Method for predicting antibody ADCC activity and application thereof

Abstract

The present invention provides a method of predicting ADCC activity of an antibody, comprising: (1) obtaining two or more samples of the antibody, the two or more samples having different defucosylation ratios; (2) respectively detecting the fucosylation removal ratio alpha and the ADCC activity EC50 value of the sample, and substituting into the following formula: # imgabs0 # to obtain the values of constants M and N, so as to obtain a relation equation of the fucosylation removal ratio alpha and the ADCC activity EC50 value of the antibody; and (3) substituting the given fucosylation removal proportion of the antibody into the relation equation to obtain the ADCC activity of the antibody under the fucosylation removal proportion.

Description

[0001] Cross - reference to related applications

[0002] This application claims the priority of a Chinese patent application with the application number CN 202311757108.0 and the filing date of December 19, 2023. The entire content of this application is incorporated herein by reference. Technical Field

[0003] The present invention relates to the field of antibodies. Specifically, the present invention relates to methods for predicting the ADCC activity of antibodies and their applications. Background Art

[0004] ADCC, antibody-dependent cell-mediated cytotoxicity, refers to the binding of the Fab segment of an antibody to the antigen epitope of a virus-infected cell or a tumor cell, and its Fc segment binds to the FcR on the surface of killer cells (NK cells, macrophages, etc.), mediating the direct killing of target cells by the killer cells. Antibodies, as components of the immune system, play an important role in disease resistance. There are various methods for detecting ADCC activity, such as the classic method using PBMC or NK cells highly expressing CD16a as effector cells to exert target cell killing, and the indirect ADCC reporter gene method using human-constructed reporter gene cells highly expressing CD16a as effector cells. Non-cell-based means for evaluating ADCC activity also include CD16a affinity detection (ELISA method, SPR or BLI), and the ADCC substitution method based on ELISA bridging the target protein and CD16a. Although cell-based ADCC experiments can simulate the cell killing effect in vitro, they have large method variability, high cost, and long cycle. The separate affinity study of CD16a only involves the binding of the Fc end of the antibody and cannot reflect the cascade effect after the Fab end of the antibody binds to the target protein and the Fc end binds to CD16a, and cannot comprehensively reflect the ADCC activity. The ADCC reporter gene method and the ADCC substitution method (ELISA bridging experiment) both have the advantages of good stability and high accuracy and can be used as quality control methods for ADCC evaluation. However, for antibody projects in the CMC stage, if samples of different glycoforms obtained at different process stages are all tested for ADCC activity, it will face the risks of long experimental cycle, high experimental cost, and delays caused by the process waiting for test results.

[0005] N-glycosylation modification at the Fc region of IgG antibodies is often related to the effector functions of antibodies. Although N-glycosylation modification at the Fc region of antibodies does not affect the binding of the Fab region of antibodies to antigens or the binding of antibodies to protein A, it often affects the binding of antibodies to Fcγ receptors and C1q, thereby affecting antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent antibody-mediated cytotoxicity (CDC). Therefore, the type and proportion of glycosylation modification are often regarded as a key quality attribute (CQA) of IgG antibody drugs.

[0006] Among various types of glycosylation modifications, fucosylation has always been considered to be closely related to the ADCC activity of antibodies. Defucosylation can increase the affinity of antibodies for the FcγRIIIa receptor, thereby enhancing the ADCC activity of antibodies. [5] . To study the quantitative relationship between the defucosylation ratio and ADCC activity, Chung et al. first used FUT-8 knockout CHO cells to express defucosylated antibodies, which were mixed with antibodies expressed by wild-type CHO cells at different ratios to produce antibodies with different defucosylation ratios. By detecting the Fcγ receptor binding activity and ADCC activity of these antibodies, it was first found that the relative activity of ADCC was linearly positively correlated with the defucosylation ratio of antibodies ("Quantitative evaluation of fucose reducing effects in a humanized antibody on Fcγ receptor binding and antibody-dependent cell-mediated cytotoxicity activities." MAbs. Vol. 4. No. 3. Taylor & Francis, 2012.). However, this study did not elaborate on which factors determined the equation of the fitted straight line in this linear relationship. That is to say, this study did not fully explain the factors affecting the linear relationship between ADCC activity and the defucosylation ratio of antibodies. Moreover, the ADCC method used in this study had a large variability, high cost, long cycle, and low throughput. To date, no literature has reported a convenient and effective method for predicting ADCC activity through the defucosylation ratio of antibodies. Summary of the Invention

[0007] The first aspect of the present invention provides a method for predicting the ADCC activity of antibodies, comprising the following steps:

[0008] (1) Obtaining two or more samples of the antibody, wherein the two or more samples have different defucosylation ratios;

[0009] (2) Detect the afucosylation ratio α and the ADCC activity EC 50 value of the sample respectively, and substitute them into the following formula:

[0010]

[0011] Obtain the values of constants M and N, and obtain the relationship equation between the afucosylation ratio α and the ADCC activity EC 50 value of the antibody; and

[0012] (3) Substitute the given afucosylation ratio of the antibody into the relationship equation to obtain the ADCC activity of the antibody at this afucosylation ratio.

[0013] In some embodiments, the EC 50 value is determined by a cell killing-based assay method, a reporter gene-based assay method, or an ELISA-based bridging assay method.

[0014] In some embodiments, the number of samples is two.

[0015] In some embodiments, the afucosylation ratios of the two samples are 0%-50% and 50%-100% respectively.

[0016] In some embodiments, the two samples are an antibody sample expressed by a wild-type host cell and an antibody sample expressed by a host cell genetically modified to reduce the fucosylation ratio of the expressed antibody respectively.

[0017] In some embodiments, the afucosylation ratios of the two samples are 0%-15% and 85%-100% respectively.

[0018] In some embodiments, the host cell genetically modified to reduce the fucosylation ratio of the expressed antibody is a host cell with the FUT8 gene knocked out.

[0019] In some embodiments, the host cell is a CHO cell.

[0020] In some embodiments, the host cell is a CHO-K1 cell.

[0021] In some embodiments, the afucosylation ratio is determined by the sum of the ratios of glycoforms with a ratio higher than 1% in the antibody.

[0022] In some embodiments, the afucosylation ratio is determined by the sum of the ratios of G0-GN, G0, Man5, Man4, and G1.

[0023] The second aspect of the present invention provides a kit for predicting the ADCC activity of an antibody, comprising two or more samples of the antibody to be tested, and an instruction manual for explaining the method of predicting the antibody ADCC; wherein the two or more samples have different defucosylation ratios, and the instruction manual describes the above ADCC prediction method.

[0024] The third aspect of the present invention provides a method for producing an antibody, comprising the following steps:

[0025] (1) Obtain two or more samples of the antibody, the two or more samples having different defucosylation ratios, and respectively detect the defucosylation ratio α and the ADCC activity EC 50 value, and substitute it into the following formula:

[0026]

[0027] Obtain the values of constants M and N, and obtain the relationship equation between the defucosylation ratio α and the ADCC activity EC 50 value of the antibody. Substitute the desired antibody ADCC activity into the equation to obtain the defucosylation ratio corresponding to the ADCC activity; and

[0028] (2) Produce an antibody, the defucosylation ratio of the antibody being the defucosylation ratio obtained in step (1).

[0029] In some embodiments, the process of producing the antibody in step (2) includes culturing a host cell and expressing the antibody in the host cell.

[0030] In some embodiments, the process of culturing the host cell includes adding a fucosylation inhibitor and / or Mn 2+ .

[0031] In a fourth aspect, the present invention provides a method for predicting the ADCC activity of an antibody, characterized in that the method includes:

[0032] Based on the defucosylation ratio α and the ADCC activity EC 50 value information of two or more samples of the antibody, fitting to obtain the relationship equation between the defucosylation ratio α and the ADCC activity EC 50 value of the antibody:

[0033] Based on the given defucosylation ratio α of the given antibody sample to be tested, obtain the predicted ADCC activity result of the antibody to be tested.

[0034] In some embodiments, the defucosylation ratios of two samples are 0%-15% and 85%-100% respectively.

[0035] In a fifth aspect, the present invention provides a computer-implemented system for predicting the ADCC activity of an antibody. The computer-implemented system performs the following operations by executing a computer program:

[0036] Obtain the defucosylation ratio α and ADCC activity EC 50 value information of two or more samples of the antibody;

[0037] By inputting the defucosylation ratio α and ADCC activity EC 50 value information of the antibody sample, fitting to obtain the relationship equation between the defucosylation ratio α and ADCC activity EC 50 value of the antibody:

[0038] By inputting the given defucosylation ratio α of the antibody sample to be tested, obtain the predicted ADCC activity result of the antibody to be tested.

[0039] In a sixth aspect, the present invention provides a non-transitory computer-readable storage medium for storing a computer program. The computer program includes instructions, and when the instructions are executed by a processor of an electronic device, the electronic device implements the method for predicting antibody ADCC as described in the fourth aspect.

