RU2683251C1 - Method of diagnosis of clear cell renal cell carcinoma and method for prediction of metastasis based on mirna genes group - Google Patents

Abstract

FIELD: medicine.SUBSTANCE: proposed group of inventions refers to biomedicine, particularly molecular and clinical oncology. Disclosed is a method of diagnosing a clear cell renal cell carcinoma (CCRCC), in which the individuals being examined are taken kidney tissue samples, DNA is extracted and purified from the samples and MC-DNA analysis is carried out by MS-PCR using primers. CCRCC is diagnosed by the presence of hypermethylation in at least two markers from the MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b/c gene group. Disclosed is a method for prediction of spinal cancer metastases, in which the individuals being tested are diagnosed with CCRCC in accordance with the above method, and for individuals with established diagnosis of CCRCC, DNA methylation is performed by MS-PCR. Predictive metastases are predicted by presence of hypermethylation in at least three markers from group of genes MIR-125b-1, MIR-375, MIR-107, MIR-1258 and MIR-203.EFFECT: disclosed methods allow diagnosing CCRCC and predicting its metastasis with high specificity and sensitivity.10 cl, 2 dwg, 4 tbl, 3 ex

Description

The inventive group the invention relates to the field of biomedicine, in particular molecular and clinical oncology, and relates to a method for the diagnosis of clear cell renal cell carcinoma (SCCR) by assessing the methylation status of a group of 7 genes, as well as a method for predicting metastasis of scCRK by assessing the methylation status of a group of 5.

In 70-80% of patients with kidney cancer, they are diagnosed with SCCR, which is characterized by the highest mortality rate among urogenital cancers. More than 35% of cases of SCCR are detected already in the late stages with the presence of metastasis, which reduces the 5-year survival rate to 9% [1].

It was shown that the proportion of microRNA genes regulated by methylation is several times higher than the genes encoding proteins [2]. However, methylation profiles of protein-coding genes, as well as miRNA expression profiles, are used as biomarkers more often, although their determination requires analysis of RNA preparations, while methylation analysis, including miRNA genes, is performed on DNA preparations, which is more accessible, especially in laboratories at clinics.

An analysis of the methylation of more than 20 miRNA genes in scKPR DNA samples allowed us to identify more than 10 new miRNA genes hypermethylated in scKPR using which marker groups were compiled to diagnose scKPR and predict metastasis.

MicroRNA genes associated with the development of tumors and associated with CpG islands were selected using the algorithms contained in the miRWalk 2.0 database (http://zmf.umm.uni-heidelberg.de/apps/zmf/mirwalk2/index.html ), and CpGcluster (http://bioinfo2.ugr.es/CpGcluster/). The optimal marker systems were selected based on the analysis of ROC (Receiver Operating Characteristic curve) -curves (characteristic curves) carried out using the resource http://www.biosoft.hacettepe.edu.tr/easyROC/, which allowed us to calculate the diagnostic and prognostic parameters of different sets of markers: the area under the ROC curve (AUC, area under curve), the optimal cut-off criterion, sensitivity and specificity.

Assessment of methylation status of 7 genes (MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c) in 70 samples of SCCR and in 19 kidney samples from post- mortal individuals without a history of oncology have made it possible to determine on their basis a group of markers for the diagnosis of this disease (panel 1). Assessment of methylation status of 5 genes (MIR-125b-1, MIR-375, MIR-107, MIR-1258, MIR-203) in 20 samples of metastatic and 50 samples of non-metastatic scCCR allowed us to determine the group of markers for predicting metastasis (panel 2). No information was found in the sources of information on the identification of hypermethylation for 8 of the 9 genes used in SCCR; previously, there was only a report on hypermethylation in scCR of the MIR-34b / c gene [3]. Hypermethylation data for scCRD of 8 genes (MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-107, MIR-1258 and MIR-203) were reported for the first time in this document.

No information was found in the information sources for the diagnosis or prognosis of metastasis of SCCR based on an analysis of the status of methylation of miRNA genes.

Earlier, the European Patent Database (CN105408494 (A) - 2016-03-16) described a method for assessing the risk of poor prognosis for the survival of patients with renal cell cancer based on methylation analysis of a group of protein coding genes (FAM150A, GRM6, ZNF540, ZFP42, ZNF154 , RIMS4 and others) [4]. This document does not consider a method for diagnosing SCCR and a method for predicting metastasis, which is necessary for treatment correction.

