Small RNAs and the competing endogenous RNA network in high grade serous ovarian cancer tumor spread.
Ontology highlight
ABSTRACT:
SUBMITTER: Bachmayr-Heyda A
PROVIDER: S-EPMC5129959 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Increasing lncRNA-associated competing triplets were found to play important roles in cancers. With the accumulation of high-throughput sequencing data in public databases, the size of available tumor samples is becoming larger and larger, which introduces new challenges to identify competing triplets. Here, we developed a novel method, called LncMiM, to detect the lncRNA-miRNA-mRNA competing triplets in ovarian cancer with tumor samples from the TCGA database. In LncMiM, non-linear correlation analysis is used to cover the problem of weak correlations between miRNA-target pairs, which is mainly due to the difference in the magnitude of the expression level. In addition, besides the miRNA, the impact of lncRNA and mRNA on the interactions in triplets is also considered to improve the identification sensitivity of LncMiM without reducing its accuracy. By using LncMiM, a total of 847 lncRNA-associated competing triplets were found. All the competing triplets form a miRNA-lncRNA pair centered regulatory network, in which ZFAS1, SNHG29, GAS5, AC112491.1, and AC099850.4 are the top five lncRNAs with most connections. The results of biological process and KEGG pathway enrichment analysis indicates that the competing triplets are mainly associated with cell division, cell proliferation, cell cycle, oocyte meiosis, oxidative phosphorylation, ribosome, and p53 signaling pathway. Through survival analysis, 107 potential prognostic biomarkers are found in the competing triplets, including FGD5-AS1, HCP5, HMGN4, TACC3, and so on. LncMiM is available at https://github.com/xiaofengsong/LncMiM.
| S-EPMC7839966 | biostudies-literature
Project description:Some long noncoding RNAs (lncRNAs) play important roles in the regulation of gene expression by acting as competing endogenous RNAs (ceRNAs). However, the roles of lncRNA associated-ceRNAs in oncogenesis are not fully understood. Here, based on lncRNA microarray data of gastric cancer, bioinformatic algorithm miRcode and microRNA (miRNA) targets database TarBase, we first constructed an lncRNA-miRNA-mRNA network. Then, we confirmed it by data of six types of other cancer including head and neck squamous cell carcinoma, prostate cancer, papillary thyroid carcinoma, pituitary gonadotrope tumors, ovarian cancer, and chronic lymphocytic leukemia. The results showed a clear cancer-associated ceRNA network. Eight lncRNAs (AC009499.1, GACAT1, GACAT3, H19, LINC00152, AP000288.2, FER1L4, and RP4-620F22.3) and nine miRNAs (miR-18a-5p, miR-18b-5p, miR-19a-3p, miR-20b-5p, miR-106a-5p, miR-106b-5p, miR-31-5p, miR-139-5p, and miR-195-5p) were involved. For instance, through its miRNA response elements (MREs) to compete for miR-106a-5p, lncRNA-FER1L4 regulates the expression of PTEN, RB1, RUNX1, VEGFA, CDKN1A, E2F1, HIPK3, IL-10, and PAK7. Furthermore, cellular experimental results indicated that FER1L4-small interfering RNA (siRNA) simultaneously suppressed FER1L4 and RB1 mRNA level. These results suggest that lncRNAs harbor MREs and play important roles in post-transcriptional regulation in cancer.
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Project description:BackgroundEsophageal cancer (ESCA) constitutes one of the most common cancers worldwide. The identification of potential biomarkers is important to improving the diagnostic accuracy and treatment efficiency for patients with ESCA. In this study, we aimed to identify biomarkers related to ESCA progression through a comprehensive analysis of long non-coding RNAs (lncRNAs), microRNA (miRNAs), and mRNA expression profiles in ESCA.MethodsDifferentially expressed lncRNAs, miRNAs, and mRNAs (DElncRNAs, DEmiRNAs, and DEmRNAs, respectively) in ESCA samples compared with normal controls were obtained. A competing endogenous RNA (ceRNA) network consisting of interacting DElncRNAs, DEmiRNAs, and DEmRNAs was constructed using a combination of the miRCode and TargetScan databases. Relationships between RNAs in the ceRNA network and overall survival in patients with EC were explored through another independent ESCA dataset from The Cancer Genome Atlas.ResultsA total of 1,014 DElncRNAs, 3,677 DEmRNAs, and 35 DEmiRNAs were identified in ESCA samples compared with normal samples. Functional enrichment analysis indicated that the DEmRNAs were involved in cell activity, inflammatory response, and oxygen metabolism-related biological processes. A ceRNA network containing 5 DEmiRNAs, 582 DEmRNAs and 764 DElncRNAs was obtained. In the survival analysis, 39 genes were found to be significantly associated with overall survival in patients with EC, including GOLGA7, NFYB, TOP1, and TMTC3.ConclusionsOur study constructed a ceRNA network for ESCA for the first time, which will be helpful for the disease's diagnosis and treatment.
