Biomarker for epithelial ovarian cancer and application thereof

Abstract

The invention discloses a biomarker for epithelial ovarian cancer and application of the biomarker. The marker comprises a basal cell adhesion molecule, mesothelin and a folic acid receptor alpha, or coding nucleic acid of the basal cell adhesion molecule, coding nucleic acid of mesothelin and coding nucleic acid of the folic acid receptor alpha, and the coding nucleic acid comprises mRNA or cDNA. The EOC CTC RNA diagnosis model is constructed by taking the biomarker as a feature, the sensitivity and the specificity can reach 88% and 83% respectively, the disease progress of a patient can be dynamically monitored, and the recurrence condition of the patient can be found earlier than that of imaging and existing serum indexes.

Description

Technical Field

[0001] The present invention belongs to the technical field of molecular biology, and relates to a biomarker for epithelial ovarian cancer and an application thereof, and in particular to a diagnostic biomarker for epithelial ovarian cancer based on a circulating tumor cell mRNA combination. Background Art

[0002] Among the various pathological types of ovarian cancer, epithelial ovarian cancer (EOC) is the most common, accounting for about 80% of ovarian malignant tumors. Due to the lack of typical clinical manifestations of ovarian cancer in the early stages and the lack of effective screening methods in clinical practice, although ovarian cancer patients initially respond well to comprehensive treatments such as surgery combined with chemotherapy, most patients will still develop drug resistance, metastasis and recurrence. Therefore, timely diagnosis of ovarian cancer is of great significance for improving the prognosis of ovarian cancer patients and improving their quality of life.

[0003] Current research data based on the general population show that serum carbohydrate antigen (CA) 125 detection, transvaginal ultrasound (TVUS) or combined screening of the two cannot achieve satisfactory screening results. Although CA125 is currently the most widely used biomarker in the diagnosis and monitoring of ovarian cancer, it can indicate the progression or regression of the tumor. However, studies have shown that CA125 is only elevated in 50% of patients with early ovarian cancer (>35U / mL), and 1% of healthy women, 3% of patients with benign ovarian tumors, and 6% of patients with benign diseases outside the ovary also have elevated CA125 levels in their serum. It can be seen that the sensitivity and specificity of CA125 are not high enough, and there is heterogeneity in the expression levels of different ovarian cancer types. Therefore, it is urgent to develop a highly sensitive, highly specific, and more stable cancer detection method in order to achieve timely diagnosis, efficacy evaluation, and recurrence monitoring of ovarian cancer.

[0004] Circulating tumor cells (CTCs) refer to tumor cells that originate from primary or metastatic tumors and fall off into the peripheral blood circulation. Because they carry important information about primary or metastatic lesions and can spread to other tissues and organs throughout the body through the blood circulation, CTCs are considered to be a promising non-invasive cancer diagnostic marker. By purifying CTCs in peripheral blood samples and analyzing the characteristic molecules therein, such as proteins, mRNA, lncRNA, etc., it is expected to achieve non-invasive, continuous, and real-time dynamic monitoring, which provides a new direction for the timely diagnosis and disease monitoring of ovarian cancer. For example, CN108085392A discloses biomarkers and uses of epithelial ovarian cancer, and the markers include hsa-miR-34b, hsa-miR-335, hsa-miR-136, hsa-let-7e, hsa-miR-1297, hsa-miR-374b, and hsa-miR-891b.

[0005] In summary, developing new biomarkers and corresponding detection methods for epithelial ovarian cancer and expanding the technical means for diagnosis, efficacy evaluation and recurrence monitoring of epithelial ovarian cancer are of great significance for the treatment of epithelial ovarian cancer. Summary of the invention

[0006] In view of the deficiencies of the prior art and actual needs, the present invention provides a biomarker for epithelial ovarian cancer and its application, providing new methods and new ideas for the diagnosis, efficacy evaluation and disease monitoring of ovarian cancer.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a biomarker for epithelial ovarian cancer, wherein the marker includes basal cell adhesion molecule (BCAM), mesothelin (MSLN) and folate receptor alpha (FOLR1), or, a nucleic acid encoding a basal cell adhesion molecule, a nucleic acid encoding a mesothelin and a nucleic acid encoding a folate receptor alpha; the encoding nucleic acid includes mRNA or cDNA.

