Methylation marker, detection reagent and detection model for detecting liver cancer

Abstract

The invention belongs to the field of molecular biological detection, particularly belongs to the field of liver cancer detection, and more particularly relates to a methylation marker chr1: 34792772-34792982 for auxiliary detection of liver cancer. According to the present invention, the sensitivity, the specificity and the AUC of the liver cancer detection by using the marker of the present invention are respectively 83.33%, 83.33% and 0.833; according to the present invention, the liver cancer can be clinically detected only by detecting the 210bp length (one probe range) of the marker, such that the cost and the time are saved, the patient really having the liver cancer malignant risk can be detected in the early stage of the canceration process with high sensitivity and high specificity, and the detection cost performance is high.

Description

Technical Field

[0001] The present invention belongs to the field of molecular biology detection, specifically, to the field of liver cancer detection, and more specifically, to methylation markers, detection reagents and detection models for detecting liver cancer. Background Art

[0002] According to the World Health Organization, primary liver cancer (PLC) ranks sixth in incidence and third in mortality among all malignant tumors. Hepatocellular carcinoma (HCC) accounts for 85% of all PLC cases, and the 5-year survival rate of patients is low (10%-19%). There are 292 million HCC-related deaths worldwide, more than half of which are related to HBV infection, making HBV infection the main factor in HCC carcinogenesis. Through clinical observation, clinicians have reached a consensus on the pathogenic role of HBV in the progression of liver disease from hepatitis to cirrhosis and further to HCC. At the time of diagnosis, most HCC patients are already in stage C or D (Barcelona Clinic Liver Cancer [BCLC] staging), so radical treatment such as surgical resection is no longer feasible. In contrast, the 5-year survival rate of BCLC stage A HCC can be as high as 70%. The serum alpha-fetoprotein (AFP) test combined with biennial liver ultrasound is currently the main strategy for screening HCC in high-risk patients. However, AFP has a low accuracy, with a specificity of 85%-90% and a sensitivity of 18%-60%, and is particularly inefficient for early liver tumors.

[0003] Progress in epigenetic research has far-reaching significance for the early diagnosis and treatment of liver cancer. Evidence shows that hypermethylation of CpG islands in the promoter of tumor suppressor genes is an important mechanism of gene inactivation. Transcriptional inactivation of different genes will affect the cell cycle, DNA repair, apoptosis, etc., and is closely related to the occurrence and development of cancer. Gene methylation refers to the process in which cytosine (C) in CpG dinucleosides on DNA molecules selectively adds methyl groups to form 5'-methylcytosine under the action of enzymes. In patients with liver cancer, methylation of CpG islands in gene promoter regions is a relatively common phenomenon. Clinically, it is believed that the detection of methylated gene markers in tissue cells and body fluids of patients with liver cancer is an effective auxiliary detection method for liver cancer, which has the value of improving the detection rate of liver cancer. If it is combined with cytopathological detection, it can greatly improve the efficiency of liver cancer diagnosis, shorten the detection cycle, and improve the accuracy of diagnosis.

[0004] Therefore, there is a need in the art for some markers, in particular, markers with good sensitivity and specificity in early liver cancer. Summary of the invention

[0005] In view of this, in a first aspect, the present invention provides a methylation marker for assisting in the detection of liver cancer:

[0006] chr1:34792772-34792982.

[0007] The sensitivity, specificity and AUC of the marker of the present invention for liver cancer detection are 83.33%, 83.33% and 0.833 respectively. The marker of the present invention only needs to detect the marker 210bp in length (one probe range) to detect liver cancer in clinical practice, saving both cost and time, and can detect patients who are really at risk of liver cancer malignant transformation at the early stage of the cancer transformation process with high sensitivity and high specificity, and the detection cost performance is high.

