Immunohistochemical detection kit and method for PD-L1

Abstract

The invention relates to the technical field of tumor diagnosis and immunohistochemical detection, and discloses a PD-L1 immunohistochemical detection kit and method.The kit is composed of a double-epitope high-affinity antibody, a color developing reagent, a signal amplification system, antigen repair liquid, a sealing reagent and the like. According to the detection method, a double-epitope antibody is combined with different active epitopes of PD-L1 in a targeted manner, the color development effect of a weak signal area is enhanced through a Tyramide dynamic signal amplification technology, meanwhile, the spatial distribution characteristics of PD-L1 and other immune markers are analyzed by introducing a multi-target fluorescence labeling technology, a multi-dimensional scoring model is established, and the tumor immune microenvironment is comprehensively evaluated. According to the method, the sensitivity and specificity of PD-L1 detection are improved, background noise interference is reduced, the problems of leak detection of a weak positive region, cross interference of multi-target detection, inaccurate single scoring model and the like are solved, and the method is widely applied to the fields of tumor immunotherapy adjoint diagnosis and microenvironment research.

Description

Technical Field

[0001] The present invention relates to the technical field of tumor diagnosis and immunohistochemical detection, and specifically to a PD-L1 immunohistochemical detection kit and method. Background Art

[0002] Currently, immune checkpoint inhibitors (such as PD-1 / PD-L1 inhibitors) have become an important means of tumor treatment. They restore T cell activity by blocking immunosuppressive signals, bringing significant survival benefits to patients. However, as an important companion diagnostic tool for screening patients for immunotherapy, PD-L1 immunohistochemistry detection still has many deficiencies in sensitivity, specificity and data interpretation capabilities, which restricts the widespread application of detection methods.

[0003] Traditional PD-L1 immunohistochemistry detection methods mainly rely on single-epitope antibodies, and the DAB colorimetric method is used to evaluate the expression of PD-L1 in tumor tissues. However, when single-epitope antibodies bind to low-expressing PD-L1 or target molecules with structural changes, their affinity and specificity are often insufficient, resulting in weak staining signals or even difficult to detect. In addition, the signal output capacity of the DAB colorimetric method is limited, especially in weakly positive samples, the visibility of the coloring area is poor, which seriously affects the sensitivity of the detection. This limitation may cause patients with weakly expressed PD-L1 to be incorrectly identified and miss the opportunity for immunotherapy.

[0004] Existing technologies attempt to introduce signal amplification technology to improve the detection ability of weak positive signals, but most of them adopt a single-round signal amplification strategy. Although the target signal can be enhanced, the background noise is also amplified synchronously, resulting in a decrease in detection specificity. High background interference is particularly obvious in complex tissues. For example, in high-background colon cancer or gastric cancer tissues, nonspecific staining often covers the target signal area, making it difficult to ensure the accuracy of the test results. At the same time, existing antigen retrieval and blocking schemes are mostly single measures, lacking effective responses to nonspecific binding behavior, further exacerbating the staining background problem.

[0005] With the development of immunohistochemistry technology, multi-target detection has become the main direction for in-depth analysis of the tumor microenvironment. By simultaneously detecting the expression and distribution of PD-L1 and other immune-related markers (such as CD8 and FOXP3), more comprehensive information can be provided for the patient's immune status. However, the traditional DAB multi-round color development method shows significant limitations in multi-target detection. Cross-interference between color development reagents makes the staining results difficult to distinguish, and the boundaries between the stained areas are blurred, making it difficult to clearly analyze the spatial relationship between tumors and immune cells. This deficiency limits the comprehensive evaluation ability of the tumor microenvironment and weakens the role of the detection method in guiding immunotherapy.

[0006] In addition, the existing PD-L1 detection scoring system is usually based on the tumor positive proportion (TPS) to evaluate the proportion of PD-L1 positive cells. Although this single scoring method is simple and intuitive, it ignores the spatial association information between the PD-L1 expression area and immune active or inhibitory cells. In highly heterogeneous tumors, TPS is difficult to fully reflect the patient's immune status, resulting in the failure to effectively identify some patients with potential responses to immunotherapy, which also affects the accuracy of predicting the effect of immunotherapy.

[0007] In summary, the existing PD-L1 immunohistochemistry detection methods have insufficient detection sensitivity in low-expression areas, the background noise in complex tissues is relatively large, the spatial resolution ability of traditional multi-target detection technology is limited, and the single-dimensional scoring system cannot comprehensively evaluate the tumor immune status. These deficiencies limit the accurate analysis of the tumor immune microenvironment by existing technologies and also hinder their further application in immunotherapy companion diagnosis. Summary of the invention

[0008] In view of the deficiencies in the prior art, the present invention provides a PD-L1 immunohistochemical detection kit and method to solve the problems of insufficient sensitivity, significant background interference, limited multi-target analysis and a single scoring model in the existing PD-L1 immunohistochemical detection.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions: A PD-L1 immunohistochemical detection kit, comprising the following components: Dual-epitope high-affinity anti-PD-L1 monoclonal antibody, with a mass fraction of 0.5% to 5%; Colorimetric reagent, with a mass fraction of 1% to 10%, wherein the colorimetric reagent is DAB colorimetric solution or Tyramide signal amplification reagent; Antigen repair solution, with a mass percentage of 5% to 15%, wherein the antigen repair solution is a citric acid buffer or an EDTA buffer; Blocking reagent, mass percentage is 2% to 10%; Stabilizer, mass percentage is 0.1% to 1%; The antibodies and reagents were prepared with phosphate buffered saline, with the balance being 100%.

[0010] Preferably, the dual-epitope high-affinity anti-PD-L1 monoclonal antibody is composed of two single-chain antibodies connected by a flexible peptide chain, and the single-chain antibodies are directed against different active epitopes of PD-L1.

[0011] Preferably, the dual-epitope high-affinity antibody is obtained by screening using phage display technology, and its affinity constant is less than 10 -9 M.

[0012] Preferably, the color developing reagent comprises a DAB substrate solution, the concentration of the DAB substrate solution is 0.02 mg / mL to 0.05 mg / mL, and is combined with 0.01% to 0.03% hydrogen peroxide.

[0013] Preferably, the antigen retrieval solution is a 0.01M to 0.05M citric acid buffer solution with a pH of 6.0 to 7.0, or a 0.01M to 0.05M EDTA buffer solution with a pH of 8.5 to 9.5.

[0014] An immunohistochemical detection method for PD-L1 comprises the following steps: S1. Place the fixed tissue sections in antigen retrieval solution for antigen retrieval; S2. Add dual-epitope high-affinity anti-PD-L1 monoclonal antibody dropwise for primary antibody incubation; S3. Add color developing reagent for color development; S4. Perform nuclear counterstaining, dehydration and sealing on the stained sections; S5. Observe the staining results under a microscope.

[0015] Preferably, the antigen repair step is to place the tissue section in an antigen repair solution and treat it at 95° C. to 100° C. for 10 to 20 minutes.

[0016] Preferably, in the antibody incubation step, the antibody concentration is 0.5 µg / mL to 1.5 µg / mL, the incubation temperature is 37° C., and the incubation time is 30 minutes to 60 minutes.

