School of Public Health, North China University of Science and Technology, Tangshan, China.
Affiliated Tangshan Gongren Hospital, North China University of Science and Technology, Tangshan, China.
Pathol Oncol Res. 2022 Aug 10;28:1610455. doi: 10.3389/pore.2022.1610455. eCollection 2022.
Lung adenocarcinoma is one of the most common malignancies. Though some historic breakthroughs have been made in lung adenocarcinoma, its molecular mechanisms of development remain elusive. The aim of this study was to identify the potential genes associated with the lung adenocarcinoma progression and to provide new ideas for the prognosis evaluation of lung adenocarcinoma. The transcriptional profiles of ten pairs of snap-frozen tumor and adjacent normal lung tissues were obtained by performing RNA-seq. Weighted gene co-expression network analysis (WGCNA) was used to construct free-scale gene co-expression networks in order to explore the associations of gene sets with the clinical features and to investigate the functional enrichment analysis of co-expression genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Set Enrichment Analysis (GSEA) analyses were performed using clusterProfiler. The protein-protein network (PPI) was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and hub genes were identified using Cytohubba in Cytoscape. Transcription factor enrichment analysis was performed by the RcisTarget program in R language. Based on RNA-seq data, 1,545 differentially expressed genes (DEGs) were found. Eight co-expression modules were identified among these DEGs. The blue module exhibited a strong correlation with LUAD, in which , , , , , , and were hub genes. A low expression level of , 2, and was detrimental to the survival of LUAD patients. Genes in the blue module enriched in 86 Gene Ontology terms and five KEGG pathways. We also found that transcription factors and were related to the biological function of the blue module. Overall, this study brings a new perspective to the understanding of LUAD and provides possible molecular biomarkers for prognosis evaluation of LUAD.
肺腺癌是最常见的恶性肿瘤之一。尽管在肺腺癌方面取得了一些历史性的突破,但它的发展分子机制仍难以捉摸。本研究旨在鉴定与肺腺癌进展相关的潜在基因,并为肺腺癌的预后评估提供新的思路。通过 RNA-seq 获得了十对冷冻肿瘤组织和相邻正常肺组织的转录谱。采用加权基因共表达网络分析(WGCNA)构建无标度基因共表达网络,以探讨基因集与临床特征的关联,并研究共表达基因的功能富集分析。使用 clusterProfiler 进行基因本体论(GO)、京都基因与基因组百科全书(KEGG)通路和基因集富集分析(GSEA)分析。使用 Search Tool for the Retrieval of Interacting Genes/Proteins(STRING)建立蛋白质-蛋白质网络(PPI),并使用 Cytoscape 中的 Cytohubba 识别枢纽基因。通过 R 语言中的 RcisTarget 程序进行转录因子富集分析。基于 RNA-seq 数据,发现了 1545 个差异表达基因(DEGs)。在这些 DEGs 中鉴定出 8 个共表达模块。蓝色模块与 LUAD 表现出强烈的相关性,其中、、、、、、和是枢纽基因。低表达水平的、、和不利于 LUAD 患者的生存。蓝色模块中的基因富集了 86 个 GO 术语和 5 个 KEGG 通路。我们还发现转录因子和与蓝色模块的生物学功能有关。总的来说,这项研究为理解 LUAD 提供了新的视角,并为 LUAD 的预后评估提供了可能的分子生物标志物。