[0040] In a seventh aspect, the present invention provides a computer system, the computer system includes:

[0041] A processor;

[0042] A memory; and

[0043] A computer program, wherein the computer program is stored in the memory and is configured to be executed by the processor. The computer program includes a method for implementing the prediction of antibody ADCC activity as described in the fourth aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 Schematic diagrams showing different types of sugars and modified antibodies, where (A) shows that the antibody has glycosylation modification in the Fc region; (B) shows different types of glycoforms of the modified antibody.

[0045] Figure 2 Showing the fitting curve of the defucosylation ratio and ADCC activity of the antibody detected by the reporter gene method.

[0046] Figure 3Show the fitting curve of the fucose removal ratio and ADCC activity of the antibody based on the ADCC alternative method detection.

[0047] Figure 4 Show the accuracy of the predicted ADCC activity of the antibody based on the reporter gene method and the ADCC alternative method. Detailed implementation mode

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] All publications, patent applications, patents and other references mentioned herein are incorporated herein by reference in their entirety. In case of conflict, the present specification (including definitions) shall prevail. Additionally, the materials, methods and examples described herein are illustrative only and not intended to be limiting.

[0050] When the terms "about" and "approximate" are used in conjunction with numerical variables, they generally mean that the value of the variable and all values of the variable are within the measurement or experimental error (e.g., 95% confidence interval of the mean) or within a wider range of the specified value (e.g., ±5% or ±10%).

[0051] The term "comprising" or its variants such as "containing", "having", "including" means including the stated steps or elements, but not excluding any other steps or elements. "Consisting of" means not including the steps or elements not listed. "Consisting essentially of" means not excluding those steps or elements that do not materially affect the basic and novel features of the claimed invention. The term "comprising" a specific step or element and its variants also includes the cases of "consisting of" the specific step or element and "consisting essentially of" the specific step or element.

[0052] When referring to a numerical range, it should be regarded as specifically disclosing the specific values of its upper and lower limits, as well as all intermediate ranges included therein, such as the intermediate range between its upper or lower limit and any intermediate value, or the intermediate range between any two of its intermediate values. And, any intermediate range, sub-range and all individual numerical values described in the said numerical range can be excluded from the said numerical range.

[0053] The term "and / or" should be understood as any one or any combination of several elements connected by this term.

[0054] The present inventors have determined the linear relationship between the antibody defucosylation ratio and ADCC activity and its influencing parameters, and established a method for predicting the ADCC activity of an antibody based on this linear relationship and the antibody defucosylation ratio. Through this method, not only can the ADCC activity of an antibody be predicted, but also the influence of the antibody defucosylation ratio on its ADCC activity can be further understood, which has certain guiding significance for the process development of antibody production. This idea is also applicable to the antibody discovery stage, that is, enhancing the ADCC activity by regulating the defucosylation ratio.

[0055] Based on the established linear relationship between the antibody defucosylation ratio and ADCC activity of the present invention, by detecting the defucosylation ratio and ADCC activity EC of two or more samples of the antibody 50 value, substituting it into the following formula: where α is the defucosylation ratio of the antibody, and the coefficients M and N of the equation reflecting the linear relationship between the two parameters of 1 / EC 50 and α can be determined, thereby determining the relationship equation between the defucosylation ratio α of the antibody and the ADCC activity EC 50 value. Subsequently, for the antibody with a given defucosylation ratio, its corresponding ADCC activity can be easily determined through this relationship equation; similarly, for the desired antibody ADCC activity, it can also be determined through this relationship equation at what defucosylation ratio the antibody will have the desired antibody ADCC activity. For the antibody sample to be tested, only the defucosylation ratio needs to be simply measured, and the predicted ADCC activity can be obtained using this equation. Those skilled in the art should understand that when the defucosylation ratio and ADCC activity of two samples are known, the coefficients M and N can be calculated by solving a simple binary linear equation. When the number of samples is greater than 2, the coefficients M and N can be determined by linear fitting.

[0056] The antibodies involved in the method of the present invention include an Fc domain, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (such as bispecific antibodies) and antibody fragments. In some embodiments, the antibody is an anti-HER2 antibody. In some embodiments, the antibody is Trastuzumab.

[0057] The different samples of the antibodies involved in the method of the present invention are samples that have the same antibody amino acid sequence (including the heavy chain variable region, the heavy chain constant region CH1, the Fc region, the light chain variable region, and / or the light chain constant region), but may have different antibody defucosylation ratios. It should be understood that the antibodies in two or more antibody samples used to determine the relationship equation between the antibody defucosylation ratio and the ADCC activity have the same antibody amino acid sequence, but have different defucosylation ratios from each other. The antibody amino acid sequence of the antibody sample to be tested is the same as that of the two or more antibody samples used to determine the relationship equation between the antibody defucosylation ratio and the ADCC activity.

[0058] The antibody samples involved in the method of the present invention, such as two or more antibody samples and / or samples to be tested used to determine the relationship equation between the antibody defucosylation ratio and the ADCC activity, can be obtained by methods well known in the art. For example, the antibody can be recombinantly expressed by a host cell and then obtained as an antibody sample after separation and purification. The method of expressing an antibody in a host cell is well known in the art. For example, a polynucleotide sequence encoding an antibody (such as an antibody heavy chain and light chain) operably linked to an expression control sequence (including but not limited to a promoter) can be introduced into a host cell to cause the host cell to express the antibody. Host cells for expressing antibodies are well known to those skilled in the art. For example, they can be human-derived cells or non-human mammalian-derived cells, such as murine-derived cells. Suitable host cells include but are not limited to murine-derived cells, such as CHO cells (such as CHO-K1 cells), SP2 / 0 cells, NS0 cells, BHK cells, or MF-9 cells; or human-derived cells, such as HEK293 cells or PER cells, etc., which can be wild-type host cells or genetically modified host cells. In some embodiments, the antibody recombinantly expressed by the host cell can be secreted into the culture supernatant of the host cell and then separated and purified to obtain the sample. In some embodiments, the separation and purification includes subjecting the culture supernatant to chromatography, such as affinity chromatography.

[0059] Antibody samples with different degrees of afucosylation can be obtained by means well-known in the art for regulating the degree of afucosylation of antibodies. For example, antibody samples with different degrees of afucosylation can be obtained by expressing antibodies using different host cells, which can result in different degrees of afucosylation of the same glycoprotein (such as an antibody) when expressing it. For example, antibodies with a higher degree of afucosylation can be obtained by expressing antibodies using host cells that have been genetically modified to reduce fucose synthesis or modification. The term "reduce fucose synthesis or modification" here means that compared with the host cells that have not been genetically modified, the amount of fucose synthesis in the genetically modified host cells is reduced or eliminated, and / or the fucosylation modification in the glycoprotein (such as an antibody) recombinantly expressed by the host cells is reduced or eliminated. For example, the antibody recombinantly expressed using CHOLec13 cells with a mutated GDP-mannose 4,6-dehydratase (GMD) gene as the host cell has a higher degree of afucosylation than the antibody recombinantly expressed by wild-type CHO cells; the antibody recombinantly expressed using host cells with the FUT8 (fucosyltransferase) gene knocked out has a higher degree of afucosylation than the antibody recombinantly expressed by wild-type cells; the antibody recombinantly expressed using CHO cells with the GDP-fucose transporter (SLC35C1) gene inactivated has a higher degree of afucosylation than the antibody recombinantly expressed by wild-type CHO cells (see Pereira N A, Chan K F, Lin P C, et al. The “less-is-more” in therapeutic antibodies: Afucosylated anti-cancer antibodies with enhanced antibody-dependent cellular cytotoxicity, MAbs. Taylor & Francis, 2018, 10(5):693-711). In addition, during the process of culturing host cells to express antibodies, the degree of fucosylation can also be adjusted by adjusting cell culture process parameters, such as adjusting pH, osmotic pressure, culture time, dissolved oxygen, culture temperature, shear force, culture medium additives (such as adding fucosylation inhibitors or Mn 2+ etc.) and culture mode (see Jiang Yifan et al., Influence and regulation of cell culture process on glycosylation modification of monoclonal antibodies, China Biotechnology Journal, 2019, 39(8):95-103).

[0060] In some embodiments, different defucosylation ratios of the antibody sample are obtained by controlling the host cell culture conditions. In some embodiments, different defucosylation modification ratios of the antibody sample are obtained by expressing with genetically engineered host cells. In some embodiments, the antibody sample, such as two or more antibody samples for determining the relationship equation between the defucosylation ratio of the antibody and the ADCC activity, may have a defucosylation ratio between 0% and 100%. For example, the fucosylation ratio may be selected from 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and / or 100%. In some embodiments, the difference in defucosylation ratio between any two of the antibody samples, such as two or more antibody samples for determining the relationship equation between the defucosylation ratio of the antibody and the ADCC activity, is not less than 10%, not less than 20%, not less than 30%, not less than 40%, not less than 50%, not less than 60%, not less than 70%, not less than 80% or not less than 90%. In some preferred embodiments, the difference in defucosylation ratio between any two of the antibody samples, such as two or more antibody samples for determining the relationship equation between the defucosylation ratio of the antibody and the ADCC activity, is not less than 50%, not less than 60%, not less than 70%, not less than 80% or not less than 90%.

