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1
Qi, Xin, Yuxin Lin, Jiajia Chen, and Bairong Shen. "Decoding competing endogenous RNA networks for cancer biomarker discovery." Briefings in Bioinformatics 21, no. 2 (January 30, 2019): 441–57. http://dx.doi.org/10.1093/bib/bbz006.
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Abstract Crosstalk between competing endogenous RNAs (ceRNAs) is mediated by shared microRNAs (miRNAs) and plays important roles both in normal physiology and tumorigenesis; thus, it is attractive for systems-level decoding of gene regulation. As ceRNA networks link the function of miRNAs with that of transcripts sharing the same miRNA response elements (MREs), e.g. pseudogenes, competing mRNAs, long non-coding RNAs, and circular RNAs, the perturbation of crucial interactions in ceRNA networks may contribute to carcinogenesis by affecting the balance of cellular regulatory system. Therefore, discovering biomarkers that indicate cancer initiation, development, and/or therapeutic responses via reconstructing and analyzing ceRNA networks is of clinical significance. In this review, the regulatory function of ceRNAs in cancer and crucial determinants of ceRNA crosstalk are firstly discussed to gain a global understanding of ceRNA-mediated carcinogenesis. Then, computational and experimental approaches for ceRNA network reconstruction and ceRNA validation, respectively, are described from a systems biology perspective. We focus on strategies for biomarker identification based on analyzing ceRNA networks and highlight the translational applications of ceRNA biomarkers for cancer management. This article will shed light on the significance of miRNA-mediated ceRNA interactions and provide important clues for discovering ceRNA network-based biomarker in cancer biology, thereby accelerating the pace of precision medicine and healthcare for cancer patients.
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Hsiao, Yi-Wen, Lin Wang, and Tzu-Pin Lu. "ceRNAR: An R package for identification and analysis of ceRNA-miRNA triplets." PLOS Computational Biology 18, no. 9 (September 9, 2022): e1010497. http://dx.doi.org/10.1371/journal.pcbi.1010497.
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Competitive endogenous RNA (ceRNA) represents a novel mechanism of gene regulation that controls several biological and pathological processes. Recently, an increasing number of in silico methods have been developed to accelerate the identification of such regulatory events. However, there is still a need for a tool supporting the hypothesis that ceRNA regulatory events only occur at specific miRNA expression levels. To this end, we present an R package, ceRNAR, which allows identification and analysis of ceRNA-miRNA triplets via integration of miRNA and RNA expression data. The ceRNAR package integrates three main steps: (i) identification of ceRNA pairs based on a rank-based correlation between pairs that considers the impact of miRNA and a running sum correlation statistic, (ii) sample clustering based on gene-gene correlation by circular binary segmentation, and (iii) peak merging to identify the most relevant sample patterns. In addition, ceRNAR also provides downstream analyses of identified ceRNA-miRNA triplets, including network analysis, functional annotation, survival analysis, external validation, and integration of different tools. The performance of our proposed approach was validated through simulation studies of different scenarios. Compared with several published tools, ceRNAR was able to identify true ceRNA triplets with high sensitivity, low false-positive rates, and acceptable running time. In real data applications, the ceRNAs common to two lung cancer datasets were identified in both datasets. The bridging miRNA for one of these, the ceRNA for MAP4K3, was identified by ceRNAR as hsa-let-7c-5p. Since similar cancer subtypes do share some biological patterns, these results demonstrated that our proposed algorithm was able to identify potential ceRNA targets in real patients. In summary, ceRNAR offers a novel algorithm and a comprehensive pipeline to identify and analyze ceRNA regulation. The package is implemented in R and is available on GitHub (https://github.com/ywhsiao/ceRNAR).
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Jayarathna, Dulari K., Miguel E. Rentería, Emilie Sauret, Jyotsna Batra, and Neha S. Gandhi. "Identifying Complex lncRNA/Pseudogene–miRNA–mRNA Crosstalk in Hormone-Dependent Cancers." Biology 10, no. 10 (October 9, 2021): 1014. http://dx.doi.org/10.3390/biology10101014.
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The discovery of microRNAs (miRNAs) has fundamentally transformed our understanding of gene regulation. The competing endogenous RNA (ceRNA) hypothesis postulates that messenger RNAs and other RNA transcripts, such as long non-coding RNAs and pseudogenes, can act as natural miRNA sponges. These RNAs influence each other’s expression levels by competing for the same pool of miRNAs through miRNA response elements on their target transcripts, thereby modulating gene expression and protein activity. In recent years, these ceRNA regulatory networks have gained considerable attention in cancer research. Several studies have identified cancer-specific ceRNA networks. Nevertheless, prior bioinformatic analyses have focused on long-non-coding RNA-associated ceRNA networks. Here, we identify an extended ceRNA network (including both long non-coding RNAs and pseudogenes) shared across a group of five hormone-dependent (HD) cancers, i.e., prostate, breast, colon, rectal, and endometrial cancers, using data from The Cancer Genome Atlas (TCGA). We performed a functional enrichment analysis for differentially expressed genes in the shared ceRNA network of HD cancers, followed by a survival analysis to determine their prognostic ability. We identified two long non-coding RNAs, nine genes, and seventy-four miRNAs in the shared ceRNA network across five HD cancers. Among them, two genes and forty-one miRNAs were associated with at least one HD cancer survival. This study is the first to investigate pseudogene-associated ceRNAs across a group of related cancers and highlights the value of this approach to understanding the shared molecular pathogenesis in a group of related diseases.
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Chen, Chen, Li Wang, Qiuju Feng, Qi Liu, Li Wang, and Shuming Huang. "Comprehensive Landscape of Modules-Dysregulated Functions Reveals a Profound Role of ceRNAs in Coronary Heart Disease." Journal of Healthcare Engineering 2022 (March 8, 2022): 1–10. http://dx.doi.org/10.1155/2022/4547413.
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Coronary heart disease (CHD) is one of the most common severe cardiovascular diseases. Competitive endogenous RNAs (ceRNA) play critical roles in complex diseases. However, our understanding of the dysregulated functions of ceRNAs in CHD remains limited. Here, we systematically analyzed the alterations of ceRNAs and identified the specific functions based on dysregulated modules from the ceRNA network. A total of 2457 significantly differential expressed genes and 212 differential expressed lncRNAs were identified. We got 76679 regulator relationship between different expression genes and miRNAs and 336 regulator relationship between differential expressed lncRNAs and miRNAs. We constructed the ceRNA network and selected five dysregulated modules. Furthermore, CHD specific functions based on dysregulated modules from the ceRNA network were identified, including histone acetylation, platelet degranulation, cAMP-dependent protein kinase complex, xenobiotic transport and so on. Our results will provide novel insight for a better understanding of the mechanism of ceRNAs and facilitate the identification of novel diagnostic and therapeutic biomarkers in CHD.
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Liang, Ying-Chun, Yu-Peng Wu, Dong-Ning Chen, Shao-Hao Chen, Xiao-Dong Li, Xiong-Lin Sun, Yong Wei, Xu Ning, and Xue-Yi Xue. "Building a Competing Endogenous RNA Network to Find Potential Long Non-Coding RNA Biomarkers for Pheochromocytoma." Cellular Physiology and Biochemistry 51, no. 6 (2018): 2916–24. http://dx.doi.org/10.1159/000496043.
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Background/Aims: Accumulating evidence has shown that long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks play crucial roles in tumor survival and patient prognosis; however, studies investigating ceRNA networks in pheochromocytoma (PCC) are lacking. In this study, we investigated the pathogenesis of PCC and whether lncRNAs acting through ceRNAs networks were associated with prognosis. Methods: A total of 183 PCC samples and 3 control samples from The Cancer Genome Atlas database were analyzed. The Empirical Analysis of Digital Gene Expression Data package in R (edgeR) was used to analyze differentially expressed RNAs. Biological processes and pathways functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. LncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.0 software based on the differentially expressed RNAs Survival package in R was used to perform survival analysis. Results: In total, 554 differentially expressed lncRNAs, 1775 mRNAs and 40 miRNAs were selected for further analysis. Subsequently, 23 lncRNAs, 22 mRNAs, and 6 miRNAs were included in the constructed ceRNA network. Meanwhile, two of the 23 lncRNAs (C9orf147 and BSN-AS2) were identified as independent predictors of overall survival in PCC patients (P< 0.05). Conclusion: This study improves the understanding of lncRNA-related ceRNA networks in PCC and suggests that the lncRNAs C9orf147 and BSN-AS2 could be independent prognostic biomarkers and potential therapeutic targets for PCC.
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Ye, Hongwei, Yuping Li, Lu Li, Yuhui Huang, Jiahui Wang, and Qin Gao. "Construction of a ceRNA network of regulated ferroptosis in doxorubicin-induced myocardial injury." PeerJ 11 (January 25, 2023): e14767. http://dx.doi.org/10.7717/peerj.14767.
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Background Ferroptosis and long-noncoding RNAs (lncRNAs) play crucial roles in doxorubicin (DOX)-induced myocardial injury (DIMI). Nevertheless, there is no research to construct competing endogenous RNAs (ceRNAs) network between lncRNAs and ferroptosis-related key gene. So our research was designed to screen ferroptosis-related genes from differentially expressed mRNAs in DIMI and construct lncRNAs regulated ferroptosis-related key gene ceRNAs network. Methods The male mice were injected with DOX intraperitoneally to induce myocardial injury, myocardial injury was evaluated by hematoxylin and eosin (HE) staining, and ferroptosis-related protein-glutathione peroxidase 4 (GPx4) protein expression was detected. The differentially expressed lncRNAs and mRNAs were detected by microarray, and the ferroptosis-related genes were screened to construct a protein-protein associations (PPA) network, the highest maximal clique centrality (MCC) score gene were identified by Cytoscape software, miRNAs bound to key genes and lncRNAs bound to miRNAs were predicted; then, the obtained lncRNAs were intersected with differentially expressed lncRNAs detected by microarray. Finally, the lncRNA/miRNA/mRNA ceRNA network of the highest MCC score gene regulating ferroptosis in DIMI was constructed. The expressions of the key components in ceRNA network were detected by qRT-PCR. Results Compared with the control group, in the DOX group, myocardial enzymes and HE staining showed that myocardium structure was changed, and GPx4 protein expression was decreased. The differentially expressed 10,265 lncRNAs and 6,610 mRNAs in the DOX group were detected via microarray. Among them, 114 ferroptosis-related genes were obtained to construct PPA networks, and Becn1 was identified as the key gene. Finally, the ceRNA network including Becn1, three miRNAs and four lncRNAs was constructed by predicting data of the Starbase database. The relative expressions of these components in ceRNA net were up-regulated and consistent with microarray results. Conclusions Based on the microarray detection results and bioinformatics analysis, we screened ferroptosis-related gene Becn1 and constructed the lncRNA/miRNA/mRNA ceRNA network of regulated ferroptosis in DIMI.
