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Abstract：
BACKGROUND: Variations exist in the response of patients with Crohn\'s disease (CD) to ustekinumab (UST) treatment, but the underlying cause remains unknown. Our objective was to investigate the involvement of immune cells and identify potential biomarkers that could predict the response to interleukin (IL) 12/23 inhibitors in patients with CD.
METHODS: The GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset.
RESULTS: A total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers.
CONCLUSIONS: Th1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients.
BACKGROUND: Trial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www.
RESULTS: gov .
METHODS: The GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset.
RESULTS: A total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers.
CONCLUSIONS: Th1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients.
BACKGROUND: Trial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www.
RESULTS: gov .
摘要：
背景：克罗恩病（CD）患者对ustekinumab（UST）治疗的反应存在差异，但根本原因仍然未知。我们的目的是研究免疫细胞的参与，并确定可以预测CD患者对白介素（IL）12/23抑制剂的反应的潜在生物标志物。
方法：GSE207022数据集，其中包括CD队列中的54名非响应者和9名UST响应者，被分析。鉴定差异表达基因(DEGs)并进行基因本体论(GO)和京都基因和基因组百科全书(KEGG)途径分析。使用最小绝对收缩和选择算子（LASSO）回归来筛选最强大的集线器基因。进行受试者工作特征(ROC)曲线分析以评估这些基因的预测性能。使用单样品基因组富集分析(ssGSEA)来估计免疫细胞类型的比例。对这些显著改变的基因进行聚类分析,形成免疫细胞相关的浸润。为了验证候选人的可靠性，在前瞻性队列中使用UST作为一线生物制剂的患者被纳入作为独立的验证数据集.
结果：在综合数据集中确定了总共99个DEG。GO和KEGG分析显示CD患者的免疫应答途径显著富集。13个基因（SOCS3，CD55，KDM5D，IGFBP5,LCN2,SLC15A1,XPNPEP2,HLA-DQA2,HMGCS2,DDX3Y,ITGB2，CDKN2B和HLA-DQA1），主要与有反应的患者和无反应的患者有关，被识别并包括在LASSO分析中。这些基因准确地预测了治疗反应，曲线下面积（AUC）为0.938。在无反应个体中，1型T辅助细胞（Th1）细胞极化相对较强。在Th1细胞与LCN2和KDM5D基因之间观察到正连接。此外，我们采用独立的验证数据集和早期实验验证来验证LCN2和KDM5D基因作为有效的预测标记.
结论：Th1细胞极化是CD患者对UST治疗无反应的重要原因。LCN2和KDM5D可用作预测标志物以有效识别无应答患者。
背景：试用注册号：NCT05542459；注册日期：2022-09-14；URL：https：//www。
结果：政府。
方法：GSE207022数据集，其中包括CD队列中的54名非响应者和9名UST响应者，被分析。鉴定差异表达基因(DEGs)并进行基因本体论(GO)和京都基因和基因组百科全书(KEGG)途径分析。使用最小绝对收缩和选择算子（LASSO）回归来筛选最强大的集线器基因。进行受试者工作特征(ROC)曲线分析以评估这些基因的预测性能。使用单样品基因组富集分析(ssGSEA)来估计免疫细胞类型的比例。对这些显著改变的基因进行聚类分析,形成免疫细胞相关的浸润。为了验证候选人的可靠性，在前瞻性队列中使用UST作为一线生物制剂的患者被纳入作为独立的验证数据集.
结果：在综合数据集中确定了总共99个DEG。GO和KEGG分析显示CD患者的免疫应答途径显著富集。13个基因（SOCS3，CD55，KDM5D，IGFBP5,LCN2,SLC15A1,XPNPEP2,HLA-DQA2,HMGCS2,DDX3Y,ITGB2，CDKN2B和HLA-DQA1），主要与有反应的患者和无反应的患者有关，被识别并包括在LASSO分析中。这些基因准确地预测了治疗反应，曲线下面积（AUC）为0.938。在无反应个体中，1型T辅助细胞（Th1）细胞极化相对较强。在Th1细胞与LCN2和KDM5D基因之间观察到正连接。此外，我们采用独立的验证数据集和早期实验验证来验证LCN2和KDM5D基因作为有效的预测标记.
结论：Th1细胞极化是CD患者对UST治疗无反应的重要原因。LCN2和KDM5D可用作预测标志物以有效识别无应答患者。
背景：试用注册号：NCT05542459；注册日期：2022-09-14；URL：https：//www。
结果：政府。
