Biomarker for screening, diagnosing and / or monitoring non-small cell lung cancer and application thereof

Abstract

The invention discloses an application of CD63 + EV PD-L1 protein in predicting the therapeutic effect of an immune checkpoint inhibitor, and particularly relates to an application of the CD63 + EV PD-L1 protein as a biomarker for predicting the early therapeutic effect of the immune checkpoint inhibitor in preparing a reagent for predicting the therapeutic effect of the immune checkpoint inhibitor. The invention provides an application of CD63 + EV PD-L1 protein in predicting the treatment effect of an immune checkpoint inhibitor, and a patient group sensitive to PD-1 / PD-L1 immunotherapy can be screened out. The evaluation method can predict the long-term response, and can improve the multi-thread treatment efficiency of the non-small cell lung cancer patient.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine technology, and in particular relates to a biomarker for screening, diagnosis and / or monitoring of non-small cell lung cancer and its application. Background Art

[0002] Lung cancer is the leading cause of cancer death worldwide, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer. The emergence of immune checkpoint inhibitors (ICIs) based on the programmed death receptor-1 (PD-1) and programmed death ligand-1 (PD-L1) signaling pathways has completely changed the treatment of non-small cell lung cancer (NSCLC) and has become a recommended choice for first-line and second-line treatment for many patients. At present, there are 11 PD-1 and PD-L1 monoclonal antibody drugs approved for marketing in China that have NSCLC indications, such as Pembrolizumab and Nivolumab. However, even in NSCLC, where immunotherapy is already mature, only 10%-30% of patients have significant efficacy in PD-1 / PD-L1 antibody treatment. Two people with apparently similar tumors may respond very differently to the same treatment.

[0003] In recent years, people have begun to pay attention to the special therapeutic effects of immunotherapy that are different from traditional chemotherapy and targeted therapy, namely pseudoprogression and delayed response. Pseudoprogression refers to the phenomenon that in the early stage of immunotherapy, due to lymphocyte infiltration and edema, activated effector T cells enter the tumor, causing tumor volume increase or new lesions, but it is not true tumor cell proliferation. It is characterized by initial disease progression, followed by tumor shrinkage or no further progression during at least two tumor assessments. Although the incidence of pseudoprogression does not exceed 10%, once it occurs, it will seriously affect the formulation of the patient's subsequent treatment plan.

[0004] PD-1 / PD-L1 immunotherapy has been widely used in multi-line treatment of patients with non-small cell lung cancer. Compared with traditional treatment, immunotherapy is slow to take effect, has large individual differences, and is difficult to predict in the long run. If used indiscriminately, its overall effectiveness is only between 10% and 30%. The current clinical universal prognostic biomarker tissue PD-L1 has very limited predictive ability, so there is an urgent need for an efficient immune checkpoint inhibitor response biomarker to screen out patient groups that are sensitive to PD-1 / PD-L1 immunotherapy. Summary of the invention

[0005] The purpose of the present invention is to provide CD63 +The application of EV PD-L1 protein as a biomarker for predicting the early efficacy of immune checkpoint inhibitors in the preparation of reagents for predicting the efficacy of immune checkpoint inhibitors is as follows:

[0006] In a first aspect, the present invention provides a biomarker for screening, diagnosis and / or monitoring of non-small cell lung cancer, wherein the biomarker is CD63 + EV PD-L1.

[0007] Preferably, the biomarkers are derived from serum.

[0008] In a second aspect, the present invention provides a kit for predicting the therapeutic efficacy of non-small cell lung cancer, wherein the kit comprises the biomarker.

[0009] Preferably, the kit is used to predict the short-term efficacy and long-term efficacy of non-small cell lung cancer.

[0010] Preferably, the median interval between the short-term efficacy and the baseline treatment time is 8.5 weeks, and the median interval between the long-term efficacy and the baseline treatment time is 35.7 weeks, and the baseline time is the patient's first treatment time.

[0011] In a third aspect, the present invention provides a system for screening, diagnosing and / or monitoring non-small cell lung cancer, the system comprising:

[0012] Detection reagent, the detection reagent is used to detect CD63 in exosomes + EV PD-L1;

[0013] The judging device is used to judge based on CD63 + The level and / or content of EV PD-L1 is used to screen, diagnose and / or monitor the treatment of non-small cell lung cancer.