[0017] Preferably, in the step S3, the color development time is 1 minute to 3 minutes, and the color development reagent includes DAB substrate solution or Tyramide signal amplification reagent.

[0018] Preferably, the staining results are quantitatively analyzed under a microscope using image analysis software, and the obtained data include the positive ratio of PD-L1 expression level.

[0019] The present invention provides a PD-L1 immunohistochemical detection kit and method, which have the following beneficial effects: 1. The present invention adopts dual-epitope high-affinity antibody technology, which significantly improves the binding stability and specificity of the antibody to the target protein by targeting two different active epitopes of PD-L1. Compared with the single-epitope antibody solution in the prior art, which is prone to false positives or false negatives, the design of the present invention effectively overcomes the problem of insufficient detection sensitivity in low-expression areas, and is particularly suitable for immunohistochemical analysis of low-expression patient samples.

[0020] 2. The present invention introduces dynamic signal amplification technology, combined with Tyramide signal amplification (TSA) and multiple rounds of cycle amplification scheme, which effectively enhances the detectability of weak signals. In the prior art, the color development signal of traditional DAB color development is easily masked by background noise when the target antigen concentration is low. However, the present invention greatly improves the detection signal-to-noise ratio by combining color development with signal amplification, ensuring the reliability and contrast of the staining results.

[0021] 3. The present invention introduces spatial omics analysis into immunohistochemistry detection, and comprehensively analyzes the dynamic characteristics of the tumor immune microenvironment through multi-target fluorescent labeling technology and AI-assisted algorithms. Unlike the existing single-target detection method that can only provide simple PD-L1 expression information, the present invention can simultaneously analyze the spatial distribution relationship between PD-L1 and other immune-related markers. This innovation realizes the multi-dimensional evaluation of the tumor immune microenvironment, making up for the deficiency of traditional technology in revealing spatial heterogeneity.

[0022] 4. The present invention adopts a comprehensive optimization scheme of antigen repair and background noise suppression, and further improves the staining specificity through the formula of efficient antigen repair solution and double blocking steps. Compared with the problems of uneven staining or excessive background staining caused by insufficient tissue processing in the prior art, the present invention significantly reduces the risk of nonspecific staining while improving the quality of the target signal, thereby optimizing the clarity and consistency of the staining results. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Schematic diagram of the steps of the immunohistochemical detection method of PD-L1 in the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The present invention provides an immunohistochemical detection kit for PD-L1, comprising the following components: The weight percentage of the dual-epitope high-affinity anti-PD-L1 monoclonal antibody is 0.5% to 5%. The dual-epitope high-affinity anti-PD-L1 monoclonal antibody is composed of two single-chain antibodies connected by a flexible peptide chain, and the single-chain antibodies target different active epitopes of PD-L1. The dual-epitope high-affinity antibody is obtained by phage display technology screening, and its affinity constant is less than 10 -9 M.

[0026] Bi-epitope antibody reagents: Components: Bi-epitope high-affinity PD-L1 monoclonal antibody (IgG1 type or scFv fragment).

[0027] Ratio: The antibody concentration is 0.5µg / mL~1.5µg / mL, dissolved in 0.01M phosphate buffer (PBS), containing 0.1%~0.3% bovine serum albumin (BSA) and 0.05%~0.1% sodium azide.

[0028] Stabilizer: Add 0.1% to 0.2% glycerol to prolong antibody stability.

[0029] The color developing reagent has a mass fraction of 1% to 10%, and the color developing reagent is a DAB color developing solution or a Tyramide signal amplification reagent; the color developing reagent includes a DAB substrate solution, the concentration of the DAB substrate solution is 0.02 mg / mL to 0.05 mg / mL, and is combined with 0.01% to 0.03% hydrogen peroxide.

[0030] Colorimetric reagent: DAB colorimetric reagent: Components: DAB substrate solution (0.02 mg / mL ~ 0.05 mg / mL), H2O2 working solution (0.01% ~ 0.03%), diluted in 0.05M Tris-HCl buffer (pH 7.6).

[0031] Tyramide signal amplification reagent: Components: Biotinylated tyramine (0.01 mg / mL to 0.03 mg / mL), mixed with horseradish peroxidase (HRP) complex solution.

[0032] The antigen repair solution has a mass fraction of 5% to 15%, and the antigen repair solution is a citric acid buffer or an EDTA buffer; the antigen repair solution is a 0.01M to 0.05M citric acid buffer with a pH of 6.0 to 7.0, or a 0.01M to 0.05M EDTA buffer with a pH of 8.5 to 9.5.

[0033] Components: Citrate buffer (pH 6.0) or EDTA buffer (pH 9.0).

[0034] Ratio: Buffer concentration is 0.01M~0.05M.

[0035] Blocking reagent, mass percentage is 2% to 10%; Components: 5% BSA or 5% skimmed milk powder solution, containing 0.05% to 0.1% sodium azide.

[0036] Ratio: Diluted in 0.01M PBS.

[0037] Stabilizer, mass percentage is 0.1% to 1%; The antibodies and reagents were prepared with phosphate buffered saline, with the balance being 100%.

[0038] The following are the preparation methods of each component: Preparation and purification of bi-epitope antibodies: Phage display screening: Using recombinant PD-L1 protein (expression region of amino acids 19-239) as the target, high-affinity single-chain antibodies (scFv) against PD-L1 were screened through phage display library.

[0039] Molecular simulation technology is used to predict the dynamic process of antibody binding to PD-L1 protein and screen the antibody epitope combination with the lowest binding free energy.

[0040] Screening conditions: target protein concentration is 0.5µg / mL~1.0µg / mL, and binding time is 1 hour~2 hours.

[0041] Elution conditions: Use 0.2 M glycine-HCl (pH 2.2) to elute the bound phage.

[0042] Two antibody fragments with different epitopes are connected through a flexible peptide chain (such as Gly4Ser) to construct a dual-epitope antibody.

[0043] HEK293 cells were transfected to express antibodies, and after purification, affinity purification was performed using a Protein A column.

[0044] The affinity constant (Kd) of the antibody was determined using surface plasmon resonance (SPR) technology.

[0045] Standard: Kd value is less than 10 -9 M is a high affinity antibody.

[0046] Preparation of colorimetric reagent: Prepare DAB color development working solution: Take 1 mL of DAB stock solution (2 mg / mL), mix it with 9 mL of 0.01 M Tris-HCl buffer (pH 7.6), and add 0.1 mL of 3% H2O2 working solution.

[0047] Prepare Tyramide signal amplification reagent: Dissolve 0.01 mg / mL biotinylated tyramide in PBS and mix with HRP at a ratio of 1:50 to 1:100 before use.

[0048] Preparation of antigen retrieval solution: Prepare citrate buffer (pH 6.0): Mix 0.1 M citric acid and 0.1 M sodium citrate solutions and adjust the pH to 6.0.

[0049] Prepare EDTA buffer (pH 9.0): dissolve 0.05M EDTA in distilled water and adjust the pH to 9.0 with NaOH. Preparation of blocking reagent: Dissolve 5% BSA in PBS buffer, add sodium azide (0.05%), and dissolve at 37°C for 15 to 30 minutes.