[0009] The present invention discovered for the first time that basal cell adhesion molecule, mesothelin and folate receptor α and their encoding nucleic acids in epithelial ovarian blood circulating tumor cells are related to the development and prognosis of epithelial ovarian cancer. They are overexpressed in patients with epithelial ovarian cancer, but lowly expressed or not expressed in normal ovarian tissue and benign ovarian tumor tissue, and can be effectively used in the diagnosis and progression monitoring of epithelial ovary.

[0010] In a second aspect, the present invention provides use of the biomarker for epithelial ovarian cancer or a detection reagent thereof as described in the first aspect in the preparation of a product for detecting epithelial ovarian cancer.

[0011] In a third aspect, the present invention provides a kit for detecting epithelial ovarian cancer, wherein the kit comprises a reagent for detecting the presence or level of the biomarker for epithelial ovarian cancer described in the first aspect.

[0012] In a fourth aspect, the present invention provides use of the biomarker for epithelial ovarian cancer or a detection reagent thereof as described in the first aspect in constructing a diagnostic model or device for epithelial ovarian cancer.

[0013] In a fifth aspect, the present invention provides a method for constructing a diagnostic model for epithelial ovarian cancer, the method comprising: based on the expression levels of the biomarkers for epithelial ovarian cancer described in the first aspect, establishing a diagnostic model using multivariate logistic regression.

[0014] In a sixth aspect, the present invention provides a diagnostic model for epithelial ovarian cancer, wherein the input variables of the diagnostic model include the expression level of the biomarker for epithelial ovarian cancer of the subject according to the first aspect, and the output variable of the diagnostic model is the score EOC CTC Score of the subject, and the calculation formula of the EOC CTC Score is:

[0015] EOC CTC Score=-3.904+0.482×A1+0.314×A2+1.7×A3.

[0016] Among them, A1 represents the expression level of basal cell adhesion molecule or its encoding nucleic acid, preferably the expression level of basal cell adhesion molecule mRNA; A12 represents the expression level of mesothelin or its encoding nucleic acid, preferably the expression level of mesothelin mRNA; A3 represents the expression level of folate receptor α or its encoding nucleic acid, preferably the expression level of folate receptor α mRNA.

[0017] The criteria for positive epithelial ovarian cancer are: EOC CTC Score>-1.64.

[0018] In a seventh aspect, the present invention provides a diagnostic device for epithelial ovarian cancer, the diagnostic device comprising an information acquisition module, a calculation module and a diagnostic module.

[0019] The information acquisition module is used to perform the following steps:

[0020] The operation of obtaining test information of the subject, wherein the test information includes the expression level information of the biomarker of epithelial ovarian cancer described in the first aspect.

[0021] The computing module is used to perform the following steps:

[0022] Substituting the expression level information of the biomarker into the diagnostic model of epithelial ovarian cancer described in the sixth aspect to calculate the EOC CTC Score value;

[0023] The diagnostic module is used to perform the following steps:

[0024] The operation of judging the health status of the subject according to the EOC CTC Score value, the judgment standard for positive epithelial ovarian cancer is: EOC CTC Score>-1.64.

[0025] Preferably, the method for obtaining the expression level information of the biomarker comprises:

[0026] Ovarian cancer circulating tumor cells are isolated from a biological sample of a subject.

[0027] Ovarian cancer circulating tumor cells were lysed and RNA was extracted, which was then reverse transcribed into cDNA.

[0028] Droplet digital PCR was used to quantitatively detect the cDNA concentration and calculate the expression level of the mRNA corresponding to the cDNA.

[0029] Preferably, the method for isolating circulating tumor cells of ovarian cancer comprises: separating peripheral blood mononuclear cells from the subject's peripheral blood by centrifugation, mixing the peripheral blood mononuclear cells with antibodies and immunomagnetic beads, and collecting the immunomagnetic beads.

[0030] Preferably, the antibodies include antibodies against epithelial adhesion molecule (EpCAM), antibodies against N-cadherin (N-cadherin), and antibodies against mesothelin (MSLN).

[0031] Preferably, the immunomagnetic beads include a silica shell, on which an anti-adhesion layer and streptavidin are sequentially modified, and the anti-adhesion layer is composed of polycarboxybetaine methacrylate (pCBMA), which can reduce nonspecific adhesion of peripheral blood mononuclear cells and the like to improve the capture efficiency of CTCs.

[0032] Preferably, the biological sample comprises peripheral blood.

