Marker combination for diagnosis of ovarian cancer and aptamer for detection and use thereof

Abstract

The application discloses a marker combination for diagnosing ovarian cancer, an aptamer for detecting the marker combination and a use, and belongs to the technical field of molecular diagnosis. The marker combination comprises phospholipids and polypeptides shown as SEQ ID NO. 1-7. The aptamer comprises nucleic acid sequences shown as SEQ ID NO. 8-15 and targets the marker combination. The AUC of the marker combination constructed by the application reaches 0.996 in joint diagnosis, and the marker combination has excellent sensitivity and specificity when used for auxiliary diagnosis of ovarian cancer. Meanwhile, the aptamer sequences targeting the marker combination are screened, and the aptamer sequences have high affinity of nanomolar (for polypeptide targets) or micromolar (for phospholipid targets), the cross-reactivity of the most similar molecules is lower than 5%, and more than 90% of the binding activity is retained after incubation in serum at 37 DEG C for 24 hours. The eight aptamers do not interfere with each other, and can be flexibly combined for multiplex detection.

Description

Technical Field

[0001] This invention belongs to the field of molecular diagnostic technology, specifically relating to a combination of biomarkers for ovarian cancer diagnosis, an aptamer for detection, and its applications. Background Technology

[0002] Ovarian cancer refers to malignant tumors that grow on the ovaries. 90%–95% of these are primary ovarian cancers, while the remaining 5%–10% are metastases from primary cancers in other parts of the body. Because early-stage ovarian cancer often lacks symptoms, and even when symptoms are present, they are nonspecific, and screening methods have limited effectiveness, early diagnosis is difficult. By the time patients seek medical attention, 60%–70% are already at an advanced stage, and treatment outcomes for advanced cases are often poor. Therefore, although the incidence of ovarian cancer is lower than that of cervical and endometrial cancer, it poses a serious threat to women's health.

[0003] Current serum biomarkers CA125 and HE4 have a sensitivity of less than 50% for early-stage ovarian cancer and are easily interfered with by benign diseases, resulting in limited specificity. Imaging examinations rely on operator experience, and tissue biopsies are invasive procedures with a risk of dissemination. Although liquid biopsy technologies (such as ctDNA and exosomes) are emerging, their high testing costs and complex procedures make them difficult to meet the screening needs of primary care settings. Therefore, developing highly sensitive, low-cost, and easy-to-use early diagnostic tools has become an urgent technical challenge in this field.

[0004] Aptamers are single-stranded DNA or RNA molecules obtained through in vitro screening that can bind to target molecules with high affinity and high specificity. Compared with traditional antibodies, aptamers have significant advantages such as controllable chemical synthesis, good batch-to-batch consistency, high thermal stability, ease of modification (e.g., labeling with fluorescent groups or biotin), and low immunogenicity. Furthermore, aptamers have an extremely broad target range, recognizing a variety of substances from ions and small molecule metabolites to proteins and even intact cells. Therefore, they are considered a core technology for next-generation molecular diagnostic probes, particularly suitable for developing point-of-care testing (POCT) products.

[0005] However, the application of existing aptamer technology in the diagnosis of ovarian cancer still faces many bottlenecks. First, the reported aptamers targeting ovarian cancer-related proteins (such as CA125 and HE4) often lack sufficient affinity to detect extremely low concentrations of the target in the serum of early-stage patients, and are prone to cross-reactions with molecules of the same family, leading to a high false-positive rate. Second, high-performance aptamers targeting small-molecule metabolites (such as lysophospholipids) are extremely scarce. The reported aptamers typically have dissociation constants (Kd) greater than 20 μM for metabolites and exhibit poor serum stability (half-life less than 6 hours), making them unsuitable for clinical testing. Furthermore, when using multiple aptamers for multi-target detection, non-specific interactions may occur between aptamers, interfering with the accuracy of the results. These issues have prevented aptamer-based multi-marker combined detection systems for ovarian cancer from entering clinical application to date. Summary of the Invention

[0006] To address the aforementioned shortcomings in existing technologies, this invention provides a combination of diagnostic biomarkers for ovarian cancer, along with aptamers for detection and their applications. This invention identifies eight significantly differentially expressed biomarkers, with a combined diagnostic AUC of 0.996. The biomarker combination constructed in this invention exhibits superior sensitivity and specificity in the auxiliary diagnosis of ovarian cancer, outperforming the current clinical guidelines-recommended ROMA index ovarian cancer risk prediction model (sensitivity and specificity of 76.0% and 85.1% for premenopausal patients, and 90.6% and 79.4% for postmenopausal patients, respectively). It holds promise for applications in the diagnosis and treatment of ovarian cancer.

