Immune reaction evaluation method

Abstract

The purpose of the present invention is to provide a method for selectively identifying an immune reaction to a specific antigen, at the level of antibody sequences, from repertoire data for immune cell receptors. An immune reaction to a specific antigen can be selectively identified, at the level of antibody sequences, by this immune reaction evaluation method, the method including: a step A for preparing repertoire data of sequences for antigen recognition sites in immune cell receptors, wherein the repertoire data is acquired from a sample collected from a subject; and a step B for collating database of a sequence for an antigen recognition site against a specific antigen with the repertoire data to identify a sequence which is identical to the sequence included in the database or a sequence of which a portion excluding two or less amino acid residues is identical to the sequence included in the database at the level of amino acid sequences.

Description

Methods for assessing immune responses

[0001] The present invention relates to a method for evaluating an immune response.

[0002] Because COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a life-threatening threat to patients with hematological malignancies, hematologists generally recommend mRNA SARS-CoV-2 vaccination (Non-Patent Documents 1 and 2). However, it has been reported that some patients with hematological malignancies, such as those who have undergone hematopoietic stem cell transplantation (HSCT) or B-cell depletion therapy, may not achieve a sufficient humoral response after vaccination (Non-Patent Documents 3-6). Even after the emergence of the omicron variant of SARS-CoV-2, which is considered to have low pathogenicity (Non-Patent Document 7), hospitalization and mortality rates in immunocompromised patients remain high, especially in patients with poor vaccination responses (Non-Patent Documents 8 and 9).

[0003] For such patients, the U.S. Food and Drug Administration (FDA) issued an emergency use authorization for tixagevimab / silgavimab in December 2021. This drug contains a neutralizing monoclonal antibody against a different epitope in the receptor-binding domain of the SARS-CoV-2 spike protein and is used as a pre-exposure prophylaxis. Based on the results of the PROVENT trial, tixagevimab / silgavimab is considered effective in preventing severe disease and shortening hospital stays in immunocompromised patients (Non-Patent Documents 10, 11). However, one research group has reported that patients with hematologic malignancies, particularly those undergoing B-cell depletion therapy or hematopoietic stem cell transplantation, remain at risk of breakthrough infection even with tixagevimab / silgavimab (Non-Patent Document 12). Recent information has shown that tixagevimab / silgavimab has low activity against certain omicron subspecies, such as BQ.1 and XBB (Non-Patent Documents 13, 14). Tixagevimab / silgavimab, which was developed before the emergence of the Omicron subspecies, has reduced activity against the currently dominant strains in certain countries (Non-Patent Documents 13 and 14).

[0004] Therefore, the FDA emphasizes that tixagevimab / silgavimab is not a substitute for vaccination and that routine vaccination should be recommended even for patients receiving tixagevimab / silgavimab. Hematologists suggest that these patients maintain multifaceted prevention measures, including infection prevention behaviors, vaccinations, and antiviral antibody drugs (Non-Patent Document 1). One study reported favorable outcomes for COVID-19 caused by the Omicron variant, as well as previous strains, in a cohort of highly vaccinated hematopoietic stem cell transplant patients (Non-Patent Document 15).

[0005] Immunogenicity, especially humoral immunity, after SARS-CoV-2 vaccination is generally assessed by enzyme-linked immunosorbent assay (ELISA) using anti-SARS-CoV-2 spike IgG antibodies (Non-Patent Document 16). Until now, vaccination responsiveness has been evaluated by measuring antibody titers after vaccination in healthy individuals and patients with various immune conditions, including cancer patients (Non-Patent Documents 17, 18).