[0033] In the present invention, in terms of sample source, biological information of EOC cancer foci can be effectively obtained for diagnosis by capturing CTCs in peripheral blood, and the tumor status can be dynamically monitored non-destructively.

[0034] In the present invention, EpCAM, N-cadherin and MSLN antibodies are used to target ovarian cancer-specific CTCs, and modified immunomagnetic beads are used to specifically capture EOC-derived CTCs in peripheral blood, wherein the immunomagnetic beads include a silica shell, an anti-adhesion layer and streptavidin, and the anti-adhesion layer is composed of polycarboxybetaine methacrylate (pCBMA), which can reduce nonspecific adhesion of peripheral blood mononuclear cells, etc., so as to improve the capture efficiency of CTCs. The antibody can be mixed with the circulating tumor cell sample first and then with the immunomagnetic beads, or can be mixed with the immunomagnetic beads first and then with the circulating tumor cell sample.

[0035] In the present invention, the diagnostic model and device can be used to assist in the diagnosis of ovarian cancer and the detection of disease progression or recurrence.

[0036] In an eighth aspect, the present invention provides use of the biomarker for epithelial ovarian cancer described in the first aspect in diagnosing and evaluating drugs for treating epithelial ovarian cancer.

[0037] Preferably, the biomarkers for epithelial ovarian cancer are used for the detection of ovarian cancer, as well as for diagnosing disease progression based on changes in biomarkers before, during and after treatment, thereby determining the effectiveness of patient treatment and timely subsequent drug intervention.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] The present invention discovered for the first time that basal cell adhesion molecules, mesothelin and folate receptor α and their encoding nucleic acids are related to the occurrence and development of epithelial ovarian cancer, detected their mRNA levels, and established an EOC CTC RNA diagnostic model using multifactor logistic regression. The diagnostic performance is better than the commonly used serum tumor marker CA125 in clinical practice, with a sensitivity and specificity of 88% and 83%, respectively, indicating that the diagnostic model has excellent diagnostic capabilities for EOC. In addition, the EOC CTCRNA diagnostic model established by the present invention shows excellent potential in the dynamic monitoring of EOC patients. The trend of CTC RNA test results in patients with no tumor progression is relatively consistent with the clinical change trend of imaging examinations and serological examinations; for patients with progressive disease, CTC RNA detection can reflect disease progression more promptly and detect early warning signs of tumor recurrence earlier. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Schematic diagram of the process for establishing a diagnostic model;

[0041] Figure 2 This is a flow chart for screening characteristic mRNA genes for EOC;

[0042] Figure 3A This is the heat map of EOC characteristic mRNA gene expression in peripheral blood PBMCs of patients with benign ovarian tumors;

[0043] Figure 3B The heat map of EOC characteristic mRNA gene expression in peripheral blood CTCs of EOC patients before and after treatment;

[0044] Figure 4 The ROC curve of a single target gene in distinguishing EOC patients from patients with benign ovarian tumors;

[0045] Figure 5 The EOC CTC Score for patients with benign ovarian tumors, EOC untreated patients, and patients undergoing EOC treatment;

[0046] Figure 6 ROC curves for distinguishing EOC from benign ovarian tumors using EOC CTC Score and CA125 (Cut off = 35 U / mL);

[0047] Figure 7 Schematic diagram of continuous sampling time and sample processing for dynamic monitoring of the efficacy of EOC patients;

[0048] Figure 8 The EOC CTC Score and clinical blood tumor indicators of the four EOC patients dynamically monitored in Example 2 of the present invention before tumor cell reduction surgery and chemotherapy;

[0049] Fig. 9A This is the preoperative MRI image of the EOC-26 patient;

[0050] Fig. 9B This is the PET-CT image of EOC-26 patient 366 days after surgery. DETAILED DESCRIPTION

[0051] To further illustrate the technical means and effects of the present invention, the present invention is further described below in conjunction with the embodiments and drawings. It should be understood that the specific implementation methods described herein are only used to explain the present invention, rather than to limit the present invention.

[0052] If no specific techniques or conditions are specified in the examples, the techniques or conditions described in the literature in the field or the product instructions are used. If no manufacturer is specified for the reagents or instruments used, they are all conventional products that can be purchased through regular channels.

