Kit and system for predicting prostatic cancer immunotherapy effect

Abstract

The invention provides a kit and a system for predicting the immunotherapy effect of prostatic cancer. The kit comprises reagents for detecting hnRNPA2B1, CD68, C163 and CD206. The correlation between the expression of the hnRNPA2B1 in the prostate tissue and the treatment of the prostate cancer immune checkpoint inhibitor is elaborated for the first time, the prostate tissue of a subject is extracted, the expression of hnRNPA2B1, CD68, C163 and CD206 proteins of the subject in the prostate tissue is measured, and the immunotherapy effect of the prostate cancer patient is predicted based on a prediction model. The kit and the system can be used for screening of immunotherapy of prostatic cancer and can also be used for research and development of new drugs.

Description

Technical Field

[0001] The present invention relates to a kit and a system for predicting the effect of immunotherapy for prostate cancer. Background Art

[0002] Prostate cancer poses a serious threat to men worldwide, with a mortality rate second only to lung cancer. While radical surgical resection and anti-androgenic therapy are effective treatments for early-stage prostate cancer, after approximately 18 months of endocrine therapy, prostate cancer often progresses from a hormone-sensitive stage to a drug-resistant stage, and the effectiveness of current first-line treatments for various types of prostate cancer gradually diminishes. The rise of immunotherapy has provided new hope for cancer treatment, with immune checkpoint inhibitors, in particular, achieving remarkable success in this field. Compared to other anti-cancer drugs, immune checkpoint inhibitors (ICIs) are not restricted to specific tumor types, are more specific in binding to tumor cells, and offer superior therapeutic efficacy with minimal side effects. However, preliminary clinical trial results suggest that immune checkpoint inhibitors are only effective in a subset of patients with prostate cancer. ICIs also face significant inter-individual variability in their efficacy. Therefore, understanding the mechanisms underlying the suboptimal efficacy of prostate cancer immunotherapy is a key challenge in clinical practice and a pressing challenge in basic research. Summary of the Invention

[0003] The object of the present invention is to overcome the deficiencies of the prior art and provide a kit and system for predicting the efficacy of immunotherapy for prostate cancer. The present invention also provides the use of at least one of a reagent for detecting hnRNPA2B1, a reagent for detecting CD68, a reagent for detecting C163, and a reagent for detecting CD206 in the preparation of a kit or system for predicting the efficacy of immunotherapy for prostate cancer.

[0004] To achieve the above objectives, the technical solutions adopted are:

[0005] The present invention provides a kit for predicting the effect of immunotherapy for prostate cancer. The kit comprises reagents for detecting hnRNPA2B1, CD68, C163 and CD206.

[0006] Preferably, the reagent for detecting hnRNPA2B1, CD68, C163 and CD206 comprises an immunohistochemical reagent for detecting hnRNPA2B1, CD68, C163 and CD206.

[0007] Preferably, the immunohistochemical reagents for detecting hnRNPA2B1, CD68, C163 and CD206 include hnRNPA2B1 primary antibody, CD68 primary antibody, C163 primary antibody, CD206 primary antibody, biotin-labeled secondary antibody, streptavidin-peroxidase and color development substrate.

[0008] Preferably, the biotin-labeled secondary antibody comprises at least one of a biotin-labeled goat anti-mouse IgG polymer and a biotin-labeled goat anti-rabbit IgG polymer.

[0009] Preferably, the chromogenic substrate is DAB.

[0010] Preferably, the immunohistochemical reagent for detecting hnRNPA2B1, CD68, C163 and CD206 further comprises an endogenous peroxidase blocker and a nonspecific staining blocker.

[0011] Preferably, the non-specific staining blocking agent comprises normal animal non-immune serum.

