| Abstract [eng] |
Small renal masses (SRMs) are stage pT1a tumours <4 cm that make up the majority of kidney cancers. Detection of SRMs is difficult due to their small size and low sensitivity of currently used diagnostic methods. These methods also are not able to distinguish malignant tumours from benign ones, and as a result, there are cases of overtreatment when a kidney (or part of it) is removed due to a harmless tumour. Active surveillance of SRMs can delay or avoid radical treatment, but in the case of SRMs, there are no available biomarker tests for diagnostic or prognostic purposes. The aim of this thesis is to determine the level of methylation of genes ZNF677, FBN2, PCDH8, TFAP2B, TAC1 and FLRT2 in the urine sediments of individuals with SRMs and to evaluate the applicability of these biomarkers for early diagnosis and monitoring of the course of the disease. The study included 54 patients who were diagnosed with SRM and underwent percutaneous biopsy to confirm renal cell carcinoma. After a diagnosis of SRM, patients were actively surveilled and periodic urine samples were collected, along with various clinical and demographic variables. The DNA extracted from the urine sediment was subjected to bisulfite modification and the methylation level was determined by quantitative methylation-specific PCR. The diagnostic and prognostic value of the biomarkers ZNF677, FBN2, PCDH8, TFAP2B, TAC1 and FLRT2 was evaluated according to the obtained methylation levels of the genes. The gene TAC1 (AUC = 0.69, sensitivity – 72.22 %, specificity – 61.96 %) and the combination of genes ZNF677, PCDH8, TAC1 and FLRT2 (AUC = 0.74, sensitivity – 90.74 %, specificity – 50 %) had the best diagnostic value. PCDH8 gene methylation level positively correlated with tumour size and negatively correlated with glomerular filtration rate, so this biomarker could be used in prognostics to evaluate tumour growth. In summary, the obtained results show the potential of the studied epigenetic biomarkers to be used for early diagnosis of SRM and for monitoring the course of the disease. |
