Comprehensive analysis of differentially expressed profiles of lncRNAs and circRNAs with associated co-expression and ceRNA networks in bladder carcinoma

132

108

Background/Aims: CircRNAs regulate gene expression in different malignancies. However, the role of Cdr1as in the tumourigenesis of bladder cancer and its potential mechanisms remain unknown. Methods: qRT-PCR was used to detect Cdr1as and target miRNA expression in bladder cancer tissues and cell lines. Biological functional experiments were performed to detect the effects of Cdr1as on the biological behaviour of bladder cancer cells in vivo and in vitro. Bioinformatic analysis was utilised to predict potential miRNA target sites on Cdr1as. Ago2 RNA binding protein immunoprecipitation assay, RNA antisense purification assay, biotin pull down assay and RNA FISH were performed to detect the interaction between Cdr1as and target miRNAs. Western blot was used to determine the expression level of p21 in bladder cancer cells. Results: Cdr1as was significantly down-regulated in bladder cancer tissues compared with adjacent normal tissues. Overexpression of Cdr1as inhibited the proliferation, invasion and migration of bladder cancer cells in vitro and slowed down tumour growth in vivo. Cdr1as sponged multiple miRNAs in bladder cancer. Moreover, Cdr1as directly bound to miR-135a and inhibited its activity in bladder cancer. Conclusion: Cdr1as is down-regulated and sponges multiple miRNAs in bladder cancer. It exerts anti-oncogenic functions by sponging microRNA-135a.

Section: Discussionmentioning

confidence: 99%

CircRNA-Cdr1as Exerts Anti-Oncogenic Functions in Bladder Cancer by Sponging MicroRNA-135a

Yang

Yuan

et al. 2018

132

108

“…It has been experimentally validated that lncRNAs are involved in the etiology and pathogenesis of various cancers, including BLCA [13][14][15][16][17][18][19][20]. The recent advances in high-throughput data technologies, including RNAsequencing and microarrays, has guided the identification of lncRNAs for prospective clinical application in BLCA [12,[21][22][23]. However, most previous studies focused on the clinical value of individual lncRNAs, which has limited potential for future clinical application.…”

Section: Introductionmentioning

confidence: 99%

RNA-Sequencing Data Reveal a Prognostic Four-lncRNA-Based Risk Score for Bladder Urothelial Carcinoma: An in Silico Update

Huang²,

et al. 2018

Background/Aims: Current practical advances in high-throughput data technologies including RNA-sequencing have led to the identification of long non-coding RNAs (lncRNAs) for potential clinical application against bladder urothelial cancer (BLCA). However, most previous studies focused on the clinical value of individual lncRNAs, which has limited the potential for future clinical application. Methods: In this study, RNA-sequencing data of lncRNAs was downloaded from The Cancer Genome Atlas database. Risk score was constructed based on survival-associated lncRNAs identified using differential expression analysis as well as univariate and multivariate Cox proportional hazards regression analysis. Receiver operating characteristic and Kaplan-Meier curve analyses were employed to evaluate the clinical and prognostic value of risk scores. Bioinformatics analyses were used to investigate the potential mechanisms of newly identified lncRNAs. Results: Among 2,127 differentially expressed lncRNAs (DELs), four new lncRNAs (AC145124.1, AC010168.2, MIR200CHG, and AC098613.1) showed valuable prognostic effects in BLCA patients. More importantly, the four-DEL-based risk score had the potential to become an independent marker for the survival status prediction of BLCA patients. Distinct co-expressed genes and signaling pathways were identified when BLCA was categorized into low- and high-risk groups. Furthermore, a protein-coding gene, HIST4H4 was found only 68 bp from the AC010168.2 DEL. HIST4H4 expression level was evidently up-regulated and positively correlated with AC010168.2 in BLCA patients. Conclusion: This in silico investigation pioneers the future investigation of the utility of prognostic lncRNAs for BLCA.

“…The ceRNA network was constructed as follows: we initially selected the DE lncRNAs and mRNAs in microarray data, and the expressions of these molecules in ESP-induced macrophages and M1 macrophages were comfirmed by qPCR, respectively. Based on the qPCR results and the screening parameter (fold change of ≥2.0 and P value<0.05), the dysregulated lncRNA or mRNA was used to perform miRNA target prediction using the latest miRBase, which collects abundant miRNAs and is extensively used as miRNA reference [41][42][43]. The obtained miRNAs were screened by miRanda and TargetScan programs.…”

Section: Rna Isolationmentioning

confidence: 99%

Long Noncoding RNA Profiling from Fasciola Gigantica Excretory/Secretory Product-Induced M2 to M1 Macrophage Polarization

Luo

Zhang

Sheng

et al. 2018

Background/Aims: Long noncoding RNAs (lncRNAs) are well known regulators of gene expression that play essential roles in macrophage activation and polarization. However, the role of lncRNA in Fasciola gigantica excretory/secretory products (ESP)-induced M2 polarization into M1 macrophages is unclear. Herein, we performed lncRNA profiling of lncRNAs and mRNAs during the ESP-induced macrophage polarization process. Methods: F. gigantica ESP was used to induce peritoneal cavity M2 macrophages in BALB/c mice (5-6 weeks old) in vivo, and these cells were subsequently isolated and stimulated with IFN-γ + LPS to induce M1 cells in vitro. LncRNA and mRNA profiling was performed via microarray at the end of both polarization stages. Results: In total, 2,844 lncRNAs (1,579 upregulated and 1,265 downregulated) and 1,782 mRNAs (789 upregulated and 993 downregulated) were differentially expressed in M2 macrophages compared to M1 macrophages, and six lncRNAs were identified during polarization. We selected 34 differentially expressed lncRNAs and mRNAs to validate the results of microarray analysis using quantitative real-time PCR (qPCR). Pathway and Gene Ontology (GO) analyses demonstrated that these altered transcripts were involved in multiple biological processes, particularly peptidase activity and carbohydrate metabolism. Furthermore, coding and non-coding gene (CNC) and mRNA-related ceRNA network analyses were conducted to predict lncRNA expression trends and the potential target genes of these lncRNAs and mRNAs. Moreover, we determined that four lncRNAs and four mRNAs might participate in F. gigantica ESP-induced M2 polarization into M1 macrophages. Conclusions: This study illustrates the basic profiling of lncRNAs and mRNAs during F. gigantica ESP-induced M2 polarization into M1 macrophages and deepens our understanding of the mechanism underlying this process.