A Novel miRNA-Based Model Can Predict the Prognosis of Clear Cell Renal Cell Carcinoma

Abstract

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent renal malignant cancer, whose survival rate and quality of life of patients are still not satisfactory. Nevertheless, the TNM staging system currently used in clinical cannot make accurate survival predictions and precise treatment decisions for ccRCC patients. Therefore, there is an urgent need for more reliable biomarkers to identify high-risk subgroups of ccRCC patients to guide timely intervention and treatment. Recently, MiRNAs have been shown to be closely related to the procession of a variety of tumors, and they have high stability in various tissues, which makes them suggested to have the potential as a prognostic biomarker of ccRCC. In this study, by analyzing and processing the miRNAs expression profile of ccRCC patients from the TCGA database, we finally constructed an excellent miRNAs signature and verified it through a variety of methods. In order to build a more accurate and reliable clinical predictive model, we integrated the miRNAs signature with other prognostic-related clinical parameters to construct a nomogram. Functional enrichment analysis showed that miRNAs in the signature may regulate the genes involved in the Hippo signaling pathway, Tight junction, and Wnt signaling pathway to cause different prognoses of ccRCC patients, which may provide a reference for subsequent basic research and targeted therapy. To conclude, our study constructed a useful miRNAs signature, which allows the prognosis stratification for ccRCC patients and thereby guides the timely and effective interventions on high-risk patients. At the same time, this study also found the potential biological pathways involved in the procession of ccRCC.

Construction of a miRNA-Based Nomogram Model to Predict the Prognosis of Endometrial Cancer

“…hsa-mir-146a is involved in posttranscriptional immune regulation of gene expression in multicellular organisms by affecting mRNA stability and translation. Some of the targets of its encoded miRNAs are tumor necrosis factor, interleukin-1 receptor-associated kinase 1, leukocyte Transcripts of interleukin 1-β, TNF receptor-related factor 6, and complement factor H. Thus, low expression of hsa-mir-146a can cause tumor cells to be unrecognized causing immune evasion and reducing inflammatory responses [ 51 ]. Both Shen et al and Pastrello et al have found hasmir-146a association with the early onset of familial breast and ovarian cancer and the passible mechanism is through BRCA1/2 mRNA expression regulation [ 52 , 53 ].…”

“…In previous studies, hsa-mir-146a and hsa-mir-3170 have been identified as being associated with uterine endometrial carcinogenesis and progression, and as independent predictors of overall survival in uterine endometrial cancer patients [ 50 ]. hsa-mir-3614 can directly target upstream genes to promote cancer cell proliferation and invasion, and its role in renal clear cell carcinoma and non-small-cell carcinoma has been confirmed [ 51 , 52 ]. Similar to our study, Lu et al also pointed out that has-mir-3614 is low-expressed in endometrial cancerous tissue [ 53 ].…”

Construction and Characterization of n6-Methyladenosine-Related lncRNA Prognostic Signature and Immune Cell Infiltration in Kidney Renal Clear Cell Carcinoma

“…However, it is difficult to improve the diagnostic accuracy and guide the choice of treatment for KIRC patients based on the TNM staging system. Several polygenic risk models have been explored, such as the miRNA model [ 7 ], glycolysis-related gene signature [ 8 ], and metabolism-related gene signature [ 9 ]. There are different advantages and limitations in these risk models; therefore, the establishment of new biomarkers and prognostic models are required for KIRC patients.…”