Biomarker composition and application thereof in methylation detection of MGMT promoter

Abstract

The invention belongs to the technical field of biological detection, and particularly relates to a biomarker composition and application thereof in methylation detection of an MGMT promoter. The biomarker composition is prepared from phospholipid (L5PL), creatinine (Creatinine) and ornithine (Ornithine) in the LDL-5 sub-component, and the biomarker composition is prepared from the phospholipid (L5PL), the creatinine (Creatinine) and the ornithine (Ornithine). Whether a glioblastoma patient carries MGMT promoter methylation or not is judged through a plurality of biomarkers, the method has the advantages of being good in sensitivity and specificity, small in patient trauma, capable of overcoming individual differences and the like, and a new solution is provided for prognosis evaluation of glioblastoma.

Description

Technical Field

[0001] The present invention belongs to the technical field of biological detection, and particularly relates to a biomarker composition and its application in the detection of MGMT promoter methylation. Background Art

[0002] Glioblastoma Multiforme (GBM), namely glioblastoma multiforme, is a highly malignant and fast-growing brain tumor, known for its invasiveness and high lethality. With the increasing aging of the global population, the number of glioma patients is rising year by year. According to the classification criteria of the World Health Organization (WHO), these tumors are classified into grade I and grade II (low-grade gliomas), grade III (anaplastic gliomas), and grade IV (glioblastomas). Since gliomas tend to grow invasively into normal brain tissue, complete surgical resection is extremely difficult. Therefore, efforts to improve the degree of surgical resection are ongoing. In addition, significant progress has been made in chemotherapy, immunotherapy, molecular targeted drugs, and radiotherapy, and these therapies have improved the prognosis of glioma patients.

[0003] The O-6-methylguanine-DNA methyltransferase (MGMT) gene is located on chromosome 10q26, and the protein encoded by it is responsible for repairing alkylation damage in DNA, especially the damage caused by chemotherapy drugs such as temozolomide. Research has shown that the methylation of CpG islands in the MGMT promoter region can lead to the silencing of this gene expression, thereby enhancing the sensitivity of tumor cells to alkylating agent chemotherapy drugs. It has been found that glioma patients with MGMT promoter methylation often show better treatment responses and longer survival periods when receiving temozolomide treatment. Specifically, the median overall survival of the MGMT unmethylated group is about 12 to 15 months, while the median overall survival of the MGMT methylated group is extended to about 21 to 27 months. This difference suggests that the MGMT promoter methylation status can be used as an important biomarker for predicting the efficacy of chemotherapy and helps to guide the selection of personalized treatment strategies.

[0004] Currently, the detection of the methylation status of the MGMT promoter mainly relies on methods such as quantitative real-time PCR or bisulfite sequencing using tissue samples obtained from surgery. However, such invasive procedures not only increase the surgical risk for patients but may also lead to complications such as brain swelling or nerve function impairment. Therefore, the development of non-invasive methods for detecting MGMT promoter methylation is of great significance for the prognosis assessment and treatment plan optimization of glioblastoma. Although imaging techniques such as magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), perfusion imaging, magnetic resonance spectroscopy (MRS), and positron emission tomography (PET) combined with specific tracers have been used to assist in judging the methylation status of the MGMT promoter, these methods have shown certain potential in predicting the MGMT methylation status, especially at the level of changes in macroscopic structure and metabolic activity. However, at the molecular level, their sensitivity and specificity are still limited and cannot replace direct molecular biology detection methods (such as methylation-specific PCR, bisulfite sequencing, etc.). Summary of the Invention

[0005] In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a biomarker composition and its application in the detection of MGMT promoter methylation.

[0006] The biomarker composition provided by the present invention can achieve efficient and non-invasive detection of the methylation status of the MGMT promoter. The application of this biomarker composition can not only provide more accurate diagnostic information for clinicians but also support personalized treatment decisions, thereby improving the quality of life and life expectancy of patients.