[0014] Preferably, the method comprises the following steps:

[0015] S1. Sample collection: Serum samples from patients with non-small cell lung cancer before initial immunotherapy were regularly collected to separate and extract exosomes;

[0016] S2. Chemical analysis: Collect tissue sections or puncture samples from patients before the first immunotherapy for immunohistochemical analysis of PD-L1 protein;

[0017] S3. Detection of differences in marker expression levels: Collect imaging evaluation information of patients within one year, divide it into short-term efficacy and long-term efficacy according to the median interval time from baseline treatment, divide the patients into treatment-effective group and treatment-ineffective group, and compare and analyze the differences in tissue PD-L1 and EV PD-L1 expression levels between the two groups;

[0018] S4. Draw the receiver operating characteristic (ROC) curve of each sample based on the expression level difference described in step S3 to evaluate the efficacy of predicting the efficacy of immune checkpoint inhibitors and determine the expression of CD63 + cutoff value of EV PD-L1 protein;

[0019] S5. Determine the therapeutic efficacy of non-small cell lung cancer according to the cutoff value of step S4.

[0020] Beneficial effects:

[0021] 1. The present invention provides CD63 + The application of EV PD-L1 protein in predicting the efficacy of immune checkpoint inhibitor therapy can screen out patient groups that are sensitive to PD-1 / PD-L1 immunotherapy.

[0022] 2. The evaluation method of the present invention can predict long-term response and improve the efficiency of multi-line treatment for patients with non-small cell lung cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 These are the characterization results of EVs extracted in Example 1 of the present invention: A is a transmission electron microscope image of EVs; B is an image of nanoparticle tracking analysis of EVs; C is a Western Blot detection result of EVs; and D is a principle flow chart of the present invention.

[0024] Figure 2 This is the prediction of the efficacy of various forms of PD-L1 in serum for patients before receiving treatment in Example 2 of the present invention: wherein A is a scatter plot of the prediction of efficacy by baseline PD-L1; B is the ROC curve of the prediction of efficacy by baseline PD-L1; and C is the objective response rate after baseline PD-L1 grouping.

[0025] Figure 3 CD63 in Example 2 of the present invention + The predictive efficacy of EV PD-L1 as an independent biomarker: A and B are the results of correlation analysis; C is CD63 + The predictive ability of EV PD-L1 in high and low expression groups of tumor tissues; D is CD63 + The predictive ability of EVPD-L1 under different treatment modalities.

[0026] Figure 4 This is the prediction of long-term efficacy of ΔPD-L1 in Example 3 of the present invention: A is a heat map of the relationship between ΔEV PD-L1 and long-term response; B is a scatter plot between ΔEV PD-L1 and long-term response; C is ROC analysis; D is ORR analysis.

[0027] Figure 5ΔEV PD-L1 is used for identification of delayed response in Example 4 of the present invention: A is a scatter plot of patients with delayed response and patients with late tumor progression; B is ΔCD63 + ROC curve of delayed response for EV PD-L1 recognition; C is ΔCD63 + Objective response rate of EV PD-L1-identified delayed response; D is a representative CT image. DETAILED DESCRIPTION

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Embodiment 1:

[0030] 1.1 Research subjects and inclusion criteria

[0031] Peripheral blood samples and CT image information were collected from 79 NSCLC patients who were treated in Nanjing Drum Tower Hospital between September 2023 and September 2024. Inclusion criteria were age 18 years or older and first-time immunotherapy with anti-PD-1 / PD-L1 inhibitors. Imaging assessment was performed by computed tomography (CT) or positron emission tomography (PET-CT), such as Figure 1 As shown in D, the efficacy evaluation was based on the latest version of the solid tumor response evaluation criteria (RECIST1.1), complete remission (CR), partial remission (PR), stable disease (SD) and progressive disease (PD). Follow-up continued until the patient's death or the last update in September 2024, with a median follow-up time of 11.5 months (range 9.4-12.2 months). The Medical Ethics Committee of Drum Tower Hospital Affiliated to Nanjing University Medical School approved the collection of blood samples and access to clinical data, and all procedures involving human participants strictly adhered to the Declaration of Helsinki. Table 1 provides the baseline clinical and pathological characteristics of the patients participating in the study.

[0032] Table 1 Baseline clinicopathological characteristics of patients

[0033]

[0034]

[0035]

[0036] 1.2 Collection and storage of blood samples

[0037] Baseline serum samples were obtained from blood collection tubes of NSCLC patients (n=79) before the first immunotherapy, and serum samples of patients were collected every three weeks. The collected blood samples were first centrifuged at 1500g for 15 minutes to remove dead cells and cell debris. In order to maintain the number and integrity of EVs, each sample was aliquoted into 500ul and stored at -80℃, and thawed in advance when isolating extracellular vesicles (EVs) to avoid repeated freezing and thawing.

[0038] 1.3EV extraction method

[0039] Extracellular vesicles were isolated using an immunomagnetic bead kit (purchased from Nanjing Renmai Biotechnology Co., Ltd.) according to its instructions. 20ul of serum sample was aspirated and incubated with antibody-coated magnetic microparticles under incubation conditions. The antibody captured the EV in the serum to form an antigen-antibody complex that bound to the magnetic beads. A magnetic field was applied to magnetic beads for magnetic separation. After discarding the supernatant, the magnetic bead complex was repeatedly washed 3 times to remove unbound impurities for subsequent EV detection.

