CN117129680A

CN117129680A - Biomarker for predicting tumor immunotherapy effect and application thereof

Info

Publication number: CN117129680A
Application number: CN202210543840.7A
Authority: CN
Inventors: 孙苏彭; 周兴宇; 隗啸南; 杨盼盼; 周静; 孙立平
Original assignee: Hangzhou Kaibaoluo Biological Science & Technology Co ltd
Current assignee: Hangzhou Kaibaoluo Biological Science & Technology Co ltd
Priority date: 2022-05-18
Filing date: 2022-05-18
Publication date: 2023-11-28

Abstract

The invention discloses a biomarker for predicting tumor immunotherapy effect, which is a group of autoantibodies of tumor-associated antigens. The invention also provides a reagent for detecting the biomarker, a kit containing the reagent, and a corresponding detection or diagnosis method.

Description

Biomarker for predicting tumor immunotherapy effect and application thereof

Technical Field

The invention relates to the field of biotechnology, in particular to a biomarker for predicting tumor immunotherapy effect and application of the biomarker in predicting tumor immunotherapy effect.

Background

Tumor immunotherapy is one of the most promising research directions in the field of tumor therapy, where therapies with immune checkpoint inhibitors (immune checkpoint inhibitor, ICI) have historically progressed, achieving significant effects of tumor growth inhibition and tumor clearance in a fraction of patients. This therapy is based on the principle of blocking the immune checkpoint pathway of programmed death growth factor-1 (PD-1)/programmed death ligand-1 (programmed death ligand-1, PD-L1), by injecting specific antibodies against PD-1 or PD-L1 into a tumor patient, so that the tumor is no longer capable of evading immune system attacks, thereby promoting elimination of tumor cells in the body. ICI involving the PD-1/PD-L1 pathway has been a hot spot of research in recent years for anti-tumor therapy. At least, various indications such as melanoma, hodgkin's lymphoma, lung cancer, head and neck squamous carcinoma, liver cancer, esophageal cancer, breast cancer, gastric cancer, nasopharyngeal cancer, lymphoma and the like are available worldwide.

While immune checkpoint inhibitors (e.g., anti-PD-1/PD-L1 antibodies) have achieved remarkable success in tumor therapy, there is data that suggest that most patients receiving ICI do not benefit from it. For example, a substantial proportion of tumor patients do not respond to anti-PD-1/PD-L1 antibodies. The data indicate that even in patients with high PD-L1 expression (50% or higher of PD-L1 expression), the response rate to ICI drugs is only between 30% and 40%. On the other hand, immune checkpoint inhibitors are a very expensive drug, a large economic burden for the patient; meanwhile, immune checkpoint inhibitors may also cause serious adverse reactions, especially the development of systemic autoimmune diseases. Thus, if a patient who is responsive to an immune checkpoint inhibitor could be pre-identified from normal tumor patients, i.e. a patient who has had ICI benefited precisely found prior to treatment, it would be helpful to increase the efficiency of treatment, reduce the cost of treatment, and reduce the risk of treatment.

Autoantibodies produced by humans during tumor immune monitoring have been used for early diagnosis of tumors and are considered as a very potential biomarker for predicting the efficacy of tumor therapy. For example, anti-p 53 autoantibodies, anti-PGP 9.5 autoantibody levels, and the like have been proposed as tools for predicting lung cancer recurrence. However, reports of related biomarkers are still very limited in terms of the relationship between autoantibody expression against tumor associated antigens and ICI response.

There remains a need in the art to provide new autoantibody biomarkers useful for predicting the therapeutic effect of ICI therapies, and to develop detection antigens for such autoantibody biomarkers to provide new predictive means for the therapeutic effect of tumour immunotherapy.

Disclosure of Invention

In order to solve the technical problems, the invention finally identifies a group of autoantibody biomarkers which can be used for predicting or judging the treatment effect of Immune Checkpoint Inhibitors (ICI) of tumors, especially lung cancer by detecting autoantibodies aiming at different antigen targets in the blood of a lung cancer patient.

It is therefore an object of the present invention to provide autoantibody biomarker combinations for predicting or judging the effect of tumour immunotherapy.

Based on the identification of autoantibody biomarkers, it is another object of the invention to provide reagents for detecting such autoantibody biomarkers, e.g. antigen protein combinations which can be used for detecting such autoantibody biomarkers in a tumor patient sample (e.g. blood); and kits comprising the detection reagents, which can be used for corresponding assays.

It is a further object of the present invention to provide the use of the autoantibody biomarker combination or antigen protein combination in the manufacture of a product for predicting or judging the effect of tumour immunotherapy.

It is a further object of the present invention to provide a method of predicting or judging the effect of a tumor immunotherapy in a patient.

The technical scheme of the invention is as follows.

In one aspect, the invention provides a biomarker for predicting or judging the effect of tumour immunotherapy in a subject, the biomarker being an autoantibody (TAAb) combination comprising autoantibodies against the following Tumour Associated Antigens (TAAs): trim21, BRCA2, P53, IMP2, MAGE-A4, TXNDC2. In other words, the biomarker is an autoantibody combination comprising an anti-Trim 21 autoantibody, an anti-BRCA 2 autoantibody, an anti-P53 autoantibody, an anti-IMP 2 autoantibody, an anti-MAGE-A4 autoantibody, and an anti-TXNDC 2 autoantibody.

According to the invention, the concentration of each autoantibody in the sample of the subject is scored one by one and the score of the biomarker, namely the autoantibody combination is calculated, and according to the scoring result of the autoantibody combination, the prediction or judgment can be performed: (i) the subject is prone to benefit from (or obtain good tumor immunotherapy effect), (ii) the subject is not prone to benefit from (or obtain poor tumor immunotherapy effect), or (iii) the subject has a worse, i.e. a greater disadvantage, tumor immunotherapy effect.

