Tang H, Wang S, Xiao G, Schiller J, Papadimitrakopoulou V, Minna J, Wistuba I I, Xie Y
Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, People's Republic of China.
Department of Medical Oncology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong, P.R. China.
Ann Oncol. 2017 Apr 1;28(4):733-740. doi: 10.1093/annonc/mdw683.
A more accurate prognosis for non-small-cell lung cancer (NSCLC) patients could aid in the identification of patients at high risk for recurrence. Many NSCLC mRNA expression signatures claiming to be prognostic have been reported in the literature. The goal of this study was to identify the most promising mRNA prognostic signatures in NSCLC for further prospective clinical validation.
We carried out a systematic review and meta-analysis of published mRNA prognostic signatures for resected NSCLC. The prognostic performance of each signature was evaluated via a meta-analysis of 1927 early stage NSCLC patients collected from 15 studies using three evaluation metrics (hazard ratios, concordance scores, and time-dependent receiver-operating characteristic curves). The performance of each signature was then evaluated against 100 random signatures. The prognostic power independent of clinical risk factors was assessed by multivariate Cox models.
Through a literature search, we identified 42 lung cancer prognostic signatures derived from genome-wide expression profiling analysis. Based on meta-analysis, 25 signatures were prognostic for survival after adjusting for clinical risk factors and 18 signatures carried out significantly better than random signatures. When analyzing histology types separately, 17 signatures and 8 signatures are prognostic for adenocarcinoma and squamous cell lung cancer, respectively. Despite little overlap among published gene signatures, the top-performing signatures are highly concordant in predicted patient outcomes.
Based on this large-scale meta-analysis, we identified a set of mRNA expression prognostic signatures appropriate for further validation in prospective clinical studies.
对非小细胞肺癌(NSCLC)患者进行更准确的预后评估有助于识别复发高危患者。文献中已报道了许多声称具有预后价值的NSCLC mRNA表达特征。本研究的目的是在NSCLC中识别最有前景的mRNA预后特征,以便进一步进行前瞻性临床验证。
我们对已发表的关于切除的NSCLC的mRNA预后特征进行了系统评价和荟萃分析。通过对从15项研究中收集的1927例早期NSCLC患者进行荟萃分析,使用三个评估指标(风险比、一致性评分和时间依赖性受试者工作特征曲线)来评估每个特征的预后性能。然后将每个特征的性能与100个随机特征进行比较。通过多变量Cox模型评估独立于临床风险因素的预后能力。
通过文献检索,我们确定了42个源自全基因组表达谱分析的肺癌预后特征。基于荟萃分析,在调整临床风险因素后,25个特征对生存具有预后价值,18个特征的表现明显优于随机特征。分别分析组织学类型时,17个特征和8个特征分别对腺癌和肺鳞状细胞癌具有预后价值。尽管已发表的基因特征之间几乎没有重叠,但表现最佳的特征在预测患者预后方面高度一致。
基于这项大规模荟萃分析,我们确定了一组mRNA表达预后特征,适合在前瞻性临床研究中进一步验证。