[0050] Slide Pretreatment: Soak the slide in 0.01% transparent poly-lysine solution and dry it at room temperature for later use.

[0051] Tissue section preparation: Tumor tissues were fixed in 10% neutral buffered formalin for 12 to 24 hours.

[0052] Use paraffin embedding and the section thickness is 3µm to 5µm.

[0053] Antigen retrieval: Place the tissue sections in antigen retrieval solution and treat with high temperature and high pressure (95℃~100℃, 10 minutes to 20 minutes).

[0054] Staining steps: The bi-epitope antibody was added dropwise to the slices at a concentration of 0.55 µg / mL to 1.5 µg / mL and incubated at 37°C for 30 to 60 minutes.

[0055] Wash three times with PBS, 3 to 5 minutes each time.

[0056] Add HRP-conjugated secondary antibody dropwise and incubate at 37°C for 15 to 30 minutes.

[0057] Add Tyramide signal amplification reagent and incubate at room temperature for 10 to 20 minutes.

[0058] Use DAB color developing solution, and the color development time is 1 minute to 3 minutes.

[0059] The contrast was enhanced with nickel-EDTA solution at room temperature for 5 to 10 minutes.

[0060] Counterstain the cell nucleus with hematoxylin and seal the slide after soaking for 10 to 20 seconds.

[0061] Spatial omics data collection and analysis: Use fluorescent probes of different wavelengths to label markers such as PD-L1, PD-1, CD8, and FOXP3.

[0062] The concentration of the fluorescent probe is 0.1µg / mL to 0.5µg / mL, and the incubation time is 30 minutes to 60 minutes.

[0063] Use a fluorescence microscope or multimodal imaging platform to collect fluorescence signals.

[0064] The image resolution is set to 1µm / pixel to 2µm / pixel.

[0065] Apply deep learning models such as UNet to identify and segment tumor regions and immune cells.

[0066] Quantify the proportion of PD-L1 positive cells (TPS) and spatial distribution density.

[0067] By optimizing the sensitivity and specificity of PD-L1 immunohistochemistry detection, utilizing dual-epitope antibody design, dynamic signal amplification technology, and spatial omics analysis methods, we can address the shortcomings of existing detection methods in terms of false positives, false negatives, and subjective results, and ultimately achieve high-precision, high-throughput tumor immune diagnosis.

[0068] Preparation and mechanism of action of dual-epitope high-affinity antibodies Antibody design and screening: Through phage display technology, high-affinity antibody fragments (scFv) were screened from two independent active sites of PD-L1 protein.

[0069] Molecular simulation technology is used to predict the dynamic process of antibody binding to PD-L1 protein and screen the antibody epitope combination with the lowest binding free energy.

[0070] Two antibody fragments are connected through a flexible peptide chain (such as Gly4Ser) to construct a dual-epitope antibody.

[0071] Affinity Optimization: The antibody sequence was optimized by site-directed mutagenesis or random mutagenesis in the CDR (complementarity determining region) region.

[0072] Antibody affinity was determined by surface plasmon resonance (SPR) and the affinity constant (Kd) was less than 10 -9 Antibodies to M.

[0073] Antibody purification: HEK293 cells were used to express antibodies, and impurities were removed by Protein A affinity purification column. The design of dual-epitope antibodies improves the stability of antibody binding to PD-L1 protein through a multi-point binding model. Compared with single-epitope antibodies, dual-epitope antibodies can more effectively bind to PD-L1 molecules in low-expression areas while reducing the risk of disengagement during the binding process. In addition, multi-point binding can improve the adaptability of antibodies when PD-L1 conformation changes (such as phosphorylation or conformational changes), thereby significantly reducing the incidence of false negatives.

[0074] Application and principle of dynamic signal amplification and staining technology Tyramide Signal Amplification (TSA): During the color development process, HRP (horseradish peroxidase) is used to catalyze the deposition of biotinylated tyramide on the target antigen area.

[0075] The signal was further amplified by adding streptavidin-horseradish peroxidase complex.

[0076] Optimization of colorimetric reagents: Prepare DAB color development working solution (concentration 0.02 mg / mL to 0.05 mg / mL) and mix it with 0.01% to 0.03% hydrogen peroxide.

[0077] For staining of low-expressing areas, use an intensifying chromogen (such as nickel-EDTA) to improve contrast.

[0078] Dynamic signal amplification loop: For low expression areas, multiple rounds of TSA cycles were performed, with each round of color development time ranging from 1 minute to 3 minutes, and the maximum number of rounds was no more than 3 times.

[0079] Tyramide signal amplification technology is based on the principle of catalytic deposition, which significantly improves the staining signal intensity of the target antigen. Through dynamic cyclic amplification, it can effectively enhance the signal in areas with low PD-L1 expression, while avoiding over-saturation of color in areas with high expression. The mechanism of dynamic signal amplification is to utilize the cumulative deposition of HRP-catalyzed substrates to achieve signal enhancement at low antigen concentrations, thereby improving the sensitivity and signal-to-noise ratio of detection.

[0080] Antigen retrieval and background noise suppression Preparation of antigen retrieval solution: Treat the sections with 0.01M-0.05M citric acid buffer (pH 6.0-7.0) or EDTA buffer (pH 8.5-9.5).

[0081] High temperature and high pressure repair conditions: 95℃~100℃, time 10 minutes to 20 minutes.

[0082] Background noise suppression: Double blocking was performed using 5% BSA and Fc fragment blocking antibody.

[0083] Before tissue staining, use 0.01% to 0.05% sodium azide solution to reduce nonspecific binding.

[0084] Mechanism analysis: Antigen retrieval restores the natural conformation of PD-L1 protein by destroying the cross-linked structure caused by formaldehyde fixation, while exposing its antibody binding epitope, thereby improving the specificity and sensitivity of staining. The mechanism of background noise suppression is to use non-specific proteins (such as BSA) or specific blockers (Fc fragment antibodies) to fill non-specific binding sites on the slice to prevent non-specific binding of antibodies to non-target proteins.

[0085] Spatial omics and multimodal fluorescence labeling analysis Multi-target fluorescent labeling: Select a variety of fluorescent probes to label antibody targets: such as PD-L1 (green), PD-1 (red), CD8 (blue), and FOXP3 (yellow).

[0086] The concentration of the fluorescent probe is 0.1µg / mL to 0.5µg / mL, and the incubation time is 30 minutes to 60 minutes.

[0087] Spatial data collection and analysis: Images were collected using a high-resolution fluorescence microscope with a pixel resolution of 1µm to 2µm.

[0088] Apply deep learning algorithms (such as the UNet model) to automatically identify and segment tumor cells and immune cell areas.

[0089] Construct a scoring model based on spatial distribution, including: Spatial activity score: The distribution density of PD-L1 and CD8 is combined to evaluate the immune activity.

[0090] Inhibition score: Immunosuppression status was assessed based on the spatial overlap between PD-L1 and FOXP3.

