Individualized medication detection system for children with acute lymphoblastic leukemia based on drug gene polymorphism

Abstract

The invention belongs to the technical field of gene detection, and relates to a drug gene polymorphism-based individualized drug use detection system for children with acute lymphatic leukemia. The drug detection system can be used for detecting gene combination or gene locus combination of a sample by utilizing the detection primer or the detection kit; the detection primer comprises an amplification primer and an extension primer, the amplification primer is a primer combination with a sequence as shown in SEQ ID NO.1-52, and the extension primer is a primer combination with a sequence as shown in SEQ ID NO.53-78. According to the method, multi-gene analysis can be carried out on a patient, more accurate drug dosage can be rapidly determined by combining pharmacogenomics characteristics of the patient, and on the premise that the curative effect is ensured, adverse reactions are reduced, and the medication compliance of a child patient is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of gene detection, and relates to an individualized drug detection system for children with acute lymphoblastic leukemia based on drug gene polymorphism. Background Art

[0002] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention, and should not necessarily be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art.

[0003] Acute lymphoblastic leukemia (ALL) is a type of acute leukemia and the most common malignant tumor in children. ALL mainly originates from B or T lymphocyte progenitor cells. Leukemia cells abnormally proliferate and aggregate in the bone marrow and inhibit normal hematopoiesis, leading to anemia, thrombocytopenia and neutropenia; leukemia cells can also invade extramedullary tissues such as meninges, gonads, thymus, liver, spleen, lymph nodes, bone tissue, etc., causing corresponding lesions. At present, the treatment principles of childhood ALL are similar internationally, using multi-drug combination therapy, which can be roughly divided into induction remission therapy, early intensive therapy, consolidation therapy, delayed intensive therapy and maintenance therapy. Anti-tumor drugs have different clinical responses for different patients, so it is necessary to adjust the dosage according to the patient's drug genotype to minimize the patient's adverse reactions.

[0004] Pharmacogenomic studies have shown that single nucleotide polymorphisms (SNPs) in the whole exon coding region are the material basis for individual differences in drug tolerance. Therefore, studying the diversity of various metabolic enzyme genes, transporter gene receptor-related genes, and disease pathway genes related to drug metabolism has become the key to achieving individualized drug treatment. However, pharmacogenetics is complex. The metabolic process of drugs in the body is often regulated by multiple enzymes. The polymorphism of drug metabolic enzyme genes determines the level of metabolic enzyme activity, resulting in different concentrations of drug metabolites in individuals, which ultimately leads to differences in adverse drug reactions. Summary of the invention

[0005] According to clinical needs, the present invention preliminarily screened 14 disease-related drugs, corresponding to 108 drug-related sites, and performed gene polymorphism detection on samples of 86 patients enrolled in the clinical group. According to the gene detection results, the patients were grouped, clinical indicators, blood drug concentrations, etc. were monitored, and the efficacy and adverse reactions of the drugs were evaluated. Finally, genes and sites with practical clinical significance for Chinese childhood leukemia patients were screened, and corresponding primers were designed according to the gene sites for corresponding detection.

[0006] Based on the above research results, the present invention provides an individualized medication detection system for children with acute lymphoblastic leukemia based on drug gene polymorphism, which can perform multi-gene analysis on patients and combine the patient's pharmacogenomic characteristics to quickly determine a more accurate drug dosage, thereby reducing adverse reactions and improving children's medication compliance while ensuring efficacy.

[0007] In order to achieve the above object, the technical solution of the present invention is:

[0008] In the first aspect, a gene combination for personalized medication guidance for children with acute lymphoblastic leukemia, the genes comprising ITPA, NUDT15, SLC19A1, GSTP1, IMPDH1, DROSHA, ABCB1, MTHFR, PNPLA3, TP53, CYP2E1, SLCO1B1, NQO1, GSTM1, GSTA1, ERCC1, CDA and TPMT.

