An anti-fouling electrochemical serum sensor based on phosphoric acid group modified polypeptide, preparation method and application

Abstract

The application discloses an anti-pollution electrochemical serum sensor based on a phosphoric acid group modified polypeptide, a preparation method and application, and belongs to the technical field of electrochemical detection. A phosphoric acid group is introduced into a polyhydroxy proline polypeptide sequence. The polyhydroxy proline region of the polypeptide has excellent hydrophilicity, can form a hydration layer, and inhibits the adsorption of pollutants through steric hindrance and energy barrier; the terminal contains two phosphoserine branches, and the phosphoric acid group can be stably connected with phytic acid molecules on the substrate through the bridging action of vanadium ions. The sensing interface constructed by the ion coordination method is not affected by biological thiols, and the strong hydrophilicity of phytic acid and the polypeptide endows the interface with excellent anti-pollution ability. The precise detection of three biomarkers (CA15-3, CEA and AFP) can be realized in serum. The comprehensive analysis of the three markers combined with machine learning evaluation can improve the accuracy of early diagnosis of breast cancer.

Description

Technical Field

[0001] This invention relates to the field of electrochemical detection technology, and more specifically to an anti-pollution electrochemical serum sensor based on phosphate-modified peptides, its preparation method, and its application. Background Technology

[0002] Breast cancer is one of the leading causes of cancer death among women worldwide, posing a serious threat to women's health. Early diagnosis and prognostic monitoring are crucial for delaying disease progression and improving patients' quality of life. Disease biomarker detection, due to its advantages such as real-time detection, minimally invasive procedures, and reproducibility, has become an important auxiliary tool. However, single biomarkers are insufficient to reflect tumor heterogeneity and disease evolution, and carry the risk of false positives or false negatives, limiting their clinical application. Combined detection, through simultaneous analysis of multiple related biomarkers, can more comprehensively and accurately assess the disease status, significantly improving diagnostic efficacy. Multiple studies have shown that combined detection has a higher diagnostic accuracy for breast cancer than single biomarkers. Therefore, constructing a highly sensitive and specific multi-target parallel detection platform has become an important research direction for the early diagnosis and precise prevention and control of breast cancer.

[0003] Electrochemical detection, with its advantages of high sensitivity, high reliability, and rapid response, is widely used in the field of biosensing. However, biomolecules such as proteins in complex body fluids are prone to non-specific adsorption onto electrode surfaces, significantly affecting detection accuracy. Peptide molecules, due to their good biocompatibility, programmable structure, and ease of functionalization, have become ideal anti-fouling materials, and their feasibility has been verified by numerous studies. In the construction of peptide-based sensing interfaces, gold-sulfur bonds (Au-S) are commonly used to immobilize peptides through interfacial self-assembly. This method is simple to operate and produces stable bonds. However, gold-sulfur bonds have relatively weak bond energies and exhibit dynamic reversibility. In environments rich in natural bio-thiols (such as glutathione), they are easily competitively replaced, leading to interfacial structural damage and functional molecule shedding, thus irreversibly impairing the detection accuracy and long-term stability of the sensor.

[0004] Therefore, it is urgent to explore new peptide immobilization methods to overcome the above-mentioned defects of Au-S and prepare sensing interfaces with excellent anti-fouling ability and stability. Summary of the Invention

[0005] In view of this, the present invention provides an anti-fouling electrochemical serum sensor based on phosphate-modified peptides, its preparation method, and its application. The preparation method provided by the present invention can be combined with three different recognition aptamers to achieve joint detection of three targets, improving the accuracy of early breast cancer diagnosis. It should be noted that metal ion coordination plays a crucial role in regulating the function of natural metalloproteins and constructing supramolecular nanostructures; based on this, metal coordination-driven self-assembly has become a widely adopted design strategy. Regarding the selection of coordinating ions and ligands, inspired by the mussel adhesion mechanism, vanadium ions (V...3+ Phytic acid, as a natural multidentate chelating agent, exhibits strong coordination ability and can efficiently complex various metal ions, making it an ideal ligand for constructing stable coordination interfaces. This invention introduces phosphate groups into the polyhydroxyproline peptide sequence. The polyhydroxyproline region of this peptide has excellent hydrophilicity, forming a hydration layer that inhibits pollutant adsorption through steric hindrance and energy barriers. Its terminal portion contains two phosphoserine branches, and the phosphate groups can be stably linked to phytic acid molecules on the substrate via vanadium ion bridging. The sensing interface constructed using this ion coordination method is unaffected by biothiols, and the strong hydrophilicity of both phytic acid and the peptide endows the interface with excellent antifouling capabilities. Therefore, the interface constructed using the metal coordination method effectively avoids the defects of gold-sulfur bond interfaces, significantly improving the sensor's antifouling performance and stability.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] An anti-pollution electrochemical serum sensor based on phosphate-modified peptides, wherein the sensor uses phytic acid-doped conductive polymer poly(3,4-ethylenedioxythiophene) as the electrode modification material. Phosphate-modified peptide PMP is used as an antifouling material; Modification of three target-specific aptamers; Connection method: PMP is fixed to the interface through metal ion coordination bridging; specific aptamers are connected to PMP through Sulfo-SMCC-mediated covalent coupling; PMP sequence: SSKPPPPPP, as shown in SEQ ID No. 1, wherein S is phosphorylated and P is hydroxylated, i.e. Sep-(Sep)-K-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp); Three target-specific aptamers: The thiol-modified CA15-3 aptamer sequence is: GCAGTTGATCCTTTGGATACCCTGG, as shown in SEQ ID No. 2, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-GCAGTTGATCCTTTGGATACCCTGG-3′; The thiol-modified CEA aptamer sequence is TTTATACCAGCTTATTCAATT, as shown in SEQ ID No. 3, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-TTTATACCAGCTTATTCAATT-3′; The thiol-modified AFP aptamer sequence is TCAGGTGCAGTTCTCGACTCGGTCTTGATGTGGGT as shown in SEQ ID No. 4, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-TCAGGTGCAGTTCTCGACTCGGTCTTGATGTGGGT-3′.

