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A Competitive Endogenous RNA Network Based on Differentially Expressed lncRNA in Lipopolysaccharide-Induced Acute Lung Injury in Mice.

ABSTRACT: Non-coding RNAs have remarkable roles in acute lung injury (ALI) initiation. Nevertheless, the significance of long non-coding RNAs (lncRNAs) in ALI is still unknown. Herein, we purposed to identify potential key genes in ALI and create a competitive endogenous RNA (ceRNA) modulatory network to uncover possible molecular mechanisms that affect lung injury. We generated a lipopolysaccharide-triggered ALI mouse model, whose lung tissue was subjected to RNA sequencing, and then we conducted bioinformatics analysis to select genes showing differential expression (DE) and to build a lncRNA-miRNA (microRNA)- mRNA (messenger RNA) modulatory network. Besides, GO along with KEGG assessments were conducted to identify major biological processes and pathways, respectively, involved in ALI. Then, RT-qPCR assay was employed to verify levels of major RNAs. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and the hub genes were obtained with the Molecular Complex Detection plugin. Finally, a key ceRNA subnetwork was built from major genes and their docking sites. Overall, a total of 8,610 lncRNAs were identified in the normal and LPS groups. Based on the 308 DE lncRNAs [p-value < 0.05, |log2 (fold change) | > 1] and 3,357 DE mRNAs [p-value < 0.05, |log2 (fold change) | > 1], lncRNA-miRNA and miRNA-mRNA pairs were predicted using miRanda. The lncRNA-miRNA-mRNA network was created from 175 lncRNAs, 22 miRNAs, and 209 mRNAs in ALI. The RT-qPCR data keep in step with the RNA sequencing data. GO along with KEGG analyses illustrated that DE mRNAs in this network were mainly bound up with the inflammatory response, developmental process, cell differentiation, cell proliferation, apoptosis, and the NF-kappa B, PI3K-Akt, HIF-1, MAPK, Jak-STAT, and Notch signaling pathways. A PPI network on the basis of the 209 genes was established, and three hub genes (Nkx2-1, Tbx2, and Atf5) were obtained from the network. Additionally, a lncRNA-miRNA-hub gene subnetwork was built from 15 lncRNAs, 3 miRNAs, and 3 mRNAs. Herein, novel ideas are presented to expand our knowledge on the regulation mechanisms of lncRNA-related ceRNAs in the pathogenesis of ALI.

SUBMITTER: Jia X

PROVIDER: S-EPMC8669720 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The competing endogenous RNA (ceRNA) network is crucial for the development and progression of tumors, including non‑small cell lung cancer (NSCLC). However, what type of ceRNA network regulates NSCLC has not been clarified. The present study aimed to elucidate the long non‑coding RNA (lncRNA)/microRNA (miRNA)/mRNA ceRNA network in NSCLC, particularly for the significance of lncRNAs in NSCLC. NSCLC‑specific differentially expressed lncRNAs, miRNAs and mRNAs in the Cancer Genome Atlas (TCGA) were analyzed and their relationship was analyzed by a ceRNA network. Their potential functions of differentially expressed mRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Furthermore, the expression levels of four selected lncRNAs in TCGA were determined and their associated survival of patients was examined. In addition, the expression profiles of these four lncRNAs in 48 NSCLC specimens and cell lines, their cellular distribution and associated clinical parameters were examined. We successfully constructed a ceRNA network, including 113 lncRNAs, 12 miRNAs and 36 mRNAs differentially expressed between NSCLC and non‑tumor tissues. LINC00525, MED4‑AS1, STEAP2‑AS1 and SYNPR‑AS1 lncRNAs were selected and validated for their association with the survival of NSCLC patients. The expression of these lncRNAs was upregulated in 48 NSCLC tissues and was varying in NSCLC cells. While LINC00525 was mainly expressed in the cytoplasm, MED4‑AS1 was in both the nucleus and cytoplasm of A549 cells. In addition, the expression of LINC00525 was significantly associated with smoking history (P<0.05); MED4‑AS1 was significantly associated with women, poor differentiation and lymph node metastasis (P<0.05); STEAP2‑AS1 was significantly associated with women (P<0.01); and SYNPR‑AS1 was significantly associated with women and adenocarcinoma (P<0.05). These lncRNAs may be valuable biomarkers for prognosis of NSCLC and the ceRNA network may provide new insights in the pathogenesis of NSCLC.

