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WO2024002165A1 - Biomarqueur de méthylation d'adn pour le diagnostic du cancer gastrique, kit et utilisation - Google Patents

Biomarqueur de méthylation d'adn pour le diagnostic du cancer gastrique, kit et utilisation Download PDF

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WO2024002165A1
WO2024002165A1 PCT/CN2023/103213 CN2023103213W WO2024002165A1 WO 2024002165 A1 WO2024002165 A1 WO 2024002165A1 CN 2023103213 W CN2023103213 W CN 2023103213W WO 2024002165 A1 WO2024002165 A1 WO 2024002165A1
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seq
primers
probe
methylation
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李彬
阮微媚
王洪
陈嘉欣
陈志伟
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AnchorDx Medical Co Ltd
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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
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    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
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    • C12Q2600/00—Oligonucleotides characterized by their use
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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/16—Primer sets for multiplex assays

Definitions

  • the invention relates to the fields of biotechnology and medical diagnosis, and in particular to a DNA methylation biomarker for diagnosing gastric cancer, a kit and its use. More specifically, the present invention relates to a combination of DNA methylation biomarkers, which provides a simple, non-invasive and highly sensitive detection method for multiple gene methylation, which can be used to detect the methylation of examined individuals. The risk of cancer, especially gastric cancer, is assessed and graded.
  • Gastric cancer remains an important cancer worldwide.
  • the incidence of gastric cancer in my country accounts for approximately 46.3% of the global gastric cancer incidence, and the number of gastric cancer deaths in my country accounts for 47.8% of the global gastric cancer deaths, ranking first in the world in terms of incidence and death.
  • the vast majority of gastric cancers are adenocarcinomas. They have no obvious symptoms in the early stage, or may present non-specific symptoms such as epigastric discomfort and belching. They are often similar to the symptoms of chronic gastric diseases such as gastritis and gastric ulcers and are easily ignored.
  • the diagnosis and treatment rate of early gastric cancer in my country is very low, only about 20%, which is far lower than Japan (80%) and South Korea (50%).
  • CpG island methylation is an important mechanism for the inactivation of tumor suppressor genes, and gastric cancer exhibits high frequency of abnormal CpG One of the tumors with island methylation.
  • gastric cancer-specific methylation markers By looking for gastric cancer-specific methylation markers and detecting their methylation levels, we can effectively distinguish between cancer and non-cancer, and then combine them with other screening methods to improve the accuracy of screening.
  • reports on methylation analysis in gastric cancer are limited to date.
  • the patent document with application number CN201410389895.2 discloses a study on the detection of RNF180 and Septin9 genes in normal people, gastric cancer and gastritis patients.
  • the sensitivity and specificity of distinguishing the genomic DNA of gastric cancer patients from healthy people are 74% and 87% respectively.
  • the sensitivity and specificity for distinguishing genomic DNA from patients with gastritis from healthy individuals were 62% and 80%, respectively.
  • the patent document with application number CN202010377370.2 discloses the detection of SDC2 and TERT genes in stool, with a sensitivity of 81.5% and a specificity of 85.2% for distinguishing gastric cancer (high-risk) samples.
  • Another patent document with application number CN201610510535.2 discloses the detection of NDRG4 gene in gastric cancer and adjacent tissue, with a diagnostic sensitivity of 65.5% and a specificity of 77.3%.
  • the Septin9 gene was found to be a specific marker in the early development and progression of colorectal cancer (Grutzmann, R., et al., Sensitive detection of colorectal cancer in peripheral blood by septin 9 DNA methylation assay.PLoS One, 2008.3 (11):p.e3759.), the SDC2 gene is also considered to be a specific marker for stool detection of colorectal cancer (Oh, T.J., et al., Feasibility of quantifying SDC2 methylation in stool DNA for early detection of colorectal cancer. Clin Epigenetics, 2017.9:p.126.). Therefore, the ability of these two genes to differentiate between gastric and colorectal cancers remains to be evaluated. Methylation detection of a single gene may lead to serious missed detection and misdetection, and combined detection of multi-gene methylation can achieve better detection results.
  • non-invasive detection methods will develop in the direction of high-throughput, low-cost, and automation. By then, non-invasive detection methods will gradually become the mainstream gastric cancer screening method relying on higher sensitivity and specificity and easy-to-accept detection methods.
  • the present invention provides a plurality of methods that can be used to identify gastric cancer.
  • Methylation biomarkers for the occurrence, progression and staging of gastric cancer, Lauren molecular typing of gastric cancer, and tumor differentiation of gastric cancer, by detecting multiple tumor-related specific methylation regions (i.e., methylation biomarkers)
  • the combination of methylation status can determine the occurrence of gastric cancer and the corresponding stages, molecular subtypes and differentiation levels.
  • the methylation level can effectively distinguish cancer/non-cancer, and different stages, different molecular subtypes and different differentiations of gastric cancer. degree.
  • a methylation biomarker for diagnosing gastric cancer wherein the methylation biomarker includes:
  • the methylation biomarker comprises:
  • the methylation biomarker is any one selected from the following groups (i) to (vii):
  • gastric cancer is selected from the group consisting of stage I, stage II, stage III or stage IV gastric cancer; and/or,
  • the gastric cancer is gastric cancer from a subject, and the subject is a mammal; preferably, the mammal is a human; and/or,
  • the methylation level of the methylation biomarker in the sample to be tested is different from the methylation level of the methylation biomarker in the sample of a subject without gastric cancer, it indicates that the methylation biomarker is different.
  • the subject corresponding to the sample to be tested has gastric cancer.
  • the methylation biomarker can be used as a biomarker for judging the progression stage of gastric cancer; or, the methylation biomarker can be used as a biomarker for judging the Lauren molecular typing of gastric cancer; Alternatively, the methylation biomarker can be used as a biomarker for classifying and distinguishing the differentiation degree of gastric cancer tumors.
