Marker composition, product for liver cancer detection or diagnosis, and use thereof

Abstract

The application discloses a marker composition, product and application thereof for liver cancer detection or diagnosis, and relates to the technical field of liver cancer diagnosis. The marker composition comprises two markers, and the positions of the two markers on a reference genome are as follows: marker 1 is located in the whole region or a partial region of chr2:63281133-63281198; and marker 2 is located in the whole region or a partial region of chr6:26250725-26250815. The marker composition provided by the application can detect or diagnose liver cancer with 100% specificity and high sensitivity, and specific methylation signals can be checked in the early stage of liver cancer, so that early intervention treatment can be realized.

Description

Technical Field

[0001] This invention relates to the field of liver cancer diagnostic technology, and more specifically, to biomarker compositions, products, and applications for liver cancer detection or diagnosis. Background Technology

[0002] Traditional blood markers commonly used in clinical practice for liver cancer include alpha-fetoprotein (AFP), abnormal prothrombin (DPC), phosphatidylinositol proteoglycan (GPC3), degamma-carboxylated prothrombin (DCP), and Golgi protein 73. These markers, combined with imaging-assisted diagnosis, require considerable experience for comprehensive evaluation. Furthermore, these traditional liver cancer screening methods have low sensitivity and accuracy, insufficient to meet the needs of early cancer screening. For example, only about 60% of patients with primary hepatocellular carcinoma have elevated serum AFP levels. Therefore, a new screening method is needed to detect liver cancer signs as early as possible, enabling early diagnosis and treatment, and improving patient survival rates.

[0003] Current detection protocols all utilize Q-PCR to detect specific methylation fragments. For example, application number 2024111619930 combines three markers, which can improve the sensitivity of liver cancer detection to 90.6-93.8% while maintaining a specificity of around 90%. Application number 2022103218830 combines multiple markers, achieving a liver cancer detection sensitivity of 81.6% and a specificity of 88.2% for healthy controls.

[0004] Compared to traditional tumor markers, DNA methylation markers offer advantages such as earlier detection, non-invasiveness, and greater accuracy. They can be detected using non-invasive methods in samples such as sputum, plasma, serum, or urine. Some DNA methylation abnormalities occur in the initial stages of tumor formation; detecting methylation markers associated with tumor development can aid in early cancer diagnosis and assess the risk of progression.

[0005] There is still room for improvement in the sensitivity and specificity of hematological tests for early-stage liver cancer. The average fragment length of ctDNA is approximately 70-200 bp, therefore, ctDNA detection places extremely high demands on sample integrity and detection sensitivity, making early tumor detection methods based on blood ctDNA quite challenging.

[0006] In actual laboratory studies, it was found that the methylation rate of certain methylation sites within the same CpG island varies significantly, with differences of ten to even a hundred times. This poses a great challenge to data analysis and model building.

[0007] In view of this, the present invention is proposed. Summary of the Invention

[0008] The purpose of this invention is to provide biomarker compositions, products and their applications for the detection or diagnosis of liver cancer, so as to detect or diagnose liver cancer with 100% specificity and high sensitivity, and to detect specific methylation signals in the early stage of liver cancer, so as to achieve early intervention and treatment.

[0009] This invention is implemented as follows:

[0010] In a first aspect, the present invention provides a biomarker composition for the detection or diagnosis of liver cancer, the biomarker composition comprising two biomarkers; the positions of the two biomarkers on the reference genome are as follows:

[0011] Marker 1 is located in the entire area or part of the area of ​​chr2:63281133-63281198;

[0012] Marker 2 is located in the entire area or part of the area of ​​chr6:26250725-26250815;

[0013] The reference genome is the GRch37 version.

[0014] Secondly, the present invention also provides the use of biomarker compositions for liver cancer detection or diagnosis in the preparation of liver cancer detection or diagnostic products.

[0015] Thirdly, the present invention also provides a liver cancer detection or diagnostic product, comprising: primers for detecting the above-mentioned liver cancer detection or diagnostic biomarker composition, wherein the liver cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes and sequencing libraries.

[0016] Fourthly, the present invention also provides the application of reagents for detecting ctDNA methylation biomarkers in the preparation of early liver cancer diagnostic products, wherein the ctDNA methylation biomarkers are the above-mentioned biomarker compositions for liver cancer detection or diagnosis.

[0017] The present invention has the following beneficial effects:

[0018] This invention utilizes blood samples from patients with early-stage liver cancer to perform methylation testing of liver cancer-specific methylation markers. While ensuring 100% specificity, the threshold values ​​for each marker are set in the range of 0.10-0.29. Sensitivity is calculated starting from a threshold of 0.1, with a methylation rate of at least three consecutive CpG sites not less than 0.1. After screening, marker 1 and marker 2 were found to be the most sensitive combination. The combined sensitivity for detecting or diagnosing early-stage liver cancer exceeds 81%. Therefore, the marker composition provided by this invention has the advantages of high specificity and high sensitivity. The 100% specificity means that the false positive rate of the marker composition provided by this invention is zero, avoiding unnecessary anxiety, unnecessary radiation exposure, and further invasive examinations.

[0019] Based on the biomarker composition for liver cancer detection or diagnosis provided by this invention, liver cancer diagnostic products, such as reagents, kits, chips, hybridization probes, or sequencing libraries, can be further developed. This will help achieve rapid, highly sensitive, and highly specific detection or diagnosis of liver cancer. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 The ROC curve is a test plot of the validation set data using 12-site combinations (markers 1-2, marker 4, markers 6-12);

[0022] Figure 2 The ROC curve is shown for testing the validation set data using a 2-site combination (marker 1-2).

[0023] Figure 3 The ROC curve is a test plot of the validation set data using a 9-site combination (markers 1-9). Detailed Implementation

[0024] Reference will now be made to detailed embodiments of the present invention, one or more of which are described below. Each example is provided for explanation and not for limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made to the invention without departing from its scope or spirit. For example, features described or illustrated as part of one embodiment may be used in another embodiment to produce further embodiments.

[0025] In this invention, the term "methylation site" is synonymous with "CpG site or CpG island".

[0026] CpG islands are regions on the genome rich in CpG dinucleotide sequences.

[0027] The term "biomarker" broadly refers to any detectable compound or cell present in or derived from a sample, such as a protein, peptide, proteoglycan, glycoprotein, lipoprotein, cell, or any of the foregoing as a differentiating molecule or fragment. Here, a differentiating molecule or fragment is a molecule or fragment that, upon detection, indicates the presence or abundance of the identified compound or cell. Biomarkers can, for example, be isolated from the sample, measured directly in the sample, or detected or determined in the sample. Biomarkers can, for example, be functional, partially functional, or non-functional.

[0028] Specifically, tumor markers are biomarkers found in serum, urine, and tissue samples from cancer patients, indicating the potential presence of tumor cells in the body. Tumor markers are used for early diagnosis, disease progression monitoring, and treatment efficacy evaluation. Since the presence and amount of tumor markers are related to factors such as tumor type, location, size, and malignancy, their detection can facilitate early diagnosis and disease monitoring, improving treatment success rates and patient survival. Cell surface markers are substances such as proteins and carbohydrates present on the surface of tumor cells. Changes in cell surface markers reflect the growth state and characteristics of tumor cells and are the most common type of tumor marker. Intracellular markers are substances such as proteins and RNA present inside tumor cells.

[0029] A methylation biomarker is a DNA methylation level or pattern in a specific gene or genomic region (usually a CpG island). This methylation state can be quantified and detected, and can be used as a biomarker to indicate specific biological processes, physiological states, disease risk, disease presence, disease subtype, prognosis, or treatment response.

[0030] The term "sample" refers to a biological specimen obtained from or derived from an individual for a purpose. The source of the biological specimen may be a fresh, frozen, and / or preserved organ or tissue sample or solid tissue derived from a biopsy or primer; blood or any blood component. The term "sample" includes biological specimens that have been manipulated in any way after their acquisition, such as by reagent treatment, stabilization, enrichment for certain components (such as proteins or polynucleotides), or embedding in a semi-solid or solid matrix for sectioning purposes.

