Potential LncRNAs Prognostic Biomarkers For Non-small Cell Lung Cancer

Part Ⅰ Comprehensive analysis of lncRNA mediated ceRNA network reveals lncRNA biomarkers in Lung squamous cell carcinomaObjective:Long non-coding RNAs（lncRNA）is one kind of the competing endogenous RNA（ceRNA）,which plays a significant role in the progression of tumorigenesis The aim of the study was to identify lncRNA biomarkers for predicting the prognosis of lung squamous cell carcinoma（LUSC）using a comprehensive analysis of lncRNA mediated ceRNA networkMethods:1.Selection of differentially expressed RNAs datasets:The differentially expressed RNAs were obtained from 502 LUSC tissues and 49 non-LUSC tissues in The Cancer Genome Atlas（TCGA）database by using the edge R package.2.Functional enrichment analysis of lncRNA-related differentially expressed mRNAs:GO function analysis and KEGG pathway analysis through DAVID database were used to predict related functions of lncRNA-related differentially expressed mRNAs.3.Predicting the mechanism of lncRNAs in LUSC:we used the miRCode database（http://www.mircode.org/）to predict the relationship between lncRNA and miRNA.MiRTarBase（http://mirtarbase.mbc.nctu.edu.tw/）,miRDB（http://www.mirdb.org/）and TargetScan（http://www.targetscan.org/）databases were used to predict the target mRNAs of miRNAs.Then,we obtained the relationship between miRNA and mRNA.Finally,the lncRNA-miRNA-mRNA ceRNA network was constructed.4.Construction of univariate and multivariate Cox regression models:univariate and multivariate Cox regression models of differentially expressed lncRNAs were used to determine whether potential lncRNAs can be used as independent prognostic factors.Predicting the mechanism of lncRNA in the Cox predictive model:We constructed a ceRNA subnetwork based on the lncRNAs in the Cox model to predict the mechanisms of lncRNA.Results:1.A total of 2185 lncRNAs,170 miRNAs,and 2053 mRNAs（P<0.01,| logFC|>2）were obtained in LUSC tissues and adjacent non-LUSC tissues.According to the standard,1263 up-regulated and 790 down-regulated mRNAs,1777 up-regulated and 408 down-regulated lncRNAs,143 up-regulated and 27 down-regulated miRNAs were identified.2.The ceRNA network of LUSC includes 184 lncRNAs,18 miRNAs and 49 mRNAs.11 of 184 differentially expressed lncRNAs and 1 of 18 differentially expressed miRNAs and 5 of 49 differentially expressed mRNAs were significantly associated with overall survival of LUSC（P<0.05）.3.Univariate and multivariate Cox regression analysis showed that the six-lncRNA（ADAMTS9-AS2,AC011483.1,TTTY16,AC006238.1,LINC00462,CACNA2D3-AS1）signature was an independent prognosis factor for predicting the prognosis of LUSC.Conclusion:1.Our study has identified differentially expressed lncRNAs,miRNAs and mRNAs which potentially predict the progression of LUSC by using the lncRNA,miRNA and mRNA transcriptome sequencing data from TCGA database to construct a ceRNA network.2.The lncRNA identified in our ceRNA network may play a pivotal role in the diagnosis and prognosis of LUSC patient.Part Ⅱ Integrative analysis of DNA methylation and transcriptome data reveals lung adenocarcinoma potential biomarkersObjective:DNA methylation plays a significant role in regulating the role of long non-coding RNAs（lncRNAs）in the development of lung adenocarcinoma.The aim of the study was to identify methylation-driven genes as biomarkers for predicting the prognosis of lung adenocarcinoma（LUAD）using bioinformatics analysisMethods:1.Selection of differentially expressed RNAs:Using the edge R package,we obtained differentially expressed lncRNAs and mRNAs in 535 LUAD tissues and 59 adjacent non-LUAD tissues from TCGA database.Selection of differential methylation genes:Using the limma R package,we obtained the differential methylation genes in 475 LUAD tissues and adjacent non-LUAD tissues from TCGA database.3.Selection of methylation-driven genes:Using the MethylMix