A marker composition, product and use thereof for lung cancer detection or diagnosis

Abstract

This invention discloses a biomarker composition, product, and application for lung cancer detection or diagnosis, relating to the field of lung cancer diagnostic technology. The biomarker composition provided by this invention has the advantages of high specificity and high sensitivity; 100% specificity means a zero false positive rate, avoiding unnecessary anxiety, unnecessary radiation exposure, and further invasive examinations. Based on the lung cancer detection or diagnostic biomarker composition provided by this invention, lung 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 lung cancer.

Description

Technical Field

[0001] This invention relates to the field of lung cancer diagnostic technology, and more specifically, to a biomarker composition, product, and application for lung cancer detection or diagnosis. Background Technology

[0002] Low-dose spiral CT is currently the only reliable and effective diagnostic method for lung diseases, and it is also the best imaging method for detecting early-stage lung cancer, especially thin-slice reconstruction imaging, which has high sensitivity in detecting early-stage lung cancer. However, low-dose spiral CT has a high false-positive rate, which can lead to unnecessary anxiety, unnecessary radiation exposure, and further invasive examinations. In actual clinical practice, chest X-rays, sputum cytology, and serum tumor marker tests are mainly used for lung cancer screening and diagnosis, but the sensitivity and specificity of these screening methods are relatively poor, and they do not have any substantial impact on the clinical mortality rate of lung cancer patients.

[0003] 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 variations frequently 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.

[0004] There is still room for improvement in the sensitivity and specificity of hematological tests for early-stage lung cancer. The abundance of tumor cell DNA (ctDNA) in blood samples is low, especially in early-stage lung cancer patients, with a median value between 1% and 4%, and 25% of patients having levels close to or below 0.1%. The copy number of tumor DNA in plasma is also low, with a median value of 50-100 copies / mL and a half-life ranging from 16 minutes to 2 hours. The average fragment length of ctDNA is approximately 70-200 bp. Therefore, ctDNA detection places extremely high demands on both sample integrity and detection sensitivity, making early tumor detection methods based on blood ctDNA quite challenging.

[0005] 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 challenge for data analysis and model building.

[0006] In view of this, the present invention is proposed. Summary of the Invention

[0007] The purpose of this invention is to provide a biomarker composition, product and application for lung cancer detection or diagnosis, which can detect or diagnose lung cancer (especially early lung cancer) with 100% specificity and high sensitivity, and can detect specific methylation signals in the early stage of lung cancer, so as to achieve early intervention and treatment.

[0008] This invention is implemented as follows:

[0009] In a first aspect, the present invention provides a biomarker composition for lung cancer detection or diagnosis, the biomarker composition comprising two biomarkers; the positions of the two biomarkers on a reference genome are shown below:

[0010] Marker 1 is located in the entire area or part of the area of ​​chr7:27225502-27225602;

[0011] Marker 2 is located in the entire area or part of the area of ​​chr5:40681765-40681840;

[0012] The reference genome is the GRch37 version.

[0013] Secondly, the present invention provides the use of biomarker compositions for lung cancer detection or diagnosis in the preparation of lung cancer detection or diagnostic products.

[0014] Thirdly, the present invention provides a lung cancer detection or diagnostic product, comprising: primers for detecting the above-mentioned lung cancer detection or diagnostic biomarker composition, wherein the lung cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes and sequencing libraries.

[0015] Fourthly, the present invention provides the application of reagents for detecting ctDNA methylation biomarkers in the preparation of early lung cancer diagnostic products, wherein the ctDNA methylation biomarkers are the aforementioned biomarker compositions for lung cancer detection or diagnosis.

[0016] The present invention has the following beneficial effects:

[0017] This invention utilizes blood samples from early-stage lung cancer patients to perform methylation testing of lung 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 lung cancer exceeds 90%. 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.

[0018] Based on the biomarker composition for lung cancer detection or diagnosis provided by this invention, lung 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 lung cancer. Attached Figure Description

[0019] 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.

[0020] Figure 1 The ROC curve is a graph showing the results of testing the validation set data with a 5-site combination (marker 1, marker 2, marker 3, marker 4, marker 5).