[0031] In a first aspect, the present invention provides a biomarker composition for the detection or diagnosis of liver cancer, the biomarker composition comprising two biomarkers; the positions of the two biomarkers on the reference genome are as follows:

[0032] Marker 1 is located in the entire area or part of the area of ​​chr2:63281133-63281198;

[0033] Marker 2 is located in the entire area or part of the area of ​​chr6:26250725-26250815;

[0034] The reference genome is the GRch37 version.

[0035] This invention utilizes a threshold setting scheme to perform combined analysis on each site and each marker. The threshold setting range for each marker is 0.10-0.29. Starting from the threshold of 0.1, the sensitivity of each combination is calculated based on the standard that the methylation rate of at least three consecutive sites is not less than 0.1.

[0036] Twenty-nine biomarkers (each containing different methylation sites, all obtainable from methylation databases or articles) yielded sensitivity results for different combinations. The sensitivity of the screening model with the highest sensitivity for each biomarker was used as the ranking reference value for that biomarker, and all biomarkers were sorted in descending order according to this reference value. Prioritizing the addition of two screening models (biomarker 1 and biomarker 2) from biomarkers with high ranking reference values ​​to the combined screening model candidate list, subsequent combinations of any screening model from each biomarker with all models in the candidate list were performed according to the biomarker's ranking reference value. The sensitivity of the new combined model was recalculated based on the training sample set and expanded, then added to the same candidate screening model list. Whenever a new model was added to the candidate list, each combined screening model in the list was reordered in descending order of sensitivity to eliminate the possibility of the new model reducing the original sensitivity. This process was repeated for each biomarker to expand the candidate screening model list as expected. After complete expansion, the combined screening model with the highest sensitivity was selected as the optimal combined screening model (i.e., biomarker combination).

[0037] After screening, biomarker 1 and biomarker 2 were found to be a highly sensitive combination. The combined biomarker has a sensitivity exceeding 81% for the detection or diagnosis of early-stage liver cancer. Therefore, the biomarker composition provided by this invention has the advantages of high specificity and high sensitivity. 100% specificity means that the false positive rate of the biomarker composition provided by this invention is zero, which can avoid unnecessary anxiety, unnecessary radiation exposure, and further invasive examinations.

[0038] In a preferred embodiment of the present invention, the liver cancer is early-stage liver cancer, and the biomarker composition further includes at least one of the following biomarkers: biomarker 3, biomarker 4, biomarker 5, biomarker 6, biomarker 7, biomarker 8, biomarker 9, biomarker 10, biomarker 11, biomarker 12 and biomarker 13.

[0039] The locations of each biomarker on the reference genome are as follows: Biomarker 3 is located in the entire or part of the region of chr8:67873718-67873823; Biomarker 4 is located in the entire or part of the region of chr12:133485299-133485385; Biomarker 5 is located in the entire or part of the region of chr2:63281224-63281328; Biomarker 6 is located in the entire or part of the region of chr2:63281223-63281319; Biomarker 7 is located in the entire or part of the region of chr12:131303599-131303698; Biomarker 8 is located in the region of chr1... 7:29298028-29298116, the entire or part of the area; Marker 9 is located in the entire or part of the area of ​​chr17:45261773-45261875; Marker 10 is located in the entire or part of the area of ​​chr4:42153735-42153840; Marker 11 is located in the entire or part of the area of ​​chr19:42901306-42901394; Marker 12 is located in the entire or part of the area of ​​chr3:179169176-179169265; Marker 13 is located in the entire or part of the area of ​​chr2:73518659-73518751.

[0040] In a preferred embodiment of the present invention, the marker composition is selected from at least one of the following:

[0041] (1) Marker 1, Marker 2 and Marker 3;

[0042] (2) Marker 1, Marker 2 and Marker 4;

[0043] (3) Marker 1, Marker 2, Marker 3 and Marker 4;

[0044] (4) Marker 1, Marker 2, Marker 3, Marker 4 and Marker 5;

[0045] (5) Marker 1, Marker 2, Marker 3, Marker 4 and Marker 6;

[0046] (6) Marker 1, Marker 2, Marker 4 and Marker 6;

[0047] (7) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5 and Marker 6;

[0048] (8) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6 and Marker 7;

[0049] (9) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5, Marker 6 and Marker 7;

[0050] (10) Marker 1, Marker 2, Marker 4, Marker 6 and Marker 7;

[0051] (11) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6 and Marker 7;

[0052] (12) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5, Marker 6, Marker 7 and Marker 8;

[0053] (13) Marker 1, Marker 2, Marker 4, Marker 6, Marker 7 and Marker 8;

[0054] (14) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7 and Marker 8;

[0055] (15) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8 and Marker 9;

[0056] (16) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9 and Marker 13;

[0057] (17) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5, Marker 6, Marker 7, Marker 8 and Marker 9;

[0058] (18) Marker 1, Marker 2, Marker 4, Marker 6, Marker 7, Marker 8 and Marker 9;

[0059] (19) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5, Marker 6, Marker 7, Marker 8, Marker 9 and Marker 10;

[0060] (20) Marker 1, Marker 2, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9 and Marker 10;

[0061] (21) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 13 and Marker 10;

[0062] (22) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9 and Marker 10;

[0063] (23) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 10 and Marker 11;

[0064] (24) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5, Marker 6, Marker 7, Marker 8, Marker 9, Marker 10 and Marker 11;

[0065] (25) Marker 1, Marker 2, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 10 and Marker 11;

[0066] (26) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 13, Marker 10 and Marker 11;

[0067] (27) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 13, Marker 10, Marker 11 and Marker 12;

[0068] (28) Marker 1, Marker 2, Marker 3, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 10, Marker 11 and Marker 12;

[0069] (29) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5, Marker 6, Marker 7, Marker 8, Marker 9, Marker 10, Marker 11 and Marker 12;

[0070] (30) Marker 1, Marker 2, Marker 4, Marker 6, Marker 7, Marker 8, Marker 9, Marker 10, Marker 11 and Marker 12.

[0071] In a preferred embodiment of the present invention, the marker composition comprises: marker 1, marker 2, marker 4, marker 6, marker 7, marker 8, marker 9, marker 10, marker 11, and marker 12.

[0072] In a preferred embodiment of the present invention, the entire region or part of the region of marker 1 includes three consecutive CpG sites or four consecutive CpG sites.

[0073] The entire region or part of the region of marker 2 includes three consecutive CpG sites or four consecutive CpG sites.

[0074] The entire region or part of the region of marker 3 includes three consecutive CpG sites;

[0075] The entire region or part of the region of marker 4 includes three consecutive CpG sites or four consecutive CpG sites.

[0076] The entire region or part of the region of marker 5 includes three consecutive CpG sites;

[0077] The entire region or part of the region of marker 6 includes three consecutive CpG sites;

[0078] The entire region or part of the region of marker 7 includes four consecutive CpG sites or five consecutive CpG sites.

[0079] The entire region or part of the region of marker 8 includes three consecutive CpG sites;

[0080] The entire region or part of the region of marker 9 includes three consecutive CpG sites;

[0081] The entire region or part of the region of marker 10 includes three consecutive CpG sites;

[0082] The entire region or part of the region of marker 11 includes three consecutive CpG sites;

[0083] The entire region or part of the region of marker 12 includes three consecutive CpG sites;

[0084] The entire region or part of the region of marker 13 includes three consecutive CpG sites.

[0085] Secondly, the present invention also provides the use of biomarker compositions for liver cancer detection or diagnosis in the preparation of liver cancer detection or diagnostic products.

[0086] In a preferred embodiment of the present invention, the liver cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes, and sequencing libraries.

[0087] A chip, also known as a suspension array or liquid array, includes a carrier and nucleic acid molecules (such as primers and / or probes) and / or antibodies bound to the surface of the carrier. In one embodiment, the chip includes, but is not limited to, an antibody chip.

[0088] The aforementioned chip carrier can be made of various materials and in various forms, such as preferably a container with a flat bottom. A more typical preferred example is a microfluidic device (e.g., a microfluidic chip), but it is not limited thereto.

