Two Single Nucleotide Polymorphisms in the Von Hippel-Lindau Tumor Suppressor Gene in Patients with Clear Cell Renal Cell Carcinoma.
Magdalena ChrabańskaNikola Szweda-GandorBogna DrozdzowskaPublished in: International journal of molecular sciences (2023)
The most common subtype of renal cell carcinoma (RCC) is clear cell type (ccRCC), which accounts for approximately 75% of cases. von Hippel-Lindau ( VHL ) gene has been shown to be affected in more than half of ccRCC cases. Two single nucleotide polymorphisms (SNPs) located in VHL gene, rs779805 and rs1642742, are reported to be involved in the occurrence of ccRCC. The aim of this study was to assess their associations with clinicopathologic and immunohistochemical parameters, as well as risk and survival of ccRCC. The study population consisted of 129 patients. No significant differences in genotype or allele frequencies of VHL gene polymorphisms were observed between ccRCC cases and control population, and we have found that our results do not indicate a significant relationship of these SNPs with respect to ccRCC susceptibility. Additionally, we did not observe a significant association of these two SNPs with ccRCC survival. However, our results conclude that rs1642742 and rs779805 in the VHL gene are associated with increased tumor size, which is the most important prognostic indicator of renal cancer. Moreover, our analysis showed that patients with genotype AA of rs1642742 have a trend towards higher likelihood of developing ccRCC within their lifetime, while allele G of rs779805 can have a preventive effect against the development of renal cancer in stage 1. Therefore, these SNPs in VHL may be useful as genetic tumor markers for the molecular diagnostics for ccRCC patients.
Keyphrases
- genome wide
- end stage renal disease
- copy number
- renal cell carcinoma
- chronic kidney disease
- ejection fraction
- dna methylation
- newly diagnosed
- prognostic factors
- papillary thyroid
- peritoneal dialysis
- risk assessment
- squamous cell carcinoma
- genome wide identification
- gene expression
- transcription factor
- young adults
- childhood cancer
- data analysis