| S-EPMC8506737 | biostudies-literature
Project description:BackgroundOsteoarthritis (OA) is one of the most common diseases in elderly people; however, the correlation between molecular alterations and the occurrence and progression of OA are still not well understood. We conducted this study to investigate the molecular changes in OA via the competing endogenous ribonucleic acid (ceRNA) network.MethodsWe downloaded the messenger RNA (mRNA) data set, GSE48556, the microRNA (miRNA) data set, GSE105027, and the long non-coding (lncRNA) data set, GSE126963 from the Gene Expression Omnibus (GEO) database, and examined the differentially expressed genes (DEGs) in these data sets. Further, we constructed a ceRNA network of the differentially expressed miRNAs, mRNAs, and lncRNAs. To determine the biological functions of the ceRNA network, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Finally, we conducted an immune cell infiltration analysisusing single-sample gene set enrichment analysis to examine the abundance of immune cells in healthy and OA patients, and compared the infiltration of 28 immune cells between the healthy and OA samples. We also analyzed the relationship between the abundance of immune cells and mRNA expression levels in the ceRNA network.ResultsUltimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network. The functional enrichment analyses showed that these lncRNAs, miRNAs, and mRNAs are involved in various significant biological process, such as the regulation of leukocyte migration, Mitogen-Activated Protein (MAP) kinase tyrosine/serine/threonine phosphatase activity, the interleukin-17 signaling pathway, the tumor necrosis factor signaling pathway, and osteoclast differentiation, and can also have a strong effect on immune cell infiltration.ConclusionsThe dual-specificity phosphatase 1-specific ceRNA network can be used as a diagnostic tool to assess the progression of OA patients.
| S-EPMC8904995 | biostudies-literature
Project description:High-grade serous ovarian cancer (HGSC) is among the most lethal forms of cancer in women. By analyzing the mRNA-seq reads from The Cancer Genome Atlas (TCGA), we uncovered a novel cancer-enriched chimeric RNA as the result of splicing between MUC1, a highly glycosylated transmembrane mucin, TRIM46, a tripartite motif containing protein, and KRTCAP2, a keratinocyte associated protein. Experimental analyses by RT-PCR (reverse transcription PCR) and Sanger sequencing using an in-house cohort of 59 HGSC patient tumors revealed a total of six MUC1-TRIM46-KRTCAP2 isoforms joined by different annotated splice sites between these genes. These chimeric isoforms are not detected in non-cancerous ovaries, yet are present in three out of every four HGSC patient tumors, a significant frequency given the exceedingly heterogeneous nature of this disease. Transfection of the cDNA of MUC1-TRIM46-KRTCAP2 isoforms in mammalian cells led to the translation of mutant MUC1 fusion proteins that are unglycosylated and cytoplasmically localized as opposed to the cell membrane, a feature resembling the tumor-associated MUC1. Because the parental MUC1 is overexpressed in 90% of HGSC tumors and has been proposed as a clinical biomarker and therapeutic target, the chimeric MUC1-TRIM46-KRTCAP2 isoforms identified in this report could represent significantly better MUC1 variants for the same clinical utilities.
