Application of gngt1 in aub-m diagnosis

Abstract

The application discloses application of GNGT1 in AUB-M diagnosis. The application finds that GNGT1 presents significant difference in two groups through detection of normal endometrial tissue samples and AUB-M tissue samples, and has high sensitivity and specificity in application to the differentiation of the two groups, the AUC value in the training set is 0.875, and the AUC value in the verification set is 0.803. Therefore, GNGT1 provided by the application has the potential to become an important index for AUB-M diagnosis, and is helpful for auxiliary diagnosis, molecular typing and targeted treatment of AUB-M.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine and relates to the application of GNGT1 in the diagnosis of AUB-M. Background Technology

[0002] Abnormal uterine bleeding (AUB) is a common gynecological condition, referring to abnormal bleeding originating from the uterine cavity that deviates from any of the normal menstrual cycle frequency, regularity, duration, or amount of bleeding. It excludes pregnancy-related and postpartum bleeding and can manifest as acute or chronic abnormal uterine bleeding. It is a common condition affecting women's normal physiological and psychological well-being and a frequent reason for women of all ages to seek medical attention. International reports indicate an incidence rate of 11%–13%, and it is also a common cause of iron-deficiency anemia. The incidence rate increases with age, reaching 24% in women aged 36–40. Domestic reports indicate it accounts for 20%–40% of all gynecological outpatient visits.

[0003] Abnormal uterine bleeding (AUB) presents in diverse ways and has complex causes. Patients may have one or more causes of AUB or related conditions. In 2011, the International Federation of Gynecology and Obstetrics (FIGO) classified common causes of AUB into two main categories and nine types, abbreviated as PALM-COEIN. Among them, AUB caused by malignancy and hyperplasia of the endometrium (AUB-M) has an insidious onset and is the most easily misdiagnosed and missed type of AUB in clinical practice, with the most serious consequences. The key factor of AUB-M is the proliferative characteristics of the endometrium, and abnormal endometrial hyperplasia may be a precancerous stage of endometrial cancer. Clinically, some patients who do not receive timely treatment have already progressed to endometrial cancer. The diagnosis or exclusion of AUB-M often requires invasive examinations such as curettage and hysteroscopy to obtain endometrial specimens for pathological examination. For most patients who repeatedly experience abnormal uterine bleeding without endometrial lesions, repeated invasive examinations may be necessary, causing harm to the patient's physical and mental health and increasing the medical burden. Therefore, in addition to existing routine pathological examinations, there is an urgent need for one or more molecular markers to indicate the tendency of endometrial malignancy in order to assess the risk of patients having existing or potential endometrial malignancy.

[0004] Currently, the diagnosis of AUB-M relies on pathological examination, which results in poor timeliness and a lack of reliable molecular markers to aid in diagnosis. Therefore, developing a molecular marker for the diagnosis and treatment of AUB-M, and its application in auxiliary diagnosis, molecular subtyping, and targeted therapy, is of great significance. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, the present invention aims to provide a biomarker GNGT1 that can distinguish between normal endometrium and AUB-M. Using the biomarker GNGT1, it is possible to assess whether a subject has AUB-M or is at risk of developing AUB-M.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A first aspect of the present invention provides the use of a reagent for detecting GNGT1 in a sample in the preparation of a product for diagnosing AUB.

[0008] Furthermore, the AUB is selected from the COEIN class and the PALM class; the COEIN class includes AUB-C, AUB-O, AUB-E, AUB-I, and AUB-N; the PALM class includes AUB-P, AUB-A, AUB-L, and AUB-M.

[0009] Furthermore, the AUB is selected from the PALM class.

[0010] Furthermore, the AUB is AUB-M.

[0011] Furthermore, the reagents for detecting GNGT1 in the sample include reagents for detecting the mRNA expression level of GNGT1 in the sample and reagents for detecting the protein expression level of GNGT1 in the sample.

[0012] Furthermore, the reagent is selected from: primers that specifically amplify GNGT1, probes that specifically recognize GNGT1, or binding agents that specifically bind to proteins encoded by GNGT1.

[0013] Furthermore, the sequences of the primers for amplifying GNGT1 are shown in SEQ ID NO.1-2.

[0014] A second aspect of the invention provides a product for diagnosing AUB, the product comprising a reagent for detecting GNGT1.

[0015] Furthermore, the AUB is selected from the COEIN class and the PALM class; the COEIN class includes AUB-C, AUB-O, AUB-E, AUB-I, and AUB-N; the PALM class includes AUB-P, AUB-A, AUB-L, and AUB-M.

