Dataset Information

Integration analysis of lncRNA and mRNA expression data identifies DOCK4 as a potential biomarker for elderly osteoporosis.

ABSTRACT:

Background

We aimed to identify some potential biomarkers for elderly osteoporosis (OP) by integral analysis of lncRNA and mRNA expression data.

Methods

A total of 8 OP cases and 5 healthy participants were included in the study. Fasting peripheral venous blood samples were collected from individuals, and total RNA was extracted. RNA-seq library was prepared and sequenced on the Illumina HiSeq platform. Differential gene expression analysis was performed using "DESeq2" package in R language. Functional enrichment analysis was conducted using the "clusterProfiler" package, and the cis- and trans-regulatory relationships between lncRNA and target mRNA were analyzed by the lncTar software. A protein-protein interaction (PPI) network was constructed using the STRING database, and hub genes were identified through the MCODE plugin in Cytoscape.

Results

We identified 897 differentially expressed lncRNAs (DELs) and 1366 differentially expressed genes (DEGs) between normal and OP samples. After co-expression network analysis and cis-trans regulatory genes analysis, we identified 69 candidate genes regulated by lncRNAs. Then we further screened 7 genes after PPI analysis. The target gene DOCK4, trans-regulated by two lncRNAs, was found to be significantly upregulated in OP samples. Additionally, 4 miRNAs were identified as potential regulators of DOCK4. The potential diagnostic value of DOCK4 and its two trans-regulatory lncRNAs was supported by ROC analysis, indicating their potential as biomarkers for OP.

Conclusion

DOCK4 is a potential biomarker for elderly osteoporosis diagnostic. It is identified to be regulated by two lncRNAs and four miRNAs.

SUBMITTER: Wu C

PROVIDER: S-EPMC10916189 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Publications

Integration analysis of lncRNA and mRNA expression data identifies DOCK4 as a potential biomarker for elderly osteoporosis.

Wu Chengai C Wang Chao C Xiao Bin B Li Shan S Sheng Yueyang Y Wang Qianqian Q Tao Jianfeng J Zhang Yanzhuo Y Jiang Xu X

BMC medical genomics 20240305 1

<h4>Background</h4>We aimed to identify some potential biomarkers for elderly osteoporosis (OP) by integral analysis of lncRNA and mRNA expression data.<h4>Methods</h4>A total of 8 OP cases and 5 healthy participants were included in the study. Fasting peripheral venous blood samples were collected from individuals, and total RNA was extracted. RNA-seq library was prepared and sequenced on the Illumina HiSeq platform. Differential gene expression analysis was performed using "DESeq2" package in ...[more]

PMID: 38443923

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Project description:BackgroundIncreasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the development and progression of tumors. Nevertheless, lncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients.MethodsThe RNA sequencing data and clinical characteristics of BC patients were obtained from the Cancer Genome Atlas database, and differentially expressed lncRNA (DElncRNAs), DEmRNAs, and DEmiRNAs were then identified between BC and normal breast tissue samples. Subsequently, the lncRNA-miRNA-mRNA ceRNA network of BC was established, and the gene oncology enrichment analyses for the DEmRNAs interacting with lncRNAs in the ceRNA network was implemented. Using univariate and multivariate Cox regression analyses, a four-lncRNA signature was developed and used for predicting the survival in BC patients. We applied receiver operating characteristic analysis to assess the performance of our model.ResultsA total of 1061 DElncRNAs, 2150 DEmRNAs, and 82 DEmiRNAs were identified between BC and normal breast tissue samples. A lncRNA-miRNA-mRNA ceRNA network of BC was established, which comprised of 8 DEmiRNAs, 48 DElncRNAs, and 10 DEmRNAs. Further gene oncology enrichment analyses revealed that the DEmRNAs interacting with lncRNAs in the ceRNA network participated in cell leading edge, protease binding, alpha-catenin binding, gamma-catenin binding, and adenylate cyclase binding. A univariate regression analysis of the DElncRNAs revealed 7 lncRNAs (ADAMTS9-AS1, AC061992.1, LINC00536, HOTAIR, AL391421.1, TLR8-AS1 and LINC00491) that were associated with OS of BC patients. A multivariate Cox regression analysis demonstrated that 4 of those lncRNAs (ADAMTS9-AS1, LINC00536, AL391421.1 and LINC00491) had significant prognostic value, and their cumulative risk score indicated that this 4-lncRNA signature independently predicted OS in BC patients. Furthermore, the area under the curve of the 4-lncRNA signature associated with 3-year survival was 0.696.ConclusionsThe current study provides novel insights into the lncRNA-related ceRNA network in BC and the 4 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of BC patients.

Dataset Information

Integration analysis of lncRNA and mRNA expression data identifies DOCK4 as a potential biomarker for elderly osteoporosis.

Background

Methods

Results

Conclusion

Publications

Integration analysis of lncRNA and mRNA expression data identifies DOCK4 as a potential biomarker for elderly osteoporosis.

Similar Datasets

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