Abstract:
Background:This study was aimed at understanding whether bronchial biopsy specimen can be used as a surrogate for DNA methylation analysis in surgically resected lung cancer. Methods:A genome-wide methylation was analyzed in 42 surgically resected tumor tissues, 136 bronchial washing, 12 sputum, and 8 bronchial biopsy specimens using the Infinium HumanMethylation450 BeadChip, and models for prediction of lung cancer were evaluated using TCGA lung cancer data. Results:Four thousand seven hundred and twenty-six CpGs (P < 1.0E-07) that were highly methylated in tumor tissues were identified from 42 lung cancer patients. Ten CpGs were selected for prediction of lung cancer. Genes including the 10 CpGs were classified into three categories: (i) transcription (HOXA9, SOX17, ZNF154, HOXD13); (ii) cell signaling (HBP1, SFRP1, VIPR2); and (iii) adhesion (PCDH17, ITGA5, CD34). Three logistic regression models based on the 10 CpGs classified 897 TCGA primary lung tissues with a sensitivity of 95.0~97.8% and a specificity of 97.4~98.7%. However, the classification performance of the models was very poor in bronchial washing samples: the area under the curve (AUC) was equal to 0.72~0.78. The methylation levels of the 10 CpGs in bronchial biopsy were not significantly different from those in surgically resected tumor tissues (P > 0.05, Wilcoxon rank-sum test). However, their methylation levels were significantly different between paired bronchial biopsy and washing (P < 0.05, Wilcoxon signed-rank test). Conclusions:The present study suggests that bronchial biopsy specimen may be used as a surrogate for DNA methylation analysis in patient with inoperable lung cancer.
journal_name
Clin Epigeneticsjournal_title
Clinical epigeneticsauthors
Um SW,Kim HK,Kim Y,Lee BB,Kim D,Han J,Kim H,Shim YM,Kim DHdoi
10.1186/s13148-017-0432-5subject
Has Abstractpub_date
2017-12-20 00:00:00pages
131eissn
1868-7075issn
1868-7083pii
432journal_volume
9pub_type
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journal_title:Clinical epigenetics
pub_type: 杂志文章
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pub_type: 临床试验,杂志文章
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更新日期:2021-01-30 00:00:00
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