R package,we obtained the methylation-driven lncRNAs and mRNAs in 465 LUAD tissues with matched DNA methylation and RNA expression and 32 adjacent non-LUAD tissues with DNA methylation data.4 Functional prediction of methylation-driven genes:GO function analysis and ConsensusPathDB pathway analysis were used to identify functional enrichment of methylation-driven genes.5.Prediction of the prognosis of LUAD:univariate and multivariate Cox regression analysis were used to identify independent prognosis factors for predicting the prognosis of LUAD.6.Identification of prognostic biomarkers of LUAD:Survival analysis of DNA methylation and gene expression revealed LUAD prognostic biomarkers for predicting the prognosis of LUAD.Results:1.We obtained a total of 99 methylation-driven mRNAs and a total of 17 methylation-driven lncRNAs using bioinformatic analysis.2.Univariate and multivariate Cox regression analysis showed that six-lncRNA（FOXE1,HOXB13-AS1₂,VMO1,HIST1H3F,AJ003147.8,ASXL3）signature can act as independent prognosis factors for predicting the prognosis of LUAD.3.Survival analysis of DNA methylation and gene expression showed that four lncRNAs（AC023824.1,AF186192.1,LINC01354 和WASIR2）and eight mRNAs（S1PR1,CCDC181,F2RL1,EFS,KLHDC9,MPV17L,GKN2,ITPRIPL1）were identified prognostic biomarkers for predicting the prognosis of LUAD.Conclusions:1.Our study identified methylation-driven lncRNAs and mRNAs using bioinformatic analysis.2.A Cox predictive model was performed to identify potential independent factors for predicting the prognosis of LUAD3.Survival analysis of DNA methylation and gene expression showed that methylation-driven lncRNAs and mRNAs can act as potential biomarkers for predicting the prognosis of LUADPart Ⅲ Effects of down-regulated LncRNA BBOX1-AS1 on the proliferation,invasion and migration of lung adenocarcinomaObjective:Long non-coding RNAs（LncRNAs）play a pivotal rule in the progression of lung cancer.The aim of the study was to identify LncRNA BBOX1-AS 1 as biomarker for predicting the prognosis of Lung adenocarcinoma and the biological function of LncRNA BBOX1-AS 1 was identified.Methods:1.The association between the expression of LncRNA BBOX1-AS 1 and lung cancer was evaluated according to the Cancer Genome Atlas（TCGA）and Gene Expression Comprehensive（GEO）database,and the differentially expressed lncRNA was obtained by edge R analysis.2.Kaplan-Meier plotting database analysis was used to perform the survival analysis of differentially expressed lncRNAs.3.Gene set enrichment（GSEA）analysis was performed using the TCGA data set.4.Cell proliferation,scratch,and invasion and migration experiments verified the functions of LncRNA BBOX 1-AS 1 in proliferation,invasion,and migration in non-small cell lung cancer,respectively Results:1.LncRNA BBOX1-AS1 was highly expressed in both LUAD and LUSC.2.The Kaplan-Meier database showed that the high expression of lncRNA BBOX1-AS1 had a poor prognosis in lung adenocarcinoma（P=0.011）.3.Down-regulation of LncRNA BBOX 1-AS 1 significantly inhibited the proliferation,migration and invasion ability of A549,H1299 cells in vitro.4.GSEA showed that Wnt signaling pathway,glycosylphosphatidylinositol-Gpi-anchored-biosynthesis and cell cycle were more abundant in lncRNABBOX1-AS1 high expression phenotype,and JAK-STAT signaling pathway,hematopoietic cell line and Graft-versus-host disease had more differential enrichment in the lncRNABBOX1-AS1 low expression phenotype.Conclusions:1.LncRNA BBOX1-AS1 can be used as a novel lncRNA to predict the prognosis of lung adenocarcinoma.2.LncRNABBOX1-AS1 can be used as an oncogene to promote the occurrence and development of lung adenocarcinoma.3.In addition,Wnt signaling pathway,glycosylphosphatidylinositol-Gpi-anchor-biosynthesis,cell cycle,JAK-STAT signaling pathway,hematopoietic cell lineage,and graft-versus-host disease may regulate the expression of lncRNABBOX1-AS1.