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Cancer Res. 2009 Jan 1;69(1):227-34. doi: 10.1158/0008-5472.CAN-08-2586.

Epigenetic profiles distinguish pleural mesothelioma from normal pleura and predict lung asbestos burden and clinical outcome.

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  • 1Department of Community Health, Center for Environmental Health and Technology, Brown University, 70 Ship Street, Providence, RI 02903, USA.

Abstract

Mechanisms of action of nonmutagenic carcinogens such as asbestos remain poorly characterized. As pleural mesothelioma is known to have limited numbers of genetic mutations, we aimed to characterize the relationships among gene-locus-specific methylation alterations, disease status, asbestos burden, and survival in this rapidly fatal asbestos-associated tumor. Methylation of 1505 CpG loci associated with 803 cancer-related genes were studied in 158 pleural mesotheliomas and 18 normal pleura. After false-discovery rate correction, 969 CpG loci were independently associated with disease status (Q < 0.05). Classifying samples based on CpG methylation profile with a mixture model approach, methylation classes discriminated tumor from normal pleura (permutation P < 0.0001). In a random forests classification, the overall misclassification error rate was 3.4%, with <1% (n = 1) of tumors misclassified as normal (P < 0.0001). Among tumors, methylation class membership was significantly associated with lung tissue asbestos body burden (P < 0.03), and significantly predicted survival (likelihood ratio P < 0.01). Consistent with prior work, asbestos burden was associated with an increased risk of death (hazard ratio, 1.4; 95% confidence interval, 1.1-1.8). Our results have shown that methylation profiles powerfully differentiate diseased pleura from nontumor pleura and that asbestos burden and methylation profiles are independent predictors of mesothelioma patient survival. We have added to the growing body of evidence that cellular epigenetic dysregulation is a critical mode of action for asbestos in the induction of pleural mesothelioma. Importantly, these findings hold great promise for using epigenetic profiling in the diagnosis and prognosis of human cancers.

PMID:
19118007
PMCID:
PMC2744125
DOI:
10.1158/0008-5472.CAN-08-2586
[PubMed - indexed for MEDLINE]
Free PMC Article
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