[0012] The present invention provides a system for predicting the effect of immunotherapy for prostate cancer, comprising:

[0013] A data input module is used to input the detection results of hnRNPA2B1, CD68, C163, and CD206 tissue protein expression levels of prostate cancer patients into the model calculation module;

[0014] A model calculation module, including a prostate cancer patient risk scoring model, is used to calculate a prostate cancer patient risk score result based on the prostate cancer patient hnRNPA2B1, CD68, C163, and CD206 tissue protein expression detection results and the prostate cancer patient risk scoring model;

[0015] The prostate cancer patient risk scoring model includes a risk scoring formula, risk score = 4.06-hnRNPA2B1*0.85+CD68*0.06+C163*0.14+CD206*0.0005;

[0016] The result output module is used to determine the effect of immunotherapy on prostate cancer patients based on the risk score of prostate cancer patients; when the patient's risk score is higher than or equal to -0.6425, the effect of immune checkpoint inhibitor treatment on the patient is poor; when the patient's risk score is lower than -0.6425, the effect of immune checkpoint inhibitor treatment on the subject is good.

[0017] The present invention also provides the use of at least one of a reagent for detecting hnRNPA2B1, a reagent for detecting CD68, a reagent for detecting C163, and a reagent for detecting CD206 in preparing a kit or system for predicting the effect of immunotherapy for prostate cancer.

[0018] The present invention also provides the use of a reagent for detecting hnRNPA2B1, a reagent for detecting CD68, a reagent for detecting C163 and a reagent for detecting CD206 in combination in preparing a kit or system for predicting the effect of immunotherapy for prostate cancer.

[0019] Beneficial effects:

[0020] This study, published in the journal Nature Communications, for the first time, demonstrates the correlation between hnRNPA2B1 expression in prostate tissue and treatment with immune checkpoint inhibitors for prostate cancer. It also provides a kit and system for predicting the efficacy of prostate cancer immunotherapy. By extracting prostate tissue from subjects and measuring the expression of hnRNPA2B1, CD68, C163, and CD206 proteins in their prostate tissue, the efficacy of immunotherapy in prostate cancer patients can be predicted based on a predictive model. This kit and system can be used for screening immunotherapies for prostate cancer and for the development of new drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 : Expression of hnRNPA2B1 in prostate cancer tissues and adjacent adjacent tissues.

[0022] Figure 2 : The relationship between hnRNPA2B1 and the occurrence and time of biochemical recurrence in prostate cancer patients, hnRNPA2B1=high: hnRNPA2B1 high expression group, hnRNPA2B1=low: hnRNPA2B1 low expression group.

[0023] Figure 3 : Survival curves of experimental mice after endpoint events occurred.

[0024] Figure 4 : Nomogram of the mathematical model for predicting the effect of immunotherapy according to the present invention.

[0025] Figure 5 : ROC curve of the mathematical model for predicting immunotherapy effect of the present invention.

[0026] Figure 6 :The optimal prediction value is calculated based on Bootstrap resampling technology and kernel estimation based smoothing method.

[0027] Figure 7 : The best prediction value of the prediction model of the present invention.

[0028] Figure 8 : The results of using the prediction model to predict the distribution of the experimental group and the control group. DETAILED DESCRIPTION

[0029] In order to better illustrate the purpose, technical solutions and advantages of the present invention, the present invention will be further described below in conjunction with specific embodiments.

[0030] Example 1

[0031] 1. Experimental Methods

[0032] 1. Immunohistochemistry: Immunohistochemistry (IHC) uses the principle of specific binding between antigens and antibodies to label proteins within tissues. The antibodies are then used to develop color through chemical reactions to determine the location and expression level of proteins within tissue cells. This experiment uses a ready-to-use immunohistochemistry kit (Maixin Biotechnology Product Number: KIT-9710), which includes:

[0033] Reagent 1: endogenous peroxidase blocker;

[0034] Reagent 2: Nonspecific staining blocking agent: normal animal non-immune serum;

[0035] Reagent 3: biotin-labeled secondary antibodies, including biotin-labeled goat anti-mouse IgG polymer and biotin-labeled goat anti-rabbit IgG polymer;

[0036] Reagent 4: Streptavidin-peroxidase.

[0037] Primary antibodies used in the experiment:

[0038] CD163 antibody, ABclonal Technology, A8383;

[0039] CD68 antibody, ABclonal Technology, A23205;

[0040] CD206 antibody, Proteintech, 60143-1-Ig;

[0041] HnRNPA2B1 antibody, Proteintech, 14813-1-AP.

