171,312 research outputs found
Integrated analysis of lncRNA-associated ceRNA network reveals potential biomarkers for the prognosis of hepatitis B virus-related hepatocellular carcinoma
No full textHongyan Li, Xiaonan Zhao, Chenghua Li, Chuanlun Sheng, Zhenzi Bai Infectious Department, China-Japan Union Hospital, Jilin University, Changchun 130033, China Background: There is evidence that abnormal expression of lncRNAs is associated with hepatitis B virus (HBV) infection-induced hepatocellular carcinoma (HCC). However, the mechanisms remain not fully elucidated. The study aimed to identify novel lncRNAs and explore their underlying mechanisms based on the ceRNA hypothesis. Methods: The RNA and miRNA expression profiling in 20 tumor and matched adjacent tissues from HBV–HCC patients were retrieved from the Gene Expression Omnibus database under accession numbers GSE77509 and GSE76903, respectively. Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) were identified using the EdgeR package. Protein–protein interaction (PPI) network was constructed for DEGs followed by module analysis. The ceRNA network was constructed based on interaction relationships between miRNAs and mRNAs/lncRNAs. The functions of DEGs were predicted using DAVID and BinGO databases. The prognosis values (overall survival [OS] and recurrence-free survival [RFS]) of ceRNA network genes were determined using The Cancer Genome Atlas (TCGA) data with Cox regression analysis and Kaplan–Meier method. Results: The present study screened 643 DELs, 83 DEMs, and 1,187 DEGs. PPI network analysis demonstrated that CDK1 and CCNE1 were hub genes and extracted in functionally related modules. E2F2, CDK1, and CCNE1 were significantly enriched into cell cycle pathway. FAM182B-miR-125b-5p-E2F2 and LINC00346-miR-10a-5p-CDK1/CCNE1 ceRNA axes were obtained by constructing the ceRNA network. Patients with high expressions of DELs and DEGs in the above ceRNA axes had poor OS, while patients with the high expression of DEMs possessed excellent OS. CDK1 was also an RFS-related biomarker, with its high expression predicting poor RFS. The upregulation of LINC00346 and CDK1 but the downregulation of miR-10a-5p in HCC was validated in other microarray datasets and TCGA database. Conclusion: The LINC00346-miR-10a-5p-CDK1 axis may be an important mechanism for HBV-related HCC, and genes in this ceRNA axis may be potential prognostic biomarkers and therapeutic targets. Keywords: hepatocellular carcinoma, hepatitis B virus, ceRNA, lncRNA, miRNA, prognosis, bioinformatics analysis, TCG
The construction and analysis of ceRNA networks in invasive breast cancer: a study based on The Cancer Genome Atlas
No full textChundi Gao,1,* Huayao Li,1,* Jing Zhuang,2,3 HongXiu Zhang,4 Kejia Wang,5 Jing Yang,2 Cun Liu,6 Lijuan Liu,2,3 Chao Zhou,2,3 Changgang Sun2,3 1College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250014, People’s Republic of China; 2Department of Oncology, Weifang Traditional Chinese Hospital, Weifang 261041, People’s Republic of China; 3Department of Oncology, Affiliated Hospital of Weifang Medical University, Weifang 261031, People’s Republic of China; 4Institute of Virology, Jinan Center for Disease Control and Prevention, Jinan 250021, People’s Republic of China; 5College of Basic Medicine, Qingdao University, Qingdao 266071, People’s Republic of China; 6College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250014, People’s Republic of China *These authors contributed equally to this work Background: Studies have shown that long noncoding RNAs (lncRNAs) make up the major proportion of the ceRNA network and can regulate gene expression by competitively binding to miRNAs. This reveals the existence of an RNA-miRNA regulatory pathway and is of great biological significance. CeRNAs, as competitive endogenous RNAs, have revealed a new mechanism of interaction between RNAs. Until now, the role of lncRNA-mediated ceRNAs in breast cancer and their regulatory mechanisms have been elucidated to some extent. Purpose: In this study, comprehensive analysis of large-scale invasive breast cancer samples in TCGA were conducted to further explore the developmental mechanism of invasive breast cancer and the potential predictive markers for invasive breast cancer prognosis in the ceRNA network. Methods: Abnormal expression profiles of invasive breast cancer associated mRNAs, lncRNAs and miRNAs were obtained from the TCGA database. Through further alignment and prediction of target genes, an abnormal lncRNA-miRNA-mRNA ceRNA network was constructed for invasive breast cancer. Through the overall survival analysis, Identification prognostic biomarkers for invasive breast cancer patients，In addition, we used Cytoscape plug-in BinGo for the different mRNA performance functional cluster analysis. Results: Differential analysis revealed that 1059 lncRNAs, 86 miRNAs, and 2138 mRNAs were significantly different in invasive breast cancer samples versus normal samples. Then we construct an abnormal lncRNA-miRNA-mRNA ceRNA network for invasive breast cancer, consisting of 90 DElncRNAs, 18 DEmiRNAs and 26 DEmRNAs.Further, 4 out of 90 lncRNAs, 3 out of 26 mRNAs, and 2 out of 18 miRNAs were useful as prognostic biomarkers for invasive breast cancer patients (P value < 0.05). It is worth noting that based on the ceRNA network, we found that the LINC00466-Hsa-mir-204- NTRK2 LINC00466-hsa-mir-204-NTRK2 axis was present in 9 RNAs associated with the prognosis of invasive breast cancer. Conclusion: This study provides an effective bioinformatics basis for further understanding of the molecular mechanism of invasive breast cancerand for predicting outcomes, which can guide the use of invasive breast cancerdrugs and subsequent related research. Keywords: invasive breast cancer, cancer genome atlas, lncRNA–miRNA–mRNA ceRNA network, bioinformatics, diagnosis and prognosis biomarker
The ceRNA regulation landscape across malignant tumors.
