阅读说明：本技术 一种用于卵巢癌早期筛查和诊断的血清蛋白标志物、试剂盒及检测方法 (Serum protein marker, kit and detection method for early screening and diagnosis of ovarian cancer ) 是由 张建营 王晓 史健翔 叶华 王鹏 代丽萍 马言 段亚茹 江秉华 于 2019-10-23 设计创作，主要内容包括：本发明公开一种用于卵巢癌早期筛查和诊断的血清蛋白标志物,属于生物医学技术领域,血清蛋白标志物为NPM1基因编码的蛋白、GNAS基因编码的蛋白、P53基因编码的蛋白、FUBP1基因编码的蛋白或KRAS基因编码的蛋白中的任意一种或两种以上的联合。同时提供包含血清蛋白标志物的试剂盒及使用血清蛋白标志物的检测方法。本发明定制138个癌症驱动基因编码的人类蛋白质芯片,共包含180个人源重组蛋白质,先通过蛋白质芯片初步筛选出卵巢癌的早期检测血清标志物,再经过ELISA实验进行验证,最终筛选出可用于卵巢癌早期筛查和诊断的一组卵巢癌联合检测血清标志物,其包括NPM1、P53、GNAS和KRAS共4种基因编码的蛋白,可辅助卵巢癌的临床诊断,具有较好的参考价值。(The invention discloses a serum protein marker for early screening and diagnosis of ovarian cancer, which belongs to the technical field of biomedicine and is the combination of any one or more than two of protein coded by NPM1 gene, protein coded by GNAS gene, protein coded by P53 gene, protein coded by FUBP1 gene or protein coded by KRAS gene. Also provided are kits comprising serum protein markers and detection methods using serum protein markers. The invention customizes 138 cancer driver gene coded human protein chips, which contain 180 human source recombinant proteins, firstly preliminarily screens out early detection serum markers of ovarian cancer through the protein chips, then verifies through ELISA experiments, and finally screens out a group of ovarian cancer combined detection serum markers for early screening and diagnosis of ovarian cancer, which comprise 4 gene coded proteins of NPM1, P53, GNAS and KRAS, can assist clinical diagnosis of ovarian cancer, and has better reference value.)

1. A serum protein marker for early screening and diagnosis of ovarian cancer, characterized by: the serum protein marker is any one or combination of more than two of protein coded by NPM1 gene, protein coded by GNAS gene, protein coded by P53 gene, protein coded by FUBP1 gene or protein coded by KRAS gene,

the protein coded by the NPM1 gene has an amino acid sequence shown as SEQ ID NO. 1;

the protein coded by the GNAS gene has an amino acid sequence shown as SEQ ID NO. 2;

the protein coded by the P53 gene has an amino acid sequence shown in SEQ ID NO. 3;

the protein coded by the FUBP1 gene has an amino acid sequence shown in SEQ ID NO. 4;

the protein coded by the KRAS gene has an amino acid sequence shown in SEQ ID NO. 5.

2. The serum protein marker for early screening and diagnosis of ovarian cancer of claim 1, wherein: the NPM1 gene has a nucleotide sequence shown as SEQ ID NO.6, the GNAS gene has a nucleotide sequence shown as SEQ ID NO.7, the P53 gene has a nucleotide sequence shown as SEQ ID NO.8, the FUBP1 gene has a nucleotide sequence shown as SEQ ID NO.9, and the KRAS gene has a nucleotide sequence shown as SEQ ID NO. 10.

3. The serum protein marker for early screening and diagnosis of ovarian cancer according to claim 2, wherein: the serum protein marker is the combination of the protein coded by the NPM1 gene, the protein coded by the GNAS gene, the protein coded by the P53 gene and the protein coded by the KRAS gene.

4. A kit, characterized in that: which comprises the serum protein marker for early screening and diagnosis of ovarian cancer according to any one of claims 1 to 3, wherein the serum protein marker is coated on a solid phase carrier.