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Sheng, Han, Huan Pan, Ming Yao, Longsheng Xu, Jianju Lu, Beibei Liu, Jianfen Shen, and Hui Shen. "Integrated Analysis of Circular RNA-Associated ceRNA Network Reveals Potential circRNA Biomarkers in Human Breast Cancer." Computational and Mathematical Methods in Medicine 2021 (December 20, 2021): 1–16. http://dx.doi.org/10.1155/2021/1732176.
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Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA–miRNA pairs and 140 miRNA–mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA–mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.
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Wang, Chao, Kunkai Su, Hanchao Lin, Beini Cen, Shusen Zheng, and Xiao Xu. "Identification and Verification of a Novel MAGI2-AS3/miRNA-374-5p/FOXO1 Network Associated with HBV-Related HCC." Cells 11, no. 21 (November 2, 2022): 3466. http://dx.doi.org/10.3390/cells11213466.
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Background: Hepatocellular carcinoma (HCC) is a very common neoplasm worldwide, and competitive endogenous RNA (ceRNA) plays an important role in the development of HCC. The purpose of this study is to investigate the molecular mechanisms of ceRNAs in HCC. Methods: This study detects potential ceRNAs from HCC through whole genome analysis of lncRNA, miRNA and mRNA expression. We then performed high-throughput sequencing of tissues from five hepatitis B related HCC patients to screen ceRNAs and those screened ceRNAs expressions were verified on tissues from an independent group of six patients. Finally, the function of ceRNAs of interest was illustrated in vitro. Result: Functional and pathway analysis of The Cancer Genome Atlas revealed ceRNA networks. The high-throughput sequencing identified 985 upregulated and 1612 downregulated lncRNAs and 887 upregulated and 1116 downregulated mRNAs in HCC patients. Differentially expressed genes were parallel to cancer-associated processes, comprising 18 upregulated and 35 downregulated significantly enriched pathways including alcoholism and viral carcinogenesis. Among them, a potential ceRNA network was detected and verified in six HCC patients. CeRNAs of the lncRNA MAGI2-AS3/miR-374-5p/FOXO1 pathway were significantly dysregulated in HCC, and validation in vitro showed that FOXO1 is positively regulated by MAGI2-AS3 through the induction of miR-374a/b-5p in HCC cells. In addition, the overexpression of FOXO1 is associated with proliferation, migration, and invasion of HCC cells and increases apoptosis of HCC cells. MiR-374a/b-5p caused an opposite effect by directly suppressing FOXO1 in HCC cells. Conclusion: CeRNA networks were found in HCC and aberrantly expressed ceRNAs of lncRNA MAGI2-AS3/miR-374-5p/FOXO1 plays a crucial role in HCC, assisting in diagnosis and providing a method for treatment.
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An, Biao, Yuan Hu, and Xiao Liang. "Integrated Analysis of the lncRNA-Associated ceRNA Network in Wilms Tumor via TARGET and GEO Databases." Genetics Research 2022 (August 31, 2022): 1–12. http://dx.doi.org/10.1155/2022/2365991.
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Wilms tumor (WT) is the most common genitourinary renal tumor that typically occurs in children under 15 and is thought to be linked to somatic and germline mutations. However, the specific functional role of competing endogenous RNAs (ceRNAs) and their potential implications in WT remain unclear. In this study, we developed an lncRNA-mediated (long noncoding RNA-mediated) ceRNA network via the R packages for WT with expression data obtained from the tumor alterations relevant for genomics-driven therapy (TARGET) database. Unsupervised hierarchical clustering analysis revealed that the WT specimens could be clearly distinguished from healthy specimens with respect to the expression of disordered RNAs. A total of 1,607 differentially expressed (DE) lncRNAs, 116 DE microRNAs (DEmiRNAs), and 3,262 DE messenger RNAs (DEmRNAs) were identified as WT-specific RNAs, and a lncRNA-miRNA-mRNA ceRNA network with 159 DElncRNAs, 18 DEmiRNAs, 131 DEmRNAs, and 792 interactions was constructed. According to the clinical survival data, 12 DElncRNAs, 5 DEmRNAs, and 2 DEmiRNAs were selected from the ceRNA network that could significantly impact the overall survival of WT patients ( P < 0.05 ). Functional enrichment analysis showed that the biological processes and pathways of DEmRNAs, such as cell cycle and virus infection, may be associated with WT. The present study constructed a dysregulated lncRNA-mediated ceRNA network in WT and discovered that lncRNA-mediated ceRNAs may serve as important regulators in WT development and progression. Survival-associated RNAs may serve as new potential biomarkers, suggesting that the constructed ceRNA network in WT might be important for determining optimal therapeutic strategies.
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Ye, Junhong, Jifu Li, and Ping Zhao. "Roles of ncRNAs as ceRNAs in Gastric Cancer." Genes 12, no. 7 (July 2, 2021): 1036. http://dx.doi.org/10.3390/genes12071036.
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Although ignored in the past, with the recent deepening of research, significant progress has been made in the field of non-coding RNAs (ncRNAs). Accumulating evidence has revealed that microRNA (miRNA) response elements regulate RNA. Long ncRNAs, circular RNAs, pseudogenes, miRNAs, and messenger RNAs (mRNAs) form a competitive endogenous RNA (ceRNA) network that plays an essential role in cancer and cardiovascular, neurodegenerative, and autoimmune diseases. Gastric cancer (GC) is one of the most common cancers, with a high degree of malignancy. Considerable progress has been made in understanding the molecular mechanism and treatment of GC, but GC’s mortality rate is still high. Studies have shown a complex ceRNA crosstalk mechanism in GC. lncRNAs, circRNAs, and pseudogenes can interact with miRNAs to affect mRNA transcription. The study of the involvement of ceRNA in GC could improve our understanding of GC and lead to the identification of potential effective therapeutic targets. The research strategy for ceRNA is mainly to screen the different miRNAs, lncRNAs, circRNAs, pseudogenes, and mRNAs in each sample through microarray or sequencing technology, predict the ceRNA regulatory network, and, finally, conduct functional research on ceRNA. In this review, we briefly discuss the proposal and development of the ceRNA hypothesis and the biological function and principle of ceRNAs in GC, and briefly introduce the role of ncRNAs in the GC’s ceRNA network.
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Zhang, Senmiao, Yanling Li, Shuyu Xin, Li Yang, Mingjuan Jiang, Yujie Xin, Yiwei Wang, Jing Yang, and Jianhong Lu. "Insight into LncRNA- and CircRNA-Mediated CeRNAs: Regulatory Network and Implications in Nasopharyngeal Carcinoma—A Narrative Literature Review." Cancers 14, no. 19 (September 20, 2022): 4564. http://dx.doi.org/10.3390/cancers14194564.
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Nasopharyngeal carcinoma (NPC) is a kind of head-and-neck malignant tumor, and distant metastasis treatment resistance is the leading cause of patient death. In-depth understanding of NPC progression and treatment failure remains to be explored. Long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) are noncoding RNAs that play key regulatory role in shaping tumor cell activities. Recent studies have revealed that lncRNA and circRNA function as competitive endogenous RNAs (ceRNAs) by regulating the posttranscriptional expression of genes as miRNA baits. The imbalanced ceRNA networks derived from lncRNA/circRNA-miRNA-mRNA interaction are widely found to contribute to NPC development. Herein, we summarize typical examples of lncRNA/circRNA-associated ceRNAs in recent years, which involved the potential molecular mechanisms in the regulation of proliferation, apoptosis, treatment resistance and metastasis of NPC, and discuss their potential clinical significance in the prognosis and treatment of NPC. Interpreting the involvement of ceRNAs networks will provide new insight into the pathogenesis and treatment strategies of NPC. However, ceRNA regulatory mechanism has some limitations currently. Screening the most effective ceRNA targets and the clinical application of ceRNA still has many challenges.
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Cheng, Yang, Lanlan Geng, Kunyuan Wang, Jingjing Sun, Wanfu Xu, Sitang Gong, and Yun Zhu. "Long Noncoding RNA Expression Signatures of Colon Cancer Based on the ceRNA Network and Their Prognostic Value." Disease Markers 2019 (March 11, 2019): 1–13. http://dx.doi.org/10.1155/2019/7636757.
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Background. The specific functional roles of long noncoding RNAs (lncRNAs) as ceRNAs in colon cancer and their potential implications for colon cancer prognosis remain unclear. In the present study, a genome-wide analysis was performed to investigate the potential lncRNA-mediated ceRNA interplay in colon cancer based on the “ceRNA hypothesis.” The prognostic value of the lncRNAs was evaluated. Methods. A dysregulated lncRNA-associated ceRNA network was constructed based on the miRNA, lncRNA, and mRNA expression profiles in combination with the miRNA regulatory network by using an integrative computational method. Molecular biological techniques, including qPCR and gene knockdown techniques, were used to verify candidate targets in colon cancer. Survival analysis was performed to identify the candidate lncRNAs with prognostic value. Results. Our network analysis uncovered several novel lncRNAs as functional ceRNAs through crosstalk with miRNAs. The QRT-PCR assays of patient tissues as well as gene knockdown colon cancer cells confirmed the expression of top lncRNAs and their correlation with target genes in the ceRNA network. Functional enrichment analysis predicted that differentially expressed lncRNAs might participate in broad biological functions associated with tumor progression. Moreover, these lncRNAs may be involved in a range of cellular pathways, including the apoptosis, PI3K-AKT, and EGFR signaling pathways. The survival analysis showed that the expression level of several lncRNAs in the network was correlated with the prognosis of patients with colon cancer. Conclusions. This study uncovered a dysregulated lncRNA-associated ceRNA network in colon cancer. The function of the identified lncRNAs in colon cancer was preliminarily explored, and their potential prognostic value was evaluated. Our study demonstrated that lncRNAs could potentially serve as important regulators in the development and progression of colon cancer. Candidate prognostic lncRNA biomarkers in colon cancer were identified.
