Lectin chip for predicting colorectal cancer immunotherapy sensitivity and preparation method and application thereof

Abstract

The invention relates to a lectin chip for predicting colorectal cancer immunotherapy sensitivity and a preparation method and application thereof, and belongs to the technical field of tumor therapy. According to the chip disclosed by the invention, three specific agglutinin probes are fixed on the surface of a solid-phase carrier in a dot matrix manner, and combined detection of at least three carbohydrate chains in human serum is realized by coating three specific agglutinin probes; the solid-phase carrier is a 14-hole three-dimensional modified glass slide and is used for fixing specific lectin as a probe; and the three specific lectin probes are respectively PHA-E, SNA-I and SSA. The lectin chip can be used for predicting colorectal cancer immunotherapy sensitivity.

Description

Technical Field

[0001] This invention relates to the field of tumor treatment technology, and in particular to a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, its preparation method and application. Background Technology

[0002] Among the predictive biomarkers for immunotherapy sensitivity in colorectal cancer (CRC), PD-L1 is used relatively more. Usually, PD-L1 is used to detect tumor tissue that needs to be removed, mainly through immunohistochemistry. The quantitative indicators are the positive percentage of tumor cells, the positive percentage of immune cells, and the overall positive score.

[0003] In actual clinical use, the accuracy of immunohistochemical detection of PD-L1 expression in predicting the efficacy of immunotherapy is only 50%. This is due to intratumoral heterogeneity; the same tumor tissue may show partial positive and partial negative expression, and may also undergo dynamic changes. Therefore, tissue PD-L1 expression levels cannot accurately predict the efficacy of immunotherapy. Furthermore, tissue PD-L1 testing requires obtaining tumor tissue, and due to the invasiveness and accessibility of tissue biopsies, many cancer patients cannot predict the effectiveness of immunotherapy.

[0004] Previous studies have found that PD-L1 expression in CRC tumor cells is modified by glycosylation, and glycosylated PD-L1 protein is more susceptible to immune escape by tumor cells. Glycosylation plays an important role in cell division and metastasis, immune response regulation, and intercellular communication in the tumor microenvironment, and is an important biomarker in tumor diagnosis, prognosis, and clinical management. Conventional PD-L1 detection uses immunohistochemistry to assess the total PD-L1 protein content in tissues, but cannot detect the content of glycosylated PD-L1. This is a major reason why tissue PD-L1 cannot accurately reflect the internal microenvironment of solid tumors. Detecting the glycosylation level of PD-L1-positive exosomals can avoid the interference of this factor and may be a novel predictive biomarker for immunotherapy efficacy. Therefore, there is an urgent need to find non-invasive immunotherapy predictive biomarkers that can obtain real-time molecular information about tumors to guide precision clinical treatment. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, as well as its preparation method and application.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, the chip comprising a solid support and lectin probes; the lectin probes are fixed on the surface of the solid support; the lectin probes are composed of PHA-E, SNA-I and SSA, each lectin being coated in different pores.

[0007] The chip of this invention has three specific lectin probes fixed in a dot matrix on the surface of a solid support. By coating each well with different three specific lectins, the chip can achieve the joint detection of at least three sugar chains in human serum. The solid support is a porous three-dimensional modified glass slide used to fix the specific lectins as probes. The three specific lectin probes are PHA-E, SNA-I, and SSA.

[0008] This invention identifies three lectin probes—PHA-E, SNA-I, and SSA—that are highly correlated with the sensitivity of colorectal cancer to immunotherapy through high-throughput screening. By combining the detection of these three lectins, the sensitivity of colorectal cancer to immunotherapy can be accurately predicted. The AUC and PRAUC of the combined detection model of the three lectins were verified to be 0.969 and 0.986, respectively.

[0009] Secondly, the present invention provides a method for preparing a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, comprising the following steps: (1) Diluted lectins, said lectins including PHA-E, SNA-I and SSA; (2) Spotting was performed on the spotting area of ​​the solid support using the method of repeated spotting of each lectin. PBS was spotted in the blank control area as a blank control and incubated at room temperature. (3) Dry the chip from step (2) to obtain the chip.