[0008] Preferred: Includes the following steps: (1) Preparation of PEDOT modified electrode: PEDOT / SPE was prepared by depositing a PEDOT thin film on the surface of SPE using a constant potential method. (2) Sensor assembly: PEDOT / SPE was incubated in a mixed solution of PMP and VCl3 to obtain the antifouling interface PMP-V³. + / PEDOT / SPE; subsequently, maleimide groups were introduced by reacting Sulfo-SMCC with the primary amine at the interface, followed by incubation with a specific aptamer to obtain Apt / PMP-V³. + / PEDOT / SPE.

[0009] Preferred method: The specific method of step (1) is as follows: On SPE, a PEDOT thin film electrode PEDOT / SPE was obtained by electrodeposition at a potential of 1.1 V for 20-60 s in a mixed solution of EDOT with a concentration of 0.02-0.04 M and phytic acid with a concentration of 0.02-0.04 M using a potentiostatic method.

[0010] Preferred method: The specific method of step (2) is as follows: PMP was mixed with VCl3 solution to obtain a final PMP concentration of 0.2-0.4 mg·mL. - ¹, The final concentration of VCl3 is 1-3 mg·mL - ¹ A mixed solution; PEDOT / SPE was incubated in the above mixed solution at room temperature for 1-2 h, and then washed to obtain PMP-V³. + / PEDOT / SPE; PMP-V³ + The / PEDOT / SPE electrode was placed in a 1-3 mM Sulfo-SMCC solution and reacted for 1-2 h; the electrode after reaction was incubated in a 2-4 μM aptamer solution for 1-3 h to obtain the sensor.

[0011] The present invention also provides the application of the above-mentioned sensor in the preparation of diagnostic products.

[0012] This invention also provides a method for processing non-diagnostic and therapeutic data using the aforementioned sensors, including quantitative detection and machine learning analysis: The sensor was placed in target solutions of different concentrations and incubated at a constant temperature. After rinsing with PBS, electrochemical detection was performed: differential pulse voltammetry (DPV), -0.2 to -0.5 V. Machine learning algorithms are used to perform binary classification analysis on changes in electrochemical signals of clinical samples: input current signal, output result.

[0013] Preferred: The constant temperature incubation temperature is 25-30℃, and the time is 60-100 min; The machine learning uses a random forest model, with the dataset allocated as a 70% training set and a 30% validation set.

[0014] Preferred: Data processing range: CA15-3: 0.001 - 1000 U·mL - ¹, CEA: 1 pg·mL - ¹ - 1 μg·mL - ¹、AFP 1 pg·mL - ¹ - 1 μg·mL - ¹; Limit of detection: CA15-3: 0.25 mU·mL - ¹, CEA: 0.32 pg·mL - ¹, AFP: 0.53 pg·mL - ¹.

[0015] Notably, this invention is the first to design and synthesize a phosphate-modified polyhydroxyproline polypeptide. The polyhydroxyproline region (-(Hyp)6-) of this polypeptide exhibits excellent hydrophilicity, forming a hydration layer that inhibits pollutant adsorption through steric hindrance and energy barriers. Its terminal portion contains two phosphoserine branches (Sep), and the phosphate group can be stably linked to phytic acid molecules on the substrate via vanadium ion coordination bridging. The sensing interface constructed using this ion coordination method is unaffected by biothiols, and the strong hydrophilicity of both phytic acid and the polypeptide endows the interface with excellent antifouling capabilities. Therefore, the interface constructed using the metal coordination method effectively avoids the defects of gold-sulfur bond interfaces, significantly improving the sensor's antifouling performance and stability.

[0016] Quantitative detection and machine learning analysis are as follows: An antifouling electrochemical serum sensor based on phosphate-modified peptides was placed in solutions of different concentrations of the target analytes CA15-3, CEA, and AFP, and incubated at a constant temperature (25-30℃ for 60-100 min). The electrode interface was then rinsed with PBS buffer to remove uncaptured target analytes, and the resulting electrode was subjected to electrochemical detection. Differential pulse voltammetry was used to record the changes in the current signal at the sensing interface after incubation in the target analyte solutions within a range of -0.2-0.5 V to achieve target analyte detection. Serum samples from healthy individuals and breast cancer patients were selected and measured using the sensor. A machine learning algorithm was employed to perform binary classification analysis on the electrochemical signal changes of the clinical samples. The current signal changes of the three biomarkers were input into the machine learning training model, which then comprehensively evaluated the signal combinations and finally output the prediction results.