  • methylation degree of the methylation biomarker is detected by one or more of the following methods: fluorescence quantitative PCR, methylation-specific PCR, digital PCR, DNA methylation Chemical chip, targeted DNA methylation sequencing, methylation-sensitive restriction endonuclease (MS-RE)-PCR/Southern method, direct sequencing method, methylation-sensitive single nucleotide primer extension (Ms- SnuPE), bisulfite-conjugated restriction endonuclease method (COBRA), methylation-sensitive single-strand conformation analysis (MS-SSCA), methylation-sensitive denaturing gradient gel electrophoresis (MS DGGE), Methylation-specific denaturing high-performance liquid chromatography (MS-DHPLC), methylation-specific microarray (MSO), methylation-sensitive melting curve analysis (MS-MCA), methylation-sensitive spot analysis (MS- DBA), methylation-specific multiple ligation-dependent probe amplification, bis
  • the method is fluorescence quantitative PCR
  • the fluorescence quantitative PCR method is a single-plex fluorescence quantitative PCR method or a multiplex fluorescence quantitative PCR method
  • the fluorescence quantitative PCR method is a multiplex fluorescence quantitative PCR channel combined detection method.
  • kits for diagnosing gastric cancer includes a method for detecting methylation in a sample to be tested as described in the first aspect of the present invention. Reagents for biomarker methylation levels.
  • the reagent is a reagent selected from the following methods for detecting the degree of methylation or detecting the degree of methylation of multiple methylated regions of DNA: fluorescence quantitative PCR, methylation Chemical-specific PCR, digital PCR, DNA methylation chip, targeted DNA methylation sequencing, methylation-sensitive restriction endonuclease (MS-RE)-PCR/Southern method, direct sequencing method, methylation Sensitive single nucleotide primer extension (Ms-SnuPE), bisulfite combined restriction endonuclease method (COBRA), methylation-sensitive single-stranded conformation analysis (MS-SSCA), methylation sensitivity Denaturing gradient gel electrophoresis (MS DGGE), methylation-specific denaturing high-performance liquid chromatography (MS-DHPLC), methylation-specific microarray (MSO), methylation-sensitive melting curve analysis (MS-MCA), methylation-sensitive spot analysis (MS-DBA), methyl
  • the method for detecting the degree of methylation or detecting the degree of methylation of multiple methylated regions of DNA is a fluorescence quantitative PCR method
  • the fluorescence quantitative PCR method is a single-plex fluorescence quantitative PCR method or a multiplex fluorescence quantitative PCR method
  • the fluorescence quantitative PCR method is a multiplex fluorescence quantitative PCR channel combined detection method.
  • the reagents include at least one set of primers and probes selected from:
  • the sample to be tested is selected from any one of the group consisting of cells, tissue samples, body fluid samples and excreta, or any combination of the above biological samples; preferably, the body fluid sample Any one selected from the group consisting of plasma, saliva and serum or any combination thereof, and the excretion is selected from any one or any combination thereof selected from the group consisting of urine, feces and colon effluent; more preferred , the biological sample to be tested is selected from plasma.
  • At least one group selected from the following combinations of primers and probes prepared for use in diagnosing the progression of gastric cancer in a subject suffering from gastric cancer, and/or gastric cancer Lauren Use in reagents or kits for molecular typing, and/or gastric cancer tumor differentiation degree classification, wherein the combination of primers and probes is used to detect the methylation biomarkers described in the first aspect of the present invention Degree of methylation:
  • the present invention provides a number of new methylation biomarkers that can be used to diagnose gastric cancer occurrence, progression staging, Lauren molecular classification and tumor differentiation degree classification.
  • the joint detection of these biomarkers has better discriminant performance. .
  • the present invention provides a kit for detecting multiple methylated regions, in which the design of primer pairs and probes and their combination methods are crucial for simultaneous and parallel detection of the methylation degree of multiple methylated regions.
  • the kit provided by the invention uses bioinformatics software to analyze the target gene sequences SEQ ID NO.1 to SEQ ID NO.42 and the internal reference gene sequence, and uses the sequence analysis software to combine the early methylation-specific primer pairs and probes. Based on needle design experience and considering the compatibility of these primer pairs and probes in multiplex PCR, we can design corresponding amplification primers and probes as well as primer and probe combinations in multiplex detection.
  • the present invention performs combined detection on methylation sites in some specific methylation regions. Taking into account the interaction between primer pairs and probe combinations of multiple methylation biomarkers, the primer pairs and probe combinations were simulated and tested to avoid false positives caused by their mismatches, so that the detection has an extremely low noise floor. Signal.
  • the method of the present invention for detecting free DNA methylation in plasma samples through real-time fluorescence quantitative PCR can realize parallel detection of the methylation status of 2-42 specific methylation regions.
  • the threshold ⁇ Ct can conveniently determine the corresponding information of biological samples, providing a fast and effective diagnosis and grading method for non-invasive detection of tumor diseases, especially gastric cancer.
  • Figure 1 shows the ROC curve of the diagnostic performance of a single methylation region of a gastric cancer-specific methylation marker detected in clinical samples using multiplex fluorescence quantitative PCR as described in Example 6.
  • Figure 2 shows the results of verifying the combined detection products of multiple fluorescence channels using the Agilent 2100 bioanalyzer described in Example 7.
  • Figure 3 shows the ROC curve of clinical samples detected using the multiple fluorescence quantitative channel combined detection method and the multiple fluorescence quantitative single channel detection method described in Example 8.
  • the terms “complementary” and “complementarity” refer to a nucleotide (for example, 1 nucleotide) or a polynucleotide (for example, a sequence of nucleotides) related to a base pairing rule.
  • the sequence 5'-A-G-T-3' is complementary to the sequence 3'-T-C-A-5'.
  • Complementarity can be "partial,” where only some nucleic acid bases match according to base pairing rules. Alternatively, there may be “complete” or “total” complementarity between nucleic acids. The degree of complementarity between nucleic acid strands affects the efficiency and strength of hybridization between nucleic acid strands. This is particularly important in amplification reactions and detection methods that rely on binding between nucleic acids.
  • polymerase chain reaction is used to amplify a target sequence.
  • This method consists of the following steps: introducing a large excess of two oligonucleotide primers into a DNA mixture containing the desired target sequence, followed by Perform precise thermal cycling sequences in the presence of DNA polymerase. Both primers are complementary to the corresponding strands of the double-stranded target sequence. To perform amplification, the mixture is denatured and the primers anneal to their complementary sequences within the target molecule. After annealing, the primers are amplified using a polymerase to form a new pair of complementary strands.