[0007] To achieve the above objectives, the technical solution adopted by the present invention to solve its technical problem is as follows: The purpose of this invention is to provide a biomarker set for the diagnosis of ovarian cancer, comprising phospholipids and polypeptides as shown in SEQ ID NO. 1-7, as specifically shown in Table 1.

[0008] Furthermore, the phospholipid is 1-linoleoyl-2-Hydroxy-sn-glycero-3-phosphocholine.

[0009] Furthermore, the fourth amino acid G of the polypeptide shown in SEQ ID NO.3 is phosphorylated.

[0010] Table 1. Markers

[0011] The fourth amino acid G of the polypeptide shown in SEQ ID NO.3 is phosphorylated.

[0012] Another object of the present invention is to provide the use of reagents for detecting the above-mentioned group of biomarkers in the preparation of ovarian cancer diagnostic agents.

[0013] Furthermore, the active ingredient of the reagent is an aptamer, the nucleic acid sequence of which is shown in SEQ ID NO. 8~15.

[0014] Another object of the present invention is to provide an aptamer that specifically binds to the above-mentioned biomarker group, comprising nucleic acid sequences as shown in SEQ ID NO. 8-15, which specifically bind to the polypeptides and phospholipids shown in SEQ ID NO. 1-7, respectively, as detailed in Table 2.

[0015] Table 2 Aptamer Sequences

[0016] Furthermore, the nucleic acid sequence shown in SEQ ID NO.8 specifically binds to the polypeptide shown in SEQ ID NO.1; The nucleic acid sequence shown in SEQ ID NO. 9 targets the polypeptide shown in SEQ ID NO. 2; The nucleic acid sequence shown in SEQ ID NO.10 targets the polypeptide shown in SEQ ID NO.3; The nucleic acid sequence shown in SEQ ID NO.11 targets the polypeptide shown in SEQ ID NO.4; The nucleic acid sequence shown in SEQ ID NO.12 targets the polypeptide shown in SEQ ID NO.5; The nucleic acid sequence shown in SEQ ID NO.13 targets the polypeptide shown in SEQ ID NO.6; The nucleic acid sequence shown in SEQ ID NO.14 targets phospholipids; The nucleic acid sequence shown in SEQ ID NO.15 targets the polypeptide shown in SEQ ID NO.7.

[0017] Another object of the present invention is to provide a kit comprising the above-described aptamer.

[0018] Another object of the present invention is to provide the use of the above-described aptamers or kits in the preparation of products for detecting the above-described biomarker group.

[0019] The beneficial effects of this invention are: This invention identified eight significantly differentially expressed biomarkers, whose combined diagnostic AUC reached 0.996. The biomarker combination constructed in this invention has superior sensitivity and specificity in the auxiliary diagnosis of ovarian cancer, and its auxiliary diagnostic results are better than the ROMA index ovarian cancer risk prediction model recommended by current clinical guidelines (sensitivity and specificity of 76.0% and 85.1% for premenopausal patients, and 90.6% and 79.4% for postmenopausal patients, respectively).

[0020] This invention also optimizes the SELEX screening strategy, designing different target presentation methods for two classes of target molecules with significantly different physicochemical properties (one being peptide fragments, and the other being phospholipid metabolites). For peptide targets, magnetic bead immobilization is used for positive screening; for phospholipid targets, a pioneering liposome embedding technology is employed to maintain their native conformation in a simulated biomembrane environment. After multiple rounds of rigorous negative screening (including competitive elution of healthy human serum proteins, blank liposomes, and structurally similar molecules), eight nucleic acid aptamers were finally obtained. ELISA and flow cytometry verification showed that these aptamers all possess high affinity at the nanomolar level (peptide targets) or micromolar level (phospholipid targets), with a cross-reactivity rate of less than 5% for the most similar molecules, and retain over 90% binding activity after incubation in serum at 37°C for 24 hours. Furthermore, there is no mutual interference among the eight aptamers, allowing for flexible combination for multiplex detection. Attached Figure Description

