整合肿瘤和基质基因表达特征与临床指标用于早期非小细胞肺癌生存分层
Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer.
作者信息
Gentles Andrew J, Bratman Scott V, Lee Luke J, Harris Jeremy P, Feng Weiguo, Nair Ramesh V, Shultz David B, Nair Viswam S, Hoang Chuong D, West Robert B, Plevritis Sylvia K, Alizadeh Ash A, Diehn Maximilian
机构信息
Department of Radiology (AJG, JPH, RVN, SKP), Department of Radiation Oncology (SVB, DBS, MD), Cancer Institute and Institute for Stem Cell Biology and Regenerative Medicine (LJL, WF, MD), Department of Medicine Division of Pulmonary and Critical Care Medicine (VSN), Department of Cardiothoracic Surgery Division of Thoracic Surgery (CDH), Department of Pathology (RBW), and Department of Medicine Division of Oncology (AAA), Stanford University, Stanford, CA.
出版信息
J Natl Cancer Inst. 2015 Aug 18;107(10). doi: 10.1093/jnci/djv211. Print 2015 Oct.
BACKGROUND
Accurate survival stratification in early-stage non-small cell lung cancer (NSCLC) could inform the use of adjuvant therapy. We developed a clinically implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables.
METHODS
Gene expression profiles from 1106 nonsquamous NSCLCs were used for generation and internal validation of a nine-gene molecular prognostic index (MPI). A quantitative polymerase chain reaction (qPCR) assay was developed and validated on an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98). A prognostic score using clinical variables was generated using Surveillance, Epidemiology, and End Results data and combined with the MPI. All statistical tests for survival were two-sided.
RESULTS
The MPI stratified stage I patients into prognostic categories in three microarray and one FFPE qPCR validation cohorts (HR = 2.99, 95% CI = 1.55 to 5.76, P < .001 in stage IA patients of the largest microarray validation cohort; HR = 3.95, 95% CI = 1.24 to 12.64, P = .01 in stage IA of the qPCR cohort). Prognostic genes were expressed in distinct tumor cell subpopulations, and genes implicated in proliferation and stem cells portended poor outcomes, while genes involved in normal lung differentiation and immune infiltration were associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR = 3.43, 95% CI = 2.18 to 5.39, P < .001 in stage I patients of the largest microarray cohort; HR = 3.99, 95% CI = 1.67 to 9.56, P < .001 in stage I patients of the qPCR cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK.
CONCLUSION
The MPI incorporates genes expressed in the tumor and its microenvironment and can be implemented clinically using qPCR assays on FFPE tissues. A composite model integrating the MPI with clinical variables provides the most accurate risk stratification.
背景
早期非小细胞肺癌（NSCLC）的准确生存分层可为辅助治疗的应用提供依据。我们开发了一种临床可实施的死亡率风险评分，纳入了独特的肿瘤微环境基因表达特征和临床变量。
方法
利用1106例非鳞状NSCLC的基因表达谱生成并内部验证了一个九基因分子预后指数（MPI）。开发了一种定量聚合酶链反应（qPCR）检测方法，并在一个独立的福尔马林固定石蜡包埋（FFPE）组织队列（n = 98）上进行了验证。利用监测、流行病学和最终结果数据生成了一个使用临床变量的预后评分，并与MPI相结合。所有生存统计检验均为双侧检验。
结果
在三个微阵列和一个FFPE qPCR验证队列中，MPI将I期患者分为不同的预后类别（在最大微阵列验证队列的IA期患者中，HR = 2.99，95%CI = 1.55至5.76，P <.001；在qPCR队列的IA期，HR = 3.95，95%CI = 1.24至12.64，P =.01）。预后基因在不同的肿瘤细胞亚群中表达，与增殖和干细胞相关的基因预示着不良预后，而与正常肺分化和免疫浸润相关的基因与较好的生存相关。将MPI与临床变量相结合具有最大的预后能力（在最大微阵列队列的I期患者中，HR = 3.43，95%CI = 2.18至5.39，P <.001；在qPCR队列的I期患者中，HR = 3.99，95%CI = 1.67至9.56，P <.001）。最后，无论EGFR、KRAS、TP53和ALK的体细胞改变如何，MPI均具有预后价值。
结论
MPI纳入了在肿瘤及其微环境中表达的基因，可通过对FFPE组织进行qPCR检测在临床上实施。将MPI与临床变量相结合的复合模型提供了最准确的风险分层。
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