[0016] Furthermore, the AUB is selected from the PALM class.

[0017] Furthermore, the AUB is AUB-M.

[0018] Furthermore, the reagent is selected from: oligonucleotide probes that specifically recognize GNGT1, primers that specifically amplify GNGT1, or binding agents that specifically bind to the protein encoded by GNGT1.

[0019] Furthermore, the sequences of the primers for amplifying GNGT1 are shown in SEQ ID NO.1-2.

[0020] Furthermore, the product includes formulations, kits, chips, or nucleic acid membrane strips capable of detecting GNGT1 expression levels.

[0021] Furthermore, the kit includes reagents for detecting GNGT1 mRNA or protein expression levels using RT-PCR, RT-qPCR, microarray detection, DNA blotting, in situ hybridization, Western blotting, flow cytometry, immunohistochemistry, ELISA, or electrochemiluminescence.

[0022] Furthermore, the product also includes reagents for processing samples.

[0023] A third aspect of the present invention provides an AUB diagnostic system, the diagnostic system comprising:

[0024] Detection component: The detection component is used to detect the expression level of GNGT1;

[0025] Result judgment component: The result judgment component is used to output whether the subject has the risk of having AUB based on the expression level of GNGT1 detected by the detection component.

[0026] Furthermore, the expression level of GNGT1 includes the mRNA expression level of GNGT1 and the protein expression level of GNGT1.

[0027] Furthermore, the AUB is selected from the COEIN class and the PALM class; the COEIN class includes AUB-C, AUB-O, AUB-E, AUB-I, and AUB-N; the PALM class includes AUB-P, AUB-A, AUB-L, and AUB-M.

[0028] Furthermore, the AUB is selected from the PALM class.

[0029] Furthermore, the AUB is AUB-M.

[0030] Furthermore, the detection components include qPCR kits, ELISA kits, immunoblotting kits, flow cytometry kits, immunohistochemistry kits, immunochromatographic kits, electrochemiluminescence kits, qPCR instruments, ELISA detection devices, immunoblotting devices, flow cytometry devices, immunohistochemistry devices, immunochromatographic devices, or electrochemiluminescence detection devices.

[0031] Furthermore, the result determination component includes an input module, an analysis module, and an output module; the input module is used to input the expression level of GNGT1; the analysis module is used to analyze whether the subject has the risk of AUB based on the expression level of GNGT1; and the output module is used to output the analysis results of the analysis module.

[0032] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the system described in the third aspect of the present invention.

[0033] The fifth aspect of the invention provides the application of GNGT1 in constructing a computational model for diagnosing AUB.

[0034] Furthermore, the AUB is selected from the COEIN class and the PALM class; the COEIN class includes AUB-C, AUB-O, AUB-E, AUB-I, and AUB-N; the PALM class includes AUB-P, AUB-A, AUB-L, and AUB-M.

[0035] Furthermore, the AUB is selected from the PALM class.

[0036] Furthermore, the AUB is AUB-M.

[0037] Advantages and beneficial effects of the present invention:

[0038] This invention selects GNGT1 as a gene marker, which can effectively distinguish between normal endometrium and AUB-M, thereby determining whether the subject has AUB-M or is at risk of developing AUB-M, thus providing a warning to the subject and enabling early intervention. Attached Figure Description

[0039] Figure 1 This is a graph showing the differential expression of GNGT1;

[0040] Figure 2 Here are the diagnostic efficacy graphs for GNGT1, where 2A is the ROC curve of GNGT1 in the training set and 2B is the ROC curve of GNGT1 in the validation set.

[0041] Specific implementation methods

[0042] This invention, through extensive and in-depth research, collected samples of AUB-M (abnormal uterine bleeding caused by malignant endometrial lesions, including endometrial cancer and endometrial dysplasia) tissue and normal endometrial tissue. It found that the content of GNGT1 in AUB-M tissue was significantly higher than that in normal endometrial tissue. Furthermore, the diagnostic efficacy of GNGT1 was analyzed, suggesting that GNGT1 can be used as a better genetic marker for the diagnosis of AUB-M.

[0043] AUB

[0044] The term "AUB" stands for "abnormal uterine bleeding," which refers to uterine bleeding that occurs at an inappropriate time during a patient's menstrual cycle or in amounts exceeding typical menstrual bleeding, such as "heavy menstrual bleeding" and "menorrhagia." These are defined as menstrual bleeding of 80 ml or more per menstrual cycle (e.g., 80 ml, 90 ml, 100 ml, 110 ml, 120 ml, 130 ml, 140 ml, 150 ml, 160 ml, 170 ml, 180 ml, 190 ml, 200 ml or more).