The European Patent Database (CN105779640 (A) - 2016-07-20) [5] describes a method for diagnosing scCCR based on an analysis of changes in the expression level of 5 miRNA genes in RNA samples. System specifications not shown. The relationship with metastasis has not been considered.

The publication [6 - prototype] is considered as the closest analogue, in which a method for the early diagnosis of kidney cancer is proposed based on an analysis of changes in the expression level of 5 microRNA genes (miR-193a-3p, miR-362, miR-572, miR-28-5p , miR-378). This method is characterized by a sensitivity of 80%, a specificity of 71%, and an AUC value of 0.807. The relationship with metastasis has not been considered.

The technical problem solved by the creation of the claimed group of inventions is to expand the arsenal of clinically convenient, requiring a very small amount (not more than 100 ng) of DNA, which makes it possible to use them for analysis of DNA methylation in small samples, and effective methods for diagnosing and predicting metastasis of clear cell renal cell cancer based on a group of microRNA genes, namely, the creation of a method for the diagnosis of clear cell renal cell cancer (SCCR) based on the developed panel (group) 1 ”of 7 microRNA genes (MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c) by detecting hypermethylation in at least two genes from this group; as well as creating a method for predicting metastasis of clear cell renal cell carcinoma (SCCR) based on the developed panel (group) “2” of 5 microRNA genes (MIR-125b-1, MIR-375, MIR-107, MIR-1258, MIR-203 ) by detecting hypermethylation in any three genes from this group.

The technical result when using each method of the claimed group of inventions connected by a single inventive concept, providing a solution to this problem is to increase the reliability of the results, simplify the technology, reduce the duration of the procedures and, thereby, increase the productivity of research.

At the same time, the detection of methylation (hypermethylation) of at least 2 genes from group (panel) 1 in the tissue of a person presumably affected by cancer, compared with healthy kidney tissue, is a diagnostic sign of SCCR. The prognosis of metastasis requires the detection of methylation (hypermethylation) of at least 3 genes from the group (panel) 2 in human tissue affected by cancer. The claimed method for diagnosing scKPR allows diagnosing scKPR based on a group of microRNA genes (panel 1) with high specificity and sensitivity. The claimed method for predicting metastasis of SCCR allows, based on a group of microRNA genes (panel 2), to predict the presence of metastases in the lymph nodes and / or other tissues of the patient with high specificity and sensitivity, which is important for treatment correction.

Figure 1 graphically shows the results of the analysis of characteristic or ROC-curves of the optimal group of markers for the diagnosis of clear cell renal cell carcinoma (Panel 1). Notes: * CI - confidence interval. The area under the curve is: AUC = 0.939. With the optimal cut-off criterion (cut-off criterion> 0), it is enough to detect methylation of 1 marker out of 7 (the first line from the top), the sensitivity is 90%, the specificity is 90%. To enhance specificity, the need was identified for methylation of at least 2 of 7 markers - cut-off criterion> 0.1429 (second row from the top), sensitivity was 79%, specificity reached 100%;

figure 2 graphically shows the results of the analysis of characteristic or ROC-curves of the optimal group of markers for the prognosis of metastasis of clear cell renal cell carcinoma (panel 2). The area under the curve is: AUC = 0.945. The optimal cut-off criterion (> 0.4) and the values of sensitivity (75%) and specificity (94%) are given. According to the cutoff criterion, methylation of at least 3 out of 5 markers is necessary.

The invention in terms of a method for the diagnosis of clear cell renal cell carcinoma consists in taking kidney tissue samples from examined individuals, isolating and purifying DNA from the samples taken, and performing DNA fragment methylation analysis using MS-PCR using primers specific for methylated and to the unmethylated allele, and scKPR is diagnosed by the presence of hypermethylation in at least two markers from the gene group: MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258 MIR-34b / c.

Preferably, the isolation and purification of DNA from kidney tissue samples is carried out by phenol-chloroform extraction.

Preferably, before methyl-specific PCR (MS-PCR), the quality and exact concentration of DNA is determined spectrophotometrically by the ratio of optical density at wavelengths of 260 and 280 nm, and bisulfite DNA conversion is also carried out.

