Construction of competing endogenous RNA interaction network as prognostic markers in metastatic melanoma.
ABSTRACT: Malignant melanoma (MM) is a malignant tumor originating from melanocytes, with high aggressiveness, high metastasis and extremely poor prognosis. MM accounts for 4% of skin cancers and 80% of mortality, and the median survival of patients with metastatic melanoma is only about 6 months, with a five-year survival rate of less than 10%. In recent years, the incidence of melanoma has gradually increased and has become one of the serious diseases that endanger human health. Competitive endogenous RNA (ceRNA) is the main model of the mechanism by which long chain non-coding RNAs (lncRNAs) play a regulatory role in the disease. LncRNAs can act as a "sponge", competitively attracting small RNAs (micoRNAs; miRNAs), thus interfering with miRNA function, and affect the expression of target gene messenger RNAs (mRNAs), ultimately promoting tumorigenesis and progression. Bioinformatics analysis can identify potentially prognostic and therapeutically relevant differentially expressed genes in MM, finding lncRNAs, miRNAs and mRNAs that are interconnected through the ceRNA network, providing further insight into gene regulation and prognosis of metastatic melanoma. Weighted co-expression networks were used to identify lncRNA and mRNA modules associated with the metastatic phenotype, as well as the co-expression genes contained in the modules. A total of 17 lncRNAs, six miRNAs, and 11 mRNAs were used to construct a ceRNA interaction network that plays a regulatory role in metastatic melanoma patients. The prognostic risk model was used as a sorter to classify the survival prognosis of melanoma patients. Four groups of ceRNA interaction triplets were finally obtained, which miR-3662 might has potential implication for the treatment of metaststic melanoma patients, and futher experiments confirmed the regulating relationship and phenotype of this assumption. This study provides new targets to regulate metastatic process, predict metastatic potential and indicates that the miR-3662 can be used in the treatment of melanoma.
Project description:Cutaneous melanoma (CM) is the most malignant tumor of skin cancers because of its rapid development and high mortality rate. Long noncoding RNAs (lncRNAs), which play essential roles in the tumorigenesis and metastasis of CM and interplay with microRNAs (miRNAs) and mRNAs, are hopefully considered to be efficient biomarkers to detect deterioration during the progression of CM to improve the prognosis. Bioinformatics analysis was fully applied to predict the vital lncRNAs and the associated miRNAs and mRNAs, which eventually constructed the competing endogenous RNA (ceRNA) network to explain the RNA expression patterns in the progression of CM. Further statistical analysis emphasized the importance of these key genes, which were statistically significantly related to one or few clinical features from the ceRNA network. The results showed the lncRNAs MGC12926 and LINC00937 were verified to be strongly connected with the prognosis of CM patients.
Project description:Lung adenocarcinoma (LUAD) is a highly malignant cancer. Although competing endogenous RNA (ceRNA)-based profiling has been investigated in patients with LUAD, it has not been specifically used to study metastasis in LUAD. We found 130 differentially expressed (DE) lncRNAs, 32 DE miRNAs and 981 DE mRNAs from patients with LUAD in The Cancer Genome Atlas (TCGA) database. We analysed the functions and pathways of 981 DE mRNAs using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Based on the target DE mRNAs and DE lncRNAs of DE miRNAs, we established an lncRNA-miRNA-mRNA ceRNA network, comprising 37 DE lncRNAs, 22 DE miRNAs and 212 DE mRNAs. Subsequently, we constructed a protein-protein interaction network of DE mRNAs in the ceRNA network. Among all, DE RNAs, 5 DE lncRNAs, 5 DE miRNAs and 45 DE mRNAs were confirmed found to be associated with clinical prognosis. Moreover, 3 DE lncRNAs, 4 DE miRNAs and 9 DE mRNAs in the ceRNA network were associated with clinical prognosis. We further screened 3 DE lncRNAs, 3 DE miRNAs and 3 DE mRNAs using clinical samples. These DE lncRNAs, DE miRNAs and DE mRNAs in ceRNA network may serve as independent biomarkers of LUAD metastasis.