[0091] Spatial omics combined with fluorescent labeling technology can intuitively reflect the spatial relationship between PD-L1 expression and immune cell distribution. The multi-channel characteristics of fluorescent labeling ensure the independent detection of different targets, while the spatial clustering algorithm can identify the distribution characteristics of tumors and immune cells in different regions. By quantifying these distribution characteristics, the dynamic equilibrium state of the tumor immune microenvironment can be evaluated from a spatial dimension, providing a basis for accurate diagnosis.

[0092] This technical solution achieves the upgrade of PD-L1 detection from qualitative staining of a single marker to spatial quantitative analysis of multiple targets through the combination of dual-epitope antibody optimization, dynamic signal amplification, antigen repair and spatial omics analysis. Its core mechanism is to improve the detection sensitivity by high-affinity antibody design, enhance the signal in low-expression areas by signal amplification technology, and evaluate the dynamics of the immune microenvironment by spatial omics, thereby comprehensively improving the accuracy and clinical applicability of PD-L1 immunohistochemistry detection.

[0093] Please refer to the attached Figure 1 As part of the present invention, the present application also provides an embodiment of an immunohistochemical detection method for PD-L1, comprising the following steps: S1. placing the fixed tissue sections in an antigen repair solution for antigen repair; the antigen repair step is to place the tissue sections in an antigen repair solution and treat at 95°C to 100°C for 10 minutes to 20 minutes; S2. Add dual-epitope high-affinity anti-PD-L1 monoclonal antibody dropwise for primary antibody incubation; in the antibody incubation step, the antibody concentration is 0.5µg / mL to 1.5µg / mL, the incubation temperature is 37°C, and the incubation time is 30 minutes to 60 minutes; S3. Add a colorimetric reagent for color development; in the color development step, the color development time is 1 minute to 3 minutes, and the colorimetric reagent includes a DAB substrate solution or a Tyramide signal amplification reagent; S4. Perform nuclear counterstaining, dehydration and sealing on the stained sections; S5. The staining results were observed under a microscope and quantitatively analyzed using image analysis software. The obtained data included the positive ratio of PD-L1 expression level.

[0094] According to the above implementation steps, the following embodiments are provided: Example 1: Highly sensitive immunohistochemical detection of PD-L1 based on dual-epitope antibodies Experimental steps: Tissue sample preparation: Patients' lung cancer tissues were fixed in 10% neutral buffered formalin for 18 hours. They were then embedded in paraffin and sliced ​​at a thickness of 4 µm. The tissues were attached to glass slides pre-coated with clear poly-lysine.

[0095] Antigen repair: Take the slices, put them into 0.01M EDTA buffer (pH 9.0), and treat them in a 95℃ autoclave for 15 minutes. After cooling, wash them with distilled water 3 times, 2 minutes each time.

[0096] Antibody incubation: Add the dual-epitope high-affinity anti-PD-L1 antibody working solution dropwise, with an antibody concentration of 1µg / mL. Incubate the sections at 37°C for 45 minutes, then wash three times with 0.01M PBS, 3 minutes each time.

[0097] Signal amplification and color development: Add HRP-labeled secondary antibody, incubate for 20 minutes, then wash. Then add Tyramide signal amplification reagent and incubate at room temperature for 10 minutes. Finally, treat with DAB color development solution for 2 minutes, and terminate the reaction with distilled water after color development.

[0098] Counterstaining and sealing: Counterstain the cell nucleus with hematoxylin solution for 10 seconds, then dehydrate, make transparent, and seal with neutral resin.

[0099] Test results: After staining, the low-expression area of ​​PD-L1 showed a clear brown signal, and the high-expression area did not show excessive color or background staining. Compared with traditional single-epitope antibodies, the signal-to-noise ratio was improved by more than 30%.

[0100] Effect: This embodiment improves the detection sensitivity of low-expression PD-L1 through the combination design of dual-epitope antibodies, and solves the problem of missed detection in low-expression areas in the prior art.

[0101] Example 2: Application of dynamic signal amplification technology in weak positive samples Experimental steps: Sample preparation: Pathological tissues from gastric cancer patients were collected and fixed for 12 hours. The slices were 5 µm thick and antigen repaired with EDTA buffer (pH 9.0) for 20 minutes.

[0102] Double-round signal amplification: After adding anti-PD-L1 monoclonal antibody (1µg / mL), incubate at 37°C for 40 minutes. Add HRP-labeled secondary antibody and incubate for 15 minutes. Add Tyramide signal amplification reagent before color development, and the first round of color development time is 3 minutes. After washing, repeat the amplification process, and the second round of color development time is 2 minutes.

[0103] Termination of staining and sealing: After washing with PBS, stop the color development, counterstain with hematoxylin and seal the slides.

[0104] Test results: In weakly positive samples, the low signal area of ​​PD-L1 expression was significantly amplified, and the staining signal showed a stable and clear brown-yellow color. Signal amplification avoids the problem of insufficient signal in weakly positive samples by traditional color development.

[0105] Effect: Dynamic signal amplification technology is used to enhance the color rendering effect in weak signal areas, solving the problem that low-concentration PD-L1 signals are easily masked by the background.

[0106] Example 3: Application of spatial omics analysis in tumor microenvironment Experimental steps: Breast cancer tissue samples were used, with a slice thickness of 3 µm. Fluorescence labeling technology was used to label PD-L1, PD-1, CD8, and FOXP3 with green, red, blue, and yellow fluorescent probes, respectively, with a concentration of 0.3 µg / mL and an incubation time of 30 minutes.

[0107] The sections were scanned with a fluorescence microscope at a resolution of 1 µm / pixel, and the fluorescence intensity and spatial distribution of each target were recorded.

[0108] The deep learning model was used to identify tumor cells and immune cell regions, calculate the PD-L1 expression density and the distance distribution of CD8 positive cells, and analyze the degree of immunosuppression in PD-L1 positive regions.

[0109] Test results: The expression of PD-L1 in the tumor border area was significantly higher than that in the tumor center area. CD8+T cells mainly gathered around the PD-L1 high expression area, while FOXP3+ cells were concentrated in the tumor center.

[0110] Effect: This example reveals the dynamic relationship between PD-L1 and immune cells in the tumor microenvironment through multi-target spatial omics analysis, making up for the deficiency of traditional detection in providing spatial information.

[0111] Example 4: Application of background noise suppression in high background tissue Experimental steps: Colon cancer tissues were processed. After antigen retrieval, a double blocking scheme was used: the surface of the sections was first treated with 5% BSA for 10 minutes, and then treated with Fc fragment blocking antibody for 15 minutes.

[0112] Anti-PD-L1 antibody (concentration 0.8 µg / mL) was added dropwise and incubated at 37°C for 30 minutes. DAB colorimetric solution was used for color development for 1 minute.

[0113] Test results: The background staining of tissue sections was significantly reduced, the PD-L1 positive signal remained clear, and the brown staining area contrasted sharply with the background.

[0114] Effect: Double blocking technology successfully reduces nonspecific binding, optimizes staining specificity and result clarity, and is particularly suitable for the detection needs of high background tissues.

[0115] Example 5: Application of multidimensional scoring in immunotherapy screening Experimental steps: Sample multi-target labeling, non-small cell lung cancer tissue samples were selected, and anti-PD-L1, PD-1 and CD8 antibodies were used for multi-target labeling. Tyramide signal amplification technology was used to enhance the staining signal.