[0021] Figure 1 Affinity curve of Pep01 and peptide aptamer AP-OC01; Figure 2 Affinity curve of Pep02 and peptide aptamer AP-OC02; Figure 3 Affinity curve of Pep03 and peptide aptamer AP-OC03; Figure 4 Affinity curve of Pep04 and peptide aptamer AP-OC04; Figure 5 Affinity curve of Pep05 and peptide aptamer AP-OC05; Figure 6 Affinity curve of Pep06 and peptide aptamer AP-OC06; Figure 7 Affinity curves of Met01 and aptamer AP-OC07; Figure 8 Affinity curve of Pep07 and peptide aptamer AP-OC08; Figure 9 This is the ROC curve for the marker group. Detailed Implementation

[0022] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0023] Example 1: Biomarker Screening 1. Sample collection 1) Sample type: serum.

[0024] 2) Collection requirements: Fasting is required. Use a coagulation tube to draw 5 mL of venous blood, let it stand for 30 min, centrifuge at 3000 rpm for 15 min, and take out about 1 mL of serum and put it into a cryopreservation tube.

[0025] 3) Sample storage: For use on the same day, store at 2~8℃; if not used on the same day, store at -20℃ for up to 30 days; for long-term storage (more than one month), store at -80℃. Do not freeze-thaw more than 3 times. 2. Sample processing 1) After calibrating the mass spectrometer, turn on the GR-TOF® 2000 fully automated sample analysis system for solid-liquid biological samples, and put in a 10μL pipette tip, the matching reagent kit and the sample to be tested; 2) Select the procedure method "Concentrated loading"; 3) Run the program a. Opening a hole; b. Take at least 10µL of serum sample and activation reagent, mix them in a 1:1 ratio, and place them in the G-row pre-reserved well for later use; c. Clean the custom pipette tip in cleaning reagent 1 and cleaning reagent 2 in sequence. Each time, aspirate at least 10µL of liquid and repeat the aspiration and dispensing process at least 3 times. d. Process the serum mixture in the G-row wells using the cleaned custom pipette tips. Aspirate at least 10 µL of solution each time, repeating the process at least three times. e. Clean the custom pipette tip after adsorbing the serum mixture using cleaning reagent 3. During cleaning, aspirate at least 10µL of liquid each time, repeating the aspiration and dispensing process at least 3 times. f. Transfer no less than 10µL of buffer reagent into the H-row pre-reserved hole, and place the customized pipette tip after using cleaning reagent 3 into the liquid to draw no less than 10µL of liquid. Repeat the suction and aspiration at least 3 times. g. Transfer at least 10µL of sample matrix solution into the H-row pre-reserved well to complete sample processing; h. Spot 2.0 µL of the solution from well H onto the biochip; i. Vacuum drying for 240 seconds.

[0026] The main components of each reagent are shown in Table 3.

[0027] Table 3 Reagent Composition

[0028] 3. Mass spectrometry detection The vacuum-dried biochip (MBT Biotarget 96 biochip target plate (Bruker)) was placed into the mass spectrometer.

[0029] Data acquisition was performed using pre-defined SP1 voltage (target high voltage), SP2 voltage (pulse high voltage), focusing voltage (lens high voltage), detector voltage (MCP voltage), pulse delay time, acquisition card range, target diameter, laser frequency, calibration method, and laser intensity. This invention, through time-of-flight mass spectrometry testing of 300 normal human samples and 500 ovarian cancer samples, discovered differences in the levels of eight serum substances between normal individuals and ovarian cancer patients, demonstrating its diagnostic capability for ovarian cancer.

[0030] Detection mode: positive ion reflector mode.

[0031] Quality range: m / z 400-10,000.

[0032] Laser parameters: Nd:YAG laser, wavelength 355 nm, repetition rate 2,000 Hz, 2,000 laser shots per sample point (50 shots per sub-point, 40 sub-points in total), laser attenuator set to medium intensity (approximately 55-65%).

[0033] Accelerating voltages: Ion source 1 voltage (SP1 voltage) 19.0 kV, ion source 2 voltage (SP2 voltage) 16.5 kV, lens voltage 8.5 kV.

[0034] Reflector voltage: 20.0 kV.

