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Abstract Background Juvenile spondyloarthropathies (JSpA) are defined as a heterogeneous group of diseases that start before the age of 16. The study aimed to identify key genes and pathways that are influenced by circRNAs and to screen potential therapeutic agents for JSpA. The study involved the analysis of circRNA expression profiles, identification of circRNA-miRNA-mRNA regulatory networks, and functional annotation of differentially expressed genes. The results of the study may have provided insights into the molecular mechanisms underlying JSpA and potential therapeutic targets for this disease. Methods In this study, sequencing data of circRNA, miRNA, and mRNA were obtained from the GEO datasets. The data were then analyzed to identify candidates for constructing a circRNA-miRNA-mRNA network based on circRNA-miRNA interactions and miRNA-mRNA interactions. Functional enrichments of genes were performed using the DAVID database. A PPI network was constructed using the STRING database and visualized using Cytoscape software. The MCODE plugin app was used to explore hub genes in the PPI network. The expression changes in immune cells were assessed using the online CIBERSORT algorithm to obtain the proportion of various types of immune cells. Finally, the Connectivity Map L1000 platform was used to identify potential agents for JSpA treatment. Overall, this study aimed to provide a comprehensive understanding of the molecular mechanisms underlying JSpA and to identify potential therapeutic agents for this disease. Results A total of 225 differentially expressed circRNAs (DEcircRNAs), 23 differentially expressed miRNAs (DEmiRNAs) and 1324 differentially expressed mRNAs (DEmRNAs) were identified. We integrated 5 overlapped circRNAs, 7 miRNAs and 299 target mRNAs into a circRNA–miRNA–mRNA network. We next identified 10 hub genes based on the PPI network. KEGG pathway analysis revealed that the DEGs were mainly associated with JAK-STAT signal pathway. We found that neutrophils accounted for the majority of all enriched cells. In addition, we discovered several chemicals as potential treatment options for JSpA. Conclusions Through this bioinformatics analysis, we suggest a regulatory role for circRNAs in the pathogenesis and treatment of JSpA from the view of a competitive endogenous RNA (ceRNA) network.

Abstract Background Retinoblastoma (RB) is the most common prevalent intraocular malignancy among infants and children, particularly in underdeveloped countries. With advancements in genomics and transcriptomics, noncoding RNAs have been increasingly utilized to investigate the molecular pathology of diverse diseases. Aims This study aims to establish the competing endogenous RNAs network associated with RB, analyse the function of mRNAs and lncRNAs, and finds the relevant regulatory network. Methods and Results This study establishes a network of competing endogenous RNAs by Spearman correlation analysis and prediction based on RB patients and healthy children. Enrichment analyzes based on Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes are conducted to analyze the potential biological functions of lncRNA and mRNA networks. Weighted gene co‐expression network analysis (WGCNA) is employed to identify gene cluster modules exhibiting the strongest correlation with RB. The results indicate a significant correlation between the lncRNA MIR17HG (R = .73, p = .02) and the RB phenotype. ceRNA networks reveal downstream miRNAs (hsa‐mir‐425‐5p and hsa‐mir455‐5p) and mRNAs (MDM2, IPO11, and ITGA1) associated with MIR17Hg. As an inhibitor of the p53 signaling pathway, MDM2 can suppress the development of RB. Conclusion In conclusion, lncRNAs play a role in RB, and the MIR17HG/hsa‐mir‐425‐5p/MDM2 pathway may contribute to RB development by inhibiting the p53 signaling pathway.