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

[0022] Figure 3 The ROC curve is a test plot of the validation set data using a combination of three loci (marker 1, marker 2, and marker 3). Detailed Implementation

[0023] 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.

[0024] In this invention, the term "methylation site" is synonymous with "CpG site or CpG island".

[0025] In a first aspect, the present invention provides a biomarker composition for lung cancer detection or diagnosis, the biomarker composition comprising two biomarkers; the positions of the two biomarkers on a reference genome are shown below:

[0026] Marker 1 is located in the entire area or part of the area of ​​chr7:27225502-27225602;

[0027] Marker 2 is located in the entire or part of the region of chr5:40681765-40681840; the reference genome is the GRch37 version of the reference genome.

[0028] This invention utilizes a threshold setting scheme to perform combined analysis on each site and each biomarker. The threshold setting range for each biomarker is 0.10-0.29. Starting from a 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. Sensitivity results for different combinations of 41 biomarkers (each biomarker contains different methylation sites) are obtained. The sensitivity of the biomarker with the highest sensitivity among all biomarkers is used as the ranking reference value for that biomarker, and all biomarkers are sorted in descending order according to this ranking reference value. Prioritizing the addition of the two screening models (i.e., the two biomarkers with the highest diagnostic sensitivity) from the biomarkers with the highest ranking reference values ​​to the combined screening model candidate list, the next step is to combine any screening model from each biomarker with all models in the screening model candidate list according to the ranking reference value. The sensitivity of the new combined model is then recalculated based on the training sample set and expanded before being added to the same screening model candidate list. Whenever a new model is added to the screening model candidate list, each combination screening model in the list is reordered in descending order of its sensitivity to eliminate the possibility that the newly added model will reduce the original sensitivity. The above process is repeated for each biomarker to expand the screening model candidate list as expected. After the complete expansion is completed, the combination screening model with high sensitivity is selected as the combination screening model (i.e., biomarker combination).

[0029] Based on the above screening method, this invention selects a combination of highly sensitive biomarkers for hematological screening of early-stage lung cancer while ensuring 100% specificity. The highly sensitive combination consists of biomarker 1 and biomarker 2. The combined biomarker has a sensitivity exceeding 90% for the detection or diagnosis of early-stage lung 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, avoiding unnecessary anxiety, unnecessary radiation exposure, and further invasive examinations.

[0030] In a preferred embodiment of the present invention, the marker composition further includes at least one of the following markers:

[0031] Marker 3, Marker 4, Marker 5 and Marker 6;

[0032] 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 chr7:27204905-27204986; Biomarker 4 is located in the entire or part of the region of chr7:27228261-27228353; Biomarker 5 is located in the entire or part of the region of chr2:63054088-63054184; Biomarker 6 is located in the entire or part of the region of chr14:38724604-38724725.

[0033] In a preferred embodiment of the present invention, the marker composition is selected from at least one of the following:

[0034] (1) Marker 1, Marker 2, Marker 3, Marker 4 and Marker 5;

[0035] (2) Marker 1, Marker 2, Marker 3, Marker 4, Marker 5 and Marker 6;

[0036] (3) Marker 1, Marker 2, Marker 3, Marker 4 and Marker 6;

[0037] (4) Marker 1, Marker 2, Marker 3 and Marker 4;

[0038] (5) Marker 1, Marker 2 and Marker 3.

[0039] The above-mentioned biomarker composition (1) achieved a sensitivity of up to 97.87% and a specificity of 100%. The lung cancer detection or diagnostic thresholds for biomarkers 1, 2, 3, 4, and 5 were set to 0.10, 0.10, 0.10, 0.11, and 0.10-0.12 (e.g., 0.1, 0.11, or 0.12), respectively. Therefore, this is a preferred composition scheme.

[0040] The above-mentioned biomarker composition (2) has a sensitivity of 97.87% and a specificity of 100%. The lung cancer detection or diagnosis thresholds for biomarkers 1, 2, 3, 4, 5 and 6 are set to 0.10, 0.10, 0.10, 0.11, 0.10 and 0.10-0.11, respectively.