[0089] The microfluidic chip is selected from T-type chip, flow focusing chip or coaxial flow chip PDMS chip or metal droplet generator or PMMA microfluidic chip.

[0090] Furthermore, the kit may also include at least one of the following: buffer solution, detection reagent, diluent, and washing solution, and is not limited thereto.

[0091] The detection products (such as kits) provided by the present invention may optionally include any reagents and / or consumables acceptable in the art for PCR reactions or for preparing PCR reaction systems. Specific embodiments may include, but are not limited to, one or more of dNTPs, salts or salt solutions, negative controls, positive controls, blank controls, calibrators, and PCR reaction containers.

[0092] The application includes at least one of the following application methods:

[0093] (1) When the liver cancer detection or diagnostic product is only used to detect biomarker 1 and biomarker 2, the liver cancer detection or diagnostic thresholds for biomarker 1 and biomarker 2 are set to 0.10 and 0.10 respectively, and liver cancer is judged as positive when the methylation rate of 3-4 consecutive CpG sites in each biomarker is not lower than the threshold; the diagnostic sensitivity reaches 81%-84%;

[0094] If the methylation rate of the tested sample is not less than 0.1 at at least 3-4 consecutive CpG sites for marker 1 and not less than 0.1 at at least 3-4 consecutive CpG sites for marker 2, the sample is assessed as positive for liver cancer. If the methylation rate of the tested sample is less than 0.1 at at least 3-4 consecutive CpG sites for marker 1, or less than 0.1 at at least 3-4 consecutive CpG sites for marker 2, the sample is assessed as negative for liver cancer.

[0095] (2) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-3, the liver cancer detection or diagnostic thresholds for biomarkers 1-3 are set to 0.10, 0.10 and 0.10 respectively, and liver cancer is judged as positive when the methylation rate of three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2 and three consecutive CpG sites in biomarker 3 is not lower than the threshold; the diagnostic sensitivity reaches 86%;

[0096] (3) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2 and 4, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2 and 4 are set to 0.10, 0.10 and 0.11, respectively. Liver cancer is judged as positive when the methylation rate of 3-4 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2 and 3 consecutive CpG sites in biomarker 4 is not lower than the threshold. The diagnostic sensitivity reaches 87-88%.

[0097] (4) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 3 and 4 are set to 0.10, 0.10, 0.10 and 0.10-0.11, respectively. Liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3 and 3-4 consecutive CpG sites in biomarker 4 is not lower than the threshold; the diagnostic sensitivity reaches 88%.

[0098] (5) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-5, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 3, 4 and 5 are set to 0.10, 0.10, 0.10, 0.11 and 0.10 respectively. Liver cancer is judged as positive when the methylation rate of three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, three consecutive CpG sites in biomarker 3, three consecutive CpG sites in biomarker 4 and three consecutive CpG sites in biomarker 5 is not lower than the threshold; the diagnostic sensitivity reaches 88%.

[0099] (6) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4 and biomarker 6, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 3, 4 and 6 are set to 0.10, 0.10, 0.10, 0.10-0.11 and 0.10, respectively. Liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3-4 consecutive CpG sites in biomarker 4 and 3 consecutive CpG sites in biomarker 6 is not lower than the threshold; the diagnostic sensitivity reaches 89%.

[0100] (7) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 4 and 6, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 4 and 6 are set to 0.10, 0.10, 0.11 and 0.10, respectively; and liver cancer is judged as positive when the methylation rate of three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, three consecutive CpG sites in biomarker 4 and three consecutive CpG sites in biomarker 6 is not lower than the threshold; the diagnostic sensitivity reaches 89%;

[0101] (8) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-6, the liver cancer detection or diagnostic thresholds for biomarkers 1-6 are set to 0.10, 0.10, 0.10, 0.11, 0.10 and 0.10 respectively. Liver cancer is judged as positive when the methylation rate of three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, three consecutive CpG sites in biomarker 3, three consecutive CpG sites in biomarker 4, three consecutive CpG sites in biomarker 5 and three consecutive CpG sites in biomarker 6 is not lower than the threshold; the diagnostic sensitivity reaches 90%.

[0102] (9) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 3, 4, 6, and 7, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 3, 4, 6, and 7 are set to 0.10, 0.10, 0.10, 0.11, 0.10, and 0.10, respectively. A positive result for liver cancer is determined by the methylation rate of three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, three consecutive CpG sites in biomarker 3, three consecutive CpG sites in biomarker 4, three consecutive CpG sites in biomarker 6, and five consecutive CpG sites in biomarker 7, all of which are not lower than the threshold. The diagnostic sensitivity reaches 90%.

[0103] (10) When the liver cancer detection or diagnostic product is used only to detect biomarkers 1-7, the liver cancer detection or diagnostic thresholds for biomarkers 1-7 are set to 0.10, 0.10, 0.10, 0.11, 0.10, 0.10 and 0.10 respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 5, 3 consecutive CpG sites in biomarker 6 and 4 consecutive CpG sites in biomarker 7 is not lower than the threshold; the diagnostic sensitivity reaches 90%;

[0104] (11) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 4, 6 and 7, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 4, 6 and 7 are set to 0.10, 0.10, 0.11, 0.10 and 0.10, respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6 and 4 consecutive CpG sites in biomarker 7 is not lower than the threshold; the diagnostic sensitivity reaches 90%;

[0105] (12) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 3, 4, 6 and 7, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 3, 4, 6 and 7 are set to 0.10, 0.10, 0.10, 0.10-0.11, 0.10 and 0.10, respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3-4 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6 and 4 consecutive CpG sites in biomarker 7 is not lower than the threshold; the diagnostic sensitivity reaches 90%;

[0106] (13) When the liver cancer detection or diagnostic product is used only to detect biomarkers 1-8, the liver cancer detection or diagnostic thresholds for biomarkers 1-8 are set to 0.10, 0.10, 0.10, 0.11, 0.10, 0.10, 0.10 and 0.10 respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 5, 3 consecutive CpG sites in biomarker 6, 4 consecutive CpG sites in biomarker 7 and 3 consecutive CpG sites in biomarker 8 is not lower than the threshold; the diagnostic sensitivity reaches 91%;

[0107] (14) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 4, 6, 7, and 8, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 4, 6, 7, and 8 are set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, and 0.1000, respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6, 4 consecutive CpG sites in biomarker 7, and 3 consecutive CpG sites in biomarker 8 is not lower than the threshold; the diagnostic sensitivity reaches 91%;

[0108] (15) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 3, 4, 6, 7, and 8, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 3, 4, 6, 7, and 8 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, and 0.1000, respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6, 4-5 consecutive CpG sites in biomarker 7, and 3 consecutive CpG sites in biomarker 8 is not lower than the threshold; the diagnostic sensitivity reaches 91%;

[0109] (16) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4 and 6-9, the liver cancer detection or diagnostic thresholds for biomarkers 1-4 and 6-9 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, and 0.1000, respectively; and liver cancer is judged as positive if the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6, 4-5 consecutive CpG sites in biomarker 7, 3 consecutive CpG sites in biomarker 8, and 3 consecutive CpG sites in biomarker 9 is not lower than the threshold; the diagnostic sensitivity reaches 92%;

[0110] (17) When the liver cancer detection or diagnostic product is used only to detect biomarkers 1-4, 6-9 and 13, the liver cancer detection or diagnostic thresholds for biomarkers 1-4, 6-9 and 13 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000 and 0.1000 respectively; and the thresholds are based on three consecutive CpG sites in biomarker 1. The methylation rate of three consecutive CpG sites in markers 2, 3, 4, 6, 7, 8, 9, and 13 is all above the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 92%.