Background: Juvenile spondyloarthropathies (JSpA) are defined as a heterogeneous group of diseases that start before the age of 16. The study aimed to identify key genes and pathways that are influenced by circRNAs and to screen potential therapeutic agents for JSpA. The study involved the analysis of circRNA expression profiles, identification of circRNA-miRNA-mRNA regulatory networks, and functional annotation of differentially expressed genes. The results of the study may have provided insights into the molecular mechanisms underlying JSpA and potential therapeutic targets for this disease. Methods: In this study, sequencing data of circRNA, miRNA, and mRNA were obtained from the GEO datasets. The data were then analyzed to identify candidates for constructing a circRNA-miRNA-mRNA network based on circRNA-miRNA interactions and miRNA-mRNA interactions. Functional enrichments of genes were performed using the DAVID database. A PPI network was constructed using the STRING database and visualized using Cytoscape software. The MCODE plugin app was used to explore hub genes in the PPI network. The expression changes in immune cells were assessed using the online CIBERSORT algorithm to obtain the proportion of various types of immune cells. Finally, the Connectivity Map L1000 platform was used to identify potential agents for JSpA treatment. Overall, this study aimed to provide a comprehensive understanding of the molecular mechanisms underlying JSpA and to identify potential therapeutic agents for this disease. Results: A total of 225 differentially expressed circRNAs (DEcircRNAs), 23 differentially expressed miRNAs (DEmiRNAs) and 1324 differentially expressed mRNAs (DEmRNAs) were identified. We integrated 5 overlapped circRNAs, 7 miRNAs and 299 target mRNAs into a circRNA–miRNA–mRNA network. We next identified 10 hub genes based on the PPI network. KEGG pathway analysis revealed that the DEGs were mainly associated with JAK-STAT signal pathway. We found that neutrophils accounted for the majority of all enriched cells. In addition, we discovered several chemicals as potential treatment options for JSpA. Conclusions: Through this bioinformatics analysis, we suggest a regulatory role for circRNAs in the pathogenesis and treatment of JSpA from the view of a competitive endogenous RNA (ceRNA) network. [ABSTRACT FROM AUTHOR]

Objective: This study aims to investigate the regulatory effect of hypoxia on human periodontal ligament stem cells (PDLSCs) through RNA sequencing (RNA SEQ). Human PDLSCs were cultured in normoxia (20% O2) or hypoxia (2% O2). Material and Methods: Total RNA was extracted and sequenced. The expression profiles of circRNAs, lncRNAs, and miRNAs were determined, and the lncRNA/circRNA‐miRNA‐mRNA networks were analyzed. Results: In total, 15 miRNAs, 449 lncRNAs, and 53 circRNAs were differentially expressed. Among them, 21 circRNAs, 262 lncRNAs, 5 miRNAs, and 5 mRNAs were selected to construct competing endogenous RNA (ceRNA) networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out to explore potential related pathways and regulatory functions. Several ceRNA axes (lncRNA‐FTX/circRNA‐FAT1‐hsa‐miR‐4781‐3p‐SMAD5 and circRNA LPAR1‐hsa‐miR‐342‐3p‐ADAR) may provide a theoretical basis on the study of osteogenic differentiation of PDLSCs under hypoxia. Conclusion: This study revealed that the expression profiles of circRNAs, lncRNAs, and miRNAs had changed significantly in PDLSCs cultured in 2% O2; specific circRNAs/lncRNAs may play a competitive role in the differentiation of PDLSCs. [ABSTRACT FROM AUTHOR]

Background: Circular RNAs (circRNAs), as a kind of endogenous non-coding RNA, have been implicated in ischemic heart diseases and vascular diseases. Based on theirs high stability with a closed loop structure, circRNAs function as a sponge and bind specific miRNAs to exert inhibitory effects in heart and vasculature, thereby regulating their target gene and protein expression, via competitive endogenous RNA (ceRNA) mechanism. However, the exact roles and underlying mechanisms of circRNAs in hypertension and related cardiovascular diseases remain largely unknown.Methods and Results: High-throughput RNA sequencing (RNA-seq) was used to analyze the differentially expressed (DE) circRNAs in aortic vascular tissues of spontaneously hypertensive rats (SHR). Compared with the Wistar-Kyoto (WKY) rats, there were marked increases in the levels of systolic blood pressure, diastolic blood pressure and mean blood pressure in SHR under awake conditions via the tail-cuff methodology. Totally, compared with WKY rats, 485 DE circRNAs were found in aortic vascular tissues of SHR with 279 up-regulated circRNAs and 206 down-regulated circRNAs. Furthermore, circRNA-target microRNAs (miRNAs) and the target messenger RNAs (mRNAs) of miRNAs were predicted by the miRanda and Targetscan softwares, respectively. Additionally, real-time RT-PCR analysis verified that downregulation of rno_circRNA_0009197, and upregulation of rno_circRNA_0005818, rno_circRNA_0005304, rno_circRNA_0005506, and rno_circRNA_0009301 were observed in aorta of SHR when compared with that of WKY rats. Then, the potential ceRNA regulatory mechanism was constructed via integrating 5 validated circRNAs, 31 predicted miRNAs, and 266 target mRNAs. More importantly, three hub genes (NOTCH1, FOXO3, and STAT3) were recognized according to PPI network and three promising circRNA-miRNA-mRNA regulatory axes were found in hypertensive rat aorta, including rno_circRNA_0005818/miR-615/NOTCH1, rno_circRNA_0009197/ miR-509-5p/FOXO3, and rno_circRNA_0005818/miR-10b-5p/STAT3, respectively.Conclusions: Our results demonstrated for the first time that circRNAs are expressed aberrantly in aortic vascular tissues of hypertensive rats and may serve as a sponge linking with relevant miRNAs participating in pathogenesis of hypertension and related ischemic heart diseases via the circRNA-miRNA-mRNA ceRNAnetwork mechanism.

