坏死样细胞凋亡（Necroptosis）是一种与凋亡不同的新型程序性细胞死亡方式。然而，Necroptosis在卵巢癌（OC）中的作用仍不明确。本研究调查了Necroptosis相关基因（NRGs）的预后价值和OC的免疫景观。从TCGA和GTEx数据库下载了基因表达谱和临床信息。鉴定了OC和正常组织中差异表达的NRGs（DE-NRGs）。进行回归分析筛选预后NRGs和构建预测风险模型。然后将患者分为高风险和低风险组，并进行GO和KEGG分析以探索两组之间的生物信息学功能。随后，通过ESTIMATE和CIBERSORT算法评估风险水平和免疫状态的相关性。基于OC中的两个NRG标记，还分析了肿瘤突变负荷（TMB）和药物敏感性。共鉴定了42个DE-NRGs在OC中。回归分析筛选出两个NRGs（MAPK10和STAT4）具有整体生存预后价值。ROC曲线表明，风险评分对五年总生存率具有更好的预测能力。高和低风险组中均显着富集免疫相关功能。巨噬细胞M1、T细胞CD4记忆活化、T细胞CD8和T细胞调节细胞浸润免疫细胞与低风险评分相关。高风险组表现出更低的肿瘤微环境得分。低风险组中TMB较低的患者预后更好，TIDE评分较低的患者对免疫检查点抑制剂反应更好。此外，顺铂和紫杉醇在低风险组中更敏感。MAPK10和STAT4可能是OC中的重要预后因素，并且两个基因的标记在预测生存结果方面表现良好。本研究提供了评估OC预后和潜在治疗策略的新方法。©2023年作者。

Necroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study investigated the prognostic value of necroptosis-related genes (NRGs) and the immune landscape in OC.The gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs) between OC and normal tissueswere identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB) and the drug sensitivity were also analyzed based on the two-NRG signature in OC.Totally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8, and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found to be more sensitive in the low-risk group.MAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.© 2023. The Author(s).