[0006] Vijenthira A, Gong IY, Fox TA, et al. Outcomes of patients with hematologic malignancies and COVID-19: a systematic review and meta-analysis of 3377 patients. Blood. 2020;136(25):2881-2892.Xhaard A, Xhaard C, D'Aveni M, et al. Risk factors for a severe form of COVID-19 after allogeneic haematopoietic stem cell transplantation: a Societe Francophone de Greffe de Moelle et de Therapie cellulaire (SFGM-TC) multicentre cohort study. Br J Haematol. 2021;192(5):e121-e124.Dhakal B, Abedin S, Fenske T, et al. Response to SARS-CoV-2 vaccination in patients after hematopoietic cell transplantation and CAR T-cell therapy. Blood. 2021;138(14):1278-1281.Watanabe M, Yakushijin K, Funakoshi Y, et al. The Safety and Immunogenicity of the BNT162b2 mRNA COVID-19 Vaccine in Japanese Patients after Allogeneic Stem Cell Transplantation. Vaccines (Basel). 2022;10(2).Funakoshi Y, Yakushijin K, Ohji G, et al.Limited increase in antibody titers following mRNA SARS-CoV-2 vaccination for more than 3 years after final dose of anti-CD20 antibody. Int J Hematol. 2022;115(1):7-10.Einarsdottir S, Martner A, Nicklasson M, et al. Reduced immunogenicity of a third COVID-19 vaccination among recipients of allogeneic hematopoietic stem cell transplantation. Haematologica. 2022;107(6):1479-1482.Malahe SRK, Hoek RAS, Dalm V, et al. Clinical Characteristics and Outcomes of Immunocompromised Patients With Coronavirus Disease 2019 Caused by the Omicron Variant: A Prospective, Observational Study. Clin Infect Dis. 2023;76(3):e172-e178.Taenaka R, Obara T, Kohno K, Aoki K, Ogawa R. Infections with the SARS-CoV-2 Omicron variant show a similar outcome as infections with the previous variants in patients with hematologic malignancies. Ann Hematol. 2022;101(8):1877-1878.Bahremand T, Yao JA, Mill C, Piszczek J, Grant JM, Smolina K.COVID-19 hospitalisations in immunocompromised individuals in the Omicron era: a population-based observational study using surveillance data in British Columbia, Canada. Lancet Reg Health Am. 2023;20:100461.Levin MJ, Ustianowski A, De Wit S, et al. Intramuscular AZD7442 (Tixagevimab-Cilgavimab) for Prevention of Covid-19. N Engl J Med. 2022;386(23):2188-2200.Jondreville L, D'Aveni M, Labussiere-Wallet H, et al. Pre-exposure prophylaxis with tixagevimab / cilgavimab (AZD7442) prevents severe SARS-CoV-2 infection in recipients of allogeneic hematopoietic stem cell transplantation during the Omicron wave: a multicentric retrospective study of SFGM-TC. J Hematol Oncol. 2022;15(1):169.Davis JA, Granger K, Roubal K, et al. Efficacy of tixagevimab-cilgavimab in preventing SARS-CoV-2 for patients with B-cell malignancies. Blood. 2023;141(2):200-203.Imai M, Ito M, Kiso M, et al. Efficacy of Antiviral Agents against Omicron Subvariants BQ.1.1 and XBB. N Engl J Med. 2023;388(1):89-91.Stuver R, Shah GL, Korde NS, et al. Activity of AZD7442 (tixagevimab-cilgavimab) against Omicron SARS-CoV-2 in patients with hematologic malignancies. Cancer Cell. 2022;40(6):590-591.Tan JY, Wee LE, Tan YH, et al. Favorable outcomes of COVID-19 in vaccinated hematopoietic stem cell transplant recipients: A single-center experience. Transpl Infect Dis. 2023:e14024.Jung K, Shin S, Nam M, et al. Performance evaluation of three automated quantitative immunoassays and their correlation with a surrogate virus neutralization test in coronavirus disease 19 patients and pre-pandemic controls. J Clin Lab Anal. 2021;35(9):e23921.Massarweh A, Eliakim-Raz N, Stemmer A, et al. Evaluation of Seropositivity Following BNT162b2 Messenger RNA Vaccination for SARS-CoV-2 in Patients Undergoing Treatment for Cancer. JAMA Oncol. 2021;7(8):1133-1140.Funakoshi Y, Yakushijin K, Ohji G, et al. Safety and immunogenicity of the COVID-19 vaccine BNT162b2 in patients undergoing chemotherapy for solid cancer.J Infect Chemother. 2022;28(4):516-520.

[0007] Importantly, because tixagevimab / silgavimab is an anti-spike IgG antibody, ELISA titers remain at fairly high levels for a long period of time in all patients who receive tixagevimab / silgavimab. Therefore, administration of tixagevimab / silgavimab masks the development of anti-spike antibodies after vaccination. This means that despite vaccination being recommended, it is not possible to evaluate the response to vaccination in these patients. This inability to selectively evaluate the targeted immune response is not unique to the situation after tixagevimab / silgavimab administration but is common to all antibody therapeutics against SARS-CoV-2, including casirivimab / imdevimab and sotrovimab, as well as other antibody therapeutics that may be clinically approved in the future. Furthermore, this issue arises not only after antibody administration, but also in situations where high antibody titers remain due to recent vaccination or infection. Furthermore, this problem is not limited to vaccines against SARS-CoV-2, but is a universal issue that applies to the evaluation of any vaccine and, ultimately, any antigen response (e.g., infection, cancer immune response, autoimmune response, etc.). However, no currently available technology can selectively evaluate only the targeted immune response. Given this situation, a new analytical method is needed that can evaluate immune responses at the level of mRNA expression, rather than at the level of protein expression, as measured by conventional ELISA antibody titers.

