Dataset Information

A Signature of Five Long Non-Coding RNAs for Predicting the Prognosis of Alzheimer's Disease Based on Competing Endogenous RNA Networks.

ABSTRACT: Long non-coding RNAs (lncRNAs) play important roles in the pathogenesis of Alzheimer's disease (AD). However, the functions and regulatory mechanisms of lncRNA are largely unclear. Herein, we obtained 3,158 lncRNAs by microarray re-annotation. A global network of competing endogenous RNAs (ceRNAs) was developed for AD and normal samples were based on the gene expressions profiles. A total of 255 AD-deficient messenger RNA (mRNA)-lncRNAs were identified by the expression correlation analysis. Genes in the dysregulated ceRNAs were found to be mainly enriched in transcription factors and micro RNAs (miRNAs). Analysis of the disordered miRNA in the lncRNA-mRNA network revealed that 40 pairs of lncRNA shared more than one disordered miRNA. Among them, nine lncRNAs were closely associated with AD, Parkinson's disease, and other neurodegenerative diseases. Of note, five lncRNAs were found to be potential biomarkers for AD. Real-time quantitative reverse transcription PCR (qRT-PCR) assay revealed that PART1 was downregulated, while SNHG14 was upregulated in AD serum samples when compared to normal samples. This study elucidates the role of lncRNAs in the pathogenesis of AD and presents new lncRNAs that can be exploited to design diagnostic and therapeutic agents for AD.

SUBMITTER: Huaying C

PROVIDER: S-EPMC7876075 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A Signature of Five Long Non-Coding RNAs for Predicting the Prognosis of Alzheimer's Disease Based on Competing Endogenous RNA Networks.

Huaying Cai C Xing Jin J Luya Jin J Linhui Ni N Di Sun S Xianjun Ding D

Frontiers in aging neuroscience 20210128

Long non-coding RNAs (lncRNAs) play important roles in the pathogenesis of Alzheimer's disease (AD). However, the functions and regulatory mechanisms of lncRNA are largely unclear. Herein, we obtained 3,158 lncRNAs by microarray re-annotation. A global network of competing endogenous RNAs (ceRNAs) was developed for AD and normal samples were based on the gene expressions profiles. A total of 255 AD-deficient messenger RNA (mRNA)-lncRNAs were identified by the expression correlation analysis. Gen ...[more]

PMID: 33584243

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Project description:Liver cancer is the most common cancer and is the epitome of a recalcitrant cancer. Increasing evidence shown that long noncoding RNAs (lncRNA) were associated with cancer-related death and could function as a competing endogenous RNA (ceRNA). To explore regulatory roles and potential prognostic biomarkers of lncRNA for liver cancer, RNA-sequencing expression data were downloaded from the TCGA database and GEO database. A total of 357 patients were randomly divided into a discovery group and a validation group, of which 313 patients can obtain clinical data. In discovery phrase, 58 lncRNAs, 16 miRNAs, and 34 mRNAs were screened to construct the ceRNA network based on 252 patients employed from discovery group. Univariate and multivariate Cox hazard regression analysis model revealed that five lncRNAs (AATK-AS1, C10orf91, LINC00162, LINC00200, and LINC00501) from 58 lncRNAs were formulated to predict the overall survival (OS). We used the value of gene expression and regression coefficients to construct a risk score based on the five lncRNAs. Next, we validated our model in the GSE116174 dataset (n = 64) and the validation group (n = 94) from TCGA database. Subgroup analysis suggest that the five lncRNAs played critical parts in early stage in cancer from both discovery and validation groups. The five lncRNAs were also found to be associated with immune cells infiltration including CD4+ memory activated, NK cells activated and mast cells activated, then the results were also validated according to the validation group. Furthermore, KEGG pathway enrichment analysis showed that these nine coexpressed modules using the method of WGCNA, and many of these pathways are associated with the development and progression of disease. At last, the transcription factor binding sites (TFBS) of the five lncRNAs were predicted, which help us to understand the potential mechanism that the TFBS adjusted the ceRNA network. In summary, the ceRNA regulatory network may contribute to a better understanding of liver cancer mechanism and provide potential prognostic biomarkers and therapeutic targets.

Project description:BackgroundCircular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) have been recently identified as new classes of non-coding RNAs which participate in carcinogenesis and tumor progression. However, the functions of these non-coding RNAs and gene expression patterns are largely unknown.MethodsWe carried out high-throughput sequencing to analyze the differential expression of RNAs in 5 coupled laryngeal cancer (LC) and corresponding adjacent noncancerous tissues. Bioinformatics analyses were performed to predict the functions of these non-coding RNAs via co-expression, competing endogenous RNA networks and pathway enrichment analysis. The differential expression of the selected RNAs were confirmed using RT-qPCR. The CCK8, EDU, Transwell, and wound healing assays were conducted to validate the biological functions of SNHG29 in LC. Western blot assay was performed to identify the effects of SNHG29 having on the epithelial to mesenchymal transition process. Kaplan-Meier analysis was used to investigate whether the expression level of SNHG29 correlated with survival in LC patients. One-way ANOVA was used to analyze the correlation between the expression of SNHG29 and clinicopathological parameters of the included patients.ResultsCompared to normal laryngeal tissues, 31,763 non-coding RNAs were upregulated and 11,557 non-coding RNAs were downregulated in cancer tissues. SNHG29 expression was low in the LC cell lines and tissues predicting a better clinical prognosis. SNHG29 was also found to inhibit the proliferation, migration, and invasion ability of LC, exerting a suppressive role in the epithelial to mesenchymal transition process as well. SNHG29 downregulation was significantly correlated with differentiation (P=0.026), T-stage (P=0.041), lymphatic metastasis (P=0.044), and clinical stage (P=0.037). We found that the biological functions of differentially expressed transcripts included cell adhesion, biological adhesion, and migration and invasion related to adherens junction pathways.ConclusionsOur study was the first to describe the non-coding RNA profile of LC, and suggested that dysregulated non-coding RNAs could be involved in LC tumorigenesis. SNHG29 was demonstrated to play crucial roles in inhibiting the pathogenesis and progression of LC. Our findings provide a new approach for further analyses of pathogenetic mechanisms, the detection of novel transcripts, and the identification of valuable biomarkers for this tumor.

Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.MethodsWe first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.ResultsWith the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The 'upregulated' ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the 'downregulated' network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.ConclusionsIn conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Dataset Information

A Signature of Five Long Non-Coding RNAs for Predicting the Prognosis of Alzheimer's Disease Based on Competing Endogenous RNA Networks.

Publications

A Signature of Five Long Non-Coding RNAs for Predicting the Prognosis of Alzheimer's Disease Based on Competing Endogenous RNA Networks.

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