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Urinary cell microRNA-based prognostic classifier for non-muscle invasive bladder cancer

View Article: PubMed Central - PubMed

ABSTRACT

Current prognostic tools for non-muscle invasive bladder cancer (NMIBC) do not have enough discriminative capacity to predict the risk of tumour progression. This study aimed to identify urinary cell microRNAs that may be useful as non-invasive predictive biomarkers of tumour progression in NMIBC patients. To this end, 210 urine samples from NMIBC patients were included in the study. RNA was extracted from urinary cells and expression of 8 microRNAs, previously described by our group, was analysed by quantitative PCR. A tumour progression predicting model was developed by Cox regression analysis and validated by bootstrapping. Regression analysis identified miR-140-5p and miR-92a-3p as independent predictors of tumour progression. The risk score derived from the model containing these two microRNAs was able to discriminate between two groups with a highly significant different probability of tumour progression (HR, 5.204; p<0.001) which was maintained when patients were stratified according to tumour risk. The algorithm was also able to identify two groups with different cancer-specific survival (HR, 3.879; p=0.021). Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable prognostic tool in NMIBC patients.

No MeSH data available.


Heatmap of the KEGG pathways enriched in two miRNA target genesHeatmap from intersection of targeted genes (genes targeted by the two miRNAs from the model) is shown. The two miRNAs are involved in multiple common pathways, especially in cancer-specific pathways (DIANA-miRpath computes log10 P-values).
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Figure 4: Heatmap of the KEGG pathways enriched in two miRNA target genesHeatmap from intersection of targeted genes (genes targeted by the two miRNAs from the model) is shown. The two miRNAs are involved in multiple common pathways, especially in cancer-specific pathways (DIANA-miRpath computes log10 P-values).

Mentions: The DIANA-miRPath miRNA analysis, by using the 2 miRNAs of the model, showed several statistically significant predicted KEGG terms related to cell cycle, TGF-β signalling pathway, MAPK signalling pathway, Wnt signalling pathway, p53 signalling pathway, and pathways in cancer among others. Consistently, when analysing the data by the gene intersection and union mode, with the two miRNAs targeting the same gene, common terms appear to be significantly enriched such as the p53 signalling pathway, TGF-β signalling pathway, cell cycle, and pathways in cancer (Figure 4 and Supplementary Figure 1).


Urinary cell microRNA-based prognostic classifier for non-muscle invasive bladder cancer
Heatmap of the KEGG pathways enriched in two miRNA target genesHeatmap from intersection of targeted genes (genes targeted by the two miRNAs from the model) is shown. The two miRNAs are involved in multiple common pathways, especially in cancer-specific pathways (DIANA-miRpath computes log10 P-values).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5392323&req=5

Figure 4: Heatmap of the KEGG pathways enriched in two miRNA target genesHeatmap from intersection of targeted genes (genes targeted by the two miRNAs from the model) is shown. The two miRNAs are involved in multiple common pathways, especially in cancer-specific pathways (DIANA-miRpath computes log10 P-values).
Mentions: The DIANA-miRPath miRNA analysis, by using the 2 miRNAs of the model, showed several statistically significant predicted KEGG terms related to cell cycle, TGF-β signalling pathway, MAPK signalling pathway, Wnt signalling pathway, p53 signalling pathway, and pathways in cancer among others. Consistently, when analysing the data by the gene intersection and union mode, with the two miRNAs targeting the same gene, common terms appear to be significantly enriched such as the p53 signalling pathway, TGF-β signalling pathway, cell cycle, and pathways in cancer (Figure 4 and Supplementary Figure 1).

View Article: PubMed Central - PubMed

ABSTRACT

Current prognostic tools for non-muscle invasive bladder cancer (NMIBC) do not have enough discriminative capacity to predict the risk of tumour progression. This study aimed to identify urinary cell microRNAs that may be useful as non-invasive predictive biomarkers of tumour progression in NMIBC patients. To this end, 210 urine samples from NMIBC patients were included in the study. RNA was extracted from urinary cells and expression of 8 microRNAs, previously described by our group, was analysed by quantitative PCR. A tumour progression predicting model was developed by Cox regression analysis and validated by bootstrapping. Regression analysis identified miR-140-5p and miR-92a-3p as independent predictors of tumour progression. The risk score derived from the model containing these two microRNAs was able to discriminate between two groups with a highly significant different probability of tumour progression (HR, 5.204; p<0.001) which was maintained when patients were stratified according to tumour risk. The algorithm was also able to identify two groups with different cancer-specific survival (HR, 3.879; p=0.021). Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable prognostic tool in NMIBC patients.

No MeSH data available.