Gastric cancer early diagnosis kit based on multi-gene methylation joint detection and application thereof

Abstract

The invention provides a stomach cancer early diagnosis kit based on multi-gene methylation joint detection and application thereof. The kit has high sensitivity and specificity, the advanced methylation specific PCR (MSP) technology is adopted, optimized primer and probe design is combined, methylated DNA as low as 0.1 pg / mu L can be accurately recognized, the detection sensitivity reaches 91.47%, the specificity reaches 95.39%, and the kit is remarkably superior to existing market products. The methylation state of the gene closely related to the gastric cancer is detected through multi-gene joint detection, and compared with single gene detection, the detection sensitivity and specificity are greatly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biotechnology, in particular to a gastric cancer early diagnosis kit based on multi-gene methylation joint detection and application thereof. BACKGROUND

[0002] Gastric cancer is one of the malignant tumors that seriously threatens human health worldwide. According to the latest data released by the International Agency for Research on Cancer (IARC) of the World Health Organization, there were about 108.9 million new cases of gastric cancer worldwide in 2020, and about 76.9 million deaths, ranking fifth in cancer-related deaths. In China, the incidence of gastric cancer is even more serious, with about 478,000 new cases and about 373,000 deaths each year, ranking first in the incidence and mortality of various malignant tumors. And due to the influence of population aging and dietary habits, the incidence of gastric cancer is on the rise, causing a heavy burden on society and family.

[0003] Due to the uneven regional distribution of medical resources in China at present, the popularization rate of early screening of gastric cancer is still low, and many gastric cancer patients are in the tumor progression stage when they are initially diagnosed, making surgical treatment difficult, with a high metastasis rate and poor prognosis. Current research suggests that the early symptom occurrence and pathological transformation process of gastric cancer is a pathological process with multiple stages, multiple influencing factors, and slow development. Excessive intake of nitrate, Helicobacter pylori infection, obesity and other factors can increase the risk of gastric cancer. In addition, changes in gene expression, gene mutations, and epigenetic changes are also closely related to the occurrence, development, invasion and metastasis of gastric cancer. In particular, due to the increase in social environmental pressure and changes in residents' dietary structure, the incidence of gastric cancer has shown a trend of younger age in recent years, and young and middle-aged gastric cancer patients have aggressive tumor, poor differentiation and large volume, etc. The malignant biological characteristics bring great mental and physical burden to patients. Therefore, it is particularly important to explore molecular diagnostic indicators, prognostic analysis factors and individualized treatment markers that can guide clinical diagnosis.

[0004] At present, gastroscopy combined with pathological biopsy is the gold standard for the diagnosis of gastric cancer. However, gastroscopy is an invasive procedure, and patients will experience a lot of pain during the examination, leading to low acceptance of the examination among some patients, especially high-risk groups. In addition, gastroscopy has a certain rate of missed diagnosis, especially for early micro lesions, which is prone to missed diagnosis due to limited field of view or inaccurate sampling.

[0005] Common serum tumor markers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) are convenient to detect, but their sensitivity and specificity in the diagnosis of gastric cancer are not ideal. Single marker detection often cannot accurately diagnose gastric cancer, and although joint detection can improve diagnostic efficiency, it still cannot meet the needs of early diagnosis. SUMMARY

[0006] The present application aims to overcome the shortcomings and deficiencies of the prior art, and provides a gastric cancer early diagnosis kit based on multi-gene methylation joint detection.

[0007] Another object of the present application is to provide the application of the gastric cancer early diagnosis kit based on multi-gene methylation joint detection.

[0008] The object of the present application is achieved by the following technical solutions:

[0009] A gastric cancer risk assessment kit based on multi-gene methylation joint detection comprises primers and probes for detecting gene methylation.

[0010] The genes include at least one of RASSF1A, CDH1 and p16.