[0009] Second, a gene locus combination for guiding personalized medication for children with acute lymphoblastic leukemia is shown in the following table;

[0010] Gene SNP site Gene SNP site ITPA rs1127354 SLCO1B1 rs4149056 NUDT15 rs116855232 NQO1 rs1800566 SLC19A1 rs1051266 GSTM1 rs3754446 GSTP1 rs1695 GSTA1 rs3957357 IMPDH1 rs2278293 GSTA1 rs3957356 DROSHA rs639174 ERCC1 rs11615 ABCB1 rs4728709 CDA rs602950 ABCB1 rs2032582 CDA rs3215400 MTHFR rs1801133 CDA rs2072671 PNPLA3 rs738409 TPMT rs1142345 TP53 rs1042522 TPMT rs1800460

[0011]

[0012] In the third aspect, a detection primer for personalized medication for children with acute lymphoblastic leukemia includes an amplification primer and an extension primer, wherein the amplification primer is a primer combination with a sequence as shown in SEQ ID NO.1 to 52, and the extension primer is a primer combination with a sequence as shown in SEQ ID NO.53 to 78.

[0013] In a fourth aspect, a detection kit for personalized medication for children with acute lymphoblastic leukemia comprises the above-mentioned detection primers and buffer.

[0014] In some embodiments, conventional reagent components for MassARRAY nucleic acid mass spectrometry detection are also included.

[0015] In a fifth aspect, a personalized drug detection system for children with acute lymphoblastic leukemia based on drug gene polymorphisms includes a detection system capable of detecting the above-mentioned gene combination or gene locus combination on a sample using the above-mentioned detection primers or detection kit.

[0016] In some embodiments, the detection system can perform any of the following methods: polymerase chain reaction, denaturing gradient gel electrophoresis, nucleic acid sequencing, nucleic acid typing chip detection, denaturing high performance liquid chromatography, in situ hybridization, biological mass spectrometry and HRM method.

[0017] In some embodiments, the detection system includes but is not limited to a sequencing detection system, a mass spectrometry detection system, and a PCR detection system, etc. Specifically, the detection system is a nucleic acid mass spectrometry detection system, preferably a MassARRAY detection system.

[0018] In some embodiments, the sample is blood, serum, plasma, cerebrospinal fluid, tissue or tissue lysate, cell culture supernatant, semen or saliva.

[0019] In a sixth aspect, a method for detecting individualized medication for children with acute lymphoblastic leukemia based on drug gene polymorphisms comprises the following steps:

[0020] Extract DNA from samples;

[0021] Performing PCR amplification on the extracted DNA using the above detection primers or the amplification primers in the detection kit;

[0022] The PCR amplification was enzymatically digested;

[0023] Using the above detection primer or the extension primer in the detection kit to extend the enzymatic hydrolysis product;

[0024] The product after the extension reaction is detected by mass spectrometry.

[0025] The beneficial effects of the present invention are:

[0026] The genes and sites screened by the present invention can evaluate the efficacy and adverse reactions of drugs. At the same time, the detection primers and detection kits provided by the present invention can detect the screened genes and sites, thereby realizing individualized medication guidance for children with acute lymphoblastic leukemia, thereby optimizing clinical treatment medication, improving drug efficacy, reducing or avoiding adverse reactions, improving prognosis and saving medical costs.

[0027] Experiments have shown that the detection primers and detection kit of the present invention can detect the screened genes and sites, thereby providing guidance to patients and effectively reducing adverse drug reactions. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0029] Figure 1 The figure is a full flow chart of the MassARRAY nucleic acid mass spectrometry detection of the present invention;

[0030] Figure 2 This is a statistical result diagram of NUDT15 genotype and 6-MP blood toxicity incidence in the present invention;

[0031] Figure 3 This is a statistical result diagram of NUDT15 genotype and 6-MP dosage tolerance of the present invention;

[0032] Figure 4 This is a statistical result diagram of the ABCB1 rs4728709 genotype and the incidence of vincristine blood toxicity in the present invention;

[0033] Figure 5 This is a statistical result diagram of the ABCB1 rs4728709 genotype and vincristine dosage tolerance of the present invention;

[0034] Figure 6 This is a result diagram before the primer optimization for the rs11127354 site of the present invention;

[0035] Figure 7 This is a result diagram before the primer optimization for the rs11127354 site of the present invention;

[0036] Figure 8 is the ROC curve of blood toxicity of the present invention;

[0037] Fig. 9 This is the ROC curve of hepatotoxicity of the present invention. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to more clearly understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below in conjunction with specific embodiments.

