Abstract Lung cancer has one of the highest mortality rates of malignant neoplasms. Lung adenocarcinoma (LUAD) is one of the most common types of lung cancer. DNA methylation is more stable than gene expression and could be used as a biomarker for early tumor diagnosis. This study is aimed to screen potential DNA methylation signatures to facilitate the diagnosis and prognosis of LUAD and integrate gene expression and DNA methylation data of LUAD to identify functional epigenetic modules. We systematically integrated gene expression and DNA methylation data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), bioinformatic models and algorithms were implemented to identify signatures and functional modules for LUAD. Three promising diagnostic and five potential prognostic signatures for LUAD were screened by rigorous filtration, and our tumor-normal classifier and prognostic model were validated in two separate data sets. Additionally, we identified functional epigenetic modules in the TCGA LUAD dataset and GEO independent validation data set. Interestingly, the MUC1 module was identified in both datasets. The potential biomarkers for the diagnosis and prognosis of LUAD are expected to be further verified in clinical practice to aid in the diagnosis and treatment of LUAD.

中文翻译：

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基因表达和 DNA 甲基化数据的综合分析确定了肺腺癌的潜在生物标志物和功能表观遗传模块

摘要 肺癌是死亡率最高的恶性肿瘤之一。肺腺癌 (LUAD) 是最常见的肺癌类型之一。DNA甲基化比基因表达更稳定，可用作早期肿瘤诊断的生物标志物。本研究旨在筛选潜在的 DNA 甲基化特征以促进 LUAD 的诊断和预后，并整合 LUAD 的基因表达和 DNA 甲基化数据以识别功能性表观遗传模块。我们系统地整合了来自癌症基因组图谱 (TCGA) 和基因表达综合 (GEO) 的基因表达和 DNA 甲基化数据，实施了生物信息学模型和算法来识别 LUAD 的特征和功能模块。通过严格过滤筛选了三个有希望的 LUAD 诊断和五个潜在的预后特征，我们的肿瘤-正常分类器和预后模型在两个独立的数据集中得到验证。此外，我们在 TCGA LUAD 数据集和 GEO 独立验证数据集中确定了功能表观遗传模块。有趣的是，在两个数据集中都发现了 MUC1 模块。LUAD诊断和预后的潜在生物标志物有望在临床实践中得到进一步验证，以帮助LUAD的诊断和治疗。