[0017] Carcinoembryonic antigen (CEA) is helpful in the diagnosis of breast cancer recurrence and prognostic assessment; cancer antigen 15-3 (CA15-3) is an important indicator for assessing postoperative recovery, recurrence, and metastasis in breast cancer, and its sensitivity is higher than that of CEA. Currently, combined detection of CEA and CA15-3 has become a common method for breast cancer diagnosis. Furthermore, although alpha-fetoprotein (AFP) has limited diagnostic efficacy when used alone, it can serve as an important supplementary biomarker for breast cancer diagnosis and treatment monitoring, showing independent predictive value and sensitivity to treatment response in multi-biomarker combined models. Previous studies have shown that combined detection of these three biomarkers is helpful for early breast cancer screening. This invention uses CA15-3, CEA, and AFP as detection targets and combines machine learning to analyze the combined detection results of the three, which is representative to a certain extent.

[0018] As can be seen from the above technical solution, compared with the prior art, the present invention discloses an anti-pollution electrochemical serum sensor based on phosphate-modified peptides, its preparation method, and its application, achieving the following technical effects: (1) This invention discloses for the first time the use of phosphate group modified peptides as anti-pollution materials in sensors.

[0019] (2) The phosphate group modified peptide disclosed in this invention is inspired by the robustness of metal ion coordination. It is the first time that phosphorylated serine has been introduced into the polyhydroxyproline peptide sequence, which realizes the fixation of peptides to the interface by metal ion coordination. Compared with the traditional strategy of fixing peptides by gold-sulfur bonds, it has better resistance to biothiol replacement and better anti-fouling ability, and also has better application potential.

[0020] (3) Most existing electrochemical sensors cannot be directly used for the detection of target substances in biological fluids. The sensor of this invention can directly measure CA15-3, CEA and AFP in serum without the need for serum pretreatment, and has strong practical application capabilities. Combined with machine learning, the accuracy of early diagnosis of breast cancer is improved by combining the analysis of the three target substances. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0022] Figure 1 The attached figure illustrates the preparation process and machine learning analysis of the anti-pollution electrochemical serum sensor based on phosphate-modified peptides provided by this invention.

[0023] Figure 2 The attached figure is a structural diagram of the phosphate-modified polypeptide provided by the present invention.

[0024] Figure 3 The attached figures are scanning electron microscope images of the PEDOT modified electrode provided by the present invention at resolutions of ×10000 (a) and ×30000 (b).

[0025] Figure 4 The attached figure shows the X-ray photoelectron spectra of different modified electrodes provided by the present invention, wherein, a: PEDOT and PMP-V 3+ / PEDOT's XPS spectrum; b: High-resolution and peak-splitting P 2p spectrum.

[0026] Figure 5 The attached figure shows the DPV current response curves of different modified electrodes provided by the present invention.

[0027] Figure 6 The attached figure shows the water contact angles of different modified electrodes provided by the present invention.

[0028] Figure 7 The attached figure shows the water contact angle of the antifouling interface constructed with different concentrations of vanadium ions provided by the present invention.

[0029] Figure 8 The attached figure shows the optimization of the sensor construction conditions provided by the present invention, wherein a: optimization of VCl3 concentration; b: optimization of PMP concentration; c: optimization of mixed solution incubation time.

[0030] Figure 9 The attached figures show fluorescence images of different modified interfaces provided by the present invention after immersion in fluorescent protein solutions, wherein a: unmodified; b: PEDOT modified; c: PMP-V 3+ / PEDOT modifier; d: Apt / PMP-V 3+ Modified with / PEDOT.

[0031] Figure 10 The attached figures show the DPV curves and signal suppression rate graphs of different modified electrodes provided by the present invention after immersion in BSA solutions of different concentrations; wherein, a: bare SPE; b: PEDOT / SPE; c: PMP-V 3+ DPV curves of / PEDOT / SPE after immersion in BSA solutions of different concentrations; d: signal suppression rate of different modified electrodes in BSA solutions of different concentrations.

[0032] Figure 11 The attached figures show the DPV curves and signal suppression rate graphs of the different modified electrodes provided by the present invention after immersion in FBS of different concentrations; wherein, a: bare SPE; b: PEDOT / SPE; c: PMP-V 3+ DPV curves of / PEDOT / SPE after immersion in FBS of different concentrations; d: signal suppression rate of different modified electrodes in FBS of different concentrations.

[0033] Figure 12 The attached figures show the DPV curves of different modified electrodes provided by the present invention after immersion in human serum of different concentrations, wherein a: bare SPE; b: PEDOT / SPE; c: PMP-V 3+ DPV curves of / PEDOT / SPE after immersion in human serum at different concentrations; d: signal inhibition rate of different modified electrodes in human serum at different concentrations.

[0034] Figure 13 The attached figures show the DPV curves of different modified electrodes provided by the present invention after immersion in whole blood of different concentrations, wherein a: bare SPE; b: PEDOT / SPE; c: PMP-V 3+ DPV curves of / PEDOT / SPE after immersion in whole blood at different concentrations; d: signal inhibition rate of different modified electrodes in whole blood at different concentrations.

[0035] Figure 14 The attached figure shows a comparison of the antifouling performance of PEDOT / SPE and Au / PEDOT / SPE provided by the present invention in different concentrations of FBS, human serum and whole blood.

[0036] Figure 15 The attached figure shows the PMP-V provided by this invention. 3+Comparison of the antifouling properties of / PEDOT / SPE and SMP / Au / PEDOT / SPE in different concentrations of FBS, human serum and whole blood.

[0037] Figure 16 The attached figure is a comparison of the long-term anti-fouling properties of different modified interfaces provided by the present invention.