Project description:<h4>Purpose</h4>Growing evidence demonstrates that long non-coding RNAs (lncRNAs) play a crucial role as competing endogenous RNAs (ceRNAs) in tumor occurrence. The lncRNAs' functions and clinical significance in laryngeal squamous cell carcinoma (LSCC) remain unclear. The study aims to reveal the lncRNA-associated ceRNA regulatory network of LSCC and clarify its clinical relevance.<h4>Methods</h4>Here, we obtained LSCC transcriptome data from The Cancer Genome Atlas (TCGA) database and identified the differential expression profile of lncRNAs, miRNAs, and mRNAs by the EdgeR R package. The function enrichment analysis of mRNAs was performed using clusterProfiler R package and GSEA3.0. Then, we constructed a ceRNA network and prognosis model based on lncRNAs through bioinformatic methods. Moreover, we explored the functions of prognosis-related lncRNA in LSCC by CCK-8 and transwell assay.<h4>Results</h4>1961 lncRNAs, 69 miRNAs, and 2224 mRNAs were identified as differentially expressed genes in LSCC tissues. According to the transcriptome differential expression profile, a ceRNA network containing 61 lncRNAs, 21 miRNAs, and 77 mRNAs was established. Then, four lncRNAs (AC011933.2, FAM30A, LINC02086, LINC02575) were identified from the ceRNA network to build a prognosis model for LSCC patients. And we found that LINC02086 and LINC02575 promoted the proliferation, migration, and invasion of LSCC cells while AC011933.2 and FAM30A inhibited these biological functions in vitro. Furthermore, we validated that LINc02086/miR-770-5p/SLC26A2 axis promoted migration in LSCC.<h4>Conclusion</h4>Four lncRNAs of the ceRNA network were abnormally expressed and related to patient prognosis in LSCC. They played a significant role in the progress of LSCC via affecting the proliferation and metastasis of tumor cells.
Project description:Objective:This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers. Methods:RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival. Results:We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs. Conclusion:Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma.
Project description:<h4>Background</h4>Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumours of the head and neck. Recent evidence has demonstrated that lncRNAs play important roles in tumour progression and could be used as biomarkers for early diagnosis, prognosis, and potential therapeutic targets. The "competitive endogenous RNA (ceRNA)" hypothesis states that lncRNAs competitively bind to miRNAs through their intramolecular miRNA reaction elements (MREs) to construct a wide range of ceRNA regulatory networks. This study aims to predict the role of ceRNA network in LSCC, for advancing the understanding of underlying mechanisms of tumorigenesis.<h4>Material and methods</h4>In this study, the functions of lncRNAs as ceRNAs in LSCC and their prognostic significance were investigated via comprehensive integrated expression profiles data of lncRNAs, mRNAs, and miRNAs obtained from The Cancer Genome Atlas (TCGA). Protein-protein interaction, gene ontology, pathway, and Kaplan-Meier curves analysis were used to profile the expression and function of altered RNAs in LSCC.<h4>Results</h4>As a result, 889 lncRNAs, 55 miRNAs and 1946 mRNAs were found to be differentially expressed in LSCC. These altered mRNAs were mainly involved in extracellular matrix organization, calcium signaling, and metabolic pathways. To study the regulatory function of lncRNAs, an lncRNA-mediated ceRNA network was constructed. This ceRNA network included 61 lncRNAs, seven miRNAs and seven target mRNAs. Of these RNAs, lncRNAs (TSPEAR-AS, CASK-AS1, MIR137HG, PART1, LSAMP-AS1), miRNA (has-mir-210) and mRNAs (HOXC13, STC2, DIO1, FOXD4L1) had a significant effect on the prognosis of LSCC.<h4>Conclusion</h4>The results of this study broaden the understanding of the mechanisms by which lncRNAs are involved in tumorigenesis. Furthermore, five lncRNAs (TSPEAR-AS, CASK-AS1, MIR137HG, PART1, LSAMP-AS1) were identified as potential prognostic biomarkers and therapeutic targets for LSCC. These results provide a basis for further experimental and clinical research.
