Identification of NAD(+) Metabolism-Derived Gene Signatures in Ovarian Cancer Prognosis and Immunotherapy.
Identification of NAD(+) Metabolism-Derived Gene Signatures in Ovarian Cancer Prognosis and Immunotherapy.
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DOI：
10.3389/fgene.2022.905238
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发表时间：
2022
影响因子：
3.7
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中科院分区：
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背景资料：烟酰胺腺嘌呤二核苷酸（NAD+）已成为细胞信号传导和存活途径的关键调节剂，影响肿瘤的发生和进展。在这项研究中，研究了循环NAD+代谢相关基因（NMRG）是否可用于预测卵巢癌（OC）患者的免疫治疗反应。 方法：在这项研究中，在OC患者中全面检查了NMRG，通过无监督聚类确定了三种不同的NMRG亚型，并基于LASSO考克斯回归分析生成了NAD+相关的预后模型，并生成了风险评分（RS）。ROC曲线和独立的验证队列用于评估模型的准确性。进行GSEA富集分析以研究可能的功能途径。此外，还研究了RS在肿瘤微环境、免疫治疗和化疗中的作用。 结果：根据NMRGs的表达模式，我们发现了三个不同的亚组。通过LASSO回归选择12个基因以创建预后风险标记。高RS被发现与更差的预后有关。在卵巢癌患者中，RS是一个独立的预后指标。免疫浸润细胞在低RS组中显著过表达，因为免疫相关的功能途径显著富集。此外，免疫治疗预测表明，低RS患者对免疫治疗更敏感。 结论：对于OC患者，NMRG是有希望的生物标志物。我们的预后标志对OC预后和免疫治疗反应具有潜在的预测价值。本研究的结果有助于提高我们对业主立案法团中的NMRG的认识。
Background: Nicotinamide adenine dinucleotide (NAD+) has emerged as a critical regulator of cell signaling and survival pathways, affecting tumor initiation and progression. In this study it was investigated whether circulating NAD+ metabolism-related genes (NMRGs) could be used to predict immunotherapy response in ovarian cancer (OC) patients. Method: In this study, NMRGs were comprehensively examined in OC patients, three distinct NMRGs subtypes were identified through unsupervised clustering, and an NAD+-related prognostic model was generated based on LASSO Cox regression analysis and generated a risk score (RS). ROC curves and an independent validation cohort were used to assess the model’s accuracy. A GSEA enrichment analysis was performed to investigate possible functional pathways. Furthermore, the role of RS in the tumor microenvironment, immunotherapy, and chemotherapy was also investigated. Result: We found three different subgroups based on NMRGs expression patterns. Twelve genes were selected by LASSO regression to create a prognostic risk signature. High-RS was founded to be linked to a worse prognosis. In Ovarian Cancer Patients, RS is an independent prognostic marker. Immune infiltrating cells were considerably overexpressed in the low-RS group, as immune-related functional pathways were significantly enriched. Furthermore, immunotherapy prediction reveal that patients with low-RS are more sensitive to immunotherapy. Conclusion: For a patient with OC, NMRGs are promising biomarkers. Our prognostic signature has potential predictive value for OC prognosis and immunotherapy response. The results of this study may help improve our understanding of NMRG in OCs.