[0035] Then, the sequences of these eight substances in clinical serum were confirmed using secondary mass spectrometry (MS / MS or TOF / TOF). In primary mass spectrometry, peptide fragments or small molecule metabolites in serum are first ionized and analyzed according to their mass-to-charge ratio (MTR), generating a primary mass spectrum showing the MTR and relative abundance of the peptide fragments. Subsequently, the peptide fragments selected in the primary mass spectrometry are fragmented, and the resulting fragment ions are again analyzed by MTR, generating a secondary mass spectrum that provides information on the MTR and relative abundance of the fragment ions. The sequences (Table 1) and specificity of these eight markers were confirmed by secondary mass spectrometry, ruling out false positives.

[0036] Example 2: Screening of peptide aptamers I. Screening of the peptide aptamer AP-OC01 1. Reagent preparation Target peptide: FVCNSGYK (solid phase synthesis, purity >95%). NHS activated magnetic beads: Thermo Fisher (10 mg / mL); The initial SELEX library was commissioned to Shanghai Sangon Biotech for synthesis of: 5'-ATACCAGCTTATTCAATT-N 40 -AGATAGTAAGTGCAATCT-3' (100 nmol, dissolved in 1 mL PBS) (SEQ ID NO.16); Binding buffer: PBS + 1mM MgCl2 + 0.01% Tween-20 (pH 7.4); Elution buffer: 8M urea (containing 10mM EDTA).

[0037] 2. SELEX Filtering (1) Target immobilization a) Take 100 μL of NHS magnetic beads + 500 μg of target peptide (dissolved in 200 μL of PBS); b) Rotate the reaction vessel at 25°C for 2 hours; c) Magnetic separation, discard the supernatant, add 500 μL of 1M ethanolamine (block for 30 minutes); d) Wash three times with 1 mL of binding buffer to obtain the target peptide-magnetic bead complex.

[0038] (2) Positive screening a) Take 50 μL of the target peptide-magnetic bead complex prepared in step (1) + 200 pmol of the initial SELEX library (dissolved in 500 μL of binding buffer). b) Incubate at 37°C with rotation for 30 minutes; c) Magnetic separation: Discard the supernatant and wash three times with 1 mL of pre-cooled binding buffer (5 minutes each time).

[0039] (3) Negative screening a) Magnetic bead-target peptide complex washed with buffer + 100 μL healthy human serum; b) Shake at 25℃ for 10 minutes → Discard the supernatant.

[0040] (4) Washing a) Add 100 μL of elution buffer → 95°C water bath for 5 minutes; b) Immediate magnetic separation and recovery of the supernatant (containing bound DNA).

[0041] (5) PCR amplification a) System: 50 μL elution buffer + 1 μM each of primers F / R + 0.2 mM dNTP + Taq polymerase; Table 4 Amplification Primers

[0042] b) Program: 95℃ 5min → [95℃ 30s → 58℃ 30s → 72℃ 30s] ×25 → 72℃ 5min; c) Purification: The ssDNA secondary library was recovered by ethanol precipitation.

[0043] d) Sequencing Screening: The ssDNA secondary library obtained in the 12th round of screening was amplified by PCR. The PCR product was ligated into the T vector and transformed into E. coli DH5α competent cells. The cells were plated on LB agar plates containing ampicillin, and white single colonies (no less than 50) were picked and sent to Shanghai Sangon Biotech for Sanger sequencing. After removing the fixed regions at both ends of the sequencing results, the random region sequences were compared and analyzed. The sequence with the highest occurrence frequency was selected as the dominant aptamer sequence, and the aptamer AP-OC01 sequence as shown in SEQ ID NO.8 was finally obtained.

[0044] Table 5 Filtering Round Parameters

[0045] 3. Affinity verification (ELISA method) (1) Coating: 50 μL Pep01-BSA (1 μg / mL) → overnight at 4℃; (2) Sealing: 100 μL 3% BSA → 37℃ for 1 hour; (3) Binding: 50 μL gradient concentration of aptamer AP-OC01 (0.1-100 nM) → 37℃ for 1 hour; (4) Detection: 50 μL anti-FAM-HRP (1:5000) → 37℃ for 45 minutes; (5) Color development: 50 μL TMB → 10 minutes at room temperature in the dark → 50 μL stop solution; (6) Reading value: 450nm wavelength, calculate Kd, the result is shown in Figure 1 .