[0010] As a preferred embodiment of the second aspect, the lectin diluent used in step (1) is a phosphate buffer solution containing 4-5% glycerol.

[0011] As a preferred embodiment of the second aspect, the concentration of the lectin spotting in (2) is 150-200 µg / mL.

[0012] Thirdly, the present invention provides the application of the lectin chip described in the first aspect for predicting the sensitivity of colorectal cancer to immunotherapy in a kit for predicting the sensitivity of colorectal cancer to immunotherapy.

[0013] As a preferred embodiment of the third aspect, the method of using the colorectal cancer immunotherapy sensitivity prediction kit is as follows: (1) Centrifuge the plasma sample of a colorectal cancer patient to obtain the serum sample to be tested; (2) Add chromatography packing material to a multi-well plate, wash with PBS and seal the outlet at the bottom of the purification plate. Add serum sample to each well, incubate at room temperature and centrifuge. Collect the supernatant to obtain sample exosomes. (3) Add the exosomes from step (2) to the lectin chip as described in claim 1 to carry out a hybridization reaction; (4) Add Anti-PD-L1 to the lectin chip from step (3) and incubate at room temperature; (5) Add fluorescently labeled secondary antibody to the lectin chip from step (4) and incubate at room temperature; (6) Dry the chip, obtain the scanning signal using a laser scanner, read the fluorescence value of each well in the chip, and obtain the readings of PHA-E, SNA-I, and SSA in the sample. Substitute the obtained readings into the following formula to obtain the total value of the sample. Total value = 1.223 × SNA-Ⅰ + 2.152 × SSA - 0.895 × PHA-E; Wherein, SNA-Ⅰ, SSA, and PHA-E represent the fluorescence values ​​detected by the lectin, respectively; When the total number value is ≥2, it is determined to be PD-L1 resistance; when the total number value is <2, it is determined to be PD-L1 sensitivity.

[0014] As a preferred embodiment of the third aspect, the fluorescent dye in step (5) is Alexa Fluor® 488.

[0015] As a preferred embodiment of the third aspect, the incubation time for step (2) is 30 minutes; the incubation time for step (3) is 60 minutes; the incubation time for step (4) is 60 minutes; and the incubation time for step (5) is 60 minutes.

[0016] As a preferred embodiment of the third aspect, the amount of exosome sample added in step (3) is 100 μL; the amount of Anti-PD-L1 diluent added in step (4) is 100 μL; and the amount of fluorescent dye-labeled secondary antibody mixture added in step (5) is 100 μL.

[0017] Fourthly, the present invention provides a kit for predicting the sensitivity to immunotherapy for colorectal cancer, the kit comprising a lectin chip for predicting the sensitivity to immunotherapy for colorectal cancer as described in the first aspect.

[0018] As a preferred embodiment of the fourth aspect, the kit further includes a PD-L1 antibody, a fluorescently labeled secondary antibody, and PBS.

[0019] Fifthly, the present invention provides a biomarker for predicting the sensitivity to immunotherapy in colorectal cancer, said biomarker being an exosome, said exosome further satisfying the following conditions: (a) Serum source; (b) Surface expression of PD-L1 protein; (c) Surface expression of CD9, CD81 and CD63 proteins; (d) The surface has characteristic glycans that are captured by lectin probes, including PHA-E, SNA-I and SSA.

[0020] This invention has discovered that PD-L1 positive (PD-L1) antibodies can bind to lectins PHA-E, SNA-I, and SSA, respectively. + ), CD9 / CD81 / CD63 positive (i.e., CD9) + / CD81 + / CD63 + Serum-derived exosomes can be used to predict the sensitivity of colorectal cancer to immunotherapy.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention presents a novel technique for constructing lectin chips to identify PD-L1-positive exosome glycosylation modifications. It eliminates the need for a cumbersome exosome extraction process, requiring only 10 μL of clinical sample. It offers advantages such as high throughput, high sensitivity, and the ability to rapidly analyze the glycan characteristics of complex components. This facilitates the analysis of abnormal PD-L1 glycosylation modifications in the exosomes of cancer patients, providing a more sensitive and specific biomarker for predicting immunotherapy efficacy. Attached Figure Description