5. The kit of claim 4, wherein: the solid phase carrier is made of polyvinyl chloride, polystyrene, polyacrylamide or cellulose.

6. The kit of claim 4 or 5, wherein: the kit also comprises any one or the combination of more than two of positive control serum, negative control serum, confining liquid, sample diluent, a second antibody, second antibody diluent, washing liquid, developing liquid and stopping liquid.

7. A method of detecting using the serum protein markers for early screening and diagnosis of ovarian cancer as claimed in any one of claims 1 to 3, wherein: the method comprises the following steps:

1) coating and sealing each serum protein marker, and then cleaning;

2) performing primary antibody incubation and cleaning with the diluted serum to be detected, and performing secondary antibody incubation and cleaning;

3) stopping the reaction after the color development of the color development system, and measuring the absorbance value;

4) by OD₄₅₀-OD₆₂₀Taking the relative OD value, deducting a blank control to obtain the absorbance value of each serum protein marker, taking the 95 th percentile of the serum OD value of the normal control group as a cutoff value, defining the patient as the ovarian cancer when the OD value of the autoantibody in the serum of the case group is greater than or equal to the 95 th percentile of the serum OD value of the normal control group, and judging the patient as normal if the OD value is not greater than the 95 th percentile;

and calculating the positive rate, sensitivity specificity, jotan index, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio of each serum protein marker.

8. The assay of claim 7 using serum protein markers for early screening and diagnosis of ovarian cancer, wherein: further comprising the step 5) of parallel joint detection: and (3) constructing a parallel joint detection model of the serum protein marker by using a logistic regression model, and calculating a joint diagnosis result.

Technical Field

The invention belongs to the technical field of biomedicine.

Background

Ovarian Cancer (OC) is one of the common malignancies of female reproductive organs. According to the global epidemiological data (GLOBOCAN 2018) published by the world health organization in 2018, the number of newly-discovered ovarian cancer cases per year is about 295414 and the number of deaths is about 184799 globally. In 2018, about 22530 women in the united states suffered from ovarian cancer, and 13980 women died of ovarian cancer. The statistical data of Chinese cancers in 2015 show that the number of new cases of ovarian cancer in China is about 52100, and the number of deaths is about 22500. Because of the large population base in China, the incidence rate of ovarian cancer in China is not high in incidence proportion, but the incidence number and death number of ovarian cancer are the top of the world in number. The incidence rate of ovarian cancer is lower than that of cervical cancer and uterine body cancer in gynecological tumors, and is third, but the mortality rate of ovarian cancer is first in gynecological tumors. As the ovary is deeply arranged in the pelvic cavity of a human body, the early clinical symptoms and signs of patients with ovarian cancer are not obvious, and effective general investigation and early diagnosis methods are clinically lacked, so that 70-80% of patients have advanced treatment, the treatment effect and prognosis are very poor, and the 5-year survival rate is lower than 20%.

At present, methods for clinically evaluating early ovarian cancer mainly comprise vaginal ultrasound examination and serum CA125 level tests, but most of pelvic lumps discovered by vaginal ultrasound are not tumors, and the increase of the serum CA125 level can also be seen in conventional periods such as female menstrual periods or other benign gynecological diseases, so that the examination or the test cannot achieve the target of early diagnosis of ovarian cancer patients, and the value of early diagnosis of ovarian cancer is not high. In order to realize early discovery, early diagnosis and early treatment of ovarian cancer, reduce the mortality rate and improve the survival rate, a new effective noninvasive early diagnosis method is urgently needed. Based on the defects of the current clinical screening method for ovarian cancer, if an ovarian cancer marker with ideal sensitivity and specificity can be found, and the detection means is low in price and convenient for screening high risk groups, huge social values can be created, medical resources and economic values can be saved, and the survival rate and the survival time of patients can be improved.