[0039] Experimental example: Basic detection method of MassARRAY nucleic acid mass spectrometry

[0040] The basic detection method of the present invention can be found in Figure 1 The process or the following specific steps:

[0041] 1. DNA sample extraction: follow the instructions of the nucleic acid extraction or purification kit.

[0042] 2. Testing steps:

[0043] 1. PCR amplification

[0044] ①Take out the required reagents, put the PCR Enzyme component on the ice box, and thaw the remaining components at room temperature and place them on the ice box for use. Shake and mix for 3 to 5 seconds before use, and centrifuge instantly. ②Prepare the PCR reaction system according to the formula table. ③After preparation, store the remaining reagents back to -20±5℃; seal the film, shake and mix for 30 seconds, centrifuge at 3000rpm for 30 seconds, and shake all the liquid on the tube wall to the bottom of the tube. If there are bubbles, flick and centrifuge until the bubbles are removed. ④Put the 384-well plate into the PCR instrument for thermal cycling reaction. ⑤After the product is removed from the machine, centrifuge at 3000rpm for 30 seconds, shake all the liquid on the tube wall to the bottom of the tube, and place it on the ice box for use.

[0045] 2. Enzymatic reaction

[0046] ① Take out the reagents required in the table below, put the component SAP Enzyme on an ice box, and thaw the remaining components at room temperature and place them on an ice box for use. Shake and mix for 3 to 5 seconds before use, and centrifuge instantly. ② Prepare the enzymatic reaction system according to the formula table:

[0047] Components Volume / μL x 2 / μL Nuclease-Free Water 1.53 3.06 SAP Buffer 0.17 0.34 SAP Enzyme (1.7U / μl) 0.3 0.6 Total 2 4

[0048] ③After preparation, store the remaining reagents back at -20±5℃; add the enzymatic mixture to the amplification product wells of the machine at 2μl / well; seal the film, shake and mix for 30s, centrifuge at 3000rpm for 30s, and shake all the liquid on the tube wall to the bottom of the tube. If there are bubbles, flick and centrifuge until the bubbles are removed. ④Put the 384-well plate into the PCR instrument for thermal cycling reaction. ⑤After the product is removed from the machine, centrifuge at 3000rpm for 30s, shake all the liquid on the tube wall to the bottom of the tube, and put it on the ice box for use.

[0049] 3. Extension reaction

[0050] ①Take out the reagents required in the table below, put the iPLEX Enzyme component on an ice box, and thaw the remaining components at room temperature and place them on an ice box for later use. Shake and mix for 3-5 seconds before use, and centrifuge instantly. ②Prepare the extension reaction system according to the formula table:

[0051] Components W1 / μL W2 / μL Nuclease-Free Water 0.62 0.62 iPLEX buffer 0.2 0.2 iPLEX Termination mix 0.2 0.2 Extend primer Mix 0.94 0.94 iPLEX Enzyme 0.04 0.04 Total 2 2

[0052] ③After preparation, store the remaining reagents back at -20±5℃; add the extension mixture to the enzymatic product wells of the machine at 2μl / well; seal the film, shake and mix for 30s, centrifuge at 3000rpm for 30s, and shake all the liquid on the tube wall to the bottom of the tube. If there are bubbles, flick and centrifuge until the bubbles are removed. ④Put the 384-well plate into the PCR instrument for thermal cycling reaction. ⑤After the product is removed from the machine, centrifuge at 3000rpm for 30s, shake all the liquid on the tube wall to the bottom of the tube, and set aside at room temperature.

[0053] 4. Mass spectrometry detection and analysis.

[0054] Example 1: Preliminary screening of drug types and gene loci

[0055] In order to achieve accurate evaluation of drug use for Chinese children, the applicant preliminarily sorted out the types of drugs that need to be included based on clinical needs, combined with clinical treatment plans for childhood leukemia and relevant literature reports. These types of drugs include drugs related to newly diagnosed acute lymphoblastic leukemia in children and drugs related to blood transplantation for childhood leukemia and refractory leukemia, a total of 15 drugs, including: mercaptopurine (6-MP), dexamethasone, vincristine, daunorubicin, asparaginase, cyclophosphamide, ifosfamide, methotrexate, cytarabine, doxorubicin, etoposide, busulphan, antithymocyte globulin, melphalan and fludarabine.

