Urine biomarkers for ovarian cancer detection and screening methods and uses thereof

Abstract

The application discloses a urine biomarker for ovarian cancer detection and a screening method and application thereof. The urine biomarker is selected from at least one of the following (1)-(5): (1) heterogeneous nuclear ribonucleoprotein A3; (2) polymeric immunoglobulin receptor; (3) small integral membrane protein 24; (4) collagen type V alpha 2 chain; and (5) microtubule-associated protein 2. The urine polypeptide group biomarker of the application has high sensitivity and specificity when used for ovarian cancer detection, and the detection process is simple and non-invasive, which is favorable for improving the early diagnosis rate of ovarian cancer and improving the survival period of ovarian cancer patients.

Description

Technical Field

[0001] This invention relates to the field of ovarian cancer diagnostic technology, and in particular to urinary biomarkers for ovarian cancer detection, as well as their screening methods and applications. Background Technology

[0002] Ovarian cancer (OC) is the most deadly gynecological malignancy. Traditional diagnostic methods for ovarian cancer (such as radioimmunoassay, mass spectrometry, immunoassay, polymerase chain reaction, and enzyme-linked immunosorbent assay) are time-consuming and complex. Currently, commonly used diagnostic indicators for ovarian cancer include serum carbohydrate antigen 125 (CA125) and serum human epididymis protein 4 (HE4), but due to their poor specificity, they often lead to diagnostic delays, making early diagnosis of ovarian cancer still difficult. The preferred treatment for ovarian cancer is surgery, followed by chemotherapy, biological therapy, hormone therapy, and radiotherapy. However, recurrence is common after systemic treatment, and the prognosis is extremely poor. Studies have reported 5-year survival rates of 90%, 70%, 40%, and 20% for stages I, II, III, and IV, respectively. Improving early screening rates could significantly improve patient survival. Therefore, improving the early diagnosis rate of ovarian cancer and providing individualized treatment as early as possible are important measures to improve the prognosis of ovarian cancer.

[0003] Reports on urinary biomarkers for ovarian cancer are limited. However, recent studies have extensively confirmed that HE4 can serve as a tumor marker for ovarian and endometrial cancer. Urinary HE4 levels and serum HE4 levels were positively correlated in all groups, and urinary HE4 showed comparable sensitivity to serum HE4 for ovarian cancer, while its specificity was significantly higher. CA125 and HE4 are the most commonly used biomarkers for ovarian cancer, but due to their low sensitivity and specificity in early diagnosis, they are typically used for the diagnosis and monitoring of advanced-stage patients.

[0004] Therefore, existing technologies still need improvement and development. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide urine biomarkers for ovarian cancer detection, as well as screening methods and applications thereof, in order to solve the problems of insufficient existing urine biomarkers for ovarian cancer and low early diagnosis rate of ovarian cancer.

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

[0007] In a first aspect, a urine biomarker for ovarian cancer detection is provided, said urine biomarker being selected from at least one of the following (1) to (5):

[0008] (1) Heterogeneous nuclear ribonucleoprotein A3 (hnRNP A3);

[0009] (2) Polymeric immunoglobulin receptor (pIgR);

[0010] (3) Small integral membrane protein 24 (SMIM24);

[0011] (4) Type V collagen alpha-2 chain (COL5A2);

[0012] (5) Microtubule-associated protein 2 (MAP2).

[0013] Secondly, a method for screening urine biomarkers as described in the first aspect is provided, including the steps of:

[0014] Urine samples from patients with ovarian tumors and healthy individuals were preprocessed by mass spectrometry to obtain the samples to be tested.

[0015] Mass spectrometry was used to examine the polypeptide components in the sample to be tested, and the peptides were assigned by database search and analysis.

[0016] By comparing the differences in degradation protein composition between ovarian tumor patients and normal healthy individuals, urinary biomarkers were screened.