In the field of ovarian cancer biomarkers, numerous scholars at home and abroad have conducted a great deal of research and exploration, and some conventional tumor markers commonly used clinically at present, such as cancer antigen 125, human epididymis protein 4 and the like, are used for diagnosing ovarian cancer. In recent years, in the field of human oncology, more and more studies have shown that tumor tissues are often accompanied by abnormal expression of cellular proteins during the development process, and some of these abnormally expressed proteins can enter the circulatory system, be recognized by the body's immune system and produce corresponding autoantibodies, and this class of proteins that are recognized by the body's immune system and produce immune response during the development process of tumor is called Tumor Associated Antigens (TAAs), and the antibodies induced by such proteins are called anti-TAA-antibodies (autoantibody). The proposal of the concept guides a new direction for the early diagnosis research of ovarian cancer, the autoantibodies have higher titer and longer existence time in the serum of a tumor patient, can be detected months or even years before clinical diagnosis is confirmed, but do not exist in the serum of a non-tumor patient and normal human or cannot be detected due to too low content, so the autoantibodies of the anti-tumor related antigens have the potential of being used as tumor immunological markers, and the finding of the TAA autoantibody index with ideal diagnostic value has important significance for the diagnosis of the ovarian cancer. Many studies provide basis and feasibility for the anti-TAAs autoantibodies to early diagnosis of ovarian cancer, but based on the complexity of the tumorigenesis process, the single diagnosis index has relatively poor capability for tumor diagnosis, and generally cannot meet the clinical tumor diagnosis requirement, for example, studies show that the frequency of the single anti-TAAs autoantibody appearing in the serum of an ovarian cancer patient is very low, generally not more than 20%, and the application of the single anti-TAAs autoantibody in tumor diagnosis is limited. Research finds that the combination of a group of anti-TAAs autoantibodies which are carefully screened out is used for diagnosing tumors, the sensitivity of tumor diagnosis can be greatly improved while the specificity of tumor diagnosis is ensured, the research of the combination of multiple anti-TAAs autoantibodies applied to early diagnosis of ovarian cancer supports the theory, and research data shows that the combination of p62, c-Myc, p53 and HCCR 4 anti-TAAs autoantibodies is used for diagnosing ovarian cancer, the sensitivity can reach 72.04 percent while the higher specificity of diagnosis is ensured, and the diagnosis value is far higher than that of a single anti-TAA autoantibody, so that the combination of multiple anti-TAAs autoantibodies for detecting ovarian cancer is a scheme with application potential.

For many years, follow-up studies have attempted to find more sensitive and specific anti-TAA autoantibodies for diagnosing ovarian cancer, optimizing the combination for diagnosing ovarian cancer. There are two common methods for finding valuable TAA autoantibodies: the first is serological screening of recombinant cDNA expression library (serological analysis of recombinant cDNA expression libraries, SEREX); the other is proteomics technology. In contrast to SEREX, proteomics technology enables screening of multiple tumor sera and enables screening of TAAs with post-translational modifications. During the development of tumors, hundreds of thousands of mutations of genes are involved, but only some key genes, called cancer driver genes, are mutated to cause the development of tumors. Studies suggest that different types of tumorigenesis generally contain 2-8 driver genes, and that mutations in these genes lead to preferential tumor growth, and that these genes can be divided into 12 signaling pathways by regulating the cell cycle, cell survival and genome to maintain 3 cell core processes. 138 cancer driver genes (see Vogelstein B. science. (2013)339(6127):1546-1558), including 74 cancer suppressor genes and 64 cancer genes, are currently found in a variety of tumor whole genome sequencing studies. The protein coded based on the cancer driving gene can also induce the body to generate corresponding autoantibodies in circulating blood of the body, and the research on the protein coded by the cancer driving gene and the autoantibodies in serum induced by the protein can reveal the occurrence, development or prognosis of tumors to a certain extent.

Disclosure of Invention

The invention aims to provide a serum protein marker for early screening and diagnosis of ovarian cancer, and also provides a kit containing the serum protein marker and a detection method using the serum protein marker.