[0053] In a specific embodiment of the present invention, Figure 1 As shown, CTCs in the peripheral blood of subjects were captured based on multi-antibody (EpCAM / MSLN / N-cadherin) modified magnetic beads to capture EOC-derived CTCs in the peripheral blood, and the expression levels of characteristic mRNAs in CTCs were detected by droplet digital PCR (ddPCR) technology to determine whether the subjects had EOC, and the progression and recurrence of the patients were diagnosed by CTC mRNA follow-up detection, and the EOCCTC RNA diagnostic model established by multivariate logistic regression was used to score the test results of the subjects' CTC mRNA.

[0054] Example 1

[0055] In this example, an EOC diagnostic model based on CTCs characteristic mRNA was constructed and evaluated.

[0056] A total of 47 subjects were recruited, including patients with benign ovarian tumors, ovarian cancer and fallopian tube cancer. All the subjects were included in the study from January to December 2022, including 15 cases of stage I-IV ovarian cancer, 2 cases of fallopian tube cancer and 30 cases of benign ovarian tumors. A total of 77 peripheral blood samples were collected.

[0057] The inclusion criteria for the study subjects are as follows: 1) Those who have not received anti-tumor treatment such as surgery, radiotherapy, chemotherapy, etc. at the time of initial diagnosis; 2) Those who understand and agree to participate in this study and have signed the informed consent form; 3) Those who have no blood system diseases. The exclusion criteria for the study subjects and blood samples are as follows: 1) Patients with a history of other malignant tumors; 2) Patients with severe infection or heart, lung, or kidney dysfunction; 3) Those who have insufficient blood volume, coagulation, or hemolysis after the blood sample collection. This study has been approved by the Ethics Review Committee of the Second Affiliated Hospital of Soochow University (approval number #JD-LK-2022-079-01), and all subjects have informed consent to this study.

[0058] Step 1: Screening of characteristic mRNA genes of EOC:

[0059] First, using the GSE4122 chip data from the Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx), and the Gene Expression Omnibus (GEO), the differentially expressed genes that were overexpressed in EOC tissues but lowly expressed or not expressed in normal ovarian tissues and benign ovarian tumor tissues were screened as candidate genes using the limma package in R. The screening criteria were set as |logFC|≥2 and P<0.001. Subsequently, the candidate genes were screened again using the immune cell subset of the Human Protein Atlas (HPA) to exclude genes that were highly expressed in immune cells. Finally, 9 target gene mRNAs that were specifically highly expressed in EOC were screened, namely BCAM (basal cell adhesion molecule), KLK10 (kallikrein-related peptidase 10), MSLN (mesothelin), LYPD1 (LY6 / PLAUR domain-containing 1), MUC16 (mucin 16), SCGB2A1 (secretory globin family 2A member 1), WFDC2 (human WAP tetradisulfide core domain protein 2), KLK7 (kallikrein-related peptidase 7), and FOLR1 (folate receptor α) ( Figure 2 ).

[0060] Step 2: Isolation of CTCs and RNA extraction from clinical patient blood samples:

[0061] 5 mL of peripheral venous blood was collected from all subjects in EDTA vacuum anticoagulation blood collection tubes. After the collection was completed, the tubes were turned upside down 5 times, transported at 4°C, and processed and used within 24 hours. To avoid epithelial cell contamination, all blood specimens were peripheral blood other than the first tube. The blood collection tubes were placed in a room temperature horizontal centrifuge and centrifuged at 300 g for 15 minutes to obtain plasma and the lower layer of blood cell sediment; after absorbing the upper layer of plasma, 1× PBS solution was added to the blood cell sediment to dilute it to 10 mL (i.e., twice the initial peripheral blood volume), and blown evenly; SepMate TM Peripheral blood mononuclear cell layer (PBMCs) was separated by centrifugation tube, and after washing, 500 μL (i.e., 0.1 times of the initial peripheral blood volume) of 1×PBS solution was added to resuspend PBMCs; the PBMCs cell suspension corresponding to 2 mL of whole blood was incubated with 0.1 mg of multi-antibody (EpCAM / MSLN / N-cadherin, antibody purchase source information is shown in Table 1) modified magnetic beads at 25°C for 30 min to capture ovarian cancer CTCs; after washing the CTC sample, 700 μL of QIAzol lysis buffer was added and the cells were lysed using Direct-zol TM RNA was extracted using an RNA Microprep Kit (ZYMO RESEARCH) and reverse transcribed into a cDNA template using a reverse transcription kit (Takara), and then stored at -20°C for future use.

