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Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer.

ABSTRACT: Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and then established a logistic model and risk score formula to evaluate its diagnostic and prognostic values, respectively. The core ceRNA network consists of 10 nodes, all of which are significantly associated with clinical outcomes. Combination of expression of the 10 ceRNAs with a logistic model achieved AUC of ROC and PR curve up to ?96 and 99% in excluding normal prostate samples, respectively. Additionally, a risk score formula constructed with the ceRNAs exhibited significant association with disease-free survival. More importantly, utilizing the expression of RNAs in the core ceRNA network as a molecular signature, the TCGA-PRAD cohort was divided into four novel clinically relevant subgroups with distinct expression patterns, highlighting a feasible way for improving patient stratification in the future. Overall, we constructed a PCa-specific core ceRNA network, which provides diagnostic and prognostic value.

SUBMITTER: Guo Z

PROVIDER: S-EPMC7406720 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer.

Guo Zihu Z Han Liang L Fu Yingxue Y Wu Ziyin Z Ma Yaohua Y Li Yueping Y Wang Haiqing H Jiang Li L Liang Shengnan S Wang Zhenzhong Z Li Furong F Xiao Wei W Wang Jingbo J Wang Yonghua Y

Frontiers in genetics 20200730

Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and ...[more]

PMID: 32849794

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Project description:Osteoporosis (OP) is a common bone disease of old age resulting from the imbalance between bone resorption and bone formation. CircRNAs are a class of endogenous non-coding RNAs (ncRNAs) involved in gene regulation and may play important roles in the development of OP. Here, we aimed to discover the OP‑related circRNA-miRNA-mRNA (ceRNA) network and the potential mechanisms. Six microarray datasets were obtained from the GEO database and the OP‑related differentially expressed genes (DEGs), circRNAs (DECs), and miRNAs (DEMs) were screened out from these datasets. Then, combined with the prediction of the relationships between DEGs, DEMs, and DECs, a ceRNA network containing 7 target circRNAs, 5 target miRNAs, and 38 target genes was constructed. Then the RNA-seq verification by using total RNAs isolated from the femurs of normal and ovariectomized Wistar rats indicated that MFAP5, CAMK2A, and RGS4 in the ceRNA network were closely associated with osteoporosis. Function enrichment analysis indicated that the target circRNAs, miRNAs, and genes were involved in the process of MAPK cascade, hormone stimulus, cadherin binding, rRNA methyltransferase, PI3K-Akt signaling pathway, and Vitamin digestion and absorption, etc. Then a circRNA-miRNA-hub gene subnetwork was constructed and the qRT-PCR analysis of human bone tissues from the femoral head was used to confirm that the transcription of hsa_circR_0028877, hsa_circR_0082916, DIRAS2, CAMK2A, and MAPK4 showed a significant correlation with osteogenic genes. Besides, the two axes of hsa_circR_0028877/hsa-miR-1273f/CAMK2A and hsa_circR_0028877/hsa-miR-1273f/DIRAS2 conformed to be closely associated with OP. Additionally, by constructing a drug-target gene network, RKI-1447, FRAX486, Hyaluronic, and Fostamatinib were identified as therapeutic options for OP. Our study revealed the potential links between circRNAs, miRNAs, and mRNAs in OP, suggesting that the ceRNA mechanism might contribute to the occurrence of OP.

Project description:Background: Acute ischemic stroke (AIS) is a severe neurological disease with complex pathophysiology, resulting in the disability and death. The goal of this study is to explore the underlying molecular mechanisms of AIS and search for new potential biomarkers and therapeutic targets. Methods: Integrative analysis of mRNA and miRNA profiles downloaded from Gene Expression Omnibus (GEO) was performed. We explored differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMirs) after AIS. Target mRNAs of DEMirs and target miRNAs of DEGs were predicted with target prediction tools, and the intersections between DEGs and target genes were determined. Subsequently, Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses, Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), competitive endogenous RNA (ceRNA) (lncRNA-miRNA-mRNA) network, protein-protein interaction (PPI) network, and gene transcription factors (TFs) network analyses were performed to identify hub genes and associated pathways. Furthermore, we obtained AIS samples with evaluation of immune cell infiltration and used CIBERSORT to determine the relationship between the expression of hub genes and infiltrating immune cells. Finally, we used the Genomics of Drug Sensitivity in Cancer (GDSC) database to predict the effect of the identified targets on drug sensitivity. Result: We identified 293 DEGs and 26 DEMirs associated with AIS. DEGs were found to be mainly enriched in inflammation and immune-related signaling pathways through enrichment analysis. The ceRNA network included nine lncRNAs, 13 miRNAs, and 21 mRNAs. We used the criterion AUC >0.8, to screen a 3-gene signature (FBL, RPS3, and RPS15) and the aberrantly expressed miRNAs (hsa-miR-125a-5p, hsa-miR-125b-5p, hsa-miR-148b-3p, and hsa-miR-143-3p) in AIS, which were verified by a method of quantitative PCR (qPCR) in HT22 cells. T cells CD8, B cells naïve, and activated NK cells had statistical increased in number compared with the acute cerebral infarction group. By predicting the IC50 of the patient to the drug, AZD0530, Z.LLNle.CHO and NSC-87877 with significant differences between the groups were screened out. AIS demonstrated heterogeneity in immune infiltrates that correlated with the occurrence and development of diseases. Conclusion: These findings may contribute to a better understanding of the molecular mechanisms of AIS and provide the basis for the development of novel treatment targets in AIS.

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Project description:Ovarian cancer (OC) is a major health threat to females, as it has high morbidity and mortality. Evidence has increasingly demonstrated that long non-coding RNAs (lncRNAs) regulate OC progression and they may have value as early diagnostic biomarkers, prognostic biomarkers and/or therapeutic targets. In the present study, the regulatory mechanisms and prognosis associated with cancer-specific lncRNAs and their related competing endogenous (ce)RNA network in OC were investigated. The differential expression profiles and prognostic significance of lncRNAs and mRNAs were systematically explored based on data from 359 OC cases from The Cancer Genome Atlas and 180 healthy individuals from the Genotype-Tissue Expression database. Functional enrichment analyses, RNA-RNA interactome prediction, ceRNA network analysis, correlation analysis and survival analysis were utilized to identify hub lncRNAs and biomarkers associated with OC diagnosis or prognosis. A total of 1,049 differentially expressed lncRNAs and 6,516 differentially expressed mRNAs between OC and healthy tissues were detected. An lncRNA-micro (mi)RNA-mRNA regulatory network in OC was further established, containing 91 lncRNAs, 23 miRNAs and 179 mRNAs. After survival analysis based on the expression of the RNAs in the ceRNA network, 8 lncRNAs, 4 miRNAs and 11 mRNAs that were significantly associated with OC patient survival (P<0.05) were obtained. Using least absolute shrinkage and selection operator-penalized Cox regression, an eight-lncRNA risk score model was generated, which was able to readily discriminate between OC and healthy individuals and predict the survival of patients with OC. In addition, the differential expression of several key lncRNAs and mRNAs was verified by reverse transcription-quantitative PCR and western blot analysis. The current study presents a novel lncRNA-miRNA-mRNA network, which provides insight into the potential pathogenesis of OC and allows the identification of prognostic biomarkers and treatment strategies for OC.

Dataset Information

Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer.

Publications

Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer.

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