Based on the purpose, the invention adopts the following technical scheme:

a serum protein marker for early screening and diagnosis of ovarian cancer is any one or combination of more than two of protein coded by NPM1 gene, protein coded by GNAS gene, protein coded by P53 gene, protein coded by FUBP1 gene or protein coded by KRAS gene,

the protein coded by the NPM1 gene has an amino acid sequence shown as SEQ ID NO. 1;

the protein coded by the GNAS gene has an amino acid sequence shown as SEQ ID NO. 2;

the protein coded by the P53 gene has an amino acid sequence shown in SEQ ID NO. 3;

the protein coded by the FUBP1 gene has an amino acid sequence shown in SEQ ID NO. 4;

the protein coded by the KRAS gene has an amino acid sequence shown in SEQ ID NO. 5.

The NPM1 gene has a nucleotide sequence shown as SEQ ID NO.6, the GNAS gene has a nucleotide sequence shown as SEQ ID NO.7, the P53 gene has a nucleotide sequence shown as SEQ ID NO.8, the FUBP1 gene has a nucleotide sequence shown as SEQ ID NO.9, and the KRAS gene has a nucleotide sequence shown as SEQ ID NO. 10.

The serum protein marker is the combination of the protein coded by the NPM1 gene, the protein coded by the GNAS gene, the protein coded by the P53 gene and the protein coded by the KRAS gene.

A kit comprising a serum protein marker for early screening and diagnosis of ovarian cancer, said serum protein marker being coated on a solid support.

The solid phase carrier is made of polyvinyl chloride, polystyrene, polyacrylamide or cellulose.

The kit also comprises any one or the combination of more than two of positive control serum, negative control serum, confining liquid, sample diluent, a second antibody, second antibody diluent, washing liquid, developing liquid and stopping liquid.

A detection method using serum protein markers for early screening and diagnosis of ovarian cancer, characterized in that: the method comprises the following steps:

1) coating and sealing each serum protein marker, and then cleaning;

2) performing primary antibody incubation and cleaning with the diluted serum to be detected, and performing secondary antibody incubation and cleaning;

3) stopping the reaction after the color development of the color development system, and measuring the absorbance value;

4) by OD₄₅₀-OD₆₂₀And (3) taking the relative OD value, deducting a blank control to obtain the absorbance value of each serum protein marker, taking the 95 th percentile of the serum OD value of the normal control group as a cut-off value, defining the patient as the ovarian cancer when the OD value of the autoantibody in the serum of the case group is greater than or equal to the 95 th percentile of the serum OD value of the normal control group, otherwise, judging the patient as normal, and calculating the positive rate, sensitivity specificity, john index, positive predicted value, negative predicted value, positive likelihood ratio and negative likelihood ratio of each serum protein marker.

Further comprising the step 5) of parallel joint detection: and (3) constructing a parallel joint detection model of the serum protein marker by using a logistic regression model, and calculating a joint diagnosis result.

Compared with the prior art, the invention has the following beneficial effects:

1) the invention customizes 138 cancer driver gene coded human protein chips, which contain 180 human source recombinant proteins in total and are used for screening potential markers which can be used for diagnosing or characterizing cancers, firstly, early detection serum markers of ovarian cancer are preliminarily screened out through the protein chips, then, ELISA experiments are carried out for verification, finally, a group of ovarian cancer serum protein markers which can be used for early screening and diagnosing of ovarian cancer are screened out, in particular to the combination of proteins coded by NPM1, P53, GNAS and KRAS genes, the area under a combined diagnosis ovarian cancer ROC curve reaches 0.686, 95 percent CI is 0.628-0.744, the sensitivity is 51.83 percent, the specificity is 83.54 percent, and the invention can assist clinical diagnosis of ovarian cancer and has better reference value.

2) The detection method has the characteristics of high sensitivity, strong specificity, low cost and the like, is simple and quick to operate, and can provide a basis for early diagnosis of ovarian cancer.