[0040] 1.4EV extraction results

[0041] The present invention uses transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and Western Blot (WB) to confirm the successful separation of EVs, and characterizes the morphology, size, concentration and specific markers of EVs. Figure 1 As shown, Figure 1 A shows the morphology of EVs observed by TEM, and their size is about 120 nm; Figure 1 B: The average particle size of EVs observed by NTA was 127.3 nm; Figure 1 C is a Western Blot showing that PD-L1 and positive markers CD63 and TSG101 are expressed in EVs, while the negative marker Calnexin used as a control is not expressed. The above results indicate that EVs were successfully extracted.

[0042] Immunochemiluminescence technology was used to detect the levels of soluble PD-L1 and exosomal PD-L1 in serum: acridinium ester-labeled PD-L1 antibody was added to react with the magnetic bead complex under incubation conditions to form a double antibody sandwich complex; the supernatant was removed by magnetic separation and the complex was washed 3 times; the excitation solution was added to make the complex produce chemiluminescent signal, and the luminescence intensity was measured by a photomultiplier.

[0043] Embodiment 2:

[0044] This example demonstrates that CD63 + EV PD-L1 protein is a better / independent biomarker for predicting early efficacy of immune checkpoint inhibitor therapy.

[0045] The present invention evaluated the expression levels of tissue PD-L1, EV surface PD-L1 and free soluble PD-L1 in serum. Figure 2 As shown in A. The baseline PD-L1 level was lower in responders than in non-responders. Considering that different EV subsets play different roles in biological processes, the present invention analyzed three different EV subsets (CD63 + EV, CD9 + EV, CD81 + EV), only CD63 + EV PD-L1 levels were statistically lower in responders than in non-responders, whereas + EV and CD81 + This trend was not observed in EVs; there was no difference at all in soluble PD-L1 and tissue PD-L1, and high tissue PD-L1 expression (a recognized marker of clinical benefit) was not associated with either early response or durable response.

[0046] The EV PD-L1 was compared with the currently recognized standard PD-L1 (TPS) in clinical practice. Figure 2 B shows CD63 + The AUC of EV PD-L1 for predicting short-term efficacy can reach 0.73 (95% CI; 0.61-0.85), and the AUC for long-term efficacy is 0.69 (95% CI; 0.56-0.82). In comparison, the AUC of the clinical gold standard tissue PD-L1 for predicting short-term efficacy and long-term efficacy is only 0.50 (95% CI; 0.33-0.67) and 0.54 (95% CI; 0.36-0.73), respectively. This shows that CD63 + The predictive efficacy of EV PD-L1 was better.

[0047] To demonstrate that CD63 + EV PD-L1 is an independent predictive biomarker. The present invention conducted a correlation analysis and the results are as follows Figure 3 As shown in A-3B, it was found that the correlation between the tissue PD-L1 and the baseline EV PD-L1 or baseline Soluble PD-L1 of the same patient was very poor, and there was no obvious correlation between the serum EV PD-L1 of patients with negative tissue PD-L1, low positive expression, and high positive expression, indicating that the sources of PD-L1 are different and are relatively independent predictive markers. Figure 3As shown in C, although CD63 + There was no significant difference in the high and low expression groups of EV PD-L1 in tumor tissue (P = 0.06, P = 0.07, P = 0.58), but considering that the tissue data was incomplete and the sample size was small in the three groups, there was a similar trend, so there is reason to believe that in a larger group, CD63 + The good predictive ability of EV PD-L1 will not be limited by the PD-L1 expression level of patient tissues. Figure 3 D The results showed that this predictive ability was well demonstrated in patients receiving both immunotherapy alone and immunotherapy combined with chemotherapy.

[0048] Embodiment 3:

[0049] This example demonstrates that CD63 + Changes in EV PD-L1 (ΔCD63 + EV PD-L1) can be used to predict durable response (long-term response).