[0008] As described above, a method capable of evaluating post-vaccination responses at the mRNA level is needed. Recently, the use of next-generation sequencers has made it possible to perform repertoire analysis, which simultaneously determines the gene sequences of antigen recognition sites on immune cell receptors (antigen receptors), in large quantities. The inventors therefore considered the use of repertoire analysis in the above-described method. However, due to the enormous diversity of immune cell receptors, it has been extremely difficult to evaluate immune responses to specific antigens individually. This difficulty is so pronounced that it is impossible to even confirm which immune cell receptors have expanded after immune intervention. This confirmation is particularly impossible when immune intervention induces a relatively mild immune response, such as with a vaccine. Thus, repertoire analysis cannot be simply applied to evaluate post-vaccination responses at the mRNA level because repertoire analysis is essentially a means of evaluating the degree and changes in immune diversity and is not intended to selectively identify immune responses to specific antigens at the antibody sequence level.

[0009] An object of the present invention is to provide a method for selectively identifying an immune response to a specific antigen at the mRNA level from repertoire data of immune cell receptors.

[0010] Against the backdrop of the recent COVID-19 pandemic, the inventors noticed that a vast amount of information, such as SARS-CoV-2 antibody sequences, has been accumulated and organized into a database. They came up with the novel idea of ​​using this database as query information to query immune cell receptor repertoire data, thereby selectively identifying immune responses to specific antigens at the antibody sequence level from the immune cell receptor repertoire data. In other words, the inventors discovered that by comparing immune cell receptor repertoire data with a database of sequences of antigen recognition sites for specific antigens, it is possible to selectively identify immune responses to specific antigens at the antibody sequence level. The present invention was completed through further investigation based on this finding.

[0011] That is, the present invention provides the following aspects of the invention. Item 1. A method for evaluating an immune response, comprising: Step A of preparing repertoire data containing a group of sequences of antigen recognition sites of immune cell receptors obtained from a specimen of a subject; and Step B of comparing the repertoire data with a database containing a group of sequences of antigen recognition sites of immune cell receptors for specific antigens, and detecting from the repertoire data sequences that are identical to the sequences contained in the database at the amino acid sequence level or identical in a portion other than two or less amino acid residues. This makes it possible to identify sequences that immunologically reacted in the subject's body at the time the specimen was collected. Item 2. The method of Item 1, further comprising Step C of deriving the number and / or frequency in the repertoire data of sequences detected in Step B. Item 3. The method of Item 2, further comprising Step D of confirming changes over time in the number and / or frequency. Item 4. Item 3. The method of Item 3, wherein in step D, it is confirmed whether the time when an increase is observed as a change over time corresponds to 11 to 20 days or 3 to 10 days after stimulation with the specific antigen. Item 5. The method of any of Items 1 to 4, wherein the subject is a subject who has been exposed to the specific antigen. Item 6. The method of Item 5, wherein the exposure to the specific antigen is vaccination. Item 7. The method of Item 6, wherein the vaccine is a nucleic acid vaccine. Item 8. The method of Item 6, wherein the vaccine is a coronavirus vaccine or an influenza vaccine.Item 9. The method of Item 7 or 8, further comprising a step E of evaluating the scientific validity of the nucleic acid vaccine by checking additional information included in the database for the sequences for which an increase in the number and / or frequency over time has been confirmed, wherein the additional information is selected from the group consisting of: [1] information on the presence or absence of neutralizing activity against an antigen, [2] information on the species or strain of the antigen, and [3] information on the epitope, and the evaluation of scientific validity is selected from the group consisting of: [1] evaluating the nucleic acid vaccine as having clinical efficacy in producing antibodies with neutralizing activity if the neutralizing activity is confirmed; [2] evaluating the nucleic acid vaccine as being compatible with the target antigen if the species or strain is confirmed to be the same as the species or strain of the target antigen for which the nucleic acid vaccine was designed; and [3] evaluating the nucleic acid vaccine as being compatible with the target epitope if the epitope is confirmed to be the same as the target epitope for which the nucleic acid vaccine was designed. The method of any one of Items 7 to 9, further comprising Step E' of evaluating, as the scientific validity of the nucleic acid vaccine, that the nucleic acid vaccine has the ability to produce antibodies whose antigen recognition site completely matches that of antibodies resulting from acquired immunity due to infection, if the sequence whose increase in the number and / or frequency over time has been confirmed is identical to the sequence included in the database at the amino acid sequence level. Item 11. The method of Items 5, wherein the exposure to the specific antigen is infection. Item 12. The method of Items 11, wherein the specific antigen is coronavirus or influenza virus. Item 13. The method of any one of Items 5 to 12, wherein the subject is a subject who has been administered an antibody drug, vaccinated, and / or infected, and the antibody drug, the vaccine, and the pathogen of the infection cause the subject's body to possess antibodies different from those produced by exposure to the specific antigen. Item 14. The method of Items 13, wherein the specific antigen is a vaccine, further comprising Step F of determining that the vaccine is functional if the number and / or frequency increases over time. Item 15. Item 15. The method according to any one of Items 5 to 14, wherein the sample is collected at the time of activation of mRNA of an immune cell receptor for the specific antigen.Item 16. The method of Item 15, wherein the activation period is 11 to 20 days or 3 to 10 days after the exposure. Item 17. The method of any of Items 1 to 3, wherein the subject has undergone cancer immunotherapy. Item 18. The method of Item 16, wherein the sample is collected at the time of activation of the mRNA of the immune cell receptor for the specific antigen. Item 19. The method of Item 17, wherein the activation period is 11 to 20 days or 3 to 10 days after the cancer immunotherapy. Item 20. The method of any of Items 1 to 16, wherein the subject has undergone immunosuppressive treatment. Item 21. The method of Item 20, wherein the immunosuppressive treatment is hematopoietic stem cell transplantation or B cell depletion therapy. Item 22. The method of Item 21, wherein the immunosuppressive treatment is hematopoietic stem cell transplantation or B cell depletion therapy, further comprising step G of determining whether or not the immune function has recovered based on whether or not the change in the number and / or frequency over time has increased. Item 23. Item 24. The method of any one of Items 1 to 16, wherein the subject is a patient with an autoimmune disease. Item 24. The method of Items 1 or 2, wherein the repertoire data is obtained from specimens of subjects who have been vaccinated against a virus strain ST1 that has emerged in the past, the specific antigen is a virus strain ST2 for which the effectiveness of the vaccine is unknown, and the method further comprises step H of evaluating that the vaccine is also effective against the virus strain ST2 if the detected sequence is present. Item 25. The method of any one of Items 1 to 24, wherein the database comprises sequences of antigen recognition sites of the immune cell receptors for the specific antigens collected from a group of research subjects in which an immune response has occurred to the specific antigen, and is obtained by the following steps: repertoire data comprising a group of sequences of antigen recognition sites of the immune cell receptors from specimens of each of the research subjects, and an activation time T of mRNA of the immune cell receptor for the specific antigen. ex , before the activation time T bf , and T after the activation period af a step of acquiring repertoire data in time series at the activation time T exItem 26. A step of selecting, as information to be collected in the database, sequences of antigen recognition sites of immune cell receptors in which proliferation is observed at activation time T ex Item 26. The method of any one of Items 1 to 25, wherein the immune cells are T cells or B cells.

