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Updated: Jun 11, 2026

Differentiating Functional Roles of Gene Expression from Immune and Non-immune Cells in Mouse Colitis by Bone Marrow Transplantation
Published on: October 1, 2012
Identification of a Novel Activated NK-Associated Gene Score Associated with Diagnosis and Biological Therapy
Siyuan Dong1,2,3, Yu Zhang1,2,3, Lingna Ye1,2,3
1Department of Gastroenterology, Sir Run Run Shaw Hospital, College of Medicine Zhejiang University, Hangzhou, China.
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.
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