一种与溃疡性结肠炎诊断及生物治疗反应相关的新型活化自然杀伤细胞相关基因评分的鉴定
Identification of a Novel Activated NK-Associated Gene Score Associated with Diagnosis and Biological Therapy Response in Ulcerative Colitis.
作者信息
Dong Siyuan, Zhang Yu, Ye Lingna, Cao Qian
机构信息
Department of Gastroenterology, Sir Run Run Shaw Hospital, College of Medicine Zhejiang University, Hangzhou, China.
Inflammatory Bowel Disease Center, Sir Run Run Shaw Hospital, College of Medicine Zhejiang University, Hangzhou, China.
出版信息
Digestion. 2025;106(1):1-22. doi: 10.1159/000540939. Epub 2024 Aug 23.
INTRODUCTION
Natural killer (NK) cells are associated with the pathogenesis of ulcerative colitis (UC); however, their precise contributions remain unclear. The present study aimed to investigate the diagnostic value of the activated NK-associated gene (ANAG) score in UC and evaluate its predictive value in response to biological therapy.
METHODS
Bulk RNA-seq and scRNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) and Single Cell Portal (SCP) databases. In the bulk RNA-seq, differentially expressed genes (DEGs) were screened by the "Batch correction" and "Robust rank aggregation" (RRA) methods. The immune infiltration landscape was estimated using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. DEGs that correlated with activated NK cells were identified as activated NK-associated genes (ANAGs). Protein-protein interaction (PPI) analysis and least absolute shrinkage and selection operator (LASSO) regression were used to screen key ANAGs and establish an ANAG score. The expression levels of the four key ANAGs were validated in human samples by real-time quantitative polymerase chain reaction (RT-qPCR) and immunofluorescence. The potential therapeutic drugs for UC were identified using the DSigDB database. Through scRNA-seq data analysis, the cell scores based on the ANAGs were calculated by "AddModuleScore" and "AUCell."
RESULTS
Immune infiltration analysis revealed a higher abundance of activated NK cells in noninflamed UC tissues (ssGSEA, p < 0.001; CIBERSORT, p < 0.01). Fifty-four DEGs correlated with activated NK cells were identified as ANAGs. The ANAG score was established using four key ANAGs (SELP, TIMP1, MMP7, and ABCG2). The ANAG scores were significantly higher in inflamed tissues (p < 0.001) and in biological therapy nonresponders (NR) tissues before treatment (golimumab, p < 0.05; ustekinumab, p < 0.001). The ANAG score demonstrated an excellent diagnostic value (AUC = 0.979). Patients with higher ANAG scores before treatment were more likely to experience a lack of response to golimumab or ustekinumab (golimumab, p < 0.05; ustekinumab, p < 0.001).
CONCLUSION
This study established a novel ANAG score with the ability to precisely diagnose UC and distinguish the efficacy of biological treatment.
INTRODUCTION
Natural killer (NK) cells are associated with the pathogenesis of ulcerative colitis (UC); however, their precise contributions remain unclear. The present study aimed to investigate the diagnostic value of the activated NK-associated gene (ANAG) score in UC and evaluate its predictive value in response to biological therapy.
METHODS
Bulk RNA-seq and scRNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) and Single Cell Portal (SCP) databases. In the bulk RNA-seq, differentially expressed genes (DEGs) were screened by the "Batch correction" and "Robust rank aggregation" (RRA) methods. The immune infiltration landscape was estimated using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. DEGs that correlated with activated NK cells were identified as activated NK-associated genes (ANAGs). Protein-protein interaction (PPI) analysis and least absolute shrinkage and selection operator (LASSO) regression were used to screen key ANAGs and establish an ANAG score. The expression levels of the four key ANAGs were validated in human samples by real-time quantitative polymerase chain reaction (RT-qPCR) and immunofluorescence. The potential therapeutic drugs for UC were identified using the DSigDB database. Through scRNA-seq data analysis, the cell scores based on the ANAGs were calculated by "AddModuleScore" and "AUCell."
RESULTS
Immune infiltration analysis revealed a higher abundance of activated NK cells in noninflamed UC tissues (ssGSEA, p < 0.001; CIBERSORT, p < 0.01). Fifty-four DEGs correlated with activated NK cells were identified as ANAGs. The ANAG score was established using four key ANAGs (SELP, TIMP1, MMP7, and ABCG2). The ANAG scores were significantly higher in inflamed tissues (p < 0.001) and in biological therapy nonresponders (NR) tissues before treatment (golimumab, p < 0.05; ustekinumab, p < 0.001). The ANAG score demonstrated an excellent diagnostic value (AUC = 0.979). Patients with higher ANAG scores before treatment were more likely to experience a lack of response to golimumab or ustekinumab (golimumab, p < 0.05; ustekinumab, p < 0.001).