[0061] In some embodiments, the antibody samples involved in the method of the present invention, such as two or more antibody samples and / or samples to be tested for determining the relationship equation between the afucosylation ratio of an antibody and its ADCC activity, may include antibodies recombinantly expressed by wild-type host cells (such as wild-type CHO cells, such as wild-type CHO-K1 cells). In some embodiments, the antibody samples involved in the method of the present invention, such as two or more antibody samples and / or samples to be tested for determining the relationship equation between the afucosylation ratio of an antibody and its ADCC activity, may include antibodies recombinantly expressed by genetically engineered host cells, where the genetic engineering may be genetic engineering capable of reducing fucose synthesis or modification in the host cells, for example, genes related to fucose synthesis or modification may be modified (such as knocked out). In some embodiments, the genetic engineering may, for example, be such that one, two, or three of the GDP-mannose 4,6-dehydratase (GMD) gene, FUT8 (fucosyltransferase) gene, and GDP-fucose transporter (SLC35C1) gene are knocked out. In some embodiments, two or more antibody samples for determining the relationship equation between the afucosylation ratio of an antibody and its ADCC activity include antibodies recombinantly expressed by wild-type host cells (such as wild-type CHO cells, such as wild-type CHO-K1 cells), and / or antibodies recombinantly expressed by host cells in which one, two, or three of the GDP-mannose 4,6-dehydratase (GMD) gene, FUT8 (fucosyltransferase 8) gene, and GDP-fucose transporter (SLC35C1) gene are knocked out (such as CHO cells in which the genes are knocked out, such as CHO-K1 cells). In some embodiments, the antibody samples involved in the method of the present invention, such as two or more antibody samples for determining the relationship equation between the afucosylation ratio of an antibody and its ADCC activity, may also include antibody samples formed by mixing antibodies recombinantly expressed by different host cells in different proportions, such as antibody samples formed by mixing antibodies recombinantly expressed by wild-type host cells and antibodies recombinantly expressed by genetically engineered host cells as described herein in different proportions.

[0062] The techniques for mutating or knocking out specific genes in host cells are well-known to those skilled in the art and can be achieved through various techniques, such as CRISPR / Cas9 technology, transcription activator-like effector nuclease (TALEN) technology, zinc-finger nuclease (ZFN), etc.

[0063] In some embodiments, the number of antibody samples for determining the relationship equation between the afucosylation ratio and the ADCC activity is two. In some embodiments, these two antibody samples are expressed by wild-type host cells and host cells with FUT8 gene knockout, respectively. In some embodiments, the difference in the afucosylation ratio of these two antibody samples is not less than 10%, not less than 20%, not less than 30%, not less than 40%, not less than 50%, not less than 60%, not less than 70%, not less than 80%, or not less than 90%. In some embodiments, the afucosylation ratios of these two antibody samples are between 0% - 50% and 50% - 100%, respectively. In some embodiments, the afucosylation modification ratios of these two antibody samples are selected from 0%, 10%, 20%, 30%, and 40%, and selected from 50%, 60%, 70%, 80%, 90%, and 100%. In some embodiments, the afucosylation modification ratios of these two antibody samples are 0% - 15% and 85% - 100%, respectively.

[0064] The "afucosylation level" or "afucosylation ratio" refers to the ratio of the fucose-free glycosylation modification of the antibody. In some embodiments, the afucosylation level can be characterized or determined by the sum of the ratios of the fucose-free glycoforms in the glycosylation modification of the antibody. In some embodiments, the afucosylation level can be characterized or determined by the sum of the ratios of the fucose-free glycoforms with a ratio higher than 1% in the glycosylation modification of the antibody. In some embodiments, the afucosylation level is characterized or determined by the sum of the ratios of G0 - GN, G0, Man5, Man4, and G1.

[0065] The methods for detecting antibody glycoforms are well-known to those skilled in the art and can be used to determine the types and / or ratios of antibody glycoforms. Suitable methods include, but are not limited to, analyzing the glycoforms of the glycosylation modification of the antibody by techniques such as HILIC-UHPLC or MALDI-TOF.

[0066] In the present invention, the ADCC activity of the antibody can be characterized or determined by the reciprocal of EC 50 . In some embodiments, the reciprocal of EC 50 has a linear relationship with the afucosylation ratio. The linear relationship between the afucosylation ratio of the antibody and the ADCC activity can be characterized by the following formula (I):

[0067]

[0068] where α represents the afucosylation ratio of the antibody.

[0069] In some embodiments, the ADCC activity of the antibody (such as EC 50The value) can be detected by an assay method based on cell killing. The assay method based on cell killing includes using PBMC or NK cells as effector cells and measuring the ADCC activity EC of the antibody by detecting the killing effect of the effector cells on target cells. 50 value.

[0070] In some embodiments, the ADCC activity (such as EC 50 value) of the antibody can be detected by a reporter gene-based assay. The reporter gene-based assay refers to using transfected cells stably expressing FcR (such as FcγR, such as FcγRIIIa) and a reporter gene as effector cells and measuring the ADCC activity of the antibody by detecting the expression level of the reporter gene. In some embodiments, the effector cells are Jurkat cells. In some embodiments, the reporter gene is a luciferase gene driven by an NFAT response element. In some embodiments, in the reporter gene-based assay, Jurkat cells expressing the FcγRIIIa receptor (such as 158F or 158V) and luciferase driven by an NFAT response element are used as effector cells, and the ADCC activity EC of the antibody is measured by detecting the luminescence signal of luciferase. 50 value.

[0071] In some embodiments, the ADCC activity (such as EC 50 value) of the antibody can be detected by an ELISA-based bridging assay (which may also be referred to herein as "ADCC surrogate method", "ELISA bridging" or "ADCC surrogate ELISA"). The ELISA-based bridging assay is a cell-free assay that binds the Fab end of the antibody to an immobilized antigen, adds a tag protein to bind the tag protein to the Fc region of the antibody, and then adds a ligand that can develop color. The ligand binds to the tag protein, and the ADCC activity EC of the antibody is measured by detecting the ligand. 50Value. In some embodiments, the tagged protein is a tagged FcR molecule, such as an FcγR molecule, such as FcγRIIIa (e.g., FcγRIIIa 158F or 158V). In some embodiments, the tag is selected from GST, biotin, His, Flag, or c-Myc, and the ligand comprises a molecule that can bind to the tag, such as streptavidin, glutathione, or an antibody that can specifically bind to the tag. In some embodiments, the ligand further comprises horseradish peroxidase (HRP). In some embodiments, the ligand is detected by an HRP-TMB colorimetric system. In some embodiments, the ELISA-based bridging assay method comprises binding an antibody to an immobilized antigen, binding the Fc region of the antibody to a biotinylated FcR (such as FcγRIIIa, e.g., FcγRIIIa 158F or 158V), adding streptavidin-HRP (SA-HRP) labeled with HRP to bind to the biotin on the FcR, and then adding the chromogenic substrate TMB, and measuring the ADCC activity EC of the antibody by detecting the absorbance at specific wavelengths (such as 450 nm and 630 nm). 50 Value. In some embodiments, the ELISA-based bridging assay method can be carried out according to the method described by Miller et al. (Development of an ELISA based bridging assay as a surrogate measure of ADCC [J]. Journal of immunological methods, 2012, 385(1-2): 45-50).

[0072] The present invention also relates to a kit for predicting the ADCC activity of an antibody, comprising two or more antibody samples for determining the relationship equation between the afucosylation ratio and the ADCC activity of the antibody as described above, or host cells for expressing these antibody samples. In some embodiments, the kit further comprises an instruction manual for the method of predicting the ADCC activity of an antibody described herein. For example, antibody samples with different afucosylation ratios can be obtained by expressing antibodies using different host cells, and the different host cells can cause the same glycoprotein (such as an antibody) to have different afucosylation ratios when expressing the same glycoprotein. In some embodiments, when these different host cells are used to express the same glycoprotein (such as an antibody), the difference in the afucosylation ratio between any two host cells expressing the same glycoprotein (such as an antibody) is not less than 10%, not less than 20%, not less than 30%, not less than 40%, not less than 50%, not less than 60%, not less than 70%, not less than 80%, or not less than 90%.

[0073] In some embodiments, the kit includes host cells for expressing the two or more antibody samples, and these host cells can result in different degrees of fucosylation of the same glycoprotein (such as an antibody) when expressing the same glycoprotein. In some embodiments, these host cells contain polynucleotides encoding the antibody and can express the antibody, which can be directly used to predict the ADCC activity of the antibody. In some embodiments, these host cells do not contain polynucleotides encoding the antibody, that is, the polynucleotides encoding the antibody have not been introduced into these host cells. Such host cells can be used to express different antibody samples and can be used for predicting the ADCC activity of different antibodies.

