Investigating miRNA-related Pathways Contributing to Kidney Cancer Pathogenesis.

BACKGROUND/AIM: Renal cell carcinoma is one of the most common types of cancer worldwide. Understanding tumor pathogenesis is important in developing better treatment. Micro RNAs (miRNAs) are key players in controlling cancer behavior. Transcription factors (TFs) are potentially responsible for controlling miRNA expression and dysregulation in kidney cancer. The objective of this study was to better understand the TF-miRNA axis of interaction. MATERIALS AND METHODS: We utilized publicly available databases to investigate miRNA-TF interactions, including ChipBase database for TFs that binds to the promoters of miRNAs which are dysregulated in renal cell carcinoma. Renal cancer-specific TFs were extracted from the list using the GENT Database. We assessed the prognostic significance of these TFs using cBioPortal. RESULTS: We identified TFs which bind to miRNA promoters, including hepatocyte nuclear factor-4 alpha (HNF-4α), E2F transcription factor 4 (E2F4), signal transducer and activator of transcription 1 (STAT1), Sp1 transcription factor (SP1), GATA binding protein 6 (GATA6), and nuclear factor kappa B (NFκB). These TFs were positively correlated with their targeted miRNAs, including miR-200c, miR-15a, miR-146b, miR-155, and miR-223. We recognized unique patterns of interactions, including a divergent effect in which multiple miRNAs are simultaneously affected by the same TF. CONCLUSION: Our results show that miRNA-TF interaction is complex. Expression levels of these TFs were found to correlate with renal carcinoma prognosis and have potential utility as biomarkers for aggressive tumor behavior. Targeting these TFs may result in modulating the expression of their target genes and miRNAs, with subsequent therapeutic implications.

ABCC2 expression in papillary renal cell carcinoma provides better prognostic stratification than WHO/ISUP nucleolar grade.

Papillary renal cell carcinoma (PRCC) classification has traditionally been divided into two histologic types, type 1 and type 2. A new biological stratification system has recently been proposed based on comprehensive morphologic and genomic analysis. The predominant molecular marker in this 4-tiered stratification is the renal drug transporter ABCC2. In this study, we assessed and validated the value of the biological grouping in a PRCC cohort of 176 patients and provided a comprehensive assessment of clinicopathological variables. Tissue microarrays (TMAs) were constructed from nephrectomy specimens. The TMAs were stained with ABCC2 and GATA3 antibodies, and the PRCC cohort was stratified into four groups PRCC1-PRCC4: PRCC1 25%, PRCC2 37%, PRCC3 36%, and PRCC4 2%. PRCC1 demonstrated lower disease stage (p = 0.041) than PRCC2 and PRCC3. The biological stratification was significant on univariate analysis when analyzing both overall survival (p = 0.039) and disease-free survival (p = 0.011). The biological groups maintained the significance of predicting overall survival after adjusting for WHO/ISUP grade, age, pathological stage, and necrosis (p = 0.049, hazard ratio: 5.008, 95% confidence interval: 1.007 to 24.909). In contrast, WHO/ISUP grade did not maintain its significance on multivariate survival analysis. ABCC2 expression profile also separated cases ≤ 4 cm, based on disease-free survival (p = 0.038). None of the patients in the PRCC1 group died of disease during the follow-up period. The proposed biologic stratification adds molecular markers to the traditional morphologic assessment to better stratify patients' prognosis. ABCC2 expression can also potentially serve as a predictive biomarker owing to its known implication in cancer biology and drug resistance.

The miR-200 family as prognostic markers in clear cell renal cell carcinoma.

OBJECTIVES: microRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by mRNA cleavage or translational repression. The miR-200 family is involved in the regulation of various tumor biologic processes including apoptosis, proliferation, invasion, and metastasis. They function mainly as tumor suppressors. In this study, we aim to validate the prognostic significance of miR-200 family using large cohort of primary clear cell renal cell carcinoma (ccRCC) and matched normal tissue and to explore the role of miR-200 family in RCC pathogenesis and progression. MATERIALS AND METHODS: We analyzed the expression of 3 members of the miR-200 family; miR-141, miR-200b, and miR-200c, between primary ccRCC, matched normal renal tissues, and nonmatched metastatic RCC. We compared clinicopathologic parameter including disease-free survival to miR-200 family expression. Additionally, we validated our results using The Cancer Genome Atlas dataset. We explored functional role of these miRNAs by bioinformatics analyses. RESULTS AND CONCLUSIONS: Expression of miR-200 family significantly decreased in cancer compared to non-neoplastic tissues. miR-141 and miR-200b were significantly down-regulated in metastatic than primary tumors. There was statistically significant negative association between all 3 miRNAs and tumor size and stage. As binary variables, univariate analyses revealed that miR-141, miR-200b, and miR-200c-positive ccRCC patients have a statistically significant lower chance of disease-recurrence or relapse and multivariate analyses showed miR-200b and miR-200c-positive patients have longer disease-free survival. We could predict disease-free survival better when 2 or more miRNAs were used as a combination. Overall survival analysis using The Cancer Genome Atlas data revealed that miR-200b-positive patients have significantly better survival. These results suggest that miR-141, miR-200b, and miR-200c are independent prognostic markers for ccRCC. Targets of these miRNAs are associated with pathways related to cancer invasion and metastasis, including TRAIL pathway, VEGF and VEGFR signaling network, and epithelial-mesenchymal transition.

Droplet digital PCR improves urinary exosomal miRNA detection compared to real-time PCR.

OBJECT: Quantification of urinary miRNAs can be challenging especially for low abundance miRNAs. We aimed to optimize the quantification of urinary exosomal miRNAs and compare the performance efficiency between droplet digital PCR (ddPCR) and real-time quantitative PCR (qPCR). METHODS: We optimized a number of parameters for ddPCR such as annealing temperatures, annealing time and PCR cycle number. We also compared the performance of ddPCR and qPCR. RESULTS: By comparing the fluorescence amplification separation, the optimal annealing temperature was 59 °C, optimal annealing time was 60s and optimal cycle number was 45 for measuring urinary exosomal miRNAs. ddPCR had much higher technical sensitivity compared to qPCR. The minimal detectable concentration of miR-29a was <50 copies/µL by ddPCR compared to 6473 copies/µL for qPCR. Also, ddPCR generated more consistent results for serially diluted samples compared to qPCR. ddPCR generated smaller within-run variations than qPCR though this did not reach statistical significance. It also resulted in better reproducibility with smaller between-run variations. CONCLUSIONS: Optimization of urinary exosomal miRNA ddPCR assay is dependent on assessing key variables including experimental annealing temperature and time as well as the number of PCR cycles. ddPCR has a higher sensitivity, reproducibility, and accuracy in comparison to qPCR.