[0022] Figure 1 Schematic diagram of the CRC immunotherapy prediction model optimized for machine learning (Figure A is the OPLS-DA analysis of data obtained from lectin microarrays; Figure B is a schematic diagram of the ability of EVArray-Lectin lectinomics to distinguish between PD-L1-sensitive and PD-L1-resistant CRC patients by OPLS-DA analysis; Figure C is a schematic diagram of screening 10 key candidate lectins (VIPpred>2) by predictor variable importance score; Figures DE are the ROC curves (D) and PR curves (E) of the machine learning diagnostic model built based on the 10 candidate lectins; Figure F is a schematic diagram of variable importance score analysis in the random forest model of the 10 candidate lectins; Figures GH are schematic diagrams of AUC, PRAUC and classification error values ​​of the random forest algorithm model under different variable combinations; Figure I is the ROC curve of the model built based on PHA-E, SSA and SNA-I). Figure 2A schematic diagram illustrating the results of validating the model's effectiveness in a validation set of 40 patients; Figure 3 This is a schematic diagram illustrating the working principle of the reagent kit for predicting the sensitivity of colorectal cancer to immunotherapy according to the present invention. Detailed Implementation

[0023] To better illustrate the purpose, technical solution, and advantages of the present invention, the present invention will be further described below in conjunction with specific embodiments.

[0024] Example 1: Screening of specific lectins for predicting immunotherapy sensitivity in colorectal cancer Serum samples from 50 CRC patients before receiving PD-L1 therapy were collected from Shenzhen People's Hospital. Based on their subsequent sensitivity to immunotherapy, they were divided into a PD-L1 resistant group and a PD-L1 sensitive group, which served as the training set. Subsequently, 40 serum samples from CRC patients before receiving PD-L1 therapy were collected from Shenzhen People's Hospital as the validation set. We then used a lectin chip (vendor: EVbio, catalog number: EVL0056, specification: 14-wells) to perform comprehensive and in-depth analysis of exosomal glycosylation modifications in the serum samples, systematically depicting the differences in exosomal glycosylation profiles among CRC patients with different sensitivities to immunotherapy, as detailed below: (1) Preparation of serum samples to be tested: The plasma samples collected from colorectal cancer patients were centrifuged at 3000g at 4°C for 20 minutes, and the supernatant was then transferred to a new centrifuge tube to obtain serum; 20 μL of each sample was taken and diluted to 100 μL with 80 μL of PBS to obtain the serum sample to be tested. (2) Extraction of exosomes: Add 100 μL of Captocore 700 composite chromatography packing material to each well of a 96-well plate (purchased from DouDian Biotechnology Co., Ltd., catalog number 004901-20), add 500 μL of PBS to each well, centrifuge at 1000g for 30 seconds to pre-treat the purification plate, repeat the PBS washing twice, seal the outlet at the bottom of the purification plate, add 100 μL of diluted serum sample to each well, incubate at room temperature for 30 min, centrifuge at 1000g for 60 seconds, collect the supernatant, add 100 μL of PBS to each well again, centrifuge at 1000g for 60 seconds, collect the supernatant, mix the supernatant collected twice, and the extracted exosome sample is obtained.

[0025] (3) Screening: (3.1) Add exosome samples (4 replicates per sample) to each well of the lectin chip and incubate at room temperature for 60 minutes to perform hybridization reaction; remove excess reaction solution, wash the chip with PBS, and repeat 3 times.

[0026] (3.2) Add the mixture of Anti-CD9 / CD81 / CD63-Biotin (CD9 / CD81 / CD63 primary antibody, used to recognize CD9 / CD81 / CD63-positive exosomes) and incubate at room temperature for 60 minutes. Discard the excess reaction solution, wash the chip with PBS, and repeat 3 times. Here, Anti-CD9 / CD81 / CD63-Biotin is used to recognize the specific CD9 / CD81 / CD63 protein on exosomes.