CONCLUSION
This study established a novel ANAG score with the ability to precisely diagnose UC and distinguish the efficacy of biological treatment.
引言
自然杀伤（NK）细胞与溃疡性结肠炎（UC）的发病机制有关；然而，它们的确切作用仍不清楚。本研究旨在探讨活化NK相关基因（ANAG）评分在UC中的诊断价值，并评估其对生物治疗反应的预测价值。
方法
从基因表达综合数据库（GEO）和单细胞门户（SCP）数据库中获取批量RNA测序（bulk RNA-seq）和单细胞RNA测序（scRNA-seq）数据集。在批量RNA测序中，通过“批次校正”和“稳健秩聚合”（RRA）方法筛选差异表达基因（DEG）。使用单样本基因集富集分析（ssGSEA）和CIBERSORT评估免疫浸润情况。与活化NK细胞相关的DEG被鉴定为活化NK相关基因（ANAG）。采用蛋白质-蛋白质相互作用（PPI）分析和最小绝对收缩和选择算子（LASSO）回归筛选关键ANAG并建立ANAG评分。通过实时定量聚合酶链反应（RT-qPCR）和免疫荧光在人体样本中验证四个关键ANAG的表达水平。使用DSigDB数据库鉴定UC的潜在治疗药物。通过scRNA-seq数据分析，通过“AddModuleScore”和“AUCell”计算基于ANAG的细胞评分。
结果
免疫浸润分析显示，在未发炎的UC组织中活化NK细胞的丰度更高（ssGSEA，p<0.001；CIBERSORT，p<0.01）。54个与活化NK细胞相关的DEG被鉴定为ANAG。使用四个关键ANAG（SELP、TIMP1、MMP7和ABCG2）建立ANAG评分。在发炎组织中以及生物治疗无反应者（NR）治疗前的组织中，ANAG评分显著更高（戈利木单抗，p<0.05；优特克单抗，p<0.001）。ANAG评分显示出优异的诊断价值（AUC=0.979）。治疗前ANAG评分较高的患者更有可能对戈利木单抗或优特克单抗无反应（戈利木单抗，p<0.05；优特克单抗，p<0.001）。
结论
本研究建立了一种新型ANAG评分，能够准确诊断UC并区分生物治疗的疗效。
引言
自然杀伤（NK）细胞与溃疡性结肠炎（UC）的发病机制有关；然而，它们的确切作用仍不清楚。本研究旨在探讨活化NK相关基因（ANAG）评分在UC中的诊断价值，并评估其对生物治疗反应的预测价值。
方法
从基因表达综合数据库（GEO）和单细胞门户（SCP）数据库中获取批量RNA测序（bulk RNA-seq）和单细胞RNA测序（scRNA-seq）数据集。在批量RNA测序中，通过“批次校正”和“稳健秩聚合”（RRA）方法筛选差异表达基因（DEG）。使用单样本基因集富集分析（ssGSEA）和CIBERSORT评估免疫浸润情况。与活化NK细胞相关的DEG被鉴定为活化NK相关基因（ANAG）。采用蛋白质-蛋白质相互作用（PPI）分析和最小绝对收缩和选择算子（LASSO）回归筛选关键ANAG并建立ANAG评分。通过实时定量聚合酶链反应（RT-qPCR）和免疫荧光在人体样本中验证四个关键ANAG的表达水平。使用DSigDB数据库鉴定UC的潜在治疗药物。通过scRNA-seq数据分析，通过“AddModuleScore”和“AUCell”计算基于ANAG的细胞评分。
结果
免疫浸润分析显示，在未发炎的UC组织中活化NK细胞的丰度更高（ssGSEA，p<0.001；CIBERSORT，p<0.01）。54个与活化NK细胞相关的DEG被鉴定为ANAG。使用四个关键ANAG（SELP、TIMP1、MMP7和ABCG2）建立ANAG评分。在发炎组织中以及生物治疗无反应者（NR）治疗前的组织中，ANAG评分显著更高（戈利木单抗，p<0.05；优特克单抗，p<0.001）。ANAG评分显示出优异的诊断价值（AUC=0.979）。治疗前ANAG评分较高的患者更有可能对戈利木单抗或优特克单抗无反应（戈利木单抗，p<0.05；优特克单抗，p<0.001）。
结论
本研究建立了一种新型ANAG评分，能够准确诊断UC并区分生物治疗的疗效。
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