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  • Title: Aberrant promoter methylation profile and association with survival in patients with non-small cell lung cancer.
    Author: Gu J, Berman D, Lu C, Wistuba II, Roth JA, Frazier M, Spitz MR, Wu X.
    Journal: Clin Cancer Res; 2006 Dec 15; 12(24):7329-38. PubMed ID: 17189404.
    Abstract:
    PURPOSE: The aim of this study was to investigate the prognostic value of hypermethylation of tumor suppressor genes in patients with non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: We examined the methylation status of nine genes in 155 tumors from patients with NSCLC using quantitative methylation-specific PCR. We analyzed the associations between gene methylation status and overall patient survival. RESULTS: The methylation index, defined as the ratio between the number of methylated genes and the number of genes tested, was significantly higher in adenocarcinomas (0.38 +/- 0.20) than in squamous cell carcinomas (0.30 +/- 0.22; P = 0.027), in tumors from older patients (0.37 +/- 0.20) than younger patients (0.30 +/- 0.22; P = 0.040), and in tumors from heavier smokers (0.39 +/- 0.21) than lighter smokers (0.29 +/- 0.20; P = 0.042). In the Cox proportional hazards model, p16 methylation was associated with significantly poorer survival [hazard ratio, 1.95; 95% confidence interval (95% CI), 1.21-3.39]. Kaplan-Meier survival curves showed that patients with hypermethylated p16 had significantly shorter survival (median = 21.7 months) than patients without p16 hypermethylation (median = 62.5 months; P = 0.0001, log-rank test). Hypermethylation of CDH1 or TIMP3 gene was associated with significantly better survival with hazard ratios of 0.51 (95% CI, 0.29-0.90) and 0.59 (95% CI, 0.36-0.97), respectively. Joint analysis of these three genes showed a significant trend for poorer survival as the number of unfavorable events increased (P = 0.0007). CONCLUSION: Hypermethylation of multiple genes exhibited significant differential effect on NSCLC patient survival. Assessment of the effect of each methylated gene on survival is needed to provide optimal prognostic value.
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