IDH1 / 2 gene multiplex digital PCR typing detection kit and application thereof

Abstract

The application provides an IDH1 / 2 gene multiplex digital PCR typing detection kit and application thereof. The application is directed to 7 hot mutation sites of R132H, R132C, R132G, R132S, R132L of the IDH1 gene and R140Q, R172K of the IDH2 gene, and realizes high typing capability, high sensitivity and high tolerance detection on a digital PCR platform through a primer probe design strategy combining LNA modification and MGB quenching technology, a two-tube multiplex reaction system distribution scheme, systematic optimization of mutant and wild type probe concentrations and establishment of independent negative reading thresholds for each target. The kit is simple to operate, consumes less sample and is suitable for IDH mutation screening and typing of tumor patients.

Description

Technical Field

[0001] This invention belongs to the field of molecular biology detection technology, specifically relating to an IDH1 / 2 gene multiplex digital PCR typing detection kit and its application, which is suitable for mutation screening and typing in cancer patients. Background Technology

[0002] Isocitrate dehydrogenase (IDH) is a key enzyme in cellular metabolism, encoded by the IDH1 and IDH2 genes. Somatic mutations in IDH1 and IDH2 are important molecular markers for various malignant tumors, particularly in acute myeloid leukemia (AML) and gliomas, where they have diagnostic, prognostic stratification, and treatment guidance value. In AML patients, the IDH1 mutation rate is approximately 6%-16%, and the IDH2 mutation rate is approximately 8%-19%. IDH1 / 2 mutations are not a single type but consist of multiple different amino acid substitutions. Most IDH1 / IDH2 mutations are located in mutation hotspot regions, namely IDH1 (R132H, R132C, R132G, R132L, and R132S) and IDH2 (R172K and R140Q). These seven mutations account for more than 95% of all IDH1 and IDH2 mutations in AML.

[0003] IDH mutation detection at initial diagnosis is fundamental for subsequent precision treatment and comprehensive management. The ELN 2022 guidelines state that while IDH mutation is not used as a standalone risk stratification indicator, it, along with co-mutation status such as NPM1 and allele load, collectively determines patient prognosis. Initial typing results can guide the selection of targeted therapy. The 2025 NCCN guidelines explicitly list IDH1 / 2 mutations as "interventional targets": IDH1 mutations can guide the use of evanixib or olutinib, while IDH2 mutations correspond to entsididine. These IDH inhibitors act on the allosteric sites of mutated IDH enzymes, blocking the conversion of α-ketoglutarate to the oncogenic metabolite 2-hydroxyglutarate, thereby inducing cancer cell differentiation. IDH1 / 2 mutations not only have high diagnostic and targeted therapy guidance value but are also being investigated as candidate biomarkers for molecular minimal residual disease (MRD) in AML.

[0004] Besides AML, IDH1 / 2 mutations also have significant diagnostic value in gliomas. According to the 5th edition of the WHO Classification of Tumors of the Central Nervous System, IDH mutation status is the gold standard for differentiating molecular subtypes of diffuse gliomas. Currently, the main technologies used clinically for IDH1 / 2 mutation detection include Sanger sequencing, real-time quantitative PCR (qPCR), and digital PCR (dPCR), but each has significant limitations. Sanger sequencing has limited sensitivity (approximately 15%-20%), making it difficult to meet the needs of low-frequency mutation detection; its accuracy at low concentrations still needs improvement; and it is cumbersome and has low throughput. qPCR is suitable for rapid screening, but its sensitivity is limited (the detection limit of commercially available kits is mostly 1%), it relies on standard curves, exhibits large batch-to-batch variability, and its multiplexing capability is limited, failing to comprehensively cover all mutation subtypes.

[0005] While dPCR offers advantages in high sensitivity and absolute quantification, existing protocols each have their own strengths in sensitivity, throughput, and genotyping capabilities, with no single protocol simultaneously achieving all three. Most reported dPCR detection systems have a detection limit of approximately 0.1%, with only a few reaching 0.07% or lower, and significant differences in detection limits exist between different mutation sites. Regarding multiplex detection, although commercial kits enable single-tube multiplex detection, they often employ regional broad detection or drop-off strategies, only reporting the presence of mutations and failing to distinguish specific subtypes or provide precise quantification. The protocols disclosed in patent applications CN113897430A, CN117402975A, and CN118308483A all have different limitations, either covering only a few sites, failing to distinguish between IDH1 R132 subtypes, or omitting IDH2 R140Q. Furthermore, primer-probe interference in multiplex systems can lead to droplet dispersion and difficulty in threshold setting, directly impacting the reliability of detecting low-frequency mutations. Most existing methods also lack systematic validation of their ability to stably detect low-frequency mutations under high input levels of wild-type DNA.

[0006] In summary, there is an urgent need in this field to develop a multiplex detection scheme for the IDH1 / 2 gene to address the following technical challenges: achieving clear subtype classification of multiple hotspot mutation sites while reducing the number of reaction tubes; ensuring stable detection of low-abundance mutations under high input levels of wild-type DNA and guaranteeing the reliability of the detection results; resolving the droplet dispersion problem in the multiplex system; and establishing independent negative interpretation thresholds for multiple sites to improve the specificity of low-frequency detection. Summary of the Invention

[0007] In one aspect, the present invention provides an IDH1 / 2 gene multiplex digital PCR genotyping kit, comprising a first detection reagent composition and a second detection reagent composition, wherein the first detection reagent composition comprises primers and probes for detecting mutations R132H, R132G, R132S, and R132C; and the second detection reagent composition comprises primers and probes for detecting mutations R140Q, R172K, and R132L.

