Methylation gene marker combination for early detection of endometrial cancer, multiplex PCR detection kit and its application

Abstract

The present invention belongs to the field of biotechnology, and particularly relates to a methylation gene marker for early detection of endometrial cancer, a multiplex PCR detection kit and an application thereof. The methylation gene marker for early detection of endometrial cancer of the present invention is selected from any at least one methylation region in any at least one gene of the target genes ADARB2, ADCYAP1, ADHFE1, C17orf64, CDO1, GAD2, GRM7, GYPC, KCNA1, KCNQ5, NETO1, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12, and endometrial cancer is diagnosed by detecting the corresponding methylation region, which has higher sensitivity and specificity, and is of great significance for improving the diagnosis rate of high-risk populations of endometrial cancer, achieving early intervention treatment and reducing mortality.

Description

[0001] The patent application for this invention is a divisional application with application number "202410149219.1". The application date of the original application is "February 2, 2024", the application number is "202410149219.1", and the name of the invention is "Methylation gene marker combination for early detection of endometrial cancer, multiplex PCR detection kit and its application". Technical Field

[0002] The invention belongs to the field of biotechnology, and particularly relates to a methylation gene marker for early detection of endometrial cancer, a multiplex PCR detection kit and applications thereof. Background Art

[0003] Endometrial cancer is an epithelial malignant tumor that occurs in the endometrium, also known as uterine body cancer, accounting for about 20-30% of gynecological malignancies. In recent years, the incidence of this tumor has gradually increased and has a clear trend of younger people. In some developed regions, its incidence has reached the first place among gynecological malignancies.

[0004] Since endometrial cancer has early symptoms of irregular vaginal bleeding and vaginal discharge, about 70% of endometrial cancer patients are diagnosed with early lesions limited to the uterine body. However, due to the non-specificity of this symptom, a large number of patients still lose the opportunity for early diagnosis when they are discovered. Early diagnosis is of great significance for endometrial cancer. On the one hand, early diagnosis and early treatment can significantly improve the survival rate and quality of life of patients; on the other hand, with the trend of younger patients with this tumor, more endometrial cancer patients still have fertility needs, and early detection will provide the possibility for conservation treatment.

[0005] There is currently no recommended method for routine screening of endometrial cancer. According to the current guidelines for the diagnosis and treatment of endometrial cancer, vaginal ultrasound and serum tumor marker CA125 are mainly used for auxiliary diagnosis in clinical practice. However, the above methods have problems with low sensitivity and / or specificity and are not suitable for population-based early routine screening of endometrial cancer. Liquid-based cytology using endometrial cell collectors can be used to screen endometrial lesions in symptomatic and high-risk populations, but it is easily affected by the operator, has limited sensitivity, and sampling is somewhat traumatic. For early screening of endometrial cancer, more accurate and non-invasive markers still need to be developed.

[0006] DNA methylation is a type of epigenetics, that is, adding a methyl group to the 5th carbon atom of the cytosine base. This modification is usually associated with gene silencing. DNA methylation is a key epigenetic regulator of gene expression and usually leads to defective gene expression. Increased methylation of tumor suppressor genes is an early event in many tumors. At present, methylation marker detection is a widely recognized source of tumor screening markers. In addition, the use of DNA methylation detection as a tumor screening method has the advantages of high sensitivity and specificity. However, there is currently a lack of detection technology, methods and products for methylation gene detection in endometrial cancer. Therefore, there is an urgent need to provide an early screening marker derived from methylation that can distinguish endometrial cancer from non-cancer groups, and the marker can be used for body fluid samples such as urine and blood, exfoliated cell collection samples such as swabs, brushes, and lavage fluids, and tumor tissue samples, etc., and can eliminate background signal interference in various types of non-invasive collection samples and accurately distinguish endometrial cancer and other disease / healthy individuals. Detection targets. Summary of the invention

[0007] In order to overcome the above-mentioned shortcomings and deficiencies of the prior art, the primary purpose of the present invention is to provide a methylation gene marker for early detection of endometrial cancer.

[0008] The present invention has discovered new methylation genes that can be used for the diagnosis of endometrial cancer or its precancerous lesions: ADARB2, ADCYAP1, ADHFE1, C17orf64, CDO1, GAD2, GRM7, GYPC, KCNA1, KCNQ5, NETO1, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12. The methylation of these genes is detected to diagnose endometrial cancer or its precancerous lesions with higher sensitivity and specificity. The present invention provides new markers and diagnostic strategies for the diagnosis of endometrial cancer and its precancerous lesions.

[0009] Another object of the present invention is to provide a multiplex PCR detection kit for early screening and diagnosis of endometrial cancer.

[0010] Another object of the present invention is to provide the use of the above-mentioned methylation gene marker in the preparation of endometrial cancer diagnostic reagents.

[0011] Another object of the present invention is to provide the use of the above-mentioned multiplex PCR detection kit in the preparation of endometrial cancer diagnosis products.

[0012] The purpose of the present invention is achieved through the following solutions:

[0013] A methylation gene marker for early detection of endometrial cancer, selected from at least one of the following methylation regions in at least one of the target genes ADARB2, ADCYAP1, ADHFE1, C17orf64, CDO1, GAD2, GRM7, GYPC, KCNA1, KCNQ5, NETO1, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12:

[0014] ADARB2 gene: chr10:1779052-1779183, chr10:1779756-1779910;

[0015] ADCYAP1 gene: chr18:907522-907672, chr18:908206-908385;

[0016] ADHFE1 gene: chr8:67344466-67344599;

[0017] C17orf64 gene: chr17:58498643-58498859, chr17:58498879-58499081;

[0018] CDO1 gene: chr5:115152259-115152414;

[0019] GAD2 gene: chr10:26504914-26505063; chr10:26506264-26506424; chr10:26506907-26507068;

[0020] GRM7 gene: chr3:6904068-6904274;

[0021] GYPC gene: chr2:127413900-127414152;

[0022] KCNA1 gene: chr12:5018675-5018893; chr12:5019386-5019578;

[0023] KCNQ5 gene: chr6:73331034-73331188; chr6:73331252-73331411;

[0024] NETO1 gene: chr18:70535858-70535996;

[0025] RYR2 gene: chr1:237205894-237206034;

[0026] SORCS3 gene: chr10:106400776-106400914, chr10:106401432-106401587;

[0027] STX16 gene: chr20:57225138-57225270;

[0028] TCTEX1D1 gene: chr1:67218010-67218198;

[0029] TMEM101 gene: chr17:42092213-42092341;

[0030] ZSCAN12 gene: chr6:28367209-28367379, chr6:28367431-28367676.

[0031] The present invention screens the types of endometrial cancer-related genes and the methylation regions of each gene, and finally screens out the above-mentioned 17 marker genes (or target genes) and their corresponding functionally optimal methylation regions. The judgment threshold can be determined by the methylation results of each marker gene. The results of each methylation region can be used for the early detection of endometrial cancer. The results are very accurate and can provide auxiliary diagnostic references for clinicians.

[0032] The present invention proposes a new marker that can be used as a diagnosis of endometrial cancer or its precancerous lesions, namely the above-mentioned methylated genes. Specifically, the present invention uses at least one of the target genes ADARB2, ADCYAP1, ADHFE1, C17orf64, CDO1, GAD2, GRM7, GYPC, KCNA1, KCNQ5, NETO1, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12 as a target, and diagnoses endometrial cancer by detecting the corresponding methylated regions, which has higher sensitivity and specificity, and has the potential and prospect of being a marker for diagnosing or screening endometrial cancer. Therefore, at least one of the above genes can be used as a biomarker for endometrial cancer, which is of great significance for improving the diagnosis rate of people at high risk of endometrial cancer, achieving early intervention treatment and reducing mortality.