In the context of the present invention, the autoantibody is an autoantibody in a sample such as serum, plasma, interstitial fluid, cerebrospinal fluid or urine, prior to a subject receiving tumour immunotherapy; preferably, the autoantibody is IgA (e.g., igA1, igA 2), igM, or IgG (e.g., igG1, igG2, igG3, igG 4).

In the context of the present invention, the subject is a mammal, preferably a primate mammal, more preferably a human. And, preferably, the tumor is renal cancer, liver cancer, ovarian cancer, cervical cancer, head and neck squamous cell cancer, nasopharyngeal cancer, urothelial cancer, laryngeal cancer, gastric cancer, melanoma, prostate cancer, hodgkin's lymphoma, bladder cancer, colorectal cancer, lung cancer, in particular lung cancer, such as small cell lung cancer, non-small cell lung cancer, lung squamous carcinoma, lung adenocarcinoma, and other subtypes of lung cancer.

In the context of the present invention, the tumor immunotherapy includes treatment with an immune checkpoint inhibitor; preferably, the tumor immunotherapy is an immune checkpoint inhibitor therapy alone or in combination with chemotherapy, radiation therapy, anti-vascular therapy, targeted therapy or other tumor treatment means, wherein the immune checkpoint inhibitor is an immune checkpoint inhibitor against PD-1, PD-L1, CTLA-4, BTLA, TIM-3, LAG-3, TIGIT, LAIR1, 2B4 and/or CD160, preferably an anti-PD-1 antibody or an anti-PD-L1 antibody. According to a specific embodiment of the invention, the antibody is a nivolumab, pamumab, bedi Li Shan, terlipressin Li Shan or other immune checkpoint inhibitor, in particular an anti-PD-1 antibody or an anti-PD-L1 antibody.

In the context of the present invention, the registration numbers of "tumor-associated antigens" in the UniProt database are as follows:

Trim21：P19474；

BRCA2：P51587；

P53：P04637；

IMP2：O14732；

MAGE-A4：P43358；

TXNDC2：Q86VQ3。

according to the invention, the biomarker, i.e. the combination of autoantibodies, can be detected, e.g. the concentration thereof, in a sample (e.g. plasma or serum) of a subject, e.g. a tumor patient, to predict or judge the efficacy of the subject in performing tumor immunotherapy.

According to the specific embodiment of the invention, the biomarker, namely the autoantibody combination, and the following technical schemes based on the biomarker can be used for realizing the prediction and judgment of the tumor immunotherapy effect based on the following modes:

(1) A low reference threshold and a high reference threshold for the detection value of each autoantibody are established. Wherein the low reference threshold can be established as the median of autoantibody measurements in a healthy control population sample (e.g. serum or plasma) plus a 2-fold SD value; the high reference threshold is established as the median of autoantibody measurements in pre-treatment samples (e.g. serum or plasma) of the diseased population after treatment to achieve PR or SD (see below) plus a SD value of 2-fold.

According to a specific embodiment of the present invention, the low reference threshold and the high reference threshold used in the present invention are respectively as follows: IMP2 (10,96), P53 (9,58), MAGE-A4 (9, 40), trim21 (12, 72), CM406 (7, 35), BRCA2 (9, 38) are expressed as tumor autoantigen names (low reference threshold, high reference threshold).

(2) For each autoantibody, scoring 0 when the detection value is less than or equal to the low reference threshold; when the detection values of TXNDC2, trim21, BRCA2 and IMP2 are larger than the low reference threshold and smaller than the high reference threshold, scoring 1; when the detection values of MAGE-A4 and P53 are larger than the low reference threshold and smaller than the high reference threshold, scoring 0.1 score; for each autoantibody, when the detection value is greater than or equal to the high reference threshold, score 2.

The scoring result obtained defines "abnormal conditions": 1) The TXNDC2 or IMP2 in TXNDC2, trim21, BRCA2 and IMP2 is 2, and the rest is 0; 2) Any two of TXNDC2, trim21, BRCA2 and IMP2 are 2, and the rest are 0; 3) BRCA2 and TXNDC2 are 1 minute at the same time, and the rest are 0 minute; 4) MAGE-A4 was 0.1 min, the remainder 0 min; 5) P53 is 0.1 score, one of Trim21 and BRCA2 is 2 score, and the rest is 0 score; 6) One or both of MAGE-A4 and P53 were 0.1 points, while one of TXNDC2 and Trim21 was 1 point, with the remainder being 0 points. When the autoantibody combination belongs to an "abnormal situation", the scoring rules change as follows: scoring of each antibody requires multiplication by-1, respectively.

(3) Based on the score for each autoantibody, the score for the autoantibody combination was calculated as follows: the fraction of autoantibody combinations is the sum of the scores of each autoantibody.

The present invention has demonstrated that when these autoantibody biomarker combinations score ∈1 (defined as "", "positive 6-TAAb" or "positive") in a sample from a subject, they readily benefit from immunotherapy, such as ICI therapy, or achieve good therapeutic results; when this score is ∈0 and < 1 (defined as "", "negative 6-TAAb" or "negative"), it is not easy to benefit from immunotherapy such as ICI treatment or to obtain poor therapeutic effect; when this score is less than or equal to-0.1 (defined as "", "aberrant 6-TAAb" or "aberrant"), the immunotherapy, e.g., ICI treatment, is less effective, i.e., the disadvantage is greater than the benefit.

Thus, the autoantibody biomarkers provided by the invention can be used to predict or judge whether a subject, e.g. a tumor patient, would benefit from immunotherapy, at least for a corresponding auxiliary judgment. The concentration of autoantibodies in the sample can be quantified by reference to a standard curve, and further the concentration level of autoantibody biomarkers can be determined by reference to a reference threshold.