[0011] The primers for detecting gene methylation include:

[0012] RASSF1A-F: TTATTTAGTGGGTAGGTTAAGTGTGTT;

[0013] RASSF1A-R: AACCTAAATACAAAAACTATAAAACCC;

[0014] CDH1-F: TTAGGTTTATGTTATTTTTTTGTTTTAGTT;

[0015] CDH1-R: CCTATAATCCCAACACTTTAAAAAAC;

[0016] p16-F: TAAATTTTATTTTTTTTAAAGGGTTT;

[0017] p16-R: CTTCTCAATAACTTCCTATTCATAC;

[0018] ACTB-F: GTTAGTTTATTATGGATGATGATAT;

[0019] ACTB-R: AAATACCTCTCTTACTCTAAACCTC;

[0020] The probes for detecting gene methylation include:

[0021] RASSF1A-probe: FAM-TGTGGTTGTCGTTGTTGTGGTCGTTTG;

[0022] CDH1-probe:

[0023] JOE-TTTAGTAGAGACGGGGTTTTATTGTGTTAGTTAGGATGGTT;

[0024] P16-probe: Texas Red-TAAGTGATGGGGCGGGGGATGGGGAAAG;

[0025] ACTB-probe: CY5-GTATTAGGGCGTGATGGTGGGTATGGGT.

[0026] The method for using the kit comprises the following steps:

[0027] The primers, probes and DNA to be detected are configured into a PCR reaction system, and the corresponding fluorescence channels are detected on a machine to output Ct values, and P values are calculated according to a formula and the results are judged.

[0028] The DNA to be detected is DNA after being converted by sulfite.

[0029] A marker for predicting the risk of gastric cancer comprises:

[0030] The methylation levels of RASSF1A, CDH1 and p16 genes.

[0031] The methylation levels of the RASSF1A, CDH1 and p16 genes are detected by primers and probes through PCR, are quantified according to reaction Ct values, and are calculated according to a formula, and if the calculation result is higher than a specified value, it is judged that the sample has a high risk of gastric cancer.

[0032] The formula is P = 0.85 * (-Ct_RASSF1A) + 0.9 * (-Ct_CDH1) + 0.75 * (-Ct_p16) + 90, wherein Ct_RASSF1A is the Ct value of the RASSF1A gene methylation detection, Ct_CDH1 is the Ct value of the CDH1 gene methylation detection, and Ct_p16 is the Ct value of the p16 gene methylation detection.

[0033] If the P value is greater than 2.0, the sample is judged to be positive, indicating a high risk of gastric cancer, and if the P value of the sample is less than 2.0, the sample is judged to be negative, indicating a low risk of gastric cancer.

[0034] The gastric cancer risk evaluation kit based on the combined detection of multiple gene methylation and / or the marker for predicting the risk of gastric cancer is applied to screening of gastric cancer treatment drugs.

[0035] The present application has the following advantages and effects relative to the prior art:

[0036] (1) The application has high sensitivity and specificity, adopts advanced methylation-specific PCR (MSP) technology, combines optimized primer and probe design, can accurately identify as low as 0.1 pg / μL of methylated DNA, the detection sensitivity reaches 91.47%, the specificity reaches 95.39%, which is significantly better than the existing market products.

[0037] (2) The application detects the methylation state of the genes closely related to gastric cancer, compared with single gene detection, greatly improves the sensitivity and specificity of detection, and can more accurately detect the risk of gastric cancer of the sample.

[0038] (3) The application only needs peripheral blood samples, avoids the invasiveness of gastroscopy, and can detect abnormal changes of RASSF1A, CDH1 and p16 gene methylation in the early stage of gastric cancer.

[0039] (4) The application is simple to operate, short in operation time, low in cost, good in stability and reliability, and good in repeatability. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 is the RASSF1A / CDH1 / p16 expression detection in gastric cancer cells.

[0041] Figure 2 is the RASSF1A / CDH1 / p16 expression detection electrophoresis map in gastric cancer cells.

[0042] Figure 3 is the RASSF1A / CDH1 / p16 promoter methylation detection result in gastric cancer cells.

[0043] Figure 4 is the RASSF1A / CDH1 / p16 promoter methylation result of tumor detection in a mouse orthotopic gastric cancer model.

[0044] Figure 5 is the RASSF1A / CDH1 / p16 promoter methylation result of blood free DNA detection in a mouse orthotopic gastric cancer model.