Abstract Background Numerous studies have highlighted that long non-coding RNAs (lncRNAs) can bind to microRNA (miRNA) sites as competing endogenous RNAs (ceRNAs), thereby affecting and regulating the expression of mRNAs and target genes. These lncRNA-associated ceRNAs have been theorized to play a significant role in cancer initiation and progression. However, the roles and functions of the lncRNA-miRNA-mRNA ceRNA network in squamous cell carcinoma of the tongue (SCCT) are still unclear. Methods The miRNA, mRNA and lncRNA expression profiles from 138 patients with SCCT were downloaded from The Cancer Genome Atlas database. We identified the differential expression of miRNAs, mRNAs, and lncRNAs using the limma package of R software. We used the clusterProfiler package for GO and KEGG pathway annotations. The survival package was used to estimate survival analysis according to the Kaplan-Meier curve. Finally, the GDCRNATools package was used to construct the lncRNA-miRNA-mRNA ceRNA network. Results In total, 1943 SCCT-specific mRNAs, 107 lncRNAs and 100 miRNAs were explored. Ten mRNAs (CSRP2, CKS2, ADGRG6, MB21D1, GMNN, RIPOR3, RAD51, PCLAF, ORC1, NAGS), 9 lncRNAs (LINC02560, HOXC13 − AS, FOXD2 − AS1, AC105277.1, AC099850.3, STARD4 − AS1, SLC16A1 − AS1, MIR503HG, MIR100HG) and 8 miRNAs (miR − 654, miR − 503, miR − 450a, miR − 379, miR − 369, miR − 190a, miR − 101, and let−7c) were found to be significantly associated with overall survival (log-rank p

Objective To analyze the prognosis-related differentially expressed long non-coding RNAs（lncRNAs） in the head and neck squamous cell carcinoma（HNSCC）tissues by using bioinformatics methods，to construct their com⁃ peting endogenous RNAs（ceRNA）networks, and to analyze their biological functions. Methods The differentially ex⁃ pressed lncRNAs in the HNSCC and control tissues were screened in the cancer genome atlas（TCGA）database by using P <0. 05 and |log2FC >1. 0 as the criteria. Kaplan-Meier Plotter survival analysis was performed to select the most diagnostic lncRNA which was unreported before and had diagnostic potential，the ceRNA network was constructed by using starBase online website，and gene ontology（GO）and Kyoto gene and genome encyclopedia（KEGG）were used to analyze their biological functions. Results One hundred and twenty-nine differentially expressed lncRNAs were screened out. HOXA11- AS was selected as a candidate lncRNA. HOXA11-AS interacted with 4 differentially expressed microRNAs（miRNAs）and 12 differentially expressed messenger RNAs（mRNAs). The biological functions were mainly enriched in the cellular response to endogenous stimuli, negative regulation of messenger ribonucleoprotein complexes and cytoplasmic translation；the signaling pathways involved were mainly reproduction-related pathways such as dorsoventral axis formation and progesterone-mediated oocyte maturation，fat metabolism-related pathways and cancer-related pathways. Conclusions We screen out the candidate lncRNA（HOXA11-AS) related to the prognosis of HNSCC，and construct a ceRNA regulatory network by taking HOXA11-AS as the center. HOXA11-AS is involved in biological functions such as cellular responses to endogenous stimuli，and the signaling pathways involved are mainly reproduction，lipid metabolism，and cancer-related pathways. [ABSTRACT FROM AUTHOR]