[0007] According to the first aspect of the present invention, the present invention provides a biomarker composition, which includes phospholipids (L5PL), creatinine, and ornithine in the LDL-5 subfraction. The biomarker composition provided by the present invention is a group of blood lipid metabolism markers. The present invention can help quickly and accurately identify whether glioblastoma patients carry MGMT promoter methylation through the combination of multiple biomarkers.

[0008] According to the second aspect of the present invention, the present invention provides a detection reagent for the biomarker composition, which can be used to detect the metabolic level of the biomarker composition.

[0009] In some embodiments, when the above detection reagent is used to detect the metabolic level of the biomarker composition, the detected sample includes the serum or plasma of the subject to be tested.

[0010] According to the third aspect of the present invention, the present invention provides the application of the biomarker composition and the detection reagent of the biomarker composition in the preparation of a detection product for MGMT promoter methylation in glioblastoma patients.

[0011] According to the fourth aspect of the present invention, the present invention provides the application of the biomarker composition and the detection reagent of the biomarker composition in the preparation of a prognosis evaluation product for glioblastoma patients.

[0012] According to the fifth aspect of the present invention, the present invention provides a kit, which includes a detection reagent for the biomarker composition.

[0013] According to the sixth aspect of the present invention, the present invention provides a detection model for MGMT promoter methylation in glioblastoma patients. In this detection model, it is judged whether a glioblastoma patient carries MGMT promoter methylation through the following formula;

[0014] mutation index = W 0 +W 1 X 1 +W 2 X 2 +...+W n X n , where n is the number of biomarkers, and n takes the value of 3; the mutation index is normalized using the Sigmoid function 1 / (1 + e (-x) ) to obtain the risk coefficient RS, that is, RS = 1 / (1 + e (-x) ); if RS ≥ the threshold value, it is judged that the glioblastoma patient carries MGMT promoter methylation; if RS < the threshold value, it is judged that the glioblastoma patient carries the wild-type MGMT promoter; X 1 、X 2 、X 3 are respectively the detection values of the metabolic levels of phospholipids, creatinine, and ornithine in the LDL-5 subcomponent; W 1 、W 2 、W 3 are respectively the weight coefficients of phospholipids, creatinine, and ornithine in the LDL-5 subcomponent; W 1 takes the value of 0.094771481, W 2 takes the value of 6.644420484, W 3 takes the value of 18.03435936; W 0 takes the value of -2.711341715; the threshold value is 0.50.

[0015] According to the seventh aspect of the present invention, the present invention provides a method for constructing a detection model for MGMT promoter methylation in glioblastoma patients, the method comprising the following steps: collecting MGMT promoter methylation samples and MGMT promoter wild-type samples from glioblastoma patients, performing plasma metabolite detection, screening significantly differentially expressed metabolites, modeling using a machine learning algorithm of logistic regression, selecting a preferred model, and using the model with the largest AUC in the test set of the preferred model as the optimal screening model, namely the detection model; the metabolites include phospholipids, creatinine and ornithine in the LDL-5 subfraction.

[0016] Compared with the prior art, the present invention has the following beneficial effects and advantages:

[0017] (1) The present invention provides a biomarker composition, which can help diagnose whether the MGMT promoter of glioblastoma patients is methylated;

[0018] (2) The present invention provides a detection reagent and a diagnostic kit, which can complete the detection only by obtaining serum or plasma, is convenient for sampling, has a low detection cost, and is suitable for the prognosis evaluation of glioblastoma patients;

[0019] (3) The biomarker composition provided by the present invention can effectively overcome the differences between individuals by combining multiple biomarkers, and improve the detection sensitivity and specificity. Specific embodiments

[0020] The following further describes the present invention in detail with reference to embodiments, but the embodiments of the present invention are not limited thereto. It should be noted that for the processes or parameters not specifically described in detail below, those skilled in the art can understand or implement them with reference to the prior art.