[0017] In a preferred embodiment, the mass spectrometry preprocessing includes the following steps:

[0018] Transfer the urine to a 3KD ultrafiltration centrifuge tube and centrifuge at 11000-13000g for 8-12 minutes to obtain the ultrafiltration solution;

[0019] The ultrafiltration solution is desalinated by passing it through a desalination column;

[0020] The peptides were eluted from the desalting column using elution buffer to obtain the elution solution;

[0021] The elution solution was centrifuged, concentrated, and dried to obtain the sample to be tested.

[0022] In a preferred embodiment, the elution buffer is prepared with water and contains 0.1 v / v% formic acid and 60 v / v% acetonitrile.

[0023] Thirdly, the application of urine biomarkers as described in the first aspect in the preparation of ovarian cancer diagnostic products is provided.

[0024] In a preferred embodiment, the diagnostic product is a reagent or kit.

[0025] Fourthly, a reagent for ovarian cancer detection is provided, the reagent comprising products for detecting urine biomarkers as described in the first aspect.

[0026] Fifthly, a kit for ovarian cancer detection is provided, the kit comprising products for detecting urinary biomarkers as described in the first aspect.

[0027] Beneficial effects: The present invention provides a urine biomarker for ovarian cancer detection. The urine biomarker has high sensitivity and specificity when used for ovarian cancer detection, and the detection process is simple and non-invasive, which is conducive to improving the early diagnosis rate of ovarian cancer and improving the survival of ovarian cancer patients. Attached Figure Description

[0028] Figure 1 This is the ROC curve of Heterogeneous nuclear ribonucleoprotein A3 for ovarian cancer detection.

[0029] Figure 2 This is the ROC curve of Collagen alpha-2(V)chain for ovarian cancer detection.

[0030] Figure 3 This is the ROC curve of the Polymeric immunoglobulin receptor for ovarian cancer detection.

[0031] Figure 4 This is the ROC curve of Small Integral Membrane Protein 24 used for ovarian cancer detection.

[0032] Figure 5 This is the ROC curve of Microfibrillar-associated protein 2 for ovarian cancer detection.

[0033] Figure 6 This is a graph showing the efficacy test results of the urine biomarkers of the present invention. Detailed Implementation

[0034] This invention provides urine biomarkers for ovarian cancer detection, screening methods and applications thereof. To make the objectives, technical solutions and effects of this invention clearer and more explicit, the invention is further described in detail below.

[0035] This invention provides urinary biomarkers for ovarian cancer detection, wherein the urinary biomarkers are selected from at least one of the following (1) to (5):

[0036] (1) Heterogeneous nuclear ribonucleoprotein A3 (hnRNP A3);

[0037] (2) Polymeric immunoglobulin receptor (pIgR);

[0038] (3) Small integral membrane protein 24 (SMIM24);

[0039] (4) Type V collagen alpha-2 chain (COL5A2);

[0040] (5) Microtubule-associated protein 2 (MAP2).

[0041] This invention provides a method for screening urine biomarkers as described above, comprising the following steps:

[0042] Urine samples from patients with ovarian tumors and healthy individuals were preprocessed by mass spectrometry to obtain the samples to be tested.

[0043] Mass spectrometry was used to examine the polypeptide components in the sample to be tested, and the peptides were assigned by database search and analysis.

[0044] By comparing the differences in degradation protein composition between ovarian tumor patients and normal healthy individuals, urinary biomarkers were screened.

[0045] In one embodiment, the mass spectrometry pretreatment includes the following steps:

[0046] Transfer the urine to a 3KD ultrafiltration centrifuge tube and centrifuge at 11000-13000g for 8-12 minutes to obtain the ultrafiltration solution;

[0047] The ultrafiltration solution is desalinated by passing it through a desalination column;

[0048] The peptides were eluted from the desalting column using elution buffer to obtain the elution solution;

[0049] The elution solution was centrifuged, concentrated, and dried to obtain the sample to be tested.

[0050] In one embodiment, the elution buffer is prepared with water and contains 0.1 v / v% formic acid and 60 v / v% acetonitrile.

[0051] This invention provides the application of the urine biomarkers described above in the preparation of ovarian cancer diagnostic products.

