Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands.
Department of Pulmonology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.
Lung Cancer. 2014 May;84(2):127-33. doi: 10.1016/j.lungcan.2014.01.019. Epub 2014 Jan 31.
Lung cancer is the most fatal cancer in the developed world due to presence of metastases at time of diagnosis. The aim of this study is to examine DNA hypermethylation in sputum compared to sputum cytology for the diagnosis of lung cancer. A novel risk analysis is introduced, using the distinction between diagnostic and risk markers.
Two independent sets were randomly composed from a prospectively collected sputum bank (Set 1: n = 98 lung cancer patients, n = 90 controls; Set 2: n = 60 lung cancer patients, n = 445 controls). Sputum cytology was performed for all samples. The following DNA hypermethylation markers were tested in both sets: RASSF1A, APC and cytoglobin (CYGB). Two statistical analyses were conducted: multivariate logistic regression and a risk classification model based on post-test probabilities.
In multivariate analysis, RASSF1A was the best of the three markers in discriminating lung cancer cases from controls in both sets (sensitivity 41-52%, specificity 94-96%). The risk model showed that 36% of lung cancer patients were defined as "high risk" (≥ 60% chance on lung cancer) based on RASSF1A hypermethylation in Set 1. The model was reproducible in Set 2. Risk markers (APC, CYGB) have less diagnostic value. Sensitivity of cytology for lung cancer diagnosis was 22%. RASSF1A hypermethylation yielded a sensitivity of 45%. The combined sensitivity for RASSF1A with cytological diagnosis increased to 52% with similar specificity (94%).
In a diagnostic setting, hypermethylation analysis in sputum is possible when a diagnostic marker is used. However, risk markers are insufficient for this purpose.
由于肺癌在诊断时已经发生转移，因此在发达国家，肺癌是最致命的癌症。本研究旨在比较痰液中的 DNA 超甲基化与痰液细胞学检查在肺癌诊断中的应用。本文采用了一种新的风险分析方法，使用诊断标志物和风险标志物之间的差异。
从一个前瞻性收集的痰液库中随机抽取两组独立样本（第 1 组：n = 98 例肺癌患者，n = 90 例对照；第 2 组：n = 60 例肺癌患者，n = 445 例对照）。对所有样本均进行痰液细胞学检查。在两组中均检测了以下 DNA 超甲基化标志物：RASSF1A、APC 和细胞球蛋白（CYGB）。进行了两种统计分析：多变量逻辑回归和基于后测概率的风险分类模型。
多变量分析显示，在两组中，RASSF1A 是区分肺癌病例与对照组的三种标志物中最好的（敏感性 41%-52%，特异性 94%-96%）。风险模型显示，基于第 1 组 RASSF1A 超甲基化，36%的肺癌患者被定义为“高风险”（≥60%患肺癌的机会）。该模型在第 2 组中具有可重复性。风险标志物（APC、CYGB）的诊断价值较低。细胞学诊断肺癌的敏感性为 22%。RASSF1A 甲基化的敏感性为 45%。当与细胞学诊断相结合时，RASSF1A 的联合敏感性提高到 52%，特异性相似（94%）。
在诊断环境中，当使用诊断标志物时，痰液中的超甲基化分析是可行的。然而，风险标志物在这方面是不够的。