[0033] Furthermore, endometrial cancer is diagnosed by in vitro detection of the methylation region corresponding to any one target gene in the sample. The sample may include body fluid samples such as urine and blood, exfoliated cell collection samples such as swabs, brushes, lavage fluids, and tumor tissue samples.

[0034] Furthermore, when the sample is a sample collected from exfoliated cells such as a swab, a brush, or an lavage fluid, and at least one of the above-mentioned target genes is used as a target, endometrial cancer can be diagnosed by detecting the corresponding methylation region, with a sensitivity and specificity of up to 100%.

[0035] Furthermore, when the sample is urine, a single target gene is used as a target, and the corresponding methylation region is detected for diagnosis, which can still achieve a sensitivity of up to 91% and a specificity of up to 95%. The prior art mostly uses the detection of endometrial tissue and cervical smear cells. The present invention only needs one molecular marker (i.e. one gene) to be used for the detection of urine samples, and can achieve high sensitivity and specificity, providing a simpler and more accurate method for the detection of endometrial cancer.

[0036] Furthermore, diagnosing endometrial cancer or precancerous lesions in the form of a combination of two or more gene methylation can significantly improve sensitivity and specificity.

[0037] The present invention also provides a detection primer for early detection of endometrial cancer, which is used to detect the methylation status of the methylation region of the above-mentioned marker gene. The nucleotide sequence of the detection primer is as follows:

[0038] ADARB2 gene:

[0039] The detection primers corresponding to chr10:1779052-1779183 are SEQ ID NOs:1-2;

[0040] The detection primers corresponding to chr10:1779756-1779910 are SEQ ID NOs:3-4;

[0041] ADCYAP1 gene:

[0042] The detection primers corresponding to chr18:907522-907672 are SEQ ID NOs:5-6;

[0043] The detection primers corresponding to chr18:908206-908385 are SEQ ID NOs:7-8;

[0044] ADHFE1 gene:

[0045] The detection primers corresponding to chr8:67344466-67344599 are SEQ ID NOs:9-10;

[0046] C17orf64 gene:

[0047] The detection primers corresponding to chr17:58498643-58498859 are SEQ ID NOs:11-12;

[0048] The detection primers corresponding to chr17:58498879-58499081 are SEQ ID NOs:13-14;

[0049] CDO1 gene:

[0050] The detection primers corresponding to chr5:115152259-115152414 are SEQ ID NOs:15-16;

[0051] GAD2 gene:

[0052] The detection primers corresponding to chr10:26504914-26505063 are SEQ ID NOs:17-18;

[0053] The detection primers corresponding to chr10:26506264-26506424 are SEQ ID NOs:19-20;

[0054] The detection primers corresponding to chr10:26506907-26507068 are SEQ ID NOs:21-22;

[0055] GRM7 gene:

[0056] The detection primers corresponding to chr3:6904068-6904274 are SEQ ID NOs:23-24;

[0057] GYPC gene:

[0058] The detection primers corresponding to chr2:127413900-127414152 are SEQ ID NOs:25-26;

[0059] KCNA1 gene:

[0060] The detection primers corresponding to chr12:5018675-5018893 are SEQ ID NOs:27-28;

[0061] The detection primers corresponding to chr12:5019386-5019578 are SEQ ID NOs:29-30;

[0062] KCNQ5 gene:

[0063] The detection primers corresponding to chr6:73331034-73331188 are SEQ ID NOs:31-32;

[0064] The detection primers corresponding to chr6:73331252-73331411 are SEQ ID NOs:33-34;

[0065] NETO1 gene:

[0066] The detection primers corresponding to chr18:70535858-70535996 are SEQ ID NOs:35-36;

[0067] RYR2 gene:

[0068] The detection primers corresponding to chr1:237205894-237206034 are SEQ ID NOs:37-38;

[0069] SORCS3 gene:

[0070] The detection primers corresponding to chr10:106400776-106400914 are SEQ ID NOs:39-40;

[0071] The detection primers corresponding to chr10:106401432-106401587 are SEQ ID NOs:41-42;

[0072] STX16 gene:

[0073] The detection primers corresponding to chr20:57225138-57225270 are SEQ ID NOs:43-44;

[0074] TCTEX1D1 gene:

[0075] The detection primers corresponding to chr1:67218010-67218198 are SEQ ID NOs:45-46;

[0076] TMEM101 gene:

[0077] The detection primers corresponding to chr17:42092213-42092341 are SEQ ID NOs:47-48;

[0078] ZSCAN12 gene:

[0079] The detection primers corresponding to chr6:28367209-28367379 are SEQ ID NOs:49-50;

[0080] The detection primers corresponding to chr6:28367431-28367676 are SEQ ID NOs:51-52.

[0081] The present invention also provides a multiplex PCR detection kit for early screening and diagnosis of endometrial cancer, which includes reagents for detecting target gene methylation;

[0082] The target gene is selected from at least one of the following genes: ADARB2, ADCYAP1, ADHFE1, C17orf64, CDO1, GAD2, GRM7, GYPC, KCNA1, KCNQ5, NETO1, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12.

[0083] The reagent includes at least one of the detection primers mentioned above.

[0084] Furthermore, the working process of the multiplex PCR detection kit may be:

[0085] (1) extracting DNA from the sample to be tested and transforming it to obtain modified DNA;

[0086] (2) The modified DNA is detected using a multiplex PCR detection kit, and the detection procedure includes two rounds of PCR reactions; the primers for the first round of multiplex PCR include a primer fragment for amplifying the target region, and a sequencing connection primer fragment of a forward sequencing primer and a reverse sequencing primer; the primers for the second round of multiplex PCR include a primer fragment that is complementary to the sequencing primer connection fragment in the first round of PCR primers and another primer fragment that includes a sequencing adapter.

[0087] In the above working process, the conversion refers to the realization of DNA methyl conversion; the reagents used can be conventional methyl conversion reagents, such as but not limited to bisulfite, bisulfite or hydrazine salt treatment, enzymatic conversion, etc.

[0088] Furthermore, the amplified products obtained by two rounds of PCR reactions were subjected to second-generation sequencing.

[0089] Furthermore, the length of the primer fragment for amplifying the targeted region is 26-38 bp.

[0090] Furthermore, the forward detection primers obtained in the first round of multiplex PCR include forward sequencing primer + NNNNNNNN + forward amplification primer, and their length can be 63-75bp; the reverse detection primers include reverse sequencing primer + NNNNNNNN + reverse amplification primer, and their length can be 69-72bp; it can also be adjusted according to the tester.

[0091] The second generation sequencing can be performed directly using the Illumina sequencer (all sequencing modes are available, including PE150, PE250, SE150, SE250, etc.).

[0092] The present invention also provides the use of the above-mentioned methylation gene marker in the preparation of endometrial cancer diagnosis products.

[0093] The present invention also provides the use of the multiplex PCR detection kit in preparing a diagnostic product for endometrial cancer.

[0094] The diagnostic product includes any one of a kit, a preparation and a chip.