[0045] In this invention, "AUB" includes AUB-P (endometrial polyp), AUB-A (uterine gland disease), AUB-L (uterine leiomyoma), AUB-M (endometrial malignancy and endometrial dysplasia), AUB-C (systemic coagulation-related disease), AUB-O (ovulation disorder), AUB-E (local endometrial abnormality), AUB-I (iatrogenic AUB), and AUB-N (unclassified AUB). Based on their initial letter abbreviations, they are divided into PALM and COEIN categories. PALM involves structural changes, while COEIN does not involve uterine structural changes.

[0046] The most common malignant lesion of the endometrium is "endometrial cancer," which includes all forms and subtypes of the disease. It is a cancer that originates in the endometrium of the uterus (womb), including but not limited to endometrioid carcinoma, clear cell carcinoma of the endometrium, mucinous carcinoma of the endometrium, serous carcinoma of the endometrium, and carcinosarcoma of the endometrium. It is more common in women during the perimenopausal and postmenopausal period.

[0047] Genetic markers

[0048] "Gene markers" are also called "biomarkers" or "molecular markers," and the three terms are used interchangeably in this invention. A gene marker is any gene or protein whose expression level in a tissue or cell is altered compared to the expression level in a normal or healthy cell or tissue.

[0049] Genetic markers can be present differentially at any level, but are generally present at levels where the increase is at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 100%, at least 110%, or at least 120%. %, at least 130%, at least 140%, at least 150%, or more; or generally present at levels reduced by at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, or 100% (i.e., not present).

[0050] Preferably, the genetic markers are present at a level of statistical significance (i.e., p-value less than 0.05 and / or q-value less than 0.10, as determined by Welch's T-test or Wilcoxon's rank-sum test).

[0051] In a specific embodiment of the present invention, the genetic marker is GNGT1.

[0052] GNGT1 includes wild-type, mutant, or fragments thereof. The term encompasses full-length, unprocessed GNGT1, as well as any form of GNGT1 derived from cell processing. The term encompasses naturally occurring variants of GNGT1 (e.g., splice variants or allelic variants). The term encompasses, for example, the GNGT1 gene, human GNGT1, and GNGT1 from any other vertebrate source, including mammals such as primates and rodents (e.g., mice and rats). As a preferred embodiment, in this invention, GNGT1 is the human gene with gene ID 2792.

[0053] In this invention, the term "sample" refers to a composition obtained from or derived from a subject (e.g., an individual of interest) that contains cells and / or other molecular entities to be characterized and / or identified based on, for example, physical, biochemical, chemical, and / or physiological characteristics. Samples include, but are not limited to: tissue samples (e.g., tumor tissue samples), primary or cultured cells or cell lines, cell supernatants, cell lysates, platelets, serum, plasma, vitreous fluid, lymph, synovial fluid, follicular fluid, semen, amniotic fluid, milk, whole blood, blood-derived cells, urine, cerebrospinal fluid, saliva, sputum, tears, sweat, mucus, tumor lysates, tissue culture media, tissue extracts such as homogenized tissue, tumor tissue, cell extracts, and combinations thereof. Preferably, the sample is selected from tissues.

[0054] In this invention, the term "diagnosis" refers to a predictive process in which the presence, absence, severity, or treatment progress of a disease, ailment, or other medical condition is evaluated. For the purposes of this invention, diagnosis also includes predictive processes for determining treatment outcomes. Similarly, the term "diagnosis" refers to determining whether a treated individual exhibits one or more characteristics of a symptom or disease. The term "diagnosis" includes establishing the presence or absence of a target, such as a target antigen or binding agent, or establishing or otherwise determining one or more characteristics of a symptom or disease, including type, grade, stage, or similar conditions. The term "diagnosis" includes initial diagnosis or testing, prognosis, and monitoring of the symptom or disease. Additionally, the term "monitoring," for example, in "monitoring the progression of a disease or symptom," refers to ongoing diagnostic work on samples obtained from a treated individual who has or is suspected of having a disease or symptom.

[0055] This invention encompasses any available method in the prior art for detecting GNGT1 expression. GNGT1 expression can be detected at the nucleic acid level (e.g., RNA transcript) or the protein level. "Detecting GNGT1 expression" aims to determine the quantity or presence of the RNA transcript or the expression product of the GNGT1 gene. "Detecting GNGT1 expression" includes instances where GNGT1 is determined not to be expressed, not to be detectable, expressed at low levels, expressed at normal levels, or overexpressed.

