Suppr超能文献

通过综合生物信息学和机器学习分析鉴定CXC趋化因子受体2(CXCR2)作为小儿嗜酸性粒细胞性食管炎一种新的非嗜酸性粒细胞依赖性诊断生物标志物

Identification of CXC Chemokine Receptor 2 (CXCR2) as a Novel Eosinophils-Independent Diagnostic Biomarker of Pediatric Eosinophilic Esophagitis by Integrated Bioinformatic and Machine-Learning Analysis.

作者信息

Wu Junhao, Duan Caihan, Han Chaoqun, Hou Xiaohua

机构信息

Division of Gastroenterology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.

出版信息

Immunotargets Ther. 2024 Feb 2;13:55-74. doi: 10.2147/ITT.S439289. eCollection 2024.

Abstract

BACKGROUND

Eosinophilic esophagitis (EoE) is a complex allergic condition frequently accompanied by various atopic comorbidities in children, which significantly affects their life qualities. Therefore, this study aimed to evaluate pivotal molecular markers that may facilitate the diagnosis of EoE in pediatric patients.

METHODS

Three available EoE-associated gene expression datasets in children: GSE184182, GSE 197702, GSE55794, along with GSE173895 were downloaded from the GEO database. Differentially expressed genes (DEGs) identified by "limma" were intersected with key module genes identified by weighted gene co-expression network analysis (WGCNA), and the shared genes went through functional enrichment analysis. The protein-protein interaction (PPI) network and the machine learning algorithms: least absolute shrinkage and selection operator (LASSO), random forest (RF), and XGBoost were used to reveal candidate diagnostic markers for EoE. The receiver operating characteristic (ROC) curve showed the efficacy of differential diagnosis of this marker, along with online databases predicting its molecular regulatory network. Finally, we performed gene set enrichment analysis (GSEA) and assessed immune cell infiltration of EoE/control samples by using the CIBERSORT algorithm. The correlations between the key diagnostic biomarker and immune cells were also investigated.

RESULTS

The intersection of 936 DEGs and 1446 key module genes in EoE generated 567 genes, which were primarily enriched in immune regulation. Following the construction of the PPI network and filtration by machine learning, CXCR2 served as a potential diagnostic biomarker of pediatric EoE with a perfect diagnostic efficacy (AUC = ~1.00) in regional tissue/peripheral whole blood samples. Multiple infiltrated immune cells were observed to participate in disrupting the homeostasis of esophageal epithelium to varying degrees.

CONCLUSION

The immune-correlated CXCR2 gene was proved to be a promising diagnostic indicator for EoE, and dysregulated regulatory T cells (Tregs)/neutrophils might play a crucial role in the pathogenesis of EoE in children.

摘要

背景

嗜酸性粒细胞性食管炎(EoE)是一种复杂的过敏性疾病,在儿童中常伴有各种特应性合并症,严重影响其生活质量。因此,本研究旨在评估可能有助于儿科患者EoE诊断的关键分子标志物。

方法

从基因表达综合数据库(GEO数据库)下载了三个可用的儿童EoE相关基因表达数据集:GSE184182、GSE197702、GSE55794,以及GSE173895。通过“limma”鉴定的差异表达基因(DEGs)与通过加权基因共表达网络分析(WGCNA)鉴定的关键模块基因进行交集分析,对共享基因进行功能富集分析。利用蛋白质-蛋白质相互作用(PPI)网络和机器学习算法:最小绝对收缩和选择算子(LASSO)、随机森林(RF)和XGBoost来揭示EoE的候选诊断标志物。受试者工作特征(ROC)曲线显示了该标志物的鉴别诊断效能,同时利用在线数据库预测其分子调控网络。最后,我们进行了基因集富集分析(GSEA),并使用CIBERSORT算法评估EoE/对照样本的免疫细胞浸润情况。还研究了关键诊断生物标志物与免疫细胞之间的相关性。

结果

EoE中936个DEGs与1446个关键模块基因的交集产生了567个基因,这些基因主要富集于免疫调节。构建PPI网络并通过机器学习过滤后,CXCR2作为儿科EoE的潜在诊断生物标志物,在区域组织/外周全血样本中具有完美的诊断效能(AUC = ~1.00)。观察到多种浸润免疫细胞不同程度地参与破坏食管上皮的稳态。

结论

免疫相关的CXCR2基因被证明是EoE的一个有前景的诊断指标,调节性T细胞(Tregs)/中性粒细胞失调可能在儿童EoE的发病机制中起关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/251d/10849108/cb4ef524bb9a/ITT-13-55-g0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验