[0046] 4. Specificity verification (flow cytometry detection) (1) Microsphere-coupled target a) Take 50 μL of streptavidin microspheres (approximately 10... 7 (each) → Centrifuge at 1000g for 5 minutes → Discard the supernatant; b) Resuspend in 100 μL PBS → Add 10 μL of biotinylated target peptide (final concentration 10 μg / mL). c) Incubate at 25°C for 2 hours by rotation → centrifuge and wash 3 times (flow cytometry buffer); d) Resuspend to 500 μL (final concentration 2 × 10⁻⁶) 6 (pcs / mL) → Store at 4℃.

[0047] (2) Competition-based experiment a) Add 50 μL of microsphere suspension (10 μL) to each well of a 96-well plate. 5 Add 50 μL of gradient concentration interfering peptide (0.1-100 times the target concentration) or 50 μL of AP-OC01-FITC (final concentration 50 nM) (see Table 6). b) Set up the following control groups c and d: c) Positive: No interfering peptide; d) Negative: No aptamer; e) Incubate at 37°C in the dark with shaking for 90 minutes (300 rpm).

[0048] (3) Flow cytometry detection a) Add 150 μL of flow cytometry buffer to each well to terminate the reaction; b) Fluorescence signals were collected under the conditions of 488 nm excitation light and 525 nm emission light in flow cytometer, and the positive rate was statistically analyzed. The results are shown in Table 8.

[0049] II. The screening process for peptide aptamers AP-OC02, AP-OC03, AP-OC04, AP-OC05, AP-OC06, and AP-OC08 was identical to that for AP-OC01, except that the target peptide and corresponding amplification primers used for each aptamer were different. The design of the amplification primers is common knowledge in this field. The final screening yielded peptide aptamer sequences as shown in SEQ ID NO. 9~13 and SEQ ID NO. 15, respectively. The affinity test results for each peptide aptamer to the target peptide are shown below. Figures 2-6 and Figure 8 The specific detection results are shown in Table 8.

[0050] Example 3: Screening of phospholipid aptamers (AP-OC07) 1. Reagent preparation Target phospholipid: 1-linoleyl-2-hydroxy-SN-glycerol-3-lecithin; Liposome components: DPPC (dipalmitoylphosphatidylcholine): 85 mol% SELEX initial library: Same as in Example 2; Target phospholipids: 10 mol% DSPE-PEG2000: 5 mol% Screening buffer: 20mM HEPES + 150mM NaCl + 2mM CaCl2 (pH 7.4). Lysis buffer: 0.5% Triton X-100 (containing 10mM Tris-HCl).

[0051] 2. SELEX Filtering (1) Liposome preparation a) Weigh the lipids: DPPC 42.5mg + target phospholipids 7.2mg + DSPE-PEG2000 5.0mg; b) Chloroform dissolution → nitrogen blowing film formation → vacuum drying for 1 hour; c) Add 2 mL of screening buffer → hydrate at 60℃ for 1 hour → vortex for 5 minutes; d) Extrusion: through a 100nm polycarbonate membrane, 11 cycles; e) Particle size detection: dynamic light scattering verification (100±10nm).

[0052] (2) Positive screening a) Take 100 μL of liposomes + 200 pmol of SELEX initial library (dissolved in 500 μL of screening buffer); b) Incubate at 37°C with rotation for 45 minutes; c) Ultracentrifugation: 100,000g × 30 minutes (4℃); d) Discard the supernatant and wash the precipitate three times with 1 mL of cold buffer.

[0053] (3) Negative screening (starting from round 6) a) The preparation of blank liposomes is the same as in step (1), except that they do not contain the target phospholipids; b) The liposomes obtained in step (2) + 100 μL of blank liposomes → shake at 25°C for 15 minutes; c) Centrifuge and wash again.

[0054] (4) Washing a) Add 200 μL of lysis buffer → shake at 25°C for 20 minutes; b) Ultracentrifugation: 100,000g × 20 minutes; c) Recover the supernatant (containing the released DNA).

[0055] (5) Preparation of secondary ssDNA libraries a) Preparation of biotinylated PCR products: Using secondary dsDNA as a template, PCR amplification was performed using a reverse primer labeled with biotin at the 5' end to obtain a double-stranded product with biotin at the positive end.