[0116] The immune activity score (SAS) was calculated based on the proportion of PD-L1 positive cells in the tumor (TPS) and the overlapping distribution of PD-L1 positive areas and CD8+ T cells. At the same time, the proportion of FOXP3 positive cells was counted to calculate the immunosuppression score (SI).

[0117] Test results: The SAS score of highly active samples was greater than 70%, while the SI score of highly inhibited samples was close to 90%.

[0118] Effect: Combined with multi-dimensional scoring, this embodiment significantly improves the ability to screen patients with potential response to immunotherapy and solves the problem of insufficient diagnostic information from single marker detection.

[0119] In order to highlight the innovation of the present invention in terms of sensitivity, specificity, background noise suppression, multi-target spatial omics analysis, etc., the following comparative examples are designed corresponding to the embodiments. The comparative examples are based on traditional methods or prior art solutions, and reflect the differences between the present invention and the prior art solutions in key technical points by fine-tuning parameters and omitting some technical processing.

[0120] Comparative Example 1: Application of single epitope antibody in PD-L1 detection Corresponding Example 1: Preparation and detection of dual-epitope high-affinity antibodies Experimental process: Tissue sample preparation: Lung cancer tissue samples were collected from patients and fixed in 10% neutral buffered formalin for 18 h. The slice thickness was 4 µm.

[0121] Antigen retrieval: Use 0.01M EDTA buffer (pH 9.0) for antigen retrieval at 95°C for 15 minutes.

[0122] Antibody incubation: Use a single epitope anti-PD-L1 antibody (22C3 monoclonal antibody) at a concentration of 1µg / mL, and incubate the sections at 37°C for 30 minutes. After incubation, wash with PBS three times, 3 minutes each time.

[0123] Color development: Add HRP-labeled secondary antibody and incubate at room temperature for 15 minutes, followed by DAB color development solution for 3 minutes.

[0124] Counterstaining and sealing: Counterstain the cell nuclei with hematoxylin and seal the slides after dehydration.

[0125] Key difference: The control group used a single-epitope antibody for detection, no dual-epitope antibody was used, and the antibody was not affinity optimized.

[0126] Comparative Example 2: PD-L1 immunohistochemistry detection without signal amplification Corresponding Example 2: Application of Dynamic Signal Amplification Technology in Weakly Positive Samples Experimental process: Sample preparation: Tissue samples from gastric cancer patients were collected, fixed for 12 hours, and sliced ​​to a thickness of 5 µm.

[0127] Antigen retrieval: Use 0.01M EDTA buffer (pH 9.0) for antigen retrieval at 100°C for 20 minutes.

[0128] Antibody incubation: PD-L1 monoclonal antibody was used at a concentration of 1 µg / mL, and the sections were incubated at 37°C for 40 minutes. After incubation, the sections were washed three times with PBS.

[0129] Color development: Add HRP-labeled secondary antibody, incubate for 15 minutes, and then directly add DAB color development solution for 3 minutes.

[0130] Counterstaining and sealing: Counterstain the sections with hematoxylin and seal the sections after dehydration.

[0131] Key difference: The comparative example omitted the Tyramide signal amplification step and only used direct DAB color development.

[0132] In order to highlight the innovation of the present invention in terms of sensitivity, specificity, background noise suppression, multi-target spatial omics analysis, etc., the following comparative examples are designed corresponding to the embodiments. The comparative examples are based on traditional methods or prior art solutions, and reflect the differences between the present invention and the prior art solutions in key technical points by fine-tuning parameters and omitting some technical processing.

[0133] Comparative Example 1: Application of single epitope antibody in PD-L1 detection Corresponding Example 1: Preparation and detection of dual-epitope high-affinity antibodies Experimental process: Tissue sample preparation: Lung cancer tissue samples were collected from patients and fixed in 10% neutral buffered formalin for 18 h. The slice thickness was 4 µm.

[0134] Antigen retrieval: Use 0.01M EDTA buffer (pH 9.0) for antigen retrieval at 95°C for 15 minutes.

[0135] Antibody incubation: Use a single epitope anti-PD-L1 antibody (22C3 monoclonal antibody) at a concentration of 1µg / mL, and incubate the sections at 37°C for 30 minutes. After incubation, wash with PBS three times, 3 minutes each time.

[0136] Color development: Add HRP-labeled secondary antibody and incubate at room temperature for 15 minutes, followed by DAB color development solution for 3 minutes.

[0137] Counterstaining and sealing: Counterstain the cell nuclei with hematoxylin and seal the slides after dehydration.

[0138] Key difference: The control group used a single-epitope antibody for detection, no dual-epitope antibody was used, and the antibody was not affinity optimized.

[0139] Comparative Example 2: PD-L1 immunohistochemistry detection without signal amplification Corresponding Example 2: Application of Dynamic Signal Amplification Technology in Weakly Positive Samples Experimental process: Sample preparation: Tissue samples from gastric cancer patients were collected, fixed for 12 hours, and sliced ​​to a thickness of 5 µm.

[0140] Antigen retrieval: Use 0.01M EDTA buffer (pH 9.0) for antigen retrieval at 100°C for 20 minutes.

[0141] Antibody incubation: PD-L1 monoclonal antibody was used at a concentration of 1 µg / mL, and the sections were incubated at 37°C for 40 minutes. After incubation, the sections were washed three times with PBS.

[0142] Color development: Add HRP-labeled secondary antibody, incubate for 15 minutes, and then directly add DAB color development solution for 3 minutes.

[0143] Counterstaining and sealing: Counterstain the sections with hematoxylin and seal the sections after dehydration.

[0144] Key difference: The comparative example omitted the Tyramide signal amplification step and only used direct DAB color development.

[0145] Comparative Example 3: Multi-target detection without fluorescent labeling Corresponding Example 3: Application of spatial omics analysis in tumor microenvironment Experimental process: Sample and antibody incubation: Breast cancer tissue samples were collected and sliced ​​to a thickness of 3 µm. PD-L1, CD8, and FOXP3 were stained sequentially using conventional immunohistochemical staining methods. Each round of staining used DAB staining solution, and the staining time was 3 minutes.

[0146] Color development sequence and blocking: After each round of staining, wash with PBS three times, block with 5% BSA for 10 minutes, and then proceed to the next round of staining.

[0147] Multiple rounds of staining and mounting: Finally, counterstain the cell nuclei and mount the slides with neutral resin.

[0148] Key difference: The control group did not use fluorescent labeling technology, but adopted multiple rounds of DAB staining to achieve multi-target detection, and could not perform spatial distribution analysis.

[0149] Comparative Example 4: Application of Single Closure Scheme in Background Noise Suppression Corresponding Example 4: Application of Background Noise Suppression in High Background Tissue Experimental process: Sample and blocking treatment: Colon cancer tissue samples were collected, and after antigen retrieval, only 5% BSA was used to block the surface of the sections for 10 minutes.

[0150] Antibody incubation and color development: Use PD-L1 monoclonal antibody (concentration 1µg / mL) and incubate at 37°C for 30 minutes. Then add HRP-labeled secondary antibody and incubate for 15 minutes. Use DAB color development solution for 2 minutes.