[0008] In some implementations, the amplified sequence corresponding to the primer is 70-150 bp in length.

[0009] In some embodiments, the first detection reagent composition comprises primers with nucleotide sequences as shown in SEQ ID No. 1 and 7, respectively; and / or the second detection reagent composition comprises primers with nucleotide sequences as shown in SEQ ID No. 1, 7, 8, 9, 14 and 15, respectively.

[0010] In some embodiments, the first detection reagent composition includes probes capable of hybridizing with the reverse complementary sequences of the sequences shown in SEQ ID No. 3-6 under digital PCR reaction conditions; and / or the second detection reagent composition includes probes capable of hybridizing with the reverse complementary sequences of the sequences shown in SEQ ID No. 10, 11 and 13 under digital PCR reaction conditions.

[0011] In some embodiments, the first detection reagent composition comprises probes with nucleotide sequences as shown in SEQ ID No. 3-6, respectively; and / or the second detection reagent composition comprises probes with nucleotide sequences as shown in SEQ ID No. 10, 11 and 13, respectively.

[0012] In some embodiments, the first detection reagent composition further includes a probe with a nucleotide sequence as shown in SEQ ID No. 2; and / or the second detection reagent composition further includes a probe with a nucleotide sequence as shown in SEQ ID No. 12.

[0013] In some embodiments, the concentration of the probe with the nucleotide sequence shown in SEQ ID No. 5 in the first detection reagent composition is about 1.2 times (e.g., 1.1 times, 1.2 times, 1.3 times, and any value between 1.1 times and 1.3 times) that of the probe with the nucleotide sequence shown in SEQ ID No. 2.

[0014] In some embodiments, the concentration of the probe with the nucleotide sequence shown in SEQ ID No. 10 in the second detection reagent composition is about 1.7 times (e.g., 1.6 times, 1.7 times, 1.8 times, and any value between 1.6 times and 1.8 times) that of the probe with the nucleotide sequence shown in SEQ ID No. 12.

[0015] On the other hand, the present invention provides the application of the above-described detection kit in the preparation of products for screening and / or typing IDH1 / 2 gene mutations in samples of subjects.

[0016] In some implementations, the screening and / or genotyping is performed by digital PCR.

[0017] In some implementations, the sample contains not less than 100 ng of wild-type DNA.

[0018] This invention provides a multiplex digital PCR genotyping kit for the IDH1 / 2 gene. Through specific primer and probe sequences, a two-tube target combination, multi-fluorescence channel configuration, and site-specific reaction condition optimization, it achieves: high genotyping capability: completes definitive subtype genotyping of 7 hotspot mutations within two tubes; high sensitivity and high tolerance: stably detects 0.05% low-frequency mutations with an input of 100 ng wild-type DNA; good droplet clustering quality: effectively solves the droplet clustering problem at easily diffuse sites; clinical applicability: simple operation, low sample consumption, suitable for initial genotyping. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the embodiments will be briefly described below.

[0020] Figure 1 The degree of separation between positive and negative droplet groups in a single system was shown under different probe concentration ratios; Figure 2 The degree of separation between positive and negative droplet groups before and after optimization of probe concentration in the multiple system was shown; Figure 3 Example 1D diagram of positive / negative droplet clusters for IDH1 targets R132C, R132H, R132S, and R132G; Figure 4 Example 1D diagram of positive / negative droplet clustering for IDH1 R132L and IDH2 R140Q, R172K targets; Figure 5 Scatter plot to verify the sensitivity of 0.05% mutation (plasmid) with 100 ng wild-type DNA input in tube 1; Figure 6Scatter plot to verify the sensitivity of 0.05% mutation (plasmid) with 100 ng wild-type DNA input in tube 2; Figure 7 Scatter plot of droplet clusters of IDH1 R132C mutant plasmid and IDH1 R132H mutant plasmid in tube 1 when the sample used is a mixture of mutant plasmid and wild-type DNA (extracted from peripheral blood of healthy individuals); Figure 8 Scatter plot of droplet clusters of IDH1 R132S mutant plasmid and IDH1 R132G mutant plasmid in tube 1 when the sample used is a mixture of mutant plasmid and wild-type DNA. Figure 9 Scatter plot of droplet clusters for IDH2 R140Q mutant plasmid, IDH2 R172K mutant plasmid and IDH1 R132L mutant plasmid in tube 2 when the sample used is a mixture of mutant plasmid and wild-type DNA. Figure 10 The results of the multichannel droplet cluster scatter plot in tube 1 in mutant plasmids and clinical samples were verified under the optimal probe ratio when the samples used were clinical samples (peripheral blood / bone marrow). Figure 11 The results of the multichannel droplet cluster scatter plot in tube 2 in mutant plasmids and clinical samples were verified under the optimal probe ratio when the samples used were clinical samples (peripheral blood / bone marrow). Figure 12 This is a linear regression analysis graph showing the results of mutation frequency detection in clinical samples using the method of the present invention and the reference method. Figure 13 This is a Bland-Altman consistency analysis diagram between the method of this invention and the reference method. Detailed Implementation

[0021] Unless otherwise stated, all technical and scientific terms used herein have the meanings commonly understood by one of ordinary skill in the art.

[0022] As used herein, the term "or" refers to a single element among the listed alternatives, unless the context explicitly indicates otherwise. The term "and / or" refers to any one, any two, any three, any more, or all of the listed alternatives.