[0041] The above-mentioned biomarker composition (3) has a sensitivity of 95.31% and a specificity of 100%.

[0042] The lung cancer detection or diagnostic thresholds for markers 1, 2, 3, 4 and 6 were set to 0.10, 0.10, 0.10, 0.11 and 0.10, respectively.

[0043] The above-mentioned biomarker composition (4) achieved a sensitivity of 95.31% and a specificity of 100%. The lung cancer detection or diagnosis thresholds for biomarkers 1, 2, 3 and 4 were set to 0.10, 0.10, 0.10 and 0.11, respectively.

[0044] The above-mentioned biomarker composition (5) has a sensitivity of 93.75% and a specificity of 100%. The lung cancer detection or diagnosis thresholds for biomarkers 1, 2 and 3 are set to 0.10, 0.10 and 0.10, respectively.

[0045] In a preferred embodiment of the present invention, the marker composition comprises: marker 1, marker 2, marker 3, marker 4, and marker 5.

[0046] In a preferred embodiment of the present invention, marker 1 is located in the entire region or part of the region of chr7:27225502-27225602, which includes three consecutive CpG sites.

[0047] Marker 2 is located in the entire or part of the region of chr5:40681765-40681840, which includes three consecutive CpG sites.

[0048] Marker 3 is located in the entire or part of the region of chr7:27204905-27204986, which includes three consecutive CpG sites.

[0049] Marker 4 is located in the entire or part of the region of chr7:27228261-27228353, which includes four consecutive CpG sites.

[0050] Marker 5 is located in the entire region or part of chr2:63054088-63054184, which includes three consecutive CpG sites.

[0051] Marker 6 is located in the entire or part of the region of chr14:38724604-38724725, which includes four consecutive CpG sites.

[0052] Secondly, the present invention provides the use of biomarker compositions for lung cancer detection or diagnosis in the preparation of lung cancer detection or diagnostic products.

[0053] In a preferred embodiment of the present invention, the lung cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes, and sequencing libraries.

[0054] 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.

[0055] 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.

[0056] 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.

[0057] 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.

[0058] The application includes at least one of the following application methods:

[0059] (1) When the lung cancer detection or diagnostic product is used only to detect biomarkers 1 and 2, the lung cancer detection or diagnostic thresholds for biomarkers 1 and 2 are set to 0.10 and 0.10-0.12, respectively. During lung cancer detection or diagnosis, if the methylation rate of the tested sample at at least three consecutive CpG sites of biomarker 1 is not less than 0.1, and the methylation rate of the tested sample at at least three consecutive CpG sites of biomarker 2 is not less than 0.1, then the sample is assessed as lung cancer positive. If the methylation rate of the tested sample at at least three consecutive CpG sites of biomarker 1 is less than 0.1, or the methylation rate of the tested sample at at least three consecutive CpG sites of biomarker 2 is less than 0.1, then the sample is assessed as lung cancer negative.

[0060] (2) When the lung cancer detection or diagnostic product is used only to detect marker 1, marker 2 and marker 3, the lung cancer detection or diagnostic thresholds for marker 1, marker 2 and marker 3 are set to 0.10, 0.10 and 0.10, respectively;

[0061] (3) When the lung cancer detection or diagnostic product is used only to detect marker 1, marker 2, marker 3 and marker 4, the lung cancer detection or diagnostic thresholds for marker 1, marker 2, marker 3 and marker 4 are set to 0.10, 0.10, 0.10 and 0.11, respectively;

[0062] (4) When the lung cancer detection or diagnostic product is used only to detect marker 1, marker 2, marker 3, marker 4 and marker 6, the lung cancer detection or diagnostic thresholds for marker 1, marker 2, marker 3, marker 4 and marker 6 are set to 0.10, 0.10, 0.10, 0.11 and 0.10, respectively;

[0063] (5) When the lung cancer detection or diagnostic product is used only to detect marker 1, marker 2, marker 3, marker 4 and marker 5, the lung cancer detection or diagnostic thresholds for marker 1, marker 2, marker 3, marker 4 and marker 5 are set to 0.10, 0.10, 0.10, 0.11 and 0.10-0.12, respectively;

[0064] (6) When the lung cancer detection or diagnostic product is used only to detect marker 1, marker 2, marker 3, marker 4, marker 5 and marker 6, the lung cancer detection or diagnostic thresholds for marker 1, marker 2, marker 3, marker 4, marker 5 and marker 6 are set to 0.10, 0.10, 0.10, 0.11, 0.10 and 0.10-0.11, respectively.

