Construction of a lncRNA-associated competing endogenous RNA regulatory network after traumatic brain injury in mouse.

Traumatic brain injury (TBI) is a major public health problem worldwide which causes high mortality and disability. Functioning as microRNA (miRNA) sponges, long non-coding RNA (lncRNA) regulates the expression of protein-coding genes in a competing endogenous RNA (ceRNA) network. However, the lncRNA-associated ceRNA in TBI remains unclear. In this study, we processed the raw SRR files of mice cortex samples of sham injury (n = 3) and TBI groups (n = 3) to count files. Then, the expression profiles of lncRNAs and mRNAs were identified, and 86 differentially expressed (DE) lncRNAs and 1201 DEmRNAs between sham and TBI groups were identified. The DEmRNAs were used to perform enrichment analyses. Next, a lncRNA-miRNA-mRNA regulatory ceRNA network was constructed. The network consisted of 23 mRNAs, 5 miRNAs and 2 lncRNAs. The expression alternations of the 5 miRNAs were validated via qRT-PCR. The subnetwork of hub lncRNA Neat1 was extracted. We identified a potential inflammatory associated regulatory axis: Neat1/miR-31-5p/Myd88 axis. The PPI network based on DEmRNA involved in ceRNA network was constructed PPI networks to identify the hub genes. Finally, DElncRNAs and DEmRNAs were selected randomly and validated by qRT-PCR. In conclusion, with the lncRNA-miRNA-mRNA ceRNA network provided above, we can improve our understanding of the regulatory mechanisms and interaction among lncRNAs, miRNAs and mRNAs in TBI process.

Wang S ，Sun Y ，Hu S ，Lou C ，Pan YB ... -  《Molecular Brain》

Analysis of the lncRNA-miRNA-mRNA network to explore the regulation mechanism in human traumatic brain injury.

Traumatic brain injury (TBI) refers to brain dysfunction with or without traumatic structural injury induced by an external force. Nevertheless, the molecular mechanism of TBI remains undefined. Differentially expressed (DE) lncRNAs, DEmRNAs and DEmiRNAs were selected between human TBI tissues and the adjacent histologically normal tissue by high-throughput sequencing. Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis of overlapping DEmRNAs between predicted mRNAs of DEmiRNAs and DEmRNAs. The competitive endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA was established in light of the ceRNA theory. In the ceRNA network, the key lncRNAs were screened out. Then key lncRNAs related ceRNA subnetwork was constructed. After that, qRT-PCR was applied to validate the expression levels of hub genes. 114 DElncRNAs, 1807 DEmRNAs and 6 DEmiRNAs were DE in TBI. The TBI-related ceRNA network was built with 73 lncRNA nodes, 81 mRNA nodes and 6 miRNAs. According to topological analysis, two hub lncRNAs (ENST00000562897 and ENST00000640877) were selected to construct the ceRNA subnetwork. Subsequently, key lncRNA-miRNA-mRNA regulatory axes constructed by two lncRNAs including ENST00000562897 and ENST00000640877, two miRNAs including miR-6721-5p and miR-129-1-3p, two mRNAs including ketohexokinase (KHK) and cyclic nucleotide-gated channel beta1 (CNGB1), were identified. Furthermore, qRT-PCR results displayed that the expression of ENST00000562897, KHK and CNGB1 were significantly decreased in TBI, while the miR-6721-5p expression levels were markedly increased in TBI. The results of our study reveal a new insight into understanding the ceRNA regulation mechanism in TBI and select key lncRNA-miRNA-mRNA axes for prevention and treatment of TBI.

Shao X ，Zhang M ，Fang J ，Ge R ，Su Y ，Liu H ，Zhang D ，Wang Q ... -  《-》

Comprehensive analysis of differentially expressed profiles of lncRNAs, mRNAs, and miRNAs in laryngeal squamous cell carcinoma in order to construct a ceRNA network and identify potential biomarkers.

This study aimed to uncover a regulatory network comprised of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) in laryngeal squamous cell carcinoma (LSCC), to explore its underlying mechanisms and development, and to identify key genetic biomarkers for the prognosis of LSCC. Here, we compared mRNA, lncRNA, and miRNA expression profiles between 111 LSCC and 12 adjacent normal tissues using RNA sequencing (RNA-Seq) data from the Cancer Genome Atlas (TCGA) database. Based on the interaction information obtained from miRcode, TargetScan, miRTarBase, and miRDB, a lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network was constructed using differentially expressed lncRNAs (DElncRNA), miRNAs (DEmiRNA), and mRNAs (DEmRNA). By assessing the functional enrichment of DEmRNAs in this network, the potential underlying mechanisms were explored. In addition, Kaplan-Meier survival analysis was used to assess genetic biomarkers related to the prognosis of LSCC patients. Upon comparing LSCC and control tissues, 1640 DElncRNAs, 75 DEmiRNAs, and 3217 DEmRNAs were identified. Based on the prediction between lncRNA-miRNA and miRNA-mRNA relationships, we constructed a ceRNA network comprised of 93 lncRNAs, nine miRNAs, and nine mRNAs. This network predicted that two lncRNAs (AC016773.1 and C00299), two mRNAs (DIO1 and STC2), and two miRNAs (hsa-mir-137 and hsa-mir-210) were significant biomarkers of LSCC prognosis according to thorough topological and survival analyses (P < .05). Through a ceRNA network analysis, our study identifies new lncRNAs, miRNAs, and mRNAs, which can be used as potential biomarkers of LSCC and as therapeutic targets for treating LSCC, thus laying a foundation for future clinical studies.

Kong X ，Qi J ，Yan Y ，Chen L ，Zhao Y ，Fang Z ，Fan J ，Liu M ，Liu Y ... -  《-》

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

Fan CN ，Ma L ，Liu N 《Journal of Translational Medicine》

Integrated Analysis of Competing Endogenous RNAs Network Reveals Potential Signatures in Osteosarcoma Development.

Heng L ，Jia Z ，Sun J ，Zhao Y ，Zhang K ，Zhu Y ，Lu S ... -  《-》