Dataset Information

Identifying Dysregulated lncRNA-Associated ceRNA Network Biomarkers in CML Based on Dynamical Network Biomarkers.

ABSTRACT: 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.

SUBMITTER: Xu J

PROVIDER: S-EPMC7049421 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identifying Dysregulated lncRNA-Associated ceRNA Network Biomarkers in CML Based on Dynamical Network Biomarkers.

Xu Junhua J Wu Min M Sun Yichen Y Zhao Hongqian H Wang Yujie Y Gao Jie J

BioMed research international 20200218

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 dynami ...[more]

PMID: 32149112

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Project description:Background:Hepatocellular carcinoma (HCC) is an aggressive cancer with a poor prognosis and a high incidence. The molecular changes and novel biomarkers of HCC need to be identified to improve the diagnosis and prognosis of this disease. We investigated the current research concentrations of HCC and identified the transcriptomics-related biomarkers of HCC from The Cancer Genome Atlas (TGCA) database. Methods:We investigated the current research concentrations of HCC using literature metrology analysis for studies conducted from 2008 to 2018. We identified long noncoding RNAs (lncRNAs) that correlated with the clinical features and survival prognoses of HCC from The Cancer Genome Atlas (TGCA) database. Differentially expressed genes (lncRNAs, miRNAs, and mRNAs) were also identified by TCGA datasets in HCC tumor tissues. A lncRNA competitive endogenous RNA (ceRNA) network was constructed from lncRNAs based on intersected lncRNAs. Survival times and the association between the expression levels of the key lncRNAs of the ceRNA network and the clinicopathological characteristics of HCC patients were analyzed using TCGA. Real-time polymerase chain reaction (qRT-PCR) was used to validate the reliability of the results in tissue samples from 20 newly-diagnosed HCC patients. Results:Analysis of the literature pertaining to HCC research revealed that current research is focused on lncRNA functions in tumorigenesis and tumor development. A total of 128 HCC dysregulated lncRNAs were identified; 66 were included in the co-expressed ceRNA network. We analyzed survival times and the associations between the expression of 66 key lncRNAs and the clinicopathological features of the HCC patients identified from TCGA. Twenty-six lncRNAs were associated with clinical features of HCC (P < 0.05) and six key lncRNAs were associated with survival time (log-rank test P < 0.05). Six key lncRNAs were selected for the validation of their expression levels in 20 patients with newly diagnosed HCC using qRT-PCR. Consistent fold changes in the trends of up and down regulation between qRT-PCR validation and TCGA proved the reliability of our bioinformatics analysis. Conclusions:We used integrative bioinformatics analysis of the TCGA datasets to improve our understanding of the regulatory mechanisms involved with the functional features of lncRNAs in HCC. The results revealed that lncRNAs are potential diagnostic and prognostic biomarkers of HCC.

Project description:ObjectiveThis study aims to construct a systematic mRNA-miRNA-lncRNA network to identify novel lncRNAs and miRNAs biomarkers for laryngeal squamous cell carcinoma (LSCC).MethodsThe mRNA, miRNA and lncRNA expression profiles of LSCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) were screened between LSCC tissues and controls. Functional analysis of DEmRNAs, DEmRNAs targeted by DEmiRNAs and DEmRNAs targeted by DElncRNAs were respectively performed. The miRWalk, starbase and DIANA-LncBase were respectively used to predict DEmiRNAs-DEmRNAs, DElncRNAs-DEmRNAs and DElncRNAs-DEmiRNAs pairs. ceRNA network was built by DEmiRNAs-DEmRNAs and DElncRNAs-DEmiRNAs pairs. LncRNA subcellular localization was predicted using lncLocator. Using published The Cancer Genome Atlas (TCGA) and external datasets (GSE127165 and GSE133632), we also validated the expression of key DElncRNAs and DEmiRNAs in ceRNA network. The diagnostic and prognostic value of candidate genes was evaluated by ROC curve analysis and survival analysis, respectively.ResultsThere were 5 mRNA datasets, 3 miRNA datasets and 2 lncRNA datasets in this study. Totally, 2957 DEmRNAs, 61 DElncRNAs and 23 DEmiRNAs were identified. Functional analysis of DEmRNAs shows that they were significantly enriched in cancer-related pathways, such as DNA replication and extracellular matrix organization. There were 11 DEmiRNAs, 17 DElncRNAs and 967 DEmRNAs in the ceRNA network. Notably, up-regulated lncRNA DGCR5-down-regulated has-miR-338-3p/has-miR-139-5p pairs in this network were experimentally validated. Moreover, down-regulated AL121839.2, down-regulated LINC02147, up-regulated AC079328.2, up-regulated AC004943.2 and up-regulated HMGA2-AS1 were located in the cytoplasm. AL121839.2 and LINC02147 interacted with has-miR-1246. AC004943.2, AC079328.2 and HMGA2-AS1 targeted has-miR-3185, has-miR-3137 and has-miR-582-5p, respectively. Based on the TCGA and external datasets (GSE127165 and GSE133632), DGCR5 and AC004943.2 were significantly up-regulated while AL121839.2 and LINC02147, has-miR-338-3p, has-miR-139-5p and has-miR-582-5p were significantly down-regulated, which were consistent with our integration analysis. DGCR5, AL121839.2, LINC02147, AC004943.2, has-miR-338-3p, has-miR-139-5p and has-miR-582-5p could predict the occurrence of LSCC. Survival analysis suggested that only, AL121839.2 has potential prognostic value for LSCC.ConclusionThis study provided novel insights into the ceRNA network and uncovered novel lncRNAs and miRNAs with diagnostic value in LSCC.

Dataset Information

Identifying Dysregulated lncRNA-Associated ceRNA Network Biomarkers in CML Based on Dynamical Network Biomarkers.

Publications

Identifying Dysregulated lncRNA-Associated ceRNA Network Biomarkers in CML Based on Dynamical Network Biomarkers.

Similar Datasets

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