[0023] The terms “including,” “containing,” “having,” and similar expressions used herein do not exclude elements not listed. These terms also include cases where the text consists only of the listed elements.

[0024] As used herein, the term "subject" refers to any individual requiring diagnosis, prognosis, or treatment, who may be a patient with a disease or a healthy individual. This term is generally used interchangeably with "patient," "subject of testing," and "subject of treatment." Subjects include mammals, such as rats, mice, rabbits, cats, and cattle. Particularly preferred is a human subject.

[0025] As used herein, the term "sample" refers to any composition in any form that includes DNA molecules and can be used for digital PCR detection, including but not limited to DNA samples extracted from bone marrow or peripheral blood and artificially prepared samples containing DNA molecules (e.g., standards).

[0026] As used in this article, a "primer" is a short, single-stranded oligonucleotide (DNA or RNA) that specifically anneals to the template nucleic acid during nucleic acid amplification, serving as the starting point for DNA polymerase synthesis and guiding the extension of the downstream nucleic acid chain. Primers used for PCR amplification are generally used in pairs, including an upstream primer (or forward primer, F) and a downstream primer (or reverse primer, R). These primers hybridize to the 3' end region of the template strand and the 3' end region of the complementary strand of the template strand, respectively, guiding amplification in the 5'→3' direction.

[0027] As used herein, the term "probe" refers to a single-stranded oligonucleotide with a detectable label (such as a fluorescent group) that can specifically hybridize with a target nucleic acid sequence under hybridization conditions. Qualitative, quantitative, or genotyping detection of the target sequence is achieved by detecting changes in the label signal. In some embodiments of this invention, the probes used are TaqMan probes, which have a fluorescent group modified at one end (e.g., the 5' end) and a quencher group modified at the other end (e.g., the 3' end) of their nucleotide sequence. Examples of fluorescent groups include FAM, VIC, HEX, Cy5, etc., and examples of fluorescent quenchers include BHQ1, BHQ2, TAMRA, etc. During the extension phase of the PCR reaction, DNA polymerase (e.g., Taq polymerase) extends along the template strand. When it encounters a probe bound to the template strand, it hydrolyzes the probe using its 5'→3' exonuclease activity. The fluorescent group and the quencher group spatially separate, the quenching effect is released, and a fluorescent signal is released (or a change in the fluorescent signal occurs). In multiplex detection, different fluorescent groups are used to facilitate differentiation of the hydrolysis of different probes.

[0028] The term "hybridization" as used in this article refers to the process by which two single-stranded nucleic acid molecules form a double-stranded nucleic acid complex through hydrogen bonding under suitable ionic strength, temperature, and other conditions, based on the principle of complementary base pairing. "Specific hybridization" means that nucleic acid molecules preferentially hybridize with target nucleic acids that have high sequence complementarity, and generally do not form stable double-stranded complexes with non-target nucleic acids containing significant mismatches. "Hybridization under stringent conditions" only allows perfectly complementary nucleic acid sequences to form stable hybridized double strands. The "hybridization under digital PCR reaction conditions" used in this article refers to a situation where at most one terminal nucleotide mismatch is allowed, which is close to hybridization under stringent conditions. Specific hybridization conditions can vary depending on the selected ionic strength, temperature, and other conditions.

[0029] This invention distributes seven key hotspot mutation sites of the IDH1 / 2 gene into two reaction tubes, each containing a first detection reagent composition and a second detection reagent composition: tube 1 simultaneously detects the mutations IDH1 R132C, R132H, R132S, and R132G; tube 2 simultaneously detects the mutations IDH2 R140Q, R172K, and IDH1 R132L (the genotyping detection system is shown in Table 1). Each target formed clear positive and negative droplet clusters in its corresponding fluorescence channel, confirming the feasibility of the probe design described above (Figure 1). Figure 3 and Figure 4 ).

[0030] The beneficial effects of this invention are: Clear subtyping and filling gaps: The two-tube reaction distinguishes five common clinical subtypes of IDH1 R132 (R132H, R132C, R132S, R132G, R132L) and incorporates IDH2 R140Q and R172K into the system, which is different from the general detection scheme that only reports positive mutations in hotspot regions.

[0031] High sensitivity and high tolerance: Stable detection of 0.05% low-frequency mutations (VAF) at an input level of 100 ng, using a mixture of mutant plasmids and wild-type DNA. Example 4 ( Figure 5 and Figure 6 Data showed that the measured mutation frequency at each mutation site at the theoretical incorporation level of 0.05% was in high agreement with the theoretical value, and the detection rate was 100% for all 8 replicates.

[0032] Clear and crosstalk-free droplet clustering: By optimizing the mutant / wild-type probe ratio (mutant probe increased by 1.6-fold / wild-type probe decreased by 1.6-fold), the droplet clustering and diffusion problem of IDH1 R132S and IDH2 R140Q was significantly improved. Specificity verification (Example 5) showed that the present invention has good specificity in both simulated systems and real clinical sample matrices. Each mutant plasmid only generated a positive signal in the corresponding channel, with a cross-reactivity rate of 0; while clinical sample data showed that for different mutation sites, the number of false positive droplets was close to the corresponding independently set cut-off value.