Abstract This study aimed to identify potential therapeutic targets in osteosarcoma (OS) through the network analysis of competing endogenous RNAs (ceRNAs). The differentially expressed miRNAs (DEMIs) and mRNAs (DEMs) were identified between OS cell lines and human mesenchymal stem cells (hMSCs) from the data deposited under GSE70415 using limma package. Functional analysis of DEMs was performed using DAVID and clusterProfiler to identify significantly enriched Gene Ontology biological processes and KEGG pathways, respectively. The DEMI-DEM interaction network was constructed using Cytoscape. LncRNA–miRNA interactions were predicted using starBase database. The ceRNA regulatory network was constructed by integrating mRNAs, miRNAs, and lncRNAs, and functional enrichment analysis was performed for the genes involved. The analysis revealed a total of 326 DEMs and 54 DEMIs between OS cells and hMSCs. We identified several novel therapeutic targets involved in the progression and metastasis of OS, such as CBX7, RAD9A, SNHG7 and miR-34a-5p. The miRNA, miR-543 (target gene: CBX7) was found to be associated with the pathway Mucin type O-glycan biosynthesis. Using the ceRNA network, we established the following regulatory interactions: NEAT1/miR-543/CBX7, SNHG7/miR-34a-5p/RAD9A, and XIST/miR-34a-5p/RAD9A. CBX7, RAD9A, lncRNA SNHG7, miR-543, and miR-34a-5p may be explored as novel therapeutic targets for treatment of OS.

Abstract Recent scientific evidence has suggested that long noncoding RNAs (lncRNAs) play an important part in tumorigenesis as an important member of competing endogenous RNAs (ceRNAs). Hundreds of RNA sequence data and relevant clinic information are freely accessible in The Cancer Genome Atlas (TCGA) datasets. However, the role of cancer‐related lncRNAs in papillary thyroid cancer (PTC) is not fully understood yet. In this study, we identified 461 RNA sequencing data from TCGA. Subsequently, 45 lncRNAs, 21 miRNAs, and 78 mRNAs were chosen to construct a ceRNA network of PTC. Then, we analyzed the correlation between these 45 PTC‐specific lncRNAs and clinic features and patient outcome. Thirty‐seven of these lncRNAs were found to be closely related to age, race, gender, lymph node metastasis, TNM staging system, and patient outcome. Additionally, three of them were linked to PTC patient overall survival. Eventually, we selected eight lncRNAs randomly and performed quantificational real‐time polymerase chain reaction (qRT‐PCR) in 28 newly diagnosed patients with PTC to verify the reliability of the above results. The results of qRT‐PCR are totally in agreement with the bioinformatics analysis. Additionally, it was found that HAND2‐AS1 was negatively related to tumor size (P

Background: Retinoblastoma (RB) is the most common prevalent intraocular malignancy among infants and children, particularly in underdeveloped countries. With advancements in genomics and transcriptomics, noncoding RNAs have been increasingly utilized to investigate the molecular pathology of diverse diseases., Aims: This study aims to establish the competing endogenous RNAs network associated with RB, analyse the function of mRNAs and lncRNAs, and finds the relevant regulatory network., Methods and Results: This study establishes a network of competing endogenous RNAs by Spearman correlation analysis and prediction based on RB patients and healthy children. Enrichment analyzes based on Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes are conducted to analyze the potential biological functions of lncRNA and mRNA networks. Weighted gene co-expression network analysis (WGCNA) is employed to identify gene cluster modules exhibiting the strongest correlation with RB. The results indicate a significant correlation between the lncRNA MIR17HG (R = .73, p = .02) and the RB phenotype. ceRNA networks reveal downstream miRNAs (hsa-mir-425-5p and hsa-mir455-5p) and mRNAs (MDM2, IPO11, and ITGA1) associated with MIR17Hg. As an inhibitor of the p53 signaling pathway, MDM2 can suppress the development of RB., Conclusion: In conclusion, lncRNAs play a role in RB, and the MIR17HG/hsa-mir-425-5p/MDM2 pathway may contribute to RB development by inhibiting the p53 signaling pathway., (© 2024 The Authors. Cancer Reports published by Wiley Periodicals LLC.)