[0027] (3.3) Add Cy3-Streptavidin to each well of the lectin chip and incubate at room temperature in the dark for 30 minutes. Discard excess reaction solution, wash the chip with PBS, and repeat 3 times. Here, Cy3-Streptavidin is used to recognize Anti-CD9 / CD81 / CD63-biotin, and the fluorescence value can be read at 532 nm.

[0028] (3.4) Add Anti-PD-L1 dilution buffer (PD-L1 protein primary antibody, used to recognize PD-L1 positive exosomes) to each well of the lectin chip and incubate at room temperature for 60 minutes. Discard excess antibody incubation buffer, wash the chip with PBS, and repeat 3 times. Here, Anti-PD-L1 is used to recognize the PD-L1 protein on exosomes.

[0029] (3.5) Add Alexa Fluor® 488-labeled secondary antibody mixture (Abcam, catalog number ab150077, Goat Anti-Rabbit IgG H&L (Alexa Fluor® 488)) to each well of the lectin chip and incubate at room temperature for 60 minutes. Discard excess reaction solution, wash the chip with PBS, and repeat 3 times. The Alexa Fluor® 488-labeled secondary antibody is used to identify Anti-PD-L1, and the fluorescence value can be read at 488 nm.

[0030] (4) Data analysis: The chip was dried, and the fluorescence values ​​of each well were read using GenePix software after scanning the 488nm and 532nm channels of a laser scanner. The mean of the four replicates for each sample was calculated, and then the PBS buffer value was subtracted to obtain the value for each sample. The data were processed with Log2 and batch effect was corrected using a combat algorithm before subsequent analysis. Total glycosylated exosomes were obtained from the fluorescence value of the 532nm channel scan signal, and glycosylated PD-L1 positivity (PD-L1) was obtained from the fluorescence value of the 488nm channel scan signal. + Exosomes. Using Limma analysis, 20 differentially expressed lectins with a fold change > 1.5 and p < 0.05 were screened to obtain the EVArray-Lectin map. The results showed that 12 of them were upregulated and 8 were downregulated.

[0031] To further analyze the key lectins in the EVArray-Lectin profile applicable to predicting CRC immunotherapy efficacy, PLS-DA analysis was performed on 56 EV lectins using SIMCA software to explore the contribution of different lectins in distinguishing between PD-L1 resistant and PD-L1 sensitive groups (see appendix). Figure 1 (AB). The results showed that the 10 EV lectins HHL, UDA, PHA_E, SNA_I, BBC, IAA, GNL, LCA, SSA, and PHA_L had strong importance as projective predictors (see appendix). Figure 1 C). Subsequently, based on the Bootstrap resampling method, we constructed a CRC immunotherapy efficacy prediction model for 10 core candidate lectins using 11 machine learning algorithms. The results showed that the Random Forest algorithm had the largest AUC and PRAUC; therefore, we selected the Random Forest algorithm for subsequent variable selection (see appendix). Figure 1 DE).

[0032] In the random forest model with 10 lectin variables, the variable importance scores of PHA-E, SNA-I, and SSA were significantly higher than those of the other 7 lectins (see appendix). Figure 1 F). We then combined 10 key EVs lectins into different combinations and measured and compared the AUC, PRAUC, and classification error of each model to select the optimal machine learning model. The results showed that among all models, the random forest model based on the combination of PHA-E, SNA-I, and SSA variables had the best performance for CRC diagnosis (num.trees: 500, mtry: sqrt(n_features), min.node.size: 1), with an AUC of 0.969 and a PRAUC of 0.986 (see appendix). Figure 1 GI). The same results were obtained in the validation set (see attached). Figure 2 Therefore, this invention uses PHA-E, SNA-I, and SSA as specific lectins for predicting the sensitivity of colorectal cancer to immunotherapy.

[0033] Example 2 This embodiment provides a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy. The chip has three specific lectin probes immobilized in a dot matrix on the surface of a solid-phase carrier. By coating each well with three different specific lectins, the chip can achieve the joint detection of at least three sugar chains in human serum. The solid-phase carrier is a 14-well three-dimensional modified glass slide (EVbio, catalog number S10225; specification: 5 slides / box, size: 75mm*25mm), used to immobilize the specific lectins as probes. The three specific lectin probes are PHA-E, SNA-I, and SSA.