[0042] (1) Preparation of paraffin sections: Take out the paraffin sections to be tested and bake them in a 65°C oven for 1 hour. Depending on the antibody being tested, positive and negative control sections should be prepared.

[0043] (2) Dewaxing and hydration: Take out the baked slides and dewax according to the following steps: xylene I for 15 min; xylene II for 15 min; xylene III I for 15 min; anhydrous ethanol I for 10 min; anhydrous ethanol I for 10 min; anhydrous ethanol III for 10 min; 95% ethanol for 5 min; 80% ethanol for 5 min; 75% ethanol for 5 min; 50% ethanol for 5 min; ddH2O for 5 min.

[0044] (3) Antigen repair: Prepare 1XEDTA antigen repair solution by mixing concentrated EDTA (50×) and ddH2O in a volume ratio of 1:49. Place the slice rack loaded with hydrated slides into a stainless steel cup loaded with 1XEDTA antigen repair solution. The amount of liquid should cover the slice rack. Place the stainless steel cup in a pressure cooker and fill it with tap water for heat conduction. Set the induction cooker to keep warm and time it for 20 minutes. After cutting off the power, keep the pressure cooker on the induction cooker and let it stand for 2-3 hours. Wait for the pressure cooker and EDTA repair solution to cool naturally to below 40°C, take out the slices, and soak them in PBS for 5 minutes, 3 times, to restore the pH value to a weak alkaline state. During the soaking period, use an immunohistochemistry pen to draw a circle 3mm around the tissue.

[0045] (4) Endogenous peroxidase blocking: Remove the slice rack and shake off the remaining liquid. Place the slice in a humidified chamber. Add the endogenous peroxidase blocking agent (reagent 1) in the ready-to-use immunohistochemistry kit to the target tissue area of ​​the slice and incubate at room temperature in the dark for 10 minutes.

[0046] (5) Blocking: Add nonspecific staining blocker (reagent 2) to the target area of ​​the slide and incubate at room temperature for 30 minutes. Avoid excessive drying of the tissue during the operation to prevent nonspecific staining.

[0047] (6) Primary Antibody Incubation: Shake the slide dry. Add the prepared primary antibody dilution solution to the target tissue area. Transfer to a 4°C refrigerator and incubate overnight.

[0048] (7) Rewarming the next day: Take out the immunohistochemistry humidifier from the 4°C refrigerator and let it stand at room temperature for about 30 minutes. Soak and wash with PBS for 10 minutes three times.

[0049] (8) Secondary antibody incubation: Shake off any residual liquid on the slide and place the slide in a humidified chamber. Add biotinylated goat anti-mouse / rabbit IgG polymer (reagent 3) to the target tissue area and incubate at room temperature for 20 minutes. Wash with PBS for 10 minutes three times.

[0050] (9) Streptomycin antibiotic-peroxidase incubation: Shake off the residual liquid on the slide and place the slide in a humidified chamber. Add an appropriate amount of streptomycin antibiotic protein-peroxidase (reagent 4) to cover the target tissue and incubate at room temperature for 20 minutes.

[0051] (10) DAB color development: The DAB color development solution was prepared using the DAB color development kit (20×) (ZLI-9017, Zhongshan Jinqiao). DAB substrate solution and 20× concentrated DAB solution were mixed at a volume ratio of 20:1. Prepare the mixed DAB color development solution immediately before use and store it in a refrigerator at 4°C in the dark. Quickly add the DAB color development solution dropwise to the target tissue area on the slide and rinse with tap water after 1 minute to terminate the color development.

[0052] (11) Hematoxylin restaining: After 30 seconds of hematoxylin staining, the sample was quickly removed, briefly differentiated with hydrochloric acid and ethanol, and rinsed with tap water for 10 minutes.

[0053] (12) Dehydration: Dehydration was completed in the following order: 95% ethanol I for 3 seconds; 95% ethanol I for 3 seconds; 100% ethanol for 5 minutes; 100% ethanol III for 5 minutes; xylene I for 2 minutes; and xylene II for 2 minutes.

[0054] (13) Sealing: Dry the slide in a fume hood, add an appropriate amount of neutral resin to the center of the slide tissue, cover with a coverslip, and let it stand until the neutral resin solidifies.