[0074] In some embodiments, the kit may include wild-type host cells and host cells genetically engineered to reduce the fucosylation ratio of the glycoproteins expressed in their cells. In some embodiments, the kit includes host cells expressing the antibody samples. For example, it may include wild-type host cells expressing the antibody and host cells expressing the antibody and genetically engineered to reduce the fucosylation ratio of the expressed antibody. In some embodiments, neither the wild-type host cells nor the genetically engineered host cells included in the kit contain polynucleotides encoding the antibody. In some embodiments, the genetically engineered host cells are host cells with the FUT8 gene knocked out. In some embodiments, these host cells can be CHO cells, such as CHO-K1 cells.

[0075] Using the ADCC activity prediction method of the present invention can guide antibody production. In some embodiments, when performing antibody production, the relationship equation between the antibody ADCC activity and its fucosylation ratio can be obtained by the aforementioned method. Substitute the desired antibody ADCC activity into the equation to obtain the corresponding fucosylation ratio of the ADCC activity. In subsequent antibody production, an antibody with the corresponding fucosylation ratio can be produced, and the ADCC activity of this antibody is the desired ADCC activity.

[0076] Antibodies with a specific fucosylation ratio can be obtained by using techniques known to those skilled in the art. For example, host cells can be used to express the antibody, and the desired fucosylation ratio can be obtained by selecting the host cells and / or culture conditions.

[0077] In the selection of host cells, for example, antibodies with a lower degree of defucosylation can be obtained by using wild-type host cells, or antibodies with a higher degree of defucosylation can be obtained by using host cells that have been genetically modified to reduce the fucosylation of the expressed antibodies. The genetic modification can be, for example, knocking out the GDP-mannose 4,6-dehydratase (GMD) gene, knocking out the FUT8 (fucosyltransferase) gene, and / or knocking out the GDP-fucose transporter (SLC35C1) gene. Compared with the corresponding wild-type host cells, the host cells subjected to these genetic modifications will express antibodies with a higher degree of defucosylation. In some embodiments, the wild-type host cells can be wild-type CHO cells (such as CHO-K1 cells), SP2 / 0 cells, NS0 cells, BHK cells, MF-9 cells, HEK cells (such as HEK293 cells), or PER cells. In some embodiments, the host cells that have been genetically modified to reduce the fucosylation of the expressed antibodies can be CHO cells (such as CHO-K1 cells), SP2 / 0 cells, NS0 cells, BHK cells, MF-9 cells, HEK cells (such as HEK293 cells), or PER cells that have been subjected to the genetic modification. "Genetically modified to reduce the fucosylation of the expressed antibodies" means that the degree of defucosylation of the antibodies expressed by the host cells subjected to the genetic modification is higher than that of the antibodies expressed by the host cells not subjected to the genetic modification.

[0078] In the selection of culture conditions, culture conditions that can increase the degree of defucosylation of antibodies can be obtained by adjusting or controlling one or more of pH, dissolved oxygen, osmotic pressure, culture temperature, culture time, medium components, shear force, and culture mode during cell culture. In some embodiments, the culture conditions that can increase the degree of defucosylation of antibodies include adding a fucosylation inhibitor (such as a fucose analog, such as 2-fluoro-L-fucose (2FF)) or 2-fluoro-peracetyl-fucose (2FP) or 2-deoxy-2-fluoro-L-fucose and / or adding Mn 2+ .

[0079] The methods described herein can be further used to determine the sensitivity of the ADCC activity of a specific antibody to defucosylation modification, and can further be used to guide the design of the production process of the antibody to obtain a higher input-output ratio. "The sensitivity of the ADCC activity of an antibody to defucosylation modification" refers to the degree to which the ADCC activity of the antibody changes when the degree of defucosylation of the antibody changes.

[0080] During the development of antibody drug production processes, many cell culture process parameters can affect the glycan profile of antibodies, including but not limited to pH, osmotic pressure, culture time, dissolved oxygen, culture temperature, shear force, culture medium additives, culture mode, etc. (see Jiang Yifan et al., Effects and Regulation of Monoclonal Antibody Glycosylation Modification during Cell Culture Process, China Biotechnology Journal, 2019, 39(8): 95-103). Based on the concept of Quality by Design, different combinations of process parameters will produce a large number of antibodies with different glycan ratios. However, the intensity and effort of fucosylation ratio regulation depend on the understanding of the impact of glycan on ADCC function. A 1% change in fucosylation ratio may bring a 10-fold change in ADCC activity, or a 10% change in fucosylation ratio may only bring a 1% change in ADCC activity. Using the degree of influence of fucosylation ratio change on ADCC activity to guide antibody production process development not only saves a large amount of detection time and material costs, but also provides direction and certainty for glycan regulation in the process development stage.

[0081] Specifically, when the change in ADCC activity of an antibody with the change in fucosylation ratio is relatively large (or the ADCC activity of the antibody is relatively sensitive to fucosylation modification), the selection and / or control of host cells and / or culture conditions can be strengthened during production to increase the fucosylation ratio of the antibody, so that the produced antibody has high ADCC activity; when the change in ADCC activity of the antibody with the change in fucosylation ratio is relatively small (or the ADCC activity of the antibody is less sensitive to fucosylation modification), there is no need to select and / or control host cells and / or culture conditions during production, or reduce and / or relax the control of host cells and / or culture conditions, but focus on increasing production and shortening the cycle to reduce production costs. In some embodiments, for example, when the change in ADCC activity of an antibody with the change in fucosylation ratio is relatively large (or the ADCC activity of the antibody is relatively sensitive to fucosylation modification), the production process (such as the commonly used production process or the initial production process) can be adjusted by replacing the host cell used therein with a host cell that can increase the fucosylation ratio of the antibody compared thereto and / or adjusting the cell culture conditions used therein to culture conditions that can increase the fucosylation ratio of the antibody compared thereto; when the change in ADCC activity of the antibody with the change in fucosylation ratio is relatively small (or the ADCC activity of the antibody is less sensitive to fucosylation modification), no adjustment aimed at changing the fucosylation ratio (including replacement and / or adjustment of host cells and / or culture conditions aimed at changing the fucosylation ratio) is made to the production process.

[0082] In some embodiments, for example, when the change in the ADCC activity of an antibody with the change in the degree of defucosylation is relatively large (or in other words, the ADCC activity of the antibody is relatively sensitive to defucosylation modification), the degrees of defucosylation of antibodies obtained using different host cells and / or different culture conditions can be compared, and the host cells and / or culture conditions that can obtain the maximum degree of defucosylation of the antibody can be selected to produce the antibody; when the change in the ADCC activity of the antibody with the change in the degree of defucosylation is relatively small (or in other words, the ADCC activity of the antibody is relatively insensitive to defucosylation modification), such comparison and selection are not carried out to reduce production costs.

[0083] A host cell capable of increasing the degree of defucosylation of an antibody can be a host cell genetically modified to reduce the fucosylation modification of the expressed antibody. Such genetic modification can be, for example, knocking out the GDP-mannose 4,6-dehydratase (GMD) gene, knocking out the FUT8 (fucosyltransferase) gene, and / or knocking out the GDP-fucose transporter (SLC35C1) gene. Compared with the corresponding wild-type host cell, the host cell subjected to these genetic modifications will express an antibody with a higher degree of defucosylation. In some embodiments, the host cell genetically modified to reduce the fucosylation modification of the expressed antibody can be a CHO cell (such as CHO-K1 cell), SP2 / 0 cell, NS0 cell, BHK cell, MF-9 cell, HEK cell (such as HEK293 cell), or PER cell subjected to the above genetic modification. "Genetically modified to reduce the fucosylation modification of the expressed antibody" means that the degree of defucosylation of the antibody expressed by the host cell subjected to the genetic modification is higher than that of the antibody expressed by the host cell not subjected to the genetic modification.

[0084] Culture conditions capable of increasing the degree of defucosylation of an antibody can be obtained by adjusting or controlling one or more of pH, dissolved oxygen, osmotic pressure, culture temperature, culture time, culture medium components, shear force, and culture mode during the cell culture process. In some embodiments, the culture conditions capable of increasing the degree of defucosylation of an antibody include adding a fucosylation inhibitor (such as a fucose analog, such as 2-fluoro-L-fucose (2FF)) or 2-fluoro-peracetyl-fucose (2FP) or 2-deoxy-2-fluoro-L-fucose and / or adding Mn 2+ .

[0085] In some embodiments, when the ADCC activity of the antibody is sensitive to afucosylation, the antibody is produced using a host cell genetically engineered to reduce the fucosylation of the expressed antibody as described herein; when the ADCC activity of the antibody is less sensitive to afucosylation, the antibody is expressed and produced using a wild-type host cell or a host cell not genetically engineered for the purpose of reducing the fucosylation of the expressed antibody.

[0086] In some embodiments, the wild-type host cell can be a wild-type CHO cell (such as CHO-K1 cell), SP2 / 0 cell, NS0 cell, BHK cell, MF-9 cell, HEK cell (such as HEK293 cell) or PER cell.