[0038] Figure 17 The attached figures show a: SMP / Au / PEDOT / SPE and b: PMP-V provided by this invention. 3+ DPV curves of / PEDOT / SPE before and after GSH treatment in FBS at different concentrations; GSH (10 mg·mL⁻¹) treatment; -1 Before and after 24 h of treatment, c: PMP-V 3+ Comparison of antifouling performance between / PEDOT / SPE and d:SMP / Au / PEDOT / SPE.

[0039] Figure 18 The attached figure shows the signal inhibition rate of two interfaces after treatment with different GSH concentrations and at the same treatment time, as provided by the present invention: a: different GSH treatment times and b: different GSH concentrations after the same treatment time.

[0040] Figure 19 The attached figure is an optimization diagram of the incubation time of the target material provided by the present invention.

[0041] Figure 20 The attached figures show the differential pulse voltammetric current response of the PMP biosensor provided by the present invention to different concentrations of CA15-3 in a: PBS and b: FBS; c: the corresponding calibration curves of the biosensor in PBS and FBS.

[0042] Figure 21 The attached figures show the differential pulse voltammetric current response of the PMP biosensor provided by the present invention to different concentrations of CEA in a: PBS and b: FBS; c: the corresponding calibration curves of the biosensor in PBS and FBS.

[0043] Figure 22 The attached figures show the differential pulse voltammetric current response of the PMP biosensor provided by the present invention to different concentrations of AFP in a: PBS and b: FBS; c: the corresponding calibration curves of the biosensor in PBS and FBS.

[0044] Figure 23 The attached figure shows a reproducibility test diagram of the PMP biosensor provided by the present invention.

[0045] Figure 24 The attached figures show a: 50-cycle CV scans of the PMP biosensor provided by this invention and b: storage stability graph.

[0046] Figure 25 The attached figure shows an analysis of serum samples from breast cancer patients and healthy controls, using a t-test. b: ROC curve analysis plot generated using clinical human serum assay data.

[0047] Figure 26 The attached figures show: a: Sensing characteristics of each biomarker provided by the RF model; b: Pearson correlation coefficient matrix of biomarker combinations.

[0048] Figure 27 The attached figures show: a: Prediction accuracy of a single biomarker and a combination of biomarkers in the RF model provided by this invention; b: Average prediction accuracy of the RF model under different numbers of biomarkers.

[0049] Figure 28 The attached figure is a confusion matrix diagram showing the classification performance based on the RF model provided by the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] This invention discloses an anti-pollution electrochemical serum sensor based on phosphate-modified peptides, its preparation method, and its application.

[0052] In this embodiment, the details of the instruments, equipment, and reagents are as follows.

[0053] Equipment: All electrochemical tests were performed at 20℃–30℃ using a CHI 660E electrochemical workstation (Shanghai Chenhua). The test system was a phosphate buffer solution (PBS, 10.0 mM, pH 7.4) containing 5.0 mM [Fe(CN)6]3- / 4- and 0.1 M KCl. A three-electrode system was used: a screen-printed electrode (SPE) as the working electrode, and the counter electrode and reference electrode were made of carbon paste and Ag / AgCl, respectively. The water contact angle was measured using a JC2000D1 measurement system (Shanghai Zhongchen). The sample morphology was observed using a Hitachi S-4800 scanning electron microscope (Japan). Fluorescence analysis of the antifouling performance of different modified electrodes was performed using a TCS-SP5 confocal laser scanning microscope (Leica, Germany). Elemental analysis of the material surface was performed using an ESCALAB 250Xi X-ray photoelectron spectrometer (Thermo Fisher Scientific, UK).

[0054] Reagents: The phosphate-modified peptide designed in the examples (amino acid sequence: SSKPPPPPP, as shown in SEQ ID No. 1, wherein S is phosphorylated and P is hydroxylated to obtain PMP, with the sequence Sep-(Sep)-K-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp)) was synthesized by Shanghai Guotai Technology Co., Ltd. The thiol-modified CA15-3 aptamer (sequence: GCAGTTGATCCTTTGGATACCCTGG, as shown in SEQ ID No. 2, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-GCAGTTGATCCTTTGGATACCCTGG-3′), the thiol-modified CEA aptamer (sequence: TTTATACCAGCTTATTCAATT, as shown in SEQ ID No. 3, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-TTTATACCAGCTTATTCAATT-3′), and the thiol-modified AFP aptamer (sequence: TCAGGTGCAGTTCTCGACTCGGTCTTGATGTGGGT, as shown in SEQ ID No. 2) As shown in No. 4, the 5′ end of which has the chemical group HS-(CH2)6 added, i.e., 5′-HS-(CH2)6-TCAGGTGCAGTTCTCGACTCGGTCTTGATGTGGGT-3′, was provided by Sangon Biotech (Shanghai) Co., Ltd. Phytic acid (PA), 3,4-ethylenedioxythiophene (EDOT) monomer, vanadium(III) chloride (VCl3), tris(2-carboxyethyl)phosphine (TCEP), and chloroauric acid (HAuCl4) were purchased from Aladdin (Shanghai, China). Potassium nitrate (KNO3) was provided by Bolinda. Carcinoembryonic antigen (CEA), fetal bovine serum (FBS), fluorescein isothiocyanate-labeled bovine serum albumin (FITC-BSA), and bovine serum albumin (BSA) were provided by Solarbio Science & Technology Co., Ltd. (Beijing, China). Sodium 4-(N-maleimidemethyl)-cyclohexane-1-carboxylic acid 3-sulfonic acid-N-hydroxysuccinimide ester (Sulfo-SMCC) was purchased from Sigma-Aldrich. Anticoagulated rabbit whole blood was provided by Henan Jushi Biotechnology Co., Ltd. (Henan, China). Serum samples from volunteers collected with prior informed consent were provided by Qingdao Central Hospital (Qingdao, China). Alpha-fetoprotein (AFP) was provided by Sangon Biotech (Shanghai) Co., Ltd. Ultrapure water (resistivity >18 MΩ·cm) was prepared using a MilliQ ultrapure water system (Bedford, USA).

