Nie Kai, Zhang Chao, Deng Minzi, Luo Weiwei, Ma Kejia, Xu Jiahao, Wu Xing, Yang Yuanyuan, Wang Xiaoyan
Department of Gastroenterology, The Third Xiangya Hospital of Central South University, Changsha, China.
Hunan Key Laboratory of Nonresolving Inflammation and Cancer, Cancer Research Institute, Central South University, Changsha, China.
Front Pharmacol. 2022 Apr 20;13:870796. doi: 10.3389/fphar.2022.870796. eCollection 2022.
Patients with Crohn's disease (CD) experience severely reduced quality of life, particularly those who do not respond to conventional therapies. Antitumor necrosis factor (TNF)α is commonly used as first-line therapy; however, many patients remain unresponsive to this treatment, and the identification of response predictors could facilitate the improvement of therapeutic strategies. : We screened Gene Expression Omnibus (GEO) microarray cohorts with different anti-TNFα responses in patients with CD (discovery cohort) and explored the hub genes. The finding was confirmed in independent validation cohorts, and multiple algorithms and cellular models were performed to further validate the core predictor. We screened four discovery datasets. Differentially expressed genes between anti-TNFα responders and nonresponders were confirmed in each cohort. Gene ontology enrichment revealed that innate immunity was involved in the anti-TNFα response in patients with CD. Prediction analysis of microarrays provided the minimum misclassification of genes, and the constructed network containing the hub genes supported the core status of TLR2. Furthermore, GSEA also supports TLR2 as the core predictor. The top hub genes were then validated in the validation cohort (GSE159034; < 0.05). Furthermore, ROC analyses demonstrated the significant predictive value of (AUC: 0.829), (AUC: 0.844), and (AUC: 0.841). Moreover, TLR2 expression in monocytes affected the immune-epithelial inflammatory response and epithelial barrier during lipopolysaccharide-induced inflammation ( < 0.05). Bioinformatics and experimental research identified TLR2, TREM1, CXCR1, FPR1, and FPR2 as promising candidates for predicting the anti-TNFα response in patients with Crohn's disease and especially TLR2 as a core predictor.
克罗恩病(CD)患者的生活质量严重下降,尤其是那些对传统疗法无反应的患者。抗肿瘤坏死因子(TNF)α通常用作一线治疗;然而,许多患者对这种治疗仍无反应,而识别反应预测因子有助于改进治疗策略。我们筛选了克罗恩病患者中具有不同抗TNFα反应的基因表达综合数据库(GEO)微阵列队列(发现队列),并探索了枢纽基因。这一发现在独立验证队列中得到证实,并通过多种算法和细胞模型进一步验证了核心预测因子。我们筛选了四个发现数据集。在每个队列中均证实了抗TNFα反应者与无反应者之间的差异表达基因。基因本体富集分析表明,先天性免疫参与了克罗恩病患者的抗TNFα反应。微阵列预测分析提供了最小的基因错误分类,且包含枢纽基因的构建网络支持了TLR2的核心地位。此外,基因集富集分析(GSEA)也支持TLR2作为核心预测因子。然后在验证队列(GSE159034;P<0.05)中对顶级枢纽基因进行了验证。此外,受试者工作特征(ROC)分析证明了TLR2(曲线下面积[AUC]:0.829)、TREM1(AUC:0.844)和FPR1(AUC:0.841)具有显著的预测价值。此外,在脂多糖诱导的炎症过程中,单核细胞中的TLR2表达影响免疫上皮炎症反应和上皮屏障(P<0.05)。生物信息学和实验研究确定TLR2、TREM1、CXCR1、FPR1和FPR2是预测克罗恩病患者抗TNFα反应的有前景的候选基因,尤其是TLR2作为核心预测因子。