[0065] Thirdly, the present invention provides a lung cancer detection or diagnostic product, comprising: primers for detecting the above-mentioned lung cancer detection or diagnostic biomarker composition, wherein the lung cancer detection or diagnostic product is selected from at least one of reagents, kits, chips, hybridization probes and sequencing libraries.

[0066] 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, and the primer sequences for detection marker 6 are shown in SEQ ID NO. 11-12.

[0067] The primer sequences are shown in Table 1 below:

[0068] Table 1. Information on primers related to biomarkers

[0069]

[0070] Fourthly, the present invention provides the application of reagents for detecting ctDNA methylation biomarkers in the preparation of early lung cancer diagnostic products, wherein the ctDNA methylation biomarkers are the aforementioned biomarker compositions for lung cancer detection or diagnosis.

[0071] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0072] Example 1

[0073] This embodiment provides a method for screening ctDNA methylation biomarkers.

[0074] (a) Collection of blood samples

[0075] 1. Whole blood collection

[0076] Blood collection method: 10 ml of blood was collected and stored in the morning on an empty stomach from 119 patients with early stage (stage I and stage II) lung cancer and 83 healthy individuals using disposable vacuum blood collection tubes (Zhejiang Medical Device Registration Certificate No. 20232221417) produced by Jiaxing Yunying Medical Laboratory Co., Ltd.

[0077] 2. Preparation of plasma samples

[0078] 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.

[0079] (ii) Pretreatment of cell-free DNA in plasma

[0080] The methylation detection sample pretreatment reagent and plasma sample lysis and sulfite conversion kit (Zhejiang Jiaxing Medical Equipment Registration No. 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.

[0081] 1. Preparation of reagents in the kit

[0082] The reagents in the above kit were prepared according to the preparation methods shown in Table 2:

[0083] Table 2. Preparation method of reagents

[0084]

[0085] 2. PEG precipitation

[0086] 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.

[0087] 3. Pyrolysis

[0088] 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.

[0089] 4. Sulfite Conversion

[0090] 4.1 System Configuration

[0091] Prepare sulfite reaction systems in 0.5 mL PCR tubes for the lysed samples as shown in the table below.

[0092] The sulfite reaction system is shown in Table 3. The plasmid and protective solution play a role in protecting the ctDNA.

[0093] Table 3. Sulfite Reaction System

[0094]

[0095] 4.2 Sulfite Conversion

[0096] 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.

[0097] 5. Bis DNA purification treatment

[0098] 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.

[0099] (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;

[0100] After installing the magnetic rod sleeve, place the purification kit into the fully automated nucleic acid extractor and follow the prescribed procedures for setup and operation:

[0101] (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.

[0102] (iii) Library enrichment reaction

[0103] The Bis DNA obtained after purification in the previous step was subjected to a library enrichment reaction.

[0104] 1. Preparation of enrichment PCR reaction

[0105] Prepare the enrichment reaction solution as needed according to the formula shown in Table 4. After preparation, dispense the solution into clean 8-strip containers. The dispensed enrichment reaction solutions are grouped according to the primer mixture (primers and physical location of lung cancer 41 marker) and are named MH enrichment PCR reaction strip-1 to MH enrichment PCR reaction strip-11.

[0106] Table 4 Enrichment PCR Reaction System

[0107]

[0108] 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;

[0109] 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;

[0110] 4. After vortexing the PCR reaction strip to mix well, centrifuge, taking care to avoid air bubbles;

[0111] 5. Place the above 11 enrichment PCR reaction strips into the PCR instrument;

[0112] 6. Open the PCR instrument settings interface, set the amplification program according to Table 5 below, and perform PCR amplification.