Project description:LncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks are thought to be involved in regulating the development of various inflammatory diseases. Up to now, the mechanism of such a network in allergic rhinitis (AR) remains unclear. In the study, we investigated the differential expression of lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) by performing a microarray analysis of peripheral blood obtained from AR patients and healthy control subjects. StarBase 2.0 was used to predict miRNAs that might interact with various DElncRNAs and DEmRNAs. We constructed a ceRNA network based on potential lncRNA-miRNA-mRNA interactions. The Cluster Profiler R package was used to perform a functional enrichment analysis of the hub-ceRNA, and Molecular Complex Detection (MCODE) was used for further identification of the hub-ceRNA network. The expression levels of genes contained in the hub-ceRNA network were validated by RT-PCR. In total, 247 DEmRNAs and 18 DelncRNAs were aberrantly expressed in the PBMCs of AR patients. A ceRNA network consisting of 3 lncRNAs, 45 miRNAs, and 75 mRNAs was constructed. A GO analysis showed that negative regulation of immune response, response to interferon-beta, and response to interferon-alpha were important terms. A KEGG pathway analysis showed that 75 mRNAs were significantly enriched in "NOD-like receptor signaling pathway" and "tryptophan metabolism". Ultimately, a hub-ceRNA network was constructed based on 1 lncRNA (AC011511.5), 5 miRNAs (hsa-miR-576-5p, hsa-miR-520c-5p, hsa-miR-519b-5p, hsa-miR-519c-5p, and hsa-miR-518d-5p), and 2 mRNAs (ZFP36L1 and SNX27). Following further verification, we found that overexpression of lncRNA AC011511.5 or inhibitor of miR-576-5p upregulated SNX27 expression. The expression of SNX27 in the lncRNA AC011511.5 overexpression & miR-576-5p inhibitor group was not different from that in the miR-576-5p inhibitor group or lncRNA AC011511.5 overexpression group, indicating that overexpression of lncRNA AC011511.5 could not further upregulate the expression of SNX27 in miR-576-5p inhibitor Jurkat cells. This network may provide new insights to search for biomarkers that can be used for the diagnosis and clinical treatment of AR.

Project description:BACKGROUND:Acute myeloid leukemia (AML) is one of the most common malignant and aggressive hematologic tumors, and its pathogenesis is associated with abnormal post-transcriptional regulation. Unbalanced competitive endogenous RNA (ceRNA) promotes tumorigenesis and progression, and greatly contributes to tumor risk classification and prognosis. However, the comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in the prognosis of AML is still rarely reported. METHOD:We obtained transcriptome data of AML and normal samples from The Cancer Genome Atlas (TCGA), Genotype-tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases, and identified differentially expressed (DE) mRNAs, lncRNAs, and circRNAs. Then, the targeting relationships among lncRNA-miRNA, circRNA-miRNA, and miRNA-mRNA were predicted, and the survival related hub mRNAs were further screened by univariate and multivariate Cox proportional hazard regression. Finally, the AML prognostic circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. RESULTS:We identified prognostic 6 hub mRNAs (TM6SF1, ZMAT1, MANSC1, PYCARD, SLC38A1, and LRRC4) through Cox regression model, and divided the AML samples into high and low risk groups according to the risk score obtained by multivariate Cox regression. Survival analysis verified that the survival rate of the high-risk group was significantly reduced (p < 0.0001). The prognostic ceRNA network of 6 circRNAs, 32 lncRNAs, 8 miRNAs, and 6 mRNAs was established according to the targeting relationship between 6 hub mRNAs and other RNAs. CONCLUSION:In this study, ceRNA network jointly participated by circRNAs and lncRNAs was established for the first time. It comprehensively elucidated the post-transcriptional regulatory mechanism of AML, and identified novel AML prognostic biomarkers, which has important guiding significance for the clinical diagnosis, treatment, and further scientific research of AML.

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A Competitive Endogenous RNA Network Based on Differentially Expressed lncRNA in Lipopolysaccharide-Induced Acute Lung Injury in Mice.

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