[0151] Key difference: The comparative example only used a single blocking step (BSA blocking) and did not use a double blocking scheme (BSA + Fc fragment blocking antibody).

[0152] Comparative Example 5: PD-L1 detection without multidimensional scoring Corresponding Example 5: Application of multi-dimensional scoring in immunotherapy screening Experimental process: Sample and antibody incubation: Non-small cell lung cancer tissue samples were collected and stained with PD-L1 antibody, and the staining signal was processed with DAB colorimetric solution.

[0153] Scoring method: Only the traditional tumor positive proportion (TPS) scoring method was used, which was based on the proportion of PD-L1 positive cells to total tumor cells.

[0154] Key difference: The control group did not combine spatial omics methods or multidimensional scoring models, but only used a single TPS scoring method, which was unable to evaluate immune activity and suppression status.

[0155] The above comparative examples all simplify or omit the innovative points of the present invention in a certain key technical step, and revolve around six core technical points: dual-epitope antibodies, dynamic signal amplification, spatial omics, multi-target fluorescent labeling, background noise suppression and multidimensional scoring, fully highlighting the advantages of the present invention in technical innovation and practicality.

[0156] For the above-mentioned embodiments and comparative examples, a one-to-one single factor comparison was conducted to verify the technical advantages of the present invention in terms of sensitivity, specificity, signal-to-noise ratio, spatial omics analysis, and multidimensional scoring. All experiments were strictly carried out around the above-mentioned embodiments and comparative examples to ensure clear comparison logic and highlight the innovation of the present invention.

[0157] Experiment 1: Comparison of detection effects of dual-epitope antibodies and single-epitope antibodies in low-expression samples Experimental procedures Sample preparation: Tissue samples of 5 non-small cell lung cancer (NSCLC) with low expression of PD-L1 were collected. The samples were fixed in 10% neutral buffered formalin for 18 hours. After paraffin embedding, the sections were sliced, and the thickness of the sections was set to 4µm. The sections were attached to transparent poly-lysine-coated slides and dried at room temperature.

[0158] Antigen retrieval: Place the sections in 0.01M EDTA buffer (pH 9.0) and treat in a 95°C autoclave for 15 minutes. After cooling to room temperature, wash with distilled water three times, 2 minutes each time.

[0159] Antibody incubation: Example 1: Add a dual-epitope high-affinity antibody (concentration 1µg / mL) to cover the slice area and incubate at 37°C for 45 minutes. Comparative Example 1: Add a single-epitope antibody (concentration 1µg / mL) and incubate for 30 minutes. After incubation, wash with PBS 3 times, 3 minutes each time.

[0160] Color development: Add HRP-labeled secondary antibody and incubate at room temperature for 15 minutes. Then use DAB color development solution (concentration 0.03 mg / mL) to treat the slices for 2 minutes. After the color development is completed, rinse with distilled water to terminate the reaction.

[0161] Counterstaining and sealing: Use hematoxylin to counterstain the sections for 10 seconds, dehydrate, and seal with neutral resin. The sealed samples are observed under a microscope.

[0162] Data acquisition and analysis: Use a microscope to take staining images of low-expression areas. Use image analysis software to calculate the PD-L1 positive cell ratio (TPS) and signal-to-noise ratio (SNR) of each sample.

[0163] Table 1: Comparison of detection effects of dual-epitope antibodies and single-epitope antibodies in samples with low PD-L1 expression: In this experiment, two high-affinity epitopes were bound to different active regions of the PD-L1 molecule through a dual-epitope antibody design. This design significantly improves the antibody's ability to bind to the target protein, especially in low-expression samples, where the dual-epitope antibody can capture more weak PD-L1 signals. However, when the target is scarce, the detection sensitivity of single-epitope antibodies is obviously insufficient, and many positive signals are ignored. Mechanistically, the multi-point binding model improves the binding stability, allowing the antibody to maintain efficient binding ability at low antigen concentrations.

[0164] In addition, the affinity optimization of the dual-epitope antibody is one of the keys to this experiment. By site-directed mutagenesis of the antibody CDR region, the binding constant (Kd) of the antibody was significantly reduced to 10 -9 M. This high affinity directly translates into stronger signal capture capabilities, especially in areas with low antigen concentration distribution. In contrast, single-epitope antibodies cannot effectively detect these areas due to affinity limitations, resulting in more prominent false negative problems.

[0165] The experiment also showed that the signal-to-noise ratio of the dual-epitope antibody was significantly better than that of the single-epitope antibody. In terms of background staining suppression, the dual-epitope antibody reduced the nonspecific staining area through stronger specific binding, thereby improving the clarity of detection. This shows that the present invention not only enhances the detection signal in low-expression samples, but also improves the background interference problem caused by nonspecific binding in traditional methods. This double improvement further verifies the rationality and scientificity of the dual-epitope antibody design.

[0166] Experiment 2: Dynamic signal amplification improves detection of weak positive signals Experimental procedures Sample preparation: Weakly positive PD-L1 expression tissues of gastric cancer were selected from 3 patients and fixed in 10% neutral buffered formalin for 12 hours. After paraffin embedding, the slice thickness was set to 5µm and attached to a transparent poly-lysine-coated slide.

[0167] Antigen retrieval: The sections were placed in 0.01M EDTA buffer (pH 9.0) and treated in a 100°C water bath for 20 minutes. After cooling to room temperature, they were washed three times with distilled water for 1 minute each time.

[0168] Antibody incubation: Example 2: Anti-PD-L1 monoclonal antibody (concentration 1 µg / mL) was added dropwise and incubated at 37°C for 40 minutes. Then washed 3 times, 2 minutes each time. Comparative Example 2: The treatment method was the same as Example 2, with the same antibody concentration and incubation time.

[0169] Signal amplification and color development: Example 2: First, add HRP-labeled secondary antibody, incubate at room temperature for 20 minutes, and then wash. Then add Tyramide signal amplification reagent, perform two rounds of amplification, and the color development time for each round is 3 minutes and 2 minutes respectively, and rinse with distilled water between rounds. Comparative Example 2: After adding HRP-labeled secondary antibody, directly use DAB color development solution for 3 minutes, without signal amplification step.

[0170] Counterstaining and sealing: Counterstain the nuclear area of ​​the slice with hematoxylin for 8 seconds. After dehydration, seal the slice with neutral resin.

[0171] Data collection and analysis: Use an optical microscope to take slice images and record the color signal intensity of the weak positive area. At the same time, the signal-to-noise ratio (SNR) and the area of ​​the positive area are measured by image analysis software. Table 2: Comparative data of dynamic signal amplification and non-amplification processing for weak positive area detection: Dynamic signal amplification technology provides a new solution for the detection of weak positive samples. In this experiment, through Tyramide signal amplification, two rounds of color development significantly enhanced the weak signal of PD-L1, making the positive staining in low expression areas clearer. The first round of amplification captured the weak antigen binding signal, and the second round of amplification further enhanced the staining contrast. In contrast, signal amplification was not used in the comparative example, and the results showed that the signal intensity in the weak positive area was significantly lower than that in the embodiment. This improvement comes directly from the recycling of HRP catalytic deposition in the amplification technology, which enables color development in areas with scarce antigens.