[0095] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0096] The present invention, by screening the types of endometrial cancer-related genes and each gene methylation region, finally screens out the above-mentioned 17 marker genes (or target genes), and the corresponding optimal functional methylation region, which can significantly improve the sensitivity and specificity of early endometrial cancer detection. The methylation gene marker of the present invention can be used for body fluid samples such as urine and blood, exfoliated cell collection samples such as swabs, brushes, and lavage fluids, and tumor tissue samples, and can eliminate background signal interference in all kinds of samples and accurately distinguish endometrial cancer and other disease / healthy individual detection targets. For urine samples collected non-invasively, even if the DNA template concentration is low, the methylation gene marker of the present invention can also achieve excellent detection sensitivity and specificity, reduce unnecessary trauma sampling, have sampling non-invasive, higher sensitivity and specificity, etc., not only optimize the allocation of medical resources, improve the acceptance of subjects, improve the screening experience, but also can ensure the accuracy of the results, to help achieve the purpose of early detection, early diagnosis, and early treatment of endometrial cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0098] Figure 1 Flow chart of the kit detection for multiplex PCR amplification methylation sequencing for sequencing multiple methylated regions.

[0099] Figure 2 Flowchart of library construction for multiplex PCR amplification and methylation sequencing.

[0100] Figure 3 This figure shows the effect of DNA fragmentation on the methylation sequencing of multiple targeted amplicon.

[0101] Figure 4This figure shows the effect of sample initial DNA loading amount on the effect of multiple targeted amplicon methylation sequencing.

[0102] Figure 5 The results are consistent with the retest results of multiplex targeted amplicon methylation sequencing and DNA methylation chip technology.

[0103] Figure 6 This is a diagram showing the methylation rate levels of gene methylation markers in endometrial cancer tissue, adjacent tissue and non-cancerous normal tissue.

[0104] Figure 7 This is a graph showing the changes in methylation rates of gene methylation markers in paired samples before and after endometrial cancer surgery. DETAILED DESCRIPTION

[0105] The present invention is further described in detail below in conjunction with examples, but the embodiments of the present invention are not limited thereto. The materials involved in the following examples can be obtained from commercial channels unless otherwise specified. The methods described are conventional methods unless otherwise specified.

[0106] Example 1: Screening of methylation gene markers for endometrial cancer

[0107] The present invention uses the TCGA public database to obtain 450K methylation chip data of 524 cancer tissues and 34 adjacent tissues of endometrial cancer, and screens sites with significantly high methylation in endometrial cancer tissues; then the CHAMP.DMP method is used to screen differential sites, with the FDR-corrected P value <0.05 and the average methylation rate of cancer tissue minus the average methylation rate of adjacent tissues >0.35 as the screening criteria, and a total of 8730 differential sites are screened out.

[0108] In addition to collecting tumor-derived cells or DNA, sampling methods such as urine, cervical swabs, vaginal swabs, and blood will inevitably involve the incorporation of components such as white blood cells or urothelial cells. The incorporation of these non-target exogenous DNAs may interfere with the detection of target markers as background signals. Therefore, the interference of background signals should be carefully handled when screening markers. Taking the above into consideration, the present invention further incorporates 78 cases of urinary tract cancer paracancerous tissues and 338 cases of white blood cell 450k methylation chip data from females in the TCGA and GEO databases, and performs CHAMP.DMP difference tests with 425 cases of endometrial cancer tissue data. Sites that simultaneously met the following conditions were included in the screening scope: (1) P value after FDR correction of two difference tests < 0.05; (2) average methylation rate of cancer tissue minus average methylation rate of paracancerous tissue of urinary tract cancer > 0; (3) average methylation rate of cancer tissue minus average methylation rate of paracancerous tissue of leukocytes > 0; (4) average methylation rate of paracancerous tissue of urinary tract cancer < 0.1; (5) average methylation rate of leukocytes < 0.1. The sites that met the above requirements were intersected with the differential sites of endometrial cancer / paracancerous tissue differential screening, and a total of 1464 sites were included in the next screening process.

[0109] In order to further evaluate the methylation levels of the above 1464 candidate sites in actual samples, the present invention performed Illumina Epic 850k chip detection on 12 exfoliated cell samples of endometrial cancer patients and 15 controls collected at the Cancer Prevention and Treatment Center of Sun Yat-sen University and Foshan First People's Hospital. This chip is an upgraded version of the 450K chip, retaining most of the 450K chip sites while adding nearly 400,000 new methylation sites. Finally, it was determined to select 17 genes including C17orf64, CDO1, KCNQ5, STX16, ZSCAN12, KCNA1, ADARB2, SORCS3, GAD2, RYR2, GRM7, ADCYAP1, NETO1, GYPC, TMEM101, ADHFE1 and TCTEX1D1. The methylation sites with the best diagnostic effect of the above genes for endometrial cancer and their effect information are shown in Table 1.

[0110] The area under the curve of the best sites of 17 genes was between 0.867 and 0.983. Among them, the AUC of 7 genes including C17orf64, CDO1, KCNQ5, STX16, ZSCAN12, KCNA1 and ADARB2 was greater than 0.98; the AUC of 7 genes including SORCS3, GAD2, RYR2, GRM7, ADCYAP1, NETO1 and GYPC was between 0.90 and 0.95. Different genes showed different advantages in detection sensitivity and specificity. Among them, the sensitivity of CDO1, KCNA1 and TCTEX1D1 genes could reach 100%, and the specificity of C17orf64, KCNQ5, STX16 and ZSCAN12 genes could reach 100%. The sensitivity of these 17 gene methylation markers was higher than 80% except GRM7 and GAD2; except TCTEX1D1, the specificity was higher than 80%. In summary, the sensitivity of C17orf64, KCNQ5, STX16 and ZSCAN12 genes can reach 91.7% when the specificity is 100%; the specificity of KCNA1 gene can reach 93.3% when the sensitivity is 100%. The above genes showed excellent discrimination ability between endometrial cancer and controls.

[0111] In addition, sites with strong discrimination ability appear in clusters around the optimal site. Within 500bp upstream and downstream of the optimal site, the above genes have 1-8 sites with AUC greater than 0.8, and 14 genes have at least 3 or more sites with AUC higher than 0.8. Genes with less than 3 sites with AUC>0.8 are also likely to be caused by the low probe coverage density and too few detection sites when the Epic850k chip was designed. The appearance of multiple site clusters further demonstrates the certainty of the above gene methylation as a diagnostic marker for endometrial cancer, and is conducive to the development of methylation site detection methods. The results show that the 17 genes of the present invention have excellent discrimination ability in endometrial cancer and control populations.

[0112] Table 1

[0113]

[0114] Note: A* is the number of sites with AUC>0.8 within 500bp upstream and downstream of the best site.

[0115] Example 2: Construction of multiplex PCR amplification methylation sequencing technology to detect marker methylation signals

[0116] For the 17 genes screened in Example 1, a method for DNA amplicon targeted methylation sequencing was established. The DNA converted by bisulfite was subjected to targeted PCR amplification and tested by next-generation sequencing to obtain the methylation level of the candidate markers in the sample. The flow chart is as follows: Figure 1 The specific steps are as follows:

[0117] 2.1 Design of multiplex PCR primers for target regions

[0118] Determination of target region: Sites located on CpG islands often appear continuously. To determine the optimal sequence amplification range, the present invention first selects the optimal amplification region for the aforementioned 17 candidate differentially methylated sites in units of genes. Taking the best site of the area under the curve (AUC) of the receiver operating characteristic curve in the gene as the center, extract the methylation rate of all 850k chips containing methylated sites on the gene in the exfoliated cells and endometrial cancer tissue data, and pull out the 150-350bp region with the most dense methylated sites and the most significant differences in exfoliated cells and tissues for the next step of primer design.