Each of the autoantibodies provided by the present invention can be detected by a variety of methods, for example, by an antigen-antibody specific reaction between a tumor-associated antigen that causes the autoantibody to appear. Accordingly, the invention also provides a reagent for detecting the autoantibody biomarker.

Depending on the specific technical means, the reagents may be reagents for detection methods such as enzyme-linked immunosorbent assay (ELISA), protein/peptide fragment chip detection, immunoblotting, microbead immunodetection, microfluidic immunodetection, etc. Preferably, the reagents are used to detect the autoantibody biomarkers of the invention by antigen-antibody reaction, for example by ELISA.

In this aspect, the reagent may be an antigen protein combination for detecting the autoantibody combination, the antigen protein combination comprising the following antigen proteins: trim21, BRCA2, P53, IMP2, MAGE-A4, TXNDC2.

The reagent can be used for detecting corresponding autoantibody biomarkers in a sample (such as blood plasma or blood serum) of a subject, such as a tumor patient, so as to realize the prediction or judgment of the effect of the immune treatment of the tumor.

In another aspect, the invention provides the use of the biomarker or reagent in the manufacture of a product for predicting or judging the effect of tumour immunotherapy in a subject. As described above, the tumor immunotherapeutic effect includes: (i) the subject is prone to benefit from (or obtain good tumor immunotherapy effect), (ii) the subject is not prone to benefit from (or obtain poor tumor immunotherapy effect), or (iii) the subject has a worse, i.e. a greater disadvantage, tumor immunotherapy effect.

In yet another aspect, the invention provides a kit comprising the agent of the invention.

Depending on the specific technical means, the kit may be a kit for detecting the autoantibody biomarker by an enzyme-linked immunosorbent assay (ELISA), protein/peptide fragment chip detection, immunoblotting, microbead immunodetection, microfluidic immunodetection, or the like. Preferably, the kit is used for detection of the autoantibody biomarker of the invention by an antigen-antibody reaction, for example by ELISA.

Thus, preferably, the kit is an enzyme-linked immunosorbent assay (ELISA) detection kit. That is, the kit is used to detect autoantibody biomarkers, e.g., to detect their concentration, in a sample from a subject by enzyme-linked immunosorbent assay. Accordingly, the kit may also include other components required for ELISA detection of autoantibody biomarkers, all as is well known in the art. For detection purposes, for example, the antigen protein in the kit may be linked to a tag peptide, such as His tag, streptavidin tag, myc tag; for another example, the kit may include a solid support, such as a support having microwells to which antigen proteins can be immobilized, such as an elisa plate; and can also comprise adsorption proteins for fixing antigen proteins on a solid carrier, diluents of blood such as serum, washing liquid, secondary antibodies with enzyme labels, chromogenic liquid, stop solution and the like.

According to a specific embodiment of the invention, in this aspect, the kit comprises reagents for the detection of autoantibodies against the following tumor associated antigens, respectively: trim21, BRCA2, P53, IMP2, MAGE-A4, TXNDC2. The agent acts as an antigenic protein, the sequence of which is referred to above as the sequence of the tumour associated antigen.

In yet another aspect, the invention provides a method for predicting or judging the effect of a tumor immunotherapy in a subject, the method comprising detecting a biomarker in a sample from the subject, the biomarker being an autoantibody combination comprising autoantibodies against tumor associated antigens: trim21, BRCA2, P53, IMP2, MAGE-A4, TXNDC2.

According to the invention, the method further comprises the steps of scoring the concentration of each autoantibody in a subject sample one by one and calculating to obtain the score of the biomarker, namely the autoantibody combination, and predicting or judging according to the scoring result of the autoantibody combination: (i) the subject is prone to benefit from (or obtain good tumor immunotherapy effect), (ii) the subject is not prone to benefit from (or obtain poor tumor immunotherapy effect), or (iii) the subject has a worse, i.e. a greater disadvantage, tumor immunotherapy effect.

Wherein the detection can be performed using the reagents of the invention, e.g., antigen protein combinations, or kits comprising the reagents.

For example, the method comprises the steps of:

(1) Obtaining a sample from the subject;

(2) Detecting the concentration of each autoantibody in the sample;

(3) Scoring the concentration of each autoantibody one by one, calculating to obtain the score of the biomarker, namely the autoantibody combination, and predicting or judging according to the scoring result of the autoantibody combination: (i) the subject is prone to benefit from (or obtain good tumor immunotherapy effect), (ii) the subject is not prone to benefit from (or obtain poor tumor immunotherapy effect), or (iii) the subject has a worse, i.e. a greater disadvantage, tumor immunotherapy effect.

Wherein, step (3) includes:

(3-1): a low reference threshold and a high reference threshold for the detection value of each autoantibody are established. Wherein the low reference threshold can be established as the median of autoantibody measurements in a healthy control population sample (e.g. serum or plasma) plus a 2-fold SD value; the high reference threshold is established as the median of autoantibody measurements in pre-treatment samples (e.g. serum or plasma) of the diseased population after treatment to achieve PR or SD (see below) plus a SD value of 2-fold.

(3-2): for each autoantibody, scoring 0 when the detection value is less than or equal to the low reference threshold; when the detection values of TXNDC2, trim21, BRCA2 and IMP2 are larger than the low reference threshold and smaller than the high reference threshold, scoring 1; when the detection values of MAGE-A4 and P53 are larger than the low reference threshold and smaller than the high reference threshold, scoring 0.1 score; for each autoantibody, when the detection value is greater than or equal to the high reference threshold, score 2.