[0056] Detection methods

[0057] This invention can be performed using a variety of nucleic acid and protein technologies known to those skilled in the art, including but not limited to: RT-PCR, RT-qPCR, microarray detection, DNA blotting, in situ hybridization (ISH), protein blotting, flow cytometry, immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), enzyme immunoassay (EIA), electrochemiluminescence immunoassay, fluorescence immunoassay (FIA), and radioimmunoassay (RIA).

[0058] The term "RT-PCR," also known as "reverse transcription polymerase chain reaction," is a technique that combines reverse transcription (RT) of RNA with polymerase chain amplification (PCR) of cDNA. First, cDNA is synthesized from RNA using reverse transcriptase. Then, using the cDNA as a template, the target fragment is amplified by DNA polymerase. RT-PCR is a sensitive and widely used technique, capable of detecting gene expression levels in cells, the abundance of RNA viruses in cells, and directly cloning the cDNA sequence of specific genes.

[0059] The term "RT-qPCR," also known as "quantitative real-time polymerase chain reaction," refers to the use of changes in fluorescence signals to detect changes in the amount of amplification products in each cycle of the PCR amplification reaction in real time, ultimately enabling precise quantitative analysis of the starting template.

[0060] "DNA blotting," also known as "Southern blotting," is used to detect specific DNA sequences. The DNA extracted from the sample is broken, separated by electrophoresis on a matrix gel, and then transferred to a membrane filter. The DNA bound to the filter hybridizes with a labeled probe complementary to the sequence of interest. The hybridized probe bound to the filter is then detected.

[0061] In situ hybridization (ISH) is a hybridization technique that uses labeled complementary DNA or RNA strands as probes to locate specific DNA or RNA sequences in a portion or section of tissue (in situ) or, if the tissue is small enough, the entire tissue (whole tissue embedded ISH). DNA ISH can be used to determine chromosome structure. RNA ISH is used to measure and locate mRNA and other transcripts (e.g., ncRNA) within tissue sections or whole tissue embedded in tissue. Typically, sample cells and tissues are treated to fix target transcripts in situ and increase probe penetration. The probe hybridizes with the target sequence at high temperature, and then excess probe is washed away. Probes labeled with radioactive, fluorescent, or antigen-labeled bases in the tissue are located and quantified using autoradiography, fluorescence microscopy, or immunohistochemistry, respectively. ISH can also use two or more probes labeled with radioactive or other non-radioactive markers to simultaneously detect two or more transcripts.

[0062] In this invention, both non-amplified and amplified nucleic acids can be detected by any conventional means.

[0063] This invention provides a product for diagnosing AUB-M, the product comprising a reagent for detecting GNGT1 in a sample.

[0064] The reagents for detecting GNGT1 in this invention include reagents for detecting gene transcription levels, such as mRNA levels, and reagents for detecting gene translation levels, such as protein levels. Reagents for detecting gene transcription levels include, but are not limited to, primers and probes, while reagents for detecting gene translation levels include protein binding agents.

[0065] A primer is an oligonucleotide that hybridizes to a sequence in a target nucleic acid ("primer binding site") and can be used as a point to initiate the synthesis along the complementary strand of the nucleic acid under conditions suitable for synthesis.

[0066] A "probe" is a molecule that can bind to a specific sequence, subsequence, or other portion of another molecule. Depending on the stringency of the hybridization conditions, a probe can bind to an oligonucleotide that lacks complete sequence complementarity with the probe. Probes can be labeled directly or indirectly. Hybridization methods include, but are not limited to, solution-phase, solid-phase, mixed-phase, or in situ hybridization assays.

[0067] "Protein binders" include, for example, protein receptors, protein-binding lectins, proteins-targeting antibodies, protein-targeting peptide bodies, bispecific dual binders, or bispecific antibody forms.

[0068] In this invention, products for diagnosing AUB-M include, but are not limited to, formulations, nucleic acid membrane strips, chips, and reagent kits.

[0069] In this invention, the nucleic acid membrane strip includes a substrate and an oligonucleotide probe immobilized on the substrate; the substrate can be any substrate suitable for immobilizing the oligonucleotide probe, such as a nylon membrane, nitrocellulose membrane, polypropylene membrane, glass slide, silicone wafer, micro-magnetic beads, etc.

[0070] In this invention, "chip" is also referred to as "array," meaning a solid support containing linked nucleic acid or peptide probes. Arrays typically contain a variety of different nucleic acid or peptide probes attached to a substrate surface at different known locations. These arrays, also called "microarrays," can typically be produced using mechanosynthesis or photoguided synthesis methods, which combine photolithography and solid-phase synthesis. Arrays can comprise flat surfaces or can be nucleic acids or peptides on beads, gels, polymer surfaces, fibers such as optical fibers, glass, or any other suitable substrate. Arrays can be packaged in a manner that allows for diagnostic or other manipulation of a fully functional device.

[0071] A "microarray" is a hybridization array element arranged in an ordered manner on a matrix, such as a polynucleotide probe (e.g., an oligonucleotide) or a binder (e.g., an antibody). The matrix can be a solid matrix, such as a glass or silica slide, beads, fiber optic adhesive, or a semi-solid matrix, such as a nitrocellulose membrane. The nucleotide sequence can be DNA, RNA, or any arrangement thereof.

[0072] The most reliable results are likely obtained when samples are processed in a laboratory setting. For example, samples can be obtained from subjects in a physician's office and then sent to a hospital or commercial medical laboratory for further testing. However, in many cases, it may be desirable to provide immediate results in a clinician's office or allow subjects to perform the test at home. In some cases, the need for portable, pre-packaged, disposable tests that can be used by subjects without assistance or guidance is more important than high accuracy. In many cases, especially with physician follow-up, preliminary testing, or even tests with reduced sensitivity and / or specificity, may suffice. Therefore, assays offered in product form can involve detecting and measuring relatively small amounts of biomarkers to reduce the complexity and cost of the assay.

[0073] Any form of sample assay capable of detecting genetic biomarkers in a sample, as described in this invention, can be used. Typically, the assay quantifies biomarkers in a sample to a certain extent, such as whether their concentration or amount is above or below a predetermined threshold. Such kits may take the form of test strips, dipsticks, boxes, cartridges, chip-based or bead-based arrays, multiwell plates, or a series of containers. One or more reagents are provided to detect the presence and / or concentration and / or amount of selected sample biomarkers. A subject's sample may be dispensed directly into the assay or indirectly from stored or previously obtained samples. The presence or absence of biomarkers above or below a predetermined threshold can be indicated, for example, by colorimetry, fluorescence, electrochemiluminescence, or other outputs (e.g., in enzyme immunoassays (EIAs), such as enzyme-linked immunosorbent assays (ELISAs).

[0074] In one embodiment, the product may comprise a solid substrate such as a chip, glass slide, array, etc., having reagents capable of detecting and / or quantifying one or more sample biomarkers immobilized at predetermined locations on the substrate. As an illustrative example, reagents immobilized at discrete predetermined locations may be provided to the chip for detecting and quantifying the presence and / or concentration and / or amount of a biomarker in a sample. As described above, increased levels of GNGT1 are found in samples from subjects with AUB-M. The chip may be configured such that a detectable output (e.g., a color change) is provided only when the concentration of the biomarker exceeds a threshold selected or distinguishing between the concentration and / or amount of a biomarker indicating a control subject and the concentration and / or amount of a biomarker indicating a patient with or predisposing to AUB-M. Thus, the presence of a detectable output (such as a color change) immediately indicates the presence of a significantly elevated level of the biomarker in the sample, suggesting that the subject has or is predisposing to AUB-M.

[0075] system

[0076] In this invention, the term "diagnostic system" refers to a system in which the operation of one or more endpoint devices needs to be monitored. A diagnostic system comprises at least two devices that transmit and / or receive data from each other. A diagnostic system can be a system of any size, including but not limited to as few as two devices, or as many as required to create a LAN, WAN, SAN, Internet, local area network, etc.

[0077] In this invention, the biomarkers can be measured individually, or, in one embodiment, simultaneously, for example, using chip or bead-based array technology. The concentrations of the biomarkers are then interpreted independently, for example, using individual cutoffs for each biomarker, or in combination.

[0078] In this invention, the term "computational model" refers to a mathematical model in computational science that enables the study of the behavior of complex systems through computer simulation. The term "computational model" used in this invention refers to a mathematical model that correlates the expression level of the biomarker GNGT1 with the risk or likelihood of AUB-M disease. Any suitable mathematical method described in the prior art can be used to associate the biomarker combination with the disease. The logarithmic function used to associate the biomarker combination with the disease preferably employs an algorithm developed and obtained through the application of statistical methods. Suitable statistical methods include discriminant analysis (DA) (i.e., linear, quadratic, regular DA), kernel methods (i.e., SVM), nonparametric methods (i.e., k-nearest neighbor classifier), PLS (partial least squares), tree-based methods (i.e., logistic regression, CART, random forest, boost / bag method), generalized linear models (i.e., logistic regression), principal component analysis (i.e., SIMCA), generalized superposition models, fuzzy logic-based methods, and methods based on neural networks and genetic algorithms. Those skilled in the art will have no problem selecting suitable statistical methods to evaluate the biomarker combination of this invention and thereby obtaining suitable mathematical algorithms. In the implementation scheme, the statistical method used to obtain the mathematical algorithm used in evaluating AUB-M is selected from DA (i.e., linear, quadratic, regular discriminant analysis), Kernel method (i.e., SVM), nonparametric method (i.e., k-nearest neighbor classifier), PLS (partial least squares), tree-based method (i.e., logistic regression, CART, random forest method, boosting method), or generalized linear model (i.e., log regression).

[0079] The system provided by this invention can be embodied in a programmable manner. Various aspects of the technology can be considered as products typically in the form of machine (or processor) executable code and / or associated data, executed or embodied in a machine-readable medium. Machine-executable code can be stored in electronic storage units such as memory (e.g., read-only memory, random access memory, flash memory) or hard disks. "Storage" media can include any or all tangible memory of computers, processors, etc., or related modules thereof, such as various semiconductor memories, tape drives, disk drives, etc., which can provide non-transitory storage for software programming at any time. All or part of the software can sometimes be communicated via the Internet or various other communication networks. For example, such communication can enable the loading of software from one computer or processor to another computer or processor, e.g., from a management server or host to a computer platform for an application server. Therefore, another type of medium capable of carrying software elements includes light waves, radio waves, and electromagnetic waves used such as physical interfaces between local devices, via wired and fiber optic terrestrial networks, and over various air links. Physical elements carrying such waves, such as wired or wireless links, optical links, etc., can also be considered as media for carrying software. As used in this invention, unless limited to a non-transitory, tangible "storage" medium.

[0080] Therefore, machine-readable media, such as computer-executable code, can take many forms, including but not limited to tangible storage media, carrier media, or physical transmission media. Non-volatile storage media include, for example, optical discs or disks, such as any storage device in any computer, etc. Volatile storage media include dynamic memory, such as the main memory of such computer platforms. Tangible transmission media include coaxial cables; copper wires and optical fibers, including wires that form buses within a computer system. Carrier transmission media can take the form of electrical or electromagnetic signals or sound or light waves, such as those generated during radio frequency and infrared data communications. Therefore, common forms of computer-readable media include, for example: floppy disks, floppy disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs or DVD-ROMs, any other optical media, punched card tapes, any other physical storage media with a perforated pattern, RAM, ROM, PROM and EPROM, FLASH-EPROM, any other memory chips or cartridges, carriers for transmitting data or instructions, cables or links for transmitting such carriers, or any other media from which a computer can read programming code and / or data. Many of these computer-readable media can be used to transmit one or more sequences of instructions to a processor for execution.

[0081] Diagnostic efficacy

[0082] The area under the receiver operating characteristic (ROC) is an indicator of the performance or accuracy of a diagnostic procedure. The accuracy of a diagnostic method is best described by its receiver operating characteristic (ROC). The ROC plot is a line graph derived from all sensitivity / specificity pairs that continuously change the decision threshold across the entire range of observed data.

[0083] The clinical performance of a laboratory test depends on its diagnostic accuracy, or its ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy measures the ability to correctly distinguish between two different conditions in a subject under investigation. Such conditions are, for example, health and disease, or disease progression versus no disease progression.

[0084] In each case, the ROC plot depicts the overlap between the two distributions by plotting sensitivity against 1-specificity over the entire range of the decision threshold. The y-axis represents sensitivity, or the true positive score [defined as (number of true positive test results) / (number of true positive test results + number of false negative test results)]. This is also referred to as the presence of the disease or condition. It is calculated only from the affected subgroup. The x-axis represents the false positive score, or 1-specificity [defined as (number of false positive results) / (number of true negative results + number of false positive results)]. It is an indicator of specificity and is calculated entirely from the unaffected subgroup. Because the true and false positive scores are calculated completely separately using test results from two different subgroups, the ROC plot is independent of the prevalence of the disease in the sample. Each point on the ROC plot represents a sensitivity / 1-specificity pair corresponding to a specific decision threshold. A test with perfect discrimination (no overlap between the two outcome distributions) has an ROC plot through the top left corner, where the true positive score is 1.0, or 100% (perfect sensitivity), and the false positive score is 0 (perfect specificity). The theoretical line graph for a non-discriminating test (where the results distribution is the same for both groups) is a 45° diagonal line from the bottom left to the top right. Most lines fall between these two extremes. (If the ROC line falls completely below the 45° diagonal, this can be easily corrected by reversing the "positive" criterion from "greater than" to "less than" or vice versa.) Qualitatively, the closer the line graph is to the top left, the higher the overall accuracy of the test.

[0085] A convenient goal for quantifying the diagnostic accuracy of laboratory tests is to express their performance using a single numerical value. The most common global metric is the area under the ROC curve (AUC). Typically, this area is always ≥0.5 (if not, the decision rule can be reversed to make it so). The value ranges between 1.0 (perfectly separating the test values ​​of the two groups) and 0.5 (no significant difference in distribution between the test values ​​of the two groups). The area depends not only on specific parts of the graph, such as the point closest to the diagonal or the sensitivity at 90% specificity, but also on the entire graph. This is a quantitative, descriptive representation of how close the ROC graph is to perfect (area = 1.0).

[0086] The overall sensitivity of the assay will depend on the specificity required to implement the methods disclosed in this invention. In some preferred settings, a specificity of 75% may be sufficient, and statistical methods and resulting algorithms can be based on this specificity requirement. Preferably, the method for assessing individuals at risk of AUB-M is based on specificities of 84.24% and 82.35%.

[0087] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. The following embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Experimental methods not specifically described in the embodiments are generally performed under conventional conditions or as recommended by the manufacturer.

[0088] Example: Expression level of GNGT1 in AUB-M

[0089] 1. Sample Source

[0090] All endometrial tissue was taken from the Obstetrics and Gynecology Hospital affiliated with Zhejiang University School of Medicine.

[0091] The training set included 30 cases of AUB-M and 30 cases of control; all patients in both groups were female, with a mean age of 50±4.76 years and no significant difference in age between the groups. The AUB-M group included 8 cases of atypical endometrial hyperplasia and 22 cases of endometrial cancer (all pathological types were endometrioid adenocarcinoma).

[0092] The validation set included 34 cases each of AUB-M and control; all patients in both groups were female, with a mean age of 52±5.12 years and no significant difference in age between the groups. AUB-M included 10 cases of atypical endometrial hyperplasia and 24 cases of endometrial cancer (all pathological types were endometrioid adenocarcinoma).

[0093] Inclusion and exclusion criteria for study participants:

[0094] AUB-M inclusion criteria: Abnormal bleeding originating from the uterine cavity that does not conform to any of the normal menstrual cycle frequency, regularity, menstrual duration, or menstrual bleeding amount. Pathologically confirmed as endometrial atypical hyperplasia or endometrial cancer.

[0095] Inclusion criteria for the control group: clinical presentation of abnormal uterine bleeding, with diagnostic curettage or hysteroscopic pathology showing a simple proliferative phase of endometrial tissue. Exclusion of other organic diseases.

[0096] Exclusion criteria: (1) Pregnancy; (2) Vaginal bleeding caused by other organic diseases, such as genital tract trauma or foreign bodies in the genital tract; (3) Hypothyroidism; (4) Acute or chronic liver disease; (5) Systemic lupus erythematosus; (6) Patients who need long-term anticoagulant therapy due to thrombotic diseases, kidney dialysis, or after placement of a cardiac stent or artificial heart valve replacement; (7) History of malignant tumors in other organs of the body; (8) History of mental illness; (9) History of taking estrogen, liver enzyme inhibitors, or other drugs within the past six months; (10) Unaware consent.

[0097] 2. Experimental Methods

[0098] 1) Tissue processing: Human endometrial tissue samples (40 mg) were removed and transported on ice with PBS. They were then washed extensively with PBS to remove all blood.

[0099] 2) RT-qPCR detection of GNGT1 expression level

[0100] The relative mRNA expression levels of GNGT1 in normal endometrium and AUB-M group were detected by real-time quantitative PCR.

[0101] Total RNA was extracted from tissues using the Trizol method, and cDNA was synthesized using the PrimeScript™ RT kit according to the manufacturer's instructions. RT-qPCR reactions were performed using the Applied Biosystems (USA) 7900HT system and the SYBR Premix ExTaq kit. Each tissue sample was tested three times. All samples used GAPDH as an internal control primer sequence, which was obtained from PrimerBank and synthesized by Generay (Shanghai, China). The fold increase was calculated using the formula fold increase = 2. -ΔΔCt Calculate mRNA expression levels. Primer sequences are shown in Table 1.

[0102] Table 1 Primer sequences

[0103] SEQ ID NO.2(GNGT1-reverse) 5'-GGATGCCCTTTACCAGTGGA-3' SEQ ID NO.3 (GAPDH-forward) 5'-GCACCGTCAAGGCTGAGAAC-3' SEQ ID NO.4 (GAPDH-reverse) 5'-TGGTGAAGACGCCAGTGGA-3'

[0104] 3. Diagnostic efficacy verification

[0105] ROC curves for the subjects were plotted using GraphPad, and AUC values, sensitivity, and specificity were analyzed to determine the diagnostic efficacy of the indicators. Gene expression levels (log2 expression levels) were used for analysis, and the point level corresponding to the highest Youden index was selected as the cutoff value.

[0106] 4. Experimental Results

[0107] 1) The expression results of GNGT1 in the training set are shown in Table 2. The results show that GNGT1 is upregulated in AUB-M tissue.

[0108] Table 2. Expression of GNGT1

[0109] baseMean 17.54702661 log2FoldChange 6.225073451 lfcSE 1.413878461 stat 4.402834913 pvalue 1.07E-05 padj 0.002662709 Expression of situation Upward

[0110] 2) The expression results of GNGT1 in the validation set are as follows: Figure 1 As shown, the results indicate that GNGT1 expression in AUB-M was significantly higher than that in the normal endometrial group, and the difference was statistically significant (p < 0.001).

[0111] 3) Diagnostic efficacy of GNGT1 on the training and validation sets, such as Figure 2 As shown in Table 3, the model cutoff for GNGT1 mRNA expression level in the diagnosis of AUB-M was 2.580 (73.53, 82.35), and the diagnostic efficacy AUC of the training set and validation set was 0.875 and 0.803, respectively. The results indicate that GNGT1 can be used to differentiate between normal endometrium and AUB-M.

[0112] Table 3 Diagnostic efficacy of GNGT1

[0113] training set 0.875 79.73 84.24 Validation set 0.803 73.53 82.35

[0114] The above description of the embodiments is only for understanding the method and core ideas of the present invention. It should be noted that those skilled in the art can make various improvements and modifications to the present invention without departing from the principles of the invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims

1. Application of reagents for detecting GNGT1 in samples in the preparation of products for diagnosing AUB; The AUB is AUB-M.

2. The application according to claim 1, characterized in that, The reagents for detecting GNGT1 in the sample include reagents for detecting the mRNA expression level of GNGT1 in the sample and reagents for detecting the protein expression level of GNGT1 in the sample.

3. The application according to claim 2, characterized in that, The reagents are selected from: primers that specifically amplify GNGT1, probes that specifically recognize GNGT1, or binding agents that specifically bind to proteins encoded by GNGT1.

4. The application according to claim 3, characterized in that, The sequences of the primers for amplifying GNGT1 are shown in SEQ ID NO.1-2.

5. The application according to claim 1, characterized in that, The products include formulations, kits, chips, or nucleic acid membrane strips capable of detecting GNGT1 expression levels.

6. The application according to claim 5, characterized in that, The kit includes reagents for detecting GNGT1 mRNA or protein expression levels using RT-PCR, RT-qPCR, microarray detection, DNA blotting, in situ hybridization, Western blotting, flow cytometry, immunohistochemistry, ELISA, and electrochemiluminescence.

7. The application according to any one of claims 1-6, characterized in that, The product also includes reagents for processing samples.

8. Application of reagents for detecting GNGT1 in the preparation of an AUB diagnostic system, the diagnostic system comprising: Detection component: The detection component is used to detect the expression level of GNGT1; Result judgment component: The result judgment component is used to output whether the subject has the risk of having AUB based on the expression level of GNGT1 detected by the detection component; The AUB is AUB-M.

9. The application according to claim 8, characterized in that, The expression level of GNGT1 includes the mRNA expression level of GNGT1 and the protein expression level of GNGT1.

10. The application according to claim 8, characterized in that, The detection components include qPCR kits, ELISA kits, immunoblotting kits, flow cytometry kits, immunohistochemistry kits, immunochromatographic kits, electrochemiluminescence kits, qPCR instruments, ELISA detection devices, immunoblotting devices, flow cytometry devices, immunohistochemistry devices, immunochromatographic devices, or electrochemiluminescence detection devices.

11. The application according to claim 8, characterized in that, The result determination component includes an input module, an analysis module, and an output module; the input module is used to input the expression level of GNGT1; the analysis module is used to analyze whether the subject has the risk of AUB based on the expression level of GNGT1; and the output module is used to output the analysis results of the analysis module.

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