[0119] Design of PCR primers for target regions: DNA methylation-specific PCR primer design software such as MethPrimer was used to design primers for each sequence. The designed primers were paired in pairs, and the paired primers were compared for compatibility to avoid problems such as primer dimers and hairpin structures between multiple pairs of primers as much as possible, thereby improving the success rate of primers. After repeated debugging, a total of 26 pairs of primers were designed for multiplex PCR detection of 17 target genes. The primer sequences, chromosomal physical locations of the amplified regions, and information on the target genes are shown in Table 2. Among them, "F" represents forward amplification primers, and "R" represents reverse amplification primers.

[0120] Table 2

[0121]

[0122]

[0123] 2.2 Two rounds of PCR amplification to construct amplicon library of target fragment and sequence it

[0124] Urine sample pretreatment and DNA extraction using ZYMO Quick-DNA TMUrine Kit, and ZYMO EZ DNA Methylation-Gold Kit was used for DNA bisulfite conversion. For DNA samples after bisulfite conversion, the present invention established a multiplex PCR primer system for 26 fragments of 17 target genes, which can cumulatively detect 280 methylation sites. The method is divided into two rounds of PCR: the primers of the first round of multiplex PCR are divided into two parts: a 26-38bp targeted region amplification primer fragment and a 29bp (forward primer) and 26bp (reverse primer) sequencing connection primer fragment; the length of the first round of multiplex forward PCR primers obtained is 63-75bp, and the length of the reverse PCR primer is 69-72bp. The primers for the second round of multiplex PCR contain a complementary fragment to the sequencing primer connection fragment in the first round of PCR primers and another primer fragment containing a sequencing adapter. The amplified products after two rounds of PCR can be directly sequenced using an Illumina sequencer for second-generation sequencing (PE150, PE250, SE150, SE250 and other sequencing modes are all acceptable). The design principles of the two-round PCR primers are as follows Figure 2 .

[0125] The specific steps are as follows:

[0126] (1) First round of PCR amplification

[0127] The first round of PCR is a multiplex PCR amplification system, and its amplification primers are divided into two parts: {sequencing primer fragment + 8 free bases + amplification primer fragment}. This kit covers the detection of 28 methylation regions including the 17 genes described in this application. The sequences of amplification primer fragments for each amplification region are shown in Table 2. The basic information of each gene methylation detection region, the reference genome position of the detection sequence, the detection sequence length, and the reference genome sequence of the detection region are shown in Table 3.

[0128] Table 3

[0129]

[0130]

[0131]

[0132]

[0133] The design idea of ​​the primer sequence of the first round of multiplex PCR primers is shown in Table 4, and the overall composition of the primers is "sequencing primer + NNNNNNNN + amplification primer". The forward sequencing primer sequence is 5'-AATGATACGGCGACCACCGAGATCTACAC-3'; eight variable bases "NNNNNNNN" are added in the middle as the barcode sequence to distinguish the sequence sample information obtained by sequencing; and then the forward amplification primers of each gene methylation are connected, see the F primers in Table 2 for details. The reverse sequencing primer sequence is 5'-CAAGCAGAAGACGGCATACGAGATTC-3'; eight variable bases "NNNNNNNN" are added in the middle as the barcode to distinguish the sequence sample information obtained by sequencing; and then the reverse amplification primers of each gene methylation are connected, see the R primers in Table 2 for details. In the present invention, the first round of multiplex PCR primers of each amplification region are mixed in equal proportions as PCR primers, bisulfite-converted DNA is used as template DNA, and KAPAHiFiMix is ​​used as DNA polymerase for amplification. The number of amplification cycles depends on the quality and concentration of the DNA template and is controlled within 15-35 cycles. The PCR reaction system consists of (amount per well): 2μL 5xKAPA HiFi buffer; 0.3μL 10mM dNTPs; 0.5μL DMSO; 0.2μL KAPA HiFi Polymerase; 1μL forward sequencing primer (5μM); 1μL reaction sequencing primer (5μM); 3μL enzyme-free water; 2μL converted DNA. PCR reaction conditions: first 95℃-5min; then 98℃-20s, 50-60℃-30s, 72℃-1min, 15-35 cycles; finally maintained at 4℃.

[0134] Table 4

[0135]

[0136] (2) Second round of PCR amplification and purification

[0137] The first round of PCR amplification products were purified using AMPure XP magnetic beads, and the purified nucleic acid was used as the template DNA for the second round of PCR for the second round of amplification. KAPAHiFiMix was used as the DNA polymerase for amplification. The amplification annealing temperature and extension time were determined according to the specific situation of the product, and the number of cycles was controlled within 10-20 cycles. The forward primer sequence for the second round of amplification is CAAGCAGAAGACGGCATACGAGATNNNNNNNNGTCTCGTGGGCTCGG, and the reverse primer sequence is AATGATACGGCGACCACCGAGATCTACACNNNNNNNNTCGTCGGCAGCGTC, where "NNNNNNNN" is the sequencer index sequence. It should be noted that the first round of PCR sequencing primers and the second round of sequencing primers can be formulated and modified according to the specific requirements of different brands and specifications of sequencers. The sequencing primers provided in the present invention only provide an example of one sequencing primer; the use of other sequencing primers that meet the requirements of the corresponding sequencer will not affect the detection results of this kit. The PCR reaction system consists of (amount per well): 2μL 5x KAPA HiFi buffer; 0.3μL 10mM dNTPs; 0.5μL DMSO; 0.2μL KAPA HiFi Polymerase; 1μL forward sequencing primer (5μM); 1μL reaction sequencing primer (5μM); 3μL enzyme-free water; 2μL first round PCR diluted product DNA. PCR reaction conditions: 95℃-5min first; then 98℃-20s, 50-60℃-30s, 72℃-1min, 10-20 cycles; finally maintained at 4℃.

[0138] (3) Amplification product mixing and quality evaluation

[0139] The second round of PCR amplification products were purified using AMPure XP magnetic beads, and the purified DNA was quantified using the qubitdsDNA high sensitivity assay kit and qPCR method. After the amplification products of different samples were mixed with equal molar mass, second-generation sequencing was performed on the corresponding sequencer.

[0140] (4) Bioinformatics analysis of sequencing data

[0141] After the sequencing data is downloaded, the fastqc software is used to check the data quality, and the software Trimmomatic is used to remove the sequencing adapters and low-quality bases and sequences to obtain qualified sequences after quality control. Subsequently, the basmap methylation sequencing data comparison software is used to compare and analyze the qualified sequences and the target sequences in the amplified region. Then, the methylation level of the CG base on each target sequence of each sample is calculated. The calculation formula for the methylation level is: methylation level of the C site = number of sequences supporting methylation / (number of sequences supporting methylation + number of sequences supporting non-methylation); According to the above formula, the methylation rate level of all methylation sites in the detection area of ​​each sample can be obtained. For sequences where the sequencing depth of a certain site is less than 50X, the methylation rate of the site of the sample is defined as a missing value NA and is no longer included in the calculation.

[0142] (5) Evaluation of targeted amplicon methylation sequencing results

[0143] ①The effect of DNA fragmentation on multiplex PCR amplification

[0144] Since DNA from samples such as exfoliated cells often has the risk of nucleic acid degradation and fragmentation, the present invention tested 5 samples with different degrees of fragmentation to observe the effect of DNA fragmentation on the test results of the kit. The results showed that for samples with severe fragmentation, the percentage of qualified sites detected by the targeted methylation sequencing technology of the present invention was above 99%, indicating that the detection method of the present invention is basically not affected by DNA fragmentation and reliable detection data can still be obtained in the case of severe fragmentation. Figure 3 and Table 5.