Preferably, the products obtained by MS-PCR, which are DNA fragments, are separated by electrophoresis in a 2% agarose gel, or in 10% polyacrylamide gel (with a PCR product less than 160 bp (nucleotide pairs)). and check the absence of the product when conducting MS-PCR with each pair of the specified group of primers on unconverted DNA.

Preferably, commercial DNA preparation # G1471 (Promega, USA), (www.promega.com/products/) is used as controls for unmethylated alleles, and commercial DNA preparation # SD1131 (Thermo Fisher Scientific, is used as a positive control for 100% methylation). , USA), (https://www.thermofisher.com/us/en/home.html).

The essence of the invention in terms of a method for predicting metastasis of clear cell renal cell carcinoma consists in taking kidney tissue samples from examined individuals, isolating and purifying DNA from the samples taken, and performing DNA fragment methylation analysis using MS-PCR using primers specific for methylated and unmethylated allele, and the prognosis of metastasis of SCCR for the presence of hypermethylation is considered confirmed to be true for at least three markers from the gene group MIR-125b-1, MIR-375, MIR-107, MIR-125 8 and MIR-203.

Preferably, the isolation and purification of DNA from kidney tissue samples is carried out by phenol-chloroform extraction.

Preferably, before methyl-specific PCR (MS-PCR), the quality and exact concentration of DNA is determined spectrophotometrically by the ratio of optical density at wavelengths of 260 and 280 nm, and bisulfite DNA conversion is also carried out. preferably, products obtained by MS-PCR, which are DNA fragments, are separated by electrophoresis in 2% agarose gel, or in 10% polyacrylamide gel (with a PCR product length of less than 160 bp), and check the absence of the product when conducting MS- PCR with each pair of the indicated group of primers on unconverted DNA.

Preferably, the commercial DNA preparation # G1471 (Promega, USA) is used as controls for unmethylated alleles, and the commercial DNA preparation # SD1131 (Thermo Fisher Scientific, USA) is used as a positive control for 100% methylation.

Diagnosis of SCCR is as follows:

Kidney tissue samples are taken from individuals examined for cancer. Isolation and purification of DNA from kidney tissue samples is carried out by phenol-chloroform extraction. The quality and exact concentration of DNA is determined spectrophotometrically by the ratio of optical density at wavelengths of 260 and 280 nm. Next, bisulfite DNA conversion is carried out followed by methyl-specific PCR (MS-PCR) [3]. To analyze the methylation of microRNA genes by MS-PCR, two pairs of primers are used that are specific to both methylated and unmethylated alleles (Table 1).

Previously, to verify the suitability of the primers and the conditions of the MS-PCR, a sequencing check is performed, i.e. it is confirmed that with these primers and the selected conditions of MS-PCR, the product corresponds to the sequence.

MS-PCR products, which are DNA fragments, are separated by electrophoresis in a 2% agarose gel, or in a 10% polyacrylamide gel (with a PCR product length of less than 160 bp). Check the absence of the product during the MS-PCR with each pair of primers on unconverted DNA. As controls for unmethylated alleles, a commercial DNA preparation # G1471 (Promega, USA) was used. Methylation - a covalent modification of DNA - is carried out by transferring the methyl group from S-adenosyl methionine to the 5th position of the pyrimidine ring of cytosine. Hypermethylation refers to aberrant (abnormal) methylation of the promoter fragments of suppressor genes in tumors in the absence of it in paired histologically normal tissue. As a positive control of 100% methylation, a commercial DNA preparation # SD1131 (Thermo Fisher Scientific, USA) is used. The correspondence of MS-PCR fragments to the studied genes is checked by direct sequencing of both chains of MS-PCR products.

Diagnosis of SCCR is carried out according to the results of detecting hypermethylation of markers from a group of 7 genes (MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c). The diagnosis of SCCR is established by the presence of hypermethylation in at least two markers from 7 of these genes (panel 1).

The results corresponding to figure 1

Prediction of metastasis of SCCR is as follows:

Kidney tissue samples are taken from individuals examined with an established diagnosis. Isolation and purification of DNA from kidney tissue samples is carried out by phenol-chloroform extraction. The quality and exact concentration of DNA is determined spectrophotometrically by the ratio of optical density at wavelengths of 260 and 280 nm. Next, bisulfite DNA conversion is carried out followed by methyl-specific PCR (MS-PCR) [3]. To analyze the methylation of microRNA genes by MS-PCR, two pairs of primers are used that are specific to both methylated and unmethylated alleles (Table 1).

