Abstract. Currently, there is no doubt about the feasibility of determining the frequency of HLA and analysis of genetic associations, including those that determine the state of immunity, in patients with the genitourinary disease. The study aimed to evaluate HLA phenotypes in patients with the most common diseases of the genitourinary system and identify risk antigens or protectors. Methods. HLA distribution was studied in 384 patients with pyelonephritis and glomerulonephritis and 464 patients with urological diseases (chronic cystitis, chronic proliferative cystitis, chronic prostatitis, prostate sclerosis, prostatic hyperplasia, and prostate cancer). HLAs were defined using a standard microlymphocytotoxic test (Terasaki’s test) on the Terasakiґs planchette with panels of anti-HLA serums (20 antigens of locus A, 31 – B and 9 – DR). The control group consisted of 350 healthy donors from Ukraine. The HLA frequencies in healthy and diseased subjects were compared taking each antigen separately, using the χ2  test. The value of the relative risk of disease (RR) was determined by the coefficient: RR = ab/cd, where a is the number of patients positive for this antigen, b is the number of persons in control, negative for this antigen; c is the number of patients negative for this antigen, d is the number of persons in control positive for this antigen. Indicators RR≥ 2.0 were considered significant. Absolute (attributive) risk of the disease as an etiological fraction, which was determined by the formula: s = x - y/1 - y, where x is the frequency of antigen in patients, y is the frequency in healthy people. The indicator s> 0,1 was considered reliable. Results. The association of the most common genitourinary diseases with certain histocompatibility antigens (RR≥2) is shown. The causal role of HLA with a significant absolute risk of pyelonephritis (А10, А11; В14, В16) and glomerulonephritis (A24, А28; B8; DR4, DR52), chronic cystitis, (including proliferative) (A10, B14, B16), chronic prostatitis (including with an autoimmune component or impaired fertility) (А24, В8, В52), sclerosis of the prostate (А24, А28), hyperplasia (А29, В38) and prostate cancer (А25, А29, В40, В44, В49) has been established. HLA-antigens associated with protection against these pathologies have also been identified - А2, А24, В21, В35 for pyelonephritis and А9, В12, В16, В18 for glomerulonephritis; А25, А26, В5, В14, В16, В17 for chronic prostatitis with its complications,  А10, B15, B17 for prostate sclerosis, А9, А10, В17 for prostate hyperplasia, A1, B5, B13, B15 for prostate cancer. Conclusion. The study proves the feasibility of identifying antigens of the HLA system and analysis of their associations with different genitourinary diseases, which allows for predicting the risks of the disease and treatment optimization.

Introduction. Prostate cancer antigen-3 (PCA3) is a genetic biomarker, which got widespread and demonstrated high diagnostic potential. This gene expresses only in prostate gland tissue, furthermore, malignant prostate neoplastic transformation leads to 70 – 100 time overexpression of it. Polyadenylated matrix RNA (mRNA) is a functional product of this gene, which do not translating into protein. Gene contains of four introns and three exon. Product of PCA’s gene detecting in post massage urine using polymerase chain reaction (PCR) in combination with reverse transcription. It could use as prognostic biomarker in patients with first negative biopsy or before it performing. Moreover, index of PCA3 can be useful in detecting tumor aggressiveness and decisions about further treatment options. Taking into account these facts, patients with high initial PSA level can avoid unnecessary biopsies. Objective: to determine critical cut-off value of PCA3 index as prognostic biomarker of PCa development. Materials and methods. Research based on routine and special test’s data of 243 men in Institute of Urology, National Academy of Medical Sciences of Ukraine in period of 2015–2020 year. RNA extraction from postmassage urine samples performed using RNeasy (Qiagen) kit. Statistical analysis performed using SPSS Statistics 19.0 (IBM SPSS Statistics 19.0) та SAS 12.0 (IBM Statistical Analysis System 12.0). Critical cut-off values determined using three methods: calculating of average value and (Xave) and standard deviation (SD) of it, Heiner index, and Youden’s index. Evaluation of optimality of determined critical cut-off values performed by comparative analysis using index of positive prognosis (IPP), index of negative prognosis (INP), diagnostic accuracy of method (DAM), Sp and Se for each of used methods. Results and discussion. First method demonstrated than 97,5 % of all results, which means absent of disease, was below critical cut-off values, due to statistical deviations and accurate demonstrate than in case of asymmetry or multimodal distribution this method was unsatisfied. Wherein IPP was 95 %, INP – 72 %, DAM – 78 %, Sp – 97,5 % and Se – 52 %. Calculation of PCA3 index area under ROC-curve was 0,810 (0,771–0,849). Using Heiner’s method critical cut-off value of PCA3 index was 14,0 с. u., where in IPP was 75 %, INP – 82 %, DAM – 78 %, Sp – 78 % and Se – 78 %. Critical cut-off values of PCA3 index 33,4 c. u. which calculated by Youden’s index demonstrated IPP – 98 %, INP – 73 %, DAM – 80 %, Sp – 99 % and Se – 57 %. Conclusions. The most optimal critical cut-off value for PCA3 index was determined using Youden’s index and was 33,4 c. u. Keywords: prostate cancer, PCA , prostate cancer antigen-3, PCA3, prostate cancer antigen-3 index, PCA3 index, critical cut-off values of PCA3 index.