Yates David R, Rehman Ishtiaq, Abbod Maysam F, Meuth Mark, Cross Simon S, Linkens Derek A, Hamdy Freddie C, Catto James W F
Institute of Cancer Studies, Academic Urology Unit, Academic Pathology Unit, and Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, United Kingdom.
Clin Cancer Res. 2007 Apr 1;13(7):2046-53. doi: 10.1158/1078-0432.CCR-06-2476.
New methods to accurately predict an individual tumor behavior are urgently required to improve the treatment of cancer. We previously found that promoter hypermethylation can be an accurate predictor of bladder cancer progression, but it is not cancer specific. Here, we investigate a panel of methylated loci in a prospectively collected cohort of bladder tumors to determine whether hypermethylation has a useful role in the management of patients with bladder cancer.
Quantitative methylation-specific PCR was done at 17 gene promoters, suspected to be associated with tumor progression, in 96 malignant and 30 normal urothelial samples. Statistical analysis and artificial intelligence techniques were used to interrogate the results.
Using log-rank analysis, five loci were associated with progression to more advanced disease (RASSF1a, E-cadherin, TNFSR25, EDNRB, and APC; P < 0.05). Multivariate analysis revealed that the overall degree of methylation was more significantly associated with subsequent progression and death (Cox, P = 0.002) than tumor stage (Cox, P = 0.008). Neuro-fuzzy modeling confirmed that these five loci were those most associated with tumor progression. Epigenetic predictive models developed using artificial intelligence techniques identified the presence and timing of tumor progression with 97% specificity and 75% sensitivity.
Promoter hypermethylation seems a reliable predictor of tumor progression in bladder cancer. It is associated with aggressive tumors and could be used to identify patients with either superficial disease requiring radical treatment or a low progression risk suitable for less intensive surveillance. Multicenter studies are warranted to validate this marker.
迫切需要新的方法来准确预测个体肿瘤行为,以改善癌症治疗。我们之前发现启动子高甲基化可以准确预测膀胱癌进展,但它并非癌症特异性的。在此,我们在一个前瞻性收集的膀胱肿瘤队列中研究一组甲基化位点,以确定高甲基化在膀胱癌患者管理中是否具有有用作用。
在96份恶性尿路上皮样本和30份正常尿路上皮样本中,对17个怀疑与肿瘤进展相关的基因启动子进行定量甲基化特异性PCR。使用统计分析和人工智能技术分析结果。
采用对数秩分析,五个位点与进展为更晚期疾病相关(RASSF1a、E-钙黏蛋白、TNFSR25、EDNRB和APC;P<0.05)。多变量分析显示,甲基化的总体程度比肿瘤分期更显著地与后续进展和死亡相关(Cox,P = 0.002)(肿瘤分期Cox,P = 0.008)。神经模糊建模证实这五个位点与肿瘤进展最相关。使用人工智能技术开发的表观遗传预测模型以97%的特异性和75%的敏感性识别肿瘤进展的存在和时间。
启动子高甲基化似乎是膀胱癌肿瘤进展的可靠预测指标。它与侵袭性肿瘤相关,可用于识别需要根治性治疗的浅表性疾病患者或进展风险低、适合进行强度较低监测的患者。需要多中心研究来验证这一标志物。