[0012] According to the present invention, a method is provided for selectively identifying immune responses to specific antigens at the mRNA level from immune cell receptor repertoire data.

[0013] This figure shows an overview of an example of the immune response evaluation method of the present invention. This figure shows a conceptual diagram of an example of creating a database applicable to the immune response evaluation method of the present invention. This figure shows a conceptual diagram of an example of applying a large-scale dataset group as a comprehensive biosensor to the immune response evaluation method of the present invention. This figure shows a conceptual diagram of an example of the scientific validity of a vaccine that can be evaluated using the immune response evaluation method of the present invention (the ability of healthy subjects to produce antibodies that completely match the antibodies acquired by a patient through infection with an antigen). Changes in anti-spike antibody titers. Anti-spike antibody titers before and after administration of tixagevimab / silgavimab were measured in 17 patients using three types of fully automated commercially available immunoassays: A) Abbott SARS-CoV-2 IgG II Quant, B) Roche Elecsys anti-SARS-CoV-2 S, C) Atellica IM SARS CoV-2 IgG. Details of study design and samples. Sequences from the CoV-AbDab database were searched for SARS-CoV-2-specific sequences in the OAS public database, healthy individuals (n = 12), COVID-19 patients (n = 3), vaccinated healthy volunteers (n = 2), and vaccinated hematopoietic stem cell transplant patients treated with tixagevimab / silgavimab (n = 2). Numbers indicate the number of sequences used. Time-dependent changes in the number and frequency of SARS-CoV-2-specific sequences in three patients infected with COVID-19. NGS analysis was performed on PBMCs collected over time after SARS-CoV-2 infection. Clone numbers (top) and frequencies (bottom) of SARS-CoV-2-specific sequences with identical V and J genes to the CoV-AbDab sequences and a Levenshtein distance of 0 (left), 1 (center), or 2 (right) for the CDR3 amino acid sequences are shown. The lower circle plot shows a cluster plot of SARS-CoV-2-specific sequences. This shows an igraph network of up to 1,000 SARS-CoV-2-specific sequences. Each node represents a single unique read with identical IGHV, IGHJ, and complementarity-determining region 3 (CDR3) amino acid sequences. Nodes were connected by edges defined by a Levenshtein distance of less than 1 for the CDR3 amino acid sequence. The node size was the percent frequency of each unique read.Changes in the number, frequency, and clusters of SARS-CoV-2-specific sequences over time after primary and booster vaccinations. Healthy volunteer 1 received a primary dose of the mRNA SARS-CoV-2 vaccine (monovalent BNT162b2) followed by a second dose 21 days later (Figure 7A). After these vaccinations, a fifth dose of the bivalent BNT162b2 vaccine was administered. After these vaccinations, SARS-CoV-2-specific sequences were searched for in the BCR repertoire data. Changes in the number, frequency, and clusters of SARS-CoV-2-specific sequences over time after primary and booster vaccinations. Healthy volunteer 2 received a fourth dose of monovalent mRNA-1273, followed by SARS-CoV-2-specific sequences 2, 6, and 9 days after the booster vaccination. Changes in the number, frequency, and clusters of SARS-CoV-2-specific sequences over time after mRNA vaccination in hematopoietic stem cell transplant recipients receiving tixagevimab / silgavimab. A recipient (T / C patient 1) received tixagevimab / silgavimab (T / C) 338 days after umbilical cord blood transplantation, followed by the mRNA vaccine (time indicated by the arrow in the "Vaccination" section). Immune cell reconstitution of helper T cells (CD3+CD4+), class-switched B cells (CD19+CD27+IgD-), and plasmablasts (CD19+CD27+CD38+) was confirmed by FACS analysis at the time of vaccination. Anti-SARS-CoV-2 antibody titers were measured using the Abbott SARS-CoV-2 IgG II Quant kit (Abbott) and the Roche Elecsys anti-SARS-CoV-2 S kit (Roche). SARS-CoV-2-specific sequences were measured before vaccination and on days 4, 9, and 11 after vaccination. Triangle dots indicate the number of clones (CDR3 AA Distance ≤ 1). T / C: Tixagevimab / silgavimab. Changes in the number, frequency, and clusters of SARS-CoV-2-specific sequences over time after mRNA vaccination