Weighted gene coexpression network analysis identifies hub genes related to KRAS mutant lung adenocarcinoma.
Weighted gene coexpression network analysis identifies hub genes related to KRAS mutant lung adenocarcinoma.
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DOI：
10.1097/md.0000000000021478
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发表时间：
2020-08-07
期刊：
影响因子：
1.6
通讯作者：
Wang X
中科院分区：
文献类型：
--
作者：
Dai D;Shi R;Han S;Jin H;Wang X
本研究的目的是利用加权基因共表达网络分析（WGCNA）来鉴定与KRAS突变（MT）肺腺癌（LUAD）的发病率和预后相关的枢纽基因。我们涉及来自癌症基因组图谱（TCGA）数据库的184个IIB至IV期LUAD样本和59个正常肺组织样本。使用R软件包“limma”鉴定差异表达基因（DEG）。WGCNA和生存分析分别由R软件包“WGCNA”和“生存”进行。用R软件包“clusterProfiler”和GSEA软件进行功能分析。网络构建和MCODE分析由Cytoscape_v3.6.1进行。在LUAD和正常肺组织中共检测到2590个KRAS MT特异性DEG，并鉴定出10个WGCNA模块。对关键模块的功能分析表明，核糖体生物发生相关的术语得到了丰富。我们观察到8个基因的表达与KRAS MT LUAD患者的不良生存率呈正相关，其中7个基因的表达经Kaplan-Meier检验数据库验证（kmplot.com/）（胸腺素β 10 [TMSB 10]，核糖体蛋白S16 [RPS 16]，线粒体核糖体蛋白L27 [MRPL 27]，细胞色素c氧化酶亚基6A 1 [COX 6A 1]，HCLS 1相关蛋白X-1 [HAX 1]，核糖体蛋白L38 [RPL 38]和ATP合成酶膜亚基DAPIT [ATP 5 MD]）。GSEA分析发现mTOR和STK 33通路在KRAS MT LUAD中上调（P <0.05，错误发现率[FDR]<0.25）。 总之，我们的研究首次使用WGCNA来鉴定KRAS MT LUAD发育中的枢纽基因。所确定的预后因素将是临床使用的潜在生物标志物。需要进一步的分子研究来证实这些基因在KRAS MT LUAD中的作用机制。
Supplemental Digital Content is available in the text The aim of current study was to use Weighted Gene Coexpression Network Analysis (WGCNA) to identify hub genes related to the incidence and prognosis of KRAS mutant (MT) lung adenocarcinoma (LUAD). We involved 184 stage IIB to IV LUAD samples and 59 normal lung tissue samples from The Cancer Genome Atlas (TCGA) database. The R package “limma” was used to identify differentially expressed genes (DEGs). WGCNA and survival analyses were performed by R packages “WGCNA” and “survival,” respectively. The functional analyses were performed by R package “clusterProfiler” and GSEA software. Network construction and MCODE analysis were performed by Cytoscape_v3.6.1. Totally 2590 KRAS MT specific DEGs were found between LUAD and normal lung tissues, and 10 WGCNA modules were identified. Functional analysis of the key module showed the ribosome biogenesis related terms were enriched. We observed the expression of 8 genes were positively correlated to the worse survival of KRAS MT LUAD patients, the 7 of them were validated by Kaplan–Meier plotter database (kmplot.com/) (thymosin Beta 10 [TMSB10], ribosomal Protein S16 [RPS16], mitochondrial ribosomal protein L27 [MRPL27], cytochrome c oxidase subunit 6A1 [COX6A1], HCLS1-associated protein X-1 [HAX1], ribosomal protein L38 [RPL38], and ATP Synthase Membrane Subunit DAPIT [ATP5MD]). The GSEA analysis found mTOR and STK33 pathways were upregulated in KRAS MT LUAD (P < .05, false discovery rate [FDR] < 0.25). In summary, our study firstly used WGCNA to identify hub genes in the development of KRAS MT LUAD. The identified prognostic factors would be potential biomarkers in clinical use. Further molecular studies are required to confirm the mechanism of those genes in KRAS MT LUAD.