The scoring result obtained defines "abnormal conditions": 1) The TXNDC2 or IMP2 in TXNDC2, trim21, BRCA2 and IMP2 is 2, and the rest is 0; 2) Any two of TXNDC2, trim21, BRCA2 and IMP2 are 2, and the rest are 0; 3) BRCA2 and TXNDC2 are 1 minute at the same time, and the rest are 0 minute; 4) MAGE-A4 was 0.1 min, the remainder 0 min; 5) P53 is 0.1 score, one of Trim21 and BRCA2 is 2 score, and the rest is 0 score; 6) One or both of MAGE-A4 and P53 were 0.1 points, while one of TXNDC2 and Trim21 was 1 point, with the remainder being 0 points. When the autoantibody combination score belongs to an "abnormal situation", the scoring rules change as follows: scoring of each antibody requires multiplication by-1, respectively.

(3-3): based on the score for each autoantibody, the score for the autoantibody combination was calculated as follows: the fraction of autoantibody combinations is the sum of the scores of each autoantibody.

When the combined score of these autoantibody biomarkers in a sample of a subject is ∈1, it is predicted or judged that it is likely to benefit from immunotherapy, such as ICI therapy, or to obtain a good therapeutic effect; when this score is ≡0 and < 1, it is not easy to benefit from immunotherapy such as ICI treatment or to obtain poor therapeutic effect; when this score is less than or equal to-0.1, the immunotherapy, such as ICI treatment, is less effective, i.e., the disadvantage is greater than the advantage.

Compared with the prior art, the invention provides a biomarker for predicting or judging the tumor immunotherapy effect, wherein the biomarker is an autoantibody combination. With the autoantibody combinations of the invention, it can be predicted or judged that a subject will benefit or not benefit from tumor immunotherapy based on the scoring of the test results.

Experiments show that the effective rate of immune checkpoint blocking treatment of a tumor patient with the autoantibody combination score of more than or equal to 1 is obviously higher than that of a tumor patient with the autoantibody combination score of more than or equal to 0 and less than 1 or the score of less than or equal to-0.1 no matter the PD-L1 expression level and the TMB level are treated by immunological first-line treatment or postline treatment, and the lung cancer subtype is treated by immunological single drug treatment or immunological combination chemotherapy.

Thus, the autoantibody biomarkers provided by the invention are able to provide accurate predictions or decisions as to whether a tumor patient would benefit from immunotherapy, particularly immune checkpoint inhibitor therapy. Based on the prediction or judgment, the patient or clinician can better decide whether the patient is to be subjected to immunotherapy, thereby avoiding excessive medical treatment, reducing treatment cost, and reducing or avoiding adverse reactions.

Drawings

Embodiments of the present invention are described in detail below with reference to the attached drawing figures, wherein:

FIG. 1.6 prediction of ICI treatment efficacy in trained cohorts with TAAb autoantibody combinations. (1A) Correlation of pre-treatment autoantibody combination detection results with efficacy assessment of patients after receiving ICI treatment. (1B) Survival curve of patients positive or negative for autoantibody combinations after treatment. (1C) Survival curves of patients with "aberrant TAAb" autoantibody combinations with other patients after treatment.

Figure 2.6-prediction of ICI treatment effect of TAAb autoantibody combinations on the cohort of validation. (2A) Correlation of pre-treatment autoantibody combination detection results with efficacy assessment of patients after receiving ICI treatment. (2B) Survival curve of patients positive or negative for autoantibody combinations after treatment. (2C) Survival curves of patients with "aberrant TAAb" autoantibody combinations with other patients after treatment.

FIG. 3.6 prediction of ICI treatment effects of TAAb autoantibody combinations on populations of different lung cancer subtypes. (3A) Survival curves of patients positive, negative or abnormal for autoantibody combinations among squamous carcinoma patients after treatment. (3B) Survival curves of patients with positive, negative or abnormal combinations of autoantibodies in non-squamous cancer patients after treatment. (3C) Relation between the detection result of autoantibody combination before treatment of squamous carcinoma patients and the evaluation of the treatment effect of patients after receiving ICI treatment. (3D) Relation between the results of autoantibody combination detection before treatment of non-squamous cancer patients and evaluation of the efficacy of patients after receiving ICI treatment.

FIG. 4.6 prediction of ICI treatment effects of TAAb autoantibody combinations on different treatment line lung cancer populations. (4A) Survival curves of patients positive, negative or abnormal for autoantibody combinations in first line treated patients after treatment. (4B) Survival curve of patients positive, negative or abnormal for autoantibody combinations in post-treatment patients. (4C) Relationship between the results of autoantibody combination detection prior to treatment of a first-line treated patient and evaluation of the efficacy of the patient after treatment with ICI. (4D) Relationship between the detection result of autoantibody combination before treatment of a patient after a back line treatment and the evaluation of the treatment effect of the patient after receiving ICI treatment.

Fig. 5.6-prediction of ICI treatment effect of TAAb autoantibody combinations on different drug combination lung cancer populations. (5A) Survival curves of patients with positive, negative or abnormal autoantibody combinations in single drug treated patients after treatment. (5B) Survival curves of patients positive, negative or abnormal in combination with autoantibodies among the combination treated patients after treatment. (5C) Relationship between the results of autoantibody combination detection prior to treatment of a single drug treated patient and evaluation of the efficacy of the patient after receiving ICI treatment. (5D) Correlation of autoantibody combination detection results before treatment of a combination treatment patient with efficacy assessment of the patient after receiving ICI treatment.

Detailed Description

In the present invention, the term "antigen" or the term "antigenic protein" is used interchangeably. Furthermore, the present invention relates to the following experimental operations or definitions. It should be noted that the present invention may also be practiced using other techniques conventional in the art and is not limited to the following experimental procedures.

Preparation and immobilization of (one) antigen proteins

The cDNA of the Tumor Associated Antigen (TAA) was cloned into the PET28 (a) expression vector containing the 6XHIS tag. At the N-or C-terminus of the antigen, streptavidin or the like (biotin-binding tag protein) is introduced. The obtained recombinant expression vector is transformed into escherichia coli for expression, after the protein is expressed in inclusion bodies, the protein is denatured by 6M guanidine hydrochloride, renaturation and folding are carried out in vitro according to a standard method, and then Ni-NTA affinity column purification is carried out through a 6XHIS tag, so that antigen protein is obtained.