in hematopoietic stem cell transplant recipients receiving tixagevimab / silgavimab. In T / C patient 2, the recipient received tixagevimab / silgavimab on day 212 after unrelated bone marrow transplantation, followed by the mRNA vaccine (time indicated by the Vaccination arrow).SARS-CoV-2-specific sequences were measured before vaccination and on days 3, 6, and 15 after vaccination. Triangle dots indicate the number of clones (CDR3 AA Distance <= 1). T / C: tixagevimab / silgavimab. Characteristics of SARS-CoV-2-specific sequences induced by COVID-19 infection or vaccination. Neutralizing and non-neutralizing functions of SARS-CoV-2-specific sequences detected in healthy individuals, COVID-19 patients, and vaccinated healthy volunteers. The frequency of SARS-CoV-2-specific sequences with (Neut+) or without (Neut-) neutralizing activity detected in the inoculations of healthy individuals (HI1-HI12), COVID-19 patients (Pt1, Pt2, Pt3), vaccinated healthy volunteers (HV1), booster-vaccinated healthy volunteers (HV1, HV2), and hematopoietic stem cell transplant recipients vaccinated with tixagevimab / silgavimab (TC1, TC2) is shown. The frequency of SARS-CoV-2-specific sequences with different CDR3 amino acid distances (LV = 0, 1, 2, respectively) is shown. The frequency of SARS-CoV-2-specific sequences with different CDR3 amino acid distances in local samples is shown. Each dot represents a SARS-CoV-2-specific sequence detected in samples from vaccinated healthy volunteers (n = 2), COVID-19 patients (n = 3), booster-vaccinated volunteers (n = 2), and vaccinated transplant recipients (n = 2). ***: p < 0.001, NS: not significant, by Kruskal-Wallis test and Dunn-Bonferroni post-hoc test. Distribution of CDR3 amino acid lengths for SARS-CoV-2-specific sequences with different CDR3 amino acid distances. Shows the percentage frequency of SARS-CoV-2-specific sequences with different CDR3 lengths detected in this study. Frequency of VJ usage for SARS-CoV-2-specific sequences with different CDR3 amino acid distances. A bubble chart shows the percentage frequency of VJ usage for SARS-CoV-2-specific sequences detected in this study. The X axis represents IGHV genes, the Y axis represents IGHJ genes, and the size of the bubble indicates frequency of usage. Characteristics of SARS-CoV-2-specific sequences induced by SARS-CoV-2 infection or vaccination.Alignment of SARS-CoV-2-specific sequences from infected and vaccinated individuals. The CDR3 amino acid sequences of IGHV4-59, IGHV3-33, IGHV3-53, IGHV3-66, and IGHV3-9 frequently found in infected and vaccinated individuals (Table 3A and Table 3B, SARS-CoV-2-specific sequences (perfect matches) from infected and vaccinated individuals) were aligned using ClustalOmega, and sequence logos were drawn using the ggseqlogo package. Characteristics of SARS-CoV-2-specific sequences induced by SARS-CoV-2 infection or vaccination were compared. Probability of generation (pGen) values ​​were compared. A histogram of pGen values ​​for 8,977 SARS-CoV-2-specific sequences from the CoV-AbDab database and 86 perfectly matched SARS-CoV-2-specific sequences (FoundCoV) detected from infected and vaccinated individuals is shown. pGen values ​​were calculated from the CDR3 amino acid sequence of each sequence using the OLGA package. Sequences with high pGen values ​​are more likely to occur, while sequences with low pGen values ​​are rarely occurring. Occupancy frequency of dominant individual clones and the top 10 clones in vaccinated healthy volunteers. Individual clones with an occupancy frequency above 0.1% in vaccinated healthy volunteers are indicated by dots. The sum of the occupancy frequencies of the top 10 clones is shown by a line. Changes in the number and frequency of SARS-CoV-2-specific sequences over time after mRNA vaccination in hematopoietic stem cell transplant recipients who received SARS-CoV-2 antibodies. The number of clones (top) and percent frequency (bottom) of SARS-CoV-2-specific sequences are plotted against time (days) since vaccination. Frequency of SARS-CoV-2-specific sequences in the OAS database. The frequency of individual samples with identical V and J genes to SARS-CoV-2-specific sequences in CoV-AbDab, but with a CDR3 amino acid sequence edit distance of 0 (LV0), 1 (LV1), or 2 (LV2), is shown for IGHG sequences in the OAS database reported between 2011 and 2020. Each dot represents a SARS-CoV-2-specific sequence detected in the OAS database.