[0172] The experiment also showed that signal amplification not only improved the signal-to-noise ratio, but also optimized the detection area of ​​the positive region. In terms of background noise processing, the specificity of Tyramide amplification significantly reduced nonspecific deposition, and this effect stems from the enhanced targeting of the catalytic reaction. Mechanistically, multiple rounds of dynamic amplification make the signal output after antibody binding more persistent, while avoiding the problem of oversaturation in highly expressed areas. This design takes into account both sensitivity and specificity.

[0173] In addition, the hierarchical amplification mechanism of dynamic amplification also provides a larger experimental control space. By adjusting the time of each round of amplification, the antigen expression characteristics of different samples can be accurately matched. The traditional direct DAB color development method has almost no signal in the low-concentration antigen area, and the dynamic amplification technology of the present invention successfully captures this hidden information, providing a more reliable tool for the immune diagnosis of low-positive patients. The experimental results fully prove that the present invention not only improves the detection ability of weak signal areas, but also enhances the visibility and repeatability of staining results.

[0174] Experiment 3: Comparison of fluorescent labeling technology and traditional DAB staining in multi-target detection Experimental procedures Sample preparation: Breast cancer patient tissue samples were collected, embedded in paraffin and sliced ​​to a thickness of 3 μm. The slices were fixed on transparent poly-lysine slides and air-dried at room temperature for 12 hours. Five slices were prepared and divided into three groups of Example and three groups of Comparative Examples.

[0175] Antigen retrieval: Use 0.01M EDTA buffer (pH 9.0) to perform antigen retrieval on the sections in a 100°C water bath for 15 minutes. After retrieval, cool to room temperature and wash with distilled water three times.

[0176] Labeling and detection: Example 3 (fluorescent labeling technology): PD-L1, PD-1, CD8, and FOXP3 in the slices were labeled with green, red, blue, and yellow fluorescent probes, respectively. The concentration of the fluorescent probe was 0.3 µg / mL, and the incubation time was 30 minutes. After each round of labeling, PBS was used for washing 3 times, each time for 3 minutes.

[0177] Images were collected at a resolution of 1µm / pixel using a multi-channel fluorescence microscope to record the spatial distribution and fluorescence signal intensity of each target. Comparative Example 3 (traditional DAB staining): PD-L1, CD8, and FOXP3 were stained in sequence using DAB colorimetric solution (concentration 0.03mg / mL), and each round of color development lasted for 3 minutes. After each round of color development, the sections were washed 3 times with PBS, and then sealed for the next round of staining. Finally, hematoxylin was counterstained, dehydrated, and the sections were sealed. The slice images after multiple rounds of staining were observed using an optical microscope to record the color distribution of the targets.

[0178] Data acquisition: Image analysis software was used to compare the signal resolution, spatial distribution accuracy, and detection efficiency of targets in the two groups of samples in areas where multiple targets coexisted.

[0179] Table 3: Comparative data of fluorescent labeling technology and traditional DAB staining in multi-target detection: The performance of fluorescent labeling technology in multi-target detection is impressive. Experimental results show that compared with traditional DAB staining, the spatial distribution accuracy of fluorescent labeling in areas where multiple targets coexist is significantly improved. This is due to the independent labeling characteristics of fluorescent probes, which allows the signal of each target to be clearly distinguished without cross-interference between color developers. When DAB staining is repeated for multiple rounds, the background staining is easily increased due to the superposition of color developers, which interferes with signal recognition.

[0180] Improving signal resolution is particularly critical. Fluorescent labeling combined with high-resolution microscopy enables high-precision detection of target signals. In areas where multiple targets coexist, fluorescent labeling can intuitively demonstrate the co-expression relationship between PD-L1 and other immune markers. In contrast, the insufficient resolution of DAB staining makes the target boundaries blurred, especially in the complex microenvironment of tumor boundaries. Traditional methods have difficulty in clearly distinguishing the coexistence of multiple targets.

[0181] From a mechanistic point of view, the advantages of fluorescent labeling lie in its specificity and flexibility. The wavelength of each fluorescent probe is independent and non-overlapping, which enables true spatial separation of multi-target labeling in the same slice. This technology breaks through the limitation of traditional DAB staining that cannot achieve efficient multi-target labeling, and provides a new perspective for comprehensive analysis of the tumor microenvironment. At the same time, the combination of fluorescent labeling technology and the spatial analysis capability of AI algorithms further amplifies its application potential in precise immune detection. This improvement not only improves detection efficiency, but also lays a solid foundation for multi-dimensional tumor diagnosis.

[0182] Experiment 4: Verification of the effectiveness of the double-blocking scheme in background noise suppression Experimental procedures Sample preparation: Colon cancer tissue samples were collected and fixed in 10% neutral buffered formalin solution for 12 hours. The tissues were embedded in paraffin and sliced, and the slice thickness was set to 4 μm. The samples were divided into 4 groups of embodiments and 4 groups of comparative examples, and 5 slices were prepared for each group.

[0183] Antigen retrieval: The sections were placed in 0.01 M citric acid buffer (pH 6.0) and antigen retrieval was performed in a 100°C water bath for 20 minutes. After cooling, they were washed three times with distilled water for 1 minute each time.

[0184] Blocking steps: Example 4: The slices were first blocked with 5% BSA solution for 10 minutes. Then, Fc fragment blocking antibody was added dropwise and incubated for 15 minutes. After each step, it was washed with PBS 3 times, each time for 3 minutes. Comparative Example 4: The slices were only blocked with 5% BSA solution for 10 minutes, and then directly incubated with antibodies without Fc fragment blocking step.

[0185] Antibody incubation and color development: Anti-PD-L1 monoclonal antibody (concentration 1µg / mL) was added, and the sections were incubated at 37°C for 30 minutes in two groups. After incubation, the sections were washed with PBS three times, each for 2 minutes. DAB color development solution (concentration 0.03mg / mL) was used for color development, and the color development time was 2 minutes.

[0186] Counterstaining and mounting: Counterstain the nuclear area of ​​the slice with hematoxylin for 10 seconds. Then dehydrate the slice and mount it with neutral resin.

[0187] Data acquisition and analysis: Observe the staining results under a microscope and take slice images. Use image analysis software to quantify the background noise intensity and positive signal area and calculate the signal-to-noise ratio (SNR).

[0188] Table 4: Comparative data of double-blocking and single-blocking schemes in background noise suppression: The experimental data clearly reflect the significant inhibitory effect of the double blocking scheme on background noise. The initial blocking of BSA solution can effectively shield nonspecific binding sites in the slice, but its effect is obviously limited for high background noise in complex tissues (such as colon cancer). After the introduction of Fc fragment blocking antibody, the binding of antibody to non-target proteins is further blocked. This targeted blocking method greatly reduces the intensity of background staining and directly improves the contrast of positive signals.

[0189] From a mechanistic analysis, BSA mainly reduces nonspecific binding by competitively binding to hydrophobic sites on the surface of the slice, but cannot accurately identify the nonspecific binding behavior of Fc receptors. Fc fragment blocking antibodies specifically target immunoglobulin Fc receptors in slices, blocking the ineffective binding of antibodies to non-target proteins. This feature makes the application of the present invention in complex tissues have greater advantages, especially in the case of high background noise.