| S-EPMC4695878 | biostudies-literature
Project description:BackgroundCircular RNAs (circRNAs) have been shown to interact with microRNAs (miRNA) as competitive endogenous RNAs (ceRNAs) to regulate target gene expression and participate in tumorigenesis. However, the role of circRNA-mediated ceRNAs in bladder cancer (BC) remains unknown. Accordingly, the aim of this study was to elucidate the regulatory mechanisms in BC based on construction of the ceRNA network.MethodsThe RNA expression profiles were obtained from public datasets in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database, and were used to establish a circRNA-miRNA-mRNA network. The interactions among proteins were analyzed using the STRING database and hubgenes were extracted using the cytoHubba application. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of differentially expressed mRNAs in BC and normal tissue samples were performed to determine the functions of the intersecting mRNAs.ResultsA total of 27 circRNAs, 76 miRNAs, and 4744 mRNAs were found to be differentially expressed between BC and normal tissues. The circRNA-miRNA-mRNA ceRNA network was established based on 21 circRNAs, 14 miRNAs, and 150 mRNAs differentially expressed in BC. We also established a protein-protein interaction network and identified 10 hubgenes, which were used to construct circRNA-miRNA-hubgene regulatory modules. The most enriched biological process GO term was strand displacement (P<0.05), and the homologous recombination and Fanconi anemia pathways were significantly enriched (P<0.05) for the differentially expressed genes in BC.ConclusionsWe screened several dysregulated circRNAs and established a circRNA-associated ceRNA network by bioinformatics analysis. The identified ceRNAs are likely critical in the pathogenesis of BC and may serve as future therapeutic biomarkers.
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Project description:RNAs may act as competing endogenous RNAs (ceRNAs), a critical mechanism in determining gene expression regulations in many cancers. However, the roles of ceRNAs in thyroid carcinoma remains elusive. In this study, we have developed a novel pipeline called Molecular Network-based Identification of ceRNA (MNIceRNA) to identify ceRNAs in thyroid carcinoma. MNIceRNA first constructs micro RNA (miRNA)-messenger RNA (mRNA)long non-coding RNA (lncRNA) networks from miRcode database and weighted correlation network analysis (WGCNA), based on which to identify key drivers of differentially expressed RNAs between normal and tumor samples. It then infers ceRNAs of the identified key drivers using the long non-coding competing endogenous database (lnCeDB). We applied the pipeline into The Cancer Genome Atlas (TCGA) thyroid carcinoma data. As a result, 598 lncRNAs, 1025 mRNAs, and 90 microRNA (miRNAs) were inferred to be differentially expressed between normal and thyroid cancer samples. We then obtained eight key driver miRNAs, among which hsa-mir-221 and hsa-mir-222 were key driver RNAs identified by both miRNA-mRNA-lncRNA and WGCNA network. In addition, hsa-mir-375 was inferred to be significant for patients' survival with 34 associated ceRNAs, among which RUNX2, DUSP6 and SEMA3D are known oncogenes regulating cellular proliferation and differentiation in thyroid cancer. These ceRNAs are critical in revealing the secrets behind thyroid cancer progression and may serve as future therapeutic biomarkers.
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Project description:Long non?coding RNAs (lncRNAs) represent potential biomarkers for the diagnosis and treatment of various diseases; however, the role of circulating acute ischemic stroke (AIS)?related lncRNAs remains relatively unknown. The present study aimed to screen crucial lncRNAs for AIS based on the competing endogenous RNA (ceRNA) hypothesis. The expression profile datasets for one mRNA, accession no. GSE16561, and four microRNAs (miRNAs), accession nos. GSE95204, GSE86291, GSE55937 and GSE110993, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified, and ClusterProfiler was used to interpret the function of the DEGs. Based on the protein?protein interaction (PPI) network and module analyses, hub DEGs were identified. A ceRNA network was established based on miRNA?mRNA or miRNA?lncRNA interaction pairs. In total, 2,041 DEGs and 5 DELs were identified between the AIS and controls samples in GSE16561, and 10 DEMs between at least two of the four miRNA expression profiles. A PPI network was constructed with 1,235 DEGs, among which 20 genes were suggested to be hub genes. The hub genes paxillin (PXN), FYN?proto?oncogene, Src family tyrosine kinase (FYN), ras homolog family member A (RHOA), STAT1, and growth factor receptor?bound protein 2 (GRB2), were amongst the most significantly enriched modules extracted from the PPI network. Functional analysis revealed that these hub genes were associated with inflammation?related signaling pathways. An AIS?related ceRNA network was constructed, in which 4 DELs were predicted to function as ceRNAs for 9 DEMs, to regulate the five identified hub genes; that is, minichromosome maintenance complex component 3 associated protein?antisense RNA 1 (MCM3AP?AS1)/long intergenic non?protein coding RNA 1089 (LINC01089)/hsa?miRNA (miR)?125a/FYN, inositol?tetrakisphosphate 1?kinase?antisense RNA 1 (ITPK1?AS1)/hsa?let?7i/RHOA/GRB2/STAT1, and human leukocyte antigen complex group 27 (HCG27)/hsa?-miR?19a/PXN interaction axes. In conclusion, MCM3AP?AS1, LINC01089, ITPK1?AS1, and HCG27 may represent new biomarkers and underlying targets for the treatment of AIS.