[0087] In some embodiments, when the ADCC activity of the antibody is sensitive to afucosylation, a fucosylation inhibitor (such as a fucose analog, such as 2-fluoro-L-fucose (2FF)) or 2-fluoro-peracetyl-fucose (2FP) or 2-deoxy-2-fluoro-L-fucose) and / or Mn is added to the host cell culture medium 2+ ; while when the ADCC activity of the antibody is less sensitive to afucosylation, no fucosylation inhibitor and / or Mn is added to the host cell culture medium 2+ .

[0088] Term definitions

[0089] The term "antibody" refers to a protein or polypeptide that exhibits binding specificity for a specific antigen, including immunoglobulins or other types of molecules containing one or more antigen-binding domains that specifically bind the antigen. The term "antibody" is used in its broadest sense and encompasses various antibody structures, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (such as bispecific antibodies) and antibody fragments, as long as they contain an Fc domain. Antibodies are glycoproteins that are glycosylated in the Fc region, and specific examples thereof include but are not limited to intact antibodies (such as classical four-chain antibody molecules). In some embodiments, the antibodies of the present invention comprise a glycosylated Fc domain and an antigen-binding domain.

[0090] An intact antibody is an immunoglobulin molecule (such as IgG) composed of four polypeptide chains or a multimer thereof (such as IgA or IgM). The four polypeptide chains include two identical heavy chains (H) and two identical light chains (L), which are interconnected by disulfide bonds to form a tetramer. Each heavy chain consists of a heavy chain variable region ("HCVR" or "VH") and a heavy chain constant region (CH, including domains CH1, CH2 and CH3). Each light chain consists of a light chain variable region ("LCVR or "VL") and a light chain constant region (CL).

[0091] Antibodies can be classified into five main different types according to the amino acid sequence of the constant region of the heavy chain: IgA, IgD, IgE, IgG, and IgM. These antibody types can be further divided into subclasses according to the size of the hinge region, the position of the inter-chain disulfide bond, and the molecular weight. For example, IgG1, IgG2a, IgG2b, IgG3, and IgG4, etc. According to the differences in the amino acid composition and arrangement of the constant region of the antibody light chain, the light chain can be divided into two types: κ and λ. The antibodies of the present invention include antibodies of any of the aforementioned classes or subclasses.

[0092] The term "Fc region" or "Fc domain" refers to the crystallizable fragment (fragment crystallizable, Fc) at the C-terminus of the immunoglobulin heavy chain. This term includes wild-type Fc domains and variant Fc domains. In some embodiments, the human IgG heavy chain Fc domain extends from Cys226 or from Pro230 to the carboxyl terminus of the heavy chain (amino acid numbering is according to the EU numbering system, also known as the EU index, as described in Kabat et al., Sequences of Proteins of Immunological Interest, 5th Edition. Public Health Service, National Institutes of Health, Bethesda, MD, 1991). In some embodiments, this term includes the C-terminal fragment of the immunoglobulin heavy chain and one or more constant regions. In some embodiments, for IgG, the Fc domain may include the immunoglobulin domains CH2 and CH3 and the hinge between CH1 and CH2. The Fc region has effector functions, including C1q binding and complement-dependent cytotoxicity (CDC), Fc receptor binding, antibody-dependent cell-mediated cytotoxicity (ADCC), phagocytosis, downregulation of cell surface receptors (such as B cell receptors), and B cell activation, etc.

[0093] The term "Fc receptor" or "FcR" refers to a receptor that binds to the Fc region of an antibody, including but not limited to receptors of the FcγRI, FcγRII, and FcγRIII subclasses.

[0094] The term "complement-dependent cytotoxicity" or "CDC" refers to the ability of a molecule to lyse a target in the presence of complement. The complement activation pathway is initiated by the binding of the first component of the complement system (C1q) to a molecule (such as an antibody) complexed with a homologous antigen.

[0095] The term "antibody-dependent cell-mediated cytotoxicity" or "ADCC" refers to the killing of target cells mediated by effector cells, where the antibody binds to an antigen on the surface of the target cell, and the effector cell binds to the Fc region of the antibody through the Fc receptor (FcR) expressed on its surface, thereby mediating the killing of the target cell by the effector cell.

[0096] The term "effector cell" refers to a cell that expresses one or more FcRs and performs effector functions. In some embodiments, the effector cell expresses FcγRIII and performs ADCC effector functions. Effector cells can be peripheral blood mononuclear cells (PBMCs), natural killer (NK) cells, monocytes, cytotoxic T cells, and neutrophils. Effector cells can also be artificially constructed cells that express FcRs (such as FcγRIII).

[0097] The term "EC 50 " is the half maximal effective concentration, which refers to the concentration that can cause 50% of the maximum biological effect change.

[0098] The term "sample" herein refers to an antibody sample, which can be a substantially purified antibody. "Substantially purified" means that the antibody has undergone a procedure to remove components other than the antibody (e.g., removing other impurities from a mixture used to produce the antibody, such as cell culture supernatant). In some embodiments, "substantially purified" means that the target antibody constitutes approximately 50%, approximately 60%, approximately 70%, approximately 80%, approximately 90%, approximately 95% or more of the protein components in the sample.

[0099] As used herein, "two or more" includes 2, 3, 4, 5, 6, 7, 8, 9, 10 or more.

[0100] The term "glycosylation modification" refers to the glycosylation of proteins, which is one of the most common post-translational modifications of proteins and is the process of transferring sugars to specific amino acid residues on proteins to form glycosidic bonds under the action of glycosyltransferases. The glycosylation types of proteins can be mainly divided into two types: N-glycosylation and O-glycosylation. Among them, "N-glycosylation modification" refers to the covalent connection of N-glycans (or N-linked glycans) to the side chain amino part (-NH2) of asparagine of proteins. "O-glycosylation modification" refers to the covalent connection of O-glycans (or O-linked glycans) to the hydroxyl part (-OH) of serine or threonine of proteins.

[0101] The glycosylation modification of antibodies mainly includes N-glycosylation modification of the Fc region. As used herein, "glycosylation modification of antibodies" can also be referred to as "N-glycosylation modification of the Fc region" or "N-glycan modification of the Fc region". IgG-type monoclonal antibodies usually have N-glycosylation modification at Asn-297 in the CH2 region.

[0102] The term "glycoform" refers to the different N-glycans contained in the glycosylation modification of antibodies (especially the N-glycosylation modification of the Fc region). Antibody N-glycans can contain different numbers of sugar molecules, including mannose (Man), N-acetylglucosamine (GlcNAc), fucose (Fuc), galactose (Gal) and / or sialic acid (SA). The core structure of N-glycans is a bi-antennary "pentasaccharide" molecule composed of three mannose (Man) molecules and two N-acetylglucosamine (GlcNAc) molecules. On this basis, different sugar molecules can be added to form a complex and variable polysaccharide molecular structure. Common N-glycosylation modification glycoforms in antibodies include G0, G0F, G1, G1F, G2, G2F, G0-GN, G0F-GN, G1FGlcNAc, G0F-GlcNAc, Man4, Man5, Man8, Man9, etc.

[0103] The term "fucosylation" or "fucose modification" can also be referred to as "core fucosylation" or "core fucose modification", and in this article it refers to the glycosylation modification in antibodies containing core fucose, which includes linking the N-glycan containing core fucose to the Fc region of the antibody. The term "core fucose" refers to the fucose linked to the innermost N-acetylglucosamine (GluNAc) of the N-glycan in the form of an α-1,6 bond.

[0104] The term "defucosylation" or "defucose modification" refers to reducing the proportion of fucose modification in antibodies, that is, reducing the proportion of N-glycan modification containing fucose in antibodies. Methods for obtaining defucosylated antibodies are well known to those skilled in the art. For example, host cells that negatively regulate fucose expression can be used, such as CHO Lec13 cells lacking endogenous GDP-mannose 4,6-dehydratase (GMD), host cells with the FUT8 (fucosyltransferase) gene knocked out, CHO cells with silenced GDP-fucose transporter (SLC35C1) gene, etc. to express antibodies (see Pereira N A, Chan K F, Lin P C, et al. The “less-is-more” in therapeutic antibodies: Afucosylated anti-cancer antibodies with enhanced antibody-dependent cellular cytotoxicity, MAbs. Taylor & Francis, 2018, 10(5): 693-711). In addition, defucosylation can also be achieved by adjusting cell culture process parameters, such as adding fucosylation inhibitors to the culture medium, to regulate post-translational fucose modification.

[0105] The term "afucosylation level" or "afucosylation ratio" refers to the ratio of fucose-free N-glycans in the glycosylation modification of an antibody.

[0106] The term "recovery rate" refers to the EC of the predicted antibody 50 value and the EC of the antibody measured by an experimental method 50 The ratio. The closer the recovery rate is to 100%, the higher the accuracy of the prediction result of the method of the present invention. In some embodiments, the recovery rate of the prediction method of the present invention is between 90% and 110%, such as 90%, 95%, 100%, 105% or 110%.