No full text(a) The number of ncRNA-related ceRNA interactions in each malignant tumor. (b) The topological characteristics of ncRNA-related ceRNA networks for the 31 malignant tumors. The Degree column is the p-value of fitting power-law distribution. The p-values equal to or more than 0.05 indicate that the degree of ncRNA-related ceRNA networks obeys the power-law distribution. The Path and Density columns represent the–log10(p-value) of Student’s t-test, and the p-values less than 0.05 display that the characteristic path lengths (or densities) of ncRNA-related ceRNA networks are significantly shorter (or higher) than those of their corresponding random networks. (c) The similarity matrix shows the similarity between each pair of lncRNA (upper triangle) and pseudogene (lower triangle) related ceRNA networks across 31 malignant tumors. (d) The radar chart shows the percentage of ceRNA regulations predicted in different numbers of malignant tumors. (e) The conserved ceRNA regulation predicted in 31 malignant tumors.</p
Integrated analysis of lncRNA-miRNA-mRNA ceRNA network in human aortic dissection
No full textAbstract Background Many studies on long chain non-coding RNAs (lncRNAs) are published in recent years. But the roles of lncRNAs in aortic dissection (AD) are still unclear and should be further examined. The present work focused on determining the molecular mechanisms underlying lncRNAs regulation in aortic dissection on the basis of the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network. Methods This study collected the lncRNAs (GSE52093), mRNAs (GSE52093) and miRNAs (GSE92427) expression data within human tissue samples with aortic dissection group and normal group based on Gene Expression Omnibus (GEO) database. Results This study identified three differentially expressed lncRNAs (DELs), 19 differentially expressed miRNAs (DEmiRs) and 1046 differentially expressed mRNAs (DEGs) identified regarding aortic dissection. Furthermore, we constructed a lncRNA-miRNA-mRNA network through three lncRNAs (including two with up-regulation and one with down-regulation), five miRNAs (five with up-regulation), as well as 211 mRNAs (including 103 with up-regulation and 108 with down-regulation). Simultaneously, we conducted functional enrichment and pathway analyses on genes within the as-constructed ceRNA network. According to our PPI/ceRNA network and functional enrichment analysis results, four critical genes were found (E2F2, IGF1R, BDNF and PPP2R1B). In addition, E2F2 level was possibly modulated via lncRNA FAM87A-hsa-miR-31-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. The expression of IGF1R may be regulated by lncRNA FAM87A-hsa-miR-16-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. Conclusion In conclusion, the ceRNA interaction axis we identified is a potentially critical target for treating AD. Our results shed more lights on the possible pathogenic mechanism in AD using a lncRNA-associated ceRNA network
Comparison of genes in ceRNA network in different TNM stages.
