Screening of Target Genes and Regulatory Function of miRNAs as Prognostic Indicators for Prostate Cancer
Zhang Xiaoli, Wei Yawei, Liu Lianna, Li Haifeng, Zhang Hui
Life Science Research Center of Hebei North University, Zhangjiakou, Hebei, China (mainland)
Med Sci Monit 2015; 21:3748-3759
MicroRNAs expression profiling of prostate cancer is becoming increasingly used due to its usefulness in diagnosis, staging, prognosis, and response to treatment. The aim of this study was to screen differentially expressed miRNAs in prostate cancer and analyze the functions and signal pathways of their target genes.
MATERIAL AND METHODS: High-throughput data of miRNAs were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 551 samples (52 normal and 499 prostate cancer cases) and 1046 miRNAs expression values were selected for further analysis. Differentially expressed miRNAs between normal and prostate cancer tissues were identified using SAMR. StarBase and TargetScan software were used to predict the miRNAs’ target group and target genes, respectively. GO functional and KEGG pathway analysis was conducted on up/down-regulated expressed miRNA with DAVID. Finally, survival analysis was performed to evaluate the association of differently expressed miRNAs signature and overall survival of prostate cancer patients.
RESULTS: A total of 162 miRNAs were differentially expressed between normal and prostate cancer samples, including 128 up-regulated and 38 down-regulated ones; hsa-mir-153-2, hsa-mir-92a-1, and hsa-mir-182 (up-regulated); and hsa-mir-29a, hsa-mir-10a, and hsa-mir-221 (down-regulated) were identified as good biomarkers. In GO and KEGG analysis, target genes of down-regulated miRNAs were significantly enriched in positive ion combination and JAK-STAT pathway annotation, respectively; the ones with up-regulated miRNAs were significantly enriched in the function of plasma membrane and MARK signaling pathway annotation, respectively. Patients were categorized into low- or high-score groups according to their risk scores from each miRNA. The patients in the low-score group had better overall survival compared with those in high-score group.
CONCLUSIONS: The 6 differentially expressed miRNAs and their target genes were used to define important molecular targets that could serve as prognostic and predictive markers in the treatment of prostate cancer. Further research on the function of the target genes in the MAPK signal pathway could provide references for treatment of prostate cancer.
Keywords: Case-Control Studies, Biomarkers, Tumor - genetics, Down-Regulation, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, MAP Kinase Signaling System, MicroRNAs - genetics, Principal Component Analysis, Prognosis, Prostatic Neoplasms - genetics, ROC Curve, Up-Regulation