[0111] (18) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-9, the liver cancer detection or diagnostic thresholds for biomarkers 1-9 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, and 0.1000, respectively; and liver cancer is judged as positive if the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 3, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 5, 3 consecutive CpG sites in biomarker 6, 4 consecutive CpG sites in biomarker 7, 3 consecutive CpG sites in biomarker 8, and 3 consecutive CpG sites in biomarker 9 is not lower than the threshold; the diagnostic sensitivity reaches 92%;

[0112] (19) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1, 2, 4, 6, 7, 8, and 9, the liver cancer detection or diagnostic thresholds for biomarkers 1, 2, 4, 6, 7, 8, and 9 are set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, and 0.1000, respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6, 4 consecutive CpG sites in biomarker 7, 3 consecutive CpG sites in biomarker 8, and 3 consecutive CpG sites in biomarker 9 is not lower than the threshold; the diagnostic sensitivity reaches 92%;

[0113] (20) When the liver cancer detection or diagnostic product is used only to detect biomarkers 1-10, the liver cancer detection or diagnostic thresholds for biomarkers 1-10 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively, and the thresholds are determined by three consecutive CpG sites in biomarker 1 and three consecutive CpG sites in biomarker 2. The methylation rate of three consecutive CpG sites in marker 3, three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 5, three consecutive CpG sites in marker 6, four consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, and three consecutive CpG sites in marker 10, all not lower than the threshold, indicates a positive result for liver cancer; the diagnostic sensitivity reaches 93%.

[0114] (21) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-2, 4 and 6-10, the liver cancer detection or diagnostic thresholds for biomarkers 1-2, 4 and 6-10 are set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000 and 0.1000 respectively; and liver cancer is judged as positive when the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6, 4 consecutive CpG sites in biomarker 7, 3 consecutive CpG sites in biomarker 8, 3 consecutive CpG sites in biomarker 9 and 3 consecutive CpG sites in biomarker 10 is not lower than the threshold; the diagnostic sensitivity reaches 93%;

[0115] (22) When the liver cancer detection or diagnostic product is used only to detect biomarkers 1-4, 6-9, 13, and 10, the liver cancer detection or diagnostic thresholds for biomarkers 1-4, 6-9, 13, and 10 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and biomarker 1 The methylation rate of three consecutive CpG sites in marker 1, three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 6, four consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 13, and three consecutive CpG sites in marker 10 is not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 93%.

[0116] (23) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4 and 6-10, the liver cancer detection or diagnostic thresholds for biomarkers 1-4 and 6-10 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, and 0.1000, respectively; and liver cancer is judged as positive if the methylation rate of 3 consecutive CpG sites in biomarker 1, 3 consecutive CpG sites in biomarker 2, 3 consecutive CpG sites in biomarker 4, 3 consecutive CpG sites in biomarker 6, 4-5 consecutive CpG sites in biomarker 7, 3 consecutive CpG sites in biomarker 8, 3 consecutive CpG sites in biomarker 9, and 3 consecutive CpG sites in biomarker 10 is not lower than the threshold; the diagnostic sensitivity reaches 93%;

[0117] (24) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4 and 6-11, the liver cancer detection or diagnostic thresholds for biomarkers 1-4 and 6-11 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and the thresholds are based on three consecutive CpG sites in biomarker 1, the biomarker... The methylation rate of three consecutive CpG sites in marker 2, three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 6, four to five consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 10, and three consecutive CpG sites in marker 11 is all not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 94%.

[0118] (25) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-11, the liver cancer detection or diagnostic thresholds for biomarkers 1-11 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and the thresholds are defined as the number of consecutive CpG sites in biomarker 1, the number of consecutive CpG sites in biomarker 2, and the number of consecutive CpG sites in biomarker 3. The methylation rate of three consecutive CpG sites in markers 4, 5, 6, 7, 8, 9, 10, and 11 is all not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 94%.

[0119] (26) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-2, 4, and 6-11, the liver cancer detection or diagnostic thresholds for biomarkers 1-2, 4, and 6-11 are set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, and 0.1000, respectively; and the thresholds are based on three consecutive CpG sites in biomarker 1. The methylation rate of three consecutive CpG sites in marker 2, three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 6, four consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 10, and three consecutive CpG sites in marker 11 all not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 94%.

[0120] (27) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4, 6-9, 13, and 10-11, the liver cancer detection or diagnostic thresholds for biomarkers 1-4, 6-9, 13, and 10-11 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and the thresholds for biomarkers 1 are listed in the table. The methylation rate of three consecutive CpG sites in marker 2, three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 6, four consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 13, three consecutive CpG sites in marker 10, and three consecutive CpG sites in marker 11 is not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 94%.

[0121] (28) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4, 6-9, 13, and 10-12, the liver cancer detection or diagnostic thresholds for biomarkers 1-4, 6-9, 13, and 10-12 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and the thresholds are based on three consecutive C values ​​in biomarker 1. The methylation rate of the following markers is not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 95%.

[0122] (29) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-4 and 6-12, the liver cancer detection or diagnostic thresholds for biomarkers 1-4 and 6-12 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and the thresholds are defined as the number of consecutive CpG sites in biomarker 1 and the number of consecutive CpG sites in biomarker 2. The methylation rate of three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 6, four to five consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 10, three consecutive CpG sites in marker 11, and three consecutive CpG sites in marker 12 is not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 95%.

[0123] (30) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-12, the liver cancer detection or diagnostic thresholds for biomarkers 1-12 are set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and the thresholds are based on three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, and biomarkers 1-12. The methylation rate of three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 5, three consecutive CpG sites in marker 6, four consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 10, three consecutive CpG sites in marker 11, and three consecutive CpG sites in marker 12 is not lower than the threshold, indicating a positive result for liver cancer; the diagnostic sensitivity reaches 95%.

[0124] (31) When the liver cancer detection or diagnostic product is only used to detect biomarkers 1-2, 4, and 6-12, the liver cancer detection or diagnostic thresholds for biomarkers 1-2, 4, and 6-12 are set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, respectively; and based on three consecutive CpG sites in biomarker 1. A positive result for liver cancer is defined as the methylation rate of three consecutive CpG sites in markers 2, 4, 6, 7, 8, 9, 10, 11, and 12 not lower than the threshold. The diagnostic sensitivity reaches 95%. Due to its high sensitivity, this composition is considered a preferred option.

[0125] Thirdly, the present invention also provides a liver cancer detection or diagnostic product, comprising: primers for detecting the above-mentioned liver cancer detection or diagnostic biomarker composition, wherein the liver cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes and sequencing libraries.

[0126] In a preferred embodiment of the present invention, the primer sequences for detection marker 1 are shown in SEQ ID NO. 1-2; the primer sequences for detection marker 2 are shown in SEQ ID NO. 3-4; the primer sequences for detection marker 3 are shown in SEQ ID NO. 5-6; the primer sequences for detection marker 4 are shown in SEQ ID NO. 7-8; the primer sequences for detection marker 5 are shown in SEQ ID NO. 9-10; the primer sequences for detection marker 6 are shown in SEQ ID NO. 11-12; the primer sequences for detection marker 7 are shown in SEQ ID NO. 13-14; the primer sequences for detection marker 8 are shown in SEQ ID NO. 15-16; the primer sequences for detection marker 9 are shown in SEQ ID NO. 17-18; the primer sequences for detection marker 10 are shown in SEQ ID NO. 19-20; the primer sequences for detection marker 11 are shown in SEQ ID NO. 21-22; and the primer sequences for detection marker 12 are shown in SEQ ID NO. 19-20. As shown in NO.23-24; the primer sequence for detecting marker 13 is shown in SEQ ID NO.25-26.

[0127] In other embodiments, the length of the primer sequence may be shortened or extended as needed, which is also within the scope of protection of this invention.

[0128] The primer sequences are shown in Table 1 below:

[0129] Table 1. Information on primers related to biomarkers

[0130]

[0131] In the table, the degenerate base R represents A / G, and the degenerate base Y represents C / T.

[0132] Fourthly, the present invention also provides the application of reagents for detecting ctDNA methylation biomarkers in the preparation of early liver cancer diagnostic products, wherein the ctDNA methylation biomarkers are the above-mentioned biomarker compositions for liver cancer detection or diagnosis.

[0133] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Where specific conditions are not specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased commercially.

[0134] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0135] Example 1

[0136] This embodiment provides a method for screening ctDNA methylation biomarkers.

[0137] (a) Collection of blood samples

[0138] 1. Whole blood collection

[0139] Blood collection method: 10 ml of blood was collected and stored in the morning on an empty stomach from 181 patients with early stage (stage I and stage II) liver cancer and (104) healthy individuals using disposable vacuum blood collection tubes (Zhejiang Medical Device Registration Certificate No. 20232221417) produced by Jiaxing Yunying Medical Laboratory Co., Ltd.

