lncrna network analysis

miRNA-mRNA-lncRNA network analysis flow chart. eCollection 2021. lncRNA-mRNA co-expression analysis. Aging 6, 992–1009. LION outperformed the random network on all four cancers, and had higher or comparable performance than TPGLDA for all four. In addition, multiple pro-inflammatory cytokines are found in the plasma of such patients . ceRNA Network Analysis Shows That lncRNA CRNDE Promotes Progression of Glioblastoma Through Sponge mir-9-5p Xiaobin Luo 1† , Tianqi Tu 1† , Yali Zhong 2† , Shangyi Xu 1 , Xiangzhou Chen 1 , Ligang Chen 1,3,4,5* and Fubing Yang 1,3,4* Hum. We noted that the acute myeloid leukemia pathway and pathway in cancer were . The results of the Wilcox test confirm that LION’s better performance, seen in Figures 2, 3, arise from an improved ranking of disease-associated lncRNAs that are significantly different from either the TGPLDA rankings or from the randomized rankings. Tumour Biol. Therefore, there is an urgent need to identify early PDAC biomarkers and new therapeutic targets. For example, with myocardial infarction (MI), we created a subnetwork with (1) 1228 protein–protein interactions between the 27 known MI genes and their nearest neighbors, and (2) 2,175 lncRNA-protein interactions involving 1235 lncRNAs. CpG methylation analysis of the MEG3 and SNRPN imprinted genes in acute myeloid leukemia and myelodysplastic syndromes. Wang WJ, Li HT, Yu JP, Han XP, Xu ZP, Li YM, Jiao ZY, Liu HB. Cytogenet. Cancer specific lncRNA, cancer specific miRNA and cancer specific mRNA were identified. Using the same experimental LncRNADisease dataset, we also create ROC curves for both TPGLDA and the randomized network. Database 2016:baw057. doi: 10.1038/nrg2521, Mizrahi, A., Czerniak, A., Levy, T., Amiur, S., Gallula, J., Matouk, I., et al. Long Non-coding RNA: A Key Regulator in the Pathogenesis of Diabetic Cardiomyopathy. Predicting miRNA-disease association based on inductive matrix completion. LncRNADisease: a database for long-non-coding RNA-associated diseases. 3.5. Gynecol. eCollection 2021. The ceRNA network was constructed with 64 lncRNAs, 18 miRNAs, and 42 mRNAs. We identified biological roles of lncRNAs using the LncRNADisease database and experimental studies in the literature. Mol. Cancer Res. Mol. Tumour Biol. These conditions are required for the random walk probabilities to converge to a unique limiting probability distribution. 3:270. doi: 10.3389/fgene.2012.00270, Feng, W., Wang, C., Liang, C., Yang, H., Chen, D., Yu, X., et al. Here, we predicted the lncRNA-disease network without a priori lncRNA-disease information. To further investigate the mechanisms of these prognosis-related lncRNA modules, functional pathway enrichment analysis was performed using co-expressed genes of lncRNAs in each prognostic lncRNA module and a prognostic lncRNA module-pathway network was constructed . TPGLDA uses known lncRNA-disease associations and known gene-disease associations, and makes predictions using a resource allocation algorithm that creates interaction profiles at each lncRNA. 2020 Oct 31;20(1):529. doi: 10.1186/s12935-020-01619-8. Novel human lncRNA-disease association inference based on lncRNA expression profiles. For further validation, we conducted real-time quantitative reverse transcription (RT)-PCR using samples from DCM patients and a doxorubicin-induced rodent model of cardiomyopathy, revealing that miR-144-3p and miR-451a were down-regulated, and miR-21-5p was up-regulated. In melanoma, a 7-lncRNA prognostic signa-ture was established using comprehensive analysis of ceRNA network [19]. doi: 10.1016/j.ygyno.2014.03.556, Sattari, A., Siddiqui, H., Moshiri, F., Ngankeu, A., Nakamura, T., Kipps, T. J., et al. qRT-PCR analysis of miRNA…, MeSH Survival analysis of lncRNAs and mRNAs in the miRNA-lncRNA-mRNA network Among all of the lncRNAs and mRNAs in the miRNA-lncRNA-mRNA network, LINC00092 and chromosome 2 open reading frame 71 (C2orf71) were shown to be closely related to prognosis ( Fig. Identifying lncRNA-disease relationships via heterogeneous clustering. This contributed volume offers a comprehensive and detailed overview of the various aspects of long non-coding RNAs and discusses their emerging significance. Please enable it to take advantage of the complete set of features! Further analysis indicated that the hub subnetwork was highly related to cancer pathways, such as 'Focal adhesion' and 'Wnt signalling pathway'. The lncRNA‐miRNA and mRNA‐miRNA interactions from starBase v2.0 database were merged to construct the lncRNA‐miRNA‐mRNA network, in which lncRNA‐mRNA interactions were confirmed by hypergeometric test. 15, 184–194. A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma. Table 2. (2014). 