[0145] Table 5

[0146] Sample No. DNA loading amount (ng) Is it fragmented? Percentage of qualified sites for targeted methylation sequencing (%) 1 8.57 yes 99.48 2 118.67 no 99.90 3 89.67 no 99.90 4 90.73 no 100.00 5 38.80 yes 99.53

[0147] ②The effect of sample loading on multiplex PCR amplification sequencing

[0148] Due to the large heterogeneity of individual sampling, samples collected non-invasively such as exfoliated cells often have insufficient nucleic acid. Therefore, the present invention tests the detection effect under different sample initial DNA loading amounts. The results show that even when the DNA input amount is less than 200ng, the average percentage of qualified sites detected by targeted methylation sequencing technology can still reach 98%, and there is no statistical difference between the percentage of qualified sites grouped with higher sample initial DNA loading amounts ( Figure 4 ). This shows that the detection method of the present invention can still obtain sufficient data when only a small amount of nucleic acid is obtained from the sample to be tested.

[0149] ③Consistency of multiplex targeted amplicon methylation sequencing and DNA methylation chip technology

[0150] There will be certain deviations in the detection results of methylation sites by different detection methods. In order to evaluate the effect of the multiplex targeted amplicon methylation sequencing constructed in this application on the true methylation level in the sample, three samples that have been tested for multiplex targeted amplicon methylation sequencing were simultaneously tested using the Illumina Epic850K methylation chip. The Epic850K methylation chip is one of the widely used and highly recognized DNA methylation detection methods. By comparing the methylation rates of the methylation sites detected by both methods, the correlation between the methylation rates of the two detection methods of the three retested samples was calculated. The results showed that the retest consistency of the two detection methods for the three samples was good, and the correlation coefficient R 2 They are 0.878, 0.941 and 0.851 respectively, which have a high positive correlation ( Figure 5 ). This shows that the detection method of the present invention can reflect the real methylation signal in the sample.

[0151] In summary, the multiple targeted amplicon methylation sequencing detection method of the present invention is compatible with common sample problems such as severe DNA fragmentation and low DNA input, can reflect the true methylation rate level in the sample, and is feasible for development into a detection kit, especially when detecting samples with large individual heterogeneity such as exfoliated cells and body fluid-derived samples.

[0152] Example 3: Diagnostic Effect of Methylation Markers in Urine Samples for Endometrial Cancer

[0153] Compared with blood samples and tissue samples, urine samples are completely non-invasive; compared with samples such as cervical swabs and vaginal swabs, they are less affected by individual sampling techniques and do not require the assistance of medical staff. The public has a high acceptance of this sampling method and can be sampled at home. The test samples in this embodiment are urine collected from 107 endometrial cancer patients and 111 control participants at the Cancer Prevention and Treatment Center of Sun Yat-sen University and the Affiliated Cancer Hospital of Guangzhou Medical University.

[0154] The sample was extracted with the detection method constructed in Example 2 of the present application, DNA was modified with bisulfite, a targeted methylation amplification library was constructed, and sequencing was performed on the Illumina platform. The sequencing data was subjected to the above-mentioned biological information analysis process to obtain the methylation levels of the methylation sites in the amplification regions of the 17 genes. After the data quality control process, 280 site information from 17 genes was included in the analysis. Since the data was quality controlled and filtered according to the sequencing depth of each gene, sites with a sequencing depth of less than 50 sequences were defined as missing. After this filtration, the number of cases finally included in the analysis of each site ranged from 97 to 106 cases, and the number of controls ranged from 105 to 111 cases.

[0155] The genes included in the present invention use targeted amplification methylation sequencing to diagnose endometrial cancer in independent samples. The methylation sites and their effect information are shown in Table 6. The methylation sites detected in the 17 genes range from 3 to 35. When determining the corresponding gene, all primer pairs covered by the gene in Table 2 are used for detection. By modeling the methylation sites in the same gene using a Logistic model, the area under the curve is between 0.788 and 0.886. Among them, the AUC of the methylation markers of three genes, including GAD2, ADCYAP1 and C17orf64, is greater than 0.85; the AUC of the 16 markers other than CDO1 is greater than 0.8. Similar to the results in Example 1, CDO1 showed excellent sensitivity of 91.3%; the sensitivity of GAD2 and GRM7 was higher than 80%; the specificity of KCNA1 and ADCYAP1 was higher than 90%. The area under the curve of the methylation sites with the best prediction effect in the above 17 gene methylation detection regions is 0.730-0.814.

[0156] Table 6

[0157] Gene A B <![CDATA[AUC 1 ]]> Sensitivity (%) Specificity (%) C <![CDATA[AUC 2 ]]> GAD2 102 109 0.886 87.3 78.0 33 0.768 ADCYAP1 105 110 0.867 64.8 92.7 19 0.802 C17orf64 101 106 0.864 74.3 88.7 29 0.780 KCNA1 105 109 0.847 62.9 95.4 35 0.781 RYR2 106 109 0.835 73.6 78.9 10 0.809 ADARB2 104 108 0.833 62.5 89.8 14 0.784 ZSCAN12 99 107 0.827 77.8 72.9 26 0.773 KQT 97 106 0.825 69.1 77.4 16 0.774 STX16 106 110 0.825 73.6 80.0 10 0.798 GRM7 106 111 0.823 82.1 70.3 11 0.786 SORCS3 104 109 0.822 68.3 84.4 17 0.794 ADHFE1 105 109 0.822 73.3 80.7 7 0.797 GYPC 106 108 0.821 70.8 82.4 27 0.730 TMEM101 102 105 0.820 76.2 73.1 19 0.814 NETO1 103 107 0.809 72.8 78.5 3 0.787 TCTEX1D1 102 105 0.802 66.7 86.7 10 0.772 CDO1 104 105 0.788 91.3 49.5 7 0.791

[0158] Note: A is the sample size of the case group included in the modeling; B is the sample size of the control group included in the modeling; AUC 1 The area under the curve for modeling all loci of the gene; C is the number of methylation sites identified in the amplified region; AUC 2 is the area under the curve of the methylation site with the best prediction effect.

[0159] Among the 17 gene methylation markers of the present invention, GAD2, ADCYAP1 and C17orf64 have the best comprehensive performance, GAD2 has an advantage in sensitivity, KCNA1 and ADCYAP1 have an advantage in specificity, so the diagnostic efficacy of the combined markers for 107 cases of endometrial cancer and 111 controls was further evaluated. When multi-gene markers are detected in combination, all primer pairs covered by the combined genes in Table 2 are used for detection. Table 7 shows the discrimination effect when two-gene, three-gene and four-gene markers are combined. Specifically, when two gene methylation markers are combined, the AUC of the combination of GAD2 and GYPC is the highest, reaching 0.928, with a sensitivity of 82.2% and a specificity of 86.8%, which is significantly improved compared to the effect of a single gene methylation marker. The remaining genes can reach 0.9 when used in pairs, showing excellent combined diagnostic performance. When the three gene methylation markers are combined, the AUC of the three markers C17orf64, GAD2 and GYPC is the highest, which can reach 0.948, with a sensitivity of 85.4% and a specificity of 91.2%. The model sensitivity is significantly improved compared with the two-marker model, and the accuracy is improved. Among them, the AUC of GAD2, GYPC combined with C17orf64, ADCYAP1, TMEM101 and ZSCAN12 can reach more than 0.94. When ADARB2, CDO1, GRM7, KCNA1, NETO1, SORCS3, STX16, TCTEX1D1 genes are combined with C17orf64, GAD2 or GYPC, the AUC can also reach 0.93. The diagnostic performance can be further improved when the four methylation gene markers are combined, among which the AUC of the marker combination of ADCYAP1, GAD2, GYPC and TMEM101 can reach 0.959, with a sensitivity of 93.9% and a specificity of 86.1%. In the optimal four-marker combination model, GAD2, GYPC and TMEM101 genes have the highest frequency of occurrence and are the key genes in the combination model. The mutual combination AUC of GAD2, GYPC, ADCYAP1, TMEM101, C17orf64, ADHFE1, ZSCAN12, TCTEX1D1, STX16, RYR2, KCNQ5, SORCS3, RYR2 and KCNA1 is close to 0.95, showing complementarity between genes.

