Combination of protein coding and noncoding gene expression as a robust prognostic classifier in stage I lung adenocarcinoma.
Combination of protein coding and noncoding gene expression as a robust prognostic classifier in stage I lung adenocarcinoma.
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蛋白质编码和非编码基因表达作为I期肺腺癌中强大的预后分类器的组合。
DOI：
10.1158/0008-5472.can-13-0031
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发表时间：
2013-07-01
期刊：
影响因子：
11.2
通讯作者：
Harris CC
中科院分区：
文献类型：
--
作者：
Akagi I;Okayama H;Schetter AJ;Robles AI;Kohno T;Bowman ED;Kazandjian D;Welsh JA;Oue N;Saito M;Miyashita M;Uchida E;Takizawa T;Takenoshita S;Skaug V;Mollerup S;Haugen A;Yokota J;Harris CC
早期肺癌患者的预后检测可为术后监测和治疗决策提供必要的指导。我们使用了一种新的策略来开发和验证早期肺癌的预后分类器。具体来说，我们关注了42个在肺癌或癌症预后中起作用的基因。这些生物学相关基因的表达及其与无复发生存期（RFS）的相关性使用来自148例I期肺腺癌患者的微阵列数据进行了评估。采用定量逆转录PCR方法对日本、美国和挪威的291例肺腺癌组织中与RFS相关的7个基因进行了进一步检测。在日本和美国/挪威队列中，只有BRCA 1、HIF 1A、DLC 1和XPO 1与预后显著相关。在日本组群中使用这四种基因开发了基于考克斯回归的分类器，并在来自美国/挪威组群的I期肺腺癌和三个公开可用的肺腺癌表达谱数据集中进行了验证。结果表明，无论用于测量基因表达的技术如何，该分类器在种族和地理上不同的人群中都是鲁棒的。我们评估了四基因分类器与miRNA miR-21（MIR 21）表达的组合，发现该组合改善了与预后的相关性，这在IA期和IB期患者的分层分析中显着。因此，四个编码基因分类器，单独或与miR-21表达，可以提供一个临床上有用的工具，以确定高风险的患者和指导建议，辅助治疗和术后监测的患者与I期肺腺癌。
Prognostic tests for patients with early-stage lung cancer may provide needed guidance on postoperative surveillance and therapeutic decisions. We used a novel strategy to develop and validate a prognostic classifier for early-stage lung cancer. Specifically, we focused on 42 genes with roles in lung cancer or cancer prognosis. Expression of these biologically relevant genes and their association with relapse-free survival (RFS) were evaluated using microarray data from 148 patients with stage I lung adenocarcinoma. Seven genes associated with RFS were further examined by quantitative reverse transcription PCR in 291 lung adenocarcinoma tissues from Japan, the United States, and Norway. Only BRCA1, HIF1A, DLC1, and XPO1 were each significantly associated with prognosis in the Japan and US/Norway cohorts. A Cox regression-based classifier was developed using these four genes on the Japan cohort and validated in stage I lung adenocarcinoma from the US/Norway cohort and three publicly available lung adenocarcinoma expression profiling datasets. The results suggest that the classifier is robust across ethnically and geographically diverse populations regardless of the technology used to measure gene expression. We evaluated the combination of the four-gene classifier with miRNA miR-21 (MIR21) expression and found that the combination improved associations with prognosis, which were significant in stratified analyses on stage IA and stage IB patients. Thus, the four coding gene classifier, alone or with miR-21 expression, may provide a clinically useful tool to identify high-risk patients and guide recommendations regarding adjuvant therapy and postoperative surveillance of patients with stage I lung adenocarcinoma.