DNA某些CpG位点甲基化水平的变化与肺鳞状细胞癌（LUSC）的发生密切相关。但其具体调控机制尚不清楚。因此，有必要系统地识别和分析那些DNA甲基化水平与LUSC上调和下调基因差异表达密切相关的关键CpG位点。由于DNA甲基化位点分散在基因组的不同区域，为了研究基因表达水平与DNA甲基化之间的相关性，我们将基因分为6个不重叠的功能区域，并提出了两步相关分析方法来识别差异DNA甲基化位点和匹配的差异表达基因。结果，我们获得了分散在27个基因中的39个关键CpG位点。通过对LUSC-正常样本对的比较分析，我们发现这些位点和基因可以准确地将LUSC样本和正常样本聚类。最后，我们使用这些位点和基因来区分 LUSC 和正常样本。结果表明它们可以作为识别 LUSC 的有效生物标志物。此外，所提出的两步相关分析方法还可以扩展到其他癌症和疾病生物标志物的鉴定。版权所有 © 2023 Elsevier Ltd. 保留所有权利。

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.Copyright © 2023 Elsevier Ltd. All rights reserved.