[0160] Table 7

[0161]

[0162]

[0163] When five methylation gene markers were included, the AUCs of all combinations were higher than 0.857. The best combination was GAD2, GYPC, ADCYAP1, TMEM101 and STX16, with an AUC of 0.960. The AUC of the GAD2, GYPC, ADCYAP1, C17orf64 and ZSCAN12 gene combination was also 0.960. A total of 130 combinations had an AUC higher than 0.95, and 17 gene markers among the 130 combinations were included in the model multiple times, fully reflecting the importance of each gene in the high-precision model.

[0164] When six gene combination markers were used, the AUCs of all combinations were higher than 0.872. The optimal combination was ADCYAP1, C17orf64, GAD2, GYPC, TCTEX1D1 and ZSCAN12, with an AUC of 0.962. Among them, the AUCs of all the top 100 combinations were higher than 0.956. All 17 gene markers were included in the model multiple times, fully reflecting the importance of each gene in the high-precision model.

[0165] When the seven-gene combination markers were used, the AUCs of all combinations were higher than 0.884. The optimal combination was ADCYAP1, C17orf64, GAD2, GYPC, TCTEX1D1, TMEM101 and ZSCAN12, with an AUC of 0.963. The combination of ADARB2, ADCYAP1, GAD2, GYPC, STX16, TCTEX1D1 and TMEM101 could also achieve the same diagnostic effect. Among the seven-gene combinations, the AUCs of all the top 100 combinations were higher than 0.960. All 17 gene markers were included in the model multiple times, fully reflecting the importance of each gene in the high-precision model.

[0166] When the eight-gene combination markers were used, the AUCs of all combinations were higher than 0.888, and the optimal combination was ADCYAP1, C17orf64, GAD2, GYPC, RYR2, TCTEX1D1, TMEM101 and ZSCAN12, with an AUC of 0.964. Among the eight-gene combinations, the AUCs of all the top 100 combinations were higher than 0.961, and all 17 gene markers were included in the model multiple times, fully reflecting the importance of each gene in the high-precision model.

[0167] In summary, the methylated gene markers or their combination of the present invention can well distinguish endometrial cancer and control individuals, and can be used to prepare a kit for diagnosing endometrial cancer. Moreover, the diagnosis of endometrial cancer or precancerous lesions in the form of two or more gene methylation combinations can significantly improve the sensitivity and specificity.

[0168] It is worth noting that among the 100 cases of endometrial cancer with clear pathological staging in the case group, 73% were in stage I (very early stage), 19% were in stage II, and only 8% were in stages III and IV (mid- and late-stage). This shows that the above-mentioned markers have excellent performance in early endometrial cancer and can be used for the early diagnosis of endometrial cancer.

[0169] Example 4: Diagnostic Effect of Methylation Markers on Endometrial Cancer in Cervical Smear Samples

[0170] In order to evaluate the diagnostic value of the 17 markers included in Example 1 for endometrial cancer in the cervical swab samples, the test samples of this embodiment are cervical swabs of 17 endometrial cancer patients and 14 control participants collected at the Cancer Prevention and Treatment Center of Sun Yat-sen University and the First People's Hospital of Foshan. Cervical swabs are relatively non-invasive sampling schemes, which can be self-sampled and have the advantage of being a non-invasive diagnostic sampling sample. The sample is extracted DNA using the detection method constructed in Example 2 of the present application, DNA bisulfite modification is performed, and a targeted methylation amplification library is constructed, and sequenced by the Illumina platform. The sequencing data is subjected to the above-mentioned biological information analysis process to obtain the methylation levels of the methylation sites in the amplification region of 17 genes. After the data quality control process, 280 site information from 17 genes is included in the analysis. Since the data is quality controlled and filtered according to the sequencing depth of each gene, the sites with a sequencing depth of less than 50 sequences are defined as missing. After this filtering, the number of cases finally included in the analysis of each site is 14-17 cases, and the number of controls is 13-14 cases.

[0171] The diagnostic effect of the genes included in this application on endometrial cancer in cervical swab samples is shown in Table 8. The methylation sites detected in the 17 genes are between 3 and 35. When determining the corresponding gene, all primer pairs covered by the gene in Table 2 are used for detection. By modeling the methylation sites in the same gene using a Logistic model, the optimal cutoff value is taken to evaluate the accuracy of each gene in distinguishing the case group and the control group. Among them, 11 gene methylation markers can achieve completely accurate discrimination of endometrial cancer and control individuals. These genes include ADARB2, ADCYAP1, C17orf64, GAD2, GYPC, KCNA1, KCNQ5, SORCS3, STX16, TMEM101 and ZSCAN12. In addition, GRM7, TCTEX1D1, CDO1 and NETO1 are completely correct in distinguishing the control group, and RYR2 is completely correct in distinguishing the case group, but the specificity of these two gene methylation markers can reach 100%, which has a good effect in the identification of the control. The above results show that when cervical swab samples are used as test samples, the 17 gene methylation markers in this application have excellent diagnostic ability for endometrial cancer.

[0172] Table 8

[0173] Gene A B C D <![CDATA[AUC 1 ]]> Sensitivity (%) Specificity (%) E <![CDATA[AUC 2 ]]> ADARB2 17 14 17 / 17 14 / 14 1.000 100.0 100.0 14 0.893 ADCYAP1 16 14 16 / 16 14 / 14 1.000 100.0 100.0 19 0.746 C17orf64 16 14 16 / 16 14 / 14 1.000 100.0 100.0 29 0.886 GAD2 17 14 17 / 17 14 / 14 1.000 100.0 100.0 33 0.863 GYPC 17 14 17 / 17 14 / 14 1.000 100.0 100.0 27 0.756 KCNA1 17 14 17 / 17 14 / 14 1.000 100.0 100.0 35 0.895 KQT 14 11 17 / 17 11 / 11 1.000 100.0 100.0 16 0.890 SORCS3 17 14 17 / 17 14 / 14 1.000 100.0 100.0 17 0.763 STX16 17 14 17 / 17 14 / 14 1.000 100.0 100.0 10 0.893 TMEM101 16 14 17 / 17 14 / 14 1.000 100.0 100.0 19 0.853 ZSCAN12 15 13 17 / 17 13 / 13 1.000 100.0 100.0 26 0.795 GRM7 17 14 16 / 17 14 / 14 0.962 94.1 100.0 11 0.805 TCTEX1D1 17 14 15 / 17 14 / 14 0.962 88.2 100.0 10 0.796 RYR2 17 14 17 / 17 12 / 14 0.950 100.0 85.7 10 0.794 ADHFE1 17 14 12 / 17 13 / 14 0.853 70.6 92.9 7 0.784 CDO1 17 14 11 / 17 14 / 14 0.840 64.7 100.0 7 0.790 NETO1 16 14 10 / 16 14 / 14 0.768 62.5 100.0 3 0.703

[0174] Note: Item A is the sample size of the case group included in the modeling; Item B is the sample size of the control group included in the modeling; Item C is the correct discrimination of the case group, samples / total samples; Item D is the correct discrimination of the control group, samples / total samples; Item E is the number of methylation sites identified in the amplified region; AUC 1 The area under the curve for modeling all loci of the gene; AUC 2 is the area under the curve of the methylation site with the best prediction effect.

