Table8_An Immune-Gene-Based Classifier Predicts Prognosis in Patients With Cervical Squamous Cell Carcinoma.XLS

Objective: Immunity plays a vital role in the human papilloma virus (HPV) persistent infection, and closely associates with occurrence and development of cervical squamous cell carcinoma (CSCC). Herein, we performed an integrated bioinformatics analysis to establish an immune-gene signature and immune-associated nomogram for predicting prognosis of CSCC patients.Methods: The list of immunity-associated genes was retrieved from ImmPort database. The gene and clinical information of CSCC patients were obtained from The Cancer Genome Atlas (TCGA) website. The immune gene signature for predicting overall survival (OS) of CSCC patients was constructed using the univariate Cox-regression analysis, random survival forests, and multivariate Cox-regression analysis. This signature was externally validated in GSE44001 cohort from Gene Expression Omnibus (GEO). Then, based on the established signature and the TCGA cohort with the corresponding clinical information, a nomogram was constructed and evaluated via Cox regression analysis, concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots and decision curve analyses (DCAs).Results: A 5-immune-gene prognostic signature for CSCC was established. Low expression of ICOS, ISG20 and high expression of ANGPTL4, SBDS, LTBR were risk factors for CSCC prognosis indicating poor OS. Based on this signature, the OS was significantly worse in high-risk group than in low-risk group (p-value < 0.001), the area under curves (AUCs) for 1-, 3-, 5-years OS were, respectively, 0.784, 0.727, and 0.715. A nomogram incorporating the risk score of signature and the clinical stage was constructed. The C-index of this nomogram was 0.76. AUC values were 0.811, 0.717, and 0.712 for 1-, 3-, 5-years OS. The nomogram showed good calibration and gained more net benefits than the 5-immune-gene signature and the clinical stage.Conclusion: The 5-immune-gene signature may serve as a novel, independent predictor for prognosis in patients with CSCC. The nomogram incorporating the signature risk score and clinical stage improved the predictive performance than the signature and clinical stage alone for predicting 1-year OS.

本研究旨在揭示免疫机制在人类乳头瘤病毒（HPV）持续性感染中的关键作用，以及其与宫颈鳞状细胞癌（CSCC）的发生和发展之间的紧密联系。为此，本研究通过整合生物信息学分析方法，构建了免疫基因特征谱及免疫关联的预后 nomogram，以预测 CSCC 患者的预后。方法上，我们从 ImmPort 数据库中检索了免疫相关基因列表，并通过 The Cancer Genome Atlas（TCGA）网站获取了 CSCC 患者的基因和临床信息。利用单因素 Cox 回归分析、随机生存森林和多元 Cox 回归分析构建了预测 CSCC 患者总生存期（OS）的免疫基因特征谱。该特征谱在外部验证的 GSE44001 群体中得到了验证。随后，基于该特征谱和相应的 TCGA 群体临床信息，构建并评估了 nomogram，通过 Cox 回归分析、一致性指数（C-index）、受试者工作特征（ROC）曲线、校准图和决策曲线分析（DCAs）进行评估。结果：建立了一个包含 5 个免疫基因的 CSCC 预后特征谱。ICOS、ISG20 的低表达以及 ANGPTL4、SBDS、LTBR 的高表达是 CSCC 预后的风险因素，表明总生存期（OS）较差。基于此特征谱，高风险组的 OS 明显低于低风险组（p 值 < 0.001），1、3、5 年 OS 的曲线下面积（AUCs）分别为 0.784、0.727 和 0.715。构建了一个整合特征谱风险评分和临床阶段的 nomogram。该 nomogram 的 C-index 为 0.76。1、3、5 年 OS 的 AUC 值分别为 0.811、0.717 和 0.712。该 nomogram 显示出良好的校准效果，比单独使用特征谱和临床阶段获得了更高的净效益。结论：该 5 个免疫基因特征谱可能作为 CSCC 患者预后预测的一个新颖且独立的指标。将特征谱风险评分和临床阶段纳入的 nomogram，在预测 1 年 OS 方面比单独使用特征谱和临床阶段具有更高的预测性能。