***p < 0.001, NS: not significant, by Kruskal-Wallis test and Dunn-Bonferroni post-hoc test. VJ usage of SARS-CoV-2-specific sequences in the OAS database. The percentage frequency of SARS-CoV-2-specific sequences with different CDR3 amino acid edit distances is displayed in separate bubble charts. The X axis represents IGHV genes, and the Y axis represents IGHJ genes, with bubble size indicating the percentage usage frequency. Characteristics of SARS-CoV-2-specific sequences. Distribution of CDR3 amino acid lengths of SARS-CoV-2-specific sequences with different CDR3 amino acid distances in the OAS database. The percentage frequency (read abundance) of SARS-CoV-2-specific sequences with different CDR3 amino acid lengths reported in the OAS database from 2011 to 2020 is shown. SARS-CoV-2-specific sequences with different CDR3 edit distances (LV0, LV1, LV2) are displayed in separate bar graphs. Alignment of SARS-CoV-2-specific sequences with the 8-amino acid CDR3 sequence of IGHV4-59. Sequence logos were generated using the ggseqlogo package. Comparison of probability of generation (pGen) values ​​for SARS-CoV-2-specific sequences. A histogram shows the pGen values ​​of 8,977 SARS-CoV-2-specific sequences from the CoV-Ab database (CoV-AbDab) and 372 exact matches found in the OAS database (FoundCoV(OAS)). The X-axis represents density, and the Y-axis represents the logarithmic value (log10) of pGen. We confirmed that administration of an mRNA vaccine against SARS-CoV-2 increased antibody sequences binding to various strains (mutant strains, Omicron strain variants) in the same subject. We confirmed that administration of an mRNA vaccine against SARS-CoV-2 increased antibody sequences binding to various strains (mutant strains, Omicron strain variants) in the same subject. It was confirmed that administration of an mRNA vaccine against SARS-CoV-2 increased antibody sequences that bind to various strains (mutant strains, Omicron strain variants) in the body of the same test subject.By administering SARS-CoV-2 mRNA vaccines designed to target different strains to the same subject, we confirmed that antibody sequences that bind to different strains increased depending on the vaccine. By administering SARS-CoV-2 mRNA vaccines designed to target different epitopes, we confirmed that antibody sequences that bind to different epitopes increased depending on the vaccine. After infection or the first vaccination, sequences matching the database in the BCR repertoire (antibody sequences with a Levenshtein distance of 0 amino acid difference in CDR3 and antibody sequences with a Levenshtein distance of 1 or less) increased within approximately two weeks. After booster vaccination, sequences matching the database in the BCR repertoire (antibody sequences with a Levenshtein distance of 0 amino acid difference in CDR3 and antibody sequences with a Levenshtein distance of 1 or less) increased within approximately one week. An explanation of B cell subset classification is provided below. After cancer immunotherapy (booster immunization), activated B cells increased within approximately one week. After cancer immunotherapy (booster immunization), activated B cells increased within approximately one week. After cancer immunotherapy (booster immunization), activated B cells increased within about a week, with even greater increases observed in patients who developed irAEs (patients 1, 2, 6, 10, and 11). The first antigen stimulation (vaccination) after hematopoietic stem cell transplantation increased sequences matching the database in the BCR repertoire (antibody sequences with a Levenshtein distance of 0 and a CDR3 amino acid difference of 1 or less) within two weeks of the first antigen stimulation. After the second or subsequent antigen stimulation (vaccination) after hematopoietic stem cell transplantation, the number of sequences matching the database in the BCR repertoire (antibody sequences with a Levenshtein distance of 0 and a CDR3 amino acid difference of 1 or less) increased within one week of the second or subsequent antigen stimulation. After inactivated influenza vaccination, the number of sequences matching the database in the BCR repertoire (containing approximately 1,300 sequences independently compiled from citations from research papers) increased within about a week. In vitro experiments related to sequence collection for expanding the database used in Figure 23A are shown.