A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients.

Recent scientific evidence has suggested that long noncoding RNAs (lncRNAs) play an important part in tumorigenesis as an important member of competing endogenous RNAs (ceRNAs). Hundreds of RNA sequence data and relevant clinic information are freely accessible in The Cancer Genome Atlas (TCGA) datasets. However, the role of cancer‐related lncRNAs in papillary thyroid cancer (PTC) is not fully understood yet. In this study, we identified 461 RNA sequencing data from TCGA. Subsequently, 45 lncRNAs, 21 miRNAs, and 78 mRNAs were chosen to construct a ceRNA network of PTC. Then, we analyzed the correlation between these 45 PTC‐specific lncRNAs and clinic features and patient outcome. Thirty‐seven of these lncRNAs were found to be closely related to age, race, gender, lymph node metastasis, TNM staging system, and patient outcome. Additionally, three of them were linked to PTC patient overall survival. Eventually, we selected eight lncRNAs randomly and performed quantificational real‐time polymerase chain reaction (qRT‐PCR) in 28 newly diagnosed patients with PTC to verify the reliability of the above results. The results of qRT‐PCR are totally in agreement with the bioinformatics analysis. Additionally, it was found that HAND2‐AS1 was negatively related to tumor size (P < 0.05). The results were consistent with the bioinformatics analysis in TCGA. Taken together, we identified the differentially expressed lncRNAs and constructed a PTC ceRNA network. The study provides a new perspective and supplement for our understanding of lncRNAs in PTC development and reveals potential diagnostic and prognostic markers in PTC. We collected and analyzed the RNA sequencing profiles of papillary thyroid cancer from The Cancer Genome Atlas. Then, we constructed the ceRNA to reveal the biomarkers in papillary thyroid cancer. [ABSTRACT FROM AUTHOR]

Background: Circular RNAs (circRNAs), as a kind of endogenous non-coding RNA, have been implicated in ischemic heart diseases and vascular diseases. Based on theirs high stability with a closed loop structure, circRNAs function as a sponge and bind specific miRNAs to exert inhibitory effects in heart and vasculature, thereby regulating their target gene and protein expression, via competitive endogenous RNA (ceRNA) mechanism. However, the exact roles and underlying mechanisms of circRNAs in hypertension and related cardiovascular diseases remain largely unknown. Methods and Results: High-throughput RNA sequencing (RNA-seq) was used to analyze the differentially expressed (DE) circRNAs in aortic vascular tissues of spontaneously hypertensive rats (SHR). Compared with the Wistar-Kyoto (WKY) rats, there were marked increases in the levels of systolic blood pressure, diastolic blood pressure and mean blood pressure in SHR under awake conditions via the tail-cuff methodology. Totally, compared with WKY rats, 485 DE circRNAs were found in aortic vascular tissues of SHR with 279 up-regulated circRNAs and 206 down-regulated circRNAs. Furthermore, circRNA-target microRNAs (miRNAs) and the target messenger RNAs (mRNAs) of miRNAs were predicted by the miRanda and Targetscan softwares, respectively. Additionally, real-time RT-PCR analysis verified that downregulation of rno&#95;circRNA&#95;0009197, and upregulation of rno&#95;circRNA&#95;0005818, rno&#95;circRNA&#95;0005304, rno&#95;circRNA&#95;0005506, and rno&#95;circRNA&#95;0009301 were observed in aorta of SHR when compared with that of WKY rats. Then, the potential ceRNA regulatory mechanism was constructed via integrating 5 validated circRNAs, 31 predicted miRNAs, and 266 target mRNAs. More importantly, three hub genes (NOTCH1, FOXO3, and STAT3) were recognized according to PPI network and three promising circRNA-miRNA-mRNA regulatory axes were found in hypertensive rat aorta, including rno&#95;circRNA&#95;0005818/miR-615/NOTCH1, rno&#95;circRNA&#95;0009197/ miR-509-5p/FOXO3, and rno&#95;circRNA&#95;0005818/miR-10b-5p/STAT3, respectively. Conclusions: Our results demonstrated for the first time that circRNAs are expressed aberrantly in aortic vascular tissues of hypertensive rats and may serve as a sponge linking with relevant miRNAs participating in pathogenesis of hypertension and related ischemic heart diseases via the circRNA-miRNA-mRNA ceRNAnetwork mechanism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Liu, Dong, Dong, Song, Zhang, Liang, Liu, Sun, Li, Zhang, Chen, Miao and Zhong.)

