Abstract

The present study aimed to evaluate the use of the 27K methylation array to investigate abnormal methylation of two genes and their associations with clinical characteristics in clear cell renal cell carcinoma (ccRCC). Six differentially-methylated genes identified using the 27K methylation array were screened in the human RCC 786-0 cell line and normal kidney tissues by bisulfite sequencing polymerase chain reaction (PCR). Differentially-methylated regions (DMRs) that were abnormally hypermethylated in the cell line were further validated in renal tumor and paired normal tissues by pyrosequencing. The correlations between DMRs and differences (methylation rate of tumor minus that of paired normal tissue) according to gender, age, tumor size, Fuhrman grade and disease stage were assessed. Gene expression prior to and following 5-Aza-2'-deoxycytidine treatment was examined using reverse transcription quantitative PCR (RT-qPCR). Two DMRs located in the FBXW10 and SMPD3 genes were found to be hypermethylated in the 786-0 cells, but not in the normal kidney tissues. Pyrosequencing results showed that the average methylation rate of FBXW10 in the cancer tissues was significantly higher compared to that in the paired normal tissues (48.78 vs. 34.62%; P<0.001). The methylation rate of SMPD3 was also higher in the cancer tissues compared with the paired normal tissues (58.98 vs. 38.66%; P<0.001). In stage T1 RCC, the methylation rate of the tumor tissue was positively correlated with the Fuhrman grade (P=0.02). The difference in methylation between the tumor and normal tissues was significantly higher in the group with high Fuhrman grade for the two genes. Furthermore, the linear correlation between methylation difference and tumor size was also confirmed (P=0.01). The RT-qPCR analysis demonstrated that SMPD3 and FBXW10 mRNA expression was significantly upregulated following 5-Aza-2'-deoxycytidine treatment. The results identified two novel DMRs located in SMPD3 and FBXW10 that were hypermethylated in the ccRCC tissue samples. The methylation profile in ccRCC could potentially provide predictive information for clinical decisions.

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