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Liu, Haiyang, Di Liu, Yexin Liu, Ming Xia, Yan Li, Mei Li, and Hong Liu. "Comprehensive analysis of circRNA expression profiles and circRNA-associated competing endogenous RNA networks in IgA nephropathy." PeerJ 8 (December 3, 2020): e10395. http://dx.doi.org/10.7717/peerj.10395.
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Background Immunoglobulin A nephropathy (IgAN) is immune-mediated primary glomerulonephritis, which is the most common reason leading to renal failure worldwide. The exact pathogenesis of IgAN is not well defined. Accumulating evidence indicates that circular RNAs (circRNAs) play crucial roles in the immune disease by involving in the competing endogenous RNA (ceRNA) network mechanism. At present, the studies of the circRNA profiles and circRNA-associated ceRNA networks in the IgAN are still scarce. This study aimed to elucidate the potential roles of circRNA-associated ceRNA networks of peripheral blood mononuclear cells (PBMCs) in IgAN patients Method CircRNA sequencing was used to identify the differential expressed circRNAs (DEcircRNAs) of PBMCs in IgAN and healthy controls; limma packages from data sets GSE25590 and GSE73953 in the Gene Expression Omnibus (GEO) database, were used to identify differentially expressed micro RNAs (miRNAs) and message RNAs (mRNAs). A circRNA-miRNA-mRNA ceRNA network was constructed to further investigate the mechanisms of IgAN. Then, GO analysis and KEGG enrichment analyses were used to annotate the genes involved in the circRNA-associated ceRNA network. Further, Protein-protein interaction (PPI) networks were established to screen potential hub genes, by using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Last, a quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify the hub genes in the ceRNA network. Result A total of 145 circRNAs, 22 miRNAs, and 1,117 mRNAs were differentially expressed in IgAN compared with controls (P < 0.05). A ceRNA network was constructed which contained 16 DEcircRNAs, 72 differential expressed mRNAs (DEmRNAs) and 11 differential expressed miRNAs (DEmiRNAs). KEGG pathway enrichment analysis illustrated the underlying biological functions of the ceRNA-associated genes, such as Nitrogen compound metabolic process, COPII-coated ER to Golgi transport vesicle, CAMP response element protein binding process (P < 0.01); meanwhile, Hepatitis B, GnRH signaling, and Prion disease were the most significant enrichment GO terms (P < 0.01). PPI network based on STRING analysis identified 4 potentially hub genes. Finally, Ankyrin repeat and SOCS box containing 16 (ASB16), SEC24 homolog C, COPII coat complex component (SEC24C) were confirmed by qRT-PCR (P < 0.05) and were identified as the hub genes of the ceRNA network in our study. Conclusion Our study identified a novel circRNA-mediated ceRNA regulatory network mechanisms in the pathogenesis of IgAN.
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Zhang, Jin, Fei Xiao, Guangliang Qiang, Zhenrong Zhang, Qianli Ma, Yang Hao, Huajie Xing, and Chaoyang Liang. "Novel lncRNA Panel as for Prognosis in Esophageal Squamous Cell Carcinoma Based on ceRNA Network Mechanism." Computational and Mathematical Methods in Medicine 2021 (September 24, 2021): 1–12. http://dx.doi.org/10.1155/2021/8020879.
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Background. The competitive endogenous RNA (ceRNA) mechanism has been discovered recently and regulating cancer-related gene expressions. The ceRNA network participates in multiple processes, such as cell proliferation and metastasis, and potentially drives the progression of cancer. In this study, we focus on the ceRNA networks of esophageal squamous cell carcinoma and discovered a novel biomarker panel for cancer prognosis. Methods. RNA expression data of esophageal carcinoma from the TCGA database were achieved and constructed ceRNA network in esophageal carcinoma using R packages. Results. Four miRNAs were discovered as the core of the ceRNA model, including miR-93, miR-191, miR-99b, and miR-3615. Moreover, we constructed a ceRNA network in esophageal carcinoma, which included 4 miRNAs and 6 lncRNAs. After ceRNA network modeling, we investigated six lncRNAs which could be taken together as a panel for prognosis prediction of esophageal cancer, including LINC02575, LINC01087, LINC01816, AL136162.1, AC012073.1, and AC117402.1. Finally, we tested the predictive power of the panel in all TCGA samples. Conclusions. Our study discovered a new biomarker panel which may have potential values in the prediction of prognosis of esophageal carcinoma.
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Li, Ziwen, Xueli An, Taotao Zhu, Tingwei Yan, Suowei Wu, Youhui Tian, Jinping Li, and Xiangyuan Wan. "Discovering and Constructing ceRNA-miRNA-Target Gene Regulatory Networks during Anther Development in Maize." International Journal of Molecular Sciences 20, no. 14 (July 15, 2019): 3480. http://dx.doi.org/10.3390/ijms20143480.
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The “competing endogenous RNA (ceRNA) hypothesis” has recently been proposed for a new type of gene regulatory model in many organisms. Anther development is a crucial biological process in plant reproduction, and its gene regulatory network (GRN) has been gradually revealed during the past two decades. However, it is still unknown whether ceRNAs contribute to anther development and sexual reproduction in plants. We performed RNA and small RNA sequencing of anther tissues sampled at three developmental stages in two maize lines. A total of 28,233 stably transcribed loci, 61 known and 51 potentially novel microRNAs (miRNAs) were identified from the transcriptomes. Predicted ceRNAs and target genes were found to conserve in sequences of recognition sites where their corresponding miRNAs bound. We then reconstructed 79 ceRNA-miRNA-target gene regulatory networks consisting of 51 known miRNAs, 28 potentially novel miRNAs, 619 ceRNA-miRNA pairs, and 869 miRNA-target gene pairs. More than half of the regulation pairs showed significant negative correlations at transcriptional levels. Several well-studied miRNA-target gene pairs associated with plant flower development were located in some networks, including miR156-SPL, miR159-MYB, miR160-ARF, miR164-NAC, miR172-AP2, and miR319-TCP pairs. Six target genes in the networks were found to be orthologs of functionally confirmed genes participating in anther development in plants. Our results provide an insight that the ceRNA-miRNA-target gene regulatory networks likely contribute to anther development in maize. Further functional studies on a number of ceRNAs, miRNAs, and target genes will facilitate our deep understanding on mechanisms of anther development and sexual plants reproduction.
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Sen, Rituparno, Suman Ghosal, Shaoli Das, Subrata Balti, and Jayprokas Chakrabarti. "Competing Endogenous RNA: The Key to Posttranscriptional Regulation." Scientific World Journal 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/896206.
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Competing endogenous RNA, ceRNA, vie with messenger RNAs (mRNAs) for microRNAs (miRNAs) with shared miRNAs responses elements (MREs) and act as modulator of miRNA by influencing the available level of miRNA. It has recently been discovered that, apart from protein-coding ceRNAs, pseudogenes, long noncoding RNAs (lncRNAs), and circular RNAs act as miRNA “sponges” by sharing common MRE, inhibiting normal miRNA targeting activity on mRNA. These MRE sharing elements form the posttranscriptional ceRNA network to regulate mRNA expression. ceRNAs are widely implicated in many biological processes. Recent studies have identified ceRNAs associated with a number of diseases including cancer. This brief review focuses on the molecular mechanism of ceRNA as part of the complex post-transcriptional regulatory circuit in cell and the impact of ceRNAs in development and disease.
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Guo, Ya, Wei Kang Pan, Zhong Wei Wang, Wang Hui Su, Kun Xu, Hui Jia, and Jing Chen. "Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis." BioMed Research International 2021 (December 6, 2021): 1–42. http://dx.doi.org/10.1155/2021/4532438.
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Objectives. Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients. Methods and Results. Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis. Conclusions. We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.
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Wang, Chenxu, Chaofan Yang, Xinying Wang, Guanlun Zhou, Chao Chen, and Guorong Han. "ceRNA Network and Functional Enrichment Analysis of Preeclampsia by Weighted Gene Coexpression Network Analysis." Computational and Mathematical Methods in Medicine 2022 (January 7, 2022): 1–14. http://dx.doi.org/10.1155/2022/5052354.
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Background. Preeclampsia (PE) is a multisystemic syndrome which has short- and long-term risk to mothers and children and has pluralistic etiology. Objective. This study is aimed at constructing a competitive endogenous RNA (ceRNA) network for pathways most related to PE using a data mining strategy based on weighted gene coexpression network analysis (WGCNA). Methods. We focused on pathways involving hypoxia, angiogenesis, and epithelial mesenchymal transition according to the gene set variation analysis (GSVA) scores. The gene sets of these three pathways were enriched by gene set enrichment analysis (GSEA). WGCNA was used to study the underlying molecular mechanisms of the three pathways in the pathogenesis of PE by analyzing the relationship among pathways and genes. The soft threshold power (β) and topological overlap matrix allowed us to obtain 15 modules, among which the red module was chosen for the downstream analysis. We chose 10 hub genes that satisfied ∣ log 2 Fold Change ∣ > 2 and had a higher degree of connectivity within the module. These candidate genes were subsequently confirmed to have higher gene significance and module membership in the red module. Coexpression networks were established for the hub genes to unfold the connection between the genes in the red module and PE. Finally, ceRNA networks were constructed to further clarify the underlying molecular mechanism involved in the occurrence of PE. 56 circRNAs, 17 lncRNAs, and 20 miRNAs participated in the regulation of the hub genes. Coagulation factor II thrombin receptor (F2R) and lumican (LUM) were considered the most relevant genes, and ceRNA networks of them were constructed. Conclusion. The microarray data mining process based on bioinformatics methods constructed lncRNA and miRNA networks for ten hub genes that were closely related to PE and focused on ceRNAs of F2R and LUM finally. The results of our study may provide insight into the mechanisms underlying PE occurrence.
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Li, Yueqi, Wudi Wei, Sanqi An, Junjun Jiang, Jinhao He, Hong Zhang, Gang Wang, et al. "Identification and analysis of lncRNA, microRNA and mRNA expression profiles and construction of ceRNA network in Talaromyces marneffei-infected THP-1 macrophage." PeerJ 9 (January 13, 2021): e10529. http://dx.doi.org/10.7717/peerj.10529.