[0175] Example 5: Diagnostic Effect of Methylation Markers on Endometrial Cancer in Vaginal Swab Samples

[0176] In order to evaluate the diagnostic value of the 17 markers included in Example 1 for endometrial cancer in cervical swab samples, the test samples in this example are vaginal swabs from 17 endometrial cancer patients and 14 control participants collected at the Cancer Prevention and Treatment Center of Sun Yat-sen University and Foshan First People's Hospital. Compared with cervical swabs, vaginal swab sampling is shallower in depth and requires less assistance from medical staff. It is one of the more non-invasive and simple and easy-to-operate sampling methods. The samples were extracted from DNA using the detection method constructed in Example 2 of the present application, DNA was modified with bisulfite, a targeted methylation amplification library was constructed, and sequenced on the Illumina platform. The sequencing data was subjected to the above-mentioned bioinformatics analysis process to obtain the methylation levels of the methylation sites in the amplification regions of the 17 genes. After the data quality control process, 280 site information from 17 genes was included in the analysis. Since the data were quality-controlled and filtered according to the sequencing depth of each gene, sites with a sequencing depth of less than 50 sequences were defined as missing. After this filtering, the number of cases finally included in the analysis for each site ranged from 15 to 17, and the number of controls ranged from 11 to 14.

[0177] The diagnostic effects of the genes included in this application on endometrial cancer in vaginal swab samples are shown in Table 9. The number of methylation sites detected in the 17 genes is between 3 and 35. When determining the corresponding gene, all primer pairs covered by the gene in Table 2 are used for detection. By modeling the methylation sites in the same gene using a Logistic model, the area under the curve is between 0.874 and 1. Among them, 13 gene methylation markers achieve completely accurate discrimination between endometrial cancer and control individuals, with an area under the curve of 1, and a sensitivity and specificity of 100%. These gene methylation markers include ADARB2, ADCYAP1, C17orf64, GAD2, GYPC, KCNA1, KCNQ5, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12. In addition, the AUC of GRM7 and CDO1 genes is greater than 0.95, showing excellent diagnostic efficacy. The AUCs of NETO1 and ADHFE1 were 0.929 and 0.874, respectively. The specificity of these two gene methylation markers can reach 100%, and they have good ability in identifying controls. The above results show that when vaginal swab samples are used as test samples, the 17 gene methylation markers in this application have excellent diagnostic ability for endometrial cancer.

[0178] Table 9

[0179] Gene A B C D <![CDATA[AUC 1 ]]> Sensitivity (%) Specificity (%) E <![CDATA[AUC 2 ]]> ADARB2 17 14 17 / 17 14 / 14 1.000 100.0 100.0 14 0.897 ADCYAP1 17 14 17 / 17 14 / 14 1.000 100.0 100.0 19 0.893 C17orf64 17 14 17 / 17 14 / 14 1.000 100.0 100.0 29 0.931 GAD2 17 14 17 / 17 14 / 14 1.000 100.0 100.0 33 0.952 GYPC 17 14 17 / 17 14 / 14 1.000 100.0 100.0 27 0.899 KCNA1 17 14 17 / 17 14 / 14 1.000 100.0 100.0 35 0.943 KQT 15 12 15 / 15 12 / 12 1.000 100.0 100.0 16 0.914 RYR2 17 14 17 / 17 14 / 14 1.000 100.0 100.0 10 0.916 SORCS3 17 14 17 / 17 14 / 14 1.000 100.0 100.0 17 0.868 STX16 17 14 17 / 17 14 / 14 1.000 100.0 100.0 10 0.929 TCTEX1D1 17 14 17 / 17 14 / 14 1.000 100.0 100.0 10 0.954 TMEM101 17 14 17 / 17 14 / 14 1.000 100.0 100.0 19 0.874 ZSCAN12 15 11 17 / 17 14 / 14 1.000 100.0 100.0 26 0.864 GRM7 17 14 16 / 17 13 / 14 0.979 94.1 92.9 11 0.857 CDO1 17 14 15 / 17 14 / 14 0.975 88.2 100.0 7 0.922 NETO1 17 14 12 / 17 14 / 14 0.929 70.6 100.0 3 0.903 ADHFE1 17 14 11 / 17 14 / 14 0.874 64.7 100.0 7 0.800

[0180] Note: Item A is the sample size of the case group included in the modeling; Item B is the sample size of the control group included in the modeling; Item C is the correct discrimination of the case group, samples / total samples; Item D is the correct discrimination of the control group, samples / total samples; Item E is the number of methylation sites identified in the amplified region; AUC 1 The area under the curve for modeling all loci of the gene; AUC 2 is the area under the curve of the methylation site with the best prediction effect.

[0181] Example 6: Detection effect of methylation markers in endometrial cancer tissue and adjacent samples

[0182] To evaluate the signals of the 17 markers included in Example 1 in endometrial cancer tissue, the test samples of this embodiment are 88 endometrial cancer tissues from endometrial cancer patients, 34 paracancerous tissues from endometrial cancer patients, and 20 normal endometrial tissues from benign fibroids collected at the Cancer Prevention and Treatment Center of Sun Yat-sen University and the First People's Hospital of Foshan. The methylation signal in the endometrial cancer tissue can reflect the true situation of the primary lesion and provide reliable verification for the marker signal in this application. The sample is extracted DNA using the detection method constructed in Example 2 of this application, DNA bisulfite modification is performed, a targeted methylation amplification library is constructed, and sequencing is performed on the Illumina platform. The sequencing data is subjected to the above-mentioned biological information analysis process to obtain the methylation levels of the methylation sites in the amplification region of 17 genes. After the data quality control process, 280 site information from 17 genes is included in the analysis.

[0183] The present invention comprehensively compared the methylation rate differences of the 17 gene methylation markers in the present application between cancer and adjacent tissues, and between cancer and normal tissues, and used the signed rank sum test to analyze the inter-group differences. The results showed that among the 280 methylation sites covered by the 17 genes, the methylation rates of cancer tissues at all sites were significantly higher than those of normal tissues (P value range: 6.4×10 -11 -6.8×10 -3 , median P value: 5.4×10 -9 ); the methylation rate of cancer tissues at 246 sites was significantly higher than that of adjacent tissues, accounting for 84%. Figure 6 The distribution of methylation rates of representative methylation sites in 17 genes in normal, adjacent and cancerous tissues is shown. As shown in the figure, the methylation rates of various methylation sites in cancerous tissues are significantly higher than those in normal and adjacent tissues, especially in genes such as GAD2, GRM7, SORCS3, TMEM101, KCNA1, GYPC, CDO1 and C17orf64, where the P value of the difference between cancer and adjacent tissues is less than 1×10 -9 .

[0184] Example 7: Comparison of the changing trends of methylation markers before and after surgery

[0185] If the markers in this application can accurately reflect the presence of endometrial cancer lesions, then the methylation signal will theoretically decrease significantly or even disappear after surgical resection of the lesions. In order to further increase the authenticity evidence of the markers at this level, this embodiment collected urine samples from 36 patients before and 3-5 days after surgery at the Sun Yat-sen University Cancer Center and Foshan First People's Hospital for dynamic monitoring of the markers in this application. Since endometrial cancer surgery mostly involves total hysterectomy, it would be inappropriate to collect cervical swabs and vaginal swabs from postoperative patients, so a more non-invasive urine sample was used as the sample type for monitoring. Because the tumor-related methylation signal released by the lesion after tumor resection will be terminated, the methylation signal of the postoperative patient should theoretically be reduced.

[0186] The methylation rate levels of the 17 gene methylation markers in this application in the preoperative and postoperative paired samples of the same patient were comprehensively compared, and the inter-group difference analysis was performed using the signed rank and paired test. The results showed that among the 280 methylation sites covered by the 17 gene methylation markers, the methylation rate of cancer tissues at 235 sites was significantly higher than that of adjacent tissues, accounting for 80%. Figure 7 The distribution of methylation rates of representative methylation sites in 17 genes in preoperative and postoperative samples is shown. As shown in the figure, compared with preoperative samples, the methylation rates of each methylation site in postoperative samples were significantly reduced. Except for STX16, the representative sites of the remaining 15 genes all reached a significant level, with a P value of 1.7×10 -3 ~1.7×10 -5 Overall, the pre- and post-operative differences in methylation sites such as ADHFE1, TMEM101, KCNA1, ADCYAP1, and GYPC were particularly significant, with P values ​​less than 1×10 -4 level.

[0187] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A methylation gene marker for early detection of endometrial cancer, characterized in that Selected from the following methylation regions in the target gene KCNA1, or a combination of the following methylation regions in at least one of the following genes, ADARB2, ADCYAP1, ADHFE1, C17orf64, CDO1, GRM7, GYPC, KCNQ5, NETO1, RYR2, SORCS3, STX16, TCTEX1D1, TMEM101 and ZSCAN12, and the following methylation regions in KCNA1, with the human genome version hg19 as the reference genome: ADARB2 gene: chr10:1779052-1779183 and chr10:1779756-1779910; ADCYAP1 gene: chr18:907522-907672 and chr18:908206-908385; ADHFE1 gene: chr8:67344466-67344599; C17orf64 gene: chr17:58498643-58498859 and chr17:58498879-58499081; CDO1 gene: chr5:115152259-115152414; GRM7 gene: chr3:6904068-6904274; GYPC gene: chr2:127413900-127414152; KCNA1 gene: chr12:5018675-5018893 and chr12:5019386-5019578; KCNQ5 gene: chr6:73331034-73331188 and chr6:73331252-73331411; NETO1 gene: chr18:70535858-70535996; RYR2 gene: chr1:237205894-237206034; SORCS3 gene: chr10:106400776-106400914 and chr10:106401432-106401587; STX16 gene: chr20:57225138-57225270; TCTEX1D1 gene: chr1:67218010-67218198; TMEM101 gene: chr17:42092213-42092341; ZSCAN12 gene: chr6:28367209-28367379 and chr6:28367431-28367676.

2. A detection primer for early detection of endometrial cancer, characterized in that: For detecting the methylation status of the marker gene methylation region in claim 1, the nucleotide sequence of the detection primer is as follows: ADARB2 gene: The detection primers corresponding to chr10:1779052-1779183 are SEQ ID NOs:1-2; The detection primers corresponding to chr10:1779756-1779910 are SEQ ID NOs:3-4; ADCYAP1 gene: The detection primers corresponding to chr18:907522-907672 are SEQ ID NOs:5-6; The detection primers corresponding to chr18:908206-908385 are SEQ ID NOs:7-8; ADHFE1 gene: The detection primers corresponding to chr8:67344466-67344599 are SEQ ID NOs:9-10; C17orf64 gene: The detection primers corresponding to chr17:58498643-58498859 are SEQ ID NOs:11-12; the detection primers corresponding to chr17:58498879-58499081 are SEQ ID NOs:13-14; CDO1 gene: The detection primers corresponding to chr5:115152259-115152414 are SEQ ID NOs:15-16; GRM7 gene: The detection primers corresponding to chr3:6904068-6904274 are SEQ ID NOs:23-24; GYPC gene: The detection primers corresponding to chr2:127413900-127414152 are SEQ ID NOs:25-26; KCNA1 gene: The detection primers corresponding to chr12:5018675-5018893 are SEQ ID NOs:27-28; The detection primers corresponding to chr12:5019386-5019578 are SEQ ID NOs:29-30; KCNQ5 gene: The detection primers corresponding to chr6:73331034-73331188 are SEQ ID NOs:31-32; the detection primers corresponding to chr6:73331252-73331411 are SEQ ID NOs:33-34; NETO1 gene: The detection primers corresponding to chr18:70535858-70535996 are SEQ ID NO:35-36; RYR2 gene: The detection primers corresponding to chr1:237205894-237206034 are SEQ ID NO:37-38; SORCS3 gene: The detection primers corresponding to chr10:106400776-106400914 are SEQ ID NOs:39-40; the detection primers corresponding to chr10:106401432-106401587 are SEQ ID NOs:41-42; STX16 gene: The detection primers corresponding to chr20:57225138-57225270 are SEQ ID NOs:43-44; TCTEX1D1 gene: The detection primers corresponding to chr1:67218010-67218198 are SEQ ID NOs:45-46; TMEM101 gene: The detection primers corresponding to chr17:42092213-42092341 are SEQ ID NOs:47-48; ZSCAN12 gene: The detection primers corresponding to chr6:28367209-28367379 are SEQ ID NOs:49-50; The detection primers corresponding to chr6:28367431-28367676 are SEQ ID NOs:51-52.

3. Use of a reagent for detecting the methylation region of a marker gene in the preparation of a detection kit or device, characterized in that The detection kit or device is used for detecting, screening or diagnosing endometrial cancer; the marker gene methylation region is the marker gene methylation region according to claim 1.

4. The use according to claim 3, characterized in that: The reagent comprises at least one of an antibody, a probe, a primer and a mass spectrometry detection reagent specifically for detecting the methylation region of the marker gene, wherein the primer comprises the detection primer according to claim 2.

5. The use according to claim 3 or 4, characterized in that: The detection sample of the detection kit or device includes at least one of a body fluid sample, an exfoliated cell collection sample and a tumor tissue sample.

6. The use according to claim 5, characterized in that: The body fluid sample includes at least one of urine and blood; the exfoliated cell collection sample includes at least one of a swab, a brush and an lavage fluid.

7. A multiplex PCR detection kit for early screening and diagnosis of endometrial cancer, characterized in that A reagent for detecting the methylation region of the marker gene according to claim 1; The reagent comprises at least one of an antibody, a probe, a primer and a mass spectrometry detection reagent specifically for detecting the methylation region of the marker gene, wherein the primer comprises the detection primer according to claim 2.

8. Use of the methylation gene marker according to claim 1 in the preparation of a diagnostic product for endometrial cancer.

9. Use of the multiplex PCR detection kit according to claim 7 in the preparation of endometrial cancer diagnosis products.

10. The use according to claim 8 or 9, characterized in that: The diagnostic product includes any one of a kit, a preparation and a chip.

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