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.

IF 6.2 Q1 IMMUNOLOGY
ImmunoTargets and Therapy Pub Date : 2024-02-02 eCollection Date: 2024-01-01 DOI:10.2147/ITT.S439289
Junhao Wu, Caihan Duan, Chaoqun Han, Xiaohua Hou
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引用次数: 0

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.

通过生物信息学和机器学习综合分析鉴定 CXC 趋化因子受体 2 (CXCR2) 是独立于嗜酸性粒细胞的新型小儿嗜酸性粒细胞性食管炎诊断生物标记物
背景:嗜酸性粒细胞食管炎(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,严重影响了他们的生活质量。因此,本研究旨在评估有助于诊断儿童嗜酸性食管炎的关键分子标记物:方法:现有三个儿童咽鼓管畸形相关基因表达数据集:从 GEO 数据库中下载了 GSE184182、GSE 197702、GSE55794 和 GSE173895 数据集。将 "limma "确定的差异表达基因(DEGs)与加权基因共表达网络分析(WGCNA)确定的关键模块基因进行交叉,并对共享基因进行功能富集分析。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被用来揭示EoE的候选诊断标记。接受者操作特征曲线(ROC)显示了该标记物的鉴别诊断效果,在线数据库也预测了其分子调控网络。最后,我们进行了基因组富集分析(GSEA),并使用 CIBERSORT 算法评估了咽喉炎/对照样本的免疫细胞浸润情况。我们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:在EoE中,936个DEGs和1446个关键模块基因的交叉产生了567个基因,这些基因主要富集在免疫调节中。在构建 PPI 网络并通过机器学习过滤后,CXCR2 成为小儿咽喉炎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果(AUC = ~1.00)。观察到多种浸润的免疫细胞在不同程度上参与破坏食管上皮的平衡:结论:与免疫相关的 CXCR2 基因被证明是食管水肿很有希望的诊断指标,失调的调节性 T 细胞(Tregs)/中性粒细胞可能在儿童食管水肿的发病机制中起着至关重要的作用。
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来源期刊
CiteScore
16.50
自引率
0.00%
发文量
7
审稿时长
16 weeks
期刊介绍: Immuno Targets and Therapy is an international, peer-reviewed open access journal focusing on the immunological basis of diseases, potential targets for immune based therapy and treatment protocols employed to improve patient management. Basic immunology and physiology of the immune system in health, and disease will be also covered.In addition, the journal will focus on the impact of management programs and new therapeutic agents and protocols on patient perspectives such as quality of life, adherence and satisfaction.
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