[0052] In one embodiment, the diagnostic product is a reagent or kit.

[0053] This invention provides a reagent for ovarian cancer detection, the reagent comprising a product for detecting urinary biomarkers as described above.

[0054] This invention provides a kit for ovarian cancer detection, the kit comprising products for detecting urinary biomarkers as described above.

[0055] The present invention will be further described below through specific embodiments.

[0056] Example 1

[0057] 1. Collection of experimental materials:

[0058] The samples in this embodiment were obtained from Fudan University Cancer Hospital in Shanghai. Urine samples were collected from 42 healthy individuals and 42 patients with ovarian malignant tumors, and stored at -80°C. The criteria for ovarian malignant tumor patients were imaging and pathological sections. The inclusion criteria for the normal control group were age-matched healthy individuals.

[0059] 2. Urine polypeptide separation method

[0060] (1) Transfer the urine sample solution (2-3 mL) to a 3KD ultrafiltration centrifuge tube, centrifuge at 12000g for 10 min;

[0061] (2) The ultrafiltration solution was desalted using a C18 desalination column;

[0062] (3) Elute the sample with Elution buffer (0.1% FA, 60% ACN), and transfer the elution solution to a new EP tube;

[0063] (4) The eluted sample is centrifuged, concentrated and dried for mass spectrometry analysis.

[0064] 3. LC-MS / MS detection and database retrieval analysis

[0065] (1) LC-MS / MS detection

[0066] After desalting, the sample was centrifuged and dried, then redissolved in Nano-LC mobile phase A (0.1% formic acid / water), bottled, and loaded for online LC-MS analysis. The dissolved sample was loaded in an appropriate volume onto a nanoViper C18 pre-column (3 μm). Then, a 20 μL volume was used for washing and desalting. The liquid chromatography system was an UltiMate 3000 RSLC nano-liquid system (ThermoFisher, USA). The sample was desalted and retained on the pre-column before separation on the analytical column. The analytical column specifications were a C18 reversed-phase column (Acclaim PepMap RSLC, 75 μm × 25 cm C18-2 μm). The gradient used in the experiment involved increasing the mobile phase B (80% acetonitrile, 0.1% formic acid) from 5% to 38% over 30 minutes. Mass spectrometry was performed using a ThermoFisher Q Exactive plus system (ThermoFisher, USA) combined with a nano-spray Nano Flex ion source (ThermoFisher, USA). The spray voltage was 1.9 kV, and the ion transfer tube heating temperature was 320 °C. The mass spectrometry scan was performed in information-dependent acquisition mode (DDA). The primary mass spectrometry resolution was 70,000 m / s, the scan range was 350–1500 m / s, and the maximum injection time was 100 ms. A maximum of 20 secondary mass spectra with charges ranging from 2+ to 5+ were acquired per DDA cycle. The maximum ion injection time for secondary mass spectrometry was 50 ms, the collision chamber energy (high-energy collision-induced dissociation, HCD) was set to 28 eV, applicable to all precursor ions, and the dynamic exclusion was set to 25 seconds.

[0067] (2) Database retrieval analysis

[0068] Raw data files acquired by mass spectrometry were processed and analyzed using PEAKS Studio 8.5 (BioinformaticsSolutions Inc., Waterloo, Canada). The database used was the Homo sapiens protein database downloaded from Uniprot, with the following search parameters set: mass tolerance of 10 ppm for primary mass spectrometry, 0.03 Da for secondary mass spectrometry, and enzyme set to none; variable modifications included: protein N-term acetylation, asparagine / glutamine deamination (Deamidation (NQ)), methionine oxidation (Oxidation (M)), glutamate pyroglutamylation (Pyro-glu), and glutamine pyroglutamyl cyclization (Pyro-Gln).

[0069] 4. Results

[0070] In biomarker research, it is typically necessary to determine a threshold value to identify whether a sample contains a specific protein. In this embodiment, the threshold value is set as the number of proteins containing a single peptide. The sensitivity and specificity of each protein are calculated using this threshold value. Sensitivity refers to the biomarker's ability to correctly identify a disease (ovarian cancer in this embodiment), while specificity refers to the biomarker's ability to correctly identify non-disease states.