Simple Summary: The exact functions and molecular mechanism of lncRNAs, acting as competitive endogenous RNAs in a cutaneous squamous cell carcinoma, remain unexplored. The present study was conducted to identify the differentially expressed lncRNAs and mRNAs and establish the lncRNA-related competing endogenous RNA networks associated with a cutaneous squamous cell carcinoma. A competing endogenous RNA network consisting of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs was constructed. As for the functional analysis of the mRNAs in the network, a FoxO signaling pathway, an autophagy and cellular senescence were the top enrichment terms based on the Kyoto Encyclopedia of Genes and Genomes analysis. We identified five core mRNAs and built a core mRNA-associated competing endogenous RNA network. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 in the core mRNA-associated competing endogenous RNA network were validated with the same expression patterns. The core mRNAs and their associated lncRNAs may provide potential therapeutic targets for cutaneous squamous cell carcinomas. A cutaneous squamous cell carcinoma (cSCC) derived from keratinocytes is the second most common cause of non-melanoma skin cancer. The accumulation of the mutational burden of genes and cellular DNA damage caused by the risk factors (e.g., exposure to ultraviolet radiation) contribute to the aberrant proliferation of keratinocytes and the formation of a cSCC. A cSCC encompasses a spectrum of diseases that range from recursor actinic keratosis (AK) and squamous cell carcinoma (SCC) in situ (SCCIS) to invasive cSCCs and further metastatic SCCs. Emerging evidence has revealed that lncRNAs are involved in the biological process of a cSCC. According to the ceRNA regulatory theory, lncRNAs act as natural miRNA sponges and interact with miRNA response elements, thereby regulating the mRNA expression of their down-stream targets. This study was designed to search for the potential lncRNAs that may become potential therapeutic targets or biomarkers of a cSCC. Considering the spirit of the study to be adequately justified, we collected microarray-based datasets of 19 cSCC tissues and 12 normal skin samples from the GEO database (GSE42677 and GSE45164). After screening the differentially expressed genes via a limma package, we identified 24 differentially expressed lncRNAs (DElncRNAs) and 3221 differentially expressed mRNAs (DEmRNAs). The miRcode, miRTarBase, miRDB and TargetScan databases were used to predict miRNAs that could interact with DElncRNAs and DEmRNAs. A total of 137 miRNA-lncRNA and 221 miRNA-mRNA pairs were retained in the ceRNA network, consisting of 31 miRNAs, 11 DElncRNAs and 155 DEmRNAs. For the functional analysis, the top enriched biological process was enhancer sequence-specific DNA binding in Gene Ontology (GO) terms. The FoxO signaling pathway, autophagy and cellular senescence were the top enrichment terms based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The combination of a STRING tool and Cytoscape software (plug-in MCODE) identified five core mRNAs and built a core mRNA-associated ceRNA network. The expression for five identified core mRNAs and their related nine lncRNAs was validated using the external dataset GSE7553. Finally, one lncRNA HLA-F-AS1 and three mRNAs named AGO4, E2F1 and CCND1 were validated with the same expression patterns. We speculate that lncRNA HLA-F-AS1 may sponge miR-17-5p or miR-20b-5p to regulate the expression of CCND1 and E2F1 in the cSCC. The present study may provide potential diagnostic and therapeutic targets for cSCC patients. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the pivotal genes or lncRNAs involved in the progression of atrial fibrillation (AF) -valvular heart disease (VHD). The mRNA profiling GSE113013 was obtained from the Gene Expression Omnibus database. The identification of differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs) was performed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were carried out for DEGs. Then, the construction of the protein-protein interaction (PPI) network was conducted. An lncRNA-miRNA-target ceRNA network was constructed after obtaining microRNAs (miRNA) related to DElncRNAs. Ultimately, key disease-related genes were screened. A total of 399 DEGs and 145 DElncRNAs were obtained. There were 283 nodes and 588 interaction pairs in the PPI network, and synaptosome-associated protein 25 (SNAP25) had higher degrees (degree = 22) in the PPI network. There were 65 interaction pairs in the ceRNA network. Here, Baculoviral IAP Repeat Containing 5 (BIRC5) was regulated by hsa-miR-1285-3p, which was regulated by lncRNA NPHP3-AS1. Gap Junction Protein Alpha 5 (GAJ5) was regulated by hsa-miR-4505, hsa-miR-1972, and hsa-miR-1199-5p. In particular, GAJ5 was enriched in the function of ion transmembrane transport regulation, whereas BIRC5 was enriched in the function of apoptosis-multiple species pathway. Similarly, Potassium Inwardly Rectifying Channel Subfamily J Member 6 (KCNJ6) was enriched in the function of an ion channel complex. VENN analysis identified BIRC5 and GJA5 as key AF-related genes. KCNJ6, SNAP25, GJA5, BIRC5, hsa-miR-1285-3p, and lncRNA NPHP3-AS1 were likely to be associated with AF-VHD development.