Drawings

FIG. 1 is a schematic diagram of the detection of a focused array-based human protein chip in an experimental example;

FIG. 2 is a schematic diagram of indirect ELISA detection in an experimental example;

FIG. 3 is ROC curve analysis and SNR value scattergram for 5 TAAs individually diagnosed with ovarian cancer screened by the protein chip in the experimental example;

FIG. 4 shows ROC curve analysis and OD scatter plot (training set) of 5 TAAs in experimental cases for single diagnosis of ovarian cancer by ELISA;

FIG. 5 is a ROC plot (validation set) of the data in the validation set for the ELISA validation of 4 TAAs for the combined diagnosis of ovarian cancer in the experimental examples;

FIG. 6 is a ROC plot of the combined diagnosis of ovarian cancer in the validation set of data for 4 TAAs (NPM1, GNAS, P53, KRAS) validated by ELISA in the experimental examples.

Detailed Description

Examples of the experiments

1 preparation of serum samples

1.1 serum samples for protein chip experiments

Primary ovarian cancer patients (ovarian cancer was pathologically diagnosed) were collected at the beijing youan hospital and the first subsidiary hospital of zheng zhou university, with patient consent and approval by the institutional review board and the hospital ethics committee. All samples are collected by a red blood collection tube for 5-10 mL of whole blood of a research object, the whole blood is placed for 2 hours at room temperature, 1000g of the whole blood is centrifuged for 15 minutes, supernatant is taken, each sample is subpackaged with a plurality of labels, the labels are placed in a refrigerator, the samples are stored at low temperature of-80 ℃, and repeated freezing and thawing are avoided.

Based on epidemiological analysis, 17 primary ovarian cancer sera were finally collected from this study, and 27 normal female control sera from the YouAn hospital for a contemporaneous physical examination were subjected to preliminary chip screening. The mean age was 48 ± 18 years in 17 patients with primary ovarian cancer, ranging from 12 to 73 years; the average age in 27 normal sera was 40 + -10 years, ranging from 21-58 years. All ovarian cancer patient sera were collected at the time the patient was initially diagnosed with ovarian cancer and had not received any chemoradiotherapy or surgical treatment, and were diagnosed between 4 months 2015 and 2016 and 5 months 2016. The normal human serum is from the physical examination population participating in the annual health physical examination and free of any malignant tumor symptoms.

1.2 serum samples for ELISA Experimental validation

(1) Serum samples were collected from the Beijing Youran Hospital and the first subsidiary Hospital of Zhengzhou university (see section 1.1 above for details).

(2) From the first subsidiary hospital of Zhengzhou university and the tumor hospital of Henan province (234 new cases of ovarian cancer, case group) and the cardiovascular survey program of Jinshui district of Zhengzhou city (234 normal persons, normal control group), the average age was 53 ± 12 years old and the age range was 15-77 years old among 234 new cases of ovarian cancer; and 234 cases of normal serum, the average age was 52 + -14 years, and the age range was 13-82 years. All ovarian cancer patient sera were collected at a time when the patient was initially diagnosed with ovarian cancer and had not received any chemoradiotherapy, and were diagnosed between 4 months 2015 and 5 months 2016. The normal human serum is from the physical examination population participating in the annual health physical examination and free of any malignant tumor symptoms.

2 protein chip customization for screening ovarian cancer diagnostic markers

138 cancer driver genes (see Vogelstein B. science. (2013)339(6127):1546-1558) encoded proteins (total 180 human recombinant proteins) Fixed on a protein chip and used for screening tumor markers. The protein chip for screening tumor markers is HuProt customized by Guangzhou Bo Chong Biotechnology Co., Ltd^TMHuman protein chips.

3. Protein chip assay

See figure 1 for experimental principles.

3.1 reagents required for the experiment

1) Sealing liquid: 3mL of 10% BSA, 7mL of 1 XPBS solution, mixed well and placed on ice.

2) Serum incubation liquid: 1mL of 10% BSA was added to 9mL of 1 XPBST solution, mixed well and placed on ice.

3) Cleaning solution: 1 XPBST solution, stored in a refrigerator at 4 ℃.