5, 2845–2851. 35, 1052–1059. Taken together, these findings allowed us to construct the regulatory network of TF-lncRNA-miRNA-mRNA in PCa . Genet. (2018). doi: 10.1093/bib/bbv031, File, T. M. (2000). This detailed volume presents a comprehensive bioinformatic and experimental toolbox for prioritizing, annotating, and functionally analyzing long non-coding RNAs (lncRNAs). Since only a tiny portion of lncRNA-disease associations have been properly annotated, an increasing number of computational methods have been proposed for predicting potential lncRNA-disease associations. Long non-coding RNAs: insights into functions. Careers. Tables 2, 3 show the top five predictions for RTIs and COPD, respectively. Pharmacother. In order to explore the role of lncRNA in the ceRNA network, we conducted GO and KEGG analysis on the target mRNA of lncRNA, and then explored the function of lncRNA. Inferring novel lncRNA-disease associations based on a random walk model of a lncRNA functional similarity network. Science 316, 1484–1488. We assessed the relative performance of LION by computing and analyzing three ROC curves: (1) LION method, (2) a current state-of-the-art method called TPGLDA, (3) a randomized network model as a negative control. doi: 10.1093/hmg/ddv001, Shi, J. Y., Huang, H., Zhang, Y. N., Long, Y. X., and Yiu, S. M. (2017). 45, D833–D839. doi: 10.1186/1752-0509-8-S1-S6, Qiu, J. J., Lin, Y. Y., Ye, L. C., Ding, J. X., Feng, W. W., Jin, H. Y., et al. 2020 Aug;20(2):1176-1190. doi: 10.3892/etm.2020.8748. (2018). The lncRNA MIAT and the MIAT-based ceRNA network may be instrumental in regulating the immune response, especially of B cells, during the progression of periodontitis. This book may serve as a comprehensive resource for researchers, graduate students and oncologists in ncRNA and cancer research and help drug development by identifying ncRNA targets. Cytoscape (version 3.7.2) was later utilized to visualize the ceRNA network of lncRNA/miRNA/mRNA. The GAS5 (growth arrest-specific transcript 5) gene fuses to BCL6 as a result of t(1;3)(q25;q27) in a patient with B-cell lymphoma. 67, 5134–5140. These lncRNAs include DANCR, NEAT1, RMST, and KCNQ1OT1 (Ke et al., 2016; Sha et al., 2017; Feng et al., 2018; Wang et al., 2018). This practical book provides up-to-date information on the particular features of ovarian cancer in older women and the best management approach. The full range of relevant topics is covered. (2007). doi: 10.1038/nmeth.3215, Turnbull, C., Ahmed, S., Morrison, J., Pernet, D., Renwick, A., Maranian, M., et al. (2019). SNRPC promotes hepatocellular carcinoma cell motility by inducing epithelial-mesenchymal transition. KEGG showed that the potential mRNA targets of these 4 lncRNAs may be concentrated in the MAPK pathway. This book provides case studies of RNA binding proteins that regulate aspects of RNA processing that are important for fundamental understanding of diseases and development. 2019 Oct 25;25:7998-8010. doi: 10.12659/MSM.915798. The impact of each lncRNA may be determined by its ability to perform numerous tasks in the cell by interacting with proteins, DNA and RNA molecules. Sci. Using tissue samples from our own patients, we also verified certain analytical results using quantitative real-time PCR (qRT-PCR). DATA SHEET S1 | Pseudocode for LION algorithm. NEAT1 is required for survival of breast cancer cells through FUS and miR-548. doi: 10.1111/exd.12341, Kapranov, P., Cheng, J., Dike, S., Nix, D. A., Duttagupta, R., Willingham, A. T., et al. doi: 10.1093/bioinformatics/bty327, Lu, W., Zhu, L., Ruan, Z. Epub 2018 Sep 19. 41, 4976–4987. Differential expression analysis of lncRNA is conducted using R package edgeR 38. Syst. The eight lncRNAs were MALAT1, XIST, HOTAIR, MEG3, GAS5, H19, CDKN2B-AS1, and PVT1. Crit Rev Eukaryot Gene Expr. doi: 10.1016/j.cancergencyto.2008.01.013, Navlakha, S., and Kingsford, C. (2010). <i>Methods</i>. Construction of a Competitive Endogenous RNA Network in Uterine Corpus Endometrial Carcinoma. Clin. doi: 10.26355/eurrev_201811_16282, Ma, C., Shi, X., Zhu, Q., Li, Q., Liu, Y., Yao, Y., et al. Identifying lncRNA-disease associations not only contributes to the understanding of biological processes, but also provides new strategies for the diagnosis and prevention of diseases. In the ceRNA network, we identified a total of 50 lncRNA nodes, 18 miRNA nodes, 81 mRNA nodes, and 2484 edges as differentially expressed profiles. Sci. This volume assembles a broad spectrum of methods used in long non-coding RNAs (lncRNA) research, ranging from computational annotation of lncRNA genes to molecular and cellular analyses of the function of individual lncRNA. A qualitative evaluation of ovarian cancer revealed the top 20 predictions by LION contained all four experimentally validated lncRNAs: MALAT1, H19, HOTAIR, and PVT1. 