Safar A Mazin, Spencer Horace, Su Xiaobo, Coffey Maureen, Cooney Craig A, Ratnasinghe Luke D, Hutchins Laura F, Fan Chun-Yang
Central Arkansas Veterans Healthcare System, Little Rock, Arkansas.
Clin Cancer Res. 2005 Jun 15;11(12):4400-5. doi: 10.1158/1078-0432.CCR-04-2378.
Enhanced prognostication power is becoming more desirable in clinical oncology. In this study, we explored the prognostic potential of multigene hypermethylation profiling in non-small-cell lung cancer.
We evaluated a panel of eight genes (p16, APC, ATM, hMLH1, MGMT, DAPK, ECAD, and RASSF1A) using methylation-specific PCR in 105 archived specimens of non-small-cell lung cancer representing all stages of the illness. We analyzed the effect of gene methylation status on outcome individually in a cumulative manner and in a combinatorial approach using recursive partitioning to identify methylation profiles, which affect overall survival.
In this data set, tumors harboring promoter hypermethylation at two or more genes exhibit similar survival trends to others in the cohort. Using recursive partitioning, three genes (APC, ATM, and RASSF1A) emerged as determinants of prognostic groups. This designation retained its statistical significance even when disease stage and age were entered into a multivariate analysis. Using this approach, patients whose tumors were hypermethylated at APC and those hypermethylated at only ATM (not also at APC or RASSF1A) enjoyed substantially longer 1- and 2-year survival than patients in the remaining groups. In 32 adjacent histologically normal lung tissue specimens, we detected similar methylation abnormalities.
Assessment of promoter hypermethylation aberrations may facilitate prognostic profiling of lung tumors, but validation in independent data sets is needed to verify these profiles. This system uses material that is abundantly available with linked outcome data and can be used to generate reliable epigenetic determinants.
在临床肿瘤学中,增强预后预测能力变得越来越重要。在本研究中,我们探讨了多基因高甲基化谱在非小细胞肺癌中的预后潜力。
我们使用甲基化特异性PCR评估了一组八个基因(p16、APC、ATM、hMLH1、MGMT、DAPK、E-cad和RASSF1A),该评估在105份代表疾病各阶段的非小细胞肺癌存档标本中进行。我们以累积方式和组合方法单独分析基因甲基化状态对结果的影响,使用递归划分来识别影响总生存期的甲基化谱。
在该数据集中,两个或更多基因启动子高甲基化的肿瘤与队列中的其他肿瘤表现出相似的生存趋势。使用递归划分,三个基因(APC、ATM和RASSF1A)成为预后分组的决定因素。即使将疾病分期和年龄纳入多变量分析,这一分类仍保持其统计学意义。使用这种方法,肿瘤在APC处高甲基化的患者以及仅在ATM处高甲基化(不在APC或RASSF1A处高甲基化)的患者,其1年和2年生存率明显长于其余组的患者。在32份相邻的组织学正常肺组织标本中,我们检测到了类似的甲基化异常。
评估启动子高甲基化畸变可能有助于肺肿瘤的预后分析,但需要在独立数据集中进行验证以证实这些分析结果。该系统使用的材料丰富且有相关的结果数据,可用于生成可靠的表观遗传决定因素。