[0056] b) Magnetic bead binding: Biotinylated PCR products were incubated with streptavidin magnetic beads (such as Dynabeads MyOneStreptavidin C1) in binding buffer (10 mM Tris-HCl, 1 mM EDTA, 2 M NaCl, pH 7.5) at room temperature for 30 minutes by rotation, so that the biotinylated DNA strands could bind to the streptavidin on the magnetic beads.

[0057] c) Alkaline denaturation separation: Remove the supernatant using magnetic separation, add 0.15 M NaOH solution, and let stand at room temperature for 5-8 minutes to denature the double-stranded DNA. After magnetic separation, the non-biotinylated sense single strand (i.e., the desired ssDNA library) is released from the supernatant, while the biotinylated antisense strand remains on the magnetic beads.

[0058] d) Neutralization and purification: Collect the supernatant, add an equal volume of neutralization buffer (0.5 M Tris-HCl, pH 7.5) to neutralize the pH, and remove salts and small molecule impurities using a desalting column or ethanol precipitation method to obtain a purified ssDNA secondary library, which is then quantified for the next round of screening.

[0059] (6) Competitive selection (starting from round 11) a) Add 10 times the molar amount of LPC (Lysophosphatidylcholine) 16:0 during positive screening; b) After pre-incubating at 37°C for 15 minutes, add the ssDNA secondary library as in the previous round.

[0060] Table 6 Filtering Round Parameters

[0061] Note: The Triton cleavage in Table 6 uses Triton X-100.

[0062] 3. Affinity verification (ELISA method) (1) Coating: Add 50 μL of liposome solution (0.5 mM) containing Met01 to the well of the lipophilic plate → let stand at 4℃ for 12 hours; (2) Sealing: 100 μL 1% BSA / 0.05% Tween-20 → 25℃ for 2 hours; (3) Binding: 50 μL of biotinylated phospholipid aptamer AP-OC07 (0.5-50 μM) → shake overnight at 4℃; (4) Detection: 50 μL streptavidin-HRP (1:10000) → 25℃ for 1 hour; (5) Color development: 50 μL TMB → room temperature, protected from light for 10 minutes → 50 μL stop solution; (6) Reading value: 450nm wavelength, calculate Kd, the result is shown in Figure 7 .

[0063] 4. Specificity verification (flow cytometry detection) (1) Microsphere pretreatment a) Take 100 μL of phospholipid microspheres (5 × 10⁻⁶) 6 (each) → Centrifuge at 800g for 5 minutes; b) Resuspend in 200 μL liposome buffer → wash 3 times; c) Adjust the final concentration to 1*10 17 per mL.

[0064] (2) Low-temperature competition combined experiment a) Add 50 μL of microsphere suspension (5 × 10⁻⁶) to each well of a pre-cooled 96-well plate (4°C). 5 Add 50 μL of interfering lipid (dissolved in ethanol, final concentration 0.1-100 μM) or 50 μL of AP-OC07-Cy5 (final concentration 1 μM). b) Incubate at 4°C with shaking for 4 hours (to prevent lipid phase transition).

[0065] (3) Flow cytometry detection a) Add 150 μL of cold buffer to each well to terminate the process; b) Fluorescence signals were immediately fed into the flow cytometer under the conditions of excitation light of 488 nm and emission light of 525 nm (sample stage maintained at 4℃), and the positive rate was statistically analyzed. The results are shown in Table 8.

[0066] Table 7 Competitive Experimental Design

[0067] Table 8. Flow Cytometry Validation Data for Aptamers

[0068] Note: Data format: Proportion of positive microspheres (mean ± SD, n=3); Target binding inhibition rate = [1 - (competition group - negative control) / (positive control - negative control)] × 100%.

[0069] As shown in the table above, the binding rates of all aptamers decreased significantly in the competition assay (inhibition rate >76%), demonstrating their specific binding to the target. AP-OC03 showed high specificity for phosphorylation modification (95.6% binding rate in the competition group), distinguishing between phosphorylated and non-phosphorylated peptides. In the presence of serum proteins (such as C3b and Fibrinogen) and structurally similar metabolites (LPC 16:0 / 18:1), the aptamers maintained a binding rate of >85% (specific group). The combination of high positive binding rate (>93%) and low background signal (<3.5%) meets the sensitivity and specificity requirements for ovarian cancer serum biomarker detection.