[0107] The term "host cell" refers to a cell that can be or has been an acceptor of a vector or an isolated polynucleotide. A host cell can be a prokaryotic cell or a eukaryotic cell. Exemplary eukaryotic cells include mammalian cells, such as primate or non-primate cells; fungal cells, such as yeast; plant cells; and insect cells. Non-limiting exemplary mammalian cells include human cells or non-human cells (e.g., mouse cells), including but not limited to CHO cells, HEK293 cells, BHK cells, PER cells, SP2 / 0 cells or NS0 cells, and their derivative cells, such as 293-6E, PER-C6 cells, CHO-DG44, CHO-K1, CHO-S and CHO-DS cells, and can also be immune effector cells, such as T cells. Host cells include the progeny of a single host cell, and the progeny may not be exactly the same as the original parental cell due to natural, accidental or intentional mutations, for example, in terms of morphology or genomic DNA. In some embodiments, the host cell is an isolated cell or cell line.

[0108] The term "recombinant expression" refers to the transcription and translation of a foreign gene in a host cell, for example, the patent and translation of a foreign gene encoding an antibody in a host cell. A foreign gene refers to any polynucleotide derived from outside the organism, which can encode a protein, such as an antibody.

[0109] The terms "genetic modification" and "gene modification" are used interchangeably herein and refer to the artificial alteration of the genetic material composition of a cell.

[0110] The term "gene knockout" refers to reducing or completely eliminating the function of a target gene, for example, eliminating or reducing the activity of the protein encoded by the target gene. The term "production process" refers to a combination of production conditions. For the production process of expressing an antibody by culturing a host cell, the production process can refer to the type of host cell, culture conditions or a combination thereof. Culture conditions refer to any one or more combinations of conditions such as pH, dissolved oxygen, osmotic pressure, culture temperature, culture time, medium components, shear force, culture mode, etc.

[0111] The term "conventional production process" refers to a production process that is conventionally adopted without considering the relationship between the ADCC activity and the defucosylation ratio of the antibody to be produced.

[0112] The term "initial production process" as used herein refers to the antibody production process formulated for the antibody to be produced before obtaining the relationship between the ADCC activity and the defucosylation ratio of the antibody.

[0113] The term "host cell and / or culture condition capable of increasing the defucosylation ratio of an antibody" means that the defucosylation ratio of the antibody produced using the host cell and / or culture condition is higher than that of other host cells and / or culture conditions (such as the host cells and / or culture conditions used in the conventional production process or the initial production process).

[0114] In addition, those of ordinary skill in the art should recognize that the methods of the present disclosure can be implemented as a computer program, and the methods of the above embodiments are executed by one or more programs. The instructions in the programs cause a computer or a processor to execute the algorithms described in connection with the accompanying drawings. These programs can be stored and provided to the computer or processor using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (such as floppy disks, magnetic tapes, and hard disk drives), magneto-optical recording media (such as magneto-optical disks), CD-ROM (compact disk read-only memory), CD-R, CD-R / W, and semiconductor memories (such as ROM, PROM (programmable ROM), EPROM (erasable programmable ROM), flash ROM, and RAM (random access memory)). Further, these programs can be provided to the computer by using various types of transitory computer-readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable media can be used to provide programs to the computer through wired communication paths such as wires and optical fibers or wireless communication paths.

[0115] In addition, according to the disclosure of the present disclosure, a computer system can also be provided. The computer system includes: a processor; a memory; and a computer program. The computer program is stored in the memory and is configured to be executed by the processor.

[0116] The present invention is further described by the following embodiments, which should not be construed as limiting the present invention.

[0117] Example 1 Theoretical Model

[0118] The ADCC activity of an antibody is jointly determined by the affinity of its Fab region for the target protein and the affinity of its Fc region for the FcγRIIIa receptor. Since the N-glycosylation modification at the Fc end does not affect the binding of the Fab end to the target protein, when investigating the effect of defucosylation on the ADCC activity of the antibody, the problem can be simplified by only considering the affinity of the Fc end for the FcγRIIIa receptor. For an antibody with fucose modification at the Fc end, it can actually be simply regarded as a mixture of 100% fucose-modified antibody molecules and fully defucosylated antibody molecules. The dissociation constant K Df of the 100% fucose-modified antibody molecule and the FcγRIIIa receptor, and the dissociation constant K Da of the fully defucosylated antibody molecule and the FcγRIIIa receptor are used to calculate the dissociation constant K D of the fucose-modified antibody with any proportion and the FcγRIIIa receptor, which can reflect the ADCC activity of the antibody.

[0119] Under ideal conditions, the binding amount of the antibody-FcγRIIIa receptor has a four-parameter logistic relationship with the antibody concentration, and the EC 50 of its curve is equal to the dissociation constant K D of the antibody-FcγRIIIa receptor interaction. Assume that the defucosylation ratio of the antibody (i.e., Afucosylation%) is α and the antibody concentration is c. Then the concentration of the fully defucosylated antibody molecule is αc, and the concentration of the 100% fucose-modified antibody molecule is (1 - α)c. Let the concentration of the FcγRIIIa receptor be c R , the concentration of the fully defucosylated antibody-FcγRIIIa receptor conjugate at equilibrium is [LR] a , and the concentration of the 100% fucose-modified antibody-FcγRIIIa receptor conjugate at equilibrium is [LR] f . Then the concentration of the unbound FcγRIIIa receptor at equilibrium is c R - [LR] a - [LR] f . Since the concentration of the FcγRIIIa receptor is much smaller than the antibody concentration free in the solution, it can be considered that the concentration of the free fully defucosylated antibody molecule at equilibrium is still αc, and the concentration of the free 100% fucose-modified antibody molecule is still (1 - α)c. Then according to the binding-dissociation equation, the following two equations can be obtained:

[0120]

[0121] Since the concentration of the antibody-FcγRIIIa receptor conjugate at equilibrium [LR] = [LR] a + [LR]f , Rearranging the above two equations, we can obtain:

[0122]

[0123] Obviously, there is a four-parameter logistic relationship between the concentration [LR] of the antibody-FcγRIIIa receptor conjugate and the initial concentration c of the antibody. Therefore, the dissociation constant K of the antibody and the FcγRIIIa receptor D is equal to the EC of this curve 50 , that is:

[0124]

[0125] Taking the reciprocal, we have:

[0126]

[0127] Thus, the dissociation constant K of the fucosylated antibody with any ratio and the FcγRIIIa receptor D is obtained. After rearrangement, the ADCC activity equation of the antibody is obtained:

[0128]

[0129] The above relationship equation can be simplified to:

[0130]

[0131] Therefore, the reciprocal of the ADCC activity EC of the antibody 50 has a linear relationship with the Afucosylation% glycoform ratio α of the antibody. Its slope is equal to the difference between the reciprocal of the dissociation constant of the fully defucosylated antibody molecule and the FcγRIIIa receptor and the reciprocal of the dissociation constant of the 100% fucosylated antibody molecule and the FcγRIIIa receptor. Its y-axis intercept is equal to the reciprocal of the dissociation constant of the 100% fucosylated antibody molecule and the FcγRIIIa receptor. Then, if there are two antibody samples with a large difference in Afucosylation%, and their Afucosylation% (α) and the EC of the ADCC activity are detected 50 respectively, substituting them into the ADCC activity equation of the antibody, the K Da and K Df constants can be obtained. For any Afucosylation% (α), substituting it into the ADCC activity equation can obtain the EC 50 . Next, the accuracy of predicting the ADCC activity EC 50 of this theoretical model will be verified through experiments.

[0132] Example 2 Experimental Verification

[0133] 1. Preparation of Fucosylated and Non-Fucosylated Trastuzumab Antibodies

[0134] The anti-HER2 antibody, Trastuzumab, was expressed using CHOK1-GenS (expressing wild-type non-fucosylated antibody) and CHOK1-ADCC+ host cells (knocking out the FUT8 gene and expressing 100% fucosylated antibody) from the self-developed platform of Pengbo Biotechnology Co., Ltd. CHOK1-GenS is a wild-type cell line obtained by suspension domestication of CHO-K1. First, the heavy and light chains of the Trastuzumab antibody were cloned into the mammalian expression vector pGenHT1.0-UP (Pengbo Biotechnology Co., Ltd.), and then the constructed plasmids were delivered into CHOK1-GenS and CHOK1-ADCC+ cells by electroporation. The supernatants of fed-batch cultures were collected respectively, and the antibody proteins were obtained by one-step affinity purification. The fucosylated Trastuzumab antibody expressed by CHOK1-GenS cells was named GenSP, and the defucosylated Trastuzumab antibody expressed by CHOK1-ADCC+ host cells was named ADCC+P.

[0135] 2. Preparation of Samples with Different Glycoform Proportions

[0136] Since the N-glycosylation modification at the Fc terminus does not affect the binding of the Fab terminus to the target protein, when investigating the effect of defucosylation on the ADCC activity of antibodies, we can simplify the problem by only considering the affinity between the Fc terminus and the FcγRIIIa receptor. For an antibody with fucose modification at the Fc terminus, it can actually be simply regarded as a mixture of antibody molecules with 0% defucosylation and 100% defucosylation. Therefore, we can obtain antibody samples with different degrees of defucosylation by mixing two antibodies with different degrees of defucosylation in different proportions. These samples between 0% defucosylation and 100% defucosylation were named MIX1-MIX10 respectively.