Notes:

Primers are selected by the authors using well-known programs (Methyl Primer Express v.1.0, Vector NTI v.10.0, etc.). Conditions MS-PCR (T _OTL ) are selected experimentally. bp - pairs of nucleotides.

MS-PCR products, which are DNA fragments, are separated by electrophoresis in a 2% agarose gel, or in a 10% polyacrylamide gel (with a PCR product length of less than 160 bp). Check the absence of the product during the MS-PCR with each pair of primers on unconverted DNA. As controls for unmethylated alleles, a commercial DNA preparation # G1471 (Promega, USA) was used. Methylation - a covalent modification of DNA - is carried out by transferring the methyl group from S-adenosyl methionine to the 5th position of the pyrimidine ring of cytosine. Hypermethylation refers to aberrant (abnormal) methylation of the promoter fragments of suppressor genes in tumors in the absence of it in paired histologically normal tissue. As a positive control of 100% methylation, a commercial DNA preparation # SD1131 (Thermo Fisher Scientific, USA) is used. The correspondence of MS-PCR fragments to the studied genes is checked by direct sequencing of both chains of MS-PCR products.

Diagnosis of SCCR is carried out according to the results of detecting hypermethylation of markers from group 5 genes (MIR-125b-1, MIR-375, MIR-107, MIR-1258, MIR-203). The diagnosis of SCCR is established by the presence of hypermethylation in at least three markers of the 5 indicated genes (panel 2).

In order to evaluate the diagnostic effectiveness of each of the proposed methods using characteristic curves. They reflect the mutual dependence of false positive and truly positive results. The full name of such curves is “Observer Operating Characteristic Curves” - Receiver Operating Characteristic curve or, in short, ROC-curve. Therefore, such curves are often called ROC curves, and the actions performed to construct them are called ROC analysis.

The characteristic curves made it possible to quantitatively compare the diagnostic efficiencies of various sets of markers and select the most optimal ones. In order to select the optimal marker panels according to the results of the examination of the verified group of patients and healthy, the data obtained for different sets of genes (marker panels) were tabulated and characteristic curves — ROC curves — were constructed from them. In figure 1 and figure 2. ROC curves are shown for optimal marker panels (panels 1 and 2), for which the program constructed ROC curves with a minimum cut-off criterion and a maximum area under the curve (AUC).

Example 1. Analysis of methylation of microRNA genes used in the claimed methods, in tumor samples and oncologically healthy kidney tissues.

7 genes were selected for the diagnosis of SCCR: MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c (panel 1), for the prognosis of metastasis - 5 genes: MIR-125b-1, MIR-375, MIR-107, MIR-1258 and MIR-203 (panel 2), a total of 9 marker genes were selected: MIR-132, MIR-125b-1, MIR-137, MIR-375 , MIR-193a, MIR-1258, MIR-34b / c, MIR-107 and MIR-203. For these 9 studied genes, micro-RNA MS-PCR was performed in 20 μl of the reaction mixture containing 67 mM Tris-HCl, pH 8.8, 16.7 mM (NH ₄ ) ₂ SO ₄ , 0.01% Tween-20; 1.5 mM MgCl ₂ , 0.25 mM each dNTP; 10-20 ng of DNA; 25 pmoles of each primer; 0.5 units Hot Start Taq DNA polymerase (SibEnzyme, Novosibirsk). Amplification was performed according to the program: 95 ° C, 5 min; 35 cycles {95 ° C, 10 s; T _otzh (see tab. 1), 20 s; 72 ° C, 30 s}; 72 ° C, 3 min. PCR was performed on a DNA Engine Dyad Cycler amplifier from Bio-Rad (USA). Primers, annealing temperature, and size of MS-PCR products are shown in Table 1.

