胰腺炎内质网应激相关中枢基因的基因组挖掘:从计算机表征的角度

IF 2.4 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Huiwei Ye, Laifa Kong
{"title":"胰腺炎内质网应激相关中枢基因的基因组挖掘:从计算机表征的角度","authors":"Huiwei Ye, Laifa Kong","doi":"10.1007/s12033-025-01388-7","DOIUrl":null,"url":null,"abstract":"<p><p>Pancreatitis, as a common exocrine pancreatic disease, poses a daunting challenge to patients' health and the medical system. Endoplasmic reticulum stress (ERS) plays an essential role in the pathologic process of pancreatitis. However, its mechanism is not fully understood. Therefore, this study was designed to deepen the understanding of the pathogenic mechanism of the disease by screening key ERS-related genes (ERSRGs) associated with pancreatitis. Pancreatitis mRNA data for GSE194331 (Normal: 32, Pancreatitis: 87) and pancreatitis GSE143754 (Normal: 9, Pancreatitis: 6) were downloaded from the GEO database and were used as a training and validation set, respectively. First, the training set GSE194331 was differentially expressed and intersected with the ERSRGs (n = 265) obtained from the MSigDB database to result in 42 differentially expressed ERSRGs (DE-ERSRGs). Subsequently, five candidate genes were further screened by PPI network and MCC and MCODE algorithms. However, according to the ROC curve results, AUC values of CCND1, BCL2, PIK3R1, and BCL2L1 were all greater than 0.6, indicating that they had good diagnostic performance, which was verified by the GSE143754 data set. Based on the GeneMANIA network, it was found that hub genes BCL2 and BCL2L1 may be the key factors in the regulation of mitochondrial metabolism. 24 differentially expressed pancreatitis-related genes (DE-PRGs) were found by difference analysis and Venn analysis. Hub genes BCL2 and PIK3R1 that were significantly correlated with 24 DE-PRGs were determined by Spearman analysis. ssGSEA algorithm was further used to reveal the significant correlation between these hub genes and the immune microenvironment of pancreatitis. The miRNA and lncRNA targeting hub genes were predicted using miRWalk, TargetScan, miRDB, and ENCORI databases, providing research directions for the mechanism of pancreatitis. Finally, the Network Analyst website was used to predict potential compounds associated with the hub gene. In conclusion, this study not only further supports the role of ERS in the development of pancreatitis but also provides a new perspective and direction for the development of biomarkers and mechanism of pancreatitis. At the same time, the results of this study provide a reliable research direction for the targeted treatment of pancreatitis.</p>","PeriodicalId":18865,"journal":{"name":"Molecular Biotechnology","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genome Mining for Hub Genes Related to Endoplasmic Reticulum Stress in Pancreatitis: A Perspective from In Silico Characterization.\",\"authors\":\"Huiwei Ye, Laifa Kong\",\"doi\":\"10.1007/s12033-025-01388-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Pancreatitis, as a common exocrine pancreatic disease, poses a daunting challenge to patients' health and the medical system. Endoplasmic reticulum stress (ERS) plays an essential role in the pathologic process of pancreatitis. However, its mechanism is not fully understood. Therefore, this study was designed to deepen the understanding of the pathogenic mechanism of the disease by screening key ERS-related genes (ERSRGs) associated with pancreatitis. Pancreatitis mRNA data for GSE194331 (Normal: 32, Pancreatitis: 87) and pancreatitis GSE143754 (Normal: 9, Pancreatitis: 6) were downloaded from the GEO database and were used as a training and validation set, respectively. First, the training set GSE194331 was differentially expressed and intersected with the ERSRGs (n = 265) obtained from the MSigDB database to result in 42 differentially expressed ERSRGs (DE-ERSRGs). Subsequently, five candidate genes were further screened by PPI network and MCC and MCODE algorithms. However, according to the ROC curve results, AUC values of CCND1, BCL2, PIK3R1, and BCL2L1 were all greater than 0.6, indicating that they had good diagnostic performance, which was verified by the GSE143754 data set. Based on the GeneMANIA network, it was found that hub genes BCL2 and BCL2L1 may be the key factors in the regulation of mitochondrial metabolism. 24 differentially expressed pancreatitis-related genes (DE-PRGs) were found by difference analysis and Venn analysis. Hub genes BCL2 and PIK3R1 that were significantly correlated with 24 DE-PRGs were determined by Spearman analysis. ssGSEA algorithm was further used to reveal the significant correlation between these hub genes and the immune microenvironment of pancreatitis. The miRNA and lncRNA targeting hub genes were predicted using miRWalk, TargetScan, miRDB, and ENCORI databases, providing research directions for the mechanism of pancreatitis. Finally, the Network Analyst website was used to predict potential compounds associated with the hub gene. In conclusion, this study not only further supports the role of ERS in the development of pancreatitis but also provides a new perspective and direction for the development of biomarkers and mechanism of pancreatitis. At the same time, the results of this study provide a reliable research direction for the targeted treatment of pancreatitis.</p>\",\"PeriodicalId\":18865,\"journal\":{\"name\":\"Molecular Biotechnology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Biotechnology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12033-025-01388-7\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Biotechnology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12033-025-01388-7","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

