| Aixia Chen,Shengnan Zhao,Fei Zhou,Hongying Lv,Donghai Liang,Tao Jiang,Lijin Zhu,Rui Liu,Jingyu Cao,Shihai Liu,Hongsheng Yu. Identification of potential immune-related prognostic biomarkers of lung cancer using gene co-expression network analysis. Oncol Transl Med, 2020, 6: 247-257. |
| 通过基因共表达网络分析鉴定肺癌的潜在免疫相关预后生物标志物 |
| Identification of potential immune-related prognostic biomarkers of lung cancer using gene co-expression network analysis |
| Received:June 15, 2020 Revised:October 13, 2020 |
| DOI：10.1007/s10330-020-0437-7 |
| 中文关键词: 肺腺癌，生信，GEO, GEPIA, 关键基因，预后，甲基化 |
| 英文关键词: lung adenocarcinoma (LUAD); bioinformatics; gene expression omnibus; gene expression profiling interactive analysis (GEPIA); prognosis; methylation |
| 基金项目:北京市希思科临床肿瘤学研究基金会（Y-HR2018-293，Y-HR2018-294） |
| Author Name | Affiliation | E-mail | | Aixia Chen | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | caxdoc@126.com | | Shengnan Zhao | Department of Medcine Oncology, Qinghai University Affilated Hospital | | | Fei Zhou | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | | | Hongying Lv | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | | | Donghai Liang | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | | | Tao Jiang | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | | | Lijin Zhu | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | | | Rui Liu | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | | | Jingyu Cao | Department of Hepatobilary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University | | | Shihai Liu | Department of Central Laboratory, The Affiliated Hospital of Qingdao University | | | Hongsheng Yu* | Department of Radiation Oncology, The Affiliated Hospital of Qingdao University | qdyuhs@126.com |
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| 中文摘要: |
| Objective: 通过整合微阵列数据集，从而发现有潜力的关键致癌基因，以获得差异表达基因并预测肺癌患者的预后。使用DAVID 网站（https://david.ncifcrf.gov）的KEGG和GO分析功能，来挖掘高通量基因组数据和进行信号通路富集分析。对基因的表达和功能进行了分析。从Gene Expression Omnibus数据库下载微阵列数据集GSE139032，从而挖掘有潜力的关键基因在肺癌预后中的作用。
Methods: 通过WGCNA分析，并通过GEPIA数据库，DAVID在线数据库，DiseaeMeth, cBioportal 和TIMER数据库的验证，我们从众多基因中筛选出KRT6C、LAMC2、LAMB3、KRT6和MYEOV。
Results: 我们发现这5个基因的表达和肺癌肿瘤分期和不良预后相关，Kaplan-Meier曲线显示，5个关键基因具有较好的预后价值，在肺腺癌中，它们的甲基化水平显著低于健康肺组织。然而，单个关键基因的记忆富集分析显示，它们都与免疫相关。
Conclusion:我们的研究结果表明，KRT6C、LAMC2、LAMB3、KRT6A和MYEOV都是肺腺癌的具有诊断和预后价值标志物。 |
| 英文摘要: |
| Objective: The objective of this study was to identify new carcinogenetic hub genes and develop the
integration of differentially expressed genes to predict the prognosis of lung cancer.
Methods: GSE139032 microarray data packages were downloaded from the Gene Expression Omnibus
for planning, testing, and review of data. We identified KRT6C, LAMC2, LAMB3, KRT6A, and MYEOV from
a key module for validation.
Results: We found that the five genes were related to a poor prognosis, and the expression levels of
these genes were associated with tumor stage. Furthermore, Kaplan-Meier plotter showed that the five
hub genes had better prognostic values. The mean levels of methylation in lung adenocarcinoma (LUAD)
were significantly lower than those in healthy lung tissues for the hub genes. However, gene set enrichment
analysis (GSEA) for single hub genes showed that all of them were immune-related.
Conclusion: Our findings demonstrated that KRT6C, LAMC2, LAMB3, KRT6A, and MYEOV are all
candidate diagnostic and prognostic biomarkers for LUAD. They may have clinical implications in LUAD
patients not only for the improvement of risk stratification but also for therapeutic decisions and prognosis
prediction. |
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