(II) preparation of plasma

Venous blood was taken in EDTA-treated or citric acid-treated blood collection tubes within one week to 1 day prior to immunotherapy. Then centrifuging for 15min at room temperature of 1000-2000 RCF; after centrifugation, the supernatant was gently transferred to another clean centrifuge tube at room temperature and stored in a-80 ℃ refrigerator for long periods of time.

ELISA detection and quantification of autoantibodies

The antigen protein produced was coated onto the microwell surface of 96 Kong Guxiang plates. Indirect coating is adopted: plates 96-Kong Guxiang were coated overnight with 5-10ug/ml biotin-labeled bovine serum albumin; on day 2, uncoated bovine serum albumin in the micropores of the solid phase plate is washed off, and 300uL of blocking solution containing BSA is added for blocking for 1 hour at room temperature; the antigen protein was added for 1.5h and then the unadsorbed antigen protein was washed away. After coating antigen protein, 300ul of stabilizing solution containing BSA is added into the microwells, and the cells are incubated for 1h and then used or dried in vacuum for standby.

As described above, the purified antigen protein is indirectly coated on the surface of the solid phase plate by a specific reaction between biotin and streptavidin. Adding diluted plasma sample into the microwells coated with antigen protein, and incubating to enable the autoantibodies in the plasma sample to be specifically combined with the antigen protein on the surface of the solid phase plate. Washing off the unbound autoantibodies, adding horseradish peroxidase-labeled anti-human IgG antibody, incubating for the second time to enable the enzyme-labeled anti-human IgG antibody to be combined with the autoantibodies adsorbed on the surface of the solid phase plate to form an antigen-antibody-enzyme-labeled antibody complex, washing off the unbound enzyme-labeled anti-human IgG antibody, adding a chromogenic agent substrate for reaction, and measuring absorbance at a wavelength of 450nm by using an enzyme-labeled instrument. The detection steps are as follows:

1. Preparation step

1. The detection reagent is allowed to stand at room temperature for at least 30 minutes to allow the reagent to return to room temperature.

2. Diluting a plasma sample to be tested: 545ul of sample diluent (PBS, containing 1% BSA) is added into a 1.5ml EP tube, 5ul of plasma sample to be tested is added into the sample diluent (the sample amount can be automatically adjusted according to the required amount, the volume ratio of the plasma sample to the sample diluent is 1:109), and the mixture is gently mixed for 5-6 times upside down.

3. After diluting and mixing each plasma sample to be tested uniformly, transferring 530ul to a clean deep hole groove.

4. Preparing a washing liquid working solution: 10 times of PBST lotion is diluted by purified water or distilled water 10 times to prepare original times of lotion for standby.

Pbs buffer: the pH was self-contained at 7.6.

2. Detection step

1. Adding an antibody: after 1 time of labeling with 270 ul/Kong Ximei of PBS buffer, 50 ul/well of diluted plasma to be tested was added to the ELISA plate and reacted on a microwell shaker at room temperature for 1h.

2. Adding a secondary antibody: secondary antibodies (horseradish peroxidase-labeled anti-human IgG antibody concentrate returned to room temperature: enzyme conjugate diluent = 1:19, which is PBS with 1% bsa) were formulated prior to use. The plates were dried 3 times with 1 XPBST wash 270 ul/Kong Xi, then 50 ul/well of secondary antibody dilution was added, the film was applied, and the reaction was performed on a microwell shaker at room temperature for 0.5h.

3. Adding a color-developing agent: the developer was prepared before use (developer a liquid: developer B liquid=1:19). The plate was dried by 3 beats with 1 Xwash 270 ul/Kong Xi, then developer was added at 100 ul/well, the first line was added to start timing, film was applied, and the reaction was performed on a microwell shaker at room temperature for 15min.

4. Terminating and reading: in the order of addition of the color-developing agent, 50 ul/well of stop solution was added and read at 450nm by an ELISA reader.

5. The level of autoantibodies in the sample is quantified by reference to a standard curve.

(IV) clinical efficacy evaluation index

Target lesions at baseline (pre-treatment) were evaluated according to the efficacy evaluation criteria for solid tumors version 1.1 (Response Evaluation Criteria in Solid Tumors RECIST Version.1, recist v 1.1), and the baseline sum of the longest diameters of target lesions was recorded for determining objective responses.

BOR: the optimal efficacy refers to a record of the optimal efficacy from the beginning of the treatment study to the end of the treatment, which is confirmed taking into consideration various factors.

PD: the sum of all target lesion diameters increases by at least 20% and the absolute value of the sum increase must also be greater than 5mm, compared to the minimum of the sum of all target lesion diameters prior to treatment; or new lesions appear.

PR: the sum of the diameters of all target lesions is reduced by at least 30% compared to the sum of the diameters of all target lesions prior to treatment.

SD: the reduction of the target lesions is not in Partial Remission (PR) and the increase is not in disease Progression (PD) compared to the minimum sum of all target lesion diameters prior to treatment, a condition intermediate PR and PD.

CR: all target lesions disappear and the short axis value of any pathological lymph node (whether or not the target lesion) must be <10mm.

PFS: progression free survival, i.e., the time from the onset of randomization to the recurrence of the disease or death of the patient for various reasons.

mPFS: median progression-free survival, i.e., median time from onset of randomization to disease recurrence or patient death due to various causes.

PD-L1 expression level: the immunohistochemistry method is adopted to evaluate the percentage of tumor cells stained with any intensity of PD-L1 membrane in all tumor cells, and the detection results are divided into four groups, namely negative, <50%, > 50%, and unknown.

