Abstract

Changes in DNA methylation level at some CpG locus are closely associated with the occurrence of lung squamous cell carcinoma (LUSC). However, its specific regulatory mechanism is still unclear. Therefore, it is necessary to systematically identify and analyze those key CpG sites whose DNA methylation levels are closely related to the differential expression of up- and down-regulated genes in LUSC. Due to the dispersion of DNA methylation sites in different regions of genome, to study the correlation between gene expression level and DNA methylation, we divided gene into 6 non-overlapping functional regions and proposed a two-step correlation analysis method to identify differential DNA methylation sites and matched differential expression genes. As a results, we obtained 39 key CpG sites scattered in 27 genes. Through comparative analysis of LUSC-normal sample pairs, we found that these sites and genes can accurately cluster LUSC samples and normal samples. Finally, we used these sites and genes to distinguish LUSC from normal samples. The results suggest that they can be used as effective biomarkers for identifying LUSC. In addition, the proposed two-step correlation analysis method can also be extended to the identification of biomarkers of other cancers and diseases.

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