Dai Dongjun, Shi Rongkai, Han Shuting, Jin Hongchuan, Wang Xian
Department of Medical Oncology.
Laboratory of Cancer Biology, Key Lab of Biotherapy, Sir Run Run Shaw Hospital, Medical School of Zhejiang University, Hangzhou, China.
Medicine (Baltimore). 2020 Aug 7;99(32):e21478. doi: 10.1097/MD.0000000000021478.
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.
本研究的目的是使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）的发生和预后相关的枢纽基因。我们纳入了来自癌症基因组图谱（TCGA）数据库的184例IIB至IV期LUAD样本和59例正常肺组织样本。使用R包“limma”来鉴定差异表达基因（DEG）。分别使用R包“WGCNA”和“survival”进行WGCNA和生存分析。功能分析通过R包“clusterProfiler”和GSEA软件进行。通过Cytoscape_v3.6.1进行网络构建和MCODE分析。在LUAD和正常肺组织之间共发现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显示核糖体生物发生相关术语富集。我们观察到8个基因的表达与KRAS MT LUAD患者较差的生存率呈正相关，其中7个基因在Kaplan-Meier绘图仪数据库（kmplot.com/）中得到验证（胸腺素β10 [TMSB10]、核糖体蛋白S16 [RPS16]、线粒体核糖体蛋白L27 [MRPL27]、细胞色素c氧化酶亚基6A1 [COX6A1]、HCLS1相关蛋白X-1 [HAX1]、核糖体蛋白L38 [RPL38]和ATP合酶膜亚基DAPIT [ATP5MD]）。GSEA分析发现mTOR和STK33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发展中的枢纽基因。所鉴定的预后因素将是临床应用中的潜在生物标志物。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。