Methylation of markers of composition 1 was analyzed for 70 patients with a morphologically established diagnosis of clear cell renal cell carcinoma (SCCR) and 19 donors (who died from non-cancerous diseases). Data on the clinical and histological characteristics of SCCR samples and on methylation of markers: MIR-132, MIR -125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c (panel 1) and MIR-125b-1, MIR-375, MIR-107, MIR-1258 and MIR -203 (panel 2) are given as an example for 14 tumor samples (table 2). Methylation data of 7 markers for the diagnosis of scKPR are also given for 19 donors in Table 3. Comparison of the data on the methylation of panel 1 markers in samples of tumors and donors allowed us to show the applicability of the method for diagnosing scKPR based on this group of markers and its high sensitivity and strict specificity (see example 2).

Example 2. Assessment of the sensitivity and specificity of the proposed method for the diagnosis of SCCR based on a group of miRNA genes.

An important property of the method for diagnosing scKCR based on 7 microRNA genes (MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c, panel 1) is a high clinical sensitivity and specificity. The presence of methylation in at least one panel 1 marker was detected in 63 of 70 patients with SCCR and in 2 of 19 donors (who died from non-cancer diseases). In accordance with these data, the clinical sensitivity and specificity of diagnosis of SCCR, calculated by the method of ROC analysis, were 90% and 90%, respectively, AUC - 0.939 (see Fig. 1). But to increase the specificity, we asked for the detection of methylation of at least two genes, then the specificity reached 100%, and the sensitivity is 79%, with the same AUC value (see Fig. 1, the table under the ROC curve). Thus, the claimed method (for the detection of methylation of 2 out of 7 markers) can diagnose SCCR in patients truly ill with this cancer with high (in 79% of cases) clinical sensitivity and strictly specific (in 100% of cases) with high reliability (AUC - 0.939 which is higher than 0.9).

Example 3. Assessment of the sensitivity and specificity of the proposed method for predicting metastasis of SCCR.

In accordance with the data on the clinical and histological characteristics, 70 samples of SCCR were divided into two groups: without metastasis - 50 samples and with detected metastasis in regional lymph nodes or distant organs - 20 samples. Table 2 shows, as examples, methylation data for 7 samples without metastasis and for 7 samples with metastasis. Using a combination of 5 microRNA genes (MIR-125b-1, MIR-375, MIR-107, MIR-1258, MIR-203, panel 2) it is possible to distinguish between the methylation level in these two groups and to predict metastasis in a patient with a clinical sensitivity of 75% and a specificity of 94%, AUC - 0.945. The reliability of the method is determined by the method of ROC analysis, according to which, to predict metastasis, it is necessary to establish methylation 3 of 5 markers of panel 2 (Fig. 2).

The inventive group of methods for the diagnosis and prognosis of metastasis of SCCR is characterized in that:

- they are based on the analysis of methylation of miRNA genes in DNA samples, which is more accessible, especially in clinical laboratories, than the analysis of miRNA levels in RNA samples, as in the patent (CN105779640 (A) - 2016-07-20) and in the publication [ 6], taken as the closest analogue;

- a diagnostic method based on the detection of methylation of at least 2 genes of panel 1 is characterized by a clinical sensitivity of 79%, a specificity of 100%, and an AUC of 0.939, which is higher than the method of the closest analogue [6], which is characterized by a sensitivity of 80%, specificity of 71% and an AUC value of 0.807. It can be seen that the claimed methods have similar sensitivity, but significantly superior in specificity and AUC. In addition, it should be noted that the closest analogue method [6] is based on the assessment of microRNA content, which is an expensive method in contrast to the analysis of methylation of microRNA genes in DNA samples;

- the inventive method using panel markers 2 allows to predict the presence or development of metastases in patients with SCCR with a clinical sensitivity of 75% and a specificity of 94% (AUC - 0.945); no similar systems have been found in the information sources for predicting metastasis of skKPR;

- the inventive method allows using the same methodologies to simultaneously diagnose SCCR and predict metastasis, which is important for treatment correction;

- ROC - analysis curves (Receiver Operating Characteristic) allow us to confirm the high information content of the claimed group of inventions.

Table 1. Characterization of primers, annealing temperature, and MS-PCR products of 9 microRNA marker genes.

Cited sources of scientific and technical information:

Bedke J1. , Gauler T, Grünwald V, Hegele A, Herrmann E, Hinz S, Janssen J, Schmitz S, Schostak M, Tesch H, Zastrow S, Miller K. Systemic therapy in metastatic renal cell carcinoma. World J Urol. 2017, 35 (2): 179-188. doi: 10.1007 / s00345-016-1868-5.

