Liu Cheng, Li Xiang, Shao Hua, Li Dan
Department of Thoracic Surgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Department of Neurology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Front Genet. 2020 Dec 21;11:565206. doi: 10.3389/fgene.2020.565206. eCollection 2020.
: Lung adenocarcinoma (LUAD) is one of the main types of lung cancer. Because of its low early diagnosis rate, poor late prognosis, and high mortality, it is of great significance to find biomarkers for diagnosis and prognosis. : Five hundred and twelve LUADs from The Cancer Genome Atlas were used for differential expression analysis and short time-series expression miner (STEM) analysis to identify the LUAD-development characteristic genes. Survival analysis was used to identify the LUAD-unfavorable genes and LUAD-favorable genes. Gene set variation analysis (GSVA) was used to score individual samples against the two gene sets. Receiver operating characteristic (ROC) curve analysis and univariate and multivariate Cox regression analysis were used to explore the diagnostic and prognostic ability of the two GSVA score systems. Two independent data sets from Gene Expression Omnibus (GEO) were used for verifying the results. Functional enrichment analysis was used to explore the potential biological functions of LUAD-unfavorable genes. : With the development of LUAD, 185 differentially expressed genes (DEGs) were gradually upregulated, of which 84 genes were associated with LUAD survival and named as LUAD-unfavorable gene set. While 237 DEGs were gradually downregulated, of which 39 genes were associated with LUAD survival and named as LUAD-favorable gene set. ROC curve analysis and univariate/multivariate Cox proportional hazards analyses indicated both of LUAD-unfavorable GSVA score and LUAD-favorable GSVA score were a biomarker of LUAD. Moreover, both of these two GSVA score systems were an independent factor for LUAD prognosis. The LUAD-unfavorable genes were significantly involved in p53 signaling pathway, Oocyte meiosis, and Cell cycle. : We identified and validated two LUAD-development characteristic gene sets that not only have diagnostic value but also prognostic value. It may provide new insight for further research on LUAD.
肺腺癌（LUAD）是肺癌的主要类型之一。由于其早期诊断率低、晚期预后差和死亡率高，寻找诊断和预后的生物标志物具有重要意义。：使用来自癌症基因组图谱的512例肺腺癌进行差异表达分析和短时间序列表达挖掘器（STEM）分析，以鉴定肺腺癌发展特征基因。生存分析用于鉴定肺腺癌不良基因和肺腺癌有利基因。基因集变异分析（GSVA）用于根据两个基因集对个体样本进行评分。采用受试者工作特征（ROC）曲线分析以及单因素和多因素Cox回归分析来探索两个GSVA评分系统的诊断和预后能力。使用来自基因表达综合数据库（GEO）的两个独立数据集来验证结果。功能富集分析用于探索肺腺癌不良基因的潜在生物学功能。：随着肺腺癌的发展，185个差异表达基因（DEG）逐渐上调，其中84个基因与肺腺癌生存相关，命名为肺腺癌不良基因集。而237个DEG逐渐下调，其中39个基因与肺腺癌生存相关，命名为肺腺癌有利基因集。ROC曲线分析和单因素/多因素Cox比例风险分析表明，肺腺癌不良GSVA评分和肺腺癌有利GSVA评分均是肺腺癌的生物标志物。此外，这两个GSVA评分系统均是肺腺癌预后的独立因素。肺腺癌不良基因显著参与p53信号通路、卵母细胞减数分裂和细胞周期。：我们鉴定并验证了两个肺腺癌发展特征基因集，它们不仅具有诊断价值，还具有预后价值。这可能为肺腺癌的进一步研究提供新的见解。