[0045] Figure 6 is a part of the clinical sample detection amplification curve result graph. DETAILED DESCRIPTION

[0046] The application will be further described in detail below in combination with examples and drawings, but the embodiments of the application are not limited thereto.

[0047] In the following embodiments, if the specific test conditions are not specified, the general test conditions or the test conditions recommended by the reagent company are usually used. If no special instructions are given, the materials, reagents, etc. used are reagents and materials obtained from commercial channels.

[0048] Experimental method of Example 1

[0049] 1.1 Prediction of methylation sites, primer design and probe synthesis

[0050] The present application adopts methylation-specific PCR (MSP) technology, and in view of the change of methylation state of RASSFlA / CDHl / pl6 gene in the process of gastric cancer, primers and probes capable of specifically recognizing the methylation and non-methylation regions of the three genes are designed, as shown in Table 1 and Table 2.

[0051] Table 1 Methylation detection primer

[0052]

[0053] Table 2 Methylation detection probe

[0054] Gene name Sequence Fluorescent channel RASSF1A FAM-TGTGGTTGTCGTTGTTGTGGTCGTTTG FAM CDH1 JOE-TTTAGTAGAGACGGGGTTTTATTGTGTTAGTTAGGATGGTT JOE P16 Texas Red-TAAGTGATGGGGCGGGGGATGGGGAAAG Texas Red ACTB CY5-GTATTAGGGCGTGATGGTGGGTATGGGT CY5

[0055] 1.2 PCR detection method

[0056] (1) Preparation of PCR pre-reaction solution

[0057] According to the amount of reaction sample, melt the PCR reaction solution and the primer mixture. Vortex mix the PCR reaction solution for 10-15 seconds, and centrifuge briefly. Each PCR reaction requires 12.5 μl of PCR reaction solution and 2.5 μl of primer mixture, 2 μL of sulfite-converted DNA template, and ddH2O to make up to 25 μL. Vortex mix the PCR pre-reaction solution, and centrifuge briefly to remove the liquid drops from the tube wall. Note: immediately re-freeze the PCR reaction solution and primer mixture after use.

[0058] (2) Preparation of PCR reaction plate

[0059] Add 15 μl of PCR pre-reaction solution to the tube holes of the selected 8-row PCR tube. Add 10 μl of DNA to the corresponding holes of the PCR tube. Seal with a tube cover, centrifuge at 1000 ± 100 rcf for 1 minute to make the mixture flow into the bottom of the tube and no bubbles appear. The sealed PCR tube can be stored at 2-8℃ for no more than 2 hours.

[0060] (3) PCR analysis system on machine

[0061] The PCR pre-reaction solution does not contain ROX or other dyes. RASSFlA selects FAM fluorescence channel, CDHl selects JOE fluorescence channel, P16 selects Texas Red fluorescence channel, and ACTB selects Cy5 channel. The reaction program is set as follows: 98℃ pre-denaturation for 5 minutes; followed by 45 cycles including 95℃ denaturation for 10 seconds, 63℃ annealing for 5 seconds, 58℃ extension for 30 seconds (collect fluorescence), and finally cooling to 25℃.

[0062] (4) Analysis condition setting

[0063] The analysis running result is that the starting point of the baseline is set as the 10th cycle, the ending point is set as the 18th cycle, the RASSF1A threshold value is 0.05, the CDH1 threshold value is 0.05, and the p16 threshold value is 0.05 (which can be fine-tuned according to the specific situation).

[0064] (5) Output data

[0065] The PCR data file is output in the txt or excel format to obtain the gene Ct value for subsequent calculation and analysis. The Ct value of ACTB as the internal reference gene is less than 35.0, which is considered as a valid sample.