4) Secondary antibody incubation solution: including a fluorescently-labeled anti-human IgM secondary antibody (cy 5-labeled, appearing red) and a fluorescently-labeled anti-human IgG secondary antibody (cy 3-labeled, appearing green).

3.2 specific Experimental procedures for protein chips

(a) Rewarming: taking out the chip from a refrigerator at-80 deg.C, re-heating in a refrigerator at 4 deg.C for half an hour, and re-heating at room temperature for 15 min.

(b) And (3) sealing: and fixing the rewarming chip in 14blocks in a fence, adding sealing liquid into each block, placing the blocks on a side swing shaking bed, and sealing for 3 hours at room temperature.

(c) Incubation of serum samples: after the blocking was completed, the blocking solution was poured out, then the prepared serum incubation solution was added quickly, 14 samples were incubated per chip (the serum samples were first frozen and thawed in a 4 ℃ chromatography cabinet and diluted 1: 50 by volume with 1 XPBST solution containing 1% BSA), the loading volume of each serum sample was 200. mu.L, the shaking table was set at 20rpm, and the incubation was carried out overnight at 4 ℃.

(d) Cleaning: taking out the chip and the chip clamp together, sucking out the sample, then quickly adding an equal volume of 1 XPBST solution, and circulating for a plurality of times to ensure that no cross contamination exists among the serum samples when the chip clamp is detached. After the chip clamp was removed, the chip was placed in a chip washing cassette containing washing solution, and washed on a horizontal shaker at room temperature at 80rpm for 3 times, each time for 10 min.

(e) And (3) secondary antibody incubation: the chip was transferred to an incubation box containing 3mL of secondary antibody incubation solution, and the shaking table was shaken laterally at 40rpm, protected from light, and left at room temperature for 60 min.

(f) Cleaning: the chip was removed (note that the upper surface of the chip was not touched or scratched), placed in a chip washing cassette with added washing solution, placed on a horizontal shaker, and washed 3 times at 80rpm for 10min each time. After completion with ddH₂O washing for 10min 2 times.

(g) And (3) drying: the chip was placed in a chip drier for centrifugal drying.

(h) Scanning: operating according to the operating specifications and instructions of the scanner.

(i) Data extraction: and aligning the chip image and each array of the result as a whole, pressing an automatic alignment button, and extracting and storing data.

(j) And carrying out data preprocessing.

(k) And (3) carrying out data analysis to obtain a final ovarian cancer serum marker, and screening the following serum protein markers by the protein chip experiment: the cancer driver genes NPM1, GNAS, P53, FUBP1 and KRAS-encoded proteins (fig. 3 is ROC curve analysis and SNR value scatter plot of single ovarian cancer diagnosis of 5 TAAs selected from the above protein chips, i.e., NPM1, GNAS, P53, FUBP1 and KRAS-encoded proteins). The protein coded by the NPM1, GNAS, P53, FUBP1 and KRAS genes sequentially has an amino acid sequence shown as SEQ ID No. 1-5, and the NPM1, GNAS, P53, FUBP1 and KRAS genes sequentially has a nucleotide sequence shown as SEQ ID No. 6-10.

4 ELISA Indirect method experimental verification

See figure 2 for experimental principles.

The specific experimental steps are as follows:

a) coating: coating according to the concentration in Table 1, 100. mu.L/well, 4 ℃ overnight;

b) and (3) sealing: 2% BSA (Solebao, Beijing, analytical pure) in 1 XPBST solution (PBS, Tween20 Solebao, Beijing), 200. mu.L/well, overnight at 4 ℃;

c) cleaning: washing with 350 μ L/well 1 XPBST solution for 3 times;

d) primary antibody incubation: diluting serum and 1 XPBST solution containing 1% BSA at a volume ratio of 1:100, 100 mu L/hole, and carrying out half water bath at 37 ℃ for 1 h;

e) cleaning: washing 5 times with 350 uL/hole 1 XPBST solution;

