International archives of allergy and immunology · 2025
A Risk Score Prognostic Model Based on four Ubiquitination- and Immune-Related Genes in Sepsis for Outcome Prediction and Treatment Guidance.
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Dong Qingyun, Xu Min
Аннотация
INTRODUCTION: Ubiquitination and immune regulation play an important role in sepsis. The purpose of this study was to explore the potential value of ubiquitination- and immune-related genes in sepsis and develop a risk score prognostic model based on sepsis ubiquitination- and immune-related genes for accurate outcome prediction and better treatment guidance.
METHODS: Differential expression and univariate Cox analyses were used to identify ubiquitination- and immune-related DEGs related to prognosis, and then a risk model was constructed using LASSO regression analysis. Subsequently, Kaplan-Meier analysis, time-dependent ROC curve analysis, immune cell infiltration analysis, functional enrichment analysis, drug prediction, and molecular docking were performed.
RESULTS: A total of 4 ubiquitination- and immune-related DEGs related to the prognosis of sepsis were identified. A risk score model was constructed based on these 4 genes. The proportion of death samples in the high-risk score group was higher and the OS was worse. The risk score was an independent prognostic factor for sepsis. The time-dependent ROC curve indicated that the risk score model had good predictive ability. The results of ssGSEA and GSEA showed that most immune cell infiltration levels decreased and immune- and inflammation-related pathways showed inhibitory states in the high-risk group. In addition, 7 protein-drug docking results were obtained. The binding energy of LCK and JNJ-26483327 was the lowest.
CONCLUSION: The 4 ubiquitination- and immune-related model genes may play an important role in sepsis by regulating immune cell infiltration and immune- and inflammatory-related pathways. The model constructed based on these 4 genes has good predictive value, which may help clinical doctors better evaluate the prognosis of sepsis patients and develop personalized treatment plans.
METHODS: Differential expression and univariate Cox analyses were used to identify ubiquitination- and immune-related DEGs related to prognosis, and then a risk model was constructed using LASSO regression analysis. Subsequently, Kaplan-Meier analysis, time-dependent ROC curve analysis, immune cell infiltration analysis, functional enrichment analysis, drug prediction, and molecular docking were performed.
RESULTS: A total of 4 ubiquitination- and immune-related DEGs related to the prognosis of sepsis were identified. A risk score model was constructed based on these 4 genes. The proportion of death samples in the high-risk score group was higher and the OS was worse. The risk score was an independent prognostic factor for sepsis. The time-dependent ROC curve indicated that the risk score model had good predictive ability. The results of ssGSEA and GSEA showed that most immune cell infiltration levels decreased and immune- and inflammation-related pathways showed inhibitory states in the high-risk group. In addition, 7 protein-drug docking results were obtained. The binding energy of LCK and JNJ-26483327 was the lowest.
CONCLUSION: The 4 ubiquitination- and immune-related model genes may play an important role in sepsis by regulating immune cell infiltration and immune- and inflammatory-related pathways. The model constructed based on these 4 genes has good predictive value, which may help clinical doctors better evaluate the prognosis of sepsis patients and develop personalized treatment plans.