[0062] Table 1

[0063]

[0064] Step 3: Quantify the characteristic mRNA genes of CTCs using ddPCR:

[0065] According to the target gene mRNA coding gene sequence screened in step 1, target gene primers and probes (Thermo Fisher) were ordered; the target gene mRNA molecules in the sample were detected by the QX200AutoDG droplet digital PCR (ddPCR) system to obtain the mRNA expression level of the EOC CTCs target gene captured in each 2mL peripheral blood sample. The volume of the ddPCR detection system is 20μL, which consists of CTCs target gene cDNA template, ddPCR probe premix (without dUTP), sterile enzyme-free water, target gene primers and probes. After PCR amplification of the target gene cDNA template, the cDNA concentration (transcripts / μL) corresponding to the target gene mRNAs in the sample was quantitatively detected by a droplet reader (QX200 Droplet Reader), and the mRNA expression level of the EOC CTCs target gene captured in each 2mL peripheral blood sample ( Figure 3A and Figure 3B ).

[0066] Step 4: Construction of ovarian cancer diagnostic model and evaluation of diagnostic efficacy:

[0067] For the preoperative blood samples of EOC patients and benign ovarian tumor patients obtained in step 3, ROC analysis was performed to calculate the area under the curve (AUC) to evaluate the diagnostic efficacy of a single target gene, and the genes with the best diagnostic efficacy were selected as modeling features, namely BCAM, MSLN and FOLR1 ( Figure 4 );

[0068] The EOC CTC RNA diagnostic model was established by multivariate logistic regression analysis. In this example, EOC CTC Score = -3.904 + 0.482 × BCAM + 0.314 × MSLN + 1.7 × FOLR. The EOC CTC Score of each subject's sample was obtained by substituting the expression of the modeling characteristic genes in the sample into the model. Figure 5 ).

[0069] The ROC curve was used to evaluate the diagnostic effect of the EOC CTC RNA diagnostic model. The results showed that the sensitivity and specificity of the model were 88% and 83% respectively under the optimal condition, the diagnostic accuracy was 85%, and the AUC reached 0.96 ( Figure 5 ). In order to compare the diagnostic ability of the EOC CTC RNA diagnostic model with the traditional ovarian cancer marker CA125, at a cutoff value of 35 U / mL, the sensitivity and specificity of CA125 were 94% and 57%, respectively, the diagnostic accuracy was 70%, and the AUC was 0.75 ( Figure 6 ). It can be seen that the EOC CTC RNA diagnostic model established by the present invention has better diagnostic performance for EOC than the clinically commonly used serum tumor marker CA125.

[0070] Example 2

[0071] This example evaluates the dynamic monitoring performance of the EOC CTC RNA diagnostic model.

[0072] This study tracked and evaluated the treatment of 4 EOC patients during tumor reduction surgery and each chemotherapy cycle. Blood samples were collected from patients before surgery and before the start of chemotherapy for continuous evaluation. The EOCCTC Score ( Figure 7 ).

[0073] After tumor resection and postoperative chemotherapy, the EOC CTCScore of two patients (EOC-74 and EOC-88) showed a gradual downward trend during treatment. The dynamic change trend of the EOC CTC Score of these two patients is consistent with the change trend of the commonly used serum tumor indicators CA125, HE4 and ROMA index in clinical practice ( Figure 8 ). The EOC CTC Score of EOC-36 patients continued to decrease after the initial surgery, but increased significantly on the 179th day after surgery. This dynamic change suggests that the condition may be abnormal. The EOC CTC Score of EOC-26 patients continued to increase from the 114th day after surgery, while the serum CA125 level indicated abnormality on the 341st day after surgery ( Figure 8 ), and finally the patient was diagnosed with multiple recurrent ovarian cancer lesions on the 366th day after surgery ( Fig. 9A and Fig. 9B ). In the dynamic monitoring of the latter two patients, EOC CTC Score detected disease progression earlier than traditional serum tumor biomarkers, indicating that EOC CTC Score can reflect changes in the disease status of cancer patients more timely, providing an opportunity to carry out relevant treatment measures as early as possible. The above results show that EOC CTC Score may become a potential auxiliary tool for monitoring the treatment response of EOC patients.

