Clinical evaluation of microRNA-145 expression in renal cell carcinoma: a promising molecular marker for discriminating and staging the clear cell histological subtype

Abstract

The vast majority of malignancies detected in renal parenchyma are diagnosed as renal cell carcinoma (RCC), whose subtype discrimination and determination of prognosis may contribute to the selection of the adequate therapy. Recently, a new class of small non-coding RNAs, known as microRNAs, has proven to be among the most promising biomarkers for providing this information. Herein, we sought to add up to this knowledge by evaluating the expression levels of microRNA-145 (miR-145) in RCC. For that purpose, total RNA from 58 cancerous and 44 adjacent non-cancerous renal tissues was firstly extracted and then polyadenylated and reverse transcribed to cDNA. MiR-145 levels were finally analyzed by developing and applying a highly sensitive real-time PCR protocol, while their clinical significance was determined via comprehensive statistical analysis. Our data showed that miR-145 was significantly downregulated in cancerous samples and could discriminate between clear cell and non-clear cell subtypes. Moreover, miR-145 expression was found to be correlated with primary tumor staging of cancerous samples, something also noticed in the clear cell RCC subset, in which miR-145 levels were negatively correlated with tumor size as well. Overall, these results indicate that miR-145 might constitute a promising molecular marker for RCC classification and staging.

Genome‐wide screening and cohorts validation identifying novel lncRNAs as prognostic biomarkers for clear cell renal cell carcinoma

“…In summary, lncRNAs serve important roles in the development and progression of cancers and may affect the survival prognosis of patients . The present study constructed a risk score model consisting of 5‐lncRNAs signature (AC009654.1, AC092490.2, LINC00524, LINC01234, and LINC01885), which may favor to evaluate the prognosis of ccRCC with superior predictive accuracy.…”

“…In summary, lncRNAs serve important roles in the development and progression of cancers and may affect the survival prognosis of patients. 32,33 The present study constructed a risk score model consisting of 5-lncRNAs signature (AC009654.1, AC092490.2, LINC00524, LINC01234, and LINC01885), which may favor to evaluate the prognosis of ccRCC with superior predictive accuracy. The pathway enrichment indicated the PI3K-Akt-mTOR and HIF signaling pathways may be the most essential mechanisms mediated by the selected five lncRNAs, which needs to be further validated by well-performed experiments and cohorts.…”

Transcriptomic Analysis Reveals the Regulatory Mechanism of Color Diversity in Rhododendron pulchrum Sweet (Ericaceae)

“…Treatment means were presented as the mean ± standard deviations of the mean using the three replicates [ 62 ]. Bioinformatics data were analyzed using R statistical software package in R Studio version 0.99.446 (RStudio, Inc. 2015) [ 63 ].…”

A Machine Learning Approach for the Classification of Kidney Cancer Subtypes Using miRNA Genome Data

“…Recent studies on mouse strains have shown that individual miRNAs or miRNA clusters are responsible for a range of diseases. It has been stated that low levels of mature miRNAs are linked to cancerous diseases [10] and miRNAs have been proven to be among the most promising biomarkers for providing information about cancer sub-type differentiation and prognosis [14]. For more details and an understanding of the miRNA and cancer correlation, please refer to [9].…”