[0033] The measured values ​​of the method of this invention are highly consistent with the reference values: Validation was performed using 25 bone marrow / peripheral blood samples (covering all 7 target sites and a wide dynamic range of approximately 0.5%-50%) confirmed by the reference method for IDH mutation. Linear regression analysis showed that the measured values ​​of the method of this invention are highly correlated with the reference values ​​(R0). 2 = 0.9817); Bland-Altman consistency analysis showed that the mean bias was 0.0074 (Log10 scale), and 92% (23 / 25) of the samples fell within the 95% consistency limit, indicating that the quantitative results of this kit in real clinical samples are in good agreement with the reference method and can be mutually verified with existing methods in clinical applications.

[0034] Primers and probes were designed based on IDH1 exon4 (reference sequence NG_023319, LRG_610) and IDH2 exon3-5 (reference sequence NG_023302, LRG_611) (see Example 1 for details on mutation sites and primer / probe information). The location of the detection target was confirmed using literature and the COSMIC database (cancer.sanger.ac.uk / cosmic). Primers and probes were designed and analyzed using SnapGene, bioEdit software, Thermo Scientific's online tool Multiple Primer Analyzer, and the IDT online tool (https: / / sg.idtdna.com / calc / analyzer / LNA), followed by multiple rounds of primer and probe screening. The strategies for probe and primer design included: ① By combining probes with different fluorescent labels, multiple mutation sites can be detected simultaneously in a single tube reaction, which is designed as a multiplex PCR detection system, greatly improving detection efficiency, saving samples and reducing costs.

[0035] ② Primers and probes were designed based on the positions of the mutated bases, and MGB quenching probes were used simultaneously. MGB binds to the minor groove region of the DNA double helix, stabilizing the probe-target hybrid. Compared with traditional TaqMan probes, MGB probes are shorter, have higher Tm values, lower tolerance for mismatches with wild-type sequences, and stronger ability to distinguish single-base mismatches.

[0036] ③ LNA modification: LNA contains bridging bicyclic glycosyl groups, which significantly enhances affinity with the complementary strand (each LNA base introduced can increase Tm by 2-8℃). When there is a mismatch between the LNA-modified probe and the target sequence, the stability of the hybrid strand decreases sharply, thereby significantly enhancing the specificity of single-base mutation recognition.

[0037] ④ Place the mutated base in the middle of the probe to maximize the mismatch effect.

[0038] ⑤ Mutant probe sequence matching mutant: Based on different base mismatch intensities, an additional mismatched base is introduced near the 3' end of the probe to further enhance specificity.

[0039] ⑥ The wild-type probe sequences are completely matched with the wild-type probes, with the wild-type probe in tube 1 being wild-type at position R132 and the wild-type probe in tube 2 being wild-type at position R172.

[0040] ⑦ The upstream and downstream primers should have a Tm value of approximately 58-60℃ and a length of 16-23 bp, avoiding continuous repetition of bases.

[0041] ⑧ The amplicon length is controlled at 70-150 bp to improve the efficiency of digital PCR amplification, enhance the ability to detect low-frequency mutations, and adapt to a variety of common clinical sample types.

[0042] Furthermore, to address the issues of blurred positive and negative droplet cluster boundaries and insufficient differentiation between low-frequency mutation signals and background at IDH1 R132S and IDH2 R140Q sites in multiplex digital PCR systems, this invention uses a single-detection system as a model to systematically optimize the concentration ratio of mutant probes to wild-type probes. The optimal optimization scheme is detailed in Example 2, and a comparison of clustering effects before and after optimization is shown in [example missing]. Figure 1 The optimal ratio was determined to be a 1.6-fold increase in the concentration of the mutant probe and a 1.6-fold decrease in the concentration of the wild-type probe. Applying this ratio to a multivariate system also significantly improved the clustering effect.

[0043] To address the differences in background noise at different mutation sites, this invention establishes independent positive thresholds (cut-off values) for each detection target to ensure the specificity of low-frequency mutation detection (see Example 6 for specific value establishment methods and threshold results).

[0044] Verification through examples shows that this invention can stably detect 0.05% low-frequency mutations with an input of 100 ng DNA, with no crosstalk or non-specific amplification between fluorescence channels, achieving stable detection of low-frequency mutations with high tolerance, high sensitivity, and high specificity. Based on a digital PCR platform, the copy number of each mutation site can be directly output as a result.

[0045] To further illustrate the present invention, the solutions provided by the present invention will be described in detail below with reference to the accompanying drawings and embodiments, but these should not be construed as limiting the scope of protection of the present invention.

[0046] Example 1: Design and synthesis of primers and probes Sequence and site information IDH1 sequence information: NG_023319: Homo sapiens isocitrate dehydrogenase (NADP(+))1 (IDH1), RefSeqGene (LRG_610) on chromosome 2. IDH2 sequence information: NG_023302: Homo sapiens isocitrate dehydrogenase (NADP(+)) 2 (IDH2), RefSeqGene (LRG_611) on chromosome 15; nuclear gene formitochondrial product. The IDH1 / 2 mutation site information is shown in Table 2, and the primer and probe sequences are shown in Table 3.

[0047] Table 1. Two-tube multiplex digital PCR typing system of the present invention Table 2 Information on IDH1 / 2 mutation sites Table 3. Primer and probe sequence and modification information Note: iXNA in the table indicates LNA modification.

[0048] Primer and probe sequence information IDH1-c.395G>A (p.R132H), amplicon length 119 bp; IDH1-c.394C>T (p.R132C), amplicon length 119 bp; IDH1-c.394C>G (p.R132G), amplicon length 119 bp; IDH1-c.394C>A (p.R132S), amplicon length 119 bp; IDH1-c.395G>T (p.R132L), amplicon length 119 bp; IDH2-c.515G>A (p.R172K), amplicon length 72 bp; IDH2-c.419G>A (p.R140Q), amplicon length 93 bp.