[0066] 1.3 Cell experiment verification

[0067] In order to verify the effect of the several groups of primers designed in 1.1, the gastric cancer cells MGC-803 and normal cells GES-1 are cultured in the laboratory for detection to verify the detection effect, and the specific steps are as follows:

[0068] ① Cell recovery: the cell culture laboratory is routinely disinfected, and ultraviolet irradiation is performed for more than 30 min; DMEM / F12 culture solution and 0.25% trypsin are preheated in a constant temperature water bath box at 37°C for 10 min for standby; the gastric cancer cells MGC-803 and normal cells GES-1 cryopreservation tubes are taken out from the liquid nitrogen storage tank and immediately placed in a 37°C water bath, and quickly shaken for 2 min to completely melt; the cell suspension is transferred into 15 ml centrifuge tubes, and 5 ml of culture solution is slowly added and centrifuged at 1000 r / min at room temperature for 5 min; the cell culture solution is used to resuspend the precipitated cells, the cell concentration is adjusted to 10^6 / mL, and the cells are cultured at 37°C with 5% CO2.

[0069] ② Cell culture and subculture: discard the old culture solution; add 2 ml of 37°C preheated PBS, gently shake to wash the cells; add 0.5 ml of trypsin digestion solution, digest at 37°C for 1-2 min until the cells are completely digested; add 5 ml of DMEM / F12 culture medium containing 10% fetal bovine serum, and terminate the digestion; subculture at a ratio of 1:3-10.

[0070] ③ After the cells are cultured for 48 h, the old culture solution is discarded; 1 ml of 37°C preheated PBS is added, and the cells are gently shaken to wash them; 0.2 ml of trypsin digestion solution is added, and the cells are digested at 37°C for 1-2 min until they are completely digested; 2 ml of DMEM culture medium containing 10% fetal bovine serum is added to terminate the digestion and collect the cells.

[0071] IV. Using blood / cell / tissue genomic DNA extraction kit (DP304 TIANGEN) to extract cell DNA, according to the nucleic acid extraction kit instructions to operate, sulfite conversion cell DNA, obtain 35 μl sulfite conversion DNA (BisDNA). Each sample test 3 PCR duplicate wells, sulfite conversion DNA (BisDNA) template volume can not be less than 32 μl.

[0072] 1.4 Experimental results

[0073] The experimental results are shown in Figures 1-3 It can be seen that the primers and probes designed in the application can effectively distinguish gastric cancer and normal cells.

[0074] Example 2 Clinical sample detection and verification

[0075] 2.1 Sample collection and processing

[0076] (1) Blood collection method

[0077] EDTA anticoagulant tube is used to collect 5 ml of venous blood. The blood sample collected using a general EDTA vacuum blood collection tube should be immediately separated into plasma. If the plasma cannot be separated immediately, it should be stored at 2-8℃ for no more than 4 hours; the plasma collected using a free DNA blood collection tube can be stored at room temperature for 4 days. The blood sample should not be frozen.

[0078] (2) Preparation and storage of plasma samples

[0079] The brake (emergency stop) function of the centrifuge should not be used to prevent damage to the blood cell layer.

[0080] The blood collection tube containing whole blood is centrifuged for 12 minutes at a centrifugal force of 1350±150 rcf. The blood collection tube is removed from the centrifuge, and a clean disposable pipette is used to transfer the plasma to a 15 ml centrifuge tube with a conical bottom made of polypropylene. The plasma is centrifuged for 12 minutes at a centrifugal force of 1350±150 rcf. A new disposable pipette is used to transfer 2.0 ml of plasma into a labeled conical-bottom centrifuge tube. The plasma sample can be stored at -20±5℃ for no more than 30 days. The plasma sample can be stored at 2-8℃ for no more than 12 hours.

[0081] 2.2 Plasma free DNA extraction and sulfite conversion

[0082] The blood / cell / tissue genomic DNA extraction kit (DP304 TIANGEN) was used to extract the plasma free DNA, and the operation was carried out according to the nucleic acid extraction kit instruction. 2ml plasma (2ml quality control) free DNA was converted by sulfite to obtain 35ul sulfite converted DNA (BisDNA). Each sample was tested with 3 PCR duplicate wells, and the volume of sulfite converted DNA (BisDNA) template should not be less than 32ul.

