Quantitative Biomedical Research Center, Hamon Center for Therapeutic Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
Clin Cancer Res. 2013 Mar 15;19(6):1577-86. doi: 10.1158/1078-0432.CCR-12-2321. Epub 2013 Jan 28.
Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for non-small cell lung cancer (NSCLC) patients. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefits of ACT in NSCLC.
An 18-hub-gene prognosis signature was developed through a systems biology approach, and its prognostic value was evaluated in six independent cohorts. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefits in NSCLC.
Using a cohort of 442 stage I to III NSCLC patients who underwent surgical resection, we identified an 18-hub-gene set that robustly predicted the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The hub genes, identified through a purely data-driven approach, have significant biological implications in tumor pathogenesis, including NKX2-1, Aurora Kinase A, PRC1, CDKN3, MBIP, and RRM2. The 12-gene predictive signature was successfully validated in two independent datasets (n = 90 and 176). The predicted benefit group showed significant improvement in survival after ACT (UT Lung SPORE data: HR = 0.34, P = 0.017; JBR.10 clinical trial data: HR = 0.36, P = 0.038), whereas the predicted nonbenefit group showed no survival benefit for 2 datasets (HR = 0.80, P = 0.70; HR = 0.91, P = 0.82).
This is the first study to integrate genetic aberration, genome-wide RNAi data, and mRNA expression data to identify a functional gene set that predicts which resectable patients with non-small cell lung cancer will have a survival benefit with ACT.
前瞻性地识别哪些非小细胞肺癌（NSCLC）患者将从辅助化疗（ACT）中获益，将改善 NSCLC 患者的临床决策。本研究旨在开发和验证一种功能性基因集，以预测 NSCLC 中 ACT 的临床获益。
通过系统生物学方法开发了一个 18 个基因的预后标志物，并在六个独立队列中评估了其预后价值。然后，将 18 个基因集与全基因组功能（RNAi）数据和遗传异常数据整合，得出一个用于预测 NSCLC 中 ACT 获益的 12 个基因预测标志物。
使用 442 名接受手术切除的 I 至 III 期 NSCLC 患者队列，我们鉴定出了一个 18 个基因的基因集，该基因集在四个微阵列平台的所有验证数据集中均能稳健地预测腺癌患者的预后。通过纯数据驱动方法鉴定的枢纽基因在肿瘤发病机制中具有重要的生物学意义，包括 NKX2-1、Aurora 激酶 A、PRC1、CDKN3、MBIP 和 RRM2。12 个基因预测标志物在两个独立数据集（n=90 和 176）中得到了成功验证。预测获益组在接受 ACT 后生存显著改善（UT 肺癌 SPORE 数据：HR=0.34，P=0.017；JBR.10 临床试验数据：HR=0.36，P=0.038），而预测非获益组在两个数据集（HR=0.80，P=0.70；HR=0.91，P=0.82）中没有生存获益。
这是第一项整合遗传异常、全基因组 RNAi 数据和 mRNA 表达数据以鉴定预测 NSCLC 患者接受 ACT 后是否有生存获益的功能性基因集的研究。