[0140] 2. Preparation of plasma samples

[0141] Centrifuge the blood collection tube containing whole blood for 12 minutes at a centrifugal force of 1500 rcf. Remove the blood collection tube from the centrifuge and transfer the supernatant plasma into a labeled 2 mL centrifuge tube to obtain the sample required for the experiment.

[0142] (ii) Pretreatment of cell-free DNA in plasma

[0143] The methylation detection sample pretreatment reagent and plasma sample lysis and sulfite conversion kit (product registration certificate number: Zhejia Medical Device Registration 20240074, catalog number C128) produced by Jiaxing Yunying Medical Laboratory Co., Ltd. were used to lyse, convert, and purify the samples. The operation steps are as follows.

[0144] 1. Preparation of reagents in the kit

[0145] The reagents in the above kit were prepared according to the preparation methods shown in Table 2:

[0146] Table 2. Preparation method of reagents

[0147]

[0148] 2. PEG precipitation

[0149] Take 1.8 mL of plasma sample, use two 2 mL empty centrifuge tubes, add 900 μL of PEG precipitation solution and 900 μL of plasma sample to each tube, vortex to mix for 5 min, and then centrifuge at 10 ℃ and 12000 rpm for 10 min using a high-speed refrigerated centrifuge.

[0150] 3. Pyrolysis

[0151] After discarding the supernatant, add 80 μL GTL, 30 μL of prepared proteinase K and 30 μL GL to each precipitate tube, pipette and sonicate for 10 min, then incubate with a constant temperature mixer at 60 ℃ and 1500 rpm for 60 min. After incubation, centrifuge at 12000 rpm for 2 min, and take 120 μL of the clarified fraction from each tube for transformation.

[0152] 4. Sulfite Conversion

[0153] 4.1 System Configuration

[0154] The lysed samples were prepared into sulfite reaction systems in 0.5 mL PCR tubes as shown in Table 3 below.

[0155] Table 3 Sulfite Reaction System

[0156]

[0157] 4.2 Sulfite Conversion

[0158] After vortexing and mixing, and briefly centrifuging, place the PCR tube in a PCR instrument and incubate at 95℃ for 5 min and 85℃ for 60 min. After incubation, cool to room temperature and briefly centrifuge to obtain the transformation product.

[0159] 5. Bis DNA purification treatment

[0160] The purified product was run using the Pure-20B purifier according to the set program. After the run was completed, the liquid was removed and placed into a new PCR 8-strip, labeled with the corresponding sample number. This is the purified Bis DNA, which can be used for the next library enrichment reaction.

[0161] (1) Sample addition: Add all the solution from the PCR tube to column 1 of the purification kit (add different samples to different wells), and be sure to record the sample number;

[0162] (2) After installing the magnetic rod sleeve, place the purification kit into the fully automated nucleic acid extractor and set it up and operate it according to the prescribed procedure:

[0163] (3) After the program finishes running, the solution is transferred to a new 1.5 mL centrifuge tube. The collected solution is the DNA after sulfite conversion. Library construction should be performed immediately.

[0164] (iii) Library enrichment reaction

[0165] The Bis DNA obtained after purification in the previous step was subjected to a library enrichment reaction.

[0166] 1. Preparation of enrichment PCR reaction

[0167] Prepare the enrichment reaction solution as needed according to the formula shown in Table 4, and then aliquot it into clean 8-strip containers. The aliquoted enrichment reaction solutions are grouped according to the primer mixture (primers for 29 blood biomarkers for liver cancer) and named MH enrichment PCR reaction strip-1 to MH enrichment PCR reaction strip-11. The 29 blood biomarkers for liver cancer were obtained through published articles and searches in methylation databases.

[0168] Table 4 Enrichment PCR Reaction System

[0169]

[0170] 2. Gently open the caps of tubes MH enrichment PCR reaction strip-1 to MH enrichment PCR reaction strip-11 prepared in the previous step, and add 0.5 μL of Taq enzyme to MH enrichment reaction solution-1 to MH enrichment PCR reaction solution-11 respectively, ensuring that the pipette tip is fully inserted into the reaction solution;

[0171] 3. Add 12 μL of the Bis DNA sample to be tested after sulfite conversion to the 11 enrichment reaction strips in sequence along the PCR tube wall, and carefully close the tube caps;

[0172] 4. After vortexing the PCR reaction strip to mix well, centrifuge, taking care to avoid air bubbles;

[0173] 5. Place the above 11 enrichment PCR reaction strips into the PCR instrument;

[0174] 6. Open the PCR instrument settings interface, set the amplification program according to Table 5 below, and perform PCR amplification.

[0175] Table 5. PCR reaction procedure for library enrichment

[0176]

[0177] (iv) Library preparation reaction

[0178] 1. Preparation for the joint connection reaction:

[0179] Prepare the required number of adapters according to the formula shown in Table 6 (excluding Ace Taq enzyme and the PCR reaction product enriched in the previous step). Alternatively, prepare the adapters in advance and aliquot them into clean 8-strand strips. Store at -20°C for later use.

[0180] After removing the connector reaction solution from the refrigerator and allowing it to melt, centrifuge it briefly in a centrifuge before use.

[0181] Table 6. Joint Connection Reaction System

[0182]

[0183] 2. Gently open the cap of the reaction strip and add 0.5 μL of Taq enzyme into the reaction strip, ensuring that the pipette tip is fully inserted into the reaction solution;

[0184] 3. Take 5 μL of the enriched PCR amplification product from the previous step and add it sequentially along the wall of the PCR tube to the adapter connection reaction strip, then carefully close the tube cap.

[0185] 4. Connect the connector to the reaction strip, shake to mix thoroughly, and then centrifuge, taking care to avoid air bubbles;

[0186] 5. Connect the above-mentioned adapter to the reaction strip and place it into the PCR instrument;

[0187] 6. Open the PCR instrument settings interface, set the amplification program according to Table 7 below, and perform PCR amplification.

[0188] Table 7. PCR reaction procedure for library preparation

[0189]

[0190] (v) Sorting of Library Products

[0191] 1. Remove the magnetic beads used for purification, vortex to mix, and incubate at room temperature for at least 30 minutes;

[0192] 2. Add 70 μL of purified water to each sample reaction tube in sequence;

[0193] 3. Take 80 μL of the incubated magnetic beads (shake well again before use) and add them sequentially to each sample reaction tube. Shake well and then incubate briefly to completely mix and resuspend the DNA and magnetic beads.

[0194] 4. Incubate at room temperature for 5 minutes;

[0195] 5. Incubate on a magnetic rack for 5 minutes until the solution is clear. Carefully aspirate the supernatant, being careful not to disturb the magnetic beads. Add the supernatant (approximately 170 μL) sequentially to new 8-tube or PCR tubes.

[0196] 6. Take 30 μL of the incubated magnetic beads and add them sequentially to an eight-tube or PCR tube containing the supernatant. Vortex to mix and then briefly incubate to completely mix and resuspend the DNA and magnetic beads.

[0197] 7. Incubate at room temperature for 5 minutes;

[0198] 8. Incubate on a magnetic rack for 5 minutes until the solution is clear. Carefully aspirate and discard the supernatant, being careful not to disturb the magnetic beads.

[0199] 9. Add 200µL of freshly prepared 80% ethanol solution (the ethanol solution should just cover the magnetic bead sample), place it on a magnetic rack, and incubate it on the magnetic rack for 30 seconds until the solution is clear. Discard the supernatant.

[0200] 10. Repeat step 9 above for a second wash;

[0201] 11. Ensure that the ethanol solution in the centrifuge tube has been completely discarded, and place the eight-tube or PCR tube on a magnetic rack to air dry at room temperature for 3-5 minutes;

[0202] 12. Remove the eight-tube or PCR tube from the magnetic rack, add 40 μL of purified water to fully wet the magnetic beads, shake well to mix, and then quickly centrifuge to collect the liquid at the bottom of the tube. Let it stand at room temperature for 5 min.