胰腺炎作为一种常见的外分泌胰腺疾病,对患者的健康和医疗系统构成了严峻的挑战。内质网应激在胰腺炎的病理过程中起重要作用。然而,其机制尚不完全清楚。因此,本研究旨在通过筛选与胰腺炎相关的关键ers相关基因(ERSRGs),加深对该病发病机制的认识。从GEO数据库中下载GSE194331(正常:32,胰腺炎:87)和GSE143754(正常:9,胰腺炎:6)的胰腺炎mRNA数据,分别作为训练集和验证集。首先,对训练集GSE194331进行差异表达,并与MSigDB数据库中得到的ersrg (n = 265)相交,得到42个差异表达的ersrg (de - ersrg)。随后,通过PPI网络和MCC和MCODE算法进一步筛选5个候选基因。但从ROC曲线结果来看,CCND1、BCL2、PIK3R1、BCL2L1的AUC值均大于0.6,说明它们具有较好的诊断性能,GSE143754数据集验证了这一点。基于GeneMANIA网络,发现中枢基因BCL2和BCL2L1可能是调控线粒体代谢的关键因子。差异分析和Venn分析共发现24个差异表达的胰腺炎相关基因(DE-PRGs)。通过Spearman分析确定与24个DE-PRGs显著相关的枢纽基因BCL2和PIK3R1。进一步利用ssGSEA算法揭示这些枢纽基因与胰腺炎免疫微环境之间的显著相关性。利用miRWalk、TargetScan、miRDB、ENCORI等数据库预测中心基因靶向miRNA和lncRNA,为胰腺炎发病机制提供研究方向。最后,利用网络分析网站预测与枢纽基因相关的潜在化合物。综上所述,本研究不仅进一步支持了ERS在胰腺炎发生发展中的作用,也为胰腺炎生物标志物和机制的开发提供了新的视角和方向。同时,本研究结果为胰腺炎的靶向治疗提供了可靠的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genome Mining for Hub Genes Related to Endoplasmic Reticulum Stress in Pancreatitis: A Perspective from In Silico Characterization.

Pancreatitis, as a common exocrine pancreatic disease, poses a daunting challenge to patients' health and the medical system. Endoplasmic reticulum stress (ERS) plays an essential role in the pathologic process of pancreatitis. However, its mechanism is not fully understood. Therefore, this study was designed to deepen the understanding of the pathogenic mechanism of the disease by screening key ERS-related genes (ERSRGs) associated with pancreatitis. Pancreatitis mRNA data for GSE194331 (Normal: 32, Pancreatitis: 87) and pancreatitis GSE143754 (Normal: 9, Pancreatitis: 6) were downloaded from the GEO database and were used as a training and validation set, respectively. First, the training set GSE194331 was differentially expressed and intersected with the ERSRGs (n = 265) obtained from the MSigDB database to result in 42 differentially expressed ERSRGs (DE-ERSRGs). Subsequently, five candidate genes were further screened by PPI network and MCC and MCODE algorithms. However, according to the ROC curve results, AUC values of CCND1, BCL2, PIK3R1, and BCL2L1 were all greater than 0.6, indicating that they had good diagnostic performance, which was verified by the GSE143754 data set. Based on the GeneMANIA network, it was found that hub genes BCL2 and BCL2L1 may be the key factors in the regulation of mitochondrial metabolism. 24 differentially expressed pancreatitis-related genes (DE-PRGs) were found by difference analysis and Venn analysis. Hub genes BCL2 and PIK3R1 that were significantly correlated with 24 DE-PRGs were determined by Spearman analysis. ssGSEA algorithm was further used to reveal the significant correlation between these hub genes and the immune microenvironment of pancreatitis. The miRNA and lncRNA targeting hub genes were predicted using miRWalk, TargetScan, miRDB, and ENCORI databases, providing research directions for the mechanism of pancreatitis. Finally, the Network Analyst website was used to predict potential compounds associated with the hub gene. In conclusion, this study not only further supports the role of ERS in the development of pancreatitis but also provides a new perspective and direction for the development of biomarkers and mechanism of pancreatitis. At the same time, the results of this study provide a reliable research direction for the targeted treatment of pancreatitis.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信