PDF(Pubmed)
Abstract：
UNASSIGNED: In spite of its high mortality rate and poor prognosis, the pathogenesis of sepsis is still incompletely understood. This study established a cuproptosis-based risk model to diagnose and predict the risk of sepsis. In addition, the cuproptosis-related genes were identified for targeted therapy.
UNASSIGNED: Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model\'s accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis.
UNASSIGNED: ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype.
UNASSIGNED: This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.
UNASSIGNED: Single-cell sequencing analyses were used to characterize the cuproptosis activity score (CuAS) and intercellular communications in sepsis. Differential cuproptosis-related genes (CRGs) were identified in conjunction with single-cell and bulk RNA sequencing. LASSO and Cox regression analyses were employed to develop a risk model. Three external cohorts were conducted to assess the model\'s accuracy. Differences in immune infiltration, immune cell subtypes, pathway enrichment, and the expression of immunomodulators were further evaluated in distinct groups. Finally, various in-vitro experiments, such as flow cytometry, Western blot, and ELISA, were used to explore the role of LST1 in sepsis.
UNASSIGNED: ScRNA-seq analysis demonstrated that CuAS was highly enriched in monocytes and was closely related to the poor prognosis of sepsis patients. Patients with higher CuAS exhibited prominent strength and numbers of cell-cell interactions. A total of five CRGs were identified based on the LASSO and Cox regression analyses, and a CRG-based risk model was established. The lower riskScore cohort exhibited enhanced immune cell infiltration, elevated immune scores, and increased expression of immune modulators, indicating the activation of an antibacterial response. Ultimately, in-vitro experiments demonstrated that LST1, a key gene in the risk model, was enhanced in the macrophage in response to LPS, which was closely related to the decrease of macrophage survival rate, the enhancement of apoptosis and oxidative stress injury, and the imbalance of the M1/M2 phenotype.
UNASSIGNED: This study constructed a cuproptosis-related risk model to accurately predict the prognosis of sepsis. We further characterized the cuproptosis-related gene LST1 to provide a theoretical framework for sepsis therapy.
摘要：
■尽管其死亡率高，预后差，脓毒症的发病机制尚不完全清楚。本研究建立了基于角化的风险模型来诊断和预测脓毒症的风险。此外,确定了与角化相关的基因用于靶向治疗.
■单细胞测序分析用于表征败血症中的细胞凋亡活性评分(CuAS)和细胞间通讯。结合单细胞和批量RNA测序鉴定了差异角化相关基因（CRG）。采用LASSO和Cox回归分析建立风险模型。进行了三个外部队列以评估模型的准确性。免疫浸润的差异，免疫细胞亚型，途径富集，在不同的组中进一步评估了免疫调节剂的表达。最后,各种体外实验，如流式细胞术，蛋白质印迹,和ELISA，用于探讨LST1在脓毒症中的作用。
■ScRNA-seq分析表明，CuAS在单核细胞中高度富集，与脓毒症患者的不良预后密切相关。具有较高CuAS的患者表现出显著的细胞-细胞相互作用的强度和数量。根据LASSO和Cox回归分析，总共确定了五个CRG，建立了基于CRG的风险模型。较低的风险评分队列表现出增强的免疫细胞浸润，免疫评分升高,免疫调节剂的表达增加，表明抗菌反应的激活。最终,体外实验表明，风险模型中的关键基因LST1，巨噬细胞对LPS的反应增强，这与巨噬细胞存活率的降低密切相关，细胞凋亡和氧化应激损伤的增强，和M1/M2表型的失衡。
■本研究构建了一个与角化相关的风险模型，以准确预测脓毒症的预后。我们进一步表征了角化相关基因LST1，为脓毒症治疗提供了理论框架。
■单细胞测序分析用于表征败血症中的细胞凋亡活性评分(CuAS)和细胞间通讯。结合单细胞和批量RNA测序鉴定了差异角化相关基因（CRG）。采用LASSO和Cox回归分析建立风险模型。进行了三个外部队列以评估模型的准确性。免疫浸润的差异，免疫细胞亚型，途径富集，在不同的组中进一步评估了免疫调节剂的表达。最后,各种体外实验，如流式细胞术，蛋白质印迹,和ELISA，用于探讨LST1在脓毒症中的作用。
■ScRNA-seq分析表明，CuAS在单核细胞中高度富集，与脓毒症患者的不良预后密切相关。具有较高CuAS的患者表现出显著的细胞-细胞相互作用的强度和数量。根据LASSO和Cox回归分析，总共确定了五个CRG，建立了基于CRG的风险模型。较低的风险评分队列表现出增强的免疫细胞浸润，免疫评分升高,免疫调节剂的表达增加，表明抗菌反应的激活。最终,体外实验表明，风险模型中的关键基因LST1，巨噬细胞对LPS的反应增强，这与巨噬细胞存活率的降低密切相关，细胞凋亡和氧化应激损伤的增强，和M1/M2表型的失衡。
■本研究构建了一个与角化相关的风险模型，以准确预测脓毒症的预后。我们进一步表征了角化相关基因LST1，为脓毒症治疗提供了理论框架。