[0055] Example 1 The construction process of the antifouling electrochemical serum sensor based on phosphate-modified peptides is as follows: Figure 1 As shown: (1) Preparation of PEDOT modified electrode: PEDOT film was obtained by electrodeposition at 1.1 V for 20 s on SPE using the amperometric method (potential constant method) in a mixed solution of 0.02 M 3,4-ethylenedioxythiophene (EDOT) and 0.02 M phytic acid (PA).

[0056] (2) Sensor preparation: The PMP solution prepared with Tris-HCl buffer (10 mM, pH = 8.0) and VCl3 solution were mixed to obtain a final PMP concentration of 0.25 mg / mL. -1 The final concentration of VCl3 was 1 mg / mL. -1 The PEDOT / GCE mixture was incubated in the above-mentioned mixed solution at room temperature for 1 h. After the reaction was complete, the mixture was rinsed with deionized water to remove unfixed PMP and V. 3+ To obtain the antifouling interface PMP-V 3+ / PEDOT / SPE; PMP-V 3+ The / PEDOT / SPE electrode was activated in 2 mM Sulfo-SMCC solution for 1 h (using the reaction of Sulfo-SMCC with the primary amine on the interface to introduce maleimide groups). The activated electrode was then incubated in 3 μM aptamer solution (dissolved in PBS buffer solution (10 mM, pH = 7.4) and reduced with 0.1 mM TCEP) for 2 h to obtain the sensor.

[0057] The joint detection and machine learning analysis process is as follows: Figure 1 As shown: By connecting aptamers that specifically recognize CA15-3, CEA, and AFP, a sensor capable of quantitatively detecting these three target markers was constructed. The sensor quantitatively detected changes in the current signals of the three biomarkers in actual samples, constructing an n×3 data matrix (n being the number of samples, with the three columns corresponding to the current change values ​​of the three biomarkers). A scikit-learn-based RandomForestClassifier was used, combined with GridSearchCV and five-fold hierarchical cross-validation to determine the optimal hyperparameters. Finally, a random forest model with 50 decision trees was selected, and binary classification analysis was performed on the electrochemical signal changes of clinical samples (label vector y: 0 = healthy, 1 = cancer). The model comprehensively evaluated the signal combinations and output predicted values, with a prediction threshold of 0.5 (≥0.5 indicating cancer, <0.5 indicating normal). This strategy helps improve the accuracy of early breast cancer diagnosis.

[0058] Example 2 Structure of phosphate-modified polypeptides (PMPs): like Figure 2 As shown, phosphate groups are introduced into the polyhydroxyproline peptide sequence. The polyhydroxyproline region of this peptide exhibits excellent hydrophilicity, forming a hydration layer that inhibits pollutant adsorption through steric hindrance and energy barriers. Its terminal portion contains two phosphoserine branches, and the phosphate groups can be stably linked to phytic acid molecules on the substrate via vanadium ion bridging. The sensing interface constructed using this ion coordination method is unaffected by biothiols, and the strong hydrophilicity of phytic acid and the peptide endows the interface with excellent antifouling capabilities. Therefore, the interface constructed using the metal coordination method effectively avoids the defects of gold-sulfur bond interfaces, significantly improving the sensor's antifouling performance and stability.

[0059] Example 3 Characterization of PEDOT-modified electrodes: Depend on Figure 3 The scanning electron microscope image of PEDOT shows that when PEDOT and PA are co-deposited on the electrode surface, an irregular three-dimensional network structure is formed at the electrode interface, which increases the specific surface area of ​​the electrode.

[0060] Example 4 Characterization of antifouling electrochemical sensors based on phosphate-modified peptides (1) XPS characterization of the sensor assembly process: XPS characterization was performed on the assembly interface to monitor the sensor fabrication process, such as... Figure 4 As shown, the PEDOT electrode is mainly composed of carbon (C), oxygen (O), sulfur (S), and phosphorus (P). After modification with PMP through vanadium ion bridging, new nitrogen (N) and vanadium (V) peaks appeared. Simultaneously, in the high-resolution XPS spectrum of phosphorus (P), characteristic peaks corresponding to POV (134.21 eV), P-OH (133.49 eV), and P=O (132.89 eV) appeared, indicating that vanadium ions successfully formed a coordination bridge between PA and PMP.

[0061] (2) Electrochemical characterization of the sensor assembly process: The assembly process of the biosensor was documented using an electrochemical workstation. For example... Figure 5As shown, DPV curves for different modified interfaces were recorded in the negatively charged probe [Fe(CN)6]3- / 4- solution. Clearly, the DPV peak current of the bare SPE (black curve) is approximately 56 μA. When PEDOT (red curve) was modified onto the electrode, the peak current increased significantly to 750 μA due to the good conductivity of the conductive polymer-modified interface and the significantly increased specific surface area. Simultaneously, PEDOT modification also improved the electrode's stability. When PMP was connected to the electrode (blue curve), the current signal of the modified electrode decreased; after further modification with the aptamer, the current decreased further (green curve). This is attributed to the poor conductivity and steric hindrance effect of biomolecules, which hindered electron transfer between the electrode interface and the solution. Finally, when the aptamer specifically bound to the target (purple curve), the current decreased further, indicating the successful construction of the sensor.