  • the steps of denaturation, primer annealing, and polymerase extension can be repeated multiple times (i.e., denaturation, annealing, and extension constitute one "cycle”; there can be many "cycles") to obtain a high concentration of amplified fragments of the desired target sequence.
  • the length of the amplified fragment of the desired target sequence is determined by the relative position of the primers relative to each other and is therefore a controllable parameter. Due to the repetitive aspect of the method, the method is known as "polymerase chain reaction"("PCR”). Since the desired amplified fragment of the target sequence becomes the dominant sequence (in concentration) in the mixture, it is said to be “PCR amplified” and is a "PCR product" or "amplicon”.
  • nucleic acid detection assay refers to any method that determines the nucleotide composition of a target nucleic acid. Nucleic acid detection assays include but are not limited to DNA sequencing methods and probe hybridization methods.
  • amplifiable nucleic acid refers to a nucleic acid that can be amplified by any amplification method. It is contemplated that "amplifiable nucleic acid” will generally comprise a “sample template”.
  • sample template refers to the nucleic acid derived from the sample that is used to analyze for the presence of a "target".
  • background template is used to refer to nucleic acids other than the sample template, which may or may not be present in the sample. Background templates are often unintentional. This may be a result of carryover, or it may be due to the presence of nucleic acid contaminants that were attempted to be purified away from the sample. For example, nucleic acids from an organism other than the nucleic acid to be detected may be present as background in the test sample.
  • the term "primer” refers to an oligonucleotide that occurs naturally or synthetically in a purified restriction digest when exposed to conditions in which the synthesis of a primer extension product complementary to a nucleic acid strand is induced (e.g., It can serve as a starting point for synthesis in the presence of nucleotides and an inducer such as DNA polymerase and at the appropriate temperature and pH).
  • Primers are preferably single-stranded for maximum efficiency of amplification, but may be double-stranded. If double-stranded, the primer is first treated to separate its strands before being used to prepare extension products.
  • the primers are oligodeoxyribonucleotides. The primer must be long enough to initiate the synthesis of the extension product in the presence of the inducer. The exact length of the primer will depend on many factors, including temperature, source of primer, and method used.
  • probe refers to an oligonucleotide (e.g., a nucleotide sequence) that occurs naturally in a purified restriction digest or is synthesized, recombinant, or produced by PCR amplification, which is capable of interacting with Another sense target oligonucleotide hybridizes. Probes can be single-stranded or double-stranded. Probes can be used for the detection, identification and isolation of specific genetic sequences (eg, "capture probes"). In some embodiments, Any probe used in the present invention can be labeled with any "reporter molecule" such that it is detectable in any detection system.
  • the term "tumor disease grade staging” means grading by determining the degree of methylation of DNA methylation markers based on detection results.
  • three grades of normal, benign and cancer can be distinguished according to the degree of DNA methylation.
  • four grades of normal, benign diseases, benign tumors and cancer can be distinguished according to the degree of DNA methylation.
  • tumor means and includes benign tumors with good prognosis (benign tumors) and malignant tumors with the ability to invade and metastasize.
  • the benign tumors are non-epithelial tumors of the stomach.
  • the malignant tumor is gastric cancer.
  • gastric cancer As used herein, the terms "gastric cancer”, “gastric cancer” and “stomach cancer” have the same meaning and refer to epithelial malignant tumors originating in the stomach.
  • gastric cancer staging refers to dividing gastric cancer into four stages (i.e., stage I, stage II) according to the staging standards jointly formulated by the American Joint Cancer Committee (AJCC) and the International Union against Cancer (UICC). , stage III and stage IV). Tumors are staged according to the following three TNM indicators.
  • TNM Tumor Node Metastasis
  • T Tumor Node Metastasis
  • T Tumor Node Metastasis
  • M Metalastasis
  • M0 distant metastasis
  • M1 distant metastasis
  • M1 distant metastasis
  • Stage I refers to superficial gastric cancer without lymph node metastasis, or the tumor has invaded the muscle layer but has not yet metastasized to local lymph nodes;
  • Stage II refers to the tumor that has infiltrated into the mucosa or submucosa, but has spread far away from the primary tumor.
  • Stage III refers to The tumor infiltrates into the muscle layer or subserosa and has metastasis to lymph nodes beyond 3cm from the primary tumor; the tumor has penetrated the extraserosa, but only has lymph node metastasis within 3cm; or the tumor has even invaded adjacent tissues and organs, but there are no lymph nodes.
  • stage IV refers to the tumor that has involved adjacent tissues and organs, and has lymph node metastasis beyond 3cm from the primary tumor; or T and N that have distant metastasis.
  • gastritis is inflammation of the gastric mucosa caused by various causes. According to the urgency of clinical onset, it can generally be divided into acute and chronic gastritis. Chronic gastritis refers to chronic inflammation or atrophic lesions of the gastric mucosa caused by different causes. Chronic gastritis is divided into: non-atrophic (superficial), atrophic and special types of gastritis based on clinical, endoscopic and histopathological results. . Non-atrophic gastritis is further divided into superficial gastritis and erosive gastritis endoscopically.
  • Atrophic gastritis is a glandular atrophy of the gastric mucosal epithelium, with thinning and aging of the gastric mucosa. It is caused by long-term chronic inflammation of the gastric mucosa. It can be divided into: atrophy with intestinal metaplasia and without intestinal metaplasia. Intestinal metaplasia is the repeated inflammation, necrosis and repair of gastric mucosal epithelial cells. During this process, under the stimulation of certain factors, the gastric mucosal epithelial cells change and become similar to the epithelial cells of the small intestine or large intestine. Atrophic gastritis is a precancerous disease that may develop into gastric cancer. Incomplete colorectal metaplasia is a precancerous lesion that easily develops into gastric cancer.
  • the term "marker” refers to a measurable molecule such as a gene, protein, metabolite, etc. Measurement of disease-related variables that can be used to diagnose a disease or indicate the severity of a disease. The presence or risk of a disease can be inferred from the biomarker parameter without measuring the disease itself.