[0049] Example 2: Screening and Determination of Mutant / Wild-Type Probe Ratio Experimental samples: bone marrow-derived IDH1 R132S and IDH2 R140Q positive DNA.

[0050] Experimental methods: Using a single detection system as a model, mutant and wild-type probes with different concentration ratios were set up for the two sites IDH1 R132S and IDH2 R140Q, for a total of 6 groups.

[0051] ① Control: Initial concentration groups of mutant and wild-type probes; ② Mutant probe increased by 1.6-fold, wild-type probe remained unchanged; ③ Mutant probe increased by 1.6-fold, wild-type probe decreased by 1.6-fold; ④ Mutant probe increased by 1.6-fold, wild-type probe decreased by 2.5-fold; ⑤ Mutant probe increased by 2-fold, wild-type probe remained unchanged; ⑥ Mutant probe increased by 2-fold, wild-type probe decreased by 1.6-fold. Specific concentrations are shown in Tables 4 and 5 below: Table 4. Concentration of primers and probes in tube 1 Table 5. Concentration of primers and probes in tube 2 Except for the probe concentration ratio, which was set according to the grouping above, the primer concentration, DNA template input amount (100ng), and thermal cycling program in each reaction system were the same as in Example 3 below. The separation degree of positive and negative droplet groups in each group was compared, with the difference in fluorescence signal between the positive and negative groups as the main evaluation index. The larger the signal difference, the clearer the separation.

[0052] The results are as follows Figure 1 As shown. Figure 1The left side shows the results of the singlet screening system for the R132S locus, and the right side shows the results of the singlet screening system for the R140Q locus. From left to right, the control, 1.6x, 1.6x, 1.6x, 2x, and 2x ratios correspond to groups ① through ⑥, respectively. The horizontal axis represents the well location. Each group shows two replicates of one wild-type DNA sample (healthy individual) and one positive DNA sample (clinical sample). Figure 1 It was found that group ③ (mutant probe 1.6×, wild-type probe 0.625×) showed the clearest separation between positive and negative droplet populations and the largest difference in fluorescence signal, thus it was determined to be the optimal ratio in the singlet system. To further verify the effectiveness of the group ③ ratio in the multiplex reaction system, the group ③ ratio and the unoptimized control ratio (group ①) were applied to IDH1 quadruple (tube 1) and IDH2 triple (tube 2) systems for multiplex validation. The results are as follows: Figure 2 As shown, where Figure 2 The left-middle figure shows the multiplex system screening results for the R132S site; on the horizontal axis, 2C and 2D represent the results before optimization, and 3C and 3D represent the results after optimization. The right-middle figure shows the multiplex system screening results for the R140Q site; on the horizontal axis, 1A and 1B represent the results before optimization, and 2A and 2B represent the results after optimization. Figure 2 It can be seen that after adopting the ratio in group ③, the separation of positive and negative droplet populations at R132S (2C / 2D) and R140Q (2A / 2B) sites was significantly improved compared with before optimization (R132S was 3C / 3D, and R140Q was 1A / 1B). The boundary between the positive and negative populations was clearly distinguishable, proving that this ratio is also applicable to multiplex systems. Based on this, a 1.6-fold increase in mutant probe and a 1.6-fold decrease in wild-type probe were determined to be the final optimal ratio, and this probe ratio was used in all subsequent experiments.

[0053] Example 3: Establishment of a Two-Tube Multiple Reaction System The complete reaction system formulations for tubes 1 and 2 are shown in Tables 6-10.

[0054] Table 6. Concentration of primers and probes in tube 1 Table 7. Concentration of primers and probes in tube 2 Table 8. Concentrations of enzymes, buffer solutions, and other components Table 9 Thermal Cycling Procedure Table 10 Exposure Time for Each Channel Droplet generation and reading: Droplet signal detection was performed using a digital PCR platform based on endpoint imaging (such as the Sinaf Digital PCR Analyzer). This platform acquires the fluorescence signals of all droplets in a single static global imaging process, featuring high signal integrity, data traceability, and excellent repeatability. It also boasts a high upper limit of sensitivity, making it particularly suitable for the stable detection of low-frequency mutations. Specific operation should be performed according to the instrument's instruction manual.

[0055] A mutant plasmid containing the target sequences of IDH1 R132C, R132H, R132S, R132G, R132L and IDH2 R140Q, R172K (20 ng) was used as a positive template, and healthy human DNA (20 ng) was used as a negative control. Digital PCR amplification was performed according to the above reaction system and thermal cycling program. The scatter plot of 1D droplet clusters for each target is shown below. Figure 3 and Figure 4 As shown. By Figure 3 and Figure 4 It can be seen that each target forms a clear positive / negative binary in the corresponding channel, with clear cluster boundaries, which confirms the feasibility of the primer and probe design and that there is no mutual interference between channels.

[0056] Example 4 Sensitivity (LoD) Assessment The sample used in this embodiment was a mixture of mutant plasmid and wild-type DNA. The mutant plasmid contained the target sequences IDH1 R132C, R132H, R132S, R132G and IDH2 R140Q, R172K, R132L, which were designed by our company and synthesized by an external contractor. The wild-type DNA was extracted from peripheral blood of healthy individuals.