[0014] The method for evaluating an immune response of the present invention is a method for evaluating an immune response to a specific antigen using antigen receptor repertoire analysis. Hereinafter, the method for evaluating an immune response of the present invention may be referred to as the "Quantification of Antigen-specific Antibody Sequence (QASAS) method." An example of the method for evaluating an immune response of the present invention is outlined in FIG. 1.

[0015] The method for evaluating an immune response of the present invention comprises: Step A of preparing repertoire data [corresponding to Figure 1(ii)] containing a group of sequences of antigen recognition sites of immune cell receptors (antigen receptors) obtained from a sample of a subject [corresponding to Figure 1(i)]; and Step B of comparing a database [corresponding to Figure 1(iii)] containing a group of sequences of antigen recognition sites of immune cell receptors for specific antigens with the repertoire data [corresponding to Figure 1(ii)], and detecting, from the repertoire data [corresponding to Figure 1(ii)], sequences that are identical to the sequences contained in the database [corresponding to Figure 1(iii)] at the amino acid sequence level or identical to the sequences contained in the database (corresponding to Figure 1(iii)] except for two or less amino acid residues [corresponding to "sequences matching the database" in Figure 1; hereinafter, sequences that are identical at the amino acid sequence level (i.e., completely identical sequences) or identical to the sequences contained in the database except for two or less amino acid residues (similar sequences containing one or two mismatches) will also be simply referred to as "matching sequences"]. This makes it possible to identify, from the many sequences contained in the repertoire data (ii), sequences that reacted immunologically in vivo in the subject at the time the sample was collected (i.e., reacted to the "antigen stimulation" in Figure 1) [corresponding to the "sequence matching the database" in Figure 1]. In this way, the method of the present invention can identify, from the many sequences contained in repertoire data (ii) and database (iii), sequences that show an immunologically appropriate reaction, i.e., sequences that can truly react with an antigen, and therefore can evaluate immune responses at the level of mRNA expression, rather than at the level of protein expression as in conventional antibody titer measurements by ELISA.

[0016] The method for evaluating an immune response of the present invention may further include a step C of deriving the number (corresponding to "number of matching sequences (clones)" in Figure 1) and / or frequency (corresponding to "proportion of matching sequences" in Figure 1) in the repertoire data of the sequences detected in step B. This allows the degree of immune response to be determined.

[0017] Furthermore, the immune response evaluation method of the present invention can further include a step D of confirming the time-dependent change in the number and / or frequency of sequences matching the database (i.e., the transition of the "number of matching sequences (clones)" or "percentage of matching sequences" on the "Day" axis in Figure 1). This allows the transition of the immune response at each time point of collection of the sample to be investigated. Note that antibody proteins take time to reach detectable levels after an immune response and remain in the body for a long period of time due to their long half-life, whereas mRNA reaches detectable levels quickly after an immune response and does not remain in the body for a long period of time due to its short half-life. Therefore, as shown by the transition of the "number of matching sequences (clones)" or "percentage of matching sequences" in Figure 1, immune responses can be quickly detected based on mRNA levels, and humoral immune activity can be monitored in real time.

[0018] The following are examples of embodiments of the method of the present invention according to the intended application purpose. Form [a] Evaluation of the scientific validity of a vaccine Case a1: Ability to produce antibodies with neutralizing activity Case a2: Type of strain (mutant strain, variant) of the target antigen Case a3: Type of target epitope Case a4: Ability to produce antibodies whose antigen recognition site perfectly matches that of antibodies through acquired immunity Form [b] Evaluation of the immune response to a vaccine Case b1: Evaluation of the immune response to a vaccine while antibodies are present due to administration of an antibody drug Case b2: Evaluation of the immune response to a vaccine while antibodies are present due to administration of another vaccine Case b3: Evaluation of the immune response to a vaccine while antibodies are present due to infection Case b4: Evaluation of the recovery of the immune response due to vaccination after immunosuppressive treatment Form [c] Diagnosis of infectious diseases Case c1: Identification of the pathogen Case c2: Determination of the suitability of existing vaccines for new pathogens Form [d] Evaluation of cancer immunity Case d1: Determination of the effectiveness of cancer immunotherapy Case d2: Identification of true neoantigens Form [e] Evaluation of the response to autoantigens Case e1: Diagnosis of the onset of autoimmune disease Case e2: Diagnosis of the progression of autoimmune disease Case e3: Evaluation of side effects after medication Form [f] Use as a comprehensive biosensor

[0019] The method for evaluating immune responses of the present invention will be described in detail below.

