Confirmation of gene expression-based prediction of survival in non-small cell lung cancer.
Confirmation of gene expression-based prediction of survival in non-small cell lung cancer.
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DOI：
10.1158/1078-0432.ccr-08-0095
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发表时间：
2008-12-15
影响因子：
11.5
通讯作者：
Qian, Yong
中科院分区：
文献类型：
--
作者：
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
可靠地识别肺癌复发和转移高危患者仍然是一个关键问题。到目前为止，还没有临床应用的基因测试来预测肺癌复发。这项研究验证了35个基因在非小细胞肺癌的各种细胞类型的预后标志。分析表明，35个基因标签可以进一步将1A期患者分为不同的预后亚组。这种肺癌预后标志与传统的临床病理因素无关，包括患者年龄、临床分期、肿瘤分化和肿瘤分级。该特征比其他肺癌特征具有更好的预后性能，包括研究队列中的5-基因特征和133-基因特征。在临床标本的实时RT-PCR和Western印迹分析中验证了所鉴定的生物标志物的基因表达和蛋白表达。这项研究表明，35基因签名可以应用于临床患者分层。确定早期非小细胞肺癌（NSCLC）患者的复发风险仍然是一个关键挑战。需要准确的基因表达特征来将患者分为高风险组和低风险组，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。用快速冷冻的肺癌肿瘤组织的实时RT-PCR和Western印迹分析进一步验证标签基因的表达。我们先前确定的35个基因标签将264名非小细胞肺癌患者分为高风险组和低风险组，具有不同的总生存率（P < 0.05，Kaplan-Meier分析，对数秩检验）。35个基因标签进一步将具有临床1A期疾病的患者分层为预后不良和预后良好亚组（P = 0.0007，Kaplan-Meier分析，对数秩检验）。该特征与非小细胞肺癌的其他预后因素无关，包括年龄、性别、肿瘤分化、肿瘤分级和肿瘤分期。用实时RT-PCR分析肺癌肿瘤标本来验证标签基因的表达。通过使用蛋白质印迹分析证实了两个标签基因TAL 2和ILF 3在肺腺癌肿瘤中的蛋白质表达。这两种生物标志物在肺癌的发生和发展中显示相关的mRNA和蛋白质过表达。结果表明，所识别的35个基因标签是非小细胞肺癌生存的准确预测因子。它提供了独立的预后信息，除了传统的临床病理学标准。
It remains a critical issue to reliably identify specific patients at high risk for recurrence and metastasis of lung cancer. To date, there has been no clinically applied gene test for predicting lung cancer recurrence. This study validated a 35-gene prognostic signature in various cell types of non-small cell lung cancer. The analysis showed that the 35-gene signature could further stratify patients at stage 1A into distinct prognostic subgroups. This lung cancer prognostic signature is independent of traditional clinicopathological factors, including patient age, clinical stage, tumor differentiation, and tumor grade. This signature had better prognostic performance than other lung cancer signatures, including the 5-gene signature and the 133-gene signature in the studied cohorts. The gene expression and protein expression of the identified biomarkers were validated in real-time RT-PCR and Western blots analysis of clinical specimens. This study indicates that the 35-gene signature could be applied in clinics for patient stratification. It remains a critical challenge to determine the risk for 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 datasets were used to evaluate our previously identified lung cancer prognostic gene signature. Expression of the signature genes was further validated with real-time RT-PCR and Western blot assays of snap frozen lung cancer tumor tissues. Our previously identified 35-gene signature stratified 264 patients with non-small cell lung cancer 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 non-small cell lung cancer, including age, sex, tumor differentiation, tumor grade, and tumor stage. The expression of the signature genes was validated with real-time RT-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 over-expression in lung cancer development and progression. The results indicate that the identified 35-gene signature is an accurate predictor of survival in non-small cell lung cancer. It provides independent prognostic information in addition to traditional clinicopathological criteria.