[0056] Potentially related genes and SNP sites were obtained based on drug retrieval, requiring that the mutation frequency of the relevant gene sites in a specific Chinese population was higher than 5%. 108 corresponding sites were obtained through preliminary screening, which are summarized in the following table.

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] Example 2: Evaluation and screening of sites

[0073] The applicant screened 86 patients according to the clinical trial inclusion and exclusion criteria and divided them into groups. Among the enrolled patients, there were 86 pediatric patients with ALL (41 males and 45 females); the average age was 6.2 years old, ranging from 2.1 to 15.8 years old; all patients received CCCG-ALL 2015 or 2018 treatment regimens.

[0074] The MassARRAY platform is used to analyze the pharmacogenomics of individualized treatment for patients, monitor clinical indicators, blood drug concentrations, etc., evaluate the efficacy and adverse reactions of drugs, and finally screen out gene loci that are significantly related to the clinical treatment of childhood leukemia in China, as follows:

[0075] 1. Operate the above-mentioned patient samples according to the instructions of the nucleic acid extraction or purification kit to obtain nucleic acid samples.

[0076] 2. Design amplification primers and UEP primers for all the aforementioned sites, establish a MassARRAY detection system, and use the aforementioned experimental process to detect and analyze the nucleic acid of each sample.

[0077] 3. Determine the adverse reaction evaluation criteria

[0078] Cardiotoxicity: If there are signs of heart failure or arrhythmia during treatment, electrocardiogram and cardiac ultrasound or arrhythmia should be checked. Cardiac toxicity can be judged to occur if the cardiac ejection fraction is <55% or the axial shortening fraction is <28% (CCLG-ALL-2008).

[0079] Liver Toxicity:

[0080]

[0081] Note: ALP: alkaline phosphatase; GGT: glutamyl transpeptidase; ALT: alanine aminotransferase; AST: aspartate aminotransferase; ULN: upper limit of normal; LLN: lower limit of normal.

[0082] Leukopenia: Grade 1: WBC count ≤ 3.0 × 10 9 / L; Level 2: ≥2.0-<3.0×10 9 / L; Level 3: ≥1.0-<2.0×10 9 / L; Level 4: <1.0×10 9 / L. WBC<2.0×10 9 / L is leukopenia [3] .

[0083] Pancreatitis: (i) Mild and moderate pancreatitis: pancreatic amylase and lipase > 3×ULN; (ii) Severe pancreatitis: abdominal pain for 72 hours, pancreatic amylase and lipase > 3×ULN, and evidence of pancreatitis on ultrasound or CT.

[0084] 4. Statistical analysis

[0085] SPSS25.0 statistical software was used for statistical analysis. One-way ANOVE analysis of variance was used to analyze the correlation between gene loci and adverse reactions and drug monitoring concentrations, and P<0.05 was statistically significant.

[0086] The specific statistical results are as follows:

[0087] 1) 6-Mercaptopurine (6-MP)

[0088] In this example, 61 patients were included in the analysis of 6-mercaptopurine-related samples.

[0089] (1) Leukopenia

[0090] According to the test statistics, 10 of the gene loci have statistically significant differences with the samples tested this time. Figure 2 The results are the correlation between the NUDT15 gene locus and the incidence of 6-MP blood toxicity. Figure 3 This is the result of the correlation between the NUDT15 gene locus and 6-MP dose tolerance. In addition, TPMT is one of the key enzymes in the 6-mercaptopurine metabolism process. In patients with TPMT enzyme deficiency, the conversion rate of mercaptopurine is reduced, and the use of standard doses of mercaptopurine may cause serious adverse reactions. It is an internationally recognized mercaptopurine-related gene that needs to be tested. Although the mutation frequency of the 4 TPMT loci in this sample is relatively low, considering its importance to 6-mercaptopurine drug metabolism and adverse reactions, the TPMT gene is retained.

[0091]

[0092]

[0093] There was no significant statistical significance between the gene loci rs3765534, rs1801131, rs1801133, and rs494852 and the sample analysis.