[0113] Table 5. PCR reaction procedure for library enrichment

[0114]

[0115] (iv) Library preparation reaction

[0116] 1. Preparation for the joint connection reaction:

[0117] 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.

[0118] After removing the connector reaction solution from the refrigerator and allowing it to melt, centrifuge it briefly in a centrifuge before use.

[0119] Table 6. Joint Connection Reaction System

[0120]

[0121] 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;

[0122] 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.

[0123] 4. Connect the connector to the reaction strip, shake to mix thoroughly, and then centrifuge, taking care to avoid air bubbles;

[0124] 5. Connect the above-mentioned adapter to the reaction strip and place it into the PCR instrument;

[0125] 6. Open the PCR instrument settings interface, set the amplification program according to Table 7 below, and perform PCR amplification.

[0126] Table 7 PCR reaction procedure for library preparation

[0127]

[0128] (v) Sorting of Library Products

[0129] 1. Remove the magnetic beads used for purification, vortex to mix, and incubate at room temperature for at least 30 minutes;

[0130] 2. Add 70 μL of purified water to each sample reaction tube in sequence;

[0131] 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.

[0132] 4. Incubate at room temperature for 5 minutes;

[0133] 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.

[0134] 6. Take 30 μL of the incubated magnetic beads and add them sequentially to an eight-tube or PCR tube containing the supernatant. Shake to mix and then briefly incubate to completely mix and resuspend the DNA and magnetic beads.

[0135] 7. Incubate at room temperature for 5 minutes;

[0136] 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.

[0137] 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.

[0138] 10. Repeat step 9 above for a second wash;

[0139] 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;

[0140] 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.

[0141] 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 ≥0.5 ng / μL. Otherwise, the library preparation sample does not meet the requirements and should be reconstructed.

[0142] 14. Perform deep sequencing on an Illumina MiniSeq sequencer, with each sample being sequenced at 300M.

[0143] (vi) Processing sample sequencing data

[0144] NGS sequencing data processing standards: FastP was used for quality control of the sequencing data, removing adapter sequences, low-quality short sequences, or simple repetitive sequences. The data was compared with the human genome reference sequence, and the sequencing depth for each locus was no less than 5000X. Plasma methylation data from 119 early-stage (stage I and II) lung cancer patients and 83 healthy individuals were divided into a training set (plasma from 64 early-stage lung cancer patients and plasma from 45 healthy individuals) and a validation set (plasma from 55 early-stage lung cancer patients and plasma from 38 healthy individuals).

[0145] (vii) Screening of markers

[0146] Using the control gene ACTB as a comparison result for the sulfite conversion assay, this invention ensures that the sulfite is completely converted to unmethylated sites. All 41 lung cancer-specific biomarkers contain multiple lung cancer methylation-specific sites. In the training set (plasma from 64 patients with early-stage lung cancer and plasma from 45 healthy individuals), this invention employs a specific threshold setting scheme to perform combined analysis on each site and each biomarker. While ensuring 100% specificity, the combination biomarker with the highest sensitivity is selected for hematological screening of early-stage lung cancer.

[0147] In the plasma methylation data of 64 early-stage lung cancer patients and 45 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 41 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 41 Lung Cancer Biomarkers". The score is calculated as sensitivity + weight * specificity, where the weight is 0.5.

[0148] 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 0.10-0.15), starting from a threshold of 0.1, with a methylation rate of at least 3 consecutive sites not less than 0.1. Rows 2 to 5 represent the sensitivity and specificity calculated for each site combination with a methylation rate of at least 0.1 for marker 1 at 3, 4, 5, 6, and 7 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.

[0149] 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 0.10–0.15.