[0070] Example 4: Construction and Validation of the OC-Score Random Forest Diagnostic Model 1. Sample Data Preparation The sample sources are as follows: Ovarian cancer group: serum from 500 patients with pathologically confirmed ovarian cancer (128 cases of stage I, 132 cases of stage II, 165 cases of stage III, and 75 cases of stage IV). Control group: Serum from 300 healthy volunteers (age matched ± 3 years); Interference group: 100 patients with benign gynecological diseases (35 cases of endometriosis, 42 cases of ovarian cysts, and 23 cases of pelvic inflammatory disease).

[0071] All samples were serum samples, collected from Zhongshan Hospital affiliated with Fudan University, and all were approved by the ethics committee and the subjects obtained informed consent.

[0072] Table 9 Data Collection

[0073] The specific process of "aptamer-flow cytometry quantification" detection in Table 9 is as follows: (1) Target-coupled microspheres: Take 50 μL of streptavidin magnetic beads / microspheres (5 × 10⁻⁶) 5 Add biotinylated target markers (such as Pep01 or Met07-BSA), incubate at room temperature by rotation for 2 hours, centrifuge, wash and resuspend for later use.

[0074] (2) Aptamer binding: The fluorescently labeled aptamer is mixed with the serum sample to be tested, and then the microsphere suspension coupled with the target is added. The mixture is incubated at 4°C or 37°C in the dark with shaking (e.g., for 90 minutes).

[0075] (3) Washing to remove non-specific binding: After incubation, add flow cytometry buffer to terminate the reaction, centrifuge and wash 3 times to remove unbound free aptamers.

[0076] (4) Flow cytometry analysis: Resuspend the washed microspheres and analyze them on the flow cytometer. Record the average fluorescence intensity (MFI) or positive rate (%) of the microsphere population under excitation light at 488 nm, emission light at 525 nm (FITC) or 670 nm (Cy5) channels.

[0077] (5) Quantitative conversion (data form): A "concentration-MFI" standard curve is established using target gradient standards of known concentrations. The MFI value of the sample to be tested is substituted into the standard curve to calculate the concentration value (nM or μM) of the marker in serum. The concentration gradient of the standard curve of this invention covers a range of 0.01 to 20 times the target dissociation constant (Kd) (0.01~50 nM for peptide aptamers and 0.01~10 μM for phospholipid aptamers).

[0078] 2. Feature Engineering (1) To avoid "false positives" that may be caused by fluctuations in total FPA release among different individuals, Figure 9 The FPA(1-16)+PO3 curve was obtained by inputting the concentration ratio of Pep03 / Pep02 into the model.

[0079] (2) The concentration range of Met01 is too large (0.1~100 μM), and directly inputting it into the model will cause "features with large values ​​to overwhelm features with small values". Therefore, the logarithm of its concentration is used as the input feature of the model to ensure that the data distribution is closer to the normal distribution and the model converges faster.

[0080] 3. Model Training This invention employs the random forest algorithm and sets the class_weight='balanced' parameter, enabling the model to automatically adjust the misjudgment penalty weights based on the number of samples in each class in the training set. This avoids the model biasing towards the majority class and ensures high sensitivity even in the early stages of ovarian cancer (when cancer signals are weak). (Reference 1: Jia Y, Yuan L, Wen W, Chen L, Zhao 10.1186 / s12916-025-04341-2. PMID: 40846961; PMCID: PMC12374407.) (Reference 2: Madda R, Petyuk VA, Wang YT, Shi T, Shriver CD, Rodland KD, Liu T. Use of Longitudinal SerumAnalysis and Machine Learning to Develop a Classifier for Cancer Early Detection. Methods Mol Biol. 2023;2628:579-592. doi: 10.1007 / 978-1-0716-2978-9_33. PMID: 36781807.).

[0081] The training set consists of 500 examples, including: Ovarian cancer group (positive): 300 cases, including 100 cases of early stage (I / II) and 200 cases of intermediate and late stage (III / IV); Non-cancer group (negative): 200 cases, including 150 healthy controls and 50 cases of benign ovarian lesions.