[0057] Experimental Methods: With an input of 100 ng wild-type DNA, each mutant plasmid was incorporated to a theoretical mutation frequency of 0.05%, with eight replicate wells for each mutation site. Digital PCR amplification and signal reading were performed according to the above reaction system and thermal cycling program. The effective droplet count, positive droplet count, and copy number of each channel were recorded for each reaction well. The mutation frequency (VAF) was calculated using the following formula: IDH1 R132C, R132H, R132S, R132G and IDH2 R172K: VAF = Mutant copy number / (mutant copy number + wild type copy number) × 100%.

[0058] IDH1 R132L and IDH2 R140Q: VAF = mutant copy number / wild-type copy number × 100% The results are as follows Figure 5 and Figure 6 As shown, Figure 5The 1D droplet cluster scatter plot is shown in tube 1 when IDH1R132C, R132H, R132S, and R132G mutant plasmids are incorporated into tube 1 with an input of 100 ng wild-type DNA, respectively, until the theoretical mutation frequency is 0.05%. Figure 6 The results show the 0.05% incorporation of the IDH2 R140Q, IDH2 R172K, and IDH1 R132L mutant plasmids in tube 2. Figure 5 and Figure 6 As can be seen, at the theoretical incorporation level of 0.05%, distinct positive droplet clusters were observed at each mutation site, with clearly distinguishable clusters compared to the negative control. The number of positive droplets, copy number, and measured mutation frequency for each mutation site are detailed in Tables 11 (tube 1) and 12 (tube 2). The mean measured mutation frequency of each target in eight repeated assays highly matched the theoretical value of 0.05%, and the detection rate of all eight repeated assays was 100%. These results demonstrate that the kit of this invention can stably detect low-frequency mutations of 0.05% at an input of 100 ng wild-type DNA.

[0059] Table 11 Data for 0.05% in Tube 1 Table 12 Data for 0.05% in Tube 2 Example 5 Specificity Verification 5.1 Plasmid-level specificity verification Experimental Samples: The samples used were single mutant plasmids (containing the target sequences of IDH1 R132C, R132H, R132S, R132G or IDH2 R140Q, R172K, R132L, at a concentration of 10). 6 (Copies / mL). The plasmid sequence was designed by our company and synthesized by an external supplier. NTC (template-free control) was set as a negative control.

[0060] Experimental Method: Each single mutant plasmid was added to the reaction systems in tubes 1 and 2, respectively. Digital PCR amplification and signal reading were performed according to the reaction system and thermal cycling program described in Example 3. The effective droplet count and copy number of each channel were recorded. If a mutant plasmid only produces a positive signal in its corresponding channel, while the copy number in other non-corresponding channels is 0 or close to 0, it is determined that there is no cross-reaction.

[0061] Experimental results are as follows Figures 7-9 As shown, Figure 7 Scatter plot of droplet clusters for IDH1 R132C mutant plasmid (VIC channel) and IDH1 R132H mutant plasmid (ROX channel) in tube 1; Figure 8Scatter plot of droplet clusters in tube 1 for IDH1 R132S mutant plasmid (CY5 channel) and IDH1 R132G mutant plasmid (ATTO425 channel); Figure 9 Scatter plot of droplet clusters in tube 2 for IDH2 R140Q mutant plasmid (VIC channel), IDH2 R172K mutant plasmid (ROX channel) and IDH1 R132L mutant plasmid (CY5 channel).

[0062] Depend on Figures 7-9 As can be seen, each mutant plasmid exhibits clear positive and negative droplet clusters in its corresponding fluorescence channel, with well-defined cluster boundaries, verifying that each probe can effectively distinguish between mutant and wild-type templates in its corresponding channel. The specificity verification results for tubes 1 and 2 are shown in Tables 13 and 14, respectively. The results show that each mutant plasmid only detected a positive signal in its corresponding fluorescence channel, with no positive signal detected in any non-corresponding channels (copy number 0); NTC showed no positive signal detected in any channel. These results indicate that the kit of this invention exhibits no cross-fluorescence interference or non-specific amplification at the plasmid level, with a cross-reactivity rate of 0.

[0063] Table 13 Specificity validation data for tube 1 (plasmid) Table 14. Specificity validation data for tube 2 (plasmid) 5.2 Validation of Clinical Sample Specificity Experimental samples: The samples used were IDH mutation-positive clinical samples (from bone marrow / peripheral blood), containing various mutation types including R132H (n=3), R132C (n=4), R132G (n=8), R132S (n=3), R140Q (n=4), R172K (n=3), and R132L (n=3).

[0064] Experimental Methods: After the concentration and purity of the extracted clinical sample DNA were determined, 100 ng was added to the digital PCR reaction. The reaction system and thermal cycling procedure described in Example 3 were followed for detection, and the copy number of each sample in each mutation channel was recorded. The independent cut-off value for each target established in Example 6 below was used as the interpretation standard. If the copy number of a sample in a non-corresponding channel was lower than the cut-off value of the corresponding target in that channel, it was determined that there was no non-specific cross-reactivity.

[0065] The results of clinical sample specificity verification are shown in Table 15 (tube 1) and Table 16 (tube 2).