[0021] Example 1: Model construction

[0022] Collect EDTA plasma samples from glioblastoma patients, obtain the MGMT promoter methylation information of the patients by methylation sequencing method, and divide them into a methylation group and an unmethylated group according to the MGMT promoter methylation status of the patient samples. A total of 34 cases in the unmethylated group and 23 cases in the methylation group samples were collected.

[0023] Equipment, materials and reagents:

[0024] (1) Instruments: Nuclear magnetic resonance spectrometer (600MHZ) (provided by Bruker Biospin AG);

[0025] (2) Main reagents: NMR blood lipid buffer (purchased from Bruker Biospin AG, model name: Plasmabufer), NMR tubes (purchased from Bruker Biospin AG, model name: NMR Tubes / cap3)

[0026] Sample detection:

[0027] 1. Take out each plasma sample from the refrigerator respectively. After waiting for complete thawing, take 340 μL of each plasma sample and mix it with 340 μL of NMR blood lipid buffer (Bruker Plasma buffer) at a ratio of 1:1. After thorough mixing, take 600 μL of the mixed solution and place it in a 5 mm NMR tube;

[0028] 2. Load the NMR tubes in step 1 into the autosampler and perform detection using the plasma detection program of a nuclear magnetic resonance spectrometer (600 MHZ) to obtain a detection spectrum;

[0029] 3. Normalize the detection spectrum in step 2 through the QuantRef management system built into the Topspin software of the nuclear magnetic resonance spectrometer (600 MHZ) to normalize the intensity of the spectrum to the proton concentration in mmol / L. Use TSP (sodium 3-trimethylsilylpropionate) and the alanine doublet signal at 1.48 ppm to correct the chemical shift. Perform qualitative analysis on the detection spectrum based on the Bruker nuclear magnetic resonance self-built library of the nuclear magnetic resonance spectrometer (600 MHZ). Use the integral of the signal group at a specific chemical shift position to quantify the metabolites and obtain the metabolite content data in the sample;

[0030] 4. Screen the differential indicators for the obtained metabolite content data (114 blood lipid indicators and 39 small molecule metabolite indicators), including the following steps:

[0031] a) Fill in the lowest detection limit LOD of each indicator for the null values;

[0032] b) Take the median of each indicator in each group (unmethylated group, methylated group) and mark them as Mn_pos and Mn_neg respectively;

[0033] c) Take the ratio of the medians of each indicator in the two groups as the differential multiple Fn = Mn_pos / Mn_neg;

[0034] d) Perform a t.test calculation on the numbers of each indicator in the two groups to obtain pn;

[0035] e) Screen the indicators with Fn ≥ 1.5 or Fn ≤ 0.67 and pn < 0.05;

[0036] 5. Obtain three indicators that meet the differential indicators: phospholipids (L5PL), creatinine, and ornithine in the LDL-5 subfraction. The screening indicators are shown in Table 1:

[0037] Table 1 Differential Indicator Values

[0038] FC (fold change) p Creatinine 1.62 0.0467 L5PL (Phospholipid) 1.77 0.0286 Ornithine 3.70 0.0318

[0039] 6. Based on the sample test data of the three indicators, establish a model using the logistic regression method, select the optimal model, and use the model with the largest AUC (AUC = 0.96) in the test set of the optimal model as the optimal screening model, which is the detection model. Among them: mutation index = W 0 +W 1 X 1 +W 2 X 2 +W 3 X 3 , W 1 , W 2 , W 3 are the weight coefficients of phospholipids (L5PL), creatinine, and ornithine in the LDL-5 subfraction respectively; W 1 , W 2 , W 3 are 0.094771481, 6.644420484, and 18.03435936 respectively, and their corresponding markers are phospholipids (L5PL), creatinine, and ornithine in the LDL-5 subfraction respectively; X 1 , X 2 , X 3 are the detection values of the metabolic levels of phospholipids (L5PL), creatinine, and ornithine in the LDL-5 subfraction respectively; the constant W 0 is -2.711341715.