[0137] Appropriate amounts of defucosylated ADCC+P samples and fucosylated samples GenSP were taken and mixed in different proportions as shown in Table 1 below. A total of 12 samples with different fucose proportions were prepared.

[0138] Table 1 Fucosylated Antibody Samples with Different Proportions

[0139] Sample name ADCC + P ratio GenSP ratio ADCC + P 100％ 0％ MiX 1 95％ 5％ MiX 2 90％ 10％ MiX 3 85％ 15％ MiX 4 80％ 20％ MiX 5 70％ 30％ MiX 6 60％ 40％ MiX 7 50％ 50％ MiX 8 30％ 70％ MiX 9 20％ 80％ MiX10 10％ 90％ GenSP 0％ 100％

[0140] 3. Glycoform Detection

[0141] The fucose removal ratio of 12 different defucosylated samples was detected using the HILIC-UHPLC method.

[0142] First, the 12 samples were diluted to 2 mg / ml with 50 mM NH4HCO3 respectively. 15 μg of protein sample was taken and 5% Rapigest-SF (manufacturer: Waters, product number 186008740) was added, and incubated at 95 °C for 5 min for protein denaturation. Subsequently, PNGase F (manufacturer: Waters, product number 186008089) was added and mixed evenly, and incubated at 50 °C for 10 min for deglycosylation treatment. Then, the released N-glycans were derivatized and labeled using RapiFluor-MS (manufacturer: Waters, product number 186007989-1). Finally, the labeled N-glycans were purified using an SPE column and prepared for on-machine detection. The glycan profiles were detected using a high-performance liquid chromatograph UHPLC (manufacturer: Agilent; model 1290) and a BEH Amide Column (manufacturer: Waters; specification: 2.1 mm × 150 mm, 1.7 μm; product number 186004742).

[0143] 4. Detection of ADCC activity by reporter gene method

[0144] HER2+-positive breast cancer cells SK-BR-3 (manufacturer: ATCC, product number HTB-30) were used as target cells, and Jurkat cells (manufacturer: BPS bioscience, product number: 60541) highly expressing human FcγRIIIa (158V variant) and luciferase reporter gene driven by the response element NFAT were used as effector cells to evaluate the ADCC activity of 12 samples with different fucose ratios. First, a SK-BR-3 cell suspension of 2.4E5 cells / ml was prepared and inoculated into a 96-well experimental plate, 100 μL / well. The samples were serially diluted, with the starting concentration of 4 μg / ml and 6-fold dilution, for a total of 8 concentration points. The cell experimental plate was taken out, and the serially diluted samples were added, 50 μL / well. The samples were incubated with the target cells at room temperature for 30 min. An effector cell suspension with a density of 2.88E6 cells / mL was prepared. After the incubation of the samples with the target cells ended, effector cells were added, 50 μL / well, and incubated in an incubator at 37 °C and 5% CO2 for 6 h. After the incubation ended, the cell experimental plate was taken out and placed at room temperature. 80 μL of luciferase detection reagent was added to each well, and incubated in the dark at room temperature for 10 - 30 min. The chemiluminescence signal values were read using a microplate reader (manufacturer: BMG, model PHEARSTAR FSX).

[0145] 5. Detection of ADCC surrogate ELISA activity

[0146] This method is a cell-free alternative to ADCC. Miller et al. (Development of an ELISA-based bridging assay as a surrogate measure of ADCC[J]. Journal of immunological methods, 2012, 385(1-2): 45-50) early confirmed that through the ELISA bridging method, that is, the Fab end of the antibody binds to the antigen protein coated on the solid phase, and the Fc end binds to the CD16a protein. With the help of the HRP-TMB color development system, the ADCC effect of the antibody can be evaluated. This method has a linear relationship with the traditional ADCC detection using cell killing as an index. Compared with the traditional method, this method has high throughput, low cost, better accuracy and reproducibility. In this article, we used a high-binding microplate (Corning, Cat. No: 9018), coated with HER-2 protein (Acrobiosystems, Cat. No: HE2-H52H2), and the coated plate was incubated overnight at 2-8°C. On the second day of the experiment, after washing the plate, it was blocked with 1% BSA for 1 h, and then the plate was washed and different samples with different fucose ratios were added at gradient dilutions to bind to the HER-2 protein. After washing the plate, biotinylated CD16a 158V protein (Sinobiological, Cat. No: 10389-H27H1-B) was added and incubated for 1 h. After washing the plate, it was then incubated with the detection reagent SA-HRP (BD, Cat. No: 554066) for 1 h. After the incubation was completed, the plate was washed, and then 100 μl of TMB (Seracare, Cat. No. 5120-0047) was added to each well for color development, and the reaction was terminated with 2 M H3PO4. The absorbance at wavelengths of 450 nm and 630 nm was read using an enzyme-linked immunosorbent assay (ELISA) reader (manufacturer Molecular Device; model M5e).

[0147] 6. Result analysis

[0148] 6.1 Use the Graphpad Prism6 data processing software, and adopt a four-parameter logistic curve fitting program to generate a curve to describe the dose-response relationship between the signal value and the sample concentration:

[0149]

[0150] x = independent variable

[0151] A = minimum dose response

[0152] B = slope

[0153] C = half-dose concentration EC 50

[0154] D = maximum dose response

[0155] Record R, EC 2 , EC 50 , slope, parameter A and parameter D according to the fitting curves of the reference product, control product and sample.

[0156] 6.2 Obtain the afucosylation percentage Afucosylation% and EC of ADCC+P and GenSP 50 , substitute into the following EC 50 and the formula of Afucosylation% (α) to obtain the linear equation for predicting ADCC activity. Substitute the Afucosylation% of other samples with different glycoforms into the equation to obtain the predicted EC of each sample 50 . According to the predicted EC 50 and the measured EC 50 calculate the recovery rate.

[0157]

[0158] Recovery rate = predicted EC 50 / measured EC 50 * 100%.

[0159] 7. Experimental results

[0160] 1. Glycoform results of samples with different glycoform ratios detected by HILIC-UHPLC

[0161] As shown in the following table, Afucosylation% gradually decreases with the decrease of the ADCC+P ratio, and 12 samples with different afucosylation ratios are obtained for subsequent research.

[0162] Table 2 Glycoform results of samples with different afucosylation ratios

[0163]

[0164] * Note: Afucosylation percentage Afucosylation% = (G0 - GN) + G0 + (Man5 / Man4) + G1, and the ratios of other afucosylated glycoforms are relatively low and not statistically analyzed. Here, Man5 / Man4 refers to the sum of Man5 and Man4. Since there are more than a dozen glycoform types at the N-terminus of the monoclonal antibody, some glycoform types with too low ratios are not included in the statistics as shown Figure 1 . Only glycoforms with a ratio higher than 1% are included in Table 2, and antibodies without fucose modification are considered afucosylated. Therefore, there is an error within 10% between the calculated afucosylation ratio in the mixed ratio and the actually measured Afucosylation%.

[0165] 2. ADCC test results by reporter gene method

[0166] The EC50 of samples with different degrees of afucosylation modification was obtained by four-parameter fitting. By fitting the relationship between the afucosylation ratios of ADCC+P, MIX1-10, and GenSP and their EC 50 , a linear equation was obtained as Figure 2 shown. It can be seen that there is a linear relationship between the afucosylation ratio of the samples used in the present invention and the ADCC activity, which is consistent with other literature reports in the field. However, this equation cannot predict the ADCC activity of antibodies with unknown afucosylation ratios, or even if it can predict, multiple sets of samples need to be used for experimental fitting of the equation, which is rather cumbersome, and a large amount of data needs to be accumulated in the actual process development before fitting can be carried out, and the practical operation convenience is insufficient.

[0167] Use the ADCC activity prediction equation formula I: to predict the ADCC activity. The EC 50 of two samples, ADCC+P and GenSP, were detected by the reporter gene method ADCC experiment, which were 2.018 ng / mL and 11.12 ng / ml respectively. The Afucosylation%(α) of the two samples, ADCC+P and GenSP, were 94.62% and 6.74% respectively. Substitute the Afucosylation% and EC 50 of the two samples into formula I respectively, and the values of M and N can be calculated to be 0.004616 and 0.05882 respectively. Therefore, the ADCC activity prediction equation for this antibody is 1 / EC 50 = 0.004616*α + 0.05882.

[0168] To verify the accuracy of the above prediction equation, substitute the measured Afucosylation% of MIX1-MIX10 into this equation to obtain the predicted ADCC activity of MIX1-MIX10 samples, that is, the predicted EC 50 . Calculate the recovery rate of MIX1-MIX10, that is, the predicted EC 50 / measured EC 50* ×100%, and evaluate the prediction accuracy of this equation. See Table 3. The predicted recovery rates of the EC 50 of each sample fluctuate within the range of 92% - 114%, indicating that the ADCC activity predicted by this method is basically consistent with the results obtained by detecting the ADCC activity of antibodies by the reporter gene method. The accuracy of this prediction method is extremely high, and the error is controlled within about 10%.