[0062] Example 5 Property characterization based on PMP interface: Surface hydrophilicity is a key indicator for evaluating antifouling performance, and its essence depends on the hydrophilic / hydrophobic properties of the modified material. Hydrophilic materials can form a hydration layer at the interface, which creates a barrier both energy-wise and spatially to prevent the adsorption of contaminants, thus effectively preventing the adsorption of biomolecules (such as proteins). Therefore, the water contact angle of different modified interfaces was first characterized. Figure 6 As shown, the unmodified SPE surface exhibits hydrophobicity with a contact angle of 101 ± 1.30°. After PEDOT deposition, the interfacial hydrophilicity significantly increases due to the presence of six hydrophilic phosphate groups in the dopant phytic acid, decreasing the contact angle to 35.10 ± 0.54°. Further modification with PMP peptide further reduces the contact angle to 17 ± 1.11°, indicating the formation of a superhydrophilic interface. Notably, the introduction of the aptamer did not impair the interfacial hydrophilicity (19.04 ± 1.03).

[0063] Furthermore, when coupling PMP, V 3+ The concentration of PMPs affects the amount of immobilized PMPs. This phenomenon can be explained by the coordination behavior mediated by trivalent metal ions: such as... Figure 7 As shown in Figure a, V should be appropriately increased. 3+ Concentration allows PMP to be bridged to the sensing interface through bidentate or polydentate coordination with PA on the interface, thereby immobilizing PMP; however, excessive vanadium ions form single-metal-ligand complexes, thus eliminating this bridging effect. This phenomenon can be macroscopically observed by measuring the water contact angle. Figure 7 As shown in b, with V 3+ As the concentration increases, the water contact angle gradually decreases, indicating an increase in the number of attached peptide molecules. When the vanadium ion concentration reaches 1 mg·mL⁻¹... -1At that time, the contact angle was 17.28°, exhibiting superhydrophilicity. Further V... 3+ Concentration increased to 5 mg·mL -1 This will lead to an increase in the water contact angle and a decrease in hydrophilicity.

[0064] Example 6 Anti-fouling performance test: To obtain optimal antifouling performance, the concentration of PMP and V... 3+ The concentration and PMP incubation time were optimized. Figure 8 First, fluorescent protein attachment experiments were performed using fluorescein-labeled bovine serum albumin (FITC-BSA) to visually evaluate the PMP-based biosensor (Apt / PMP-V). 3+ / PEDOT) antifouling properties ( Figure 9 Under the same test conditions, unmodified surface, PEDOT modified surface, and PMP-V... 3+ / PEDOT-modified surfaces were used as controls. Fluorescence analysis showed that, compared with unmodified and PEDOT-modified surfaces ( Figure 9 Compared to a) and b), PMP-V 3+ / PEDOT and Apt / PMP-V 3+ The fluorescence intensity of the PEDOT-modified surface is almost zero. Figure 9 (c and d). Subsequently, the antifouling performance of the PMP-based biosensor was quantitatively analyzed by measuring its DPV signal before and after exposure to biological media and calculating the signal inhibition rate. Figure 10 - Figure 13 As shown, compared with the unmodified PMP interface, the PMP-modified electrode exhibited significantly improved antifouling ability in biomedia containing single protein solution (BSA), serum (FBS and human serum), and whole blood. Based on this, further improvements were made to the metal ion coordination method (PMP-V... 3+ The antifouling properties of PMP-V (PMP-V) and the gold-sulfur bond interface (SMP / Au / PEDOT / SPE) were compared and analyzed to verify the antifouling performance of the former. 3+ The superiority of / PEDOT / SPE).

[0065] like Figure 14 As shown, the Au / PEDOT modified interface exhibits poor antifouling performance in various biopolluted media, with a signal inhibition rate approximately 10% higher than that of the PEDOT modified interface. The PEDOT modified interface contains abundant phosphate groups, which can bind water molecules through hydrogen bonds to form a hydration layer, thereby resisting the adsorption of biopollutants; in contrast, the introduction of gold nanoparticles weakens the antifouling performance. Even after peptide coupling, the antifouling performance of the two interfaces still differs (…). Figure 15As the modification progresses, PMP-V 3+ The antifouling performance of both / PEDOT / SPE and SMP / Au / PEDOT / SPE was significantly improved. However, in undiluted FBS (6.3% vs 15.9%), undiluted human serum (6.0% vs 16.3%), and undiluted rabbit blood (7.1% vs 18.7%), PMP-V... 3+ / PEDOT / SPE exhibits superior anti-fouling performance compared to SMP / Au / PEDOT / SPE.

[0066] In addition, such as Figure 16 As shown, the PMP-modified electrode exhibited excellent antifouling performance in 50% whole blood, with a signal inhibition rate as low as 11.2% over a period of up to 3 weeks. This value is significantly lower than that of the gold-sulfur bond-constructed sensing interface (20.5%), and far lower than that of the PEDOT-modified electrode (27.2%) and the bare electrode (96.4%). This result is attributed to PMP-V 3+ / PEDOT / SPE itself has superior antifouling capabilities and excellent stability compared to SMP / Au / PEDOT / SPE.

