The current staging system for non-small cell lung cancer (NSCLC) is inadequate for predicting outcome. Risk score, a linear combination of the values for the expression of each gene multiplied by a weighting value which was estimated from univariate Cox proportional hazard regression, can be useful. The aim of this study is to analyze survival-related genes with TaqMan Low-Density Array (TLDA) and risk score to explore gene-signature in lung cancer. A total of 96 NSCLC specimens were collected and randomly assigned to a training (n = 48) or a testing cohort (n = 48). A panel of 219 survival-associated genes from published studies were used to develop a 6-gene risk score. The risk score was used to classify patients into high or low-risk signature and survival analysis was performed. Cox models were used to evaluate independent prognostic factors. A 6-gene signature including ABCC4, ADRBK2, KLHL23, PDS5A, UHRF1 and ZNF551 was identified. The risk score in both training (HR = 3.14, 95% CI: 1.14-8.67, p = 0.03) and testing cohorts (HR = 5.42, 95% CI: 1.56-18.84, p = 0.01) was the independent prognostic factor. In merged public datasets including GSE50081, GSE30219, GSE31210, GSE19188, GSE37745, GSE3141 and GSE31908, the risk score (HR = 1.50, 95% CI: 1.25-1.80, p < 0.0001) was also the independent prognostic factor. The risk score generated from expression of a small number of genes did perform well in predicting overall survival and may be useful in routine clinical practice.

中文翻译：

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非小细胞肺癌的分子基因特征和预后。

当前的非小细胞肺癌（NSCLC）分期系统不足以预测结果。风险评分（每个基因的表达值乘以根据单变量Cox比例风险回归估算的权重值的线性组合）可能会有用。这项研究的目的是使用TaqMan低密度阵列（TLDA）和风险评分来分析与生存相关的基因，以探索肺癌的基因特征。总共收集了96个NSCLC标本，并随机分配给训练（n = 48）或测试队列（n = 48）。一组来自已发表研究的219个与生存相关的基因被用来制定6个基因的风险评分。使用风险评分将患者分类为高风险或低风险签名，并进行生存分析。使用Cox模型评估独立的预后因素。鉴定出包括ABCC4，ADRBK2，KLHL23，PDS5A，UHRF1和ZNF551的6基因签名。独立的预后因素是培训（HR = 3.14，95％CI：1.14-8.67，p = 0.03）和测试队列（HR = 5.42，95％CI：1.56-18.84，p = 0.01）中的风险评分。在包括GSE50081，GSE30219，GSE31210，GSE19188，GSE37745，GSE3141和GSE31908的合并公共数据集中，风险评分（HR = 1.50，95％CI：1.25-1.80，p <0.0001）也是独立的预后因素。由少量基因表达产生的风险评分在预测总体存活率方面确实表现良好，并且可能在常规临床实践中很有用。p = 0.01）是独立的预后因素。在合并的公共数据集中，包括GSE50081，GSE30219，GSE31210，GSE19188，GSE37745，GSE3141和GSE31908，风险评分（HR = 1.50，95％CI：1.25-1.80，p <0.0001）也是独立的预后因素。由少量基因表达产生的风险评分在预测总体存活率方面确实表现良好，并且可能在常规临床实践中很有用。p = 0.01）是独立的预后因素。在包括GSE50081，GSE30219，GSE31210，GSE19188，GSE37745，GSE3141和GSE31908的合并公共数据集中，风险评分（HR = 1.50，95％CI：1.25-1.80，p <0.0001）也是独立的预后因素。由少量基因表达产生的风险评分在预测总体存活率方面确实表现良好，并且可能在常规临床实践中很有用。