[0066] Table 15 Specificity validation data for tube 1 (clinical samples: bone marrow / peripheral blood) Table 16. Specificity validation data for tube 2 (clinical samples: bone marrow / peripheral blood) As shown in Tables 15 and 16, under the optimal probe ratio, each mutation type in the clinical samples showed obvious positive signal clusters only in the corresponding channels, while no signals higher than the cut-off value were detected in non-corresponding channels, indicating good clustering quality (e.g., ...). Figure 10 and Figure 11 Based on the complete absence of cross-reactivity observed in plasmid validation, clinical samples, due to the complexity of the sample matrix (such as wild-type allele background, residual impurities from nucleic acid extraction, and potentially low-abundance background signals), occasionally exhibited extremely low levels of background signals in non-corresponding channels. However, these levels were all lower than the independent cut-off values ​​established for the corresponding targets in Example 6, indicating that these signals are normal background noise and do not constitute cross-reactivity or non-specific amplification. These results demonstrate that the kit of this invention also exhibits good channel specificity in real clinical samples, with non-specific background signals between targets all below the independently established cut-off values, thus not affecting the accurate interpretation of clinical samples.

[0067] Example 6: Establishment of a site-specific negative interpretation threshold Experimental samples: Wild-type DNA derived from peripheral blood of healthy individuals (100 ng each).

[0068] Experimental Methods: 100 ng of each sample was added to a digital PCR reaction, and the reaction system and thermal cycling procedure described in Example 3 were followed for detection. The number of positive droplets at each mutation site was recorded. For each mutation site, the mean (Mean) and standard deviation (SD) of the number of false positive droplets from 42 negative samples were calculated. The independent positive interpretation threshold for each mutation site was determined by mean + 3 × standard deviation (Mean + 3SD). This method ensures that the false positive rate of a single test is controlled below 0.15% (based on the normal distribution theory, Mean + 3SD corresponds to a false positive rate of approximately 0.135%).

[0069] The number of false positive droplets at each mutation site in the 42 negative samples is detailed in Table 17. The final cut-off values ​​for each mutation site are summarized in Table 18.

[0070] Table 17 Number of positive droplets in negative samples Table 18. Thresholds for Site-Specific Negative Interpretation As shown in Tables 17 and 18, when the number of positive droplets at a certain mutation site in a sample exceeds the corresponding cut-off value, it is determined to be a positive mutation at that site; if it is lower than or equal to the cut-off value, it is determined to be a negative mutation. The establishment of independent thresholds for each target effectively eliminates the risk of misjudgment caused by differences in background noise between different sites, ensuring the specificity of low-frequency mutation interpretation.

[0071] Example 7: Clinical Sample Consistency Validation Experimental Samples: A total of 25 IDH mutation-positive clinical samples (bone marrow / peripheral blood source) were included, covering all 7 target sites (R132H, R132C, R132G, R132S, R140Q, R172K, R132L). Each site contained multiple different abundance levels, with the original mutation abundance covering a wide dynamic range of approximately 0.5%-50%. Mutation types, measured values, and reference values ​​for each sample are detailed in Table 19.

[0072] Table 19 Comparison of measured and reference values ​​for different mutation sites Experimental Methods: In 25 samples, reference values ​​were determined using the Bio-Rad digital PCR platform and next-generation sequencing (NGS), respectively. Both methods are currently recognized technologies in the field of IDH mutation detection and quantification, and their quantitative results have been verified in numerous studies to have high reliability and reproducibility. This study treated the results of both methods as equivalent reference value estimates and included them in regression and consistency analyses to test the generalization ability of the method under different reference systems. To eliminate the heteroscedasticity of different abundance levels on statistical analysis and to satisfy the normality assumption, both the measured values ​​and reference values ​​of the kit were Log10 transformed, and all subsequent statistical analyses were based on the Log10 transformed data. The Log10 transformed reference values ​​were used as the x-axis, and the Log10 transformed measured values ​​of the kit as the y-axis. Linear regression analysis was performed using the least squares method to calculate the regression equation and the coefficient of determination (R²). 2 To assess the consistency of the results from the two methods, the Bland-Altman method was used for analysis over a wide dynamic range. For each sample, the mean after Log10 transformation [Log10(SNF measured value) + Log10(reference value)] / 2 was used as the x-axis, and the difference Log10(SNF measured value) - Log10(reference value) was used as the y-axis. The mean of the differences across all samples was calculated as the bias (BIAS), and the standard deviation (SD) of the differences was calculated. The 95% consensus boundary (LoA) was defined as BIAS ± 1.96 × SD.

[0073] Experimental results are as follows Figure 12 As shown, the paired linear regression analysis results after Log10 transformation are: regression equation y = 1.025x + 0.045, coefficient of determination R0 2 =0.9820. The regression slope of 1.025 is close to the ideal value of 1, and the intercept of 0.045 is close to 0, indicating that regardless of whether digital PCR or NGS is used as the reference benchmark, the method of this invention maintains a high linear correlation with the reference value. Figure 13 As shown, the Bland-Altman consistency analysis results indicate that the mean bias (BIAS) between the method of this invention and the reference method is 0.0157 (Log10 scale), corresponding to a geometric mean ratio of 1.037. This means that the measured values ​​of this method are on average approximately 1.037 times higher than those of the reference method, suggesting no systematic bias between the two methods. The 95% consensus limit (LoA) is -0.1693 to 0.2007 (Log10 scale), which, when converted to ratios, corresponds to the measured values ​​of this method being 0.68 to 1.59 times the reference values. In 25 paired samples, the differences in 23 samples (92%) fell within the 95% consensus limit. Based on the combined results of linear regression and Bland-Altman consistency analysis, the method of this invention and the reference method have good consistency in quantifying IDH mutation abundance. This verifies that the method has robust and accurate quantitative performance in different reference platforms (Bio-Rad dPCR, NGS) and different clinical sample sources (bone marrow, peripheral blood), supporting the reliable application of this kit in clinical samples.