[0083] 2.3 Training set sample enrollment and data fitting

[0084] In the Fifth Affiliated Hospital of Guangzhou Medical University, 489 cases of effective sample number were enrolled in the case enrollment and positive judgment value research, aged 25-80 years old, including 141 cases of gastric cancer patients, pathologically confirmed as gastric cancer, diagnosed as I-IV stage; another 207 cases of normal gastric samples, 141 cases of other interference samples (including gastritis, enteritis, etc.). The experiment was agreed by the patient or patient's family, and was approved by the ethics committee of the Fifth Affiliated Hospital of Guangzhou Medical University.

[0085] The sample data were statistically analyzed by various methods, including 1 / 3 PCR reaction Ct value, 2 / 3 PCR reaction Ct value, 3 / 3 PCR reaction Ct value, 3 PCR reaction average Ct value, single gene, two genes, three genes, three gene combination fitting formula, etc. The detection sensitivity, specificity and total coincidence rate of different analysis methods were compared, and finally the three gene fitting P value formula method was determined as the highest detection accuracy. In order to determine the best critical point, the Youden index (the difference between true positive rate and false positive rate) was used to determine the most suitable sensitivity and specificity corresponding to the Cutoff value, and the ROC method was used for calculation. The accuracy is optimal when the Cutoff value is 2.0. The specific judgment method is as follows:

[0086] Each sample was tested by 3 PCR parallel tests, and the average Ct value of RASSF1A / CDH1 / p16 gene 3 duplicate wells was calculated, wherein the Ct value of each gene without amplification was defined as 45.0. When the Ct value of ACTB gene was <35.0, the sample detection result was valid. In the case of determining the validity of sample detection result, the sample P value >2.0 was judged as positive, and the sample P value <2.0 was judged as negative. The P value calculation formula is P=0.85*(-Ct_RASSF1A)+0.9*(-Ct_CDH1)+0.75*(-Ct_p16)+90.

[0087] Table 3 Normal gastric sample (207 cases)

[0088] Group name RASSF1A CDH1 p16 Negative results (examples) 203 205 198 Positive results (examples) 4 2 9

[0089] Table 4 Gastric cancer patient sample (141 cases)

[0090] Group name RASSF1A CDH1 p16 Negative results (examples) 6 4 7 Positive results (examples) 135 137 134

[0091] Table 5 Other interference samples (141 cases)

[0092] Group name RASSF1A CDH1 p16 Negative results (examples) 138 129 137 Positive results (examples) 3 12 4

[0093] 2.4 Validation set validation

[0094] In order to verify the sensitivity and accuracy of the detection method, the three-gene fitting formula and other positive judgment value methods were verified again using the test set samples. The effective number of cases in the test set study was 223, including 69 normal stomach samples, 51 gastric cancer patient samples, and 103 other interference samples.

[0095] The results showed that the specificity of the three-gene fitting P value formula method was 93.19% (95% CI: 90.65%-97.72%), the sensitivity was 92.47% (95% CI: 82.41%-96.53%), and the total coincidence rate was 91.74% (95% CI: 89.49%-95.99%). This detection method can effectively distinguish between gastric cancer samples and normal samples. Compared with single gene detection, it greatly improves the sensitivity and specificity of detection and can more accurately assist in the diagnosis of gastric cancer.

[0096] Table 6 Normal stomach samples (69 cases)

[0097] Group name RASSF1A CDH1 p16 Negative results (examples) 68 62 61 Positive results (examples) 1 7 8

[0098] Table 7 Gastric cancer patient samples (51 cases)

[0099] Group name RASSF1A CDH1 p16 Negative results (examples) 48 48 51 Positive results (examples) 3 3 0

[0100] Table 8 Other interference samples (103 cases)

[0101] Group name RASSF1A CDH1 p16 Negative results (examples) 99 95 92 Positive results (examples) Group name RASSF1A CDH1 Negative results (examples) Positive results (examples) Group name RASSF1A CDH1 Negative results (examples) Positive results (examples) 4 8 11

[0102] Quality control performance indicators:

[0103] Negative quality control: 1 negative quality control, 3 PCR parallel tests, RASSF1A 3 PCR reactions without Ct or average Ct > 43.0, CDH1 3 PCR reactions without Ct or average Ct > 43.0, p16 3 PCR reactions without Ct or average Ct > 43.0, internal reference ACTB amplification curve normal and average Ct ≤ 35.0, P value < 2.0.