f) and (3) secondary antibody incubation: HRP-labeled mouse anti-human IgG (Olympic, Wuhan) and 1 XPBST solution containing 1% BSA at a volume ratio of 1:10000 are diluted, 100 mu L/hole are put in a half water bath at 37 ℃ for 1 h;

g) cleaning: washing 5 times with 350 uL/hole 1 XPBST solution;

h) color development: TMB color development System, solution A (200 mgTMB.2HCl in 1L deionized water, Solebao, Beijing, analytical grade) and solution B (9.2g citric acid, 37g Na)₂HPO₄12H2O and 8ml of 0.75% H₂O₂Dissolving in 1L deionized water) at a volume ratio of 1:1, mixing, and keeping at room temperature in dark place for 5-15min until the desired color is obtained;

i) and (4) terminating: absorbance was measured within 10min after 50. mu.L/well of 10% concentrated sulfuric acid.

j) Measuring the absorbance: OD450-OD620 are taken as relative OD values, blank control is deducted, IgG is adjusted for normalization, and then subsequent data processing is carried out (the data processing method is shown in the following data processing part b-d of '5').

The coating concentrations of the 5 TAAs screened by the protein chip experiment when the ELISA experiment is performed are shown in table 1 below, and the arrangement table of the 96-well plate of the ELISA experiment is shown in table 2 below. In table 2, the positive quality control refers to serum with a higher OD value of the ELISA experiment and positive corresponding antibody through Western Blot experiment verification, the negative quality control refers to serum with an OD value near the mean value of the ELISA experiment in normal control population and negative through Western Blot verification, the blank is serum diluent, IgG 1-IgG 8 are human IgG antibodies diluted in a gradient manner, and the concentrations are 10, 20, 50, 100, 150, 200, 250 and 300ng/ml in sequence.

TABLE 15 coating concentrations of each of the TAAs

Table 2 96-well plate arrangement for ELISA experiments

The experimental results are as follows: the results of 5 TAAs tested by ELISA were shown in FIGS. 4 and 5. FIGS. 4 and 5 are ROC curve analysis graphs and corresponding OD scatter plots of 5 TAAs, NPM1, GNAS, P53, FUBP1 and KRAS, for diagnosis of ovarian cancer alone in ELISA validation experiments. As can be seen in FIG. 4, the area under the ROC curve for diagnosing ovarian cancer by a single index is 0.53-0.71, wherein the area under the curve for P53 is the largest and is 0.708; the area under the ROC curve of KRAS is 0.694; the area under the ROC curve for FUBP1 was the smallest and 0.533. As can be seen from FIG. 4, the OD values of the 5 indexes are distributed between 0 and 1, and the OD values of the median are basically distributed between 0.2 and 0.4.

5 data processing

The differential expression protein is screened out by using the focused array human protein chip in an ovarian cancer group and an NC normal control group through statistical data analysis, and the specific method is as follows:

(1) the initial screening result of the chip is obtained through Focused Array protein chip experiment.

(2) And (3) stability analysis: in the experimental process, the test samples test are repeated according to different time, different chips and different positions so as to evaluate the stability of different chips at different time.

(3) Data analysis and results: samples after high background and extreme sample interference were removed, and 180 proteins of the IgG response type were subjected to consistent statistical analysis with the following analysis logic:

a) in order to eliminate the situation of signal nonuniformity caused by inconsistent background values among different protein points in the same chip, the background normalization method is used for processing, the ratio of the foreground value to the background value of each protein, namely F/B, is realized, SNR (signal to noise ratio), namely the mean value of the F/B of two repeated proteins, is defined on the basis, and subsequent statistical analysis is carried out.

b) AUC > 0.5 was defined for all proteins under the ROC curve (Area under the ROC, AUC) and the corresponding P values for ovarian cancer versus control, with P <0.05 being the lowest screening criterion.