[0094] (2) Hepatotoxicity

[0095] No genetic loci significantly associated with 6-mercaptopurine-induced liver toxicity were found during the analysis.

[0096] 3) Related to metabolism

[0097] The analysis showed that the gene locus rs1801133 was statistically significant with the samples tested this time.

[0098] 2) Dexamethasone

[0099] A total of 71 patients were analyzed for dexamethasone-related samples, and no gene loci were found to be significantly associated with adverse reactions caused by dexamethasone. 3) Vincristine

[0100] A total of 71 patients were included in the analysis of vincristine-related samples.

[0101] (1) Leukopenia

[0102] One gene locus was detected to be statistically significant with the samples tested this time, and the others were not significant (see Figure 4 and 5 ).

[0103]

[0104] (2) Hepatotoxicity

[0105] One gene locus, ABCB1, was detected to be statistically significant with the samples tested this time, while the others were not significant.

[0106]

[0107] 4) Doxorubicin

[0108] A total of 71 patients were included in the analysis of doxorubicin-related samples.

[0109] (1) Leukopenia

[0110] One gene locus was detected to be statistically significant with the samples tested this time, and the others were not significant.

[0111]

[0112] (2) Cardiotoxicity

[0113] During the analysis, no genetic loci were found to be significantly associated with doxorubicin-induced cardiotoxicity.

[0114] 5) Daunorubicin

[0115] A total of 71 patients were included in the analysis of daunorubicin-related samples.

[0116] (1) Cardiotoxicity

[0117] No genetic loci significantly associated with daunorubicin-induced cardiotoxicity were detected in the analysis.

[0118] 6) Cyclophosphamide

[0119] A total of 71 patients were included in the analysis of cyclophosphamide-related samples.

[0120] (1) Leukopenia

[0121] Three gene loci were detected to be statistically significant with the samples tested this time, and the others were not significant.

[0122]

[0123] (2) Hepatotoxicity

[0124] No genetic loci were found to be significantly associated with cyclophosphamide-induced hepatotoxicity in the analysis.

[0125] 7) Cytarabine

[0126] A total of 71 patients were included in the analysis of cytarabine-related samples.

[0127] (1) Leukopenia

[0128] A total of 3 gene loci were detected that were statistically significant with the samples tested this time, as follows.

[0129]

[0130] (2) Hepatotoxicity

[0131] A total of 5 gene loci were detected that were statistically significant with the samples tested this time.

[0132]

[0133] 8) Methotrexate

[0134] A total of 71 patients' methotrexate-related samples were analyzed.

[0135] (1) Leukopenia

[0136] A total of 2 gene loci were detected that were statistically significant with the samples tested this time.

[0137]

[0138] 9) Asparaginase

[0139] A total of 71 patients were included in the analysis of pegaspargase-related samples.

[0140] (1) Pancreatitis

[0141] No genetic loci were found to be significantly associated with pegaspargase-induced pancreatitis in the analysis.

[0142] (2) Hepatotoxicity

[0143] No genetic loci were found to be significantly associated with pegaspargase-induced hepatotoxicity in the analysis.

[0144] 10) Etoposide

[0145] A total of 71 patients with etoposide-related samples were analyzed, and no gene loci significantly correlated with adverse reactions caused by etoposide were found.

[0146] 11) Ifosfamide

[0147] A total of 71 patients with ifosfamide-related samples were analyzed, and no gene loci significantly correlated with adverse reactions caused by ifosfamide were found.

[0148] 12)Busulphan

[0149] A total of 14 patients were analyzed for busulfan-related samples, and one patient developed liver toxicity. Based on the genetic analysis of this patient, the following gene loci are recommended:

[0150] (1) Hepatotoxicity

[0151] It was found that 3 gene loci were statistically significant with the tested samples, as follows.

[0152]

[0153] 13) Fludarabine

[0154] (1) Hepatotoxicity

[0155] A total of 14 patients were analyzed for fludarabine-related samples, and no gene loci significantly associated with fludarabine-induced liver toxicity were found.

[0156] 14) Melphalan

[0157] A total of 14 patients were analyzed for melphalan-related samples, and no gene loci significantly correlated with adverse reactions caused by melphalan were found.