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Background Competitive endogenous RNA (ceRNA) reveals new mechanisms for interactions between RNAs, which have been considered to play a significant role in pathogen-host innate immune response. However, knowledge of ceRNA regulatory networks in Talaromyces marneffei (TM)-macrophages is still limited. Methods Next-generation sequencing technology (NGS) was used to obtain mRNA, miRNA and lncRNA expression profiles in TM-infected macrophages. The R package DESeq2 was used to identify differentially expressed lncRNA, miRNA and mRNA. The R package GOseq was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and the ceRNA network of lncRNA–miRNA–mRNA interaction was constructed in Cytoscape. Similarly, functional enrichment analysis on mRNA in the ceRNA network. Finally, two mRNAs and four lncRNAs in the ceRNA network were randomly selected to verify the expression using qRT-PCR. Results In total, 119 lncRNAs, 28 miRNAs and 208 mRNAs were identified as differentially expressed RNAs in TM-infected macrophages. The constructed ceRNA network contains 38 lncRNAs, 10 miRNAs and 45 mRNAs. GO and KEGG analysis of mRNA in the ceRNA network indicated that activated pathways in TM-infected macrophages were related to immunity, inflammation and metabolism. The quantitative validation of the expression of four randomly selected differentially expressed lncRNAs, AC006252.1, AC090197.1, IL6R-AS1, LINC02009 and two mRNAs, CSF1, NR4A3 showed that the expression levels were consistent with those in the RNA-sequencing. Conclusions The ceRNA network related to immunity, inflammation and metabolism plays an important role in TM-macrophage interaction. This study may provide effective and novel insights for further understanding the underlying mechanism of TM infection.
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Tan, Juan, Weimin Wang, Bin Song, Yingjian Song, and Zili Meng. "Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma." BioMed Research International 2020 (August 4, 2020): 1–12. http://dx.doi.org/10.1155/2020/2837906.
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Increasing evidence has shown competitive endogenous RNAs (ceRNAs) play key roles in numerous cancers. Nevertheless, the ceRNA network that can predict the prognosis of lung adenocarcinoma (LUAD) is still lacking. The aim of the present study was to identify the prognostic value of key ceRNAs in lung tumorigenesis. Differentially expressed (DE) RNAs were identified between LUAD and adjacent normal samples by limma package in R using The Cancer Genome Atlas database (TCGA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function enrichment analysis was performed using the clusterProfiler package in R. Subsequently, the LUAD ceRNA network was established in three steps based on ceRNA hypothesis. Hub RNAs were identified using degree analysis methods based on Cytoscape plugin cytoHubba. Multivariate Cox regression analysis was implemented to calculate the risk score using the candidate ceRNAs and overall survival information. The survival differences between the high-risk and low-risk ceRNA groups were determined by the Kaplan-Meier and log-rank test using survival and survminer package in R. A total of 2,989 mRNAs, 185 lncRNAs, and 153 miRNAs were identified. GO and KEGG pathway function enrichment analysis showed that DE mRNAs were mainly associated with “sister chromatid segregation,” “regulation of angiogenesis,” “cell adhesion molecules (CAMs),” “cell cycle,” and “ECM-receptor interaction.” LUAD-related ceRNA network was constructed, which comprised of 54 nodes and 78 edges. Top ten hub RNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-340-5p, hsa-miR-377-3p, hsa-miR-21-5p, hsa-miR-326, SNHG1, RALGPS2, and PITX2) were identified according to their degree. Kaplan-Meier survival analyses demonstrated that hsa-miR-21-5p and RALGPS2 had a significant prognostic value. Finally, we found that a high risk of three novel ceRNA interactions (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) was positively associated with worse prognosis. Three novel ceRNAs (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) might be potential biomarkers for the prognosis and treatment of LUAD.
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Zhang, Zhiyuan, Wenwei Qian, Sen Wang, Dongjian Ji, Qingyuan Wang, Jie Li, Wen Peng, et al. "Analysis of lncRNA-Associated ceRNA Network Reveals Potential lncRNA Biomarkers in Human Colon Adenocarcinoma." Cellular Physiology and Biochemistry 49, no. 5 (2018): 1778–91. http://dx.doi.org/10.1159/000493623.
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Background/Aims: Long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) play significant roles in the development of tumors, but the functions of specific lncRNAs and lncRNA-related ceRNA networks have not been fully elucidated for colon adenocarcinoma (COAD). In this study, we aimed to clarify the lncRNA-microRNA (miRNA)-mRNA ceRNA network and potential lncRNA biomarkers in COAD. Methods: We extracted data from The Cancer Genome Atlas (TCGA) and identified COAD-specific mRNAs, miRNAs, and lncRNAs. The biological processes in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed for COAD-specific mRNAs. We then constructed a ceRNA network of COAD-specific mRNAs, miRNAs and lncRNAs and analyzed the correlation between expression patterns and clinical features of the lncRNAs involved. After identifying potential mRNA targets of 4 lncRNAs related to overall survival (OS), we conducted stepwise analysis of these targets through GO and KEGG. Using tissue samples from our own patients, we also verified certain analytical results using quantitative real-time PCR (qRT-PCR). Results: Data from 521 samples (480 tumor tissue and 41 adjacent non-tumor tissue samples) were extracted from TCGA. A total of 258 specific lncRNAs, 206 specific miRNAs, and 1467 specific mRNAs were identified (absolute log2 [fold change] > 2, false discovery rate < 0.01). Analysis of KEGG revealed that specific mRNAs were enriched in cancer-related pathways. The ceRNA network was constructed with 64 lncRNAs, 18 miRNAs, and 42 mRNAs. Among these lncRNAs involved in the network, 3 lncRNAs (LINC00355, HULC, and IGF2-AS) were confirmed to be associated with certain clinical features and 4 lncRNAs (HOTAIR, LINC00355, KCNQ1OT1, and TSSC1-IT1) were found to be negatively linked to OS (log-rank p < 0.05). KEGG showed that the potential mRNA targets of these 4 lncRNAs may be concentrated in the MAPK pathway. Certain results were validated by qRT-PCR. Conclusion: This study providing novel insights into the lncRNA-miRNA-mRNA ceRNA network and reveals potential lncRNA biomarkers in COAD.
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Dong, Yanru, Weibo Wen, Tiezheng Yuan, Lan Liu, and Xiangdan Li. "Novel Prognostic Biomarkers for Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) Patients via Analysis of Competing Endogenous RNA (ceRNA) Network." Disease Markers 2023 (February 8, 2023): 1–12. http://dx.doi.org/10.1155/2023/1766080.
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Background. Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is a common malignant gynecological cancer. The ceRNA networks play important roles in many tumors, while RILPL2-related ceRNA network has been seldom studied in CESC. Methods. All CESC data was obtained from TCGA database. Differentially expressed RNAs and predicted target RNAs were cross analyzed to construct ceRNA network. RNA and clinicopathological characteristics’ influence on overall survival (OS) were determined by univariate and multivariate Cox regression analyses. Lasso regression was used to construct the prediction model. Coexpression analysis was performed to explore the association of gene expression with CESC. This was followed by an experimental validation based on these results. Results. Between high and low RILPL2 expression CESC patients, totally 1227 DEmRNAs, 39 DEmiRNAs, and 1544 DElncRNAs were identified. After multiple cross analyses, 1 miRNA hsa-miR-1293, 20 mRNAs, and 43 lncRNAs were maintained to construct ceRNA network. CADM3-AS1, LINC00092, and ZNF667-AS1 in ceRNA network were significantly associated with the OS of CESC patients, and patients with low expression of these lncRNAs had worse prognosis. Significant lower expressions of these lncRNAs were also observed in CESC cell line compared with normal cell line. Conclusion. Low expressions of CADM3-AS1, LINC00092, and ZNF667-AS1 in ceRNA network were probably promising poor prognostic biomarkers for CESC patients. The genes show a prospective research area for CESC-targeted treatment in the future.
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Xu, Junhua, Min Wu, Yichen Sun, Hongqian Zhao, Yujie Wang, and Jie Gao. "Identifying Dysregulated lncRNA-Associated ceRNA Network Biomarkers in CML Based on Dynamical Network Biomarkers." BioMed Research International 2020 (February 18, 2020): 1–8. http://dx.doi.org/10.1155/2020/5189549.
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The incidence of chronic myeloid leukemia (CML) is increasing year by year, which is a serious threat to human health. Early diagnosis can reduce mortality and improve prognosis. LncRNAs have been shown to be effective biomarkers for a variety of diseases and can act as competitive endogenous RNA (ceRNA). In this study, the dysregulated lncRNA-associated ceRNA networks (DLCN) of the chronic phase (CP), accelerated phase (AP), and blastic crisis (BC) for CML are constructed. Then, based on dynamic network biomarkers (DNB), some dysregulated lncRNA-associated ceRNA network biomarkers of CP, AP, and BC for CML are identified according to DNB criteria. Thus, a lncRNA (SNHG5) is identified from DLCN_CP, a lncRNA (DLEU2) is identified from DLCN_AP, and two lncRNAs (SNHG3, SNHG5) are identified from DLCN_BC. In addition, the critical index (CI) used to detect disease outbreaks shows that CML occurs in CP, which is consistent with clinical medicine. By analyzing the functions of the identified ceRNA network biomarkers, it has been found that they are effective lncRNA biomarkers directly or indirectly related to CML. The result of this study will help deepen the understanding of CML pathology from the perspective of ceRNA and help discover the effective biomarkers of CP, AP, and BC for CML in the future, so as to help patients get timely treatment and reduce the mortality of CML.
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Liu, Yuehui, and Fan Ye. "Construction and integrated analysis of crosstalking ceRNAs networks in laryngeal squamous cell carcinoma." PeerJ 7 (July 22, 2019): e7380. http://dx.doi.org/10.7717/peerj.7380.
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Background 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. Material and Methods 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. Results 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. Conclusion 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.
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Fiscon, Giulia, Federica Conte, Lorenzo Farina, and Paola Paci. "Network-Based Approaches to Explore Complex Biological Systems towards Network Medicine." Genes 9, no. 9 (August 31, 2018): 437. http://dx.doi.org/10.3390/genes9090437.
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Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss the widespread DIAMOnD (disease module detection) algorithm. Starting from the assumption that PPI networks can be viewed as maps where diseases can be identified with localized perturbation within a specific neighborhood (i.e., disease modules), DIAMOnD performs a systematic analysis of the human PPI network to uncover new disease-associated genes by exploiting the connectivity significance instead of connection density. The past few years have witnessed the increasing interest in understanding the molecular mechanism of post-transcriptional regulation with a special emphasis on non-coding RNAs since they are emerging as key regulators of many cellular processes in both physiological and pathological states. Recent findings show that coding genes are not the only targets that microRNAs interact with. In fact, there is a pool of different RNAs—including long non-coding RNAs (lncRNAs) —competing with each other to attract microRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The framework of regulatory networks provides a powerful tool to gather new insights into ceRNA regulatory mechanisms. Here, we describe a data-driven model recently developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma. On the other hand, a very promising example of the co-expression network is the one implemented by the software SWIM (switch miner), which combines topological properties of correlation networks with gene expression data in order to identify a small pool of genes—called switch genes—critically associated with drastic changes in cell phenotype. Here, we describe SWIM tool along with its applications to cancer research and compare its predictions with DIAMOnD disease genes.
