Lung adenocarcinoma and mesothelioma DNA methylation

Pathologic differentiation of tissue of origin in tumors found in the lung can be challenging, with differentiation of mesothelioma and lung adenocarcinoma emblematic of this problem. Indeed, proper classification is essential for determination of treatment regimen for these diseases, making accurate and early diagnosis critical. Here we investigate the potential of epigenetic profiles of lung adenocarcinoma, mesothelioma, and non-malignant pulmonary tissues (n=285) as differentiation markers in an analysis of DNA methylation at 1413 autosomal CpG loci associated with 773 cancer-related genes. Using an unsupervised recursively-partitioned mixture modeling technique for all samples, the derived methylation profile classes were significantly associated with sample type (P < 0.0001). In a similar analysis restricted to tumors, methylation profile classes significantly predicted tumor type (P < 0.0001). Random forests classification of CpG methylation of tumors - which splits the data into training and test sets - accurately differentiated MPM from lung adenocarcinoma over 99% of the time (P < 0.0001). In a locus-by-locus comparison of CpG methylation between tumor types, 1266 CpG loci had significantly different methylation between tumors following correction for multiple comparisons (Q < 0.05); 61% had higher methylation in adenocarcinoma. Using the CpG loci with significant differential methylation in a pathways analysis revealed significant enrichment of methylated gene-loci in Cell Cycle Regulation, DNA Damage Response, PTEN Signaling, and Apoptosis Signaling pathways in lung adenocarcinoma when compared to mesothelioma. Methylation-profile-based differentiation of lung adenocarcinoma and mesothelioma is highly accurate, informs on the distinct etiologies of these diseases, and holds promise for clinical application. Mesotheliomas (n=158) and grossly non-tumorigenic parietal pleura (n=18) were obtained following surgical resection at Brigham and Women’s Hospital through the International Mesothelioma Program from a pilot study conducted in 2002 (n=70) and an incident case series beginning in 2005 (n=88) with a participation rate of 85%. We used biopsy specimens from patients treated for NSCLC at the Massachusetts General Hospital from 1992 – 1996 (18) including lung adenocarcinomas (n=57) and non-malignant pulmonary tissues (n=48) (of which 22 (39%) were taken from the adenocarcinoma patients) (18). Additional normal lung tissues were obtained from the National Disease Research Interchange from donors free of lung malignancy (n=4).

肺部肿瘤组织起源的病理分型极具挑战性，其中间皮瘤与肺腺癌的鉴别堪称该类难题的典型代表。事实上，正确的分类对于确定此类疾病的治疗方案至关重要，因此准确且早期的诊断尤为关键。
本研究探讨肺腺癌、间皮瘤及非恶性肺组织（n=285）的表观遗传谱作为分化标志物的潜力，分析了与773个癌症相关基因相关的1413个常染色体CpG位点（CpG locus）的DNA甲基化水平。研究采用无监督递归分区混合建模技术对所有样本进行分析，所得甲基化谱分型与样本类型显著相关（P < 0.0001）。
在仅针对肿瘤样本的类似分析中，甲基化谱分型可显著预测肿瘤类型（P < 0.0001）。对肿瘤样本的CpG甲基化进行随机森林分类——该方法将数据划分为训练集与测试集——可在超过99%的情况下准确区分恶性胸膜间皮瘤（Malignant Pleural Mesothelioma，MPM）与肺腺癌（P < 0.0001）。
在逐位点比较肿瘤间的CpG甲基化水平后，经多重比较校正，共有1266个CpG位点的甲基化水平在两类肿瘤间存在显著差异（Q < 0.05）；其中61%的位点在腺癌中甲基化水平更高。对存在显著差异甲基化的CpG位点进行通路分析显示，与间皮瘤相比，肺腺癌中甲基化基因位点显著富集于细胞周期调控、DNA损伤应答、PTEN信号通路及凋亡信号通路。
基于甲基化谱的肺腺癌与间皮瘤分型准确率极高，可为揭示这两类疾病的不同病因提供参考，并有望应用于临床实践。
本研究中的间皮瘤样本（n=158）及大体非肿瘤性壁层胸膜组织（n=18）均取自布莱根妇女医院（Brigham and Women’s Hospital）国际间皮瘤项目，来自2002年开展的一项预试验（n=70）及2005年启动的新发病例队列（n=88），受试者参与率为85%。
我们使用了1992年至1996年在麻省总医院（Massachusetts General Hospital）接受非小细胞肺癌（Non-Small Cell Lung Cancer，NSCLC）治疗患者的活检样本，其中包括肺腺癌样本（n=57）及非恶性肺组织样本（n=48，其中22份（39%）取自肺腺癌患者）。
额外的正常肺组织取自美国国家疾病研究交换库（National Disease Research Interchange）的无肺部恶性肿瘤供体（n=4）。