[0055] (14) Film interpretation: Two pathologists will interpret the immunostaining results. Ten high-power fields are randomly selected for each sample, and the intensity and area of ​​the staining results are recorded. The staining intensity is divided into four levels: strong dark brown staining is scored as 3 points, moderate brown-yellow staining is scored as 2 points, weak light yellow staining is scored as 1 point, and blue staining is scored as 0 points. The percentage of the stained area is recorded.

[0056] (15) Data analysis: H-score = (∑i╳Pi)

[0057] i represents the staining intensity score, and Pi represents the percentage of cells with this staining intensity.

[0058] 2. TCGA Data Analysis

[0059] Biochemical recurrence (BCR) of prostate cancer typically refers to a re-increase in prostate-specific antigen (PSA) levels in the blood after initial treatment (such as surgery or radiotherapy). This suggests that residual tumor may lead to prostate cancer recurrence, and residual tumor recurrence after primary treatment is the main cause of increased prostate cancer mortality. This study was based on the TCGA-PRAD database, which was obtained from the prostate cancer cohort in the TCGA database (http: / / tcga-data.nci.nih.gov / tcga / tcgaHome2.jsp). Using the survival package in Rstudio software, univariate Cox regression analysis was performed on batch genes, with BCR as the outcome endpoint and P < 0.05 as the statistical standard.

[0060] 3. Animal experiments:

[0061] Based on previous research, we determined that hnRNPA2B1 is associated with macrophage differentiation within the prostate cancer microenvironment. This biological behavior influences the efficacy of prostate cancer immunotherapy. Therefore, we designed an animal study to verify this finding. C57 TRAMP mice bearing orthotopic prostate cancer tumors were used for this study. Pre-treatment expression of hnRNPA2B1, CD206, CD163, and CD68 was assessed by immunohistochemistry (IHC). All mice were divided into two groups: one treated with an immune checkpoint inhibitor and the other with a control agent. Survival was recorded. Tumor death or no death after 360 days was defined as the endpoint. Upon the occurrence of the endpoint, mice were sacrificed, prostates dissected, embedded in paraffin, and stained for hnRNPA2B1, CD206, CD163, and CD68 by IHC, and scored.

[0062] 2. Experimental results:

[0063] (1) IHC evaluation of hnRNPA2B1 expression in cancer and non-cancerous cells

[0064] We evaluated the expression of hnRNPA2B1 in prostate cancer tissues and adjacent tissues using IHC. Figure 1 The results showed that in prostate cancer, especially in tumor cells of cancerous tissue, the expression of hnRNPA2B1 was significantly higher than that in normal glands adjacent to the prostate cancer.

[0065] (2) Biochemical recurrence curve

[0066] We used prostate cancer data from the public database TCGA to analyze the relationship between hnRNPA2B1 and the occurrence and time of biochemical recurrence in prostate cancer patients. Figure 2As shown, there were 375 patients in the hnRNPA2B1 high expression group and 124 patients in the hnRNPA2B1 low expression group. The biochemical recurrence curves of the two groups were significantly different (p<0.001).

[0067] (3) Animal experiments

[0068] After all the endpoint events of the experimental mice occurred, the survival curve was drawn according to the experimental groups, and the Kaplan-Meier survival analysis was performed using R language. The results are as follows Figure 3 As shown: Group 1 is the immune checkpoint inhibitor treatment group, Group 0 is the control group, and the p value is 0.033. This shows that the immune checkpoint inhibitor group has a significantly better treatment effect than the control group.

[0069] (4) Constructing a prediction model

[0070] After the mice were dissected, the expression of hnRNPA2B1, CD206, CD163, and CD68 in prostate tissue was evaluated by IHC. A logistic regression model was used to construct a mathematical model for predicting the effect of immunotherapy. The model formula was 4.06-hnRNPA2B1*0.85+CD68*0.06+C163*0.14+CD206*0.0005, where hnRNPA2B1, CD68, C163, and CD206 refer to their respective protein expression levels. The above mathematical model was plotted as a nomogram using the rms package in R language ( Figure 4 ). Validate the model, draw the ROC curve, and calculate the area under the curve ( Figure 5 ), the results showed AUC = 0.84.