[0067] Example 7 Sensor stability test: To verify PMP-V 3+ The / PEDOT / SPE interface outperformed the SMP / Au / PEDOT / SPE interface in resisting biothiol substitution and maintaining interfacial stability. Both interfaces were treated with reduced glutathione (GSH), and antifouling experiments were conducted. Results are as follows: Figure 17 As shown, after treatment with GSH (10 mg·mL⁻¹) -1 After treatment (24 h), the antifouling performance of SMP / Au / PEDOT / SPE in FBS was significantly weakened, with its signal inhibition rate in undiluted FBS increasing by approximately 10%, indicating that the antifouling peptides at this interface were replaced by biothiols, and the original antifouling structure was disrupted. In contrast, PMP-V 3+ The / PEDOT / SPE interface maintained stable antifouling properties before and after GSH treatment, demonstrating that the bridging effect of vanadium ions can effectively resist bio-thiol substitution, thereby maintaining the stability of the interface structure.

[0068] In addition, to comprehensively assess pollution resistance and biothiol resistance, a 10 mg / mL solution was used. -1 GSH was applied to the interface for different durations, followed by anti-contamination testing in undiluted FBS. Figure 18 As shown in Figure a, the signal rejection ratio of SMP / Au / PEDOT / SPE increases with time; however, the PMP-V... 3+The signal inhibition rate of / PEDOT / SPE remained essentially unchanged, indicating that the Au-S bond is more susceptible to disruption by biothiols, and vanadium ion bridging exhibits stronger resistance. Furthermore, the same results were observed after 24 hours of treatment with different concentrations of GSH. Figure 18 (b) The anti-fouling ability of SMP / Au / PEDOT / SPE decreases with increasing concentration, while that of PMP-V... 3+ The antifouling properties of / PEDOT / SPE remain essentially unchanged. These results demonstrate that PMP-V 3+ The / PEDOT / SPE interface exhibits excellent interface stability and can maintain its anti-fouling properties for a long time in complex biological environments.

[0069] Example 8 Sensor performance testing: This invention achieves precise diagnosis of breast cancer by jointly detecting multiple disease biomarkers. Three biomarkers—CA15-3, CEA, and AFP—were selected from a variety of potential targets for detection. Previous studies have shown that combined analysis of these three biomarkers is helpful for early breast cancer screening. Therefore, an anti-fouling electrochemical sensor was constructed. This sensor can detect CA15-3, CEA, and AFP separately by changing the corresponding recognition aptamers. To determine the optimal incubation time, the incubation duration of the target biomarkers was optimized, and 80 minutes was selected as the optimal incubation time. Figure 19 ).like Figures 20 to 22 As shown, the biosensor operates in the range of 0.001 to 1000 U·mL. 1 (CA15-3), 1 pg·mL -1 Up to 1 μg·mL -1 (CEA) and 1 pg·mL -1 Up to 1 μg·mL -1 (AFP) exhibited excellent linearity (R0.05) over a wide concentration range. 2 = 0.9993, 0.9993 and 0.9988), and its regression equation is ΔI = 55.83 + 14.69 lgC ΔI = 153.53 + 11.90 lgC and ΔI = 161.42 + 12.90lgC. Calculated using the IUPAC-recommended 3σ / k method, their detection limits are as low as 0.25 mU·mL. -1 0.32 pg·mL -1 and 0.53 pg·mL -1 Furthermore, even in undiluted FBS, the biosensor still exhibited a good linear response to the three disease biomarkers.

[0070] To evaluate the reproducibility of the PMP-based biosensor, seven independently fabricated sensing electrode pairs with a concentration of 100 ng·mL⁻¹ were used. -1 The alpha-fetoprotein (AFP) was tested. Figure 23 As shown, the DPV signals from all repeated tests were highly consistent, with a relative standard deviation (RSD) as low as 2.1%, indicating good reproducibility of the sensor. Stability is a key factor in ensuring reliable sensor performance. The operational stability of the PMP-based biosensor was evaluated using continuous cyclic voltammetry. Figure 24 As shown in Figure a, the curves obtained from 50 consecutive CV scans almost completely overlap, demonstrating excellent stability. Furthermore, after storing the sensor in PBS at 4°C for 15 days, the signal retention rate remained above 94.2%. Figure 24 (b)

[0071] Example 9 Sensor Practical Application Evaluation This invention incorporated 60 serum samples, 28 from breast cancer patients and 32 from healthy controls, aiming to evaluate the clinical applicability of the developed PMP-based sensor. Each serum sample was introduced into the sensing platform, incubated for 80 minutes, and the peak DPV current was recorded as the output signal. Each sample provided data for three biomarkers. Figure 25 As shown in Figure a, the obtained data clusters reveal a significant difference between the breast cancer group and the healthy control group. To further evaluate the diagnostic performance of the three biomarkers, receiver operating characteristic (ROC) curves were plotted. Figure 25 (b) The areas under the curve (AUC) for CA15-3, CEA, and AFP were 0.951, 0.938, and 0.878, respectively. These results indicate that CA15-3 expression levels have higher accuracy in distinguishing breast cancer patients from healthy controls.

[0072] To explore the application potential of serum disease biomarkers in clinical diagnosis, a random forest (RF) machine learning algorithm was used to analyze the association between the sensor signal sets of three different biomarkers and clinical outcomes. Under a supervised learning framework, 70% of the clinical sample dataset (n = 42 samples) was used as the training set for model training, while the remaining 30% was used as a blind test set to evaluate the model's performance in breast cancer screening. The DPV current changes obtained from each biomarker detection were input into the trained random forest model, which output two diagnostic results: breast cancer and normal.

