Abstract Background Histone modifications, DNA methylation, and microRNA (miRNA)-mediated gene silence are examples of epigenetic changes that regulate gene expression without causing sequence changes. The early phases of neoplastic transformation are characterized by the occurrence of these epigenetic changes, which are believed to be crucial for the development and progression of cancer. To increase the sensitivity and practicality of miRNA analysis, we developed a measuring technique using a ZEN double quencher into hydrolysis probe in reverse transcription quantitative polymerase chain reaction (RT-qPCR). Additionally, we developed a method for DNA methylation analysis employing methylation-sensitive restriction enzymes (MSRE) and methylation-insensitive restriction enzymes (MIRE) that can analyze a number of samples quickly. We examined the clinical usefulness of using these systems to understand the level of miRNA expression and methylation in bladder cancer. Methods In this study, 64 biopsied tissues from transurethral bladder tumor resection (TURBT) were used. For miRNA extraction, Cica geniusTM RNA Prep Kit (For Tissue) II (KANTO CHEMICAL CO.,INC.) and a solution that improves miRNA extraction efficiency were used. Using stem-loop RT primers, complementary DNA was created from the isolated miRNA solution. Quantitative analysis was performed by RT-qPCR using a ZEN double quencher probe and miR-21,30a, 200c, and U6 were used as target. Genomic DNA (gDNA) was extracted from the TURBT sample using High Pure PCR Template Preparation Kit (Roche). Restriction enzyme digestion was performed using HapII (Takara Bio) as MSRE and MspI (Takara Bio) as MIRE; the latter has the same recognition site as HapII but is not affected by the presence or absence of methylation. Real-time PCR was performed on the LightCycler 96 (Roche) using Universal ProbeLibrary probes (Roche) targeting ESM1, SFMBT2, and SEPTIN9. From the obtained Cp value, each methylation rate was calculated. The Fisher’s exact test was used to statistically analyze the relationship among miRNA, methylation data and other clinicopathological factors. Results For miR-30a, we observed a higher expression of miRNA was linked to more advanced T stage (P = 0.047). Additionally, ESM1 methylation exhibited a significant correlation with greater grade (P = 0.004) and T stage progress (P = 0.018). Data on miRNA abundance and methylation rate were combined in order to uncover a link with clinical data that was not apparent from either set of data separately. Samples with higher values for both miR-21 and ESM1 methylation rates were shown to have high grade (P = 0.007) and progress to the T stage (P = 0.006). Furthermore, samples with higher values for both miR-200c and SEPTIN9 methylation rates did not progress to the T stage (P = 0.013). Conclusion The combined miRNA and methylation data revealed relationships with clinical results that could not be discovered with either data separately, highlighting the clinical usefulness of the current study’s findings.
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