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Abstract：
UNASSIGNED: Studies have shown that Nicotinamide adenine dinucleotide (NAD+) metabolism can promote the occurrence and development of glioma. However, the specific effects and mechanisms of NAD+ metabolism in glioma are unclear and there were no systematic researches about NAD+ metabolism related genes to predict the survival of patients with glioma.
UNASSIGNED: The research was performed based on expression data of glioma cases in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Firstly, TCGA-glioma cases were classified into different subtypes based on 49 NAD+ metabolism-related genes (NMRGs) by consensus clustering. NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were gotten by intersecting the 49 NMRGs and differentially expressed genes (DEGs) between normal and glioma samples. Then a risk model was built by Cox analysis and the least shrinkage and selection operator (LASSO) regression analysis. The validity of the model was verified by survival curves and receiver operating characteristic (ROC) curves. In addition, independent prognostic analysis of the risk model was performed by Cox analysis. Then, we also identified different immune cells, HLA family genes and immune checkpoints between high and low risk groups. Finally, the functions of model genes at single-cell level were also explored.
UNASSIGNED: Consensus clustering classified glioma patients into two subtypes, and the overall survival (OS) of the two subtypes differed. A total of 11 NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were screened by overlapping 5,995 differentially expressed genes (DEGs) and 49 NAD+ metabolism-related genes (NMRGs). Next, four model genes, PARP9, BST1, NMNAT2, and CD38, were obtained by Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses and to construct a risk model. The OS of high-risk group was lower. And the area under curves (AUCs) of Receiver operating characteristic (ROC) curves were >0.7 at 1, 3, and 5 years. Cox analysis showed that age, grade G3, grade G4, IDH status, ATRX status, BCR status, and risk Scores were reliable independent prognostic factors. In addition, three different immune cells, Mast cells activated, NK cells activated and B cells naive, 24 different HLA family genes, such as HLA-DPA1 and HLA-H, and 8 different immune checkpoints, such as ICOS, LAG3, and CD274, were found between the high and low risk groups. The model genes were significantly relevant with proliferation, cell differentiation, and apoptosis.
UNASSIGNED: The four genes, PARP9, BST1, NMNAT2, and CD38, might be important molecular biomarkers and therapeutic targets for glioma patients.
UNASSIGNED: The research was performed based on expression data of glioma cases in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Firstly, TCGA-glioma cases were classified into different subtypes based on 49 NAD+ metabolism-related genes (NMRGs) by consensus clustering. NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were gotten by intersecting the 49 NMRGs and differentially expressed genes (DEGs) between normal and glioma samples. Then a risk model was built by Cox analysis and the least shrinkage and selection operator (LASSO) regression analysis. The validity of the model was verified by survival curves and receiver operating characteristic (ROC) curves. In addition, independent prognostic analysis of the risk model was performed by Cox analysis. Then, we also identified different immune cells, HLA family genes and immune checkpoints between high and low risk groups. Finally, the functions of model genes at single-cell level were also explored.
UNASSIGNED: Consensus clustering classified glioma patients into two subtypes, and the overall survival (OS) of the two subtypes differed. A total of 11 NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were screened by overlapping 5,995 differentially expressed genes (DEGs) and 49 NAD+ metabolism-related genes (NMRGs). Next, four model genes, PARP9, BST1, NMNAT2, and CD38, were obtained by Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses and to construct a risk model. The OS of high-risk group was lower. And the area under curves (AUCs) of Receiver operating characteristic (ROC) curves were >0.7 at 1, 3, and 5 years. Cox analysis showed that age, grade G3, grade G4, IDH status, ATRX status, BCR status, and risk Scores were reliable independent prognostic factors. In addition, three different immune cells, Mast cells activated, NK cells activated and B cells naive, 24 different HLA family genes, such as HLA-DPA1 and HLA-H, and 8 different immune checkpoints, such as ICOS, LAG3, and CD274, were found between the high and low risk groups. The model genes were significantly relevant with proliferation, cell differentiation, and apoptosis.
UNASSIGNED: The four genes, PARP9, BST1, NMNAT2, and CD38, might be important molecular biomarkers and therapeutic targets for glioma patients.
摘要：
UNASSIGNED:研究表明烟酰胺腺嘌呤二核苷酸(NAD+)代谢可促进胶质瘤的发生发展。然而,NAD+代谢在脑胶质瘤中的具体作用和机制尚不清楚,目前尚无关于NAD+代谢相关基因预测脑胶质瘤患者生存的系统研究。
UNASSIGNED：这项研究是基于肿瘤基因组图谱（TCGA）和中国胶质瘤基因组图谱（CGGA）数据库中胶质瘤病例的表达数据进行的。首先,根据49个NAD+代谢相关基因（NMRGs），通过共识聚类将TCGA-胶质瘤病例分为不同的亚型。通过将正常和神经胶质瘤样品之间的49个NMRG和差异表达基因（DEG）相交，获得了NAD代谢相关的差异表达基因（NMR-DEG）。然后通过Cox分析和最小收缩和选择算子（LASSO）回归分析建立了风险模型。通过生存曲线和受试者工作特征(ROC)曲线验证了模型的有效性。此外,通过Cox分析对风险模型进行独立预后分析.然后，我们还鉴定了不同的免疫细胞，HLA家族基因和高危和低危人群之间的免疫检查点。最后,还探讨了模型基因在单细胞水平的功能。
未经评估：共识聚类将神经胶质瘤患者分为两种亚型，两种亚型的总生存期（OS）不同。通过重叠的5,995个差异表达基因(DEG)和49个NAD+代谢相关基因(NMRG)筛选出11个NAD+代谢相关差异表达基因(NMR-DEG)。接下来,四个模型基因，通过Cox回归和最小绝对收缩和选择算子（Lasso）回归分析获得PARP9，BST1，NMNAT2和CD38，并构建风险模型。高危人群OS较低。受试者工作特征曲线(ROC)曲线的曲线下面积(AUC)在1年、3年和5年均>0.7。Cox分析显示年龄,G3级，G4级，IDH状态，ATRX状态,BCR状态,风险评分是可靠的独立预后因素。此外,三种不同的免疫细胞，肥大细胞激活，NK细胞激活和B细胞幼稚，24个不同的HLA家族基因，如HLA-DPA1和HLA-H，和8个不同的免疫检查点,比如ICOS，在高风险和低风险组之间发现了LAG3和CD274。模型基因与增殖显著相关,细胞分化，和凋亡。
未经证实：四个基因，PARP9，BST1，NMNAT2和CD38可能是神经胶质瘤患者的重要分子生物标志物和治疗靶标。
UNASSIGNED：这项研究是基于肿瘤基因组图谱（TCGA）和中国胶质瘤基因组图谱（CGGA）数据库中胶质瘤病例的表达数据进行的。
未经评估：共识聚类将神经胶质瘤患者分为两种亚型，
未经证实：四个基因，