[0190] In addition, the multi-layer protection mechanism of the double-blocking scheme also ensures the purity of the positive signal. A single blocking method is prone to form artifacts or diffusion effects around highly expressed targets, while double blocking accurately protects the signal quality around the target through a multi-layer blocking strategy. This design enhances the specificity of detection while avoiding false positive results caused by background staining. This experimental result not only verifies the technical advantages of the present invention, but also further illustrates the rationality of the mechanism, especially its superiority in complex tumor tissues.

[0191] Experiment 5: Comparison of single-dimensional TPS scoring and multi-dimensional scoring models in evaluating immune status Experimental procedures Sample preparation: Tissue samples from patients with non-small cell lung cancer (NSCLC) were selected, and 5 highly heterogeneous tumor sections were taken for comparative experiments. The section thickness was set to 4µm, and paraffin-embedded tissues fixed in 10% neutral buffered formalin were attached to transparent polylysine slides for 18 hours.

[0192] Antigen retrieval: Use 0.01M EDTA buffer (pH 9.0) and place the sections in a 100°C water bath for antigen retrieval for 20 minutes. After cooling, rinse with distilled water three times, 2 minutes each time.

[0193] Antibody labeling and incubation: Example 5 (multidimensional scoring model): PD-L1 (green fluorescence), CD8 (red fluorescence), and FOXP3 (blue fluorescence) were labeled respectively. The concentration of the fluorescent probe was 0.3 µg / mL, and the incubation time was 30 minutes. Wash with PBS 3 times after each round of labeling, each time for 2 minutes. Comparative Example 5 (single-dimensional TPS scoring): Use anti-PD-L1 monoclonal antibody and incubate at 37°C for 40 minutes. Use DAB colorimetric solution for color development for 3 minutes and then counterstain with hematoxylin.

[0194] Data collection and analysis: Example 5: Use a multi-channel fluorescence microscope to capture images and record the spatial distribution of PD-L1 and other markers (CD8, FOXP3). Combined with the AI ​​algorithm, calculate the immune activity score (SAS) and inhibition score (SI). Comparative Example 5: Use an optical microscope to capture slices, record the proportion of PD-L1 positive cells in tumor cells, and calculate the tumor positive ratio (TPS).

[0195] Table 5: Comparative data of single-dimensional TPS scoring and multi-dimensional scoring model in immune status assessment: The traditional TPS scoring model cannot fully reflect the complexity of the tumor microenvironment. It only considers the proportion of PD-L1 positive cells and is powerless to the dynamic balance of immune activity and inhibition. This experiment introduced spatial information and multi-target markers through a multidimensional scoring system, revealing the relationship between PD-L1 and other key immune markers (such as CD8 and FOXP3). Experimental data show that SAS and SI can more accurately reflect the activation and inhibition status of the immune microenvironment, providing more intuitive auxiliary decision-making for immunotherapy.

[0196] The key to multidimensional scoring is that it integrates spatial omics and quantitative analysis. In highly heterogeneous tumors, a single TPS score tends to underestimate or ignore local immune active areas. The present invention uses fluorescent labeling technology combined with AI analysis to quantify the coexistence of PD-L1 and immune cells in different regions. The SAS score directly reflects the degree of overlap between CD8-positive cells and PD-L1 high expression areas, while the SI score reveals the dominant role of immunosuppressive T cells (FOXP3 positive) in the tumor environment. This dynamic association is not provided by the TPS model.

[0197] From a mechanistic point of view, the calculation logic of SAS and SI is highly consistent with the actual structure of the tumor microenvironment. CD8 and FOXP3 are markers of immune activation and inhibition, respectively, and their overlapping relationship with PD-L1 distribution determines the immune response state of the tumor. The experimental results verified the rationality of the multi-dimensional scoring system, which breaks the limitation of single marker quantification and provides a new technical path for personalized immunotherapy.

[0198] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An immunohistochemical detection kit for PD-L1, characterized in that: Includes the following components: Dual-epitope high-affinity anti-PD-L1 monoclonal antibody, with a mass fraction of 0.5% to 5%; Colorimetric reagent, with a mass fraction of 1% to 10%, wherein the colorimetric reagent is DAB colorimetric solution or Tyramide signal amplification reagent; Antigen repair solution, with a mass percentage of 5% to 15%, wherein the antigen repair solution is a citric acid buffer or an EDTA buffer; Blocking reagent, mass percentage is 2% to 10%; Stabilizer, mass percentage is 0.1% to 1%; The antibodies and reagents were prepared with phosphate buffered saline, with the balance being 100%.

2. The immunohistochemical detection kit for PD-L1 according to claim 1, characterized in that: The dual-epitope high-affinity anti-PD-L1 monoclonal antibody connects two single-chain antibodies via a flexible peptide chain, and the single-chain antibodies target different active epitopes of PD-L1.

3. The immunohistochemical detection kit for PD-L1 according to claim 1, characterized in that: The dual-epitope high-affinity antibody is obtained by screening using phage display technology, and its affinity constant is less than 10 -9 M.

4. The immunohistochemical detection kit for PD-L1 according to claim 1, characterized in that: The color developing reagent comprises a DAB substrate solution, the concentration of the DAB substrate solution is 0.02 mg / mL to 0.05 mg / mL, and is mixed with 0.01% to 0.03% hydrogen peroxide.

5. The immunohistochemical detection kit for PD-L1 according to claim 1, characterized in that: The antigen repair solution is a 0.01M-0.05M citric acid buffer solution with a pH of 6.0-7.0, or a 0.01M-0.05M EDTA buffer solution with a pH of 8.5-9.

5.

6. An immunohistochemical detection method for PD-L1, characterized in that: Using the PD-L1 immunohistochemical detection kit according to any one of claims 1 to 5 comprises the following steps: S1. Place the fixed tissue sections in antigen retrieval solution for antigen retrieval; S2. Add dual-epitope high-affinity anti-PD-L1 monoclonal antibody dropwise for primary antibody incubation; S3. Add color developing reagent for color development; S4. Perform nuclear counterstaining, dehydration and sealing on the stained sections; S5. Observe the staining results under a microscope.

7. The immunohistochemical detection method of PD-L1 according to claim 6, characterized in that: The antigen repair step is to place the tissue section in an antigen repair solution and treat it at 95° C. to 100° C. for 10 to 20 minutes.

8. The immunohistochemical detection method of PD-L1 according to claim 6, characterized in that: In the antibody incubation step, the antibody concentration is 0.5 µg / mL to 1.5 µg / mL, the incubation temperature is 37° C., and the incubation time is 30 minutes to 60 minutes.

9. The immunohistochemical detection method of PD-L1 according to claim 6, characterized in that: In the step S3, the color development time is 1 minute to 3 minutes, and the color development reagent includes DAB substrate solution or Tyramide signal amplification reagent.

10. The immunohistochemical detection method of PD-L1 according to claim 6, characterized in that: The staining results were quantitatively analyzed under a microscope using image analysis software, and the resulting data included the positive ratio of the PD-L1 expression level.

Images