[0071] This embodiment compares degradation proteins and their associated peptides in 32 ovarian cancer patients and 32 non-ovarian cancer control groups. To find the optimal combination of biomarkers, this embodiment calculates the sum of the sensitivity and specificity of each protein and then sorts them in descending order of this sum. This sorting helps identify proteins that are most likely to appear in ovarian cancer but not necessarily in all non-disease samples. Using this method, this embodiment screens out several specific degradation proteins, with the following results:

[0072] (1) Heterogeneous nuclear ribonucleoprotein A3, Collagen alpha-2(V) chain, Polymeric immunoglobulin receptor, Small integral membrane protein 24, and Microfibrillar-associated protein 2 were identified in descending order. These five degradation proteins exhibited relatively high sensitivity and specificity compared to other proteins, and all had AUC values ​​greater than 0.8. Therefore, they were considered potential biomarkers. Their ROC curves are shown below. Figures 1-5 As shown.

[0073] (2) The peptide belonging to Heterogeneous nuclear ribonucleoprotein A3 is M(+42.01)EVKPPP (SEQ ID NO.1), and its related peptides and derivative peptides (M(+42.01)EVKPPPGRPQ PDSGRRR, M(+42.01)EVKPPPGRPQPDSGRR, M(+42.01)EVKPPPGRPQPDSGR, etc.) were detected in 19 patients;

[0074] The peptide belonging to the Collagen alpha-2(V) chain is GPEGPPGEPGPPGPP (SEQ ID NO.2), and related peptides such as (GPEGPPGEPGPPG, GPEGPPGEPGPP, GPEGPPGEPGP, etc.) were detected in 10 patients.

[0075] The peptide belonging to the polymeric immunoglobulin receptor is EEKAVADTRDQADGSRASVDSGS SEEQGGSSRA (SEQ ID NO.3), and its related peptides (EEKAVADTRDQADGSRASVDSGSSEEQGGSSRALVSTLVPLG, EEKAVADTRDQADGSRASVDSGSSEEQGGSS RALVSTLVP, EEKAVADTRDQADGSRASVDSGSSEEQGGSSRALVSTL, etc.) were detected in 10 patients.

[0076] The peptide belonging to Small integral membrane protein 24 is Q(-17.03)QATEHRLKP (SEQ ID NO.4), and its related peptides (Q(-17.03)QATEHRLKPWLVG, Q(-17.03)QATE HRLKPWL and Q(-17.03)QATEHRLKPW, etc.) were detected in 13 patients;

[0077] The peptide belonging to Microfibrillar-associated protein 2 is PLPPPFPDHV (SEQ ID NO. 5), which was detected in 22 patients along with its associated peptides (PLPPFPDHV, LPPFPDH, and LPPFPDHV).

[0078] 5. Efficacy detection of biomarkers

[0079] (1) Detection method

[0080] Qualitative differences in the types of degraded proteins in the urine of healthy individuals and ovarian cancer patients were directly compared.

[0081] (2) Test results

[0082] In the urine of another 10 ovarian cancer patients and a control group, the detection values ​​of the above five degradation proteins showed significant differences, as shown in the following results. Figure 6 As shown. By Figure 6 As can be seen, the five degradation proteins proposed in this embodiment appeared at a minimum frequency of 6 times and a maximum of 10 times in 10 validated ovarian cancer samples. Although two proteins were detected in the control group, this does not rule out the potential risk of ovarian cancer in these samples. This result indicates that the urine biomarkers proposed in this embodiment can predict ovarian cancer with relatively high accuracy.

[0083] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. Use of a urinary biomarker for the manufacture of a diagnostic product for ovarian cancer, characterized in that, The urine biomarker is small integral membrane protein 24.

2. Use according to claim 1, characterized in that, The diagnostic product is a reagent or a kit.

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