[0203] 13. Place the 8-tube or PCR tube on a magnetic rack and let it stand for 5 minutes until the solution is clear. Transfer 30 μL of the supernatant to a new 8-tube or 1.5 mL centrifuge tube to obtain the sequencing library. Use the Equalbit 1×dsDNA HS Assay Kit and its matching Qubit fluorescence instrument to detect the concentration. The library concentration should be ≥0.4 ng / μL. Otherwise, the library preparation sample does not meet the requirements and should be reconstructed.

[0204] 14. Perform deep sequencing on an Illumina MiniSeq sequencer, with each sample being sequenced at 300M.

[0205] (vi) Processing sample sequencing data

[0206] NGS sequencing data processing standards: FastP program is used for quality control of the sequencing data, removing adapter sequences, low-quality short sequences, or simple repetitive sequences. The data is then compared with the human genome reference sequence, and the sequencing depth for each locus is no less than 5000X. Plasma methylation data from 181 early-stage (stage I and II) hepatocellular carcinoma patients and 104 healthy individuals were divided into a training set (plasma from 101 early-stage hepatocellular carcinoma patients and plasma from 64 healthy individuals) and a validation set (plasma from 80 early-stage hepatocellular carcinoma patients and plasma from 40 healthy individuals).

[0207] (vii) Screening of markers

[0208] Using the control gene ACTB as a comparison result of the sulfite conversion assay, this invention ensures that the sulfite is completely converted to unmethylated sites. All 29 liver cancer-specific biomarkers contain multiple liver cancer-specific methylation sites. In the training set (plasma from 101 patients with early-stage liver cancer and plasma from 64 healthy individuals), this invention uses different threshold setting schemes to perform combined analysis on each site and each biomarker. Under the condition of ensuring 100% specificity, the combination biomarker with the highest sensitivity is selected for hematological screening of early-stage liver cancer.

[0209] In the plasma methylation data of 101 patients with early-stage liver cancer and 64 healthy individuals in the training set, considering both the accuracy of the sequencer and the distribution of methylation rates in the experiment of this invention, the threshold range for each biomarker was set between 0.10 and 0.29 while ensuring 100% specificity. Starting from a threshold of 0.1, the sensitivity of each combination was calculated based on the standard that the methylation rate of at least three consecutive sites was not less than 0.1. Sensitivity results for different combinations were obtained for all 29 biomarkers (each containing different methylation sites). The sensitivity of the screening model with the highest sensitivity for each biomarker was used as the ranking reference value for that biomarker. All biomarkers were sorted in descending order according to the above ranking reference value. The results are shown in the "Sensitivity Ranking Table of 29 Biomarkers for Liver Cancer". The score is calculated as: Sensitivity + Weight * Specificity, with the weight set to 0.5.

[0210] The table below, using marker 1 as an example, shows the sensitivity, specificity, and score of each combination calculated within the set range of 0.10-0.29 (Table 8 shows the threshold range of 0.10-0.16), starting from a threshold of 0.1, with a methylation rate of at least 3 consecutive sites not less than 0.1. The first to fourth rows represent the sensitivity and specificity calculated for each site combination with a methylation rate of at least 0.1 for 3, 4, 5, and 6 consecutive sites, respectively. Based on this, the sensitivity of the screening model with the highest sensitivity among all markers is used as the ranking reference value for that marker, i.e., ranking and selecting the number of consecutive sites with the highest sensitivity and the threshold condition for each marker. All markers are then sorted in descending order according to the above ranking reference value.

[0211] Table 8 shows the sensitivity, specificity, and score for each combination of methylation rates at at least three consecutive sites within a threshold range of 0.10–0.16.

[0212]

[0213] Continuing with the priority of adding the two screening models from biomarkers with the highest ranking reference values ​​to the combined screening model candidate list, we then sequentially combine any screening model from each biomarker with all models in the candidate list according to their ranking reference values. The sensitivity of the new combined model is recalculated based on the training sample set, and this expanded model is added to the same candidate list. Whenever a new model is added to the candidate list, each combined screening model in the list is reordered in descending order of sensitivity to eliminate the possibility of the new model reducing the original sensitivity. This process is repeated for each biomarker to expand the candidate list as expected. After complete expansion, the combined screening model with the highest sensitivity is selected as the optimal combined screening model. The sensitivity ranking table for the 29 biomarkers for liver cancer is shown in Table 9.

[0214] The results are shown in "Table 10: List of Optimal Sensitivity Combinations for Liver Cancer". The results show that 5 combinations have consistent sensitivity, with the highest being 95% and specificity of 100%. The combination with the fewest biomarkers (10) is biomarker 1, biomarker 2, biomarker 4, biomarker 6, biomarker 7, biomarker 8, biomarker 9, biomarker 10, biomarker 11, and biomarker 12, with thresholds of 0.1, 0.1, 0.11, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, respectively.

[0215] Table 9. Sensitivity ranking of 29 biomarkers for liver cancer.

[0216]

[0217] Table 10. Diagnostic performance of optimal liver cancer biomarkers

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224] In the table, 3 consecutive refers to 3 consecutive CpG sites on the same marker, and 4 consecutive refers to 4 consecutive CpG sites on the same marker.

[0225] Comparative Example 1

[0226] In the plasma methylation data of 101 patients with early-stage liver cancer and 64 healthy individuals in the training set, for each methylation site of a specific biomarker, the ROC curve analysis method in IBM SPSS Statistics 25 was used. The early-stage liver cancer samples were identified as state variable 1, and the healthy individuals were identified as state variable 0. The methylation rate of each methylation site was used as the test variable to obtain the ROC curve. The methylation rate at which the specificity was 100% was used as the threshold of that methylation site. Each biomarker contains several methylation sites. The average of the thresholds of each methylation site was used as the threshold of that biomarker, resulting in 29 biomarker thresholds.

[0227] In the training set, if the methylation rate of three consecutive sites (the consecutive methylation sites in this application are not necessarily adjacent in the physical location of the genome) of each biomarker is not less than the threshold of the biomarker, the biomarker is judged to be positive. If only one biomarker is positive, the sample is judged to be positive. According to this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0228] A marker is considered positive if three consecutive sites are positive, and a sample is considered positive if even one site is positive. The diagnostic efficacy of different liver cancer markers is shown in Table 11 below:

[0229] Table 11 shows the diagnostic efficacy of different liver cancer markers, where a marker is considered positive if three consecutive sites are positive.

[0230]

[0231] The individual threshold values ​​for each liver cancer marker are shown in Table 12 below:

[0232] Table 12 Single threshold values ​​for various liver cancer markers

[0233]

[0234] If the methylation rate of four consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only one biomarker is positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0235] A positive result at four consecutive loci indicates a positive biomarker, while a positive result at even one biomarker indicates a positive result. The diagnostic efficacy of different liver cancer biomarkers is shown in Table 13 below:

[0236] Table 13 shows the diagnostic efficacy of different liver cancer markers, where a positive result at four consecutive loci indicates a positive marker.

[0237]

[0238] If the methylation rate of 5 consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only 1 biomarker is positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0239] If the methylation rate of 6 consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only 1 biomarker is positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0240] If the methylation rate of 7 consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only 1 biomarker is positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0241] In the training set, if the methylation rate of three consecutive sites for each biomarker is not less than the threshold of that biomarker, the biomarker is considered positive. If only two biomarkers are positive, the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0242] If the methylation rate of four consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only two biomarkers are positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0243] In the training set, if the methylation rate of 5 consecutive sites for each marker is not less than the threshold of that marker, the marker is considered positive. If only 2 markers are positive, the sample is considered positive. Based on this standard, different combinations of markers (1 marker, 2 markers, 3 markers, ... 29 markers) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity).