[0008] Specifically, the methylation marker of the present invention is located at the sequence shown at position 34792772 to position 34792982 on chromosome 1 of the human genome, specifically, as shown below:

[0009] ACCTGGTGGAGAGAACAGAGGAGAGGAAGGGTAGGTCAGCCCCTCTTGCCCCTCCCCACCGCAAATCACACAGGCCCACCTCCCCGGAGTGGGTTTAGGGAGTCTGCACCTCCCAGTCCCCGCCCCCGCCCTCTCCAGCGCCCGCCGCCCTCCCCGTCGCGTTTCCTGCCCCCACCCCGCCCCTCTGCGCTATTTAAGGCGCCCCC.

[0010] In a second aspect, the present invention provides a composition for assisting in the detection of methylation markers for liver cancer, the composition comprising a detection reagent for detecting the methylation level in the following regions:

[0011] chr1:34792772-34792982.

[0012] Among them, chr1:34792772-34792982 shows a section of the CpG island in the gene promoter region.

[0013] In the present invention, "CpG island" is the abbreviation of cytosine (C)-phosphate (p)-guanine (G), which refers to some regions rich in CpG dinucleotides on the genome, with a length of 300 to 3000 bp.

[0014] In some embodiments, the detection reagent of the present invention can be used to detect the methylation level of a CpG island or a sequence on a CpG island in a corresponding gene region present in a sample.

[0015] In the present invention, a "sample" is a biological sample selected from an individual, specifically, for example, selected from histological sections, tissue biopsies / paraffin-embedded tissues, and the like.

[0016] In the present invention, "detection reagent" refers to a reagent for detecting the methylation level of a gene in a sample, wherein the methylation level is measured by amplification-sequencing, chip detection, or methylation fluorescence quantitative PCR.

[0017] In some specific embodiments, the methylation level detection reagent can also be a detection reagent for detecting the average methylation level of a gene fragment.

[0018] In some specific embodiments, the methylation level detection reagent can also be a detection reagent for detecting one or more methylation sites within a gene segment.

[0019] In some specific embodiments, the detection reagents include, but are not limited to, nucleic acid primers and sequencing Tag sequences, for measuring methylation levels by amplification-sequencing.

[0020] In some specific embodiments, the detection reagent includes but is not limited to a chip, wherein the chip is a methylation chip having a probe that specifically binds to a methylation region, and the chip is used to measure the methylation level.

[0021] In some specific embodiments, the detection reagents include, but are not limited to, nucleic acid primers and nucleic acid probes for measuring methylation levels by methylation fluorescence quantitative PCR.

[0022] Furthermore, the detection reagent also includes an internal standard primer and an internal standard probe.

[0023] In a specific embodiment, the target of the internal standard primer and probe is the ACTB gene.

[0024] When the detection reagent includes nucleic acid primers and nucleic acid probes, the detection reagent detects the methylation level of nucleic acid in the sample by methylation fluorescent quantitative PCR.

[0025] In the present invention, "methylation fluorescent quantitative PCR" refers to converting the region to be detected by sulfite or digesting it with a methylation-sensitive restriction endonuclease, and then performing fluorescent quantitative PCR detection using primers and probes specifically designed for the detection target, thereby obtaining the methylation level of the region to be detected.

[0026] The above reagent combination may also include other reagents, specifically, for example, various reagents required for pre-treatment or pre-processing of the sample, such as a sample release agent for extracting sample nucleic acid, a purification agent for purifying sample nucleic acid, bisulfite or bisulfite used for conversion, etc.

[0027] In a fourth aspect, the present invention provides a model for assisting the detection of liver cancer, wherein the model is:

[0028] HCC_score=50+50*[(M-1 / 2*(N_M+C_M)] / [1 / 2*abs(C_M-N_M)]

[0029] Wherein, M is the methylation value of the marker of the present invention of the subject, N_M is the mean methylation value of the healthy population in the model, which is 0.37, and C_M is the mean methylation value of the liver cancer patients in the model, which is 0.47. When HCC_score>=50, it is predicted that the subject is at high risk of liver cancer; HCC_score<50, it is predicted that the subject has a low risk of cancer and belongs to the healthy population.

[0030] In a fifth aspect, the present invention provides a device, comprising:

[0031] at least one processor; and

[0032] a memory communicatively connected to at least one of the processors; wherein,

[0033] The memory stores instructions executable by the processor, and the instructions are used to be executed by the processor to implement any of the above-mentioned models for assisting in detecting liver cancer.