2019 Dec;23(12):8410-8419. doi: 10.1111/jcmm.14721. Careers. 107, 824–833. doi: 10.1093/bib/bbw060, Chen, X., and Yan, G. Y. LncRNA loc285194 is a p53-regulated tumor suppressor. Despite its promise, the limitations that influence the prediction of LION include the literature biases in the protein-disease, lncRNA-proteins, and protein–protein interactions datasets. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. We would like to thank Marc Santolini for his help and discussion. 3.2 Construction and analysis of lncRNA‐miRNA‐mRNA ceRNA network. This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August ... This process was repeated for all of the 747 diseases for which a non-bipartite and connected subnetwork could be constructed. MS and EM performed the computational and statistical analyses. The purpose of this study was to investigate the lncRNA prognostic markers related to melanoma autophagy and predict the prognosis of patients with melanoma. Computational approaches have been developed to predict lncRNA-protein interactions, such as lncPro and RPI-Pred (Suresh et al., 2015; Shi et al., 2017; Xiao et al., 2017; Zheng et al., 2017). A total of 399 differentially expressed lncRNAs (DElncRNAs) have been identified between 497 NSCLC tissues and 54 normal tissues in the TCGA database, and 105 of which were correlated with acetylation regulators. Figure 1. Objective . 26, 155–165. To predict and rank disease associated lncRNAs, we first constructed a tripartite lncRNA-protein-disease network from the datasets described in section “Data Sources and Construction of Multi-Level Complex Network” (Figure 1). NPInter v3.0: an upgraded database of noncoding RNA-associated interactions. Methods: LION achieved an AUC value of 96.8% for cardiovascular diseases, 91.9% for cancer, and 90.2% for neurological diseases by using experimentally verified lncRNAs associated with diseases. EVLncRNAs: a manually curated database for long non-coding RNAs validated by low-throughput experiments. lncRInter: a database of experimentally validated long non-coding RNA interaction. doi: 10.1007/978-3-319-78680-3_3, Barsyte-Lovejoy, D., Lau, S. K., Boutros, P. C., Khosravi, F., Jurisica, I., Andrulis, I. L., et al. Bioinformatics 34, 3357–3364. 2018;49(5):1778-1791. doi: 10.1159/000493623. -. In this study, we developed a network distance analysis model for lncRNA-miRNA association prediction . Inhibition of PVT1 is linked to induction of an apoptotic response and proliferation inhibition of ovarian cancer cell lines [17908964]. 13, e1005912. doi: 10.1002/j.1460-2075.1986.tb04578.x, Grammatikakis, I., Panda, A. C., Abdelmohsen, K., and Gorospe, M. (2014). PPI network analysis and key gene identification. Framework to create the lncRNA-Disease-Network (LDN). We first constructed a tripartite network from 28,488 protein-disease associations compiled from OMIM and GWAS databases, 141,296 protein–protein interactions, and 3,998 lncRNA-protein interactions (Figure 1). Nat. RTIs, COPD, and myocardial infarctions all have HOTAIR in the top five predictions. Oncogene 36, 304–317. When compared against experimental lncRNA-disease associations, LION accurately predicted lncRNAs for both broad disease categories (cancers, cardiovascular diseases, and neurological/psychiatric diseases) and individual cancers (breast, blood, ovarian, and bladder), with AUCs all over 0.85. 18, 558–576. In this work, we propose LncRNA rankIng by NetwOrk DiffusioN (LION). 15, 806–814. To our knowledge, this approach is the first of its kind to make accurate predictions from protein interactome and lncRNA-protein data, without requiring known lncRNA-disease associations. We generated the random network by starting with the lncRNA-disease network predicted with LION, and randomly shuffling node labels to create a random graph null model with the same connectivity structure, enabling comparison with LION’s predictions as a control. The random walk method exploits the local network neighborhood of diseases to measure the proximity of lncRNAs to the disease genes based on the probabilities of the connecting edges. 2:71. doi: 10.3389/fbioe.2014.00071, Ariel, I., Sughayer, M., Fellig, Y., Pizov, G., Ayesh, S., Podeh, D., et al.