[0034] Table 1: Example 3 This embodiment provides a method for preparing a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, comprising the following steps: Each lectin was diluted to 200 µg / mL with PBS containing 5% glycerol and then printed in quadruplicate at a concentration of 200 µg / mL onto the surface of a 14-well three-dimensional modified glass slide (75.6 mm x 25.0 mm, Capital Biochip Corp, Beijing, China) using a microarray (Arrayjet, Roslin, UK). This yielded a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, with each well containing only one lectin.

[0035] In this embodiment, the lectin SSA was purchased from EY Corporation, catalog number L-3501-2, specification 2mg; SNA-I was purchased from EY Corporation, catalog number L-6802-2, specification 2mg; and PHA-E was purchased from Vector Corporation, catalog number L-1120, specification 5mg.

[0036] Example 4 This embodiment provides the application of lectin chips for predicting the sensitivity of colorectal cancer to immunotherapy in a kit for predicting the sensitivity of colorectal cancer to immunotherapy. The specific usage method is as follows: (1) Preparation of serum samples to be tested: The plasma samples collected from colorectal cancer patients were centrifuged at 3000g at 4°C for 20 minutes, and the supernatant was then transferred to a new centrifuge tube to obtain serum; 20 μL of each sample was taken and diluted to 100 μL with 80 μL of PBS to obtain the serum sample to be tested. (2) Extraction of exosomes: Add 100 μL of Captocore 700 composite chromatography packing material to each well of a 96-well plate, add 500 μL of PBS to each well, centrifuge at 1000g for 30 seconds to pre-treat the purification plate, repeat the PBS washing twice, seal the outlet at the bottom of the purification plate, add 100 μL of diluted serum sample to each well, incubate at room temperature for 30 min, centrifuge at 1000g for 60 seconds, collect the filtrate, add 100 μL of PBS to each well, centrifuge at 1000g for 60 seconds, mix the two collected filtrates, which is the extracted exosome sample.

[0037] (3) Add 100 μL of exosome sample to each well of the ensemble chip prepared in Example 3 and incubate at room temperature for 60 minutes to carry out the hybridization reaction; remove the excess reaction solution from each well, add 200 μL of PBS to wash the chip, and repeat 3 times.

[0038] (4) Add 100 μL of Anti-PD-L1 dilution buffer (PD-L1 protein primary antibody, used to recognize PD-L1 positive exosomes) to each well and incubate at room temperature for 60 minutes. Discard excess antibody incubation solution, add 200 μL of PBS to each well, wash the chip, and repeat 3 times. Here, Anti-PD-L1 is used to recognize the PD-L1 protein on exosomes.

[0039] (5) Add 100 μL of Alexa Fluor® 488-labeled secondary antibody mixture to each well and incubate at room temperature for 60 minutes. Discard the excess reaction solution, add 200 μL of PBS to each well, wash the chip, and repeat 3 times. The Alexa Fluor® 488-labeled secondary antibody is used to identify Anti-PD-L1 and the fluorescence value can be read at 488 nm.

[0040] (6) Dry the chip, scan the signal using a laser scanner at 488nm channel, and read the fluorescence value of the antibody chip using GenePix software. Calculate the mean of the four replicates of each agglutinin for each sample, then subtract the PBS buffer value to obtain the antibody value. The antibody value is the PHA-E, SNA-I, and SSA value. Substitute the PHA-E, SNA-I, and SSA values ​​into the following formula: Formula: Total value = 1.223 × SNA-Ⅰ + 2.152 × SSA - 0.895 × PHA-E SNA-Ⅰ, SSA, and PHA-E represent the fluorescence values ​​of the lectin detected by scanning the 488nm channel of a laser scanner.

[0041] When the total number is greater than or equal to 2, it is determined to be PD-L1 resistance; when the total number is less than or equal to 2, it is determined to be PD-L1 sensitivity.