[0040] 7. Normalize the mutation index Sigmoid of each sample using the function 1 / (1+e (-x) ) to obtain the risk coefficient RS = 1 / (1+e (-x) ). When determining whether a glioblastoma patient carries MGMT promoter methylation or evaluating the prognosis of a glioblastoma patient, if the patient's RS ≥ the threshold, it is determined that the glioblastoma patient carries MGMT promoter methylation and has a good prognosis; if RS < the threshold, it is determined that the glioblastoma patient carries the wild-type MGMT promoter and has a relatively poor prognosis.

[0041] Example 2: Sample Detection and Verification

[0042] 1. Fifteen glioblastoma patients were selected and the methylation status of the MGMT promoter was detected using methylation sequencing; at the same time, the corresponding EDTA plasma samples of these 15 patients were obtained;

[0043] 2. The risk scores RS of the 15 patients were obtained according to Steps 1, 2, 3, 6, and 7 in Example 1;

[0044] 3. Determine whether the patient's RS is greater than 0.5 to determine the methylation status of the MGMT promoter in the patient sample. If RS≥0.5, it is determined that the MGMT promoter of the sample has been methylated. If RS < the threshold, it is determined that the MGMT promoter of the sample has not been methylated;

[0045] By collecting 15 patient samples, the RS values were obtained through detection and compared with the methylation status of the MGMT promoter detected by methylation sequencing. The results are shown in Table 2 below.

[0046] Table 2 Detection of patients and methylation of the MGMT promoter

[0047]

[0048]

[0049] The statistical results showed that among the 15 verified patient samples collected, 6 were positive and 9 were negative for MGMT promoter methylation detected by methylation sequencing. When evaluated using this method, 14 samples were correct. One positive sample had a score of 0.47, close to the threshold of 0.5, and was judged negative by this method. The overall accuracy rate of the small verification cohort was 93%.

[0050] The above embodiments are only the preferred embodiments of the present invention, which are only used to explain the present invention and not to limit the present invention. Any changes, substitutions, modifications, etc. made by those skilled in the art without departing from the spirit and essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A biomarker composition, characterized in that: Includes phospholipids, creatinine and ornithine in the LDL-5 subfraction.

2. The detection reagent of the biomarker composition according to claim 1, characterized in that: The detection reagent is used to detect the metabolic level of each biomarker in the biomarker composition.

3. The detection reagent of the biomarker composition according to claim 2, characterized in that: The metabolic level of each biomarker in the biomarker composition is detected, and the sample detected includes serum or plasma of the subject.

4. Use of the biomarker composition according to claim 1 or the detection reagent of the biomarker composition according to any one of claims 2 to 3 in the preparation of a product for detecting MGMT promoter methylation in glioblastoma patients.

5. Use of the biomarker composition of claim 1 or the detection reagent of the biomarker composition of any one of claims 2 to 3 in the preparation of a product for evaluating the prognosis of glioblastoma patients.

6. A kit, characterized in that A detection reagent comprising the biomarker composition according to any one of claims 2 to 3.

7. A model for detecting MGMT promoter methylation in patients with glioblastoma, characterized in that: In the detection model, the following formula is used to determine whether a glioblastoma patient carries MGMT promoter methylation: mutation index = W0 + W1X1 + W2X2 + ... + W n X n , where n is the number of biomarkers, and the value of n is 3; the mutation index is normalized using the Sigmoid function to obtain the risk coefficient RS; If RS≥threshold, it is judged that the glioblastoma patient carries MGMT promoter methylation; if RS<threshold, it is judged that the glioblastoma patient carries the wild-type MGMT promoter; the X1, X2, and X3 are the metabolic level detection values ​​of phospholipids, creatinine, and ornithine in LDL-5 subfractions, respectively; the W1, W2, and W3 are the weight coefficients of phospholipids, creatinine, and ornithine in LDL-5 subfractions, respectively; the W1 value is 0.094771481, the W2 value is 6.644420484, and the W3 value is 18.03435936; the W0 value is -2.711341715; the threshold is 0.50.

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