To construct a ceRNA regulatory network as prognostic biomarkers for bladder cancer.
Jiazhi JiangYaqiong BiXiao-Ping LiuDonghu YuXin YanJie YaoTongzu LiuSheng LiPublished in: Journal of cellular and molecular medicine (2020)
Emerging evidence demonstrates that competing endogenous RNA (ceRNA) hypothesis has played a role in molecular biological mechanisms of cancer occurrence and development. But the effect of ceRNA network in bladder cancer (BC), especially lncRNA-miRNA-mRNA regulatory network of BC, was not completely expounded. By means of The Cancer Genome Atlas (TCGA) database, we compared the expression of RNA sequencing (RNA-Seq) data between 19 normal bladder tissue and 414 primary bladder tumours. Then, weighted gene co-expression network analysis (WGCNA) was conducted to analyse the correlation between two sets of genes with traits. Interactions between miRNAs, lncRNAs and target mRNAs were predicted by MiRcode, miRDB, starBase, miRTarBase and TargetScan. Next, by univariate Cox regression and LASSO regression analysis, the 86 mRNAs obtained by prediction were used to construct a prognostic model which contained 4 mRNAs (ACTC1 + FAM129A + OSBPL10 + EPHA2). Then, by the 4 mRNAs in the prognostic model, a ceRNA regulatory network with 48 lncRNAs, 14 miRNAs and 4 mRNAs was constructed. To sum up, the ceRNA network can further explore gene regulation and predict the prognosis of BC patients.
Keyphrases
- network analysis
- long non coding rna
- genome wide analysis
- single cell
- poor prognosis
- rna seq
- genome wide
- papillary thyroid
- transcription factor
- spinal cord injury
- genome wide identification
- end stage renal disease
- binding protein
- risk assessment
- newly diagnosed
- gene expression
- emergency department
- peritoneal dialysis
- magnetic resonance imaging
- dna methylation
- young adults
- lymph node metastasis
- machine learning
- patient reported outcomes
- deep learning
- single molecule
- adverse drug