[0244] If the methylation rate of 6 consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only 2 biomarkers are positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0245] In the training set, if the methylation rate of 7 consecutive sites for each biomarker is not less than the threshold of that biomarker, the biomarker is considered positive. If only 2 biomarkers are positive, the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0246] If the methylation rate of three consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only three biomarkers are positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0247] In the training set, if the methylation rate of four consecutive sites for each biomarker is not less than the threshold of that biomarker, the biomarker is considered positive. If only three biomarkers are positive, the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0248] In the training set, if the methylation rate of 5 consecutive sites for each marker is not less than the threshold of that marker, the marker is considered positive. If only 3 markers are positive, the sample is considered positive. Based on this standard, different combinations of markers (1 marker, 2 markers, 3 markers, ... 29 markers) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity).

[0249] If the methylation rate of 6 consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only 3 biomarkers are positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0250] If the methylation rate of 7 consecutive sites in each biomarker in the training set is not less than the threshold of that biomarker, then the biomarker is considered positive. If only 3 biomarkers are positive, then the sample is considered positive. Based on this standard, different combinations of biomarkers (1 biomarker, 2 biomarker combinations, 3 biomarker combinations... 29 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0251] Combinations of samples with more consecutive methylation sites (up to 14 sites) and more biomarkers (up to 29 biomarkers) as positive were analyzed, and the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations was statistically calculated. After a long period of calculation, the results showed that when there were 7 biomarkers (a biomarker was considered positive if the methylation value of 3 consecutive sites was not less than the methylation threshold, and a sample was considered positive if only 1 biomarker was positive) (a total of 1,560,780 combinations), the sensitivity ranged from 30% to 87%, with a specificity of 100%. Increasing the number of biomarkers to 8 or more did not increase the maximum sensitivity, and the highest sensitivity remained at 87%. With 9 biomarkers (a biomarker is considered positive if 4 consecutive sites have methylation values ​​not less than the methylation threshold, and a sample is considered positive if only one biomarker is positive) (a total of 10,015,005 combinations), the sensitivity ranged from 37% to 85%, and the specificity was 100%. Increasing the number of biomarkers to 10 or more did not increase the maximum sensitivity, which remained at 85%. It can be predicted that the sensitivity will decrease further with higher screening standards.

[0252] Comparative Example 2

[0253] In the plasma methylation of 101 patients with early-stage liver cancer and 64 healthy individuals in the training set, for each methylation site of a specific biomarker, the ROC curve analysis method in IBM SPSS Statistics 25 was used. The early-stage liver cancer samples were identified as state variable 1, and the healthy individuals were identified as state variable 0. The average methylation rate of the methylation sites in the biomarker was used as the test variable to obtain the ROC curve. The methylation rate at which the specificity was 100% was used as the threshold of the biomarker, and 29 biomarker thresholds were obtained.

[0254] Based on the statistical analysis of different combination schemes in Comparative Example 1, and after extensive calculations, the results showed that with 10 biomarkers (a biomarker is considered positive if methylation values ​​at 3 consecutive sites are not less than the methylation threshold, and a sample is considered positive if only 1 biomarker is positive) (a total of 29,10 = 200-30010 combinations), the sensitivity ranged from 51% to 94%, and the specificity ranged from 98% to 100%. Adding 11 or more biomarkers did not increase the maximum sensitivity; the highest sensitivity remained at 94%. With 10 biomarkers (a biomarker is considered positive if methylation values ​​at 4 consecutive sites are not less than the methylation threshold, and a sample is considered positive if only 1 biomarker is positive) (a total of 29,10 = 200-30010 combinations), the sensitivity ranged from 46% to 90%, and the specificity ranged from 98% to 100%. Adding 11 or more biomarkers did not increase the maximum sensitivity; the highest sensitivity remained at 90%. It can be predicted that its sensitivity will decrease as screening standards become higher.

[0255] In this comparative example, the individual thresholds for each liver cancer marker are shown in Table 14 below:

[0256] Table 14. Statistical table of single thresholds for various liver cancer markers.

[0257]

[0258] The marker is considered positive if three consecutive sites are positive, and the diagnostic efficacy is considered positive if only one marker is positive, as shown in Table 15 below:

[0259] Table 15 shows the diagnostic efficacy of various marker combinations when three consecutive sites are positive.

[0260]

[0261] A positive result at four consecutive loci indicates a positive biomarker, while a positive result at even one biomarker indicates a positive result. The diagnostic efficacy of this method is shown in Table 16 below.

[0262] Table 16 shows the diagnostic efficacy when four consecutive positive sites indicate a positive biomarker, and when even one positive biomarker indicates a positive sample.

[0263]

[0264] Comparative Example 3

[0265] In the plasma methylation data of 101 patients with early-stage liver cancer and 64 healthy individuals in the training set, the thresholds for 29 early-stage liver cancer-specific biomarkers were all set to 0.1, and the sensitivity range of the combinations was statistically analyzed according to the different combination schemes in Comparative Example 1.

[0266] After a long period of calculation, the results showed that when there were 10 biomarkers (a biomarker was considered positive if the methylation value of 3 consecutive sites was not less than the methylation threshold, and a sample was considered positive if only 1 biomarker was positive) (a total of 20030010 combinations of combin(29,10) = 20030010), the sensitivity ranged from 61% to 95%, and the specificity was 92% to 100%. The addition of 11 or more biomarkers did not increase the maximum sensitivity, and the highest sensitivity remained at 95%. At this time, the 10 biomarkers were biomarker 1, biomarker 2, biomarker 4, biomarker 6, biomarker 7, biomarker 8, biomarker 9, biomarker 10, biomarker 11, and biomarker 12. Conversely, under the standard that a biomarker is considered positive if four consecutive methylation values ​​at four sites are not less than the methylation threshold, and a sample is considered positive if only one biomarker is positive, the sensitivity of a combination of 10 biomarkers ranges from 56% to 91%, with a specificity of 100%. Increasing the number of biomarkers to 11 or more does not increase the maximum sensitivity; the highest sensitivity remains at 91%, indicating relatively low sensitivity. It can be predicted that its sensitivity will decrease further with higher screening standards.

[0267] In this comparative example, the individual thresholds for each liver cancer marker are shown in Table 17 below:

[0268] Table 17 shows the individual threshold values ​​for various liver cancer markers.

[0269]

[0270] The marker is considered positive if three consecutive sites are positive, and the diagnostic efficacy is considered positive if only one marker is positive, as shown in Table 18 below:

[0271] Table 18 shows the diagnostic efficacy when three consecutive positive sites indicate a positive biomarker, and when even one positive biomarker indicates a positive sample.

[0272]

[0273] A positive result at four consecutive loci indicates a positive biomarker, while a positive result at even one biomarker indicates a positive result. The diagnostic efficacy of this biomarker is shown in Table 19 below.

[0274] Table 19 shows the diagnostic power when four consecutive positive sites indicate a positive biomarker, and when even one positive biomarker indicates a positive sample.

[0275]

[0276] As can be seen from the different schemes of the training set above, the marker screening method provided in Example 1 selects the marker combination with the best sensitivity and specificity.

[0277] Example 2

[0278] Methylation data from plasma samples of 80 patients with early-stage liver cancer and 40 healthy individuals were used as a validation set to validate the sensitivity and specificity of a 10-site combination (marker 1, marker 2, marker 4, marker 6, marker 7, marker 8, marker 9, marker 10, marker 11, and marker 12).

[0279] Following the method in Example 1, the plasma free DNA of the validation set samples was pretreated (refer to step (II) of Example 1). The extracted plasma free DNA was subjected to sulfite conversion according to step (II) of Example 1. After library enrichment reaction (nucleotide sequence of Primer mixture shown in Example 1), library preparation reaction, and library product sorting, deep sequencing was performed. The sample sequencing data was processed and compared to obtain the plasma methylation data of the validation set.

[0280] The thresholds for liver cancer detection or diagnosis of biomarkers 1-2, 4, and 6-12 were set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, and 0.1000, respectively. A positive result for liver cancer was defined as having a methylation rate not lower than the threshold for three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, three consecutive CpG sites in biomarker 4, three consecutive CpG sites in biomarker 6, four consecutive CpG sites in biomarker 7, three consecutive CpG sites in biomarker 8, three consecutive CpG sites in biomarker 9, three consecutive CpG sites in biomarker 10, three consecutive CpG sites in biomarker 11, and three consecutive CpG sites in biomarker 12.