[0074] Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, and not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

[0075] References: 1.Zarnegar-Lumley, S., et al., Characteristics and prognostic impact of IDH mutations in AML: a COG, SWOG, and ECOG analysis. Blood Advances,2023. 7(19): p. 5941-5953. 2.Di, J., et al., The Validation of Digital PCR–Based Minimal Residual Disease Detection for the Common Mutations in IDH1 and IDH2 Genes in Patients with Acute Myeloid Leukemia. The Journal of Molecular Diagnostics, 2025. 27(2): p. 100-108. 3. Wu Huirong, Cheng Juan, Research progress on IDH mutations in acute myeloid leukemia.International Journal of Medical Sciences, 2025. 33(05): p. 1534-1537. 4.Zeidan, AM and E. Wang, Advancing AML Treatment: Evidence-Based Regimens and Guideline Updates for Targeted Treatments in R / R AML [Podcast]. Blood and Lymphatic Cancer: Targets and Therapy, 2025: p. 69-7 5.Josephine, A., et al. IDH enzyme inhibition in cancer therapy: mechanisms, mutational insights, and effects of IDH inhibitors in glioma, acute myeloid leukemia and chondrosarcoma. 3 Biotech, 2026. 16(4): p. 137. 6.Boertjes, EL, et al., Utility of IDH1 / 2 mutations as biomarkers for detection of measurable residual disease in acute myeloid leukemia. BloodAdvances, 2025. 9(19): p. 4860-4 7.Dantec, M., et al. Disease characteristics and monitoring of IDH1 / IDH2-mutated acute myeloid leukemia. Blood Cancer Journal, 2025. 15(1): p.101. 8.Nikitsenka, K., et al. Improved Detection of Minimal Residual Disease in AML: Validation of IDH1 / 2 ddPCR Assays in the Perspective of Treatment with Target Inhibitors. International Journal of MolecularSciences, 2025. 26(21): p. 10397. 9.Kraus, TF, et al. Ultra-Fast Intraoperative IDH-Mutation Analysis Enables Rapid Stratification and Therapy Planning in Diffuse Gliomas. International Journal of Molecular Sciences, 2025. 26(19): p. 9639. 10.Dash, DP, et al. A New Highly Sensitive Realtime PCR Assay with Faster Turnaround Time for Detecting IDH1 and IDH2 mutations in Acute Myeloid Leukemia (AML) Patients. Blood, 2017. 130: p. 2681. 11.Ten Broek, RW, et al. Mutational analysis using Sanger and next generation sequencing in sporadic spindle cell hemangiomas: a study of 19 cases. Genes, Chromosomes and Cancer, 2017. 56(12): p. 855-860. 12.Patel, K.P., et al., Diagnostic testing for IDH1 and IDH2 variants in acute myeloid leukemia: an algorithmic approach using high-resolution melting curve analysis. The Journal of Molecular Diagnostics, 2011. 13(6): p.678-686。

Claims

1. An IDH1 / 2 gene multiplex digital PCR genotyping kit, comprising a first detection reagent composition and a second detection reagent composition, wherein the first detection reagent composition comprises primers and probes for detecting mutations R132H, R132G, R132S, and R132C; and the second detection reagent composition comprises primers and probes for detecting mutations R140Q, R172K, and R132L.

2. The detection kit of claim 1, wherein the first detection reagent composition comprises primers with nucleotide sequences as shown in SEQ ID No. 1 and 7, respectively; and / or the second detection reagent composition comprises primers with nucleotide sequences as shown in SEQ ID No. 1, 7, 8, 9, 14 and 15, respectively.

3. The detection kit of claim 1 or 2, wherein the first detection reagent composition comprises probes capable of hybridizing with the reverse complementary sequences of the sequences shown in SEQ ID No. 3-6 under digital PCR reaction conditions; and / or the second detection reagent composition comprises probes capable of hybridizing with the reverse complementary sequences of the sequences shown in SEQ ID No. 10, 11 and 13 under digital PCR reaction conditions.

4. The detection kit according to any one of claims 1-3, wherein, The first detection reagent composition comprises probes with nucleotide sequences as shown in SEQ ID No. 3-6, respectively; and / or the second detection reagent composition comprises probes with nucleotide sequences as shown in SEQ ID No. 10, 11 and 13, respectively.

5. The detection kit according to any one of claims 1-4, wherein, The first detection reagent composition further includes a probe with a nucleotide sequence as shown in SEQ ID No. 2; and / or the second detection reagent composition further includes a probe with a nucleotide sequence as shown in SEQ ID No.

12.

6. The test kit according to any one of claims 1-4, wherein, In the first detection reagent composition, the concentration of the probe with the nucleotide sequence shown in SEQ ID No. 5 is 1.2 times that of the probe with the nucleotide sequence shown in SEQ ID No.

2.

7. The test kit according to any one of claims 1-6, wherein, In the second detection reagent composition, the concentration of the probe with the nucleotide sequence shown in SEQ ID No. 10 is 1.7 times that of the probe with the nucleotide sequence shown in SEQ ID No.

12.

8. The use of the test kit according to any one of claims 1-7 in the preparation of a product for screening and / or genotyping IDH1 / 2 gene mutations in samples of subjects.

9. The application of claim 8, wherein the screening and / or genotyping is performed by digital PCR.

10. The application as described in claim 8 or 9, wherein the sample contains not less than 100 ng of wild-type DNA.

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