[0150]

[0151] Continuing with priority, the two screening models (marker 1 and marker 2) from the markers with the highest ranking reference values ​​are added to the combined screening model candidate list. Subsequently, based on the marker ranking reference values, any screening model from each marker is combined with all models in the screening model candidate list. The sensitivity of the new combined model is recalculated based on the training sample set, and this expanded model is added to the same screening model candidate list. Whenever a new model is added to the screening model candidate list, each combined screening model in the list is reordered in descending order of sensitivity to eliminate the possibility that the addition of a new model will reduce the original sensitivity. The above process is repeated for each marker to expand the screening model candidate list as expected. After the complete expansion is completed, the combined screening model with the highest sensitivity is selected as the optimal combined screening model. The sensitivity ranking table of 41 lung cancer markers is shown in Table 9.

[0152] The results are shown in Table 10, "Optimal Diagnostic Performance of Lung Cancer Biomarkers." The results indicate that the combination of five biomarkers achieved a maximum sensitivity of 97.87% and a specificity of 100%. The biomarker combination was Biomarker 1|Biomarker 2|Biomarker 3|Biomarker 4|Biomarker 5, with threshold values ​​of 0.1000|0.1000|0.1000|0.1100|0.1000 respectively. Adjusting these threshold values ​​to 0.1000|0.1000|0.1000|0.1100|0.1100 or 0.1000|0.1000|0.1100|0.1200 would also achieve the same sensitivity and specificity.

[0153] Table 9. Sensitivity Ranking of 41 Lung Cancer Biomarkers

[0154]

[0155] Table 10. Diagnostic performance of optimal lung cancer biomarkers

[0156]

[0157] 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.

[0158] Comparative Example 1

[0159] In the plasma methylation data of 64 early-stage lung cancer patients and 45 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 lung 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 41 biomarker thresholds.

[0160] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0161] 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 lung cancer markers is shown in Table 11 below:

[0162] Table 11 shows the diagnostic efficacy of different lung cancer biomarkers, where a biomarker is considered positive if three consecutive sites are positive.

[0163]

[0164] The individual threshold values ​​for each lung cancer biomarker are shown in Table 12 below:

[0165] Table 12 Single thresholds for various lung cancer biomarkers

[0166]

[0167] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0168] A marker is considered positive if four consecutive sites are positive, and a sample is considered positive if even one site is positive. The diagnostic efficacy of different lung cancer markers is shown in Table 13 below:

[0169] Table 13 shows the diagnostic efficacy of different lung cancer biomarkers, where a biomarker is considered positive if four consecutive sites are positive.

[0170]

[0171] 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... 41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0172] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0173] 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... 41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0174] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0175] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0176] 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 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0177] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0178] 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 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0179] 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0180] 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 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...41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0181] 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 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... 41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0182] In the training set, if the methylation rate of 6 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...41 markers) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity).

[0183] 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... 41 biomarker combinations) are statistically calculated to determine the sensitivity range (minimum sensitivity - maximum sensitivity) of different combinations.

[0184] Combinations of samples with more consecutive methylation sites and more biomarkers (up to 41 biomarkers) as positive were used to statistically calculate the sensitivity range (minimum sensitivity - maximum sensitivity) for different combinations.

[0185] After extensive calculations, the results showed that the sensitivity ranged from 17% to 95% and the specificity was 100% when using combinations of four biomarkers (a biomarker is considered positive if three 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 101,270 combinations). Adding five or more biomarkers did not increase the maximum sensitivity; the highest sensitivity remained at 95%. Combinations of other positive biomarker criteria with four or more consecutive positive sites and positive sample criteria with two or more positive biomarkers showed even lower sensitivity. The sensitivity ranged from 9% to 91% and the specificity was 100% when using combinations of four biomarkers (a biomarker is considered positive if four 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 101,270 combinations). Adding five or more biomarkers did not increase the maximum sensitivity; the highest sensitivity remained at 91%. It can be predicted that its sensitivity will decrease as screening standards become higher.

[0186] Comparative Example 2

[0187] In the plasma methylation of 64 early-stage lung cancer patients and 45 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 lung 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 41 biomarker thresholds were obtained.