[0074] In summary, based on the EOC CTC RNA diagnostic model of the present invention, EOC can be accurately diagnosed from benign controls, and the diagnostic model has a better diagnostic effect on EOC than the clinical serum tumor marker CA125, and the area under the curve (AUC) of the receiver operating characteristic curve (ROC) is 0.96, which is significantly higher than 0.75 of CA125, and the difference between the two is statistically significant (P<0.0001), and the diagnostic specificity and accuracy are both higher than CA125; in terms of dynamic monitoring, the EOC CTC RNA diagnostic model can reflect the disease progression earlier and detect the recurrence of patients more timely compared with imaging and the existing serum detection indicator CA125.

[0075] The applicant declares that the present invention illustrates the detailed method of the present invention through the above-mentioned embodiments, but the present invention is not limited to the above-mentioned detailed method, that is, it does not mean that the present invention must rely on the above-mentioned detailed method to be implemented. Those skilled in the art should understand that any improvement of the present invention, equivalent replacement of various raw materials of the product of the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

Claims

1. A biomarker for epithelial ovarian cancer, characterized in that: The markers include basal cell adhesion molecule, mesothelin and folate receptor α, or nucleic acids encoding basal cell adhesion molecule, mesothelin and folate receptor α; The encoding nucleic acid includes mRNA or cDNA.

2. Use of the biomarker for epithelial ovarian cancer or a detection reagent thereof according to claim 1 in the preparation of a product for detecting epithelial ovarian cancer.

3. A kit for detecting epithelial ovarian cancer, characterized in that: The kit comprises a reagent for detecting the presence or level of the biomarker for epithelial ovarian cancer according to claim 1.

4. Use of the biomarker for epithelial ovarian cancer or a detection reagent thereof according to claim 1 in constructing a diagnostic model or device for epithelial ovarian cancer.

5. A diagnostic model for epithelial ovarian cancer, characterized in that: The input variables of the diagnostic model include the expression level of the biomarker for epithelial ovarian cancer of claim 1 of the subject; The output variable of the diagnostic model is the subject's score EOC CTC Score, and the calculation formula of the EOC CTC Score is: EOC CTC Score=-3.904+0.482×A1+0.314×A2+1.7×A3; Wherein, A1 represents the expression level of basal cell adhesion molecule or its encoding nucleic acid, A12 represents the expression level of mesothelin or its encoding nucleic acid, and A3 represents the expression level of folate receptor α or its encoding nucleic acid; The criteria for positive epithelial ovarian cancer are: EOC CTC Score>-1.

64.

6. A diagnostic device for epithelial ovarian cancer, characterized in that: The diagnostic device includes an information acquisition module, a calculation module and a diagnostic module; The information acquisition module is used to perform the following steps: An operation of obtaining test information of a subject, wherein the test information includes the expression level information of the biomarker for epithelial ovarian cancer according to claim 1; The computing module is used to perform the following steps: Substituting the expression level information of the biomarker into the diagnostic model for epithelial ovarian cancer according to claim 5 to calculate the EOC CTC Score value; The diagnostic module is used to perform the following steps: The operation of judging the health status of the subject according to the EOC CTC Score value, the judgment standard for positive epithelial ovarian cancer is: EOC CTC Score>-1.

64.

7. The diagnostic device for epithelial ovarian cancer according to claim 6, characterized in that: The method for obtaining the expression level information of the biomarker comprises: isolating ovarian cancer circulating tumor cells from a biological sample of a subject; Ovarian cancer circulating tumor cells were lysed and RNA was extracted and reverse transcribed into cDNA; Droplet digital PCR was used to quantitatively detect the cDNA concentration and calculate the expression level of the mRNA corresponding to the cDNA.

8. The diagnostic device according to claim 7, characterized in that The method for separating circulating tumor cells of ovarian cancer comprises: separating peripheral blood mononuclear cells from peripheral blood of a subject by centrifugation, mixing the peripheral blood mononuclear cells with antibodies and immunomagnetic beads, and collecting the immunomagnetic beads; Preferably, the antibodies include antibodies to epithelial adhesion molecules, antibodies to cadherin, and antibodies to mesothelin; Preferably, the biological sample comprises peripheral blood.

9. Use of the biomarker for epithelial ovarian cancer according to claim 1 in diagnosing and evaluating drugs for treating epithelial ovarian cancer.

10. The use according to claim 9, characterized in that: The biomarkers for epithelial ovarian cancer are used for the detection of ovarian cancer and the diagnosis of disease progression based on changes in biomarkers before, during and after treatment, thereby determining the treatment effect on patients and timely intervention of subsequent drugs.

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