Guo Nancy L, Wan Ying-Wooi, Tosun Kursad, Lin Hong, Msiska Zola, Flynn Daniel C, Remick Scot C, Vallyathan Val, Dowlati Afshin, Shi Xianglin, Castranova Vincent, Beer David G, Qian Yong
Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, West Virginia 26506-9300, USA.
Clin Cancer Res. 2008 Dec 15;14(24):8213-20. doi: 10.1158/1078-0432.CCR-08-0095.
It is a critical challenge to determine the risk of recurrence in early stage non-small cell lung cancer (NSCLC) patients. Accurate gene expression signatures are needed to classify patients into high- and low-risk groups to improve the selection of patients for adjuvant therapy.
Multiple published microarray data sets were used to evaluate our previously identified lung cancer prognostic gene signature. Expression of the signature genes was further validated with real-time reverse transcription-PCR and Western blot assays of snap-frozen lung cancer tumor tissues.
Our previously identified 35-gene signature stratified 264 patients with NSCLC into high- and low-risk groups with distinct overall survival rates (P < 0.05, Kaplan-Meier analysis, log-rank tests). The 35-gene signature further stratified patients with clinical stage 1A diseases into poor prognostic and good prognostic subgroups (P = 0.0007, Kaplan-Meier analysis, log-rank tests). This signature is independent of other prognostic factors for NSCLC, including age, sex, tumor differentiation, tumor grade, and tumor stage. The expression of the signature genes was validated with real-time reverse transcription-PCR analysis of lung cancer tumor specimens. Protein expression of two signature genes, TAL2 and ILF3, was confirmed in lung adenocarcinoma tumors by using Western blot analysis. These two biomarkers showed correlated mRNA and protein overexpression in lung cancer development and progression.
The results indicate that the identified 35-gene signature is an accurate predictor of survival in NSCLC. It provides independent prognostic information in addition to traditional clinicopathologic criteria.
确定早期非小细胞肺癌（NSCLC）患者的复发风险是一项严峻挑战。需要准确的基因表达特征来将患者分为高风险和低风险组，以改善辅助治疗患者的选择。
使用多个已发表的微阵列数据集来评估我们先前鉴定的肺癌预后基因特征。通过对冷冻肺癌肿瘤组织进行实时逆转录 - PCR和蛋白质印迹分析，进一步验证特征基因的表达。
我们先前鉴定的35个基因的特征将264例NSCLC患者分为高风险和低风险组，两组的总生存率明显不同（P < 0.05，Kaplan - Meier分析，对数秩检验）。该35个基因的特征进一步将临床1A期疾病患者分为预后不良和预后良好的亚组（P = 0.0007，Kaplan - Meier分析，对数秩检验）。该特征独立于NSCLC的其他预后因素，包括年龄、性别、肿瘤分化、肿瘤分级和肿瘤分期。通过对肺癌肿瘤标本进行实时逆转录 - PCR分析，验证了特征基因的表达。使用蛋白质印迹分析在肺腺癌肿瘤中证实了两个特征基因TAL2和ILF3的蛋白表达。这两种生物标志物在肺癌发生和发展过程中显示出相关的mRNA和蛋白过表达。
结果表明，鉴定出的35个基因的特征是NSCLC生存的准确预测指标。除了传统的临床病理标准外，它还提供独立的预后信息。
