hsa-mir-3199-2 and hsa-mir-1293 as Novel Prognostic Biomarkers of Papillary Renal Cell Carcinoma by COX Ratio Risk Regression Model Screening.

Papillary renal cell carcinoma(PRCC) is the second most common and aggressive renal cell carcinoma. Identification of novel microRNA biomarkers could be beneficial for the diagnosis and prognosis of PRCC patients. We aimed to screen differentially expressed miRNAs that can act as prognostic factors and to predict the survival of PRCC patients. High-throughput data of miRNAs of 274 PRCC samples were downloaded from TCGA (The Cancer Genome Atlas) dataset and interested miRNAs were identified. Hierarchical clustering and principal component analysis (PCA) were performed on these miRNAs. Critical genes that can act as prognostic factors were screened by LASSO. What's more, Kaplan-Meier survival analysis and ROC (Receiver Operating Characteristic) growth curve were used to testify the accuracy of the model. Biological processes of putative targets of miRNAs were analyzed by bioinformatics methods such as GO (Go Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. A total of 105 differentially expressed miRNAs were screened out in PRCC samples compared with healthy controls. Two critical miRNAs, hsa-mir-3199-2, and hsa-mir-1293, were screened out by LASSO (Least Absolute Shrinkage and Selection Operator), including 197 and 189 target genes, respectively. Furthermore, its' accuracy was testified by ROC analysis with the AUC (Area under the curve) value of 0.7774968 and 0.6743466. These miRNAs were significantly enriched in pathways as platelet activating factor biosynthetic process, epithelial cell maturation, and IkappaB kinase complex. In conclusion, hsa-mir-3199-2 and hsa-mir-1293 that can act as prognostic biomarkers of PRCC were screened out, which can provide new insights for the clinical treatment of the disease. J. Cell. Biochem. 118: 3488-3494, 2017.