[0034] In some embodiments, the device further includes at least one input device and at least one output device; in the device, the processor, memory, input device, and output device are connected via a bus.

[0035] In a sixth aspect, a storage medium is provided, wherein the storage medium stores computer instructions, and the computer instructions are used to be executed by the computer to implement any of the above-mentioned models for assisting in the detection of liver cancer.

[0036] In some embodiments, the storage medium is a computer-readable storage medium.

[0037] In a seventh aspect, the present invention provides a device comprising

[0038] A model module, which is used to execute any of the above models for assisting in detecting liver cancer; and

[0039] Detection module, detects the methylation level of chr1:34792772-34792982 region.

[0040] In an eighth aspect, the present invention provides use of the above-mentioned markers or models in preparing a kit or device for assisting the detection of liver cancer.

[0041] Furthermore, the kit or device for assisting the detection of liver cancer is a kit or device for assisting the detection of liver cancer using a blood sample.

[0042] In a ninth aspect, the present invention provides a kit for detecting methylation genes for liver cancer, the kit comprising the composition or model as described above.

[0043] Furthermore, the kit also includes, but is not limited to, at least one of a reagent for extracting nucleic acid, a reagent for purifying nucleic acid, and bisulfite.

[0044] Furthermore, the kit also includes a negative sample.

[0045] Specifically, the negative sample is human genomic DNA that has been sequenced to verify that there is no methylation of the target gene.

[0046] Furthermore, the kit also includes dNTPs, Mg 2+ , at least one of a methylation-sensitive restriction endonuclease, a PCR buffer, and a hot-start enzyme.

[0047] Furthermore, the methylation-sensitive restriction endonuclease includes at least one of HpaII, HinP1I and HhaI.

[0048] Furthermore, the range of the final concentration of each component is as follows: Mg 2+ 1~6mM, dNTPs 1~80mM, methylation-sensitive restriction endonuclease 0.01~30U, primer 0.1~40μM, probe 0.1~20μM. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is the AUC result graph of the marker of the present invention;

[0050] Figure 2 This is the AUC result diagram of the comparative marker. DETAILED DESCRIPTION

[0051] The present invention will be described in detail below in conjunction with specific embodiments and examples, and the advantages and various effects of the present invention will be more clearly presented. It should be understood by those skilled in the art that these specific embodiments and examples are used to illustrate the present invention, rather than to limit the present invention.

[0052] Example 1: Screening of methylation genes

[0053] The methylated gene sequences were determined using data from healthy people, hepatitis B patients, cirrhosis patients and HCC patients. The DMRs with significant differences (methylation value difference between groups > 0.1 and p-value < 0.05) between the three comparisons (healthy individuals vs. hepatitis B patients, hepatitis B patients vs. cirrhosis patients, and cirrhosis patients vs. liver cancer patients) were calculated using a bioinformatics algorithm. It was found that there was only one identical DMR (chr1: 34792772-34792982) in the three groups, thus screening out the DMR marker chr1: 34792772-34792982 for HCC.

[0054] Example 2: Detection of marker methylation levels

[0055] Targeted bisulfite sequencing (TBS) was performed using 10–40 ng of cfDNA input from each participant, with a targeted panel that covers 461 kb of the human genome, consisting of 827 CpG islands. Bisulfite conversion is a routine and prerequisite step for TBS, which chemically converts unmethylated cytosine into uracil, which will be interpreted as thymine during sequencing. Therefore, the efficiency of bisulfite conversion directly affects the accuracy of detecting cytosine methylation levels, and evaluating the conversion rate is an essential QC step for bisulfite sequencing. To quantitatively evaluate the efficiency of bisulfite conversion, each DNA sample was bisulfite converted using the EpiArt DNA Methylation Bisulfite Kit (Vazyme Biotech, Nanjing, China). WGBS libraries were constructed for each cfDNA sample using the Rainbow Sugar cfDNA Methyl-Seq Library Preparation Kit (Rapha Biotech, Inc., Shenzhen, China). WTBS libraries were constructed using Qsep100 (Bio-Optics. Inc., Taiwan, China) and Qubit 4.0 (Thermo Fisher. Inc., MA, USA). The eight libraries were sent to a separate channel of the MGI-2000 sequencer for sequencing using DNBSEQ technology and PE100 sequencing mode.