(V) establishing a low reference threshold and a high reference threshold for the detection value of each autoantibody

The median of autoantibody measurements in plasma of healthy control population (242 cases of physical examination center of first affiliated hospital of Zhejiang university) plus 2 times SD value was used as low reference threshold.

The median of autoantibody measurements in plasma before treatment of patients who achieved PR or SD after treatment in a training cohort (see example 1 below) plus a 2-fold SD value was used as the high reference threshold.

The low and high reference thresholds for each autoantibody were determined as:

tumor autoantigen name (low reference threshold, high reference threshold): IMP2 (10,96), P53 (9,58), MAGE-A4 (9, 40), trim21 (12, 72), CM406 (7, 35), BRCA2 (9, 38).

Scoring of autoantibody combinations

For each autoantibody, scoring 0 when the detection value is less than or equal to the low reference threshold; when the detection values of TXNDC2, trim21, BRCA2 and IMP2 are larger than the low reference threshold and smaller than the high reference threshold, scoring 1; when the detection values of MAGE-A4 and P53 are larger than the low reference threshold and smaller than the high reference threshold, scoring 0.1 score; for each autoantibody, when the detection value is greater than or equal to the high reference threshold, score 2.

Based on the score for each autoantibody, the score for the autoantibody combination was calculated as follows: the fraction of autoantibody combinations is the sum of the scores of each autoantibody.

When the autoantibody biomarker combination score is ∈1 (defined as "6-TAAb positive", "positive 6-TAAb" or "positive") in a sample from a subject, it is predicted or judged that it is likely to benefit from immunotherapy, such as ICI therapy, or to obtain a good therapeutic effect; when this score is ≡ 0 and < 1 (defined as "6-TAAb negative", "negative 6-TAAb" or "negative"), it is not easy to benefit from immunotherapy such as ICI treatment or to obtain poor therapeutic effect; when this score is less than or equal to-0.1 (defined as "6-TAAb abnormality", "abnormal 6-TAAb" or "abnormality"), the immunotherapy, such as ICI treatment, is less effective, i.e., the disadvantage is greater than the advantage.

(seventh) statistical analysis method

Both groups were statistically analyzed using GraphPad Prism v.6 (GraphPad Prism software, san diego, california) and IBM SPSS Statistics for Windows (IBM, new york) using the Mann-Whitney U test. In analyzing the relationship between each parameter, a Spearman correlation analysis was performed. Median progression-free survival (median Progression Free Survival, mPFS) was analyzed by Kaplan-Meier method. The mPFS differences between patient subgroups were analyzed using a log rank test.

The invention is described below with reference to specific examples. It will be appreciated by those skilled in the art that these examples are for illustration of the invention only and are not intended to limit the scope of the invention in any way. Sample collection was informed consent of the patient and was approved by the regulatory authorities.

The experimental methods in the following examples are conventional methods unless otherwise specified. The raw materials and reagent materials used in the examples below are all commercially available products unless otherwise specified.

Example 1

To establish an autoantibody combination indicative of the effect of immunotherapy, the study first recruited 124 patients diagnosed with advanced lung cancer whose plasma was collected prior to ICI treatment and examined lung cancer patients for the presence of autoantibodies to purified antigen proteins. This group of people is called the training queue. Specific information of this experimental population is shown in table 1.

Table 1 training queue crowd information.

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* : unlike the positive patients mentioned elsewhere in the present invention, positive herein refers to the detection of the expression of any one of the 6 autoantibodies in the patient's plasma, i.e. positive;

* *: unlike the positive patients mentioned elsewhere in the present invention, negative here means that the expression of all 6 autoantibodies in the patient's plasma is not detected, i.e. negative.

The "positive rate" appearing in the following experimental result analysis is the percentage of the occurrence of autoantibody combined positive results (see above) in the corresponding population.

The results showed that the positive rate of the autoantibody combination in the training cohort was 46.8%. The data also show that phase IV patients have a higher positive rate (50% vs.21.4%, p=0.0436) than phase III patients. In addition, patients receiving first-line ICI treatment had a higher positive rate than post-line treatment patients (57.8% vs.40.5%, p= 0.0638). Other clinical features such as age, sex, history of smoking, pathological subtypes, PD-L1 expression, etc. were not found to have significant relevance to the detection of autoantibody combinations.

To verify the predictive ability of an autoantibody combination established in a training cohort for ICI treatment, 118 patients with advanced lung cancer were independently enrolled in another treatment center, whose plasma was collected prior to receiving ICI treatment, and will be used to verify whether 6-TAAb autoantibody combinations could be used in different populations with similar ability to predict ICI treatment effects. This group of people is called the validation queue. Specific information of this experimental population is shown in table 2.

Table 2. Verify queue crowd information.

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The positive rate of the 6-TAAb autoantibody combination in the validation cohort was 56%. Patients receiving first line ICI treatment also tended to have a higher positive rate than post-line treatment patients. Other clinical features such as age, sex, history of smoking, pathological subtypes, PD-L1 expression, etc. were not found to have significant relevance to the detection of autoantibody combinations.

Example 2

The 6-TAAb autoantibody combination test was performed on 124 patients with advanced lung cancer (training cohort) from Shanghai pulmonary hospital, and the test results were used to predict the efficacy of ICI treatment in these patients.

The data show that the median progression-free survival for positive 6-TAAb patients is 317 days, for negative patients 118 days, and for "abnormal" patients only 55 days. In terms of objective remission rate, the positive patients were 41%, the negative patients were 25%, and the "abnormal" patients were only 11%. Meanwhile, 41% of 6-TAAb positive patients were evaluated for Partial Remission (PR) after ICI treatment, and 10% were evaluated for disease Progression (PD); in contrast, only 25% of negative 6-TAAb patients were assessed for Partial Remission (PR), while 20% of patients were assessed for disease Progression (PD). Thus, for this group of people, positive 6-TAAb detection results predict that patients will be prone to benefit or good therapeutic effect from immunotherapy, such as ICI therapy; negative 6-TAAb autoantibody combination detection results, predicted not to benefit readily from immunotherapy, such as ICI therapy; when the 6-TAAb autoantibody combination detection result is "abnormal", it is predicted that a worse therapeutic effect is obtained from immunotherapy such as ICI treatment.