The aim of our study is to construct the competing endogenous RNA (ceRNA) network of head and neck squamous cell carcinoma (HNSCC) and identify key long noncoding RNAs (lncRNAs) to predict prognosis. The genes whose expression were differentially in HNSCC and normal tissues were explored by the Cancer Genome Atlas database. The ceRNA network was constructed by the Cytoscape software. The lncRNAs which could estimate the overall survival were explored from Cox proportional hazards regression. There are 1997, 589, and 82 mRNAs, lncRNAs, and miRNAs whose expression were statistically significant different, respectively. Then, the network between miRNA and mRNA or miRNA and lncRNA was constructed by miRcode, miRDB, TargetScan, and miRanda. Five mRNAs, 10 lncRNAs, and 3 miRNAs were associated with overall survival. Then, 11-lncRNAs were found to be prognostic factors. Therefore, our research analyzed the potential signature of novel 11-lncRNA as candidate prognostic biomarker from the ceRNA network for patients with HNSCC., (© 2019 Wiley Periodicals, Inc.)

Background: Non-small cell lung cancer (NSCLC) is the most common cancer and the pathogenesis remain unclear. According to the competing endogenous RNA (ceRNA) theory, long noncoding RNA (lncRNA) have a competition with mRNAs for the connecting with miRNAs that affecting the level of mRNA. In this work, the ceRNA network and the important genes to predict the survival prognosis were explored., Methods: In the study, we recognized differently expressed genes (mRNAs, lncRNAs and miRNAs) between NSCLC and normal tissues from The Cancer Genome Atlas database (fold change >2, P<0.01) using edgeR. Then, the interaction between lncRNA and miRNA or mRNA and miRNA was explored by miRcode, miRDB, TargetScan, and miRanda. Furthermore, the functions and KEGG pathway were analyzed with DAVID and KOBAS. The connections of these mRNAs were explored by STRING online database. The relation between genes in the network and survival time were further explored by survival package in R., Results: By bioinformatics tools, we explored 155 lncRNAs, 30 miRNAs and 68 mRNAs and constructed ceRNA network. The functions and KEGG pathway of 68 mRNAs were further analyzed. AQP2, EGF, SLC12A1, TRPV5 and AVPR2 was in the center of network and may play key roles in the development of NSCLC. And mRNA (CCNB1, COL1A1, E2F7, EGLN3, FOXG1 and PFKP), miRNA (miR-31, miR-144 and miR-192) and lncRNA (AC080129.1, AC100791.1, AL163952.1, AP000525.1, AP003064.2, C2orf48, C10orf91, FGF12-AS2, HOTAIR, LINC00518, LNX1-AS1, MED4-AS1, MIG31HG, MUC2, TTTY16 and UCA1) were closely related with overall survival (OS)., Conclusions: In summary, the present study provides a deeper understanding of the lncRNA-related ceRNA network in NSCLC and some genes may be new target to treat for NSCLC patients., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare.