Marker for detection of cervical cancer DNA methylation and application thereof

Abstract

The present application relates to the technical field of cervical cancer gene detection, especially IPC C12Q1, more particularly to a marker for DNA methylation detection of cervical cancer and application thereof. The present application determines the combined diagnosis of 5 or 6 genes by detecting the degree of DNA methylation of 12 genes in 228 clinical samples, so as to improve the detection rate of HSIL (high-grade squamous intraepithelial lesion) and cervical cancer.

Description

Technical Field

[0001] This invention relates to the field of cervical cancer gene detection technology, particularly to IPC C12Q1, and more specifically to a biomarker for cervical cancer DNA methylation detection and its application. Background Technology

[0002] Cervical cancer is the most common gynecological malignancy and one of the leading causes of cancer-related deaths in women. It is the fourth leading cause of cancer incidence and mortality among women worldwide, accounting for 6.5% of all new cancer cases in women each year.1 In my country, it is conservatively estimated that there are approximately 100,000 confirmed cases and 30,000 deaths annually.

[0003] Regarding current new technologies for cervical cancer screening, the WHO's 2021 "Guidelines for Screening and Treatment of Cervical Precancerous Lesions (Second Edition)" identifies DNA methylation testing as a novel molecular detection technique. DNA methylation testing is currently under evaluation by the WHO and will be incorporated into the updated guidelines. DNA methylation is recognized as the most common epigenetic abnormality in the precancerous and advanced stages of cancer. Tumor suppressor gene DNA methylation is one of the key mechanisms for the inactivation of tumor suppressor genes in the early stages of tumorigenesis. DNA methylation of some key tumor suppressor genes in cervical cancer has been confirmed in numerous studies. Among the host genes with the most studied and targeted epigenetic changes associated with cervical cancer and its precursors are cell adhesion molecule 1 (CADM1); death-associated protein kinase 1 (DAPK1); myelin and lymphocyte, T cell differentiation protein (MAL); pairing box 1 (PAX1); telomerase reverse transcriptase (TERT), etc.; currently, there are also two CADM1 and MAL, three CADM1, MAL and miR124-2, and four JAM3, EPB41L3, TERT and C130RF1. Eight, five marker groups (PAX1, DAPK1, RARβ, WIF1, and SLIT2) have been used for combined diagnosis, but currently, the three methylation groups (JAM3 / ANKRD18CP, C13ORF18 / JAM3 / ANKRD18CP, and JAM3 / GFRA1 / ANKRD18CP) have the highest combined diagnostic accuracy for detecting CIN2+ in cervical samples; their sensitivities have been reported as 72%, 74%, and 73%, respectively, with corresponding specificities of 79%, 76%, and 77%. Therefore, there is a need to develop a highly accurate biomarker for the detection of DNA methylation in cervical cancer. Summary of the Invention

[0004] To address the problems in the prior art, the first aspect of the present invention provides a biomarker for the detection of DNA methylation in cervical cancer, including one or more of SOX1, PAX1, EPB41L3, JAM3, SFRP4, CADM1, FAM19A4, PHACTR3, PRDM14, SST, ZIC1, and ZNF671.

[0005] In some preferred embodiments, the biomarkers for cervical cancer DNA methylation detection are FAM19A4, PHACTR3, SST, ZIC1, PAX1 or FAM19A4, PHACTR3, SST, ZIC1, PAX1, SOX1 or FAM19A4, PHACTR3, SST, ZIC1, PAX1, ZNF671.

[0006] The method for screening biomarkers for cervical cancer DNA methylation detection includes the following steps:

[0007] S1: DNA methylation of 12 genes was detected in HeLa and SiHa cancer cell lines, and significant DNA methylation was found in all 12 genes.

[0008] S2: In 228 clinical samples, methylation of 12 genes was detected in each sample to obtain methylation results of 12 genes;

[0009] S3: A comprehensive score is given for the results of gene DNA methylation detection.

[0010] Preferably, the 228 clinical samples were from Shanghai First Maternity and Infant Hospital.

[0011] Preferably, the specific process for detecting DNA methylation of the 12 genes is as follows:

[0012] M1: Extract TCT samples using a TCT DNA extraction kit;

[0013] M2: Performs bisulfite conversion;

[0014] M3: Nucleic acid purification;

[0015] M4: Methylation-specific quantitative PCR detection;

[0016] M5: DNA methylation data analysis.

[0017] Preferably, the bisulfite conversion uses a bisulfite conversion kit.

[0018] Preferably, the process of using the bisulfite conversion kit is as follows: take a DNA sample, add Bisulfite solution and DNA protection solution, and then use a PCR instrument for conversion. Set the PCR parameters as follows: 99℃ for 15 min; 50℃ for 30 min; 99℃ for 5 min; 50℃ for 90 min.

[0019] Preferably, the kit used for M4 detection is a methylation-specific real-time PCR kit.

[0020] Preferably, the quantitative PCR program in M4 is as follows: pre-denaturation: 94℃, 5 min; PCR cycling: 94℃, 15 sec; 60℃, 30 sec; 50 cycles; collecting fluorescence signal at 60℃ in the second step of the PCR cycle; 37℃, 10 sec; cooling.

[0021] Preferably, the TCT DNA extraction kit is purchased from Shanghai Ruian Gene Technology Co., Ltd.

[0022] Preferably, the bisulfite conversion kit was purchased from Shanghai Ruian Gene Technology Co., Ltd.

[0023] Preferably, the methylation-specific real-time PCR kit was purchased from Shanghai Ruian Gene Technology Co., Ltd.

[0024] Preferably, the comprehensive scoring method in S3 is to select 142 clinical samples, count the number of combined genes detected in healthy, LSIL, HSIL, and cancer clinical samples, the number of positive, negative, QC unqualified, and the number of valid samples, and calculate the detection rate.

[0025] The second aspect of the present invention provides an application of a biomarker for the detection of DNA methylation in cervical cancer, which is applied to a cervical cancer DNA methylation detection kit.

[0026] This invention detected the DNA methylation levels of 12 genes in 228 clinical samples. Based on the data of DNA methylation of these 12 genes, different gene combinations were selected to achieve the highest detection rate with the fewest possible combinations. This invention provides a combination of biomarkers with high detection rates for detecting patients at the HSIL and cervical cancer stages, with a detection rate of 77.8% for HSIL and 100% for cervical cancer. The inventors creatively discovered that 15 gene biomarkers were selected from cervical cancer-related literature, and after verification, 12 of these genes—SOX1, PAX1, EPB41L3, JAM3, SFRP4, CADM1, FAM19A4, PHACTR3, PRDM14, SST, ZIC1, and ZNF671—showed DNA methylation in cervical cancer cell lines. DNA methylation of 12 genes was detected in each of 228 clinical samples. This yielded DNA methylation values ​​and ROC curves for each gene in healthy individuals, those with LSIL (mild cervical dysplasia), HSIL, and at different stages of cervical cancer. The detection rates of cervical cancer-related gene DNA methylation at different stages of cervical cancer were also obtained. Using this data, the inventors creatively combined several marker genes for joint diagnosis, obtaining a comprehensive score for combined marker diagnosis. Higher detection rates of HSIL and cervical cancer indicate higher accuracy in combined diagnosis. The marker combination with high detection rates in this invention can accurately detect patients at both the HSIL and cervical cancer stages, with a detection rate of 77.8% for HSIL and 100% for cervical cancer.

[0027] This invention employs a combination of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and SOX1 biomarkers for diagnosis, or a combination of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and ZNF671 biomarkers, or a combination of FAM19A4, PHACTR3, SST, ZIC1, and PAX1 biomarkers for diagnosis, all of which can improve the accuracy of distinguishing between normal, LSIL and HSIL, and cervical cancer risk. The inventors have discovered that some patients with mild cervical dysplasia LSIL, also known as CIN I, do not require further colposcopy during cervical cancer screening. To better differentiate between normal cervical tissue, LSIL, HSIL, and cervical cancer, this invention employs a combination of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and SOX1 biomarkers for diagnosis, or a combination of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and ZNF671 biomarkers, or a combination of FAM19A4, PHACTR3, SST, ZIC1, and PAX1 biomarkers for diagnosis, thereby improving the sensitivity and specificity of early cervical cancer diagnosis.

[0028] Beneficial effects

[0029] This invention detects the DNA methylation level of 12 genes using 228 clinical samples. Based on the DNA methylation data of the 12 genes, different gene combinations are selected to achieve the highest detection rate with the fewest gene combinations. This invention provides a combination of biomarkers with a high detection rate to detect patients at the HSIL and cervical cancer stages, with a detection rate of 77.8% for HSIL and 100% for cervical cancer.

[0030] This invention employs a combination of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and SOX1 biomarkers for diagnosis, or a combination of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and ZNF671 biomarkers, or a combination of FAM19A4, PHACTR3, SST, ZIC1, and PAX1 biomarkers for diagnosis, all of which can improve the accuracy of distinguishing between normal, LSIL and HSIL, and cervical cancer risk.

[0031] This invention confirms that DNA methylation of 12 genes is closely related to precancerous lesions and cervical cancer in HPV-infected cervical cancer, and that combined gene therapy can improve the detection rate of HSIL and cervical cancer. Attached Figure Description

[0032] Figure 1 For 228 clinical samples, 12 genes deltaC T Value data; it can be seen that when the patient's disease is HSIL and cervical cancer, the corresponding deltaC of the 12 genes is... T The values ​​are all low.

[0033] Figure 2 The ROC curves are for the 12 markers in Example 1.

[0034] Figure 3 For the detection of 11 cervical cancer-related genes in the healthy stage in Example 1, delta C T Value heatmap.

[0035] Figure 4 For the detection of 11 cervical cancer-related genes in the LSIL stage in Example 1, delta C T Value heatmap.

[0036] Figure 5 For the detection of 11 cervical cancer-related genes in the HSIL stage in Example 1, delta C T Value heatmap.

[0037] Figure 6 For the detection of 11 cervical cancer-related genes in the Cancer stage in Example 1, delta C T Value heatmap.

[0038] Figure 7 The ROC curves for the six markers in Example 8 are shown. Detailed Implementation

[0039] Example 1

[0040] The biomarkers for cervical cancer DNA methylation detection described in Example 1 are FAM19A4, PHACTR3, SST, ZIC1, PAX1, and SOX1.

[0041] The method for screening biomarkers for cervical cancer DNA methylation detection includes the following steps:

[0042] S1: DNA methylation of 12 genes was detected in HeLa and SiHa cancer cell lines, and significant DNA methylation was found in all 12 genes.

[0043] S2: In 228 clinical samples, methylation of 12 genes was detected in each sample to obtain methylation results of 12 genes;

[0044] S3: The DNA methylation detection results of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and SOX1 markers were comprehensively scored, and the detection results are shown in Table 1.

[0045] The 228 clinical samples were from Shanghai First Maternity and Infant Hospital.

[0046] The specific process for detecting DNA methylation in the 12 genes is as follows:

[0047] M1: Extract TCT samples using a TCT DNA extraction kit;

[0048] M2: Performs bisulfite conversion;

[0049] M3: Nucleic acid purification;

[0050] M4: Methylation-specific quantitative PCR detection;

[0051] M5: DNA methylation data analysis.

[0052] The ROC curves of 12 genes from 228 clinical samples in the DNA methylation data analysis are shown below. Figure 2 As shown.

[0053] The detection rates of DNA methylation of 11 cervical cancer-related genes at different stages of cervical cancer development in the DNA methylation data analysis are shown in Table 2.

[0054] The DNA methylation data analysis included the detection of 11 cervical cancer-related genes at different stages of cervical cancer development (delta C). T Value heatmap, such as Figures 3-6 As shown.

[0055] The bisulfite conversion uses a bisulfite conversion kit.

[0056] The procedure for using the bisulfite conversion kit is as follows: Take 10 μL of DNA sample, add 47 μL of Bisulfite solution and 13 μL of DNA protection solution, and then use a PCR instrument for conversion. Set the PCR parameters as follows: 99℃, 15 min; 50℃, 30 min; 99℃, 5 min; 50℃, 90 min.

[0057] The kit used for M4 detection is a methylation-specific real-time PCR kit.

[0058] The quantitative PCR program in M4 is as follows: pre-denaturation: 94℃, 5 min; PCR cycling: 94℃, 15 sec; 60℃, 30 sec; 50 cycles; collect fluorescence signal at 60℃ in the second step of PCR cycling; 37℃, 10 sec, cooling.

[0059] The TCT DNA extraction kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0060] The bisulfite conversion kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0061] The methylation-specific real-time PCR kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0062] The comprehensive scoring method in S3 involves selecting 142 clinical samples, statistically analyzing the number of combined genes detected in healthy, LSIL, HSIL, and cancer clinical samples, as well as the number of positive, negative, QC-unqualified, and valid samples, and calculating the detection rate.

[0063] Example 2

[0064] The biomarkers for cervical cancer DNA methylation detection described in Example 2 are FAM19A4, PHACTR3, SST, ZIC1, and PAX1.

[0065] The method for screening biomarkers for cervical cancer DNA methylation detection includes the following steps:

[0066] S1: DNA methylation of 12 genes was detected in HeLa and SiHa cancer cell lines, and significant DNA methylation was found in all 12 genes.

[0067] S2: In 228 clinical samples, methylation of 12 genes was detected in each sample to obtain methylation results of 12 genes;

[0068] S3: The results of DNA methylation detection of FAM19A4, PHACTR3, SST, ZIC1, and PAX1 markers were comprehensively scored, and the detection results are shown in Table 3.

[0069] The 228 clinical samples were from Shanghai First Maternity and Infant Hospital.

[0070] The specific process for detecting DNA methylation in the 12 genes is as follows:

[0071] M1: Extract TCT samples using a TCT DNA extraction kit;

[0072] M2: Performs bisulfite conversion;

[0073] M3: Nucleic acid purification;

[0074] M4: Methylation-specific quantitative PCR detection;

[0075] M5: DNA methylation data analysis.

[0076] The ROC curves of 12 genes from 228 clinical samples in the DNA methylation data analysis are shown below. Figure 2 As shown.

[0077] The detection rates of DNA methylation of 11 cervical cancer-related genes at different stages of cervical cancer development in the DNA methylation data analysis are shown in Table 2.

[0078] The DNA methylation data analysis included the detection of 11 cervical cancer-related genes at different stages of cervical cancer development (delta C). T Value heatmap, such as Figures 3-6 As shown.

[0079] The bisulfite conversion uses a bisulfite conversion kit.

[0080] The procedure for using the bisulfite conversion kit is as follows: Take 10 μL of DNA sample, add 47 μL of Bisulfite solution and 13 μL of DNA protection solution, and then use a PCR instrument for conversion. Set the PCR parameters as follows: 99℃, 15 min; 50℃, 30 min; 99℃, 5 min; 50℃, 90 min.

[0081] The kit used for M4 detection is a methylation-specific real-time PCR kit.

[0082] The quantitative PCR program in M4 is as follows: pre-denaturation: 94℃, 5 min; PCR cycling: 94℃, 15 sec; 60℃, 30 sec; 50 cycles; collect fluorescence signal at 60℃ in the second step of PCR cycling; 37℃, 10 sec, cooling.

[0083] The TCT DNA extraction kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0084] The bisulfite conversion kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0085] The methylation-specific real-time PCR kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0086] The comprehensive scoring method in S3 involves selecting 142 clinical samples, statistically analyzing the number of combined genes detected in healthy, LSIL, HSIL, and cancer clinical samples, as well as the number of positive, negative, QC-unqualified, and valid samples, and calculating the detection rate.

[0087] Example 3

[0088] The biomarkers for cervical cancer DNA methylation detection described in Example 3 are SOX1, PAX1, EPB41L3, JAM3, SFRP4, CADM1, FAM19A4, PHACTR3, PRDM14, SST, and ZIC1.

[0089] The method for screening biomarkers for cervical cancer DNA methylation detection includes the following steps:

[0090] S1: DNA methylation of 12 genes was detected in HeLa and SiHa cancer cell lines, and significant DNA methylation was found in all 12 genes.

[0091] S2: In 228 clinical samples, methylation of 12 genes was detected in each sample to obtain methylation results of 12 genes;

[0092] S3: The DNA methylation detection results of SOX1, PAX1, EPB41L3, JAM3, SFRP4, CADM1, FAM19A4, PHACTR3, PRDM14, SST, and ZIC1 markers were comprehensively scored, and the detection results are shown in Table 4.

[0093] The 228 clinical samples were from Shanghai First Maternity and Infant Hospital.

[0094] The specific process for detecting DNA methylation in the 12 genes is as follows:

[0095] M1: Extract TCT samples using a TCT DNA extraction kit;

[0096] M2: Performs bisulfite conversion;

[0097] M3: Nucleic acid purification;

[0098] M4: Methylation-specific quantitative PCR detection;

[0099] M5: DNA methylation data analysis.

[0100] The ROC curves of 12 genes from 228 clinical samples in the DNA methylation data analysis are shown below. Figure 2 As shown.

[0101] The detection rates of DNA methylation of 11 cervical cancer-related genes at different stages of cervical cancer development in the DNA methylation data analysis are shown in Table 2.

[0102] The DNA methylation data analysis included the detection of 11 cervical cancer-related genes at different stages of cervical cancer development (delta C). T Value heatmap, such as Figures 3-6 As shown.

[0103] The bisulfite conversion uses a bisulfite conversion kit.

[0104] The procedure for using the bisulfite conversion kit is as follows: Take 10 μL of DNA sample, add 47 μL of Bisulfite solution and 13 μL of DNA protection solution, and then use a PCR instrument for conversion. Set the PCR parameters as follows: 99℃, 15 min; 50℃, 30 min; 99℃, 5 min; 50℃, 90 min.

[0105] The kit used for M4 detection is a methylation-specific real-time PCR kit.

[0106] The quantitative PCR program in M4 is as follows: pre-denaturation: 94℃, 5 min; PCR cycling: 94℃, 15 sec; 60℃, 30 sec; 50 cycles; collect fluorescence signal at 60℃ in the second step of PCR cycling; 37℃, 10 sec, cooling.

[0107] The TCT DNA extraction kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0108] The bisulfite conversion kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0109] The methylation-specific real-time PCR kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0110] The comprehensive scoring method in S3 involves selecting 142 clinical samples, statistically analyzing the number of combined genes detected in healthy, LSIL, HSIL, and cancer clinical samples, as well as the number of positive, negative, QC-unqualified, and valid samples, and calculating the detection rate.

[0111] Example 4

[0112] The biomarkers for cervical cancer DNA methylation detection described in Example 4 are FAM19A4, PHACTR3, and PAX1.

[0113] The method for screening biomarkers for cervical cancer DNA methylation detection includes the following steps:

[0114] S1: DNA methylation of 12 genes was detected in HeLa and SiHa cancer cell lines, and significant DNA methylation was found in all 12 genes.

[0115] S2: In 228 clinical samples, methylation of 12 genes was detected in each sample to obtain methylation results of 12 genes;

[0116] S3: The results of DNA methylation detection of FAM19A4, PHACTR3, and PAX1 markers were comprehensively scored, and the detection results are shown in Table 5.

[0117] The 228 clinical samples were from Shanghai First Maternity and Infant Hospital.

[0118] The specific process for detecting DNA methylation in the 12 genes is as follows:

[0119] M1: Extract TCT samples using a TCT DNA extraction kit;

[0120] M2: Performs bisulfite conversion;

[0121] M3: Nucleic acid purification;

[0122] M4: Methylation-specific quantitative PCR detection;

[0123] M5: DNA methylation data analysis.

[0124] The ROC curves of 12 genes from 228 clinical samples in the DNA methylation data analysis are shown below. Figure 2 As shown.

[0125] The detection rates of DNA methylation of 11 cervical cancer-related genes at different stages of cervical cancer development in the DNA methylation data analysis are shown in Table 2.

[0126] The DNA methylation data analysis included the detection of 11 cervical cancer-related genes at different stages of cervical cancer development (delta C). T Value heatmap, such as Figures 3-6 As shown.

[0127] The bisulfite conversion uses a bisulfite conversion kit.

[0128] The procedure for using the bisulfite conversion kit is as follows: Take 10 μL of DNA sample, add 47 μL of Bisulfite solution and 13 μL of DNA protection solution, and then use a PCR instrument for conversion. Set the PCR parameters as follows: 99℃, 15 min; 50℃, 30 min; 99℃, 5 min; 50℃, 90 min.

[0129] The kit used for M4 detection is a methylation-specific real-time PCR kit.

[0130] The quantitative PCR program in M4 is as follows: pre-denaturation: 94℃, 5 min; PCR cycling: 94℃, 15 sec; 60℃, 30 sec; 50 cycles; collect fluorescence signal at 60℃ in the second step of PCR cycling; 37℃, 10 sec, cooling.

[0131] The TCT DNA extraction kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0132] The bisulfite conversion kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0133] The methylation-specific real-time PCR kit was purchased from Shanghai Ruiang Gene Technology Co., Ltd.

[0134] The comprehensive scoring method in S3 involves selecting 142 clinical samples, statistically analyzing the number of combined genes detected in healthy, LSIL, HSIL, and cancer clinical samples, as well as the number of positive, negative, QC-unqualified, and valid samples, and calculating the detection rate.

[0135] Example 5

[0136] The specific implementation method of Example 5 is the same as that of Example 1, except that the markers used for cervical cancer DNA methylation detection are SST and ZIC1.

[0137] Step S3 involves comprehensively scoring the DNA methylation detection results of SST and ZIC1 markers, and the detection results are shown in Table 6.

[0138] Example 6

[0139] The specific implementation of Example 6 is the same as that of Example 1, except that the biomarkers for cervical cancer DNA methylation detection are PAX1 and PHACTR3.

[0140] Step S3 involves comprehensively scoring the DNA methylation detection results of PAX1 and PHACTR3 markers. The detection results are shown in Table 7.

[0141] Example 7

[0142] The specific implementation of Example 7 is the same as that of Example 1, except that the biomarkers for cervical cancer DNA methylation detection are PAX1 and FAM19A4.

[0143] Step S3 involves comprehensively scoring the DNA methylation detection results of PAX1 and FAM19A4 markers. The detection results are shown in Table 8.

[0144] Example 8

[0145] The specific implementation of Example 8 is the same as that of Example 1, except that the biomarkers for cervical cancer DNA methylation detection are FAM19A4, PHACTR3, SST, ZIC1, PAX1, and ZNF671.

[0146] Step S3 involves comprehensively scoring the DNA methylation detection results of FAM19A4, PHACTR3, SST, ZIC1, PAX1, and ZNF671 biomarkers. The number of original and correctly predicted combinatorial genes in healthy, LSIL, HSIL, and cancer samples, as well as the total clinical samples, are statistically analyzed, and the accuracy rate is calculated. The results are recorded in Table 9.

[0147] Table 1

[0148]

[0149]

[0150] Table 2

[0151]

[0152] Table 3

[0153] Number of tests 23 47 18 54 Positive 0 5 14 45 Negative 23 38 4 0 QC failure 0 4 0 9 Valid sample size 23 43 18 45 Detection rate 0.0％ 11.6％ 77.8％ 100％

[0154] Table 4

[0155] Number of tests 23 47 18 54 Positive 0 5 14 45 Negative 23 38 4 0 QC failure 0 4 0 9 Valid sample size 23 43 18 45 Detection rate 0.0％ 11.6％ 77.8％ 100％

[0156] Table 5

[0157] Number of tests 23 47 18 54 Positive 0 5 14 42 Negative 23 38 4 3 QC failure 0 4 0 9 Valid sample size 23 43 18 45 Detection rate 0.0％ 11.6％ 77.8％ 93.3％

[0158] Table 6

[0159] Number of tests 23 47 18 54 Positive 0 43 11 45 Negative 23 0 7 0 QC failure 0 4 0 9 Valid sample size 23 43 18 45 Detection rate 0.0％ 0.0％ 61.1％ 100％

[0160] Table 7

[0161] Number of tests 23 47 18 54 Positive 0 4 14 41 Negative 23 39 4 4 QC failure 0 4 0 9 Valid sample size 23 43 18 45 Detection rate 0.0％ 9.3％ 77.8％ 91.1％

[0162] Table 8

[0163] Number of tests 23 47 18 54 Positive 0 4 13 39 Negative 23 39 5 6 QC failure 0 4 0 9 Valid sample size 23 43 18 45 Detection rate 0.0％ 9.3％ 72.2％ 86.7％

[0164] Table 9

[0165] Normal 114 109 95.61％ LSIL 46 43 93.48％ HSIL 21 15 71.43％ Cervical Cancer 47 46 97.87％ total 228 213 93.42％

[0166] The ROC curves of the 6 genes in Example 8 are as follows: Figure 7 As shown, the six gene markers in Example 8 all showed good predictive results.

Claims

1. A biomarker for detecting DNA methylation in cervical cancer, characterized in that, The biomarkers used for cervical cancer DNA methylation detection are FAM19A4, PHACTR3, SST, ZIC1, PAX1, or FAM19A4, PHACTR3, SST, ZIC1, PAX1, SOX1, or FAM19A4, PHACTR3, SST, ZIC1, PAX1, ZNF671.

2. The application of a reagent for detecting cervical cancer marker DNA methylation in the preparation of a cervical cancer DNA methylation detection kit, characterized in that, The markers are FAM19A4, PHACTR3, SST, ZIC1, PAX1, or FAM19A4, PHACTR3, SST, ZIC1, PAX1, SOX1, or FAM19A4, PHACTR3, SST, ZIC1, PAX1, ZNF671.

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