[0082] Using the concentrations of Pep01, Pep02, Pep04, Pep05, Pep06, and Pep07, and the feature-engineered concentration parameter of Met01, as well as the concentration parameters of Pep07 of the validation set sample in Table 8 (containing a total of 400 clinical serum samples, including 200 cases of ovarian cancer positive group (120 cases of early stage I / II and 80 cases of mid-to-late stage III / IV) and 200 cases of non-cancer negative control group (including 150 healthy volunteers and 50 patients with benign gynecological diseases, including 18 cases of endometriosis, 21 cases of ovarian cysts, and 11 cases of pelvic inflammatory disease) as individual input features, the ROC curve of a single target was obtained by inputting these parameters into the above model (see Table 8). Figure 9 Then, using all the above target combinations as input features, they are input into the model to obtain the ROC curve of the marker group (see...). Figure 9 ).

[0083] In the figure, C3 (1306-1319) is the ROC curve of target Pep04, C3 (1304-1319) is the ROC curve of target Pep05, FPA (1-16) + PO3 is the ROC curve of Pep02 / Pep03 (concentration ratio), PLG (524-549) is the ROC curve of Pep06, FPA (1-16) is the ROC curve of Pep02, CFH (176-183) is the ROC curve of Pep01, LysoPC (18: / 0:0):[M+H+] is the ROC curve of Met01, PFKL is the ROC curve of Pep07, and the curve below PFKL represents the ROC curve of the biomarker combination formed by the above targets.

[0084] like Figure 9 As shown, the ROC curve reveals that the model achieves a high balance between sensitivity and specificity at the optimal threshold (the point of maximum Youden index), with the area under the curve approaching the theoretical limit of 1.0. The model's AUC is 0.993 (95% CI: 0.992-1.000), with a sensitivity of 94.1% (93.9% detection rate of early stage I / II cancer) and a specificity of 98.2% (only 1 misdiagnosed case out of 100 benign lesions). The curve closely follows the upper left corner, achieving a true positive rate of >90% at a false positive rate of 0.01, significantly superior to the control model (ROMA index AUC = 0.89, EarlySEEK AUC = 0.92).

[0085] Finally, it should be noted that the above specific embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A biomarker set for the diagnosis of ovarian cancer, characterized in that, It includes phospholipids and polypeptides such as SEQ ID NO.1~7.

2. The biomarker group for ovarian cancer diagnosis according to claim 1, characterized in that, The phospholipid is 1-linoleyl-2-hydroxy-SN-glycerol-3-lecithin.

3. The biomarker group for ovarian cancer diagnosis according to claim 1, characterized in that, The fourth amino acid G of the polypeptide shown in SEQ ID NO.3 is phosphorylated.

4. Use of the reagent for detecting the biomarker group according to any one of claims 1 to 3 in the preparation of ovarian cancer diagnostic preparations.

5. The use according to claim 4, characterized in that, The active ingredient of the reagent is an aptamer, and its nucleic acid sequence is shown in SEQ ID NO. 8~15.

6. An aptamer specifically binding to the marker set according to any one of claims 1 to 3, characterized in that, This includes nucleic acid sequences as shown in SEQ ID NO. 8~15, which specifically bind to the polypeptides and phospholipids shown in SEQ ID NO. 1~7, respectively.

7. The aptamer according to claim 6, characterized in that, The nucleic acid sequence shown in SEQ ID NO. 8 specifically binds to the polypeptide shown in SEQ ID NO. 1; The nucleic acid sequence shown in SEQ ID NO. 9 targets the polypeptide shown in SEQ ID NO. 2; The nucleic acid sequence shown in SEQ ID NO.10 targets the polypeptide shown in SEQ ID NO.3; The nucleic acid sequence shown in SEQ ID NO.11 targets the polypeptide shown in SEQ ID NO.4; The nucleic acid sequence shown in SEQ ID NO.12 targets the polypeptide shown in SEQ ID NO.5; The nucleic acid sequence shown in SEQ ID NO.13 targets the polypeptide shown in SEQ ID NO.6; The nucleic acid sequence shown in SEQ ID NO.14 targets phospholipids; The nucleic acid sequence shown in SEQ ID NO.15 targets the polypeptide shown in SEQ ID NO.

7.

8. A reagent kit, characterized in that, Includes the aptamer as described in claim 6 or 7.

9. Use of the aptamer of claim 6 or 7 or the kit of claim 8 in the preparation of a product for detecting the biomarker group of any one of claims 1 to 3.

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