Integrated Analysis Of LncRNA-associated CeRNA Network For Ovarian Cancer Via TCGA,GTEx And GEO Datasets

Background: Abnormal expression of long non-coding RNAs(lncRNA)play a significant role in the incidence and progression of high-grade serous ovarian cancer(HGSOC),which is a leading cause of mortality among gynecologic malignant tumor patients.In this study,our aim is to identify lncRNA-associated competing endogenous RNA(ceRNA)axes that could define more reliable prognostic parameters of HGSOC,and to investigate the lncRNAs' potential mechanism.We hoped that the lncRNAs could be potential diagnostic biomarkers and therapeutic targets.Methods: The RNA-seq and miRNA expression profiles of ovarian cancer were downloaded from The Cancer Genome Atlas(TCGA)and the Genotype-Tissue Expression(GTEx)database,and we selected the HGSOC profiles;while for obtaining the differentially expressed lncRNAs(DELs),miRNAs(DEMs),and genes(DEGs),we used edge R,limma and DESeq2 R packages.P<0.05 and |Log FC|?1 were set as the threshold value.After validating the lncRNA,miRNA and mRNA expressions,using integrated three RNA expression profiles(GSE18520,GSE27651,GSE54388)and miRNA profile(GSE47841)from the Gene Expression Omnibus(GEO)database,we performed Gene Ontology(GO)and Kyoto Encyclopedia of Gene and Genome(KEGG)pathway analyses through Cluster Profiler,in order to understand the biological processes and signaling pathways in which the different expressed genes are involved,and predict their functions in the development of HGSOC.The prognostic value of these genes was determined with Kaplan–Meier survival analysis and Cox regression analysis utilizing survival and survminer R package.Then the OS-related DELs were mapped into the star Base database to predict their target miRNAs.Comparing with the OS-related DEMs,lncRNA/miRNA interacted networks were constructed.Subsequently,the target genes of selected DEMs were searched using miRTar Base database for identified DEMs–DEGs interaction.The ceRNA network was constructed using Cytoscape.We performed GO and KEGG analyses for the mRNAs in the ceRNA network.On the basis of the results above,we screened the key lncRNAs that took valuable roles in HGSOC and the ceRNA axes in which they involved.Results: A total of 111 DELs(77 downregulated and 34 upregulated),2,620 DEGs(1,535 downregulated and 1,085 upregulated)while 186 DEMs(101 downregulated and 85 upregulated)were identified after integrating the results from TCGA,GTEx and GEO databases.The functional analysis indicated that upregulated genes were mainly involved in the biological processes such as regulation of cell cycle phase transition and positive regulation of cell cycle,and pathway of cell cycle,oxidative phosphorylation,homologous recombination,cytokine-cytokine receptor interaction and IL-17 signaling pathway,indicating the relationship between upregulated genes and cell division as well as tumor-associated pathways.33 DELs(25 upregulated and 8 downregulated),134 DEMs(76 upregulated and 58 downregulated),and 1,612 DEGs(949 upregulated and 663 downregulated)were detected that could be positively correlated with overall survival(OS)of HGSOC.With the 1,612 analyzed genes,we constructed a ceRNA network,which indicated a pre-dominant involvement of the immune-related pathways.Among them,LINC00858,LINC00665 and FTX may be involved in the immune regulation of HGSOC through ceRNA axis,FTX-miR-150-5p-STK11,LINC00665-miR-449b-5p-RRAGD,LINC00665-miR449b-5p-VAV3,LINC00858-miR-324-5p-PAK4.Conclusion: We defined three prognostic biomarkers for the incidence and progression of HGSOC,LINC00858,LINC00665 and FTX,which may play their biological functions through ceRNA axes;among which four were indicated to have a positive correlation with immune regulation of HGSOC,namely;FTX-miR-150-5pSTK11,LINC00665-miR-449b-5p-RRAGD,LINC00665-miR449b-5p-VAV3,LINC00858-miR-324-5p-PAK4.