Lei Kai, Tan Binghua, Liang Ruihao, Lyu Yingcheng, Wang Kexi, Wang Wenjian, Wang Kefeng, Hu Xueting, Wu Duoguang, Lin Huayue, Wang Minghui
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University Guangzhou, Guangdong, China.
Department of Thoracic Surgery, Sun Yat-sen Memorial Hospital, Sun Yat-sen University Guangzhou, Guangdong, China.
Am J Cancer Res. 2022 Nov 15;12(11):5160-5182. eCollection 2022.
Necroptosis is a new programmed formation of necrotizing cell death, which plays important role in tumor biological regulation, including tumorigenesis and immunity. In this study, we aimed to establish and validate a prediction model based on necroptosis-related genes (NRGs) for lung adenocarcinoma (LUAD) prognosis and tumor immunity. The training set consisted of samples from The Cancer Genome Atlas (TCGA) dataset (n = 334), and the validation sets consisted of samples from the Gene Expression Omnibus (GEO) (n = 439) and clinical (n = 20) datasets. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that 28 necroptosis-related differentially expressed genes (DEGs) were enriched in cell death and immune regulation. RT-qPCR and western blot results showed the low expression of necroptosis markers in LUAD cells. A prognostic gene signature based on 6 NRGs ( and ) was constructed and the risk score was calculated. Multivariate Cox regression analysis showed that the risk score was an independent risk factor [hazard ratio (HR) = 1.220, 95% confidence interval (CI): 1.154-1.290, P<0.001]. In the TCGA cohort, a high-risk score was associated with poor prognosis, weak immune infiltration, and low expression at immune checkpoints, which was validated in the GEO and clinical cohorts. Our findings showed that the patients in the low-risk group had a better progression-free survival (PFS) [not reached vs. 8.5 months, HR = 0.18, 95% CI: 0.04-0.72, P<0.001] than those in the high-risk score group. Immunotherapy tolerance was found to be correlated with the high-risk score, and the risk score combined with PD-L1 (AUC = 0.808, 95% CI: 0.613-1.000) could better predict the immunotherapy response of LUAD. A nomogram was shown to have a strong ability to predict the individual survival rate of patients with LUAD in the TCGA and GSE68465 cohorts. We constructed and validated a potential prognostic signature consisting of 6 NRGs to predict the prognosis and tumor immunity of LUAD, which may be helpful to guide the individualized immunotherapy of LUAD.
坏死性凋亡是一种新的程序性坏死性细胞死亡形式,在肿瘤生物学调节中发挥重要作用,包括肿瘤发生和免疫。在本研究中,我们旨在建立并验证基于坏死性凋亡相关基因(NRGs)的预测模型,用于预测肺腺癌(LUAD)的预后和肿瘤免疫。训练集由来自癌症基因组图谱(TCGA)数据集的样本组成(n = 334),验证集由来自基因表达综合数据库(GEO)(n = 439)和临床(n = 20)数据集的样本组成。基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路分析表明,28个坏死性凋亡相关差异表达基因(DEGs)在细胞死亡和免疫调节中富集。RT-qPCR和蛋白质印迹结果显示LUAD细胞中坏死性凋亡标志物表达较低。构建了基于6个NRGs的预后基因特征并计算了风险评分。多因素Cox回归分析表明,风险评分是一个独立的危险因素[风险比(HR)= 1.220,95%置信区间(CI):1.154 - 1.290,P < 0.001]。在TCGA队列中,高风险评分与预后不良、免疫浸润较弱以及免疫检查点低表达相关,这在GEO和临床队列中得到了验证。我们的研究结果表明,低风险组患者的无进展生存期(PFS)[未达到 vs. 8.5个月,HR = 0.18,95% CI:0.04 - 0.72,P < 0.001]优于高风险评分组。发现免疫治疗耐受性与高风险评分相关,风险评分与PD-L1联合使用(AUC = 0.808,95% CI:0.613 - 1.000)可以更好地预测LUAD的免疫治疗反应。在TCGA和GSE68465队列中,列线图显示出强大的预测LUAD患者个体生存率的能力。我们构建并验证了一个由6个NRGs组成的潜在预后特征,以预测LUAD的预后和肿瘤免疫,这可能有助于指导LUAD的个体化免疫治疗。