The results are shown in FIG. 1.

Example 3

The 6-TAAb autoantibody combination test was performed on 118 patients with advanced lung cancer (validation cohorts) from beijing co-hospital, and the test results were used to predict the efficacy of ICI treatment in these patients.

The data show that the median progression free survival for positive 6-TAAb patients is 8.8 months, for negative patients is 3.9 months, and for "abnormal" patients is only 2.05 months. In terms of objective remission rate, the positive patients were 48.8%, the negative patients were 20.9%, and the "abnormal" patients were only 14.3%. Thus, for this group of people, positive 6-TAAb detection results predict that patients will be prone to benefit or good therapeutic effect from immunotherapy, such as ICI therapy; negative 6-TAAb autoantibody combination detection results, predicted not to benefit readily from immunotherapy, such as ICI therapy; when the 6-TAAb autoantibody combination detection result is "abnormal", it is predicted that a worse therapeutic effect is obtained from immunotherapy such as ICI treatment.

The results are shown in FIG. 2.

Example 4

In order to screen immunotherapy predictive markers suitable for clinical application, various scenes of immunotherapy of groups of lung cancer patients are as much as possible in a verification queue of the study. First, according to pathological characteristics, patient groups of different subtypes in patients with advanced lung cancer are selected. Of the squamous carcinoma patients, patients with positive 6-TAAb detection result have significantly longer median progression-free survival after ICI treatment than those with negative 6-TAAb detection result, and the received treatment effect is also significantly better than those of the negative patients, with Objective Remission Rate (ORR) as an evaluation index, with 33.3% of 6-TAAb positive patients and 22.2% of negative patients. Of the non-squamous carcinoma patients, the median progression-free survival of 6-TAAb positive patients was 8.8 months, while negative patients were 7 months; likewise, the objective remission rate was 54.8% for positive patients, which is significantly higher than 20.4% for negative patients.

The "abnormal" 6-TAAb assay results indicate poor ICI treatment in both squamous and non-squamous carcinoma patients. Of squamous carcinoma patients, the median progression-free survival of "abnormal 6-TAAb" patients was 3.2 months, while positive patients were 5.7 months; of the non-squamous carcinoma patients, the progression-free survival of "abnormal 6-TAAb" patients was only 1.5 months, while that of positive patients was 8.8 months.

Therefore, 6-TAAb has no predictive performance preference for patients with advanced lung cancer of different subtypes, and can be applied to 6-TAAb autoantibody combination detection. Also, in different subtypes of lung cancer, positive 6-TAAb detection results predict that patients will be prone to benefit or good therapeutic effect from immunotherapy, such as ICI therapy; negative 6-TAAb autoantibody combination detection results, predicted not to benefit readily from immunotherapy, such as ICI therapy; when the 6-TAAb autoantibody combination detection result is "abnormal", it is predicted that a worse therapeutic effect is obtained from immunotherapy such as ICI treatment, i.e., the disadvantage is greater than the advantage.

The results are shown in FIG. 3.

Example 5

Patients receiving ICI treatment are classified into first line treatment patients and post line treatment patients according to the number of treatment lines of the verification queue patients. Of the first-line treated patients, positive 6-TAAb patients had significantly longer number of stages in no-progress than negative patients; the objective remission rate was 52.4% for positive patients, which was significantly higher than 29.4% for negative patients. Of post-line treated patients, positive TAAb patients had a median progression-free survival of 8.8 months, and negative patients had a survival of 3.71 months; the objective remission rate of positive 6-TAAb patients is 50%, and the objective remission rate of negative patients is 16%.

When the 6-TAAb detection of a patient is "abnormal", such a patient does not show significant differences in therapeutic efficacy from a negative patient in a first-line treated patient; whereas in post-line treated patients, the objective remission rate for "abnormal 6-TAAb" patients was 0%, significantly lower than 16% for negative patients. Regardless of the number of treatment lines, the median progression-free survival of "abnormal 6-TAAb" patients was significantly shorter than that of positive patients. In first line treatment, the median progression-free survival of "abnormal 6-TAAb" patients was 6.54 months, and positive patients were 10.48 months; in post-line treatment, the "abnormal 6-TAAb" patient was 1.66 months, and the positive patient was 4.67 months.

Therefore, 6-TAAb has no preference in predicting performance for patients with advanced lung cancer with different treatment line numbers, and can be applied to 6-TAAb autoantibody combination detection. Also, in different treatment line number lung cancer, positive 6-TAAb detection results predict that patients will be prone to benefit or good treatment outcome from immunotherapy, e.g., ICI treatment; negative 6-TAAb autoantibody combination detection results, predicted not to benefit readily from immunotherapy, such as ICI therapy; when the 6-TAAb autoantibody combination detection result is "abnormal", it is predicted that a worse therapeutic effect is obtained from immunotherapy such as ICI treatment, i.e., the disadvantage is greater than the advantage.

The results are shown in FIG. 4.

Example 6

Patients are classified into ICI monotherapy patients and chemotherapy/ICI combination therapy patients according to the administration of the patients in the verification queue. In the single drug treated patient group, the median progression-free survival for 6-TAAb positive patients was significantly longer than for negative patients, and the objective remission rate was 40%, which was significantly higher than for 28.6% of negative patients. Similarly, the median progression-free survival for 6-TAAb positive patients was 7.2 months in chemotherapy/ICI combination patients, and 4.3 months for negative patients; in terms of objective remission rate, the 6-TAAb positive patients were 40.6%, slightly better than the negative patients by 39.1%.

