摘要
目的肺癌发生和发展是一个多基因参与、长时间演变的复杂过程。因此有必要对肺癌分子机制进行系统研究。本研究采用癌症基因组图谱(the cancer genome atlas,TCGA)数据库分析肺腺癌(lung adenocarcinoma,LUAD)中差异表达的长链非编码RNA(long non-coding RNA,LncRNA)、信使RNA(messenger RNA,mRNA)和微小RNA(microRNA,miRNA),构建基因间调控网络,并进一步筛选和分析与患者生存预后相关的RNA分子,为肺腺癌分子标志物及治疗靶点的发掘提供依据。方法TCGA数据库获得535例肺腺癌样本和59例正常肺组织样本的RNA测序(RNA sequencing,RNA-Seq)数据,521例肺腺癌样本和46例正常肺组织样本的miRNA-seq数据以及522例肺腺癌患者临床信息进行分析。使用R语言中的“DESeq”鉴定差异表达RNA。通过miRcode数据库预测差异表达的lncRNA和miRNA之间的相互作用,并根据TargetScan、miRTarBase和miRDB数据库进一步检索miRNA靶向的mRNA。基于RNA间的相互作用构建lncRNA-miRNA-mRNA ceRNA网络。使用DAVID 6.8和R语言中的“clusterprofiler”对网络中mRNA基因功能和信号通路进行富集分析。采用Kaplan-Meier生存分析差异表达的RNA与肺腺癌患者生存预后的关联性。采用多因素Cox风险回归筛选出影响肺腺癌患者总体生存率的独立RNA分子。结果数据分析结果表明共有lncRNA 1647个、miRNA 120个和mRNA 2503个在肺腺癌中差异表达,差异倍数>2,P<0.01。经RNA间相互作用分析结果表明这些差异表达的RNA中有lncRNA 138个,miRNA 22个和mRNA 36个参与了ceRNA网络构建。36个mRNA主要富集于11个生物学进程和5个细胞信号通路中,P<0.05。Kaplan-Meier生存分析表明,LINC00518(P<0.001)、AP002478.1(P=0.011)等31个LncRNA;CCNB1(P<0.001)、CHEK1(P=0.005)等16个mRNA以及1个miRNAhsa-mir-31(P=0.021)与肺腺癌患者总体生存率有关联。多因素Cox回归分析结果表明,患者TNM分期,LINC00221、UCA1、STEAP2-AS1、LINC00518、E2F7、DLC1、CCNE2和SALL1可作为肺腺癌患者预后的独立危险因素(HR>1,P<0.05),而MED4-AS1和CLSPN可作为肺腺癌患者预后保护因素(HR<1,P<0.05)。结论根据肺腺癌中差异表达的RNA成功构建了ceRNA调控网络,有助于进一步探索肺腺癌发生发展分子机制。同时,对网络中RNA的生物学功能进行了初步分析并筛选出影响肺腺癌患者生存预后的风险因子,有望为肺腺癌患者诊断和预后提供新的生物标志物。
OBJECTIVE The occurrence and development of lung cancer is a complex process involving multiple genes and long-term evolution.Therefore,it is necessary to systematically study the molecular mechanism of lung cancer.In this study,the TCGA database was used to analyze the differentially expressed LncRNA,mRNA,miRNA in lung adenocarcinoma and constructing regulatory network.Screening and analysis of RNA related to the survival prognosis of patients can provide a basis for the discovery of molecular markers and therapeutic targets of lung adenocarcinoma.METHODS The RNAseq(535lung adenocarcinoma samples,59normal samples),miRNAseq(521lung adenocarcinoma samples,46normal samples)and 522clinical data were collected form The Cancer Genome Atlas(TCGA)database.Differentially expressed RNA was identified using"DESeq"in the R language.The interaction between these differentially expressed RNAs was predicted by databases(miRcode,TargetScan,miRTarBase and miRDB).The lncRNA-miRNA-mRNA ceRNA network was constructed based on the interaction between RNAs.Using DAVID 6.8and"clusterprofiler"to performed enrichment analysis of mRNA gene functions and regulatory pathways in the network.Kaplan-Meier survival analysis of the correlation between differentially expressed RNA and survival prognosis in patients with lung adenocarcinoma.Multivariate Cox risk regression screening for independent RNA molecules affecting the overall survival rate of lung adenocarcinoma patients.RESULTS There were 1647lncRNAs,120miRNAs and 2503mRNAs were differentially expressed in LUAD(Fold change>2,P<0.01).Among these differentially expressed RNAs,138lncRNAs,22miRNAs,and 36mRNAs participated in the construction of the ceRNA network.Thirty-six mRNAs were mainly concentrated in 11biological processes and 5cellular signaling pathways,P<0.05.Thirty-one lncRNAs such as LINC00518(P<0.001),AP002478.1(P=0.011),16mRNAs such as CCNB1(P<0.001),CHEK1(P=0.005)and 1miRNAhsa-mir-31(P=0.021)were significantly associated with overall survival in lung adenocarcinoma patients.Multivariate Cox regression analysis showed that the TNM staging,LINC00221,UCA1,STEAP2-AS1,LINC00518,E2F7,DLC1,CCNE2,and SALL1 were independent risk factors for prognosis in patients with lung adenocarcinoma(HR>1,P<0.05),while MED4-AS1 and CLSPN were protective factors for the prognosis(HR<1,P<0.05).CONCLUSIONS The ceRNA regulatory network was successfully constructed based on the differentially expressed RNA in lung adenocarcinoma,which is helpful to further explore the molecular mechanism of the development of lung adenocarcinoma.At the same time,a preliminary analysis of the biological function of RNA in the network was carried out,and screen out the risk factors that affect the survival prognosis of lung adenocarcinoma patients,which is expected to provide new biomarkers for the diagnosis and prognosis of lung adenocarcinoma patients.
作者
史杨
李爱芳
黄建胜
丁卉
赵志钢
SHI Yang;LI Ai-fang;HUANG Jian-sheng;DING Hui;ZHAO Zhi-gang(Department of Clinical Laboratory,Lishui Hospital of Zhejiang University,Lishui 323000,P.R.China)
出处
《中华肿瘤防治杂志》
CAS
北大核心
2020年第16期1298-1304,共7页
Chinese Journal of Cancer Prevention and Treatment
基金
浙江省自然基金(LY18H160059)。
作者简介
第一作者:史杨,男,安徽宿州人,硕士,主要从事分子生物学和微生物学的研究工作。Tel:86-578-2285568,E-mail:sylsjyk@163.com;通信作者:赵志钢,男,浙江丽水人,主任技师,主要从事临床医学、感染性疾病及传染病的研究工作。Tel:86-578-2285568,E-mail:zjlszzg@163.com。