[0020] 1. Step A In step A, repertoire data of sequences of antigen recognition sites of immune cell receptors obtained from a subject's sample (corresponding to Figure 1(i)) is prepared.

[0021] 1-1. Repertoire Data A repertoire is the totality of adaptive immune receptors (immune repertoire) that a subject possesses and that change over time.

[0022] The biological sample that is the source of repertoire data is not particularly limited as long as it contains immune cells, and examples thereof include body fluid samples such as blood and lymph, and tissue homogenates, preferably body fluid samples, more preferably blood (even more preferably peripheral blood mononuclear cells).

[0023] The repertoire data includes sequences of antigen recognition sites of immune cell receptors. B cells or T cells can be selected as immune cells. When B cells are selected as immune cells, preferred examples include forms [a] to [c], [e], and [f]. When T cells are selected as immune cells, preferred examples include forms [d] and [f].

[0024] In the repertoire data used in the present invention, the immune cells from which the sequences of the antigen recognition site are derived include immune cells specific to a specific antigen, but also randomly include immune cells that are not specific to a specific antigen, and no distinction is made between them. In other words, in the repertoire data used in the present invention, the immune cells from which the sequences of the antigen recognition site are derived are not immune cells specific to a specific antigen narrowed down from all immune cells obtained from the above-mentioned biological sample, but typically include all immune cells that can be identified from the above-mentioned biological sample (for example, all B cells or all T cells that can be identified from peripheral blood mononuclear cells).

[0025] The repertoire data may include information acquired from one subject, or may include information acquired from multiple subjects with common subject attributes.

[0026] The sequence of the antigen recognition site of an immune cell receptor includes a gene sequence that determines the clonotype of the immune cell. Such a gene sequence may be any sequence that forms a complementarity determining region upon rearrangement. Specifically, such gene sequences include sequences of the V and J segments of the TCR α chain, TCR γ chain, and immunoglobulin L chain, as well as sequences of the V, D, and J segments of the TCR β chain, TCR δ chain, and immunoglobulin H chain. Furthermore, such a complementarity determining region may be at least one of CDR1, CDR2, and CDR3, but preferably includes at least CDR3.

[0027] The repertoire data may be obtained by a repertoire analysis method. Repertoire analysis methods are known, and involve determining the sequence (gene sequence) of an antigen recognition site of an immune cell receptor from a biological sample of a subject by next-generation sequencing. Typically, the repertoire data can be obtained by extracting total RNA from the biological sample of the subject, synthesizing cDNA, nucleic acid amplifying the immune cell receptor gene sequence, and performing large-scale sequencing by next-generation sequencing to assign the sequence (gene sequence) region of the antigen recognition site. In nucleic acid amplification, it is preferable to uniformly amplify the immune cell receptor gene sequence without bias (unbiased gene amplification), and the design of a multiplex primer panel for such unbiased gene amplification can also be selected based on known techniques.

[0028] The number of sequences included in the repertoire data is not particularly limited, and may be determined depending on the scale of one analysis of the next-generation sequencing used, the number of subjects who provided the repertoire data, etc. Specifically, the number of sequences included in the repertoire data may be, in terms of the number of immune cell receptors, for example, 100,000 to 10 million, 300,000 to 5 million, or 500,000 to 3 million.

[0029] Note that the repertoire analysis method applicable to the present invention includes not only bulk analysis, which analyzes gene expression in immune cells at the cell population level, but also single-cell analysis, which analyzes gene expression in immune cells at the individual cell level.

[0030] 1-2. Subjects The subject is not particularly limited as long as it is a subject for which an immune response needs to be evaluated, and can be selected depending on the purpose of application of the method of the present invention. Specific examples of subjects include subjects exposed to a specific antigen, subjects undergoing cancer immunotherapy, and subjects suffering from an autoimmune disease. Furthermore, biological species of subjects include humans and non-human animals (including, but not limited to, mice, rats, zebrafish, etc.).

[0031] 1-2-1. Subjects exposed to a specific antigen The exposure to a specific antigen is not particularly limited as long as it is an event that leads to activation of an immune response, and examples thereof include vaccination and infection.

[0032] 1-2-1-1. Subjects vaccinated with a specific antigen Subjects vaccinated with a specific antigen can be selected as subjects exposed to a specific antigen. In this case, evaluation of the