When the 6-TAAb detection result of the patient is abnormal, the objective remission rate is 0% in the single-drug treatment patient and is far lower than 28.6% of the negative patient, which indicates that the ICI treatment does not bring any positive effect; the median progression-free survival was only 1.28 months, while the negative patient was 3.25 months. In patients treated by chemotherapy/ICI combination, the objective remission rate of 6-TAAb abnormal patients is 17.3 percent, which is slightly lower than 20 percent of negative patients; the median progression-free survival was 2.48 months in patients with 6-TAAb abnormalities, much shorter than 7.2 months in positive patients.

Therefore, 6-TAAb has no preference in predicting performance for patients with advanced lung cancer in different administration conditions, and can be applied to 6-TAAb autoantibody combination detection. Moreover, in lung cancer with different dosing situations, positive 6-TAAb detection results predict that patients will be prone to benefit or good therapeutic effect from immunotherapy, e.g. ICI therapy; negative 6-TAAb autoantibody combination detection results, predicted not to benefit readily from immunotherapy, such as ICI therapy; when the 6-TAAb autoantibody combination detection result is "abnormal", it is predicted that a worse therapeutic effect is obtained from immunotherapy such as ICI treatment, i.e., the disadvantage is greater than the advantage.

The results are shown in FIG. 5.

The above description of the embodiments of the present invention is not intended to limit the present invention, and those skilled in the art can make various changes or modifications according to the present invention without departing from the spirit of the present invention, and shall fall within the scope of the appended claims.

Claims

1. A biomarker for predicting or judging the effect of a tumor immunotherapy in a subject, the biomarker being an autoantibody combination comprising autoantibodies against the following Tumor Associated Antigens (TAAs): trim21, BRCA2, P53, IMP2, MAGE-A4, TXNDC2.

2. The biomarker according to claim 1, wherein the autoantibodies are autoantibodies in a sample such as serum, plasma, interstitial fluid, cerebrospinal fluid or urine prior to subjecting the subject to tumour immunotherapy;

preferably, the autoantibody is IgA, igM or IgG.

3. The biomarker according to claim 1 or 2, wherein the subject is a mammal, preferably a primate mammal, more preferably a human;

preferably, the tumor is renal cancer, liver cancer, ovarian cancer, cervical cancer, squamous cell carcinoma of the head and neck, nasopharyngeal cancer, urothelial cancer, laryngeal cancer, gastric cancer, melanoma, prostate cancer, hodgkin's lymphoma, bladder cancer, colorectal cancer, lung cancer, in particular lung cancer, such as small cell lung cancer, non-small cell lung cancer, squamous lung cancer, adenocarcinoma of the lung, and other subtypes of lung cancer;

preferably, the immunotherapy comprises treatment with an immune checkpoint inhibitor; preferably, the immune therapy is an immune checkpoint inhibitor therapy alone or in combination with chemotherapy, radiation therapy, anti-vascular therapy, targeted therapy or other tumor treatment means, wherein the immune checkpoint inhibitor is an immune checkpoint inhibitor against PD-1, PD-L1, CTLA-4, BTLA, TIM-3, LAG-3, TIGIT, LAIR1, 2B4 and/or CD160, preferably an anti-PD-1 antibody or an anti-PD-L1 antibody.

4. A reagent for detecting the biomarker of any of claims 1 to 3.

5. The reagent according to claim 4, wherein the reagent is a reagent for enzyme-linked immunosorbent assay (ELISA), protein/peptide fragment chip detection, immunoblotting, microbead immunodetection, microfluidic immunodetection; preferably, the reagent is used to detect the biomarker by an antigen-antibody reaction, for example by ELISA;

more preferably, the reagent is an antigen protein combination for detecting the autoantibody combination, the antigen protein combination comprising the following antigen proteins: trim21, BRCA2, P53, IMP2, MAGE-A4, TXNDC2.

6. Use of a biomarker according to any of claims 1 to 3 or an agent according to claim 4 or 5, in the manufacture of a product for predicting or judging the effect of tumour immunotherapy in a subject.

7. The use according to claim 6, wherein the subject is a mammal, preferably a primate mammal, more preferably a human;

preferably, the tumor is renal cancer, liver cancer, ovarian cancer, cervical cancer, squamous cell carcinoma of the head and neck, nasopharyngeal cancer, urothelial cancer, laryngeal cancer, gastric cancer, melanoma, prostate cancer, hodgkin's lymphoma, bladder cancer, colorectal cancer, lung cancer, in particular lung cancer, such as small cell lung cancer, non-small cell lung cancer, squamous lung cancer, adenocarcinoma of the lung, and other subtypes of lung cancer.

8. The use of claim 7, wherein the immunotherapy comprises treatment with an immune checkpoint inhibitor;

preferably, the immune therapy is an immune checkpoint inhibitor therapy alone or in combination with chemotherapy, radiation therapy, anti-vascular therapy, targeted therapy or other tumor treatment means, wherein the immune checkpoint inhibitor is an immune checkpoint inhibitor against PD-1, PD-L1, CTLA-4, BTLA, TIM-3, LAG-3, TIGIT, LAIR1, 2B4 and/or CD160, preferably an anti-PD-1 antibody or an anti-PD-L1 antibody.

9. A kit comprising the reagent of claim 4 or 5.

10. The kit according to claim 9, wherein the kit is a kit for enzyme-linked immunosorbent assay (ELISA), protein/peptide chip detection, immunoblotting, microbead immunoassay, microfluidic immunoassay; preferably, the kit is for detecting the biomarker by an antigen-antibody reaction;

more preferably, the kit is an ELISA detection kit.