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Zhou, Dongkai, Bingqiang Gao, Qifan Yang, Yang Kong, and Weilin Wang. "Integrative Analysis of ceRNA Network Reveals Functional lncRNAs in Intrahepatic Cholangiocarcinoma." BioMed Research International 2019 (November 25, 2019): 1–9. http://dx.doi.org/10.1155/2019/2601271.
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Intrahepatic cholangiocarcinoma (ICC) is the second most common lethal liver cancer worldwide. Currently, despite the latest developments in genomics and transcriptomics for ICC in recent years, the molecular pathogenesis promoting ICC remains elusive, especially in regulatory mechanisms of long noncoding RNAs (lncRNAs), which acts as competing endogenous RNA (ceRNA). In order to elucidate the molecular mechanism of functional lncRNA, expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were obtained from The Cancer Genome Atlas (TCGA) database and an integrative analysis of the ICC-associated ceRNA network was performed. Moreover, gene oncology enrichment analyses for the genes in the ceRNA network were implemented and novel prognostic biomarker lncRNA molecules were identified. In total, 6,738 differentially expressed mRNAs (DEmRNAs), 2,768 lncRNAs (DElncRNAs), and 173 miRNAs (DEmiRNAs) were identified in tumor tissues and adjacent nontumor ICC tissues with the thresholds of adjusted P<0.01 and logFC>2. An ICC-specific ceRNA network was successfully constructed with 30 miRNAs, 16 lncRNAs, and 80 mRNAs. Gene oncology enrichment analyses revealed that they were associated with the adaptive immune response, T cell selection and positive regulation of GTPase activity categories. Among the ceRNA networks, DElncRNAs ARHGEF26-AS1 and MIAT were found to be hub genes in underexpressed and overexpressed networks, respectively. Notably, univariate Cox regression analysis indicated that DElncRNAs HULC significantly correlated with overall survival (OS) in ICC patients (P value < 0.05), and an additional survival analysis for HULC was reconfirmed in an independent ICC cohort from the Gene Expression Omnibus (GEO) database. These findings contribute to a more comprehensive understanding of the ICC-specific ceRNA network and provide novel strategies for subsequent functional studies of lncRNAs in ICC.
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Luo, Liang, Lei-Lei Zhang, Wen Tao, Tao-Lin Xia, and Liao-Yuan Li. "Prediction of potential prognostic biomarkers in metastatic prostate cancer based on a circular RNA-mediated competing endogenous RNA regulatory network." PLOS ONE 16, no. 12 (December 3, 2021): e0260983. http://dx.doi.org/10.1371/journal.pone.0260983.
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Recently, studies on competing endogenous RNA (ceRNA) networks have become prevalent, and circular RNAs (circRNAs) have crucial implications for the development and progression of carcinoma. However, studies relevant to metastatic prostate cancer (mPCa) are scant. This study aims to discover potential ceRNAs that may be related to the prognosis of mPCa. RNA-Seq data were obtained from the MiOncoCirc database and Gene Expression Omnibus (GEO). Differential expression patterns of RNAs were examined using R packages. Circular RNA Interactome, miRTarBase, miRDB and TargetScan were applied to predict the corresponding relation between circRNAs, miRNAs and mRNAs. The Gene Ontology (GO) annotations were performed to present related GO terms, and Gene Set Enrichment Analysis (GSEA) tools were applied for pathway annotations. Moreover, survival analysis was conducted for the hub genes. We found 820 circRNAs, 81 miRNAs and 179 mRNAs that were distinguishingly expressed between primary prostate cancer (PCa) and mPCa samples. A ceRNA network including 45 circRNAs, 24 miRNAs and 56 mRNAs was constructed. In addition, the protein–protein interaction (PPI) network was built, and 10 hub genes were selected by using the CytoHubba application. Among the 10 hub genes, survival analysis showed that ITGA1, LMOD1, MYH11, MYLK, SORBS1 and TGFBR3 were significantly connected with disease-free survival (DFS). The circRNA-mediated ceRNA network provides potential prognostic biomarkers for metastatic prostate cancer.
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Wang, Yuanyong, Tong Lu, Yang Wo, Xiao Sun, Shicheng Li, Shuncheng Miao, Yanting Dong, Xiaoliang Leng, and Wenjie Jiao. "Identification of a putative competitive endogenous RNA network for lung adenocarcinoma using TCGA datasets." PeerJ 7 (April 23, 2019): e6809. http://dx.doi.org/10.7717/peerj.6809.
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The mechanisms underlying the oncogenesis and progression of lung adenocarcinoma (LUAD) are currently unclear. The discovery of competitive endogenous RNA (ceRNA) regulatory networks has provided a new direction for the treatment and prognosis of patients with LUAD. However, the mechanism of action of ceRNA in LUAD remains elusive. In the present study, differentially expressed mRNAs, microRNAs (miRs) and long non-coding RNAs from the cancer genome atlas database were screened. CeRNAs for LUAD were then identified using online prediction software. Among the ceRNAs identified, family with sequence similarity 83 member A (FAM83A), miR-34c-5p, KCNQ1OT1 and FLJ26245 were observed to be significantly associated with the overall survival of patients with LUAD. Of note, FAM83A has potential significance in drug resistance, and may present a candidate biomarker for the prognosis and treatment of patients with LUAD.
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Bo, Hao, Zhizhong Liu, Fang Zhu, Dai Zhou, Yueqiu Tan, Wenbing Zhu, and Liqing Fan. "Long noncoding RNAs expression profile and long noncoding RNA-mediated competing endogenous RNA network in nonobstructive azoospermia patients." Epigenomics 12, no. 8 (April 2020): 673–84. http://dx.doi.org/10.2217/epi-2020-0008.
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Aim: To analyze the expression profile and competing endogenous RNA (ceRNA) network of long noncoding RNAs (lncRNAs) in nonobstructive azoospermia (NOA). Materials & methods: The lncRNA expression profile in NOA was determined by microarray reanalysis. Differential expression analysis was performed by R software. The ceRNA network was constructed using correlation analysis and gene target miRNA prediction. Metascape was used for enrichment analysis. Again ceRNA network was validated by quantitative real-time PCR. Results: Many lncRNAs are differently expressed in NOA. LncRNAs might participate in spermatogenesis through ceRNA mechanism. The ceRNA network included male gamete generation and other pathways. LINC00467 in the network regulated the expression of LRGUK and TDRD6. Conclusion: LncRNAs are involved in NOA and potential biomarkers and therapeutic targets for NOA.
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Liu, Xiu-Juan, Hong-Lin Yin, Yan Li, Hao Hao, Yang Liu, and Quan-Lin Zhao. "The Construction and Analysis of a ceRNA Network Related to Salt-Sensitivity Hypertensives." BioMed Research International 2022 (October 14, 2022): 1–14. http://dx.doi.org/10.1155/2022/8258351.
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Background. Salt-sensitivity hypertensives (SSH) are an independent risk factor for cardiovascular disease. However, the mechanism of SSH is not clear. This study is aimed at constructing a competing endogenous RNA (ceRNA) network related to SSH. Methods. Data sets were collected from the Gene Expression Omnibus database (GEO) to extract data on salt sensitivity RNA of patients with or without hypertensives in GSE135111. Firstly, we analyzed differentially expressed genes (DEGs, log 2 FC ≥ 0.5 and P < 0.05 ) and differentially expressed lncRNAs (DELs, log2FC ≥1 and P<0.05) between SSH and salt-sensitive normotension (SSN). Then, the gene ontology (GO), KEGG pathway enrichment analysis, and PPI network construction of DEGs were performed, and the hub genes in the PPI network by cytoHubba (12 methods) were screened out. Finally, a ceRNA network was constructed based on lncRNA-miRNA-mRNA pairs and hub genes. Results. 163 DEGs and 65 DELs were screened out. The GO and KEGG pathway analyses of DEGs were mainly enriched in metabolism (e.g., insulin secretion and cellular response to glucagon stimulus and peptidyl-tyrosine dephosphorylation,) and plasma membrane signaling (e.g., cell adhesion and chemical synaptic transmission and integral component of membrane). Additionally, a ceRNA network, including 1 mRNA (EGLN3), 2 miRNAs (hsa-miR-17-5p and hsa-miR-20b-5p), and 1 lncRNA (C1orf143) was successfully constructed. Conclusions. In conclusion, the proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the pathogenesis of SSH. Importantly, candidate lncRNAs, miRNAs, and mRNAs can be further evaluated as a potential therapeutic targets for SSH.
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Luo, Zhiwen, and Xinyu Bi. "Effect of an lncRNA-associated ceRNA regulatory network in MVI-positive hepatocellular carcinoma on their sensitivity to sorafenib." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e16615-e16615. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e16615.
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e16615 Background: Microvascular invasion (MVI) is a histological feature of hepatocellular carcinoma (HCC) related to aggressiveness. But different sensitivity to first line targeted drug, sorafenib, in MVI+ HCC has been observed. Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; so lncRNAs are considered as a major part of competitive endogenous RNA (ceRNA) network and have attracted growing attention. We explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in MVI+ HCC, and ceRNA network’s potential impact on prognosis and sensitivity to sorafenib in MVI+ HCC patient. Methods: We studied the expression profiles, prognostic value of lncRNA, miRNA, and mRNA from MVI+ HCC patients, established a prognosis-related network of dysregulated ceRNAs and analyzed its role in sensitivity to sorafenib and radiomics features by bioinformatics methods. Results: A ceRNA network including 13 lncRNAs, 3 miRNAs, and 2 mRNAs specific to MVI+ HCC was established. 6 lncRNAs ( ARHGEF7-AS1, ATP2B2-IT1, LINC00330, MUC2, TLR8-AS1 and ZNF385D-AS1), 2 miRNAs ( hsa-mir-206 and hsa-mir-373) and two mRNAs ( PAX3, SIK1) were prognostic biomarkers for MVI+ HCC. PAX3 was an unfavorable prognostic gene (HR = 1.9, 95%CI 1.01 ~ 3.60), while SIK1 favored the prognosis (HR = 0.4, 95%CI 0.19 ~ 0.85). PAX3 as a stratification in recurrence predicting model was used to identify MVI+ HCC with high or low recurrence risk. Datamining into the dataset of phase 3 STORM trial showed no difference in the influence of PAX3 level on the outcome between sorafenib HCC group and placebo HCC group. However, deep datamining into GDSC dataset revealed our high PAX3 group in MVI+ HCC related to resistance to sorafenib ( P = 0.0039). Radiomics features were extracted from CT of MVI+ HCC, and texture analysis in MVI+ HCCs is ongoing. Conclusions: The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the pathogenesis of MVI in HCC. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network have shown to be potential therapeutic targets and prognostic biomarkers for MVI+ HCC. PAX3 might play a vital role in the mechanism of sorafenib resistance in MVI+ HCC, exclusively, this aggressive HCC subtype. The ongoing experiments on radiomics might add potent supports to identify sorafenib sensitive MVI+ HCC.