[0073] The results of machine learning analysis are as follows Figure 26 - As shown in Figure 28, Figure 26Figure 'a' shows the relative importance of each biomarker used for disease classification in the random forest model. CA15-3 has a relatively high importance (0.391), while CEA and AFP have importance values ​​of 0.360 and 0.248, respectively. To further improve the model's predictive accuracy, a strategy combining multiple biomarkers was adopted. The Pearson correlation heatmap of the biomarkers shows their expression correlation across all samples and reveals potential synergistic or complementary relationships. Figure 26 As shown in Figure b, the correlation coefficient between CA15-3 and CEA is 0.47, the correlation coefficient between CA15-3 and AFP is 0.55, and the correlation coefficient between CEA and AFP is 0.4. These moderate correlations support the combined use of these three biomarkers in a biomarker combination. When the signals of these three biomarkers are used as input combinations, the prediction accuracy of the random forest model reaches 96.7% (…). Figure 27 (a) indicates that a reasonable combination of biomarkers can effectively improve the accuracy of machine learning-based decision-making. Figure 27 (b). Meanwhile, analysis of the confusion matrix on the validation set shows that it has high sensitivity and specificity in distinguishing between breast cancer patients and healthy individuals. Figure 28 ).

[0074] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0075] Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An anti-fouling electrochemical serum sensor based on phosphate-modified peptides, characterized in that: The sensor uses phytic acid-doped conductive polymer poly(3,4-ethylenedioxythiophene) as the electrode modification material. Phosphate-modified peptide PMP is used as an antifouling material; Modification of three target-specific aptamers; Connection method: PMP is fixed to the interface through metal ion coordination bridging; specific aptamers are connected to PMP through Sulfo-SMCC-mediated covalent coupling; PMP sequence: SSKPPPPPP, as shown in SEQ ID No. 1, wherein S is phosphorylated and P is hydroxylated, i.e. Sep-(Sep)-K-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp)-(Hyp); Three target-specific aptamers: The thiol-modified CA15-3 aptamer sequence is: GCAGTTGATCCTTTGGATACCCTGG, as shown in SEQ ID No. 2, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-GCAGTTGATCCTTTGGATACCCTGG-3′; The thiol-modified CEA aptamer sequence is TTTATACCAGCTTATTCAATT, as shown in SEQ ID No. 3, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-TTTATACCAGCTTATTCAATT-3′; The thiol-modified AFP aptamer sequence is TCAGGTGCAGTTCTCGACTCGGTCTTGATGTGGGT as shown in SEQ ID No. 4, wherein the chemical group HS-(CH2)6 is added to the 5′ end, i.e., 5′-HS-(CH2)6-TCAGGTGCAGTTCTCGACTCGGTCTTGATGTGGGT-3′.

2. The method for preparing the sensor according to claim 1, characterized in that, Includes the following steps: (1) Preparation of PEDOT modified electrode: PEDOT / SPE was prepared by depositing a PEDOT thin film on the surface of SPE using a constant potential method. (2) Sensor assembly: PEDOT / SPE was incubated in a mixed solution of PMP and VCl3 to obtain the antifouling interface PMP-V³. + / PEDOT / SPE; subsequently, maleimide groups were introduced by reacting Sulfo-SMCC with the primary amine at the interface, followed by incubation with a specific aptamer to obtain Apt / PMP-V³. + / PEDOT / SPE.

3. The preparation method according to claim 2, characterized in that, The specific method for step (1) is as follows: On SPE, a PEDOT thin film electrode PEDOT / SPE was obtained by electrodeposition at a potential of 1.1 V for 20-60 s in a mixed solution of EDOT with a concentration of 0.02-0.04 M and phytic acid with a concentration of 0.02-0.04 M using a potentiostatic method.

4. The preparation method according to claim 2, characterized in that, The specific method for step (2) is as follows: PMP was mixed with VCl3 solution to obtain a final PMP concentration of 0.2-0.4 mg·mL. - ¹, The final concentration of VCl3 is 1-3 mg·mL - ¹ A mixed solution; PEDOT / SPE was incubated in the above mixed solution at room temperature for 1-2 h, and then washed to obtain PMP-V³. + / PEDOT / SPE; PMP-V³ + PEDOT / SPE was placed in 1-3 mM Sulfo-SMCC solution and reacted for 1-2 h. The reacted electrode was incubated in a 2-4 μM aptamer solution for 1-3 h to obtain the sensor.

5. The application of the sensor according to claim 1 in the preparation of diagnostic products.

6. A method for processing non-diagnostic and therapeutic data using the sensor described in claim 1, characterized in that, Including quantitative detection and machine learning analysis: The sensor was placed in target solutions of different concentrations and incubated at a constant temperature. After rinsing with PBS, electrochemical detection was performed: differential pulse voltammetry (DPV), -0.2 to -0.5 V. Machine learning algorithms are used to perform binary classification analysis on changes in electrochemical signals of clinical samples: input current signal, output result.

7. The method according to claim 6, characterized in that: The constant temperature incubation is 25-30℃ for 60-100 min; The machine learning uses a random forest model, with the dataset allocated as a 70% training set and a 30% validation set.

8. The method according to claim 6, characterized in that: Data processing range: CA15-3: 0.001 - 1000 U·mL - ¹, CEA: 1 pg·mL - ¹ - 1 μg·mL - ¹、AFP 1pg·mL - ¹ - 1 μg·mL - ¹; Limit of detection: CA15-3: 0.25 mU·mL - ¹, CEA: 0.32 pg·mL - ¹, AFP: 0.53 pg·mL - ¹.

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