[0071] (5) Calculate the best prediction value

[0072] We use the cutpointr package to calculate the best prediction value, based on the Bootstrap resampling technique and the smoothing method based on kernel estimation. This method can make the results of the cutpoints less dependent on the current research sample and more stable. Figure 6 The upper left picture shows the distribution of the independent variable (dsi) in the two groups; Figure 6 The upper right picture is the ROC curve; Figure 6 The lower left picture is the distribution of cutting points after bootstrap; Figure 6 The image on the lower right shows the distribution of evaluation indicators (sensitivity + specificity). The results show that the best prediction value in the prediction model is -0.6425 ( Figure 7 ), the sensitivity was 0.875 and the specificity was 0.7419.

[0073] (6) Group comparison of the prediction model's predictive effectiveness between the experimental group and the control group

[0074] Furthermore, we used the above prediction model to predict the distribution of the experimental group and the control group. The results are as follows: Figure 8 As shown in the data, the prediction model is ineffective for predicting the prognosis of the non-immunotherapy group of prostate cancer, while for the immunotherapy group of prostate cancer, the prediction model has good predictive efficacy.

[0075] 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 the technical solutions of the present invention may be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A kit for predicting the effect of immunotherapy for prostate cancer, characterized in that: The kit includes reagents for detecting hnRNPA2B1, CD68, C163 and CD206.

2. The kit according to claim 1, characterized in that The reagents for detecting hnRNPA2B1, CD68, C163 and CD206 include immunohistochemical reagents for detecting hnRNPA2B1, CD68, C163 and CD206.

3. The kit according to claim 2, characterized in that The immunohistochemical reagents for detecting hnRNPA2B1, CD68, C163 and CD206 include hnRNPA2B1 primary antibody, CD68 primary antibody, C163 primary antibody, CD206 primary antibody, biotin-labeled secondary antibody, streptavidin-peroxidase and color development substrate.

4. The kit according to claim 3, characterized in that The biotin-labeled secondary antibody comprises at least one of a biotin-labeled goat anti-mouse IgG polymer and a biotin-labeled goat anti-rabbit IgG polymer.

5. The kit according to claim 3, characterized in that The color developing substrate is DAB.

6. The kit according to claim 3, characterized in that The immunohistochemical reagents for detecting hnRNPA2B1, CD68, C163 and CD206 also include an endogenous peroxidase blocker and a nonspecific staining blocker.

7. The kit according to claim 5, characterized in that The non-specific staining blocking agent includes normal animal non-immune serum.

8. A system for predicting the effect of immunotherapy for prostate cancer, characterized in that: include: A data input module is used to input the detection results of hnRNPA2B1, CD68, C163, and CD206 tissue protein expression of prostate cancer patients into the model calculation module; A model calculation module, including a prostate cancer patient risk scoring model, is used to calculate a prostate cancer patient risk scoring result based on the prostate cancer patient hnRNPA2B1, CD68, C163, CD206 tissue protein expression detection results and the prostate cancer patient risk scoring model; The risk scoring model for prostate cancer patients includes a risk scoring formula, risk score = 4.06-hnRNPA2B1*0.85+CD68*0.06+C163*0.14+CD206*0.0005; The result output module is used to determine the effect of immunotherapy on prostate cancer patients based on the risk score of prostate cancer patients; when the patient's risk score is higher than or equal to -0.6425, the effect of immune checkpoint inhibitor treatment on the patient is poor; when the patient's risk score is lower than -0.6425, the effect of immune checkpoint inhibitor treatment on the subject is good.

9. Use of at least one of a reagent for detecting hnRNPA2B1, a reagent for detecting CD68, a reagent for detecting C163, and a reagent for detecting CD206 in the preparation of a kit or system for predicting the effect of immunotherapy for prostate cancer.

10. Use of a reagent for detecting hnRNPA2B1, a reagent for detecting CD68, a reagent for detecting C163 and a reagent for detecting CD206 in combination for preparing a kit or system for predicting the effect of immunotherapy for prostate cancer.

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