  • the term "real-time fluorescence quantitative PCR” means in a DNA amplification reaction, with A method of measuring the total amount of product after each polymerase chain reaction (PCR) cycle using fluorescent chemicals. A method of quantitatively analyzing specific DNA sequences in the sample to be tested using internal or external reference methods.
  • the cycle threshold (Cycle threshold, Ct value) means: the number of cycles experienced when the fluorescence signal in each reaction tube reaches the set threshold.
  • the setting method of fluorescence threshold is as follows: the fluorescence signal of the first 15 cycles of the PCR reaction is used as the fluorescence background signal.
  • the default (default) setting of the fluorescence threshold is the standard deviation of the fluorescence signal of 3 to 15 cycles. 10 times.
  • the amplification efficiency range is required to be 90%-110% (3.6>k>3.1).
  • the term "cut off value” refers to a critical Ct value for judging whether a sample is negative or positive for a certain biomarker. According to certain embodiments of the present invention, the "cut off value” (i.e., positive judgment value) is obtained based on a certain number of sample data and statistical processing.
  • the critical Ct value can be based on the required sensitivity or specificity. requirements vary.
  • sensitivity refers to the proportion of positive samples detected from confirmed positive samples.
  • the true positive is the recognized gold standard. Confirmed positive.
  • the term "subject” may be a mammal or a cell, tissue, organ or part of the mammal.
  • mammal refers to any kind of mammal, preferably human (including humans, human subjects or human patients).
  • Subjects and mammals include, but are not limited to, farm animals, sporting animals, pets, primates, horses, dogs, cats, and rodents such as mice and rats.
  • diagnosis includes the detection or identification of a disease state or condition in a subject, the determination of the likelihood that a subject will develop a given disease or condition, or the determination of the likelihood that a subject suffering from a disease or condition will respond to treatment. to determine the prognosis of a subject suffering from a disease or condition (or its likely progression or decline) withdrawal) and to determine the effect of treatment in subjects suffering from the disease or condition.
  • methylation refers to the methylation of cytosine (Cytosine, referred to as C) at the C5 or N4 position of cytosine, the N6 position of adenine (Adenine, referred to as A) or other types of methylation.
  • Nucleic acid methylation In vitro amplified DNA is usually unmethylated because generally in vitro DNA amplification methods do not preserve the methylation pattern of the amplified template.
  • unmethylated DNA or “methylated DNA” can also refer to amplified DNA that is unmethylated or methylated from the original template, respectively.
  • methylated nucleotide or “methylated nucleotide base” refers to the presence of a methyl moiety on a nucleotide base, where the methyl moiety is not present in the recognized in typical nucleotide bases.
  • cytosine does not contain a methyl moiety on its pyrimidine ring, but 5-methylcytosine contains a methyl moiety at position 5 of its pyrimidine ring. Therefore, cytosine is not a methylated nucleotide and 5-methylcytosine is.
  • Thymine (T) contains a methyl moiety at position 5 of its pyrimidine ring; however, for the purposes of this article, thymine is not considered a methylated nucleoside when present in DNA acid because thymine is the typical nucleotide base of DNA.
  • methylation status may optionally be represented or indicated by the term "methylation value" (eg, indicating methylation frequency, fraction, ratio, percentage, etc.).
  • Methylation values can be quantified, e.g., after restriction digestion with methylation-dependent restriction enzymes, or by comparing amplification profiles after bisulfite reaction, or by comparing bisulfite treatment and Unprocessed nucleic acid sequences are generated. Therefore, values such as methylation values represent methylation status and can therefore be used as quantitative indicators of methylation status in multiple copies of a locus.
  • the degree of co-methylation is expressed or indicated by the methylation status of more than one methylation site. Within a methylation region, when the methylation status of more than one methylation site is methylated is defined as comethylation.
  • methylation frequency or “methylation percent (%)” refers to the number of instances of a molecule or locus that is methylated relative to the number of instances of the molecule or locus that is unmethylated.
  • bisulfite reagent refers to a bisulfite reagent that in some embodiments contains Reagents of bisulfite, disulfite, hydrogen sulfite or combinations thereof, DNA treated with bisulfite reagents, unmethylated cytosine nucleosides
  • the acid will be converted to uracil, while the methylated cytosine and other bases remain unchanged, so methylated and unmethylated cytidines can be distinguished in, for example, CpG dinucleotide sequences.
  • methylation assay refers to any assay used to determine the methylation status of one or more CpG dinucleotide sequences within a nucleic acid sequence.
  • the detection means includes the use of methylation-specific polymerase chain reaction, nucleic acid sequencing, mass spectrometry, methylation-specific nucleases, mass-based separation, or target capture.
  • the detection of the above-mentioned methylated region of the present invention includes the following main steps: (1) using a DNA extraction kit to extract genomic DNA and/or free DNA from the biological sample to be tested; (2) performing sulfite treatment on the DNA Hydrogen salt conversion; (3) Perform methylation detection on multiple methylated regions on the DNA that has been converted by bisulfite.
  • DNA eg, genomic DNA, such as extracted genomic DNA or processed genomic DNA
  • genomic DNA is isolated by any standard means in the art, including using commercially available kits.
  • the biological sample to be detected is any one of the group consisting of cells, tissue samples, body fluid samples, and excreta, or any combination of the above biological samples; in some cases, the body fluid sample is selected from Any one or any combination thereof from the group consisting of plasma, saliva and serum, and said excretion is any one or any combination thereof from the group consisting of urine, feces and colonic effluent; in other cases , the biological sample to be tested is selected from plasma.
  • AUC is an abbreviation for "area under the curve.” Specifically, it refers to the area under the receiver operating characteristic (ROC) curve.
  • ROC receiver operating characteristic
  • a ROC curve is a plot of the true positive rate versus the false positive rate for different possible block cut points of a diagnostic test. It illustrates the trade-off between sensitivity and specificity depending on the chosen cleavage point (any increase in sensitivity will be accompanied by a decrease in specificity).
  • the area under the ROC curve (AUC) is a measure of the accuracy of a diagnostic test (the larger the area, the better; optimal is 1; a random test will have an ROC curve on the diagonal with an area of 0.5; see: JPEgan. (1975) Signal Detection Theory and ROC Analysis, Academic Press, NewYork).
