The aim of this study was to clarify the significance of DNA methylation alterations during lung carcinogenesis. Infinium assay was performed using 139 paired samples of non-cancerous lung tissue (N) and tumorous tissue (T) from a learning cohort of patients with lung adenocarcinomas (LADCs). Fifty paired N and T samples from a validation cohort were also analyzed. DNA methylation alterations on 1,928 probes occurred in N samples relative to normal lung tissue from patients without primary lung tumors, and were inherited by, or strengthened in, T samples. Unsupervised hierarchical clustering using DNA methylation levels in N samples on all 26,447 probes subclustered patients into Cluster I (n = 32), Cluster II (n = 35) and Cluster III (n = 72). LADCs in Cluster I developed from the inflammatory background in chronic obstructive pulmonary disease (COPD) in heavy smokers and were locally invasive. Most patients in Cluster II were non-smokers and had a favorable outcome. LADCs in Cluster III developed in light smokers were most aggressive (frequently showing lymphatic and blood vessel invasion, lymph node metastasis and an advanced pathological stage), and had a poor outcome. DNA methylation levels of hallmark genes for each cluster, such as IRX2, HOXD8, SPARCL1, RGS5 and EI24, were again correlated with clinicopathological characteristics in the validation cohort. DNA methylation profiles reflecting carcinogenetic factors such as smoking and COPD appear to be established in non-cancerous lung tissue from patients with LADCs and may determine the aggressiveness of tumors developing in individual patients, and thus patient outcome. What's new? While genetic abnormalities are well studied in human cancers, epigenetic changes, especially in the early stages of carcinogenesis, remain largely unknown. Here, the authors perform a genome-wide analysis focusing on DNA methylation profiles in "normal" lung tissue adjacent to lung adenocarcinomas. Using single-CpG-resolution Infinium assays, they identify distinct DNA methylation profiles clustering with specific risk factors such as cigarette smoking, inflammation and chronic obstructive pulmonary disease. The authors speculate that these epigenetic profiles detected in the neighboring cells may influence the aggressiveness of tumors developing in individual patients and may thus help predict disease outcome.
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