研究表明亚洲非吸烟女性肺癌可能具有独特的遗传特性。目前尚需对这一人群进行综合组学研究以确定关键基因突变和差异表达基因，并评价这些变异与已确认的风险因素的相关性。我们的前期研究发现肺癌患者具有特异的唾液转录组图谱并验证了七个表达上调的肿瘤相关基因。进一步研究显示，非吸烟女性肺癌患者具有特异的唾液基因突变图谱和基因表达图谱。为综合评价遗传和环境因素与非吸烟女性肺癌患者唾液标志物图谱变化的相关性，本课题拟采用前瞻性样本采集和回顾性盲法评价的研究方案，通过表达数量性状座位（eQTL）和权重基因共表达网络分析（WGCNA）方法研究非吸烟肺癌女性的唾液外显子组和转录组，依据在独立样本中可获得验证的基因标志物与风险因素的相关性，确定针对这一人群特异的标志物模型；并进一步评价这些模型是否有助于提高CT有效性及区分良性和恶性肿瘤的准确率。本研究的开展将为大样本临床验证和人群筛查提供理论依据和候选标志物模型。

GWAS studies have shown that the etiology of lung cancer in female never-smokers in Asia may have unique genetic characteristics. Comprehensive functional study is required to identify the key gene variants that directly account for the underlying association, as well as to study how these variants interact with established environmental risk factors, including environmental tobacco smoke, cooking fumes and fuel use, in never-smoking females in Asia. In our previous study, salivary transcriptome of lung cancer patients were profiled and led to the discovery and validation of seven up-regulated gene markers. These salivary mRNA biomarkers possess the discriminatory power for the early detection of lung cancer, providing the proof of concept of salivary biomarkers for the non-invasive detection of systematic diseases. Further studies also found that never-smoking female lung cancer patients exhibited distinct salivary gene mutation patterns and gene expression patterns. In order to evaluate the correlation between genetic and environmental factors and variations of salivary gene biomarkers in never-smoking female lung cancer patients, we designed this study based on the PRoBE principle (prospective specimen collection and retrospective blinded evaluation) that was suggested by NCI. We will analyze the salivary exome and transcriptome in never-smoking female lung cancer patients; identify and validate distinct gene mutations and differentially expressed genes using expression quantitative trait loci (eQTL) and weighted gene co-expression network analysis (WGCNA); evaluate their correlations with established risk factors and build distinct biomarker models for this high-risk group. Furthermore, we will evaluate the potential of these biomarker models for increasing the efficacy of CT screening and determining which of the frequently detected lung nodules on CT scan are malignant. The results of this study will poise the theoretical basis and biomarker model candidates for the initiation of a multi-center validation and non-invasive population screening in a definitive clinical context.