Integrative Analysis of four miRNA prognostic signatures of prostate cancer [post]

Chen Chi, Xianwu Chen, Liping Yao, Min Li, Lanting Xiang, Xidan Dong, Xiaoling Guo, Quanbo Zhang
2020 unpublished
Background Prostate cancer (PCa) is the most common urological cancer among men, having a poor prognosis, which is hard to accurately evaluate based on the present methods. MicroRNAs (miRNAs), a class of internal non-coding small RNA, can involve in the regulation of tumor biological function. So far, many researchers have tried to explore the relationship of malignant progress of PCa with miRNA, while there are just limited studies conducting the comprehensive analysis of miRNA in PCa clinical
more » ... RNA in PCa clinical significance. Methods The data of miRNA and mRNA expressions in PCa were downloaded from TCGA database, and were performed the overall survival (OS) analysis using Survival package of R software to harvest the differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs). The bioinformatics tools such as TargetScan, miRDB, and miRanda were also conducted to forecast the desired target genes related with prognostic DEMs. In addition, both GO and KEGG analyses were used to uncover the fundamental signaling pathways and cellular processes in PCa as well as the protein-protein interaction (PPI) network was constructed through STRING and Cytoscape software. Results Firstly, 4 DEMs (miR-19a-3p, miR-144-3p, miR-223-5p, and miR-483-3p) were found having significantly associated with overall survival in PCa. Based on the criteria with FDR < 0.05 and |log2FC| > 1, 33 genes were screened out as DEGs. Besides, the functional enrichment analysis revealed that these DEGs of 4 miRNAs may participate in cancer-related pathways like FoxO and PI3K-Akt signaling pathway. Lastly, the low expression of CD177 may be potentially associated with poor survival of patients in PCa. Conclusion This study systematically analyzed multiple PCa prognostic DEMs (miR-19a-3p, miR-144-3p, miR-223-5p, and miR-483-3p), and verified a novel DEG signature (CD177) that can be used to effectively assess the prognosis of PCa patients.
doi:10.21203/rs.3.rs-34448/v1 fatcat:kgczvjgmlbfbtlks4vqlx6m7cy