[0158] 15) Antithymocyte globulin

[0159] A total of 14 patients with anti-thymocyte globulin-related samples were analyzed, and no gene loci significantly correlated with adverse reactions caused by anti-thymocyte globulin were found.

[0160] Based on the above analysis results, the present invention finally determined the following 26 gene loci to reflect the personalized medication tips for children.

[0161]

[0162] Example 3: Primer system design optimization

[0163] For the 26 SNP sites identified above, the MassARRAY primer sequences were redesigned and sequence optimization was performed after the initial design. Due to space constraints, the primer sequence optimization is only shown as an example.

[0164] Taking the rs1127354 site as an example, the amplification primers designed for the rs1127354 site in this embodiment were tested and found to have high and low peaks and mixed peaks in the amplification results (see Figure 6 ), adjust the primer sequence, add individual bases after the reverse primer (see the table below for details), appropriately reduce the above problems, and the amplification results after optimization are as follows Figure 7 The detection results were relatively ideal, and the optimized primer set was selected for system construction.

[0165]

[0166] After all sequences were evaluated by single system and multiplex system, the applicant finally determined the primer system as shown in the following table. The specific primers include amplification primers and UEP extension primers.

[0167]

[0168]

[0169]

[0170] Example 4: Detection system performance verification

[0171] Subsequently, based on the primer system of Example 3, the final MassARRAY detection system was established, and the performance of the system was verified. The system verification of this example included verification of precision, accuracy, sensitivity and specificity, and the clinical value of the system was demonstrated through verification and evaluation, as follows.

[0172] 1) Precision analysis

[0173] Experimental design: This experiment selected two samples of each sample type (peripheral blood and oral swab) for a total of four samples to complete the precision experiment. Each batch of experiments set up one NTC (water) and one standard NA12878. Primer Mix batches 1 and 2 were prepared at different times. The precision results of bioinformatics analysis are shown in the following table:

[0174]

[0175]

[0176] Intra-batch precision: Each sample was repeated 3 times in the same batch to compare the intra-batch precision:

[0177] Inter-batch precision: The same operator tests the same sample in multiple batches and compares the inter-batch precision;

[0178] Inter-individual comparison: 3 operators test the same sample and compare the differences in results between them;

[0179] Comparison between reagents: Use primer mixes from different batches to test the same sample and compare the differences between reagent batches.

[0180] Note: n / m means that there are m mutation sites in the sample and n mutation sites were successfully detected. For example: 26 / 26 means that there are 26 mutation sites in the sample and 26 mutation sites were successfully detected.

[0181] As can be seen from the experimental results in the above table, the precision within the batch, between batches and total precision are all 100%; the consistency rate of personnel comparison results is 100%; the consistency rate of results from different batches of reagents is 100%.

[0182] 2) Accuracy analysis

[0183] Experimental design: The accuracy analysis detection sites also include all 26 point mutations, and compare the MassARRAY and Sanger sequencing results; the validation samples include peripheral blood, oral swabs and standards, a total of 17 cases. The specific accuracy test results are shown in the table below:

[0184]

[0185]

[0186] It can be seen that using the first-generation Sanger sequencing results as the gold standard, the MassARRAY test results are completely consistent with an accuracy of 100%.

[0187] 3) Sensitivity analysis

[0188] Experimental design: Using accuracy data, the ratio of the number of samples judged as positive by both MassARRAY and the control test method to the number of samples judged as positive by the control test method, that is, true positive / (true positive + false negative) × 100%. The analysis sensitivity is ≥95%, which means the verification is passed.

[0189] The experimental results are also shown in the table above. Heterozygous mutation and homozygous mutation samples were regarded as positive samples. According to site statistics, Sanger detected 12 positive samples, including 4 heterozygous mutations and 8 homozygous mutations; MassARRAY detected 12 positive samples, including 4 heterozygous mutations and 8 homozygous mutations; analysis sensitivity = 12 / 12 = 100%.

[0190] 4) Specificity analysis

[0191] The specificity test results are also shown in the accuracy table. The homozygous wild-type samples were taken as negative samples. According to the site statistics, Sanger detected 14 negative samples and MassARRAY detected 14 negative samples. The analysis specificity = 14 / 14 = 100%.

