Dataset Information

LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation.

ABSTRACT: LnCeVar (http://www.bio-bigdata.net/LnCeVar/) is a comprehensive database that aims to provide genomic variations that disturb lncRNA-associated competing endogenous RNA (ceRNA) network regulation curated from the published literature and high-throughput data sets. LnCeVar curated 119 501 variation-ceRNA events from thousands of samples and cell lines, including: (i) more than 2000 experimentally supported circulating, drug-resistant and prognosis-related lncRNA biomarkers; (ii) 11 418 somatic mutation-ceRNA events from TCGA and COSMIC; (iii) 112 674 CNV-ceRNA events from TCGA; (iv) 67 066 SNP-ceRNA events from the 1000 Genomes Project. LnCeVar provides a user-friendly searching and browsing interface. In addition, as an important supplement of the database, several flexible tools have been developed to aid retrieval and analysis of the data. The LnCeVar-BLAST interface is a convenient way for users to search ceRNAs by interesting sequences. LnCeVar-Function is a tool for performing functional enrichment analysis. LnCeVar-Hallmark identifies dysregulated cancer hallmarks of variation-ceRNA events. LnCeVar-Survival performs COX regression analyses and produces survival curves for variation-ceRNA events. LnCeVar-Network identifies and creates a visualization of dysregulated variation-ceRNA networks. Collectively, LnCeVar will serve as an important resource for investigating the functions and mechanisms of personalized genomic variations that disturb ceRNA network regulation in human diseases.

SUBMITTER: Wang P

PROVIDER: S-EPMC7145649 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation.

Wang Peng P Li Xin X Gao Yue Y Guo Qiuyan Q Ning Shangwei S Zhang Yunpeng Y Shang Shipeng S Wang Junwei J Wang Yanxia Y Zhi Hui H Fang Ying Y Shen Weitao W Zhang Guangmei G Chen Steven Xi SX Li Xia X

Nucleic acids research 20200101 D1

LnCeVar (http://www.bio-bigdata.net/LnCeVar/) is a comprehensive database that aims to provide genomic variations that disturb lncRNA-associated competing endogenous RNA (ceRNA) network regulation curated from the published literature and high-throughput data sets. LnCeVar curated 119 501 variation-ceRNA events from thousands of samples and cell lines, including: (i) more than 2000 experimentally supported circulating, drug-resistant and prognosis-related lncRNA biomarkers; (ii) 11 418 somatic m ...[more]

PMID: 31617563

Similar Datasets

Project description:Renal cell carcinoma (RCC) ranks among the leading causes of cancer-related mortality. Despite extensive research, the precise etiology and progression of RCC remain incompletely elucidated. Long noncoding RNA (lncRNA) has been identified as competitive endogenous RNA (ceRNA) capable of binding to microRNA (miRNA) sites, thereby modulating the expression of messenger RNAs (mRNA) and target genes. This regulatory network is known to exert a pivotal influence on cancer initiation and progression. However, the specific role and functional significance of the lncRNA-miRNA-mRNA ceRNA network in RCC remain poorly understood. The RCC transcriptome data was obtained from the gene expression omnibus database. The identification of differentially expressed long noncoding RNAs (DElncRNAs), differentially expressed miRNAs, and differentially expressed mRNAs (DEmRNAs) between RCC and corresponding paracancer tissues was performed using the "Limma" package in R 4.3.1 software. We employed a weighted gene co-expression network analysis to identify the key DElncRNAs that are most relevant to RCC. Subsequently, we utilized the encyclopedia of RNA interactomes database to predict the interactions between these DElncRNAs and miRNAs, and the miRDB database to predict the interactions between miRNAs and mRNAs. Therefore, key DElncRNAs were obtained to verify the expression of their related genes in the The Cancer Genome Atlas database and to analyze the prognosis. The construction of RCC-specific lncRNA-miRNA-mRNA ceRNA network was carried out using Cytoscape 3.7.0. A total of 286 DElncRNAs, 56 differentially expressed miRNAs, and 2065 DEmRNAs were identified in RCC. Seven key DElncRNAs (GAS6 antisense RNA 1, myocardial infarction associated transcript, long intergenic nonprotein coding RNA 921, MMP25 antisense RNA 1, Chromosome 22 Open Reading Frame 34, MIR34A host gene, MIR4435-2 host gene) were identified using weighted gene co-expression network analysis and encyclopedia of RNA interactomes databases. Subsequently, a network diagram comprising 217 nodes and 463 edges was constructed based on these key DElncRNAs. The functional analysis of DEmRNAs in the ceRNA network was conducted using Kyoto Encyclopedia of Genes and Genomes and gene ontology. We constructed RCC-specific ceRNA networks and identified the crucial lncRNAs associated with RCC using bioinformatics analysis, which will help us further understand the pathogenesis of this disease.

Project description:ObjectiveERCC4 is one of the most significant molecules of Nucleotide Excision Repair (NER), which has been researched due to its high expression in colorectal cancer (CRC). This study aimed to find out the ceRNA (competitive endogenous RNA) network of ERCC4 in CRC.Methods and materialsPan cancer mRNA expression of ERCC4 was evaluated using TCGA database. The protein expression of ERCC4 was evaluated based on the Human Protein Atlas (HPA). We screened DElncRNAs and DEmiRNAs in two groups of ERCC4 high and ERCC4 low expression in CRC. Then a lncRNA-miRNA-ERCC4 regulatory network was constructed based on DElncRNAs and DEmiRNAs using Starbase database and visualized by Cytoscape software. Kaplan-Meier analysis was performed to evaluate the prognostic value of the ceRNA network. Further, RT-PCR was performed to validate the expression of the representative molecules in the ceRNA network in CRC and normal tissues. The relationship between drug sensitivity and these molecules were also evaluated using RNAactDrug database.ResultsERCC4 was overexpressed in a variety of tumors at mRNA levels, including CRC. High expression of ERCC4 was also observed on protein level in CRC. A total of 1,885 DElncRNAs and 68 DEmiRNAs were identified from CRC samples in ERCC4 high and ERCC4 low expression groups. Predicted by the Starbase database, we got interacting miRNAs and lncRNAs of ERCC4 from the DEmiRNAs and DElncRNAs, and a lncRNA-miRNA-ERCC4 regulatory network was constructed. Kaplan-Meier survival curves results showed that miR-200c-3p (hazard ratio [HR] = 0.62, P = 0.032), MALAT1 (HR = 1.54, P = 0.016), and AC005520.2 (hazard ratio [HR] = 1.75, P = 0.002) were significantly associated with the prognosis of CRC. After validation by RT-PCR, we found that ERCC4 and MALAT1 were up-regulated in CRC compared with normal tissues, while miR-200c-3p was down-regulated. A strong negative correlation was observed between MALAT1 and miR-200c-3p. Drug sensitivity analysis showed that ERCC4, miR-200c and MALAT1 were all associated with Cisplatin.ConclusionWe constructed a ceRNA network of ERCC4 in CRC, of which the MALAT1-miR-200c-3p-ERCC4 axis may be involved in the development, prognosis and chemotherapy sensitivity of CRC. These findings might provide novel clues and insights on the molecular mechanisms of ERCC4 and NER pathway in CRC.

Dataset Information

LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation.

Publications

LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets