A set of blood markers and their application and method, storage medium and device for assisting in diagnosing benign or malignant nodular thyroid disease

Abstract

The present invention relates to the field of proteomics technology, and specifically to a group of blood markers and their application and methods, storage media and devices for assisting in the diagnosis of benign and malignant nodular thyroid disease. The blood markers are TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10; the method for assisting in the diagnosis of benign and malignant nodular thyroid disease comprises the following steps: (1) performing binary logistic regression analysis on the relative concentration data of blood markers in serum samples, drawing ROC curves, and determining the optimal diagnostic limit value; (2) calculating the Prob value of the patient's serum; (3) comparing the Prob value of the patient's serum with the optimal diagnostic limit value to determine the benign and malignant. The marker selected by the present invention is serum protein, and sampling can be completed by blood sampling, which is minimally invasive to the patient and is not affected by the morphology of the nodules, which is helpful for early detection of the disease and evaluation of its progress.

Description

Technical Field

[0001] The present invention relates to the technical field of proteomics, and in particular to a group of blood markers and their application as well as a method, storage medium and device for assisting in diagnosing benign or malignant nodular thyroid disease. Background Art

[0002] Nodular thyroid disease (NTD) is a common endocrine disease characterized by localized masses in the thyroid tissue, which may appear as single or multiple nodules. Although most thyroid nodules are benign, some of them will develop into thyroid cancer. Early differentiation between benign and malignant nodules is crucial for the choice of clinical treatment.

[0003] The judgment of benign or malignant thyroid nodules is a complex physiological process, which is affected by many factors. Currently, the diagnosis of thyroid nodules mainly relies on imaging examinations (such as ultrasound) and fine needle aspiration cytology (FNA), but these methods have certain limitations, especially for some nodules with fuzzy morphology and unclear boundaries. The diagnostic accuracy of traditional diagnostic methods is limited, and a high number of false positive or false negative results may occur. Therefore, the development of auxiliary diagnostic methods based on new biomarkers is of great significance to improve the diagnostic efficiency and accuracy of thyroid nodules.

[0004] In recent years, the rapid development of high-throughput omics technology has made it possible to discover new biomarkers. Proteomics research can systematically reveal the relative abundance and differential expression of proteins in biological samples, thereby helping to identify molecular features closely related to the disease. CN 111292801 A discloses a method for evaluating thyroid nodules by combining protein mass spectrometry with deep learning. First, the protein matrix results of the thyroid tissue sample to be tested are obtained, and then the protein matrix results are input into the deep learning model, and finally the probability of malignant thyroid nodules of the thyroid tissue sample to be tested is output. The disadvantage of this method is that it is necessary to obtain thyroid tissue samples for testing through thyroid puncture, which is an invasive examination, the pain during the operation is relatively obvious, and the postoperative care requirements are also high. Summary of the invention

[0005] In view of the technical problems of the limitations of the existing common assessment methods for benign and malignant thyroid nodules, such as imaging examinations and fine needle aspiration cytology, the present invention finds that the expression level of specific proteins in the blood can sensitively reflect the state of the pathological process in the body, and based on this, provides a group of blood markers and their application and methods, storage media and devices for assisting in the diagnosis of benign and malignant nodular thyroid diseases. The markers selected by the present invention are serum proteins, which can be sampled by blood sampling, are minimally invasive to patients, and are not affected by the morphology of nodules, which helps to detect the disease early and evaluate its progression.

[0006] The technical solution of the present invention is as follows:

[0007] In a first aspect, the present invention provides a group of blood markers, specifically TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10.

[0008] In a second aspect, the present invention provides an application of the above-mentioned blood marker in the preparation of a product to assist in determining whether nodular thyroid disease is benign or malignant, such as a detection kit.

[0009] In a third aspect, the present invention provides a method for assisting in the diagnosis of benign or malignant nodular thyroid disease using the above-mentioned blood markers, comprising the following steps:

[0010] (1) Binary logistic regression analysis was performed on the relative concentration data of blood markers TSHB (thyroid stimulating hormone beta subunit), OMG (myelin oligodendrocyte protein), NT5E (extracellular 5'-nucleotidase), HAO1 (hydroxy acid oxidase 1), VMO1 (human vitelline membrane protein 1), LGALS4 (galectin 4), CRH (corticotropin-releasing hormone), TG (thyroglobulin), GAST (gastrin), and EPHA10 (ephrin A receptor 10) in serum samples to obtain the binary logistic regression equation, draw the ROC curve, and calculate the point on the curve with the maximum sum of sensitivity and specificity. The classification threshold corresponding to this point was used as the optimal diagnostic limit value;

[0011] (2) Calculate the Prob value of the patient's serum, Prob = 1 / (1+e -y ), where y is the calculation result obtained by substituting the relative concentration data of each blood marker in the patient's serum into the binary logistic regression equation;

[0012] (3) When the Prob value of the patient's serum is ≥ the optimal diagnostic limit, it is judged as a malignant nodule; when the Prob value of the patient's serum is < the optimal diagnostic limit, it is judged as a benign nodule.

[0013] Furthermore, step (1) was performed using SPSS software.

[0014] In a fourth aspect, the present invention provides a more specific method for assisting in the diagnosis of benign or malignant nodular thyroid disease using the above-mentioned blood markers, comprising the following steps:

[0015] S1: Calculate the Prob value of the patient's serum according to the following formula;

[0016] Prob=1 / (1+e -y ),

[0017] y=-0.2855228-0.2616326×CTSHB -0.0682475×C OMG -1.1625307×C NT5E +0.1484289×C HAO1 +2.2295773×C VMO1 -1.1700533×C LGALS4 +0.9549436×C CRH -0.7024510×C TG +1.3915070×C GAST -1.3661147×C EPHA10 ,

[0018] In the formula, C TSHB , C OMG , C NT5E , C HAO1 , C VMO1 , C LGALS4 , C CRH , C TG , C GAST and C EPHA10 They are the relative concentration data of blood markers TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10 in the serum of patients;

[0019] S2: Compare the calculated Prob value of the patient's serum with 0.7229477. When the Prob value of the patient's serum is ≥ 0.7229477, it is judged as a malignant nodule; when the Prob value of the patient's serum is < 0.7229477, it is judged as a benign nodule.

[0020] Furthermore, all steps of the method for assisting in the diagnosis of benign and malignant nodular thyroid disease described in the third and fourth aspects can be implemented by a computer or other device and used for non-disease diagnosis and treatment purposes.

[0021] Furthermore, in the third and fourth aspects, the relative concentration data of blood markers TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10 are obtained by Olink proteomics technology. Olink proteomics technology detects protein expression levels with high resolution and high sensitivity, and can perform qualitative and relative quantitative analysis, providing a basis for auxiliary diagnosis and risk assessment of nodular thyroid disease.

[0022] In a fifth aspect, the present invention provides a computer-readable storage medium for assisting in the diagnosis of benign and malignant nodular thyroid disease. A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method described in the third and fourth aspects are implemented.

[0023] In a sixth aspect, the present invention provides a device for assisting in the diagnosis of benign and malignant nodular thyroid disease, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the method described in the third and fourth aspects when executing the computer program.

[0024] The beneficial effects of the present invention are:

[0025] The present invention uses Olink proteomics technology to screen out ten proteins (TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10) from serum. These proteins are closely related to the functional state of thyroid tissue, involving multiple biological processes such as cell proliferation, apoptosis, oxidative stress response and inflammation, and can provide important information for judging the benign or malignant nature of nodules. There is currently no report on the use of this group of serum proteins to assist in the diagnosis of benign or malignant nodular thyroid disease. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 It is the distribution of the relative expression levels of blood markers in the serum samples of Example 1 in benign and malignant nodules.

[0028] Figure 2 This is the ROC curve of the blood markers in Example 3 for distinguishing benign and malignant nodular thyroid disease.

[0029] Figure 1 In the table, * indicates p<0.05, i.e. the results are significantly different; ** indicates p<0.01, i.e. the results are highly significantly different; and *** indicates p<0.001, i.e. the results are extremely significantly different. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] Example 1

[0032] A total of 51 patients diagnosed with nodular thyroid disease were selected as test subjects. After pathological diagnosis, 24 patients were found to have benign nodules and 27 patients were found to have malignant nodules.

[0033] Blood was collected from 51 test subjects, and recombinant proteins of known concentrations were used as standard substances. The relative concentrations of serum proteins in the serum samples were detected using Olink proteomics technology, and a group of blood markers that can effectively distinguish between benign and malignant nodular thyroid disease were screened out. The distribution of the relative expression levels of this group of blood markers in benign and malignant nodules is shown in the figure. Figure 1 The specific composition is shown in Table 1 below.

[0034] Table 1 Ten blood markers for diagnosis of benign and malignant nodular thyroid disease

[0035]

[0036] Depend on Figure 1 It can be seen that this group of blood markers can be used to construct a diagnostic model for the benign and malignant nature of nodular thyroid disease, and to prepare products to assist in judging the benign and malignant nature of nodular thyroid disease. For example, a recombinant protein of blood marker with a known concentration is prepared as a standard substance to prepare a detection kit. When used, the detection kit uses Olink proteomics technology to detect the relative concentrations of TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10 in serum samples.

[0037] Example 2

[0038] A method for assisting in the diagnosis of benign or malignant nodular thyroid disease comprises the following steps:

[0039] (1) SPSS software was used to perform binary logistic regression analysis on the relative concentration data of each blood marker in serum samples to obtain the binary logistic regression equation, draw the ROC curve, and calculate the point on the curve with the maximum sum of sensitivity and specificity. The classification threshold corresponding to this point was used as the optimal diagnostic limit value;

[0040] (2) Calculate the Prob value of the patient's serum, Prob = 1 / (1+e -y ), where y is the calculation result obtained by substituting the relative concentration data of each blood marker in the patient's serum into the binary logistic regression equation;

[0041] (3) When the Prob value of the patient's serum is ≥ the optimal diagnostic cutoff value, it is judged as a malignant nodule; when the Prob value of the patient's serum is < the optimal diagnostic cutoff value, it is judged as a benign nodule;

[0042] The blood markers described in step (1) and step (2) are the blood marker combination consisting of TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10 screened in Example 1. The relative concentration data of blood markers in serum samples and patient serum can be obtained by using a detection kit using the above blood marker recombinant protein of known concentration as a standard substance through Olink proteomics technology.

[0043] Example 3

[0044] According to the method described in Example 2, a model for auxiliary diagnosis of benign and malignant nodular thyroid disease was constructed and applied based on 51 patients diagnosed with nodular thyroid disease, and the 51 patients were the patients in Example 1. The specific steps are as follows:

[0045] (1) Using a detection kit with a known concentration of blood marker recombinant protein as the standard substance, the relative concentration of each blood marker (TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10) in the serum samples was detected by Olink proteomics technology.

[0046] (2) SPSS software was used to perform logistic regression analysis on the relative concentration data of the ten proteins TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10, and a model for assisting in the diagnosis of benign and malignant nodular thyroid disease was constructed. The binary logistic regression equation is as follows:

[0047] y=-0.2855228-0.2616326×C TSHB -0.0682475×C OMG -1.1625307×C NT5E +0.1484289×C HAO1 +2.2295773×C VMO1 -1.1700533×C LGALS4 +0.9549436×C CRH-0.7024510×C TG +1.3915070×C GAST -1.3661147×C EPHA10 ;

[0048] (3) Draw the ROC curve, such as Figure 2 As shown, the AUC (area under the curve) is 0.793. The point with the maximum sum of sensitivity and specificity on the ROC curve is found. The classification threshold corresponding to this point is 0.7229477, that is, 0.7229477 is the optimal diagnostic limit value. At this time, the corresponding sensitivity is 0.741, indicating that the accuracy of the model in detecting malignant cases (true positive) is 74.1%; the specificity is 0.792, indicating that the accuracy of the model in correctly identifying benign cases (true negative) is 79.2%. It can be seen that the blood standard obtained by screening in Example 1 can assist in the diagnosis of benign and malignant nodular thyroid disease, and the effect is good;

[0049] (4) The relative concentration of each blood marker in the patient's serum was detected by Olink proteomics technology, and the obtained relative concentration data were substituted into the binary logistic regression equation obtained in step (2), and the y value was calculated. Then, according to Prob = 1 / (1 + e -y ), obtain the Prob value of the patient's serum;

[0050] (5) Compare the Prob value of the patient's serum with 0.7229477. When the Prob value of the patient's serum is ≥ 0.7229477, it is judged as a malignant nodule; when the Prob value of the patient's serum is < 0.7229477, it is judged as a benign nodule.

[0051] Example 4

[0052] A computer-readable storage medium for assisting in the diagnosis of benign or malignant nodular thyroid disease. The computer-readable storage medium stores a computer program, which implements the steps of the method of Example 2 or Example 3 when executed by a processor.

[0053] Example 5

[0054] A device for assisting in the diagnosis of benign or malignant nodular thyroid disease comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the steps of the method of Example 2 or Example 3 are implemented.

[0055] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A method for assisting in the diagnosis of benign or malignant nodular thyroid disease using blood markers, characterized in that: The steps include: (1) Binary logistic regression analysis was performed on the relative concentration data of blood markers TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST, and EPHA10 in serum samples to obtain the binary logistic regression equation, draw the ROC curve, and calculate the point on the curve with the maximum sum of sensitivity and specificity. The classification threshold corresponding to this point was used as the optimal diagnostic limit value; (2) Calculate the Prob value of the patient's serum, Prob = 1 / (1+e -y ), where y is the calculation result obtained by substituting the relative concentration data of each blood marker in the patient's serum into the binary logistic regression equation; (3) When the Prob value of the patient's serum is ≥ the optimal diagnostic cutoff value, it is judged as a malignant nodule; when the Prob value of the patient's serum is < the optimal diagnostic cutoff value, it is judged as a benign nodule; All steps of the method for assisting in diagnosing benign or malignant nodular thyroid disease are implemented by a computer.

2. The method according to claim 1, characterized in that Step (1) was performed using SPSS software.

3. A method for assisting in the diagnosis of benign or malignant nodular thyroid disease using blood markers, characterized in that: The steps include: S1: Calculate the Prob value of the patient's serum according to the following formula; Prob=1 / (1+e -y ), y=-0.2855228-0.2616326×C TSHB -0.0682475×C OMG -1.1625307×C NT5E +0.1484289×C HAO1 +2.2295773×C VMO1 -1.1700533×C LGALS4 +0.9549436×C CRH -0.7024510×C TG +1.3915070×C GAST -1.3661147×C EPHA10 , In the formula, C TSHB , C OMG , C NT5E , C HAO1 , C VMO1 , C LGALS4 , C CRH , C TG , C GAST and C EPHA10 They are the relative concentration data of blood markers TSHB, OMG, NT5E, HAO1, VMO1, LGALS4, CRH, TG, GAST and EPHA10 in the serum of patients; S2: Compare the calculated Prob value of the patient's serum with 0.7229477. When the Prob value of the patient's serum is ≥ 0.7229477, it is judged as a malignant nodule; when the Prob value of the patient's serum is < 0.7229477, it is judged as a benign nodule. All steps of the method for assisting in diagnosing benign or malignant nodular thyroid disease are implemented by a computer.

4. A computer-readable storage medium for assisting in the diagnosis of benign or malignant nodular thyroid disease, characterized in that: A computer program is stored on the computer-readable storage medium, and when the computer program is executed by the processor, the steps of the method as claimed in claim 1, 2 or 3 are implemented.

5. A device for assisting in the diagnosis of benign or malignant nodular thyroid disease, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the steps of the method according to claim 1, 2 or 3 are implemented when the processor executes the computer program.

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