Project description:BACKGROUND The aims of this study were to use RNA expression profile bioinformatics data from cases of thyroid cancer from the Cancer Genome Atlas (TCGA), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Gene Ontology (GO) databases to construct a competing endogenous RNA (ceRNA) network of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs). MATERIAL AND METHODS TCGA provided RNA profiles from 515 thyroid cancer tissues and 56 normal thyroid tissues. The DESeq R package analyzed high-throughput sequencing data on differentially expressed RNAs. GO and KEGG pathway analysis used the DAVID 6.8 and the ClusterProfile R package. Kaplan-Meier survival statistics and Cox regression analysis were performed. The thyroid cancer ceRNA network was constructed based on the miRDB, miRTarBase, and TargetScan databases. RESULTS There were 1,098 mRNAs associated with thyroid cancer; 101 mRNAs were associated with overall survival (OS). Multivariate analysis developed a risk scoring system that identified seven signature mRNAs, with a discriminative value of 0.88, determined by receiver operating characteristic (ROC) curve analysis. A ceRNA network included 13 mRNAs, 31 lncRNAs, and seven miRNAs. Four out of the 31 lncRNAs and all miRNAs were down-regulated, and the remaining RNAs were upregulated. Two lncRNAs (MIR1281A2HG and OPCML-IT1) and one miRNA (miR-184) were significantly associated with OS in patients with thyroid cancer. CONCLUSIONS Differential RNA expression profiling in thyroid cancer was used to construct a ceRNA network of mRNAs, lncRNAs, and miRNAs that showed potential in evaluating prognosis.
Project description:The aberrant expression of long noncoding RNAs (lncRNAs) has drawn increasing attention in the field of hepatocellular carcinoma (HCC) biology. In the present study, we obtained the expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in 371 HCC tissues and 50 normal tissues from The Cancer Genome Atlas (TCGA) and identified hepatocarcinogenesis-specific differentially expressed genes (DEGs, log fold change???2, FDR < 0.01), including 753 lncRNAs, 97 miRNAs, and 1,535 mRNAs. Because the specific functions of lncRNAs are closely related to their intracellular localizations and because the cytoplasm is the main location for competitive endogenous RNA (ceRNA) action, we analyzed not only the interactions among these DEGs but also the distributions of lncRNAs (cytoplasmic, nuclear or both). Then, an HCC-associated deregulated ceRNA network consisting of 37 lncRNAs, 10 miRNAs, and 26 mRNAs was constructed after excluding those lncRNAs located only in the nucleus. Survival analysis of this network demonstrated that 15 lncRNAs, 3 miRNAs, and 16 mRNAs were significantly correlated with the overall survival of HCC patients (p?<?0.01). Through multivariate Cox regression and lasso analysis, a risk score system based on 13 lncRNAs was constructed, which showed good discrimination and predictive ability for HCC patient survival time. This ceRNA network-construction approach, based on lncRNA distribution, not only narrowed the scope of target lncRNAs but also provided specific candidate molecular biomarkers for evaluating the prognosis of HCC, which will help expand our understanding of the ceRNA mechanisms involved in the early development of HCC.