[0192] In summary, the system of the present invention shows excellent results in terms of detection precision and accuracy as well as sensitivity and specificity, and the system can be effectively used for the detection of clinical samples.

[0193] Example 5

[0194] According to the inclusion and exclusion criteria of the clinical trial, 92 patients (50 males and 42 females) were screened and verified, with an average age of 7.1 years, ranging from 1.8 to 12.9 years; children with ALL were randomly divided into a standard dose group and a genetic testing guidance group; the genetic testing guidance group performed the above-mentioned gene polymorphism test before the start of treatment, and reduced the initial drug dose by 25%-75% based on the genetic test results. All patients used the CCCG-ALL 2018 treatment regimen. During the treatment of patients, 28 patients (60.8%) in the standard dose group developed hematotoxicity, and 13 patients (28.2%) in the genetic testing guidance group developed hematotoxicity, which was a decrease of 32.6% compared with the standard dose group (p = 0.003, OR = 0.25, 95% CI, 0.106–0.606; AUC = 0.665). Figure 8 As shown in the results, 16 patients (34.8%) in the standard-dose group developed hepatotoxicity, and 6 patients (13.0%) in the genetic testing-guided group developed hepatotoxicity, which was a decrease of 21.8% compared with the standard-dose group (p = 0.015, OR = 0.27, 95% CI, 0.095–0.779; AUC = 0.653). Fig. 9 shown.

[0195] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A gene combination for guiding personalized medication for children with acute lymphoblastic leukemia, characterized by: The genes include ITPA, NUDT15, SLC19A1, GSTP1, IMPDH1, DROSHA, ABCB1, MTHFR, PNPLA3, TP53, CYP2E1, SLCO1B1, NQO1, GSTM1, GSTA1, ERCC1, CDA and TPMT.

2. A gene locus combination for guiding personalized medication for children with acute lymphoblastic leukemia, characterized in that: As shown in the table below; 。 3. A detection primer for personalized medication for children with acute lymphoblastic leukemia, characterized in that: It comprises an amplification primer and an extension primer, wherein the amplification primer is a primer combination with a sequence as shown in SEQ ID NO.1-52, and the extension primer is a primer combination with a sequence as shown in SEQ ID NO.53-78.

4. A detection kit for personalized medication for children with acute lymphoblastic leukemia, characterized in that: The method comprises the detection primer and buffer according to claim 3.

5. The detection kit according to claim 4, characterized in that: Also included are conventional reagent components for MassARRAY nucleic acid mass spectrometry detection.

6. A personalized drug detection system for children with acute lymphoblastic leukemia based on drug gene polymorphism, characterized by: The invention comprises a detection system, wherein the detection system can detect the gene combination according to claim 1 or the gene locus combination according to claim 2 on the sample by using the detection primer according to claim 3 or the detection kit according to claim 4 or 5.

7. The detection system according to claim 6, characterized in that: The detection system can perform any of the following methods: polymerase chain reaction, denaturing gradient gel electrophoresis, nucleic acid sequencing, nucleic acid typing chip detection, denaturing high performance liquid chromatography, in situ hybridization, biological mass spectrometry and HRM method.

8. The detection system according to claim 6, characterized in that: The detection system includes but is not limited to a sequencing detection system, a mass spectrometry detection system and / or a PCR detection system. Preferably, the detection system is a nucleic acid mass spectrometry detection system; preferably, a MassARRAY detection system.

9. The detection system according to claim 6, characterized in that: The sample is blood, serum, plasma, cerebrospinal fluid, tissue or tissue lysate, cell culture supernatant, semen or saliva.

10. A method for detecting individualized medication for children with acute lymphoblastic leukemia based on drug gene polymorphism, comprising the following steps: Extract DNA from samples; Performing PCR amplification on the extracted DNA using the detection primers described in claim 3 or the amplification primers in the detection kit described in claim 4 or 5; The PCR amplification was enzymatically digested; Using the detection primer described in claim 3 or the extension primer in the detection kit described in claim 4 or 5 to perform an extension reaction on the enzymatic hydrolysis product; The product after the extension reaction is detected by mass spectrometry.

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