No full textThe number of asterisks represents the degree of difference (a)Differential expression of lncRNAs contained in the ceRNA network in low-risk samples and high-risk samples(b) Differential expression of miRNAs contained in the ceRNA network in low-risk samples and high-risk samples(c) Differential expression of mRNAs contained in the ceRNA network in low-risk samples and high-risk samples.</p
Out-of-Equilibrium ceRNA Crosstalk
No full textAmong non-coding RNAs, microRNAs are pivotal post-transcriptional regulators of gene expression in higher eukaryotes. Through a titration-based mechanism of interaction with their target RNAs, microRNAs can mediate a weak but pervasive form of RNA cross-regulation, as different endogenous RNAs can be effectively coupled by competing for microRNA binding (a phenomenon now known as “crosstalk”). Mathematical modeling has been proven of great help in unraveling many features of these competing endogenous RNA (ceRNA) interactions. However, although many studies have been devoted to the steady-state properties of this indirect regulatory layer, little is known about how the information encoded in frequency, amplitude, duration, and other features of regulatory signals can affect the resulting ceRNA crosstalk picture and hence the overall patterns of gene expression. Here, we focus on such dynamical aspects, with a special emphasis on the encoding and decoding of time-dependent signals
Identification of Pivotal ceRNA Networks Associated with Stanford-A Aortic Dissection via Integrated Bioinformatics Analysis
No full textYuyuan Hu,1,* Zhenhao Liu,2,* Yan Qin,3,* Nan Wu,4 Tao Yang,2 Xinmeng Cheng,5 Chunyan Wang,6 Xuening Wang2 1Department of Cardiac Surgery, the First Affiliated Hospital of Shandong Second Medical University, Weifang, 261000, People’s Republic of China; 2Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences Tongji Shanxi Hospital, Taiyuan, 030032, People’s Republic of China; 3Department of Science and Technology Education, Shanxi Center for Clinical Laboratory, Taiyuan, 030012, People’s Republic of China; 4Department of Cardiac Surgery, Shanxi Provincial People’s Hospital, Fifth Hospital of Shanxi Medical University, Taiyuan, 030012, People’s Republic of China; 5Department of Cardiovascular Surgery, the Affiliated Cardiovascular Hospital of Shanxi Medical University and Shanxi Cardiovascular Hospital (Institute), Taiyuan, Shanxi, 030000, People’s Republic of China; 6Department of Clinical Laboratory, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xuening Wang, Department of Cardiovascular Surgery, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, 99 Longcheng Road, Taiyuan, 030032, People’s Republic of China, Tel +86 15035118416, Email [email protected] Chunyan Wang, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, No. 3 Zhigongxin Street, Xinghualing, Taiyuan, Shanxi, People’s Republic of China, +86 15110313926, Email [email protected]: Stanford-A Aortic dissection (TAAD) is a rare and fatal disease, genetic factors remains poorly known. Study has confirmed that lncRNA play an important role in various physiological and pathological processes. This study attempts to elucidate the underlying molecular mechanisms of TAAD through lncRNA-associated competitive endogenous RNA (ceRNA) networks.Methods: In this study, aortic vascular of 5 TAAD and 5 control (ischemic heart disease) were subjected to lncRNA and mRNA microarray analysis, and differentially expressed mRNAs (DEGs) and differentially expressed lncRNAs (DELs) were identified. The differentially expressed miRNAs (DEmiR) were screened by GSE98770 dataset. The ceRNA network (lncRNA-miRNA-mRNA) was constructed by bioinformatics analysis. The accuracy of hub genes as biomarkers for predicting TAAD was evaluated by receiver operating characteristic (ROC) curve. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR).Results: This study revealed 161 DELs, 87 DEmiRs and 103 DEGs between TAAD and control. We constructed ceRNA networks based on the screened 1 lncRNA, 4 miRNAs and 7 mRNAs. We identified three lncRNA-miRNA-mRNA regulatory axes, namely the VCAN axis (LINC01355 - hsa-miR-186-5p / hsa-miR-30a-5p /hsa-miR-30c-5p - VCAN), LOX axis (LINC01355-hsa-miR-145-5p/hsa-miR-186-5p/ hsa-miR-30a-5p / hsa-miR-30c-5p - LOX), and CTSS axis (LINC01355 - hsa-miR-186-5p - CTSS) based on gene ontology, pathway enrichment and protein-protein interaction (PPI) network, which may play an important role in TAAD. The clinical performance of VCAN, CTSS, and LOX in TAAD diagnosis was evaluated, and the AUCs of VCAN, CTSS, and LOX were 0.920 (p< 0.001), 0.880 (p=0.002) and 0.840 (p=0.011), respectively. Furthermore, mRNA expression of VCAN in human aortic tissue significantly overexpressed in the TAAD patients (p< 0.001).Conclusion: This study identifies three ceRNA interaction axes, especially VCAN associated with TAAD pathogenesis, providing fundamentals of bioinformatics for understanding the molecular mechanisms of TAAD pathogenesis and developing potential therapeutic strategies for TAAD.Keywords: Stanford-A aortic dissection, lncRNA, ceRNA network, VCAN, bioinformatics analysi
Venn diagram and ceRNA network.
No full textA, Intersection of predicted miRNA and DEmiRNA; B, Intersection of predicted mRNA and DEmRNA; C, ceRNA network. The expression levels of these RNA molecules were indicated by different colors, with blue representing low expression and red representing high expression.</p
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