c) Based on the above logic, the ovarian cancer group (17 primary ovarian cancer patient sera collected from the first subsidiary hospital of the Beijing Youran Hospital and Zheng State university) and the Youran control group (27 normal sera of Youran Hospital) were compared, differential proteins significantly higher than the control group in the ovarian cancer group were selected as ovarian cancer candidate markers, and finally 5 serum protein markers (NPM1, GNAS, P53, FUBP1 and KRAS) were selected by the chip to evaluate the diagnostic value of ovarian cancer. Wherein, the protein coded by the NPM1 gene has an amino acid sequence shown as SEQ ID NO.1, the protein coded by the GNAS gene has an amino acid sequence shown as SEQ ID NO.2, the protein coded by the P53 gene has an amino acid sequence shown as SEQ ID NO.3, the protein coded by the FUBP1 gene has an amino acid sequence shown as SEQ ID NO.4, and the protein coded by the KRAS gene has an amino acid sequence shown as SEQ ID NO. 5.

The NPM1 gene has a nucleotide sequence shown as SEQ ID NO.6, the GNAS gene has a nucleotide sequence shown as SEQ ID NO.7, the P53 gene has a nucleotide sequence shown as SEQ ID NO.8, the FUBP1 gene has a nucleotide sequence shown as SEQ ID NO.9, and the KRAS gene has a nucleotide sequence shown as SEQ ID NO. 10. The information sources of the above 5 genes are shown in Table 3 below.

Information sources of Table 35 genes

Name of Gene	Uniprot database accession number	NCBI reference sequence accession number
			KRAS	Q15046	NM_004985
NPM1	P06748-2	NM_199185
			GNAS	Q5JWF2	NM_080425
TP53	P04637	NM_000546
			FUBP1	Q96AE4	NM_003902

(4) The ELISA experiment verification is carried out on the 5 serum protein markers screened by the protein chip: the method comprises the steps of verifying the samples of the submission chip and verifying the samples collected outside the submission chip again, thereby realizing the verification of the protein chip and ensuring the popularization.

(5) The experimental results are as follows: ELISA experiment verification is carried out on 5 serum protein markers screened by the protein chip, and 468 research objects are further randomly divided into a training group and a verification group by using a random sampling method for all verification people. The training set is a small sample and is used for verifying the screening result of the company chip, the verification set is a large sample, and further screening verification is carried out according to the analysis result of the training set.

The grouping method comprises the following steps: editing ID numbers of 234 ovarian cancer patients according to 1-234, correspondingly generating a random number between 0 and 1 by using a random function RAND () command in EXCEL, arranging the random numbers in the order from small to large, taking the first 70 sequentially corresponding IDs as a training group, and taking the rest as a verification group. Similarly, the above-described process was performed for 234 normal controls. Finally, 70 cases of ovarian cancer and 70 cases of normal control in the training group are obtained, the total number is 140 cases, 164 cases of ovarian cancer and 164 cases of normal control in the verification group are obtained, and the total number is 328. And taking the 95 th percentile of the normal control group serum OD value as a cutoff value, defining the patient as the ovarian cancer when the OD value of the autoantibody in the case group serum is greater than or equal to the 95 th percentile of the normal control group serum OD value, and judging the patient as normal if the patient is not, thereby calculating indexes such as the positive rate, sensitivity, specificity, john's index, positive predicted value, negative predicted value, positive likelihood ratio, negative likelihood ratio and the like of each TAAs autoantibody.

Parallel joint detection: the parallel joint detection model is constructed by using a logistic regression model, the index with the highest sensitivity is taken as a starting point, the sensitivity can be improved to the maximum extent and higher specificity can be kept after every addition of one index, and the number of the parallel antibodies takes the highest detectable sensitivity as an end point.

For the analysis of the diagnostic value and the economic benefit of the model constructed above, the model containing 4 indexes (NPM1, GNAS, P53 and KRAS) has the best effect, as shown in FIG. 6 and Table 3, the area under the ROC curve of the combined diagnosis ovarian cancer reaches 0.686, 95% CI is 0.628-0.744, the sensitivity is 51.83%, and the specificity is 83.54%.