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Project description:The aim of the present study was to identify novel microRNA (miRNA) or long noncoding RNA (lncRNA) signatures of laryngeal cancer recurrence and to investigate the regulatory mechanisms associated with this malignancy. Datasets of recurrent and nonrecurrent laryngeal cancer samples were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus database (GSE27020 and GSE25727) to examine differentially expressed miRNAs (DE‑miRs), lncRNAs (DE‑lncRs) and mRNAs (DEGs). miRNA‑mRNA and lncRNA‑miRNA networks were constructed by investigating the associations among these RNAs in various databases. Subsequently, the interactions identified were combined into a competing endogenous RNA (ceRNA) regulatory network. Feature genes in the miRNA‑mRNA network were identified via topological analysis and a recursive feature elimination algorithm. A support vector machine (SVM) classifier was established using the betweenness centrality values in the miRNA‑mRNA network, consisting of 32 optimal feature‑coding genes. The classification effect was tested using two validation datasets. Furthermore, coding genes in the ceRNA network were examined via pathway enrichment analyses. In total, 21 DE‑lncRs, 507 DEGs and 55 DE‑miRs were selected. The SVM classifier exhibited an accuracy of 94.05% (79/84) for sample classification prediction in the TCGA dataset, and 92.66 and 91.07% in the two validation datasets. The ceRNA regulatory network comprised 203 nodes, corresponding to mRNAs, miRNAs and lncRNAs, and 346 lines, corresponding to the interactions among RNAs. In particular, the interactions with the highest scores were HLA complex group 4 (HCG4)‑miR‑33b, HOX transcript antisense RNA (HOTAIR)‑miR‑1‑MAGE family member A2 (MAGEA2), EMX2 opposite strand/antisense RNA (EMX2OS)‑miR‑124‑calcitonin related polypeptide α (CALCA) and EMX2OS‑miR‑124‑γ‑aminobutyric acid type A receptor γ2 subunit (GABRG2). Gene enrichment analysis of the genes in the ceRNA network identified that 11 pathway terms and 16 molecular function terms were significantly enriched. The SVM classifier based on 32 feature coding genes exhibited high accuracy in the classification of laryngeal cancer samples. miR‑1, miR‑33b, miR‑124, HOTAIR, HCG4 and EMX2OS may be novel biomarkers of recurrent laryngeal cancer, and HCG4‑miR‑33b, HOTAIR‑miR‑1‑MAGEA2 and EMX2OS‑miR‑124‑CALCA/GABRG2 may be associated with the molecular mechanisms regulating recurrent laryngeal cancer.
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Project description:Gastric cancer (GC) is one of the most frequently occurring life-threatening malignancies worldwide. Due to its high mortality rate, the discovery of putative biomarkers that may be sensitive and specific to GC is of seminal importance. Long non-coding RNAs (lncRNAs) are non-translatable RNAs whose transcript length exceeds 200 base pairs. The dysregulation of lncRNA expression plays a key role in tumorigenesis and development. In the present study, the expression profiles of lncRNAs, microRNAs and mRNAs of 361 GC tissues (and 32 normal gastric tissues) were downloaded from The Cancer Genome Atlas database. Furthermore, differentially expressed RNAs were analyzed by the DEseq package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses confirmed some significant dysregulated signaling pathways and target RNAs. As a result, an lncRNA-associated competing endogenous RNA (ceRNA) network was constructed. Kaplan-Meier analysis of the differentially expressed RNAs associated with GC pathogenesis confirmed that the lncRNAs PVT1, HAND2-AS1 and ZNF667-AS1 were potentially associated with the prognosis of GC (P<0.05). The present study suggests the mechanism of ceRNA networks in GC, and further demonstrates that aberrant lncRNA expression may be used as an effective diagnostic tool (or target) for the prognosis of GC.
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