基于ceRNA网络分析和随机森林算法的痛风病关键lncRNAs鉴定:基于ceRNA网络分析和随机森林算法的研究

IF 2.4 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Molecular Biotechnology Pub Date : 2025-03-01 Epub Date: 2024-03-12 DOI:10.1007/s12033-024-01099-5
Zi-Chen Shao, Wei-Kang Sun, Qin-Qin Deng, Ling Cheng, Xin Huang, Lie-Kui Hu, Hua-Nan Li
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引用次数: 0

摘要

本研究的重点是通过ceRNA网络分析和随机森林(RF)算法,在铜死和铁死机制下识别潜在的与痛风相关的关键lncRNA,旨在为痛风的分子机制提供新的见解,并为未来痛风的治疗策略提供潜在的分子靶点。首先,我们对痛风微阵列芯片进行了深入的生物信息学分析,筛选出关键的杯突症相关基因(CRGs)和关键的铁突症相关基因(FRGs)。利用这些数据,我们构建了痛风的关键ceRNA网络。最后,通过RF算法结合ROC曲线确定了与痛风相关的关键lncRNA,并利用比较毒物基因组学数据库(CTD)进行了验证。我们成功鉴定了NLRP3、LIPT1和DBT为痛风相关的关键CRG,G6PD、PRKAA1、LIG3、PHF21A、KLF2、PGRMC1、JUN、PANX2和AR为痛风相关的关键FRG。根据ceRNA理论,关键ceRNA网络确定了4个下调的关键lncRNA(SEPSECS-AS1、LINC01054、REV3L-IT1和ZNF883)和3个下调的mRNA(DBT、AR和PRKAA1)。根据CTD验证推断得分和靶mRNA的生物学功能,我们确定了潜在的痛风相关lncRNA ZNF883/hsa-miR-539-5p/PRKAA1调控轴。本研究通过应用ceRNA网络分析和RF算法,首次发现了痛风相关铜死和铁死机制中的关键lncRNA ZNF883,从而填补了这一领域的研究空白,并为痛风的分子机制提供了新的见解。我们进一步发现,lncRNA ZNF883可能通过调控PRKAA1而在痛风患者中发挥作用,其机制可能与近端肾小管的尿酸重吸收和炎症调控有关。所提出的lncRNA ZNF883/hsa-miR-539-5p/PRKAA1调控轴可能是控制痛风疾病进展的潜在RNA调控途径。这一发现为痛风的治疗提供了新的分子靶点,对未来痛风的治疗策略具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Key lncRNAs in Gout Under Copper Death and Iron Death Mechanisms: A Study Based on ceRNA Network Analysis and Random Forest Algorithm.

This study focused on identifying potential key lncRNAs associated with gout under the mechanisms of copper death and iron death through ceRNA network analysis and Random Forest (RF) algorithm, which aimed to provide new insights into the molecular mechanisms of gout, and potential molecular targets for future therapeutic strategies of gout. Initially, we conducted an in-depth bioinformatics analysis of gout microarray chips to screen the key cuproptosis-related genes (CRGs) and key ferroptosis-related genes (FRGs). Using these data, we constructed a key ceRNA network for gout. Finally, key lncRNAs associated with gout were identified through the RF algorithm combined with ROC curves, and validated using the Comparative Toxicogenomics Database (CTD). We successfully identified NLRP3, LIPT1, and DBT as key CRGs associated with gout, and G6PD, PRKAA1, LIG3, PHF21A, KLF2, PGRMC1, JUN, PANX2, and AR as key FRGs associated with gout. The key ceRNA network identified four downregulated key lncRNAs (SEPSECS-AS1, LINC01054, REV3L-IT1, and ZNF883) along with three downregulated mRNAs (DBT, AR, and PRKAA1) based on the ceRNA theory. According to CTD validation inference scores and biological functions of target mRNAs, we identified a potential gout-associated lncRNA ZNF883/hsa-miR-539-5p/PRKAA1 regulatory axis. This study identified the key lncRNA ZNF883 in the context of copper death and iron death mechanisms related to gout for the first time through the application of ceRNA network analysis and the RF algorithm, thereby filling a research gap in this field and providing new insights into the molecular mechanisms of gout. We further found that lncRNA ZNF883 might function in gout patients by regulating PRKAA1, the mechanism of which was potentially related to uric acid reabsorption in the proximal renal tubules and inflammation regulation. The proposed lncRNA ZNF883/hsa-miR-539-5p/PRKAA1 regulatory axis might represent a potential RNA regulatory pathway for controlling the progression of gout disease. This discovery offered new molecular targets for the treatment of gout, and had significant implications for future therapeutic strategies in managing the gout.

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来源期刊
Molecular Biotechnology
Molecular Biotechnology 医学-生化与分子生物学
CiteScore
4.10
自引率
3.80%
发文量
165
审稿时长
6 months
期刊介绍: Molecular Biotechnology publishes original research papers on the application of molecular biology to both basic and applied research in the field of biotechnology. Particular areas of interest include the following: stability and expression of cloned gene products, cell transformation, gene cloning systems and the production of recombinant proteins, protein purification and analysis, transgenic species, developmental biology, mutation analysis, the applications of DNA fingerprinting, RNA interference, and PCR technology, microarray technology, proteomics, mass spectrometry, bioinformatics, plant molecular biology, microbial genetics, gene probes and the diagnosis of disease, pharmaceutical and health care products, therapeutic agents, vaccines, gene targeting, gene therapy, stem cell technology and tissue engineering, antisense technology, protein engineering and enzyme technology, monoclonal antibodies, glycobiology and glycomics, and agricultural biotechnology.
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