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Kim, Nam Hee, Sang Hyun Song, Yun Hee Choi, Kyu Ho Hwang, Jun Seop Yun, Hyeeun Song, So Young Cha, et al. "Competing Endogenous RNA of Snail and Zeb1 UTR in Therapeutic Resistance of Colorectal Cancer." International Journal of Molecular Sciences 22, no. 17 (September 3, 2021): 9589. http://dx.doi.org/10.3390/ijms22179589.
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The epithelial-mesenchymal transition (EMT) comprises an important biological mechanism not only for cancer progression but also in the therapeutic resistance of cancer cells. While the importance of the protein abundance of EMT-inducers, such as Snail (SNAI1) and Zeb1 (ZEB1), during EMT progression is clear, the reciprocal interactions between the untranslated regions (UTRs) of EMT-inducers via a competing endogenous RNA (ceRNA) network have received little attention. In this study, we found a synchronized transcript abundance of Snail and Zeb1 mediated by a non-coding RNA network in colorectal cancer (CRC). Importantly, the trans-regulatory ceRNA network in the UTRs of EMT inducers is mediated by competition between tumor suppressive miRNA-34 (miR-34) and miRNA-200 (miR-200). Furthermore, the ceRNA network consisting of the UTRs of EMT inducers and tumor suppressive miRs is functional in the EMT phenotype and therapeutic resistance of colon cancer. In The Cancer Genome Atlas (TCGA) samples, we also found genome-wide ceRNA gene sets regulated by miR-34a and miR-200 in colorectal cancer. These results indicate that the ceRNA networks regulated by the reciprocal interaction between EMT gene UTRs and tumor suppressive miRs are functional in CRC progression and therapeutic resistance.
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Chen, Lixian, Zhonglu Ren, and Yongming Cai. "Construction and Analysis of Survival-Associated Competing Endogenous RNA Network in Lung Adenocarcinoma." BioMed Research International 2021 (February 11, 2021): 1–17. http://dx.doi.org/10.1155/2021/4093426.
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Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.
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Li, Jianxin, Xin Wang, Yinchun Wang, and Qingqiang Yang. "H19 promotes the gastric carcinogenesis by sponging miR-29a-3p: evidence from lncRNA–miRNA–mRNA network analysis." Epigenomics 12, no. 12 (June 2020): 989–1002. http://dx.doi.org/10.2217/epi-2020-0114.
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Aim: To identify novel competing endogenous RNA (ceRNA) network correlated with the prognosis of gastric cancer (GC) patients. Materials & methods: We systematically analyzed the aberrantly expressed genes in human GC to construct a ceRNA network by using multiple bioinformatic tools. Results: Aberrantly expressed mRNAs in GC were identified. By means of stepwise reverse prediction and validation from mRNA to lncRNA, a ceRNA network comprised of H19, miR-29a-3p, COL3A1, COL5A2, COL1A2 and COL4A1 was constructed, and all genes in the network are significantly correlated with the prognosis of GC patients. Conclusion: The present study successfully constructed a GC related ceRNA network, and provided potential targets for GC clinical treatment.
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Ari Yuka, Selcen, and Alper Yilmaz. "Effect of SARS-CoV-2 infection on host competing endogenous RNA and miRNA network." PeerJ 9 (October 20, 2021): e12370. http://dx.doi.org/10.7717/peerj.12370.
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Competing endogenous RNAs (ceRNA) play a crucial role in cell functions. Computational methods that provide large-scale analysis of the interactions between miRNAs and their competitive targets can contribute to the understanding of ceRNA regulations and critical regulatory functions. Recent reports showed that viral RNAs can compete with host RNAs against host miRNAs. Regarding SARS-CoV-2 RNA, no comprehensive study had been reported about its competition with cellular ceRNAs. In this study, for the first time, we used the ceRNAnetsim package to assess ceRNA network effects per individual cell and competitive behavior of SARS-CoV-2 RNA in the infected cells using single-cell sequencing data. Our computations identified 195 genes and 29 miRNAs which vary in competitive behavior specifically in presence of SARS-CoV-2 RNA. We also investigated 18 genes that are affected by genes that lost perturbation ability in presence of SARS-CoV-2 RNA in the human miRNA:ceRNA network. These transcripts have associations with COVID-19-related symptoms as well as many dysfunctions such as metabolic diseases, carcinomas, heart failure. Our results showed that the effects of the SARS-CoV-2 genome on host ceRNA interactions and consequent dysfunctions can be explained by competition among various miRNA targets. Our perturbation ability perspective has the potential to reveal yet to be discovered SARS-CoV-2 induced effects invisible to conventional approaches.
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Xu, Jingxi, and Jiangtao Li. "Construction of a three commitment points for S phase entry cell cycle model and immune-related ceRNA network to explore novel therapeutic options for psoriasis." Mathematical Biosciences and Engineering 19, no. 12 (2022): 13483–525. http://dx.doi.org/10.3934/mbe.2022630.
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<abstract> <p>While competing endogenous RNAs (ceRNAs) play pivotal roles in various diseases, the proliferation and differentiation of keratinocytes are becoming a research focus in psoriasis. Therefore, the three commitment points for S phase entry (CP1–3) cell cycle model has pointed to a new research direction in these areas. However, it is unclear what role ceRNA regulatory mechanisms play in the interaction between keratinocytes and the immune system in psoriasis. In addition, the ceRNA network-based screening of potential therapeutic agents for psoriasis has not been explored. Therefore, we used multiple bioinformatics approaches to construct a ceRNA network for psoriasis, identified CTGF as the hub gene, and constructed a ceRNA subnetwork, after which validation datasets authenticated the results' accuracy. Subsequently, we used multiple online databases and the single-sample gene-set enrichment analysis algorithm, including the CP1–3 cell cycle model, to explore the mechanisms accounting for the increased proliferation and differentiation of keratinocytes and the possible roles of the ceRNA subnetwork in psoriasis. Next, we performed cell cycle and cell trajectory analyses based on a single-cell RNA-seq dataset of psoriatic skin biopsies. We also used weighted gene co-expression network analysis and single-gene batch correlation analysis-based gene set enrichment analysis to explore the functions of CTGF. Finally, we used the Connectivity Map to identify MS-275 (entinostat) as a novel treatment for psoriasis, SwissTargetPrediction to predict drug targets, and molecular docking to investigate the minimum binding energy and binding sites of the drug to target proteins.</p> </abstract>
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Mao, Jia, Yufei Zhou, Licheng Lu, Ping Zhang, Runhua Ren, Yaqiong Wang, and Jing Wang. "Identifying a Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease." Cardiology Research and Practice 2021 (June 23, 2021): 1–10. http://dx.doi.org/10.1155/2021/6682183.
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Background. Accumulating evidence supports the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, exosomal-associated competing endogenous RNA- (ceRNA-) mediated regulatory mechanisms in CHD are largely unexplored. The present study aimed to explore exosomal-associated ceRNA networks in CHD. Methods. Data from 6 CHD patients and 32 normal controls were downloaded from the ExoRBase database. CHD and normal controls were compared by screening differentially expressed mRNAs (DEMs), lncRNAs (DELs), and circRNAs (DECs) in serum exosomes. MicroRNAs (miRNAs) targeting DEMs were predicted using the Targetscan and miRanda databases, and miRNAs targeted by DELs and DECs were predicted using the miRcode and starBase databases, respectively. The biological functions and related signaling pathways of DEMs were analyzed using the David and KOBAS databases. Subsequently, a protein-protein interaction (PPI) network was established to screen out on which hub genes enrichment analyses should be performed, and a ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD. Results. A total of 312 DEMs, 43 DELs, and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA,” “telomere organization,” and “negative regulation of gene expression, epigenetic.” PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which ubiquitin C (UBC) was the most important. Hub genes were mainly enriched in “cellular protein metabolic process” functions. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 73 predicted miRNAs, 10 DELs, and 15 DECs. The LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC and RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions. Our findings provide a novel perspective on the potential role of exosomal-associated ceRNA network regulation of the pathogenesis of CHD.
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Han, Xueqiong, Jianxun Lu, Chun Chen, Yongran Deng, Mingmei Pan, Qigeng Li, Huayun Wu, Zhenlong Li, and Bingqiang Ni. "Seven Hub Genes Predict the Prognosis of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network." Journal of Oncology 2022 (October 12, 2022): 1–14. http://dx.doi.org/10.1155/2022/3379330.
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Purpose. This study was aimed at identifying hub genes and ceRNA regulatory networks linked to prognosis in hepatocellular carcinoma (HCC) and to identify possible therapeutic targets. Methods. Differential expression analyses were performed to detect the differentially expressed genes (DEGs) in the four datasets (GSE76427, GSE6764, GSE62232, and TCGA). The intersected DEmRNAs were identified to explore biological significance by enrichment analysis. We built a competitive endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA. The mRNAs of the ceRNA network were used to perform Cox and Kaplan-Meier analyses to obtain prognosis-related genes, followed by the selection of genes with an area under the curve >0.8 to generate the random survival forest model and obtain feature genes. Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes. Finally, the infiltration status of immune cells in the HCC samples was determined. Results. A total of 1923 intersected DEmRNAs were identified in four datasets and involved in cell cycle and carbon metabolism. ceRNA network was created using 10 lncRNAs, 67 miRNAs, and 1,923 mRNAs. LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2. Among them, TMEM106C, LARS, and KPNA2 had a poor prognosis. KPNA2 was considered a key gene base on LASSO and Cox analyses and involved in the ceRNA network. T helper 2 cells and T helper cells showed a higher degree of infiltration in HCC. Conclusion. The findings revealed seven hub genes implicated in HCC prognosis and immune infiltration. A corresponding ceRNA network may help reveal their potential regulatory mechanism.
