes, DYRK2 and TRIM32, were identified, with ROC curves demonstrating their diagnostic potential. Further analyses, including GSEA, immune cell profiling, competing endogenous RNA network, and single-cell analysis, revealed their mechanism of action and regulatory network. Finally, SB-431542 was identified as a potential therapeutic agent for keloids through CMap and molecular docking.

本研究旨在探索瘢痕疙瘩中程序性细胞死亡相关基因的表达模式和机制,并确定早期诊断和治疗的分子靶点。我们首先探讨了瘢痕疙瘩的表达、免疫和生物功能谱。通过使用各种机器学习方法,我们确定了两个关键基因 DYRK2 和 TRIM32,其 ROC 曲线显示了它们的诊断潜力。进一步的分析,包括GSEA、免疫细胞图谱、竞争性内源性RNA网络和单细胞分析,揭示了它们的作用机制和调控网络。最后,通过 CMap 和分子对接,SB-431542 被确定为治疗瘢痕疙瘩的潜在药物。
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来源期刊
CiteScore
4.10
自引率
6.20%
发文量
179
审稿时长
4-8 weeks
期刊介绍: The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.
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