A systematic method was proposed to infer differential gene regulatory networks (GRNs) among lung adenocarcinoma (LUAD) samples at different stages by integrating multi-omics data to uncover significant network features and to identify tumor progression (TP) biomarker genes. The mRNA expressions, copy number variations, and DNA methylations of two independent LUAD cohorts (TCGA and SPORE) at stages I, II, and III were used, respectively. As results, the transition from normal to early onset was showed to be critical to reveal the pathogenesis of LUAD; 61 genes were identified as TP-related biomarkers, including two types of microRNAs of ABLIM2 and ZFAS1. These identified biomarkers may set light on the underlying mechanism of LUAD TP and may serve as potential drug targets for new treatments. Moreover, our study provides a general framework for TP biomarker identification for other types of cancer, which may improve the mechanism research for cancer development.

中文翻译：

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肺腺癌肿瘤进展生物标志物发现的多组学差异基因调控网络推断

提出了一种系统方法，通过整合多组学数据以揭示显着的网络特征并识别肿瘤进展 (TP) 生物标志物基因，从而推断不同阶段肺腺癌 (LUAD) 样本之间的差异基因调控网络 (GRN)。分别使用 I、II 和 III 阶段的两个独立 LUAD 队列（TCGA 和 SPORE）的 mRNA 表达、拷贝数变化和 DNA 甲基化。结果表明，从正常到早发的转变对于揭示 LUAD 的发病机制至关重要。61个基因被鉴定为TP相关的生物标志物，包括ABLIM2和ZFAS1两种microRNA. 这些已确定的生物标志物可以阐明 LUAD TP 的潜在机制，并可能作为新治疗的潜在药物靶点。此外，我们的研究为其他类型癌症的 TP 生物标志物鉴定提供了一个总体框架，这可能会改善癌症发展的机制研究。