[0169] Table 3. Calculation of EC 50 recovery rate by the reporter gene method ADCC equation

[0170]

[0171] 3. EC50 results of ADCC alternative ELISA bridging assay

[0172] The EC50 values of samples with different degrees of afucosylation modification were obtained by four-parameter fitting. By fitting the relationship between the afucosylation ratios of ADCC+P, MIX1-10, and GenSP and their EC50 values, a linear equation was obtained as Figure 3 shown. It can be seen that there is a linear relationship between the afucosylation ratio of the samples used in the present invention and the ADCC activity, which is consistent with other literature reports in the art. However, this equation cannot predict the ADCC activity of antibodies with unknown afucosylation ratios. Or even if it can be predicted, multiple sets of samples need to be used for experimental fitting of the equation, which is rather cumbersome. Moreover, in the actual process development, a large amount of data needs to be accumulated before fitting can be carried out, and the practical operation convenience is insufficient.

[0173] Use the ADCC activity prediction equation formula I: to predict the ADCC activity. The EC 50 values of two samples, ADCC+P and GenSP, were detected by the ADCC alternative ELISA assay, which were 150.6 ng / mL and 614.7 ng / mL respectively. The Afucosylation%(α) of the two samples, ADCC+P and GenSP, were 94.62% and 6.74% respectively. Substitute the Afucosylation% and EC 50 values of the two samples, ADCC+P and GenSP, into formula I respectively, and the values of M and N can be calculated as 5.705E-5 and 0.001242 respectively. Therefore, the prediction equation 1 / EC 50 = 5.705E-5 * Afucosylation% + 0.001242 is obtained.

[0174] To verify the accuracy of the above prediction equation, the measured Afucosylation% of MIX1-MIX10 was substituted into this equation to obtain the predicted ADCC activity of the MIX1-MIX10 samples, that is, the predicted EC 50 . Calculate the recovery rate of MIX1-MIX10, that is, the predicted EC 50 / measured EC 50* ×100%, and evaluate the prediction accuracy of this equation. See Table 4. The EC 50 recovery rates of each sample fluctuate within the range of 96% to 108%, indicating that the ADCC activity predicted by this method is basically consistent with the results obtained by detecting the ADCC activity of antibodies using the ELISA bridging method. The accuracy of this prediction method is extremely high, and the error is controlled within 10%.

[0175] Table 4. Calculation of EC by the inference equation of ADCC alternative method50 Recovery rate

[0176]

[0177] 4. Evaluation of the prediction accuracy of two ADCC detection methods

[0178] The EC of 10 samples MIX1 - MIX10 obtained by two ADCC detection methods 50 Recovery rates were compared and analyzed as follows Figure 4 As shown in Table 5, based on the reporter gene method and the ADCC surrogate method, the EC 50 was substituted into the corresponding formula to calculate that the predicted ADCC activity of the antibody was close to the experimentally measured ADCC activity value of the antibody. The SD value was less than 0.1 and the RSD was less than 10%, indicating that the above two methods were very accurate in predicting the ADCC activity of the antibody. The ADCC surrogate method and the reporter gene method predicted the EC 50 with average recovery rates of 101% and 106% respectively, and RSDs of 4% and 7% respectively. The accuracy of both methods was good, especially the EC 50 obtained by the ADCC surrogate method had high accuracy in predicting ADCC activity, and the RSD value was only 4%. In projects lacking a suitable source of target cells, the ADCC surrogate method can be preferably used to predict ADCC activity based on different Afucosylation% ratios.

[0179] Table 5. Comparison results of the speculation accuracy of two ADCC methods

[0180]

[0181] The ADCC activity was positively correlated with the afucosylation ratio Afucosylation%, and the linearity was good. From the Afucosylation% ratios and the EC of the ADCC activities of two different samples 50 the ADCC activity equation could be obtained, and through this equation, the EC 50 with known Afucosylation% could be obtained. For the ADCC method, the reporter gene method or the ADCC surrogate method ELISAbridging could be selected. The predicted recovery rates of the two methods were 106 ± 7.5% and 101 ± 4.5% respectively.

[0182] The embodiments of the present invention are not limited to those described in the above embodiments. Without departing from the spirit and scope of the present invention, those of ordinary skill in the art can make various changes and improvements in form and details, and all of these are considered to fall within the protection scope of the present invention.

Claims

1. A method for predicting antibody ADCC activity, comprising the following steps: (1) obtaining two or more samples of the antibody, wherein the two or more samples have different defucosylation ratios; (2) Detecting the defucosylation ratio α and ADCC activity EC of the samples respectively 50 Substitute the value into the following formula: Obtain the values ​​of constants M and N, and obtain the defucosylation ratio α and ADCC activity EC of the antibody. 50 The relationship equation of the value; and (3) Substituting the given defucosylation ratio of the antibody into the relationship equation to obtain the ADCC activity of the antibody at the defucosylation ratio.

2. The method according to claim 1, wherein the EC 50 Values ​​are determined by cell killing-based assays, reporter gene-based assays, or ELISA-based bridging assays.

3. The method according to claim 1 or 2, wherein the number of samples is two.

4. The method according to claim 3, wherein the defucosylation ratios of the two samples are 0%-50% and 50%-100%, respectively.

5. The method according to claim 3 or 4, wherein the two samples are respectively an antibody sample expressed by a wild-type host cell and an antibody sample expressed by a host cell genetically modified to reduce the fucosylation ratio of the expressed antibody.

6. The method according to claim 5, wherein the defucosylation ratios of the two samples are 0%-15% and 85%-100%, respectively. 7 . The method according to claim 5 , wherein the host cell genetically modified to reduce the fucosylation ratio of the expressed antibody is a host cell in which the FUT8 gene is knocked out.

8. The method according to any one of claims 5 to 7, wherein the host cell is a CHO cell.

9. The method according to claim 8, wherein the host cell is a CHO-K1 cell.

10. The method according to any one of claims 1 to 9, wherein the defucosylation ratio is determined by the sum of the ratios of glycoforms having a ratio higher than 1% in the antibody.

11. The method according to any one of claims 1 to 10, wherein the defucosylation ratio is determined by the sum of the ratios of G0-GN, G0, Man5, Man4 and G1.

12. A kit for predicting antibody ADCC activity, comprising two or more samples of an antibody to be tested, and instructions for illustrating a method for predicting the antibody ADCC; wherein the two or more samples have different defucosylation ratios, and the instructions describe the method according to any one of claims 1 to 10.

13. A method for producing an antibody, comprising the steps of: (1) obtaining two or more samples of the antibody, wherein the two or more samples have different defucosylation ratios; and detecting the defucosylation ratio α and ADCC activity EC of the samples respectively. 50 Substitute the value into the following formula: Obtain the values ​​of constants M and N, and obtain the defucosylation ratio α and ADCC activity EC of the antibody. 50 The desired ADCC activity of the antibody is substituted into the equation to obtain the defucosylation ratio corresponding to the ADCC activity; and (2) producing the antibody, wherein the defucosylation ratio of the antibody is the defucosylation ratio obtained in step (1).

14. The method for producing an antibody according to claim 13, wherein the process of producing the antibody in step (2) comprises culturing host cells and expressing the antibody in the host cells.

15. The method for producing an antibody according to claim 14, wherein the process of culturing the host cell comprises adding a fucosylation inhibitor and / or Mn to the culture medium. 2+ .

16. A method for predicting antibody ADCC activity, characterized in that: The method comprises: Based on the defucosylation ratio α and ADCC activity EC of two or more samples of the antibody 50 The defucosylation ratio α and ADCC activity EC of the antibody were obtained by fitting the value information. 50 The relationship equation of the value is: Based on a given defucosylation ratio α of a given test antibody sample, a predicted ADCC activity result of the test antibody is obtained.

17. The method according to claim 16, wherein the defucosylation ratios of the two samples are 0%-15% and 85%-100%, respectively.

18. A computer-implemented system for predicting antibody ADCC activity, wherein the computer-implemented system implements the following operations by executing a computer program: Obtain the defucosylation ratio α and ADCC activity EC of two or more samples of the antibody 50 Value information; Defucosylation ratio α and ADCC activity EC of the antibody sample were analyzed by 50 The defucosylation ratio α and ADCC activity EC of the antibody were obtained by fitting. 50 The relationship equation of the value is: By inputting a given defucosylation ratio α of the antibody sample to be tested, the predicted ADCC activity result of the antibody to be tested is obtained.

19. A non-transitory computer-readable storage medium for storing a computer program, wherein the computer program comprises instructions, and when the instructions are executed by a processor of an electronic device, the electronic device implements the method for predicting antibody ADCC according to claim 16 or 17.

20. A computer system, comprising: processor; Memory; and A computer program, wherein the computer program is stored in the memory and configured to be executed by the processor, the computer program comprising instructions for implementing the method for predicting antibody ADCC activity according to claim 16 or 17.

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