[0188] According to the statistical analysis of different combination schemes in Comparative Example 1, after a long period of calculation, the results showed that when there were 5 biomarkers (the biomarker was judged to be positive if the methylation value of 3 consecutive sites was not less than the methylation threshold, and the sample was judged to be positive if only 1 biomarker was positive) (a total of Combin(41,5) = 749398 combinations), the sensitivity ranged from 42% to 98%, and the specificity ranged from 80% to 100%. The specificity was 98% when the sensitivity was at its maximum of 98%. The addition of 6 or more biomarkers did not increase the maximum sensitivity, and the highest sensitivity remained at 98%. When using 6 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 749,398 Combin(41,5) = 749,398 combinations), the sensitivity ranges from 33% to 98%, and the specificity from 96% to 100%. The specificity is 96% at the maximum sensitivity of 98%. Increasing the number of biomarkers to 7 or more does not increase the maximum sensitivity; the highest sensitivity remains at 96%. It can be predicted that its sensitivity will decrease with higher screening standards.

[0189] In this comparative example, the individual thresholds for each lung cancer biomarker are shown in Table 14 below:

[0190] Table 14 Statistical table of single thresholds for various lung cancer biomarkers

[0191]

[0192] 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:

[0193] Table 15 shows the diagnostic efficacy of various marker combinations when three consecutive sites are positive.

[0194]

[0195] 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.

[0196] 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.

[0197]

[0198] Comparative Example 3

[0199] In the plasma methylation of 64 early-stage lung cancer patients and 45 healthy individuals in the training set, the thresholds of 41 early-stage lung cancer-specific biomarkers were all set to 0.1, and the sensitivity range of combinations was statistically analyzed according to different combinations in Scheme A.

[0200] After extensive calculations, the results showed that when using a combination of four biomarkers (where a biomarker is considered positive if three 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 101,270 combinations), the sensitivity ranged from 41% to 97%, the specificity from 78% to 100%, and the maximum specificity was 93% when the sensitivity was 97%. Increasing the number of biomarker combinations to five or more did not increase the maximum sensitivity; the highest sensitivity remained at 97%. Conversely, under the criteria of a biomarker being considered positive if four consecutive sites have methylation values ​​not less than the methylation threshold, and a sample being considered positive if only one biomarker is positive, a combination of six biomarkers (a total of 4,496,388 combinations) had a sensitivity range of 36% to 97%, a specificity from 80% to 100%, and a maximum specificity of 96% when the sensitivity was 97%. Increasing the number of biomarker combinations to seven or more did not increase the maximum sensitivity, which remained at 97%. It is predictable that the sensitivity will decrease with higher screening standards.

[0201] 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 17 below:

[0202] Table 17 shows the diagnostic power of a biomarker when three consecutive positive sites indicate a positive biomarker, and when a sample is positive if even one biomarker is positive.

[0203]

[0204] 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 18 below.

[0205] Table 18 shows the diagnostic efficacy when four consecutive positive sites indicate a positive biomarker, and when even one positive biomarker indicates a positive sample.

[0206]

[0207] 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.

[0208] Example 2

[0209] Methylation data from plasma samples of 55 patients with early-stage lung cancer and 38 healthy individuals were used as the validation set to validate the sensitivity and specificity of a 5-site combination (marker 1, marker 2, marker 3, marker 4, and marker 5), with thresholds (i.e., methylation rates) of 0.1000, 0.1000, 0.1000, 0.1100, and 0.1000, respectively.

[0210] 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 as shown in SEQ ID NO: 1-12), 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.

[0211] Calculate the sensitivity of the 5-site combination for lung cancer. Figure 1 The results showed that the optimal combination of sites selected in Example 1 had a diagnostic sensitivity of 98.18% (only one patient with early-stage lung cancer was not detected), a specificity of 100%, an area under the ROC curve (AUC) of 0.991, a lower limit of 95% confidence interval of 0.970, an upper limit of 1.000, a standard error of 0.011, and an asymptotic significance of 0.000 (based on the null hypothesis: true region).

[0212] Example 3

[0213] Methylation data from plasma of 55 patients with early-stage lung cancer and plasma of 38 healthy individuals were used as a validation set to verify the sensitivity and specificity of the two-site combination (marker 1 and marker 2). The threshold (i.e., methylation rate) for both was 0.1000, and the experimental method was the same as in Example 2.