[0104] Positive quality control: 1 positive quality control, 3 PCR parallel tests, the results are RASSF1A average Ct≤35.0, CDH1 average Ct≤35.0, p16 average Ct≤35.0, while the normal amplification curve of the internal reference ACTB and average Ct≤35.0, P≥2.0.

[0105] The above embodiments are the preferred embodiments of the present application, but the embodiments of the present application are not limited to the above embodiments, and any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present application should be equivalent replacement methods, and are included in the protection scope of the present application.

Claims

1. A gastric cancer risk assessment kit based on multiple gene methylation joint detection, characterized in that: it comprises primers and probes for detecting gene methylation. 2.The gastric cancer risk assessment kit based on multiple gene methylation joint detection according to claim 1, characterized in that: the genes include at least one of RASSF1A, CDH1 and p16. 3.The gastric cancer risk assessment kit based on multiple gene methylation joint detection according to claim 1, characterized in that: the primers for detecting gene methylation include: RASSF1A-F: TTATTTAGTGGGTAGGTTAAGTGTGTT; RASSF1A-R: AACCTAAATACAAAAACTATAAAACCC; CDH1-F: TTAGGTTTATGTTATTTTTTTGTTTTAGTT; CDH1-R: CCTATAATCCCAACACTTTAAAAAAC; p16-F: TAAATTTTATTTTTTTTAAAGGGTTT; p16-R: CTTCTCAATAACTTCCTATTCATAC; ACTB-F: GTTAGTTTATTATGGATGATGATAT; ACTB-R: AAATACCTCTCTTACTCTAAACCTC. 4.The gastric cancer risk assessment kit based on multiple gene methylation joint detection according to claim 1, characterized in that: the probes for detecting gene methylation include: RASSF1A-probe: FAM-TGTGGTTGTCGTTGTTGTGGTCGTTTG; CDH1-probe: JOE-TTTAGTAGAGACGGGGTTTTATTGTGTTAGTTAGGATGGTT; P16-probe: Texas Red-TAAGTGATGGGGCGGGGGATGGGGAAAG; ACTB-probe: CY5-GTATTAGGGCGTGATGGTGGGTATGGGT. 5.The gastric cancer risk assessment kit based on multiple gene methylation joint detection according to claim 1, characterized in that: the use method of the kit comprises the following steps: primers, probes and DNA to be tested are configured into a PCR reaction system, the corresponding fluorescence channels are detected on a machine, Ct values are output, P values are calculated according to a formula and results are judged. 6.The gastric cancer risk assessment kit based on multiple gene methylation joint detection according to claim 5, characterized in that: the DNA to be tested is DNA after sulfite conversion. The formula is P=0.85*(-Ct_RASSF1A)+0.9*(-Ct_CDH1)+0.75*(-Ct_p16)+90, wherein Ct_RASSF1A is the Ct value of RASSF1A gene methylation detection, Ct_CDH1 is the Ct value of CDH1 gene methylation detection, and Ct_p16 is the Ct value of p16 gene methylation detection. If the P value is greater than 2.0, the sample is judged to be positive, indicating a higher risk of gastric cancer; if the P value is less than 2.0, the sample is judged to be negative, indicating a lower risk of gastric cancer.

7. A marker for predicting the risk of gastric cancer, characterized by It comprises: The methylation levels of RASSF1A, CDH1 and p16 genes.

8. The marker for predicting the risk of gastric cancer according to claim 7, characterized in that: The methylation levels of RASSF1A, CDH1 and p16 genes are detected by primers and probes through PCR, quantified by reaction Ct value, and weighted calculation, and if the calculation result is higher than a specified value, it is judged that the sample has a high risk of gastric cancer.

9. The application of the gastric cancer risk assessment kit based on the combined detection of multiple gene methylation according to claims 1-6 in screening gastric cancer treatment drugs.

10. The application of the marker for predicting the risk of gastric cancer according to claims 7-8 in screening gastric cancer treatment drugs.

Images