Project description:Wilms' tumor (WT) is one of the most common types of renal carcinoma in children. The aim of the present study was to construct a competitive endogenous RNA (ceRNA) regulation network and explore novel prognostic biomarkers for WT. The expression profiles were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs). Based on the interactions between microRNAs (miRNAs) and mRNAs/long non-coding RNAs (lncRNAs), a ceRNA network was constructed. Functional enrichment analyses were subsequently conducted to explore the functions of the ceRNA-associated DEmRNAs. Survival analysis was performed to screen for prognosis-associated RNAs and the ?2 test was used to assess the associations between prognosis-associated RNA expression and histology classification/clinical staging. The present study identified 1,784 lncRNAs, 114 miRNAs and 3,337 mRNAs, which were abnormally expressed in WT compared with that in normal samples. By prediction, pairing and network analysis, a ceRNA network consisting of 38 DElncRNAs, 18 DEmiRNAs and 99 DEmRNAs was established. These DEmRNAs were significantly enriched in pathways associated with the occurrence and development of WT. By combining the expression data with survival analysis, seven prognosis-associated RNAs were identified (P<0.05). Of these seven RNAs, two (zinc finger and BTB domain containing 4; and deleted in lymphocytic leukemia 2) were significantly associated with clinical staging and histology classification. Lastly, the expression levels of the seven RNAs were verified in the Gene Expression Omnibus database. The present study revealed that 7 RNAs might be considered as novel prognostic biomarkers and potential treatment targets for therapy in WT. In addition, the ceRNA regulation network could provide novel strategies for further studies on lncRNAs and miRNAs in WT.
Project description:<h4>Introduction</h4>Kidney renal clear cell carcinoma (KIRC) has a high incidence globally, and its pathogenesis remains unclear. Long non-coding RNA (lncRNA), as a molecular sponge, participates in the regulation of competitive endogenous RNA (ceRNA). We aimed to construct a ceRNA network and screened out possible lncRNAs to predict KIRC prognosis.<h4>Material and methods</h4>All KIRC data were downloaded from the TCGA database and screened to find the possible target lncRNA; a ceRNA network was designed. Next, GO functional enrichment and KEGG pathway of differentially expressed mRNA related to lncRNA were performed. We used Kaplan-Meier curve analysis to predict the survival of these RNAs. We used Cox regression analysis to construct a model to predict KIRC prognosis.<h4>Results</h4>In the KIRC datasets, 1457 lncRNA, 54 miRNA and 2307 mRNA were screened out. The constructed ceRNA network contained 81 lncRNAs, nine miRNAs, and 17 mRNAs differentially expressed in KIRC. Survival analysis of all differentially expressed RNAs showed that 21 lncRNAs, four miRNAs, and two mRNAs were related to the overall survival rate. Cox regression analysis was performed again, and we found that eight lncRNAs were related to prognosis and used to construct predictive models. Three lnRNAs from independent samples were meaningful.<h4>Conclusion</h4>The construction of ceRNA network was involved in the process and transfer of KIRC, and three lncRNAs may be potential targets for predicting KIRC prognosis.
Project description:Background:Glioblastoma multiforme (GBM) is the most seriously brain tumor with extremely poor prognosis. Recent research has demonstrated that competitive endogenous RNA (ceRNA) network which long noncoding RNAs (lncRNAs) act as microRNA (miRNA) sponges to regulate mRNA expression were closely related to tumor development. However, the regulatory mechanisms and functional roles of ceRNA network in the pathogenesis of GBM are remaining poorly understood. Methods:In this study, we systematically analyzed the expression profiles of lncRNA and mRNA (GSE51146 dataset) and miRNA (GSE65626 dataset) from GEO database. Then, we constructed a ceRNA network with the dysregulated genes by bioinformatics methods. The TCGA and GSE4290 dataset were used to confirm the expression and prognostic value of candidate mRNAs. Results:In total, 3413 differentially expressed lncRNAs and mRNAs, 305 differentially expressed miRNAs were indentified in GBM samples. Then a ceRNA network containing 3 lncRNAs, 5 miRNAs, and 60 mRNAs was constructed. The overall survival analysis of TCGA databases indicated that two mRNAs (C1s and HSD3B7) were remarkly related with the prognosis of GBM. Conclusion:The ceRNA network may increase our understanding to the pathogenesis of GBM. In general, the candidate mRNAs from the ceRNA network can be predicted as new therapeutic targets and prognostic biomarkers for GBM.