[0281] Figure 1 The results showed a sensitivity of 95% (only 4 patients with early-stage liver cancer were not detected), a specificity of 100%, an AUC area under the ROC curve of 0.975, a lower limit of 95% confidence interval of 0.947, an upper limit of 1.000, a standard error of 0.014, and an asymptotic significance of 0.000 (based on the null hypothesis: true region = 0.5).

[0282] Example 3

[0283] Methylation data from plasma samples of 80 patients with early-stage liver cancer and 40 healthy individuals were used as a validation set to verify the sensitivity and specificity of the two-site combination (marker 1 and marker 2).

[0284] Following the method in Example 1, the plasma free DNA of the validation set samples was pretreated (refer to step (II) of Example 1). The extracted plasma free DNA was subjected to sulfite conversion according to step (II) of Example 1. After library enrichment reaction (nucleotide sequence of Primer mixture shown in Example 1), library preparation reaction, and library product sorting, deep sequencing was performed. The sample sequencing data was processed and compared to obtain the plasma methylation data of the validation set.

[0285] The thresholds for liver cancer detection or diagnosis of biomarkers 1 and 2 were set to 0.1000 and 0.1000, respectively. A positive result for liver cancer was defined as the methylation rate of three consecutive CpG sites in biomarker 1 and three consecutive CpG sites in biomarker 2 not being lower than the threshold.

[0286] Figure 2 The results showed that the sensitivity (67 / 80) was 83.75%, the specificity was 100%, the area under the ROC curve was 0.919, the lower limit of the 95% confidence interval was 0.868, the upper limit was 0.969, the standard error was 0.026, and the asymptotic significance was 0.000 (according to the null hypothesis: true region = 0.5).

[0287] Example 4

[0288] Methylation data from plasma samples of 80 patients with early-stage liver cancer and 40 healthy individuals were used as a validation set to verify the sensitivity and specificity of a 9-site combination (markers 1, 2, 3, 4, 5, 6, 7, 8, and 9).

[0289] Following the method in Example 1, the plasma free DNA of the validation set samples was pretreated (refer to step (II) of Example 1). The extracted plasma free DNA was subjected to sulfite conversion according to step (II) of Example 1. After library enrichment reaction (nucleotide sequence of Primer mixture shown in Example 1), library preparation reaction, and library product sorting, deep sequencing was performed. The sample sequencing data was processed and compared to obtain the plasma methylation data of the validation set.

[0290] The thresholds for liver cancer detection or diagnosis of biomarkers 1-9 were set to 0.1000, 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, and 0.1000, respectively. Liver cancer was considered positive if the methylation rate of three consecutive CpG sites in biomarker 1, three consecutive CpG sites in biomarker 2, three consecutive CpG sites in biomarker 3, three consecutive CpG sites in biomarker 4, three consecutive CpG sites in biomarker 5, three consecutive CpG sites in biomarker 6, four consecutive CpG sites in biomarker 7, three consecutive CpG sites in biomarker 8, and three consecutive CpG sites in biomarker 9 was not lower than the threshold.

[0291] Figure 3 The results showed that the sensitivity (73 / 80) was 91.25%, the specificity was 100%, the area under the ROC curve was 0.956, the lower limit of the 95% confidence interval was 0.919, the upper limit was 0.993, the standard error was 0.019, and the asymptotic significance was 0.000 (according to the null hypothesis: true region = 0.5).

[0292] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. The application of a reagent for detecting the methylation rate of a liver cancer marker composition in the preparation of early liver cancer detection or diagnostic products, characterized in that, The biomarker composition comprises 10 biomarkers; the biomarker composition includes: biomarker 1, biomarker 2, biomarker 4, biomarker 6, biomarker 7, biomarker 8, biomarker 9, biomarker 10, biomarker 11, and biomarker 12, and the positions of the 10 biomarkers on the reference genome are shown below: Marker 1 is located in the entire area of ​​chr2:63281133-63281198; Marker 2 is located in the entire area of ​​chr6:26250725-26250815; Marker 4 is located in the entire region of chr12:133485299-133485385; Marker 6 is located in the entire region of chr2:63281223-63281319; Marker 7 is located in the entire region of chr12:131303599-131303698; Marker 8 is located in the entire region of chr17:29298028-29298116; Marker 9 is located in the entire region of chr12:133485299-133485385; Marker 6 is located in the entire region of chr12:133485299-133485385; Marker 7 is located in the entire region of chr12:131303599-131303698; Marker 8 is located in the entire region of chr17:29298028-29298116; Marker 9 is located in the entire region of chr12:133485299-133485385; Marker 9 is located in the entire region of chr12:133485299-133485385; Marker 6 is located in the entire region of chr12:133485299-133485385; Marker 7 is located in the entire region of chr12:133485299-133485385; Marker 8 is located in the entire region of chr12:133485299-133485385; Marker 9 is located in the entire region of chr12:133485299-133485385; The entire region of chr17:45261773-45261875; the entire region of chr4:42153735-42153840; the entire region of chr19:42901306-42901394; the entire region of chr3:179169176-179169265; the reference genome is the GRch37 version of the reference genome.

2. The application according to claim 1, characterized in that, The entire region of marker 1 includes three consecutive CpG sites or four consecutive CpG sites. The entire region of marker 2 includes three consecutive CpG sites or four consecutive CpG sites. The entire region of marker 4 includes three consecutive CpG sites or four consecutive CpG sites.

3. The application according to claim 1, characterized in that, The entire region of marker 6 includes three consecutive CpG sites; The entire region of the marker 7 includes four consecutive CpG sites or five consecutive CpG sites. The entire region of marker 8 includes three consecutive CpG sites; The entire region of marker 9 includes three consecutive CpG sites; The entire region of the marker 10 includes three consecutive CpG sites.

4. The application according to claim 1, characterized in that, The entire region of the marker 11 includes three consecutive CpG sites; The entire region of the marker 12 includes three consecutive CpG sites.

5. The application according to any one of claims 1-4, characterized in that, The early liver cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes, and sequencing libraries; The application includes the following application methods: When the liver cancer detection or diagnostic product is used only to detect biomarkers 1-2, 4, and 6-12, the liver cancer detection or diagnostic thresholds for biomarkers 1-2, 4, and 6-12 are set to 0.1000, 0.1000, 0.1100, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, 0.1000, and 0.1000, respectively; and the thresholds are based on three consecutive CpG sites in biomarker 1. The following markers are considered positive for liver cancer if the methylation rate of three consecutive CpG sites in marker 2, three consecutive CpG sites in marker 4, three consecutive CpG sites in marker 6, four consecutive CpG sites in marker 7, three consecutive CpG sites in marker 8, three consecutive CpG sites in marker 9, three consecutive CpG sites in marker 10, three consecutive CpG sites in marker 11, and three consecutive CpG sites in marker 12 is not lower than the threshold.

6. A product for early detection or diagnosis of liver cancer, characterized in that, It includes: Primers for detecting the liver cancer biomarker composition according to any one of claims 1-5, wherein the early liver cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes, and sequencing libraries; the primer sequences for detecting biomarker 1 are shown in SEQ ID NO. 1-2, the primer sequences for detecting biomarker 2 are shown in SEQ ID NO. 3-4, the primer sequences for detecting biomarker 4 are shown in SEQ ID NO. 7-8, the primer sequences for detecting biomarker 6 are shown in SEQ ID NO. 11-12, the primer sequences for detecting biomarker 7 are shown in SEQ ID NO. 13-14, the primer sequences for detecting biomarker 8 are shown in SEQ ID NO. 15-16, the primer sequences for detecting biomarker 9 are shown in SEQ ID NO. 17-18, the primer sequences for detecting biomarker 10 are shown in SEQ ID NO. 19-20, the primer sequences for detecting biomarker 11 are shown in SEQ ID NO. 21-22, and the primer sequences for detecting biomarker 12 are shown in SEQ ID NO. 19-20. Shown in NO.23-24.

7. The application of reagents for detecting ctDNA methylation biomarkers in the preparation of early liver cancer diagnostic products, characterized in that, The ctDNA methylation biomarker is the liver cancer biomarker composition according to any one of claims 1-5.

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