[0214] Figure 2 The results showed that the sensitivity was 89.09% (6 early-stage lung cancer patients were not detected), the specificity was 100%, the area under the ROC curve (AUC) was 0.945, the lower limit of the 95% confidence interval was 0.896, the upper limit was 0.995, the standard error was 0.025, and the asymptotic significance was 0.000 (based on the null hypothesis: true region).

[0215] Example 4

[0216] Methylation data from plasma of 55 patients with early-stage lung cancer and plasma of 38 healthy individuals were used as a validation set to verify the sensitivity and specificity of the three-site combination (marker 1, marker 2, and marker 3). The threshold (i.e., methylation rate) for each marker was 0.1000. The experimental method was the same as in Example 2.

[0217] Figure 3 The results showed that the sensitivity was 92.7% (four early-stage lung cancer patients were not detected), the specificity was 100%, the area under the ROC curve (AUC) was 0.964, the lower limit of the 95% confidence interval was 0.923, the upper limit was 1.000, the standard error was 0.021, and the asymptotic significance was 0.000 (based on the null hypothesis: true region).

[0218] 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. Use of a reagent for detecting the methylation rate of a marker composition in the preparation of a product for the detection or diagnosis of lung cancer, characterized in that, The marker combination comprises 2 markers; the positions of the 2 markers on the reference genome are as follows: Marker 1 is located at the entire region of chr7: 27225502-27225602; Marker 2 is located at the entire region of chr5: 40681765-40681840; The reference genome is the reference genome of GRch37 version.

2. Use according to claim 1, characterized in that, The marker combination is selected from at least one of the following: (1) the marker 1, the marker 2, marker 3, marker 4 and marker 5; (2) the marker 1, the marker 2, marker 3, marker 4, marker 5 and marker 6; (3) the marker 1, the marker 2, marker 3, marker 4 and marker 6; (4) the marker 1, the marker 2, marker 3 and marker 4; (5) the marker 1, the marker 2 and marker 3; The positions of each marker on the reference genome are as follows: the marker 3 is located at the entire region of chr7: 27204905-27204986; the marker 4 is located at the entire region of chr7: 27228261-27228353; the marker 5 is located at the entire region of chr2: 63054088-63054184; the marker 6 is located at the entire region of chr14: 38724604-38724725, and the reference genome is the reference genome of GRch37 version.

3. Use according to claim 2, characterized in that, The marker 1 is located at the entire region of chr7: 27225502-27225602, which comprises 3 consecutive CpG sites; The marker 2 is located at the entire region of chr5: 40681765-40681840, which comprises 3 consecutive CpG sites; The marker 3 is located at the entire region of chr7: 27204905-27204986, which comprises 3 consecutive CpG sites; The marker 4 is located at the entire region of chr7: 27228261-27228353, which comprises 4 consecutive CpG sites; The marker 5 is located at the entire region of chr2: 63054088-63054184, which comprises 3 consecutive CpG sites; The marker 6 is located at the entire region of chr14: 38724604-38724725, which comprises 4 consecutive CpG sites.

4. Use according to claim 1, characterized in that, The lung cancer detection or diagnosis product is selected from at least one of the following: reagent, kit, chip, hybridization probe and sequencing library.

5. Use according to claim 1 or 2, characterized in that, The lung cancer detection or diagnosis product comprises primers for detecting the marker combination required for the lung cancer detection or diagnosis.

6. Use according to claim 5, characterized in that, The primer sequence for detecting the marker 1 is shown as SEQ ID NO. 1-2, the primer sequence for detecting the marker 2 is shown as SEQ ID NO. 3-4, the primer sequence for detecting the marker 3 is shown as SEQ ID NO. 5-6, the primer sequence for detecting the marker 4 is shown as SEQ ID NO. 7-8; the primer sequence for detecting the marker 5 is shown as SEQ ID NO. 9-10; and the primer sequence for detecting the marker 6 is shown as SEQ ID NO. 11-12.

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