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List, Markus, Azim Dehghani Amirabad, Dennis Kostka, and Marcel H. Schulz. "Large-scale inference of competing endogenous RNA networks with sparse partial correlation." Bioinformatics 35, no. 14 (July 2019): i596—i604. http://dx.doi.org/10.1093/bioinformatics/btz314.
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AbstractMotivationMicroRNAs (miRNAs) are important non-coding post-transcriptional regulators that are involved in many biological processes and human diseases. Individual miRNAs may regulate hundreds of genes, giving rise to a complex gene regulatory network in which transcripts carrying miRNA binding sites act as competing endogenous RNAs (ceRNAs). Several methods for the analysis of ceRNA interactions exist, but these do often not adjust for statistical confounders or address the problem that more than one miRNA interacts with a target transcript.ResultsWe present SPONGE, a method for the fast construction of ceRNA networks. SPONGE uses ’multiple sensitivity correlation’, a newly defined measure for which we can estimate a distribution under a null hypothesis. SPONGE can accurately quantify the contribution of multiple miRNAs to a ceRNA interaction with a probabilistic model that addresses previously neglected confounding factors and allows fast P-value calculation, thus outperforming existing approaches. We applied SPONGE to paired miRNA and gene expression data from The Cancer Genome Atlas for studying global effects of miRNA-mediated cross-talk. Our results highlight already established and novel protein-coding and non-coding ceRNAs which could serve as biomarkers in cancer.Availability and implementationSPONGE is available as an R/Bioconductor package (doi: 10.18129/B9.bioc.SPONGE).Supplementary informationSupplementary data are available at Bioinformatics online.
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Song, Yueqiang, Jia Li, Yiming Mao, and Xi Zhang. "ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation." Frontiers in Molecular Biosciences 9 (May 13, 2022). http://dx.doi.org/10.3389/fmolb.2022.865408.
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The competing endogenous RNA (ceRNA) network is a newly discovered post-transcriptional regulation that controls both physiological and pathological progresses. Increasing research studies have been pivoted on this theory to explore the function of novel non-coding RNAs, pseudogenes, circular RNAs, and messenger RNAs. Although there are several R packages or computational tools to analyze ceRNA networks, an urgent need for easy-to-use computational tools still remains to identify ceRNA regulation. Besides, the conventional tools were mainly devoted to investigating ceRNAs in malignancies instead of those in neurodegenerative diseases. To fill this gap, we developed ceRNAshiny, an interactive R/Shiny application, which integrates widely used computational methods and databases to provide and visualize the construction and analysis of the ceRNA network, including differential gene analysis and functional annotation. In addition, demo data in ceRNAshiny could provide ceRNA network analyses about neurodegenerative diseases such as Parkinson’s disease. Overall, ceRNAshiny is a user-friendly application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying ceRNA networks.
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Huang, Runzhi, Ziqi Liu, Tingli Tian, Dianwen Song, Penghui Yan, Huabin Yin, Peng Hu, et al. "The construction and analysis of tumor-infiltrating immune cells and ceRNA networks in metastatic adrenal cortical carcinoma." Bioscience Reports 40, no. 3 (March 2020). http://dx.doi.org/10.1042/bsr20200049.
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Abstract Purpose: To construct and analyze tumor-infiltrating immune cell and ceRNA (competitive endogenous RNA) networks in metastatic adrenal cortical carcinoma (ACC). Methods: A ceRNA network was established to identify the ceRNAs involved in metastasis of ACC based on 92 samples from TCGA, including 18 cases of metastasis and 74 cases of non-metastatic primary tumors. And the algorithm “cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)” was used to quantify the proportion of immune cells in ACC. In addition, predictive nomograms based on the types of important immune cells or ceRNAs were constructed to predict ACC prognosis. Moreover, we evaluated the relationships between metastatic ACC-specific immune cells and ceRNA networks to identify the potential immune gene characteristics. Results: Ten prognostic biomarkers were identified as key members of the ceRNA network and three tumor-infiltrating immune cells were identified by CIBERSORT algorithm. Some important co-expression patterns between immune cells and ceRNAs network indicate significant correlation between Macrophages M0 and hsa-miR-130b-3p (P < 0.001), Macrophages M0 and H2AFX (P = 0.003). Conclusions: The present study inferred that the metastasis-related ceRNAs of H2AFX, hsa-miR-130b-3p and Macrophages M0 might play important roles in ACC metastasis.
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Wang, Peng, Xin Li, Yue Gao, Qiuyan Guo, Shangwei Ning, Yunpeng Zhang, Shipeng Shang, et al. "LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation." Nucleic Acids Research, October 16, 2019. http://dx.doi.org/10.1093/nar/gkz887.
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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.
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Zhong, Yinming, Sicen Pan, Shunji Zhi, Yue Li, Zhiping Xiu, Changran Wei, and Jiesi Luo. "Construction and investigation of circRNA-associated ceRNA regulatory network in molecular subtypes of breast cancer." Current Computer-Aided Drug Design 18 (June 15, 2022). http://dx.doi.org/10.2174/1573409918666220615151614.
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Background: Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) that indirectly regulate gene expression and function by binding microRNAs (miRNAs). A growing body of evidence indicates that the ceRNA networks can be used as an effective method to investigate cancer; however, the construction and analysis of ceRNA networks, especially circRNA-miRNA-mRNA regulatory network, in different subtypes of breast cancer has not been previously performed. Methods: First, the expression profiles of circRNA, miRNA, and mRNA were downloaded from the GEO database, differentially expressed genes were obtained using GEO2R, and a ceRNA network, was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs, which was consisted of 10 circRNAs, 25 miRNAs and 39 mRNAs. Further studies of BC subtypes based on TCGA datasets were also performed to validate the effect of novel ceRNA network. Results and Discussion: Then, the related genes in the regulatory network were analyzed by GO functional annotation and KEGG pathway enrichment. The analysis showed that targeted genes were enriched in 97 GO terms and 25 KEGG pathways, respectively, involved in the molecular typing of breast cancer. Meanwhile, Kaplan-Meier analysis revealed that three key genes (MKI67, DEF8, and GFRA1) were significantly associated with BC tumor differentiation and prognosis. Conclusion: The current study provides a potential application of ceRNA network within BC subtypes, and may offer new targets for their diagnosis, therapy and prognosis.
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Wang, Jing, and Jie Li. "LncRNA MIR155HG functions as a ceRNA for inhibition of lung adenocarcinoma growth and prediction of prognosis." Archives of Medical Science, February 9, 2021. http://dx.doi.org/10.5114/aoms/131198.
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IntroductionLong non-coding RNAs (lncRNAs) functioning as competing endogenous RNAs (ceRNAs) play critical roles in tumour progression. However, prognosis-related ceRNA networks in lung adenocarcinoma (LUAD) have not been well characterised.Material and methodsLUAD datasets were downloaded from the TCGA database, and the patients were divided into metastasis and non-metastasis groups. The differential expression of lncRNAs (DELs), miRNAs (DEMs), and mRNAs (DEGs) was analysed using the Limma package. Next, interactions between miRNA, lncRNA, and mRNA were predicted by miRcode, miRTarBase, miRDB, and TargetScan. The ceRNA network was constructed based on these interactions using Cytoscape software. DEG enrichment analysis was performed by GO and KEGG. After the prognosis analysis, we further screened molecules and constructed the prognosis-related ceRNA network. Moreover, the interactions between lncRNA, miRNA, and mRNA were validated by biological experiments.Results854 DELs, 150 DEMs, and 2211 DEGs between metastasis and non-metastasis LUAD patients were identified. Functional enrichment analysis suggested that DEGs were closely related to key biological processes involved in LUAD progression. The prognosis-related ceRNA network included 1 miRNA, 2 lncRNAs, and 4 mRNAs. In this network, MIR155HG and ADAMTS9-AS2 can function as ceRNAs of miR-212 to regulate EPM2AIP1, LAX1, PRICKLE2, and CD226. Moreover, our study confirmed that MIR155HG inhibited the proliferation, migration, and invasion of LUAD cells by sponging miR-212-3p to regulate CD226.ConclusionsThis ceRNA network contributes to understanding the pathogenesis of LUAD. Furthermore, the molecules in the network are valuable predictive factors for LUAD prognosis as well as potential therapeutic biomarkers.
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Wen, Xiao, Lin Gao, Tuo Song, and Chaoqun Jiang. "CeNet Omnibus: an R/Shiny application to the construction and analysis of competing endogenous RNA network." BMC Bioinformatics 22, no. 1 (February 18, 2021). http://dx.doi.org/10.1186/s12859-021-04012-y.
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Abstract Background The competing endogenous RNA (ceRNA) regulation is a newly discovered post-transcriptional regulation mechanism and plays significant roles in physiological and pathological progress. CeRNA networks provide global views to help understand the regulation of ceRNAs. CeRNA networks have been widely used to detect survival biomarkers, select candidate regulators of disease genes, and predict long noncoding RNA functions. However, there is no software platform to provide overall functions from the construction to analysis of ceRNA networks. Results To fill this gap, we introduce CeNet Omnibus, an R/Shiny application, which provides a unified framework for the construction and analysis of ceRNA network. CeNet Omnibus enables users to select multiple measurements, such as Pearson correlation coefficient (PCC), mutual information (MI), and liquid association (LA), to identify ceRNA pairs and construct ceRNA networks. Furthermore, CeNet Omnibus provides a one-stop solution to analyze the topological properties of ceRNA networks, detect modules, and perform gene enrichment analysis and survival analysis. CeNet Omnibus intends to cover comprehensiveness, high efficiency, high expandability, and user customizability, and it also offers a web-based user-friendly interface to users to obtain the output intuitionally. Conclusion CeNet Omnibus is a comprehensive platform for the construction and analysis of ceRNA networks. It is highly customizable and outputs the results in intuitive and interactive. We expect that CeNet Omnibus will assist researchers to understand the property of ceRNA networks and associated biological phenomena. CeNet Omnibus is an R/Shiny application based on the Shiny framework developed by RStudio. The R package and detailed tutorial are available on our GitHub page with the URL https://github.com/GaoLabXDU/CeNetOmnibus.
