Yin Xiao-Hong, Yu Li-Ping, Zhao Xiao-Hong, Li Qin-Mei, Liu Xiao-Ping, He Li
Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei province, China.
Wuhan University School of Health Sciences, Wuhan, Hubei province, China.
J Cancer. 2020 Jan 29;11(7):1940-1948. doi: 10.7150/jca.37003. eCollection 2020.
To identify a multi-gene prognostic factor in patients with lung adenocarcinoma (LUAD). Prognosis-related genes were screened in the TCGA-LUAD cohort. Then, patients in this cohort were randomly separated into training set and test set. Least absolute shrinkage and selection operator (LASSO) regression was performed to the penalized the Cox proportional hazards regression (CPH) model on the training set, and a prognostication combination based on the result of LASSO analysis was developed. By performing Kaplan-Meier curve analysis, univariate and multivariable CPH model on the overall survival (OS) as well as recurrence free survival (RFS), the prognostication performance of the multigene combination were evaluated. Moreover, we constructed a nomogram and performed decision curve analysis to evaluate the clinical application of the multigene combination. We obtained 99 prognosis-related genes and screened out a 4-gene combination (including CIDEC, ZFP3, DKK1, and USP4) according to the LASSO analysis. The results of survival analyses suggested that patients in the 4-gene combination low-risk group had better OS and RFS than those in the 4-gene combination high-risk group. The 4-gene mentioned was demonstrated to be independent prognostic factor of patients with LUAD in the training set(OS, HR=11.962, P<0.001; RFS, HR=9.281, P<0.001) and test set (OS, HR=5.377, P=0.003; RFS, HR=2.949, P=0.104). More importantly, its prognosis performance was well in the validation set (OS, HR=0.955, P=0.002; RFS, HR=1.042, P<0.001). We introduced a 4-gene combination which could predict the survival of LUAD patients and might be an independent prognostic factor in LUAD.
识别肺腺癌（LUAD）患者的多基因预后因素。在TCGA-LUAD队列中筛选与预后相关的基因。然后，将该队列中的患者随机分为训练集和测试集。对训练集上的Cox比例风险回归（CPH）模型进行最小绝对收缩和选择算子（LASSO）回归惩罚，并基于LASSO分析结果开发一种预后组合。通过进行Kaplan-Meier曲线分析、对总生存期（OS）以及无复发生存期（RFS）进行单变量和多变量CPH模型分析，评估多基因组合的预后性能。此外，我们构建了列线图并进行决策曲线分析，以评估多基因组合的临床应用。我们获得了99个与预后相关的基因，并根据LASSO分析筛选出一个4基因组合（包括CIDEC、ZFP3、DKK1和USP4）。生存分析结果表明，4基因组合低风险组患者的OS和RFS优于4基因组合高风险组患者。在训练集（OS，HR=11.962，P<0.001；RFS，HR=9.281，P<0.001）和测试集（OS，HR=5.377，P=0.003；RFS，HR=2.949，P=0.104）中，上述4个基因被证明是LUAD患者的独立预后因素。更重要的是，其在验证集（OS，HR=0.955，P=0.002；RFS，HR=1.042，P<0.001）中的预后性能良好。我们引入了一个可预测LUAD患者生存情况的4基因组合，它可能是LUAD的一个独立预后因素。