2. Vrba L., Muñoz-Rodríguez J.L., Stampfer M.R., Futscher B.W. miRNA gene promoters are frequent targets of aberrant DNA methylation in human breast cancer. Plos one. 2013, 8 (1): e54398.

3. Beresneva EV, Rykov SV, Khodyrev DS, Pronina IV, Ermilova VD, Kazubskaya TP, Braga EA, Loginov VI Methylation profile of a group of microRNA genes in clear cell renal cell carcinoma; association with cancer progression. Genetics. 2013; 49 (3): 366-375.

4. European Patent Base: CN105408494 (A) - 2016-03-16. KANAI YAE; ARAI ERI; TIAN YING. Method for predicting prognosis of renal cell carcinoma.

5. European Patent Base: CN105779640 (A) - 2016-07-20. CUI XUEJUN. MiRNA biomarker and detection kit used for renal cancer diagnosis.

Wang C6. ., Hu J., Lu M., Gu H., Zhou X., Chen X., Zen K., Zhang CY, Zhang T., Ge J., Wang J., Zhang C. A panel of five serum miRNAs as a potential diagnostic tool for early-stage renal cell carcinoma. Sci. Rep. 2015; 5: 7610. doi: 10.1038 / srep07610.

Claims (10)

1. A method for the diagnosis of clear cell renal cell carcinoma, in which kidney tissue samples are taken from the examined individuals, DNA is extracted and purified from the samples taken, and DNA fragments are methylated using MS-PCR analysis using primers specific for both methylated and unmethylated allele, and SCCR is diagnosed by the presence of hypermethylation in at least two markers from the gene group: MIR-132, MIR-125b-1, MIR-137, MIR-375, MIR-193a, MIR-1258, MIR-34b / c . 2. The method according to p. 1, characterized in that the extraction and purification of DNA from kidney tissue samples is carried out by phenol-chloroform extraction. 3. The method according to p. 2, characterized in that before performing methyl-specific PCR (MS-PCR), the quality and the exact concentration of DNA are determined spectrophotometrically by the ratio of optical density at wavelengths of 260 and 280 nm, and bisulfite DNA conversion is also carried out. 4. The method according to p. 3, characterized in that the products obtained by MS-PCR, which are DNA fragments, are separated by electrophoresis in 2% agarose gel, or in 10% polyacrylamide gel (with a PCR product length of less than 160 bp ) and check the absence of the product during the MS-PCR with each pair from the indicated group of primers on unconverted DNA. 5. The method according to claim 4, characterized in that the commercial DNA preparation # G1471 (Promega, USA) is used as controls for unmethylated alleles, and the commercial DNA preparation # SD1131 (Thermo Fisher Scientific is used as a positive control for 100% methylation) , USA). 6. A method for predicting metastasis of clear cell renal cell carcinoma, in which examined individuals are diagnosed with scKPR in accordance with clause 1 and metastasis is predicted for individuals with a diagnosis of scKPR, for which DNA is extracted and purified from the samples taken and produced by MS - PCR analysis of methylation of DNA fragments using primers specific for both methylated and unmethylated alleles, and the prognosis of metastasis of SCCR by the presence of hype is considered confirmed methylation in at least three groups of genes markers of MIR-125b-1, MIR-375, MIR-107, MIR-1258 and MIR-203. 7. The method according to p. 6, characterized in that the isolation and purification of DNA from samples of kidney tissue is carried out by phenol-chloroform extraction. 8. The method according to p. 7, characterized in that before performing methyl-specific PCR (MS-PCR), the quality and the exact concentration of DNA are determined spectrophotometrically by the ratio of optical density at wavelengths of 260 and 280 nm, and bisulfite DNA conversion is also carried out. 9. The method according to p. 8, characterized in that the products obtained by MS-PCR, which are DNA fragments, are separated by electrophoresis in 2% agarose gel, or in 10% polyacrylamide gel (with a PCR product length of less than 160 bp ) and check the absence of the product during the MS-PCR with each pair from the indicated group of primers on unconverted DNA. 10. The method according to p. 9, characterized in that the commercial DNA preparation # G1471 (Promega, USA) is used as controls for unmethylated alleles, and the commercial DNA preparation # SD1131 (Thermo Fisher Scientific is used as a positive control for 100% methylation) , USA).

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