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Han, Pihua, Haiming Yang, Xiang Li, Jie Wu, Peili Wang, Dapeng Liu, Guodong Xiao, Xin Sun, and Hong Ren. "Identification of a novel cancer stemness-associated ceRNA axis in lung adenocarcinoma via stemness indices analysis." Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics, 2020. http://dx.doi.org/10.3727/096504020x16037124605559.
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To identify a novel cancer stemness-related ceRNA regulatory axis in lung adenocarcinoma (LUAD) via weighted gene coexpression network analysis of a stemness index. The RNA sequencing expression profiles of 513 cancer samples and 60 normal samples were obtained from the TCGA database. Differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) were identified with R software. Functional enrichment analysis was conducted using DAVID 6.8. The ceRNA network was constructed via multiple bioinformatics analyses, and the correlations between possible ceRNAs and prognosis were analyzed using Kaplan-Meier plots. Then, WGCNA was applied to distinguish key genes related to the mRNA expression-based stemness index (mRNAsi) in LUAD. After combining the weighted gene coexpression and ceRNA networks, a novel ceRNA regulatory axis was identified, and its biological functions were explored in vitro and vivo. In total, 1,825 DElncRNAs, 291 DEmiRNAs, and 3,742 DEmRNAs were identified. Functional enrichment analysis revealed that the DEmRNAs might be associated with LUAD onset and progression. The ceRNA network was constructed with 14 lncRNAs, 10 miRNAs and 52 mRNAs. Kaplan-Meier analysis identified 2 DEmiRNAs, 5 DElncRNAs and 41 DEmRNAs with remarkable prognostic power. One gene (MFAP4) in the ceRNA network was found to be closely related to mRNAsi by using WGCNA. Functional investigation further confirmed that the C8orf34-as1/miR-671-5p/MFAP4 regulatory axis has important functions in LUAD cell migration and stemness. This study provides a deeper understanding of the lncRNA-miRNA-mRNA ceRNA network and, more importantly, reveals a novel ceRNA regulatory axis, which may provide new insights into novel molecular therapeutic targets for inhibiting LUAD stem characteristics.
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Zhang, Mengying, Xiyun Jin, Junyi Li, Yi Tian, Qi Wang, Xinhui Li, Juan Xu, Yongsheng Li, and Xia Li. "CeRNASeek: an R package for identification and analysis of ceRNA regulation." Briefings in Bioinformatics, May 4, 2020. http://dx.doi.org/10.1093/bib/bbaa048.
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Abstract Competitive endogenous RNA (ceRNA) represents a novel layer of gene regulation that controls both physiological and pathological processes. However, there is still lack of computational tools for quickly identifying ceRNA regulation. To address this problem, we presented an R-package, CeRNASeek, which allows identifying and analyzing ceRNA–ceRNA interactions by integration of multiple-omics data. CeRNASeek integrates six widely used computational methods to identify ceRNA–ceRNA interactions, including two global and four context-specific ceRNA regulation prediction methods. In addition, it provides several downstream analyses for predicted ceRNA–ceRNA pairs, including regulatory network analysis, functional annotation and survival analysis. With examples of cancer-related ceRNA prioritization and cancer subtyping, we demonstrate that CeRNASeek is a valuable tool for investigating the function of ceRNAs in complex diseases. In summary, CeRNASeek provides a comprehensive and efficient tool for identifying and analysis of ceRNA regulation. The package is available on the Comprehensive R Archive Network (CRAN) at https://CRAN.R-project.org/package=CeRNASeek.
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Zhu, Dandan, Sifan Wu, Yafang Li, Yu Zhang, Jierong Chen, Jianhong Ma, Lixue Cao, Zejian Lyu, and Tieying Hou. "Ferroptosis-related gene SLC1A5 is a novel prognostic biomarker and correlates with immune infiltrates in stomach adenocarcinoma." Cancer Cell International 22, no. 1 (March 19, 2022). http://dx.doi.org/10.1186/s12935-022-02544-8.
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Abstract Background Stomach adenocarcinoma (STAD) is associated with high morbidity and mortality rates. Ferroptosis is an iron-dependent form of cell death, which plays an important role in the development of many cancers. Tumor-associated competing endogenous RNAs (ceRNAs) regulate tumorigenesis and development. Our study aimed to construct ceRNA networks and explore the relationship between ferroptosis-related genes in the ceRNA network and immune infiltration in STAD. Methods Based on the interactions among long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs), a ceRNA network was constructed to illustrate the relationships among lncRNAs, miRNAs, and mRNAs. Subsequently, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) functional enrichment analyses were carried out to explore the functions and interactions of the differentially expressed (DE) mRNAs related to the ceRNA network. Differential expression and prognostic analysis of ferroptosis-related genes in the ceRNA network were performed using the R package “limma” and “survminer.” The correlation between ferroptosis-related genes and tumor-infiltrating immune cells was analyzed using Spearman correlation analysis and CIBERSORT. Quantitative real-time PCR (qRT-PCR) was used to validate the expression of ferroptosis-related genes in STAD cells lines. Results A ceRNA network consisting of 29 DElncRNAs, 31 DEmiRNAs, and 182 DEmRNAs was constructed. These DEmRNAs were significantly enriched in pathways related to the occurrence and development of STAD. The ferroptosis-related gene SLC1A5 was upregulated in STAD (P < 0.001) and was associated with better prognosis (P = 0.049). The CIBERSORT database and Spearman correlation analysis indicated that SLC1A5 was correlated with eight types of tumor-infiltrating immune cells and immune checkpoints, including PD-L1(CD-274) and PD-1(PDCD1). The SLC1A5 mRNA was found to be highly expressed in STAD cells lines. Conclusions Our study provides insights into the function of ceRNAs in STAD and identifies biomarkers for the development of therapies for STAD. The ferroptosis-related gene SLC1A5 in the ceRNA network was associated with both tumor-infiltrating immune cells and immune checkpoints in the tumor microenvironment, suggesting that SLC1A5 may be a novel prognostic marker and a potential target for STAD immunotherapy in the future.
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Xu, Xiaonan, Kaizhen Wang, Olga Vera, Akanksha Verma, Neel Jasani, Ilah Bok, Olivier Elemento, Dongliang Du, Xiaoqing Yu, and Florian A. Karreth. "Gain of chromosome 1q perturbs a competitive endogenous RNA network to promote melanoma metastasis." Cancer Research, July 14, 2022. http://dx.doi.org/10.1158/0008-5472.can-22-0283.
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Abstract Somatic copy number alterations (CNA) promote cancer, but the underlying driver genes may not be comprehensively identified if only the functions of the encoded proteins are considered. mRNAs can act as competitive endogenous RNAs (ceRNA) that sponge miRNAs to post-transcriptionally regulate gene expression in a protein coding-independent manner. We investigated the contribution of ceRNAs to the oncogenic effects of CNAs. Chromosome 1q gains promoted melanoma progression and metastasis at least in part through overexpression of three mRNAs with ceRNA activity: CEP170, NUCKS1, and ZC3H11A. These ceRNAs enhanced melanoma metastasis by sequestering tumor suppressor miRNAs. Orthogonal genetic assays with miRNA inhibitors and target site blockers, along with rescue experiments, demonstrated that miRNA sequestration is critical for the oncogenic effects of CEP170, NUCKS1, and ZC3H11A mRNAs. Furthermore, chromosome 1q ceRNA-mediated miRNA sequestration alleviated the repression of several pro-metastatic target genes. This regulatory RNA network was evident in other cancer types, suggesting chromosome 1q ceRNA deregulation as a common driver of cancer progression. Taken together, this work demonstrates that ceRNAs mediate the oncogenicity of somatic CNAs.
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Xue, Jia, Haoran Chen, Jinqi Lu, Haojun Zhang, Jie Geng, Peifeng He, and Xuechun Lu. "Identification of immunity-related lncRNAs and construction of a ceRNA network of potential prognostic biomarkers in acute myeloid leukemia." Frontiers in Genetics 14 (June 14, 2023). http://dx.doi.org/10.3389/fgene.2023.1203345.
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Objective: Using bioinformatics analyses, this study aimed to identify lncRNAs related to the immune status of acute myeloid leukemia (AML) patients and ascertain the potential impact in immunity-related competing endogenous RNA (ceRNA) networks on AML prognosis.Methods: AML-related RNA-seq FPKM data, AML-related miRNA expression microarray data, and gene sets associated with immunity-related pathways were, respectively, obtained from the TCGA, GEO, and ImmReg databases. An immunity-related ceRNA network was then constructed according to the predicted interactions between AML-related mRNAs, lncRNAs, and miRNAs. After performing LASSO and multivariate Cox regression analyses, lncRNAs in the ceRNA network were used to establish an AML prognostic model. According to mutual regulatory relationships and consistent trends of expression among candidate ceRNAs, two ceRNA subnetworks related to the AML prognostic model were determined. Finally, the correlation between the expression levels of mRNAs, lncRNAs, and miRNAs in each ceRNA subnetwork and immune cell infiltration (assessed by combining the ESTIMATE and CIBERSORT methods and ssGSEA) was analyzed.Results: A total of 424 immunity-related differentially expressed (IR-DE) mRNAs (IR-DEmRNAs), 191 IR-DElncRNAs, and 69 IR-DEmiRNAs were obtained, and a ceRNA network of 20 IR-DElncRNAs, 6 IR-DEmRNAs, and 3 IR-DEmiRNAs was established. Univariate Cox regression analysis was conducted on 20 IR-DElncRNAs, and 7 of these were identified to be significantly correlated with the overall survival (OS) time in AML patients. Then, two IR-DElncRNAs (MEG3 and HCP5) were screened as independent OS-related factors by LASSO and multivariable Cox regression analyses, and a prognostic model was constructed to evaluate the survival risk in AML patients. Survival analyses indicated that the OS of patients was often poor in the high-risk group. Additionally, from this model, two ceRNA regulatory pathways, namely, MEG3/miR-125a-5p/SEMA4C and HCP5/miR-125b-5p/IL6R, which were potentially involved in the immune regulation of AML prognosis were identified.Conclusion: lncRNAs HCP5 and MEG3 may act as key ceRNAs in the pathogenesis in AML by regulating immune cell representation as part of the regulatory lncRNA-miRNA-mRNA axes. The candidate mRNAs, lncRNAs, and miRNAs included in the ceRNA network identified here may serve as useful prognostic biomarkers and immunotherapeutic targets for AML.