构建铁死亡相关长链非编码RNA模型预测卵巢癌患者预后及免疫微环境

Construction of a ferroptosis-related lncRNA model to predict prognosis and immune microenvironment of ovarian cancer patients

目的构建一种可预测卵巢癌患者预后的铁死亡相关长链非编码RNA(lncRNA)模型,并探讨不同危险人群的免疫特征及免疫检查点相关基因的差异表达。方法构建铁死亡相关lncRNA的卵巢癌患者的预后模型,根据模型计算风险值(Riskscore)的中位值,将卵巢癌患者分为高风险组和低风险组。对患者的生存状态、肿瘤浸润的免疫细胞、免疫检查点抑制剂(ICI)相关基因表达量进行分析。结果构建出由5个lncRNA构成的预后模型。与低风险组患者相比,高风险组患者的生存时间明显缩短(P<0.001)。单因素Cox回归分析显示:年龄(HR=1.021,95%CI:[1.008,1.034],P=0.001)和Riskscore(HR=1.689,95%CI:[1.382,2.065],P<0.001)与卵巢癌患者的总生存预后相关;多因素Cox回归分析显示:Riskscore是总生存期的独立预测因素(HR=1.629,95%CI:[1.324,2.005],P<0.001)。多项免疫途径在两组之间的差异具有统计学意义。免疫检查点如程序性细胞死亡蛋白-1,程序性死亡配体-1,细胞毒性T淋巴细胞相关抗原-4等在两组中的表达也显著不同。结论基于铁死亡相关lncRNA的卵巢癌患者预后模型,可预测卵巢癌患者的预后和免疫状态,将有助于卵巢癌患者的个体化治疗。

Objective This study aimed at constructing a ferroptosis-related(long non coding RNA,lncRNA)model which can predict the prognosis of patients with ovarian cancer,and to explore the immune characteristics and differential expression of genes related to immune checkpoints in different risk groups.Methods Ferroptosis-related lncRNA were identified.Differentially expressed genes were obtained and analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses.Differentially expressed lncRNA were analyzed to construct a ferroptosis-related lncRNA prognostic model.According to the median value of Riskscore,patients with ovarian cancer were divided into high-risk and low-risk groups.The survival status,tumor infiltrating immune cells and immune checkpoint inhibition related markers in different groups were analyzed.Results A prognostic model composed of 5 lncRNA was constructed.Compared with the low-risk group,the survival time of the high-risk group was significantly shorter(P<0.001).Univariate Cox regression analysis showed that age(HR=1.021,95%CI:[1.008,1.034],P=0.001)and Riskscore(HR=1.689,95%CI:[1.382,2.065],P<0.001)were related to the overall survival of patients with ovarian cancer,and multivariate Cox regression analysis showed that Riskscore was still an independent predictor of overall survival(HR=1.629,95%CI:[1.324,2.005],P<0.001).There were significant differences in multiple immune pathways between the two groups.The expression of immune checkpoints such as programmed cell death protein 1,programmed death-ligand 1,cytotoxic T lymphocyte-associated protein 4,etc.was also significantly different between the two risk groups.Conclusion The prognostic model based on ferroptosis-related lncRNA can predict the prognosis and immune status of patients with ovarian cancer,and this predictive model will help determine the prognosis and individualized treatment of patients with ovarian cancer.