  • Methods for detecting DNA methylation include: methylation-specific PCR (MSP), DNA methylation chip, targeted DNA methylation sequencing, digital PCR and fluorescence quantitative PCR, methylation-sensitive restriction endonuclease Enzyme (MS-RE)-PCR/Southern method, direct sequencing method, methylation-sensitive single nucleotide primer extension (Ms-SnuPE), bisulfite combined restriction endonuclease method (COBRA), formazan Methylation-sensitive single-strand conformation analysis (MS-SSCA), methylation-sensitive denaturing gradient gel electrophoresis (MS DGGE), methylation-specific denaturing high-performance liquid chromatography (MS-DHPLC), methylation-specific Microarray (MSO), methylation-sensitive melting curve analysis (MS-MCA), methylation-sensitive spot analysis (MS-DBA), methylation-specific
  • MSP methylation-specific PCR
  • MS-RE methylation-sensitive restriction endonucleas
  • the present invention uses fluorescence quantitative PCR method
  • This embodiment discloses a DNA methylation marker region used for detection, diagnosis, classification or prediction of individual biological samples, treatment monitoring and tumor disease detection, which is selected from the methylation regions listed in Table 1 by [CG] Target sequence indicating at least one methylated region.
  • This embodiment discloses a DNA methylation marker combination for tumor disease detection, including at least 15 long oligonucleotide fragments that are equivalent to or complementary to the nucleic acid sequences of SEQ ID NO. 43 to SEQ ID NO. 121 and Its complementary sequence, the nucleic acid sequence is selected from the group consisting of at least one target sequence that is equivalent to or complementary to SEQ ID NO.1 to SEQ ID NO.42, and the oligonucleotide contains at least one methylation indicated by [CG] site.
  • SEQ ID NO. 3 described in Table 1 provides the methylation of multiple methylation site regions of the RPRM gene.
  • the SEQ ID NO.3 sequence is as follows (corresponding to chromosome position chr2:154335199-154335536):
  • RPRM reprimo
  • RPRM is a tumor suppressor gene that is activated by p53 and then participates in regulating the cell cycle. It participates in regulating cell growth and tumor cell migration by triggering cell cycle arrest, inhibiting cell proliferation, promoting cell apoptosis and other multiple mechanisms. In regulating cell It plays an important role in signaling pathways including proliferation, migration, cell survival, etc. and the dynamic balance of tissues. Studies have shown that RPRM can inhibit the expression of CDC2 and thereby inhibit the nuclear transport of cyclin B1, triggering cell cycle G2/M phase arrest.
  • the nucleic acid sequence used to detect the presence of methylation in at least one methylation site region in the RPRM gene and its fragments includes at least 15 oligos selected from the continuous sequence equivalent to SEQ ID NO. Long stretches of nucleotides. For example, the nucleotide sequence represented by SEQ ID NO.48 shown as double underline in SEQ ID NO.3, and the nucleotide sequence represented by SEQ ID NO.49 shown as underlined in SEQ ID NO.3.
  • nucleic acid sequence used to detect whether there is methylation in at least one methylation site region in the RPRM gene and its fragments includes the following nucleic acid sequences selected from those complementary to SEQ ID NO.3 (its specific sequence is such as SEQ ID NO. .369) of the continuous sequence of at least 15 oligonucleotide long fragments, for example, the nucleotide sequence represented by SEQ ID NO.50 indicated by double underlines in SEQ ID NO.369.
  • primers and probes can be designed based on sequences that are equivalent to or complementary to SEQ ID No. 3 and used to detect the presence of methylation in at least one methylation site region in the RPRM gene and its fragments.
  • Sequences suitable as primers and probes for PCR amplification may include any suitable length, for example, may include at least 13 nucleotides, or may include at least 20, 25, 30 or more than 30 nucleotides. glycosides.
  • the nucleic acid sequence used to detect whether there is methylation in at least one methylation site region in the RPRM gene and its fragments includes a sequence that is equal to or complementary to a sequence selected from SEQ ID NO.48 to SEQ ID NO.50 At least 15 oligonucleotide-long fragments of the sequence.
  • primers and probes can be designed based on a continuous nucleic acid sequence that is identical to or complementary to SEQ ID NO. 48 to SEQ ID NO. 50.
  • Sequences suitable as primers and probes for PCR amplification may include any suitable length, for example, may include at least 13 nucleotides, including at least one methylation region indicated by [CG].
  • This embodiment discloses a methylation test kit for gastric cancer detection, diagnosis, classification or prediction, treatment monitoring, prognosis or other evaluation of multiple methylated regions of gastric cancer, including multiple methylated region methylation kits
  • Specific primer pairs and probes, the specific primer and probe sequences are shown in Table 3:
  • SEQ ID NO.127, SEQ ID NO.208 and SEQ ID NO.288 are respectively designed based on the DNA methylation region shown in SEQ ID NO.48 contained in the target sequence SEQ ID NO.3
  • the forward primer, reverse primer and probe; SEQ ID NO.128, SEQ ID NO.209 and SEQ ID NO.289 are respectively based on the target sequence SEQ ID NO.3 such as SEQ ID NO.49.
  • multiple sets of primers and probe combinations can be designed for the same methylation site region, and each set of primers and probes may have differences in performance.
  • appropriate primers and probes will be selected based on the combination of specific methylated regions.
  • the detection combination of methylated regions also includes corresponding internal reference primers and probes as well as internal reference sequences, such as internal reference 1 to internal reference 2 as shown below:
  • Internal reference sequence 1 (SEQ ID NO. 364): AAAACCTACTCCTCCCTTAAAAATTACAAAAACCACAACCTAATAAAAAAAATAACCACCACCCAACACACAATAACAAACACAAATTCACAATCCAAAAAACTTACTAAACCTCCTCCATCAC; the primers and probes corresponding to the internal reference sequence 1 are:
  • the primers and probes corresponding to the internal reference sequence 2 are:
  • the kit provided in this example needs to include a PCR amplification primer and a probe set (the probe can be modified with fluorescent groups such as FAM, VIC, NED or CY5).
  • the primers and probes described in this example were purchased from Sangon Bioengineering (Shanghai) Co., Ltd., and the multiplex fluorescence quantitative PCR reagents were purchased from Takara Company.
  • Fluorescent quantitative PCR reaction program 95°C for 5 minutes; 95°C for 15 seconds, 60°C for 40 seconds, 15 cycles; 95°C for 15 seconds, 62°C for 40 seconds (fluorescence collection), 45 cycles.
  • the optimal linear range of the single-plex detection results of most of the primer probes is within 1%-100% methylation rate, or the amplification efficiency is between 80%-120%, or linear The correlation coefficient is greater than 0.98.
  • the "optimal linear range” mentioned in Table 5 of this example means that the fully methylated standard with the corresponding percentage mass content shows good linearity within this range when the completely unmethylated standard is used as the background. relation.
  • the "linear correlation coefficient” is used to reflect the relationship between methylation percentage and Ct value. The closer it is to 1, the stronger the correlation between methylation percentage and Ct value.
  • “Amplification efficiency” is a stable and reliable method for evaluating PCR amplification efficiency. A series of diluted samples are used, and a standard qPCR program is used to amplify to obtain the Ct value.
  • Example 3 Using the primer pairs and probes of the methylated region and the internal reference gene provided in Example 3, combine the primers and probes of every 3 to 4 target genes, perform multiplex fluorescence quantitative PCR, and amplify the targets in the target region. sequence, and the detection results are evaluated by the amplification threshold Ct.
  • the specific operations are as follows:
  • Example 3 Use the probe of the methylated region described in Example 3 to select appropriate fluorescent group modifications according to the combination of specific methylated regions.
  • the primers and probes of each methylated region participate in at least one combination. Multiplex fluorescence quantitative PCR detection.
  • primers and probes SEQ ID NO.128, SEQ ID NO.209 and SEQ ID NO.289 used to detect the presence of methylation in the methylation site region SEQ ID NO.49 of the RPRM gene are included as follows Detection in combination A and B:
  • the ⁇ Ct value obtained by multiplex fluorescence quantitative PCR using any combination of primers and probes for 3 to 4 target gene methylation regions is similar to the ⁇ Ct value of single-plex fluorescence quantitative PCR, and there is no significant difference. . Judging from this, the combination scheme of multiple fluorescence quantification does not cause mutual interference in the amplification efficiency of the methylated region.
  • the quantitative performance is equivalent to the quantification of a single region, and can achieve the simultaneous quantification of 3 to 4 methylated regions. detection.
  • the plasma cell-free DNA extraction kit was purchased from LIFE Company, and the extraction method was performed according to the kit instructions.
  • the DNA bisulfite conversion kit was purchased from ZYMO RESEARCH Company and was operated according to the instructions of the kit.
  • Example 5 The multiplex fluorescence quantitative PCR detection combination in Example 5 was used to conduct parallel detection of co-methylation of multiple methylated regions and internal reference genes on each clinical sample.
  • the sample amount before conversion of sample DNA was 10ng.
  • Amplification method and reaction The procedure is the same as in Example 5.
  • the above data show that the methylated region has good discriminating ability for distinguishing gastric cancer and non-gastric cancer groups in plasma samples.
  • the present invention performs combined detection on methylation sites in some specific methylation regions. Considering the interaction between multiple methylation biomarker primer and probe pair combinations, primer pairs and probe combinations were simulated and tested to avoid false positives caused by their mismatches. By optimizing the detection system and amplification procedures, The detection has extremely low noise floor while maintaining good amplification efficiency and linear correlation.
  • the multiple fluorescence channel merging and detection combination methods (combinations 1-9) used in this embodiment are as follows:
  • the primer-probe mixture equipped with 1-3 methylated region merging channels can amplify the target sequence of the target region, and the product size is about 70-130 bp.
  • a pre-stage landing PCR method is used to ensure the specificity of amplification. Specifically: 95°C for 5 minutes; 95°C for 15 seconds, cooling down by 0.3°C per cycle starting from 64.5°C, 40 seconds, 15 cycles; 95°C for 15 seconds, 62°C for 40 seconds (fluorescence collection), 45 cycles.
  • test results are compared with the single-channel detection of multiplex fluorescence quantitative PCR methylation region. Its technical performance is As shown in Table 11 below:
  • the “linear range” mentioned in Table 11 of this example means that when the completely unmethylated standard is used as the background, the corresponding percentage mass content of the fully methylated standard shows a good linear relationship within this range.
  • the "Linear Correlation Coefficient” described in Table 11 is used to measure the relationship between percent methylation and Ct values. The closer it is to 1, the stronger the correlation between methylation percentage and Ct value.
  • the "CV” mentioned in Table 11 is the coefficient of variation, which is used to reflect the degree of dispersion of several sets of detection data. The smaller the CV, the smaller the data fluctuation and the better the repeatability.
  • the "amplification efficiency” described in Table 11 is a stable and reliable method for evaluating PCR amplification efficiency.
  • the inventor used an Agilent 2100 bioanalyzer to verify the combined detection products of multiple fluorescence channels.
  • the results are shown in Figure 2.
  • the theoretical size of the amplification product is 78 to 108 bp, and the size of the internal reference is about 125 bp.
  • the analysis results of the Agilent 2100 Bioanalyzer are consistent with the theoretical results, and the non-methylated standard has no other products except the internal reference. This combination proved to be highly specific.
  • Example 8 Parallel detection of multiple methylated regions in clinical samples using multiple fluorescence channel combined detection methods
  • Example 7 The channel merging combination described in Example 7 was used to conduct parallel detection of multiple methylation regions on clinical plasma samples from 59 cases of gastric cancer (case group) and 110 cases of non-gastric cancer (control group).
  • the clinical information statistics of the test samples are shown in Table 12 below:
  • the plasma cell-free DNA extraction kit was purchased from LIFE Company, and the extraction method was performed according to the kit instructions.
  • Example 7 Using the channel merging combination described in Example 7, multiple methylated regions and internal reference genes were detected in parallel for each clinical sample.
  • the loading amount of sample DNA before conversion is 10ng.
  • the amplification method and reaction procedure are the same as in Example 7.
  • the above data shows that compared with single-channel multiplex detection using multiple fluorescence quantitative PCR channel combined detection, the methylated region used has better discriminative ability for distinguishing gastric cancer and non-gastric cancer groups in plasma samples.
  • the diagnostic performance is similar without significant difference.
  • the combined detection of multiple channels can achieve parallel detection of multi-methylated regions with lower sample input without sacrificing diagnostic performance.
  • Example 9 Using multiple methylation regions to identify gastric cancer
  • the unit performs corresponding prediction model construction and analysis.
  • Feature selection methods such as LASSO, random forest, recursive feature elimination algorithm, and marker correlation were respectively used to optimize the model features of the multiple methylation regions, and the selected methylation region was used based on a single methylation region threshold.
  • the iterative combination logistic regression modeling method was used to construct a model for predicting the occurrence of gastric cancer, and multiple methylation region prediction models (combination of multiple methylation regions) were obtained. Its model prediction performance (including AUC, sensitivity under Youden cut-off and specificity, Youden index) compared with the single methylation region judgment model described in Example 6, its prediction performance is listed in Table 14 below:
  • Table 14 Discriminative performance of methylated region combinations for discriminating gastric cancer occurrence
  • Table 14 show that compared with the prediction performance of a single methylated region for gastric cancer, the prediction model obtained by the combination of multiple methylated regions has superior diagnostic performance. At the same time, in these models, the risk score of the gastric cancer population was significantly higher than that of the non-gastric cancer population, indicating that the combination of these methylated regions can be used as a biomarker for general screening of gastric cancer based on plasma DNA.
  • Example 10 Discriminative performance of multiple methylated regions in determining the progression (stage) of gastric cancer
  • the methylation detection data of multiple methylated regions of the 58 gastric cancer clinical plasma samples were analyzed using the detection method described in Example 6.
  • Early gastric cancer (stage I) was used as the control group, and advanced and late gastric cancer (stage II-IV) were used as the case group for analysis.
  • the input unit evaluates the methylation regions that can be used to discriminate the degree of progression, and simultaneously constructs and analyzes the corresponding degree of progression (stage) discrimination model for multiple methylation region combinations.
  • Feature selection methods such as LASSO, random forest, recursive feature elimination algorithm and marker mutual correlation were used to optimize the model features of the multiple methylated regions, and the selected methylated regions were Domain uses an iterative combination logistic regression modeling method based on a single methylation region threshold to construct a gastric cancer progression (stage) discrimination model, and obtains multiple methylation region discrimination models (multiple methylation region combinations), whose model discrimination
  • the performance including AUC, sensitivity and specificity under Youden cut-off, and Youden index
  • the judgment performance is listed in Table 15 below:
  • Table 15 Discriminative performance of methylated region combinations for discriminating the progression of gastric cancer
  • Table 15 show that the scores of the single methylation region are significantly different in early gastric cancer and advanced and late gastric cancer, which can be used as a reminder of the progression and prognosis of gastric cancer.
  • the discriminant model obtained by the combination of multiple methylated regions has superior diagnostic performance, indicating that the combination of these methylated regions can be used as a biological model for discriminating the progression of gastric cancer based on plasma DNA. Mark.
  • Example 11 Discriminative performance of multiple methylated regions for Lauren classification of gastric cancer
  • the methylation detection data of multiple methylated regions of the 58 gastric cancer clinical plasma samples were analyzed using the detection method described in Example 6.
  • Early gastric cancer (stage I) was used as the control group, and advanced and late gastric cancer (stage II-IV) were used as the case group for analysis.
  • the unit evaluates the methylation regions that can be used to determine the degree of progression, and simultaneously constructs and analyzes the corresponding progression degree (stage) discrimination model for multiple methylation region combinations.
  • Feature selection methods such as LASSO, random forest, recursive feature elimination algorithm, and marker correlation were respectively used to optimize the model features of the multiple methylation regions, and the selected methylation region was used based on a single methylation region threshold.
  • the iterative combination logistic regression multi-classification modeling method was used to construct a gastric cancer progression (stage) discrimination model, and multiple methylation region discrimination models (combination of multiple methylation regions) were obtained.
  • the model discrimination performance single type discrimination
  • Sensitivity, overall accuracy and overall AUC compared with the listed single methylation region judgment models that can be used to judge the degree of progression, its judgment performance is listed in Table 16 below:
  • Table 16 Discriminative performance of methylated region combinations for discriminating molecular classification of gastric cancer
  • the results in Table 16 show that the single methylation region has a certain sensitivity in distinguishing three types of gastric cancer tumors, and can be used as a hint for different molecular classifications of gastric cancer.
  • the discriminant model obtained by the combination of multiple methylated regions has superior diagnostic performance, indicating that the combination of these methylated regions can be used as a molecular classification of gastric cancer based on plasma DNA Lauren Discriminative biomarkers.
  • Example 12 Discriminative performance of multiple methylated regions on the differentiation degree of gastric cancer
  • Feature selection methods such as LASSO, random forest, recursive feature elimination algorithm, and marker correlation were respectively used to optimize the model features of the multiple methylation regions, and the selected methylation region was used based on a single methylation region threshold.
  • the iterative combination logistic regression multi-classification modeling method was used to construct a three-class gastric cancer differentiation discrimination model, and multiple methylation region discrimination models (combination of multiple methylation regions) were obtained.
  • the model discrimination performance sensitivity of single type discrimination
  • overall accuracy and overall AUC compared with the listed single methylation region judgment models that can be used to judge the differentiation degree of gastric cancer tumors, its judgment performance is listed in Table 17 below:
  • Table 17 Discriminative performance of methylated region combinations for discriminating the differentiation degree of gastric cancer
  • the results in Table 17 show that the single methylation region has a certain sensitivity in judging gastric cancer tumors with different degrees of differentiation, and can be used as a hint for classifying gastric cancer tumors with different degrees of differentiation.
  • the discriminant model obtained by the combination of multiple methylated regions has superior diagnostic performance, indicating that the combination of these methylated regions can be used to classify and discriminate the degree of differentiation of gastric cancer tumors based on plasma DNA. of biomarkers.
  • Example 13 The combined detection method of multiple fluorescent quantitative PCR channels of multiple methylated regions is useful in determining the occurrence of gastric cancer, the degree of progression (stage) of gastric cancer, Lauren molecular typing and the degree of differentiation of gastric cancer. Other applications
  • Example 8 The detection method described in Example 8 was used to analyze the methylation detection data of multiple methylation regions in the 59 gastric cancer and 110 non-gastric cancer clinical plasma samples.
  • gastric cancer samples were used as the case group, and non-gastric cancer samples were used as the control group.
  • stage I early gastric cancer
  • stage II-IV advanced and late gastric cancer
  • stage II-IV advanced and late gastric cancer
  • ⁇ Ct (methylated region 1) Ct (methylated region 1) - Ct (internal reference) ) is used as data input unit, evaluate the methylated regions that can be used for the application, and simultaneously perform corresponding discriminant model construction and analysis on multiple methylated region combinations.
  • Feature selection methods such as LASSO, random forest, recursive feature elimination algorithm, and marker correlation were respectively used to optimize the model features of the multiple methylation regions, and the selected methylation region was used based on a single methylation region threshold.
  • the iterative combination logistic regression modeling method was used to construct the corresponding discriminant model and obtain multiple methylation region discriminant models (combination of multiple methylation regions). Its model discriminant performance (including AUC, Youden cut-off Sensitivity and specificity, Youden index) compared with the listed single methylation region judgment models that can be used for the application, its judgment performance is listed in the following tables 18 to 20:
  • Table 18 Predictive performance of marker combinations as discriminant models for gastric cancer occurrence
  • Table 19 Predictive performance of marker combinations as a discriminant model for progression (stage) of gastric cancer
  • Table 20 Discriminant model marker combination as the Lauren molecular classification of gastric cancer
  • Tables 18 to 20 show that the score of the single methylation region is significantly different in the application comparison group of the diagnostic judgment, which can be used as a reminder for the occurrence, progression and molecular classification of gastric cancer.
  • the discriminant model obtained by the combination of multiple methylated regions has superior diagnostic performance, indicating that the combination of these methylated regions can be used to discriminate the occurrence and progression of gastric cancer based on plasma DNA. and biomarkers for molecular classification.

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Abstract

L'invention concerne un biomarqueur de méthylation d'ADN pour le diagnostic d'un cancer gastrique, un kit et une utilisation. La présente invention concerne un biomarqueur de méthylation pour le diagnostic d'un cancer gastrique, le biomarqueur de méthylation comprenant un fragment équivalent et/ou complémentaire d'au moins une des séquences cibles représentées dans les SEQ ID NO : 1 à 42 et présentant une longueur d'au moins 15 oligonucléotides, et le fragment des oligonucléotides comprenant au moins un site de méthylation indiqué par CG. La combinaison fournie de détection conjointe de la méthylation de plusieurs gènes présente de meilleures performances en matière de discrimination. L'invention concerne en outre un kit pour détecter une pluralité de régions de méthylation. La conception des paires d'amorces et des sondes, ainsi que le procédé de combinaison correspondant, sont essentiels pour détecter simultanément le degré de méthylation de la pluralité de régions de méthylation en parallèle. La présente invention concerne également un moyen de diagnostic et de classement rapide et efficace pour la détection non invasive des maladies tumorales, en particulier du cancer gastrique.
PCT/CN2023/103213 2022-06-29 2023-06-28 Biomarqueur de méthylation d'adn pour le diagnostic du cancer gastrique, kit et utilisation Ceased WO2024002165A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118064579A (zh) * 2024-01-23 2024-05-24 瑞博奥(广州)生物科技股份有限公司 一种检测RNF180和Septin9基因甲基化的试剂盒

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104046685A (zh) * 2013-03-12 2014-09-17 香港中文大学 用于胃癌的诊断和预后的表观遗传生物标志物adamts9
US20180334720A1 (en) * 2017-05-19 2018-11-22 The Chinese University Of Hong Kong Tumor suppressor rec8 as a biomarker for gastric cancer
CN108977544A (zh) * 2018-08-06 2018-12-11 北京艾克伦医疗科技有限公司 用于鉴定胃癌和/或胃息肉的试剂盒及其应用
CN111235238A (zh) * 2018-09-14 2020-06-05 深圳市晋百慧生物有限公司 Dna甲基化检测方法及相关应用
US20210222260A1 (en) * 2018-07-26 2021-07-22 Exellon Medical Technology Co., Ltd Method and kit for identifying gastric cancer status
CN114277135A (zh) * 2021-10-25 2022-04-05 广州市基准医疗有限责任公司 胃癌淋巴结转移相关的甲基化生物标记物及其组合和检测试剂盒

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110151443A1 (en) * 2009-12-23 2011-06-23 The Chinese University of Hong Kong Room 328, Pi Ch'iu Building Marker for gastric cancer
AU2016315924B2 (en) * 2015-08-31 2022-08-25 Exact Sciences Corporation Detecting gastric neoplasm
US20200277677A1 (en) * 2017-10-06 2020-09-03 Youhealth Oncotech, Limited Methylation markers for diagnosing cancer
CN112662765A (zh) * 2020-03-17 2021-04-16 博尔诚（北京）科技有限公司 一种检测6种中国高发癌症的探针组合物

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104046685A (zh) * 2013-03-12 2014-09-17 香港中文大学 用于胃癌的诊断和预后的表观遗传生物标志物adamts9
US20180334720A1 (en) * 2017-05-19 2018-11-22 The Chinese University Of Hong Kong Tumor suppressor rec8 as a biomarker for gastric cancer
US20210222260A1 (en) * 2018-07-26 2021-07-22 Exellon Medical Technology Co., Ltd Method and kit for identifying gastric cancer status
CN108977544A (zh) * 2018-08-06 2018-12-11 北京艾克伦医疗科技有限公司 用于鉴定胃癌和/或胃息肉的试剂盒及其应用
CN111235238A (zh) * 2018-09-14 2020-06-05 深圳市晋百慧生物有限公司 Dna甲基化检测方法及相关应用
CN114277135A (zh) * 2021-10-25 2022-04-05 广州市基准医疗有限责任公司 胃癌淋巴结转移相关的甲基化生物标记物及其组合和检测试剂盒

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118064579A (zh) * 2024-01-23 2024-05-24 瑞博奥(广州)生物科技股份有限公司 一种检测RNF180和Septin9基因甲基化的试剂盒

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Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 28/05/2025)