Abstract
BackgroundDNA methylation was suggested as the promising biomarker for lung cancer diagnosis. However, it is a great challenge to search for the optimal combination of methylation biomarkers to obtain maximum diagnostic performance.ResultsIn this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency for non-small cell lung cancer (NSCLC) in a large Chinese Han NSCLC retrospective cohort. Three high-throughput DNA methylation microarray datasets (458 samples) were collected in the discovery stage. After normalization, batch effect elimination and integration, significantly differentially methylated genes and the best combination of the biomarkers were determined by the leave-one-out SVM (support vector machine) feature selection procedure. Then, candidate promoters were examined by the methylation status determined single nucleotide primer extension technique (MSD-SNuPET) in an independent set of 150 pairwise NSCLC/normal tissues. Four statistical models with fivefold cross-validation were used to evaluate the performance of the discriminatory algorithms. The sensitivity, specificity and accuracy were 86.3%, 95.7% and 91%, respectively, in Bayes tree model. The logistic regression model incorporated five gene methylation signatures at AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, adjusted for age, sex and smoking, showed robust performances in which the sensitivity, specificity, accuracy, and area under the curve (AUC) were 78%, 97%, 87%, and 0.91, respectively.ConclusionsIn summary, a high-throughput DNA methylation microarray dataset followed by batch effect elimination can be a good strategy to discover optimal DNA methylation diagnostic panels. Methylation profiles of AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, could be an effective methylation-based assay for NSCLC diagnosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-014-0035-3) contains supplementary material, which is available to authorized users.
Highlights
DNA methylation was suggested as the promising biomarker for lung cancer diagnosis
Batch effect elimination and candidate gene selection non-small cell lung carcinoma (NSCLC)-related public DNA methylation microarrays were searched through the Gene Expression Omnibus (GEO), ArrayExpress and The Cancer Genome Atlas Project (TCGA) projects
Meta-analysis of the DNA methylation microarrays showed that Neurotensin receptor-1 (NTSR1) (P = 5.4 × 10-15), solute carrier family 5 (SLC5A8) (P = 5.9 × 10-9), galanin receptor 1 (GALR1) (P = 9.9 × 10-10) and angiotensin II receptor (AGTR1) (P = 6.7 × 10-5) were significantly hypermethylated in NSCLC, whereas zinc finger (ZMYND10) (P = 6.2 × 10-20) was significantly hypomethylated in NSCLC (Additional file 1: Figure S3)
Summary
DNA methylation was suggested as the promising biomarker for lung cancer diagnosis. it is a great challenge to search for the optimal combination of methylation biomarkers to obtain maximum diagnostic performance. While the overall 5-year survival rates for late stage III and IV of NSCLC patients were just 5% to 14% and 1%, Among all the genetic variations, single nucleotides polymorphisms (SNPs) have been considered as the most stable biomarker for heritable disease, since the status of the SNPs can be detected with almost 100% accuracy and unchanged during the entire life. It is specific and powerful for a single gene-caused disease.
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