[0056] The raw sequencing data of TBS samples were controlled and filtered using fastp. The bisulfite conversion rate was calculated as the percentage of cytosine converted to thymine in Lambda DNA, because they are all unmethylated. Next, after removing PCR duplicate sequences using SAMtools, the qualified reads were mapped to the human reference genome (GRCh38.p14) using the sequence alignment software BWA. Then, MethDackel was used to detect the methylation level of all CpG sites, and finally python was used to calculate the methylation level in the range of sample chr1:34792772-34792982. The clinical status of the data cohort and the methylation level in the marker region were combined into a two-dimensional expression profile, and the XGBoost machine learning algorithm was used for model training and testing; after the optimal model was established, the model could score the risk value of liver cancer (HCC_score) according to the methylation level of the subject's marker. For example, for subject test1, the marker methylation level is 0.45, and the HCC_score calculated by the model is 65. Clinical testing verifies that test1 is a liver cancer patient, which is consistent with the model prediction result.

[0057] Example 3: Effect of the markers of the present invention on the detection of liver cancer

[0058] In order to demonstrate the detection effect of the specific region of the marker GJA4 of the present invention, the detection performance of the markers of different regions of GJA4 in clinical samples was compared. Blood collected from 45 HCC patients and 58 healthy subjects was used to detect the markers of the present invention and the comparative markers. The detection was performed according to the method described in Example 2. The results are shown in FIG. Figures 1-2 And as shown in Table 1.

[0059] Table 1

[0060] Markers Sensitivity Specificity AUC chr1:34792772-3479298 83.33％ 83.33％ 0.833 chr1:34792944-34793200 21.42％ 70.58％ 0.563

Claims

1. A methylation marker for auxiliary detection of liver cancer: chr1: 34792772-34792982.

2. A composition for assisting in the detection of methylation markers for liver cancer, the composition comprising a detection reagent for detecting the methylation level in the following region: chr1: 34792772-34792982.

3. The composition according to claim 2, characterized in that The detection reagent is a detection reagent used in amplification-sequencing, chip detection, or methylation fluorescence quantitative PCR detection of methylation levels.

4. The composition according to claim 3, characterized in that The detection reagent is any one or more of a nucleic acid primer, a sequencing tag sequence, a methylation chip, and a nucleic acid probe.

5. A model for assisting the detection of liver cancer, the model being: HCC_score = 50-50*[(M-1 / 2*(N_M+C_M)] / [1 / 2*abs(N_M-C_M)], in, M is the methylation value of the marker as claimed in claim 1 of the subject, N_M is the mean methylation value of the healthy population in the model, which is 0.37, and C_M is the mean methylation value of the liver cancer patients in the model, which is 0.

47. When HCC_score>=50, it is predicted that the subject is at high risk of liver cancer; when HCC_score<50, it is predicted that the subject has a low risk of cancer and belongs to the healthy population.

6. A device comprising: at least one processor; as well as a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions executable by the processor, and the instructions are used to be executed by the processor to implement the model for assisting in detecting liver cancer as claimed in claim 5.

7. A device comprising: A model module, which is used to execute the model for assisting in the detection of liver cancer as described in claim 5; as well as Detection module, detects the methylation level of chr1:34792772-34792982 region.

8. A kit for detecting liver cancer, characterized in that: The kit comprises the composition of claim 2 and / or the model of claim 4.

9. The kit according to claim 8, characterized in that The kit also includes at least one of a reagent for extracting nucleic acid, a reagent for purifying nucleic acid, and bisulfite.

10. Use of the marker according to claim 1 or the model according to claim 4 in preparing a kit or device for assisting the detection of liver cancer.

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