[0050] Example 2 found that although the baseline EVPD-L1 level can have a good predictive ability for short-term treatment response, its predictive efficiency for long-term response is extremely reduced. Therefore, the present invention monitored the changes in EVPD-L1 within 9 weeks after the patient's baseline medication to evaluate whether ΔEV PD-L1 can predict the long-term response to immunotherapy. The present invention collected serum samples from 67 patients in the cohort 3 weeks, 6 weeks, and 9 weeks after baseline treatment, and selected the maximum value of EVPD-L1 within 9 weeks. ΔEV PD-L1 was defined as the ratio of the maximum value to the baseline. The median interval between the maximum value and the baseline was 3.4 weeks. Compared with the baseline, the highest level of EVPD-L1 in patients within 9 weeks increased by an average of 2.1 times. The reason for the unavailability of samples was patient death (n=5) or patient loss of follow-up (n=7). The relationship between ΔEV PD-L1 and long-term response is as follows Figure 4 As shown in A-4B, ΔCD63 + EV PD-L1 was significantly correlated with treatment response (P=0.0022). Figure 4 ROC curve analysis of C showed that ΔEV PD-L1 showed good discrimination between treatment responders (n=19) and non-responders (n=48) (AUC reached 0.68). Through ROC curve analysis, we calculated ΔCD63 + The optimal cut-off value of EVPD-L1 is when ΔCD63 + When EV PD-L1>2.6, the sensitivity of predicting long-term response was 56% and the specificity was 88.1%. + Changes in EV PD-L1 (ΔCD63 +EV PD-L1) can predict the long-term response of patients, ΔCD63 + Patients with EV PD-L1>2.6 were more likely to gain long-term benefit from immunotherapy.

[0051] Embodiment 4:

[0052] This example demonstrates that ΔCD63 + EV PD-L1 can be used to identify delayed responses unique to immunotherapy.

[0053] PD-L1 immunotherapy activates T lymphocytes and the body's own immune system to kill tumors. This process takes an average of about three months to show significant survival benefits for patients (Rittmeyer A, Barlesi F, Waterkamp D, et al. Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial [J]. The Lancet, 2017, 389 (10066): 255-65.). In the early stages of treatment, problems such as poor efficacy and immune-related adverse reactions may occur, which will have a huge impact on the patient's subsequent treatment plan.

[0054] The present invention selected 37 patients who had no obvious response in the early stage from 79 patients. Among these 37 patients, 10 had tumor shrinkage in the later stage. The CD63 + The changes in EV PD-L1 were significantly greater, and the other 27 people still had no response in the later stage. The present invention conducted a comparative analysis, and the results were as follows Figure 5 As shown in A, it was found that ΔCD63+EV PD-L1 could clearly distinguish the two groups of patients.

[0055] Objective response rate (ORR) refers to the proportion of patients whose tumor volume shrinks to a predetermined value. Figure 5 As shown in B-5C, the results showed that when this change was greater than 2.035 times, ΔEV PD-L1 was able to identify patients with delayed reactions with a specificity of 85.19%, and the objective response rate of the identified patients could reach 71.43%, indicating that the prediction model provided by the present invention can accurately locate potential patient groups that may achieve long-term benefits from immunotherapy. Figure 5D shows CT images of two representative patients during their treatment cycles.

[0056] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A biomarker for screening, diagnosis and / or monitoring of non-small cell lung cancer, characterized in that: The biomarker is CD63 + EV PD-L1.

2. The biomarker according to claim 1, characterized in that The biomarkers are derived from serum.

3. A kit for predicting the therapeutic efficacy of non-small cell lung cancer, characterized in that: The kit comprises the biomarker of claim 1.

4. The kit according to claim 3, characterized in that The kit is used for predicting the short-term efficacy and long-term efficacy of non-small cell lung cancer.

5. The kit according to claim 4, characterized in that The median interval between the short-term efficacy and the baseline treatment time was 8.5 weeks, and the median interval between the long-term efficacy and the baseline treatment time was 35.7 weeks. The baseline time was the patient's first treatment time.

6. A system for screening, diagnosing and / or monitoring non-small cell lung cancer, characterized in that: The system comprises: Detection reagent, the detection reagent is used to detect CD63 in exosomes + EV PD-L1; The judging device is used to judge based on CD63 + The level and / or content of EV PD-L1 is used to screen, diagnose and / or monitor the treatment of non-small cell lung cancer.

7. The method for using the system of claim 6, characterized in that: The steps include: S1. Sample collection: Serum samples from patients with non-small cell lung cancer before initial immunotherapy were regularly collected to separate and extract exosomes; S2. Chemical analysis: Collect tissue sections or puncture samples from patients before the first immunotherapy for immunohistochemical analysis of PD-L1 protein; S3. Detection of differences in marker expression levels: Collect imaging evaluation information of patients within one year, divide it into short-term efficacy and long-term efficacy according to the median interval time from baseline treatment, divide the patients into treatment-effective group and treatment-ineffective group, and compare and analyze the differences in tissue PD-L1 and EV PD-L1 expression levels between the two groups; S4. Draw the receiver operating characteristic (ROC) curve of each sample based on the expression level difference described in step S3 to evaluate the efficacy of predicting the efficacy of immune checkpoint inhibitors and determine the expression of CD63 + cutoff value of EV PD-L1 protein; S5. Determine the therapeutic efficacy of non-small cell lung cancer according to the cutoff value of step S4.

Images