[0042] The lectin chip constructed using this invention can specifically capture exosomes that are highly correlated with the sensitivity to immunotherapy for colorectal cancer. PD-L1-positive exosomes are captured using PD-L1 antibodies, and PD-L1 antibodies are recognized using fluorescently labeled secondary antibodies. The sensitivity to immunotherapy for colorectal cancer is determined by the fluorescence signal value.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A lectin chip for predicting immunotherapy sensitivity in colorectal cancer, characterized in that, The chip includes a solid support and a lectin probe; The lectin probe is fixed on the surface of the solid support; The lectin probes consist of PHA-E, SNA-I, and SSA, with each lectin encapsulated in a different well.

2. A method for preparing a lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy, characterized in that, Includes the following steps: (1) Diluted lectins, said lectins including PHA-E, SNA-I and SSA; (2) Spotting was performed on the spotting area of ​​the solid support using the method of repeated spotting of each lectin. PBS was spotted in the blank control area as a blank control and incubated at room temperature. (3) Dry the chip from step (2) to obtain the chip.

3. The method for preparing the lectin chip as described in claim 2, characterized in that, The lectin diluent used in step (1) is a phosphate buffer solution containing 4-5% glycerol by volume.

4. The method for preparing the lectin chip as described in claim 2, characterized in that, The concentration of the lectin spotting in (2) is 150-200 µg / mL.

5. The application of the lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy as described in claim 1 in a kit for predicting the sensitivity of colorectal cancer to immunotherapy.

6. The application as described in claim 5, characterized in that, The method of using the kit for predicting the sensitivity of colorectal cancer to immunotherapy is as follows: (1) Centrifuge the plasma sample of a colorectal cancer patient to obtain the serum sample to be tested; (2) Add chromatography packing material to a multi-well plate, wash with PBS and seal the outlet at the bottom of the purification plate. Add serum sample to each well, incubate at room temperature and centrifuge. Collect the supernatant to obtain sample exosomes. (3) Add the exosomes from step (2) to the lectin chip as described in claim 1 to carry out a hybridization reaction; (4) Add Anti-PD-L1 to the lectin chip from step (3) and incubate at room temperature; (5) Add fluorescently labeled secondary antibody to the lectin chip from step (4) and incubate at room temperature; (6) Dry the chip, obtain the scanning signal using a laser scanner, read the fluorescence value of each well in the chip, and obtain the readings of PHA-E, SNA-I, and SSA in the sample. Substitute the obtained readings into the following formula to obtain the total value of the sample. Total value = 1.223 × SNA-Ⅰ + 2.152 × SSA - 0.895 × PHA-E; Wherein, SNA-Ⅰ, SSA, and PHA-E represent the fluorescence values ​​detected by the lectin, respectively; When the total number value is ≥2, it is determined to be PD-L1 resistance; when the total number value is <2, it is determined to be PD-L1 sensitivity.

7. The application as described in claim 6, characterized in that, The fluorescent dye in step (5) is Alexa Fluor. ® 488.

8. The application as described in claim 6, characterized in that, The incubation time for step (2) is 30 minutes; the incubation time for step (3) is 60 minutes; the incubation time for step (4) is 60 minutes; the incubation time for step (5) is 60 minutes; the amount of exosome sample added in step (3) is 100 μL; the amount of Anti-PD-L1 diluent added in step (4) is 100 μL; the amount of fluorescent dye-labeled secondary antibody mixture added in step (5) is 100 μL.

9. A kit for predicting immunotherapy sensitivity in colorectal cancer, characterized in that, The kit includes the lectin chip for predicting the sensitivity of colorectal cancer to immunotherapy as described in claim 1.

10. A biomarker for predicting immunotherapy sensitivity in colorectal cancer, characterized in that, The marker is an exosome, and the exosome meets the following conditions: (a) Serum source; (b) Surface expression of PD-L1 protein; (c) Surface expression of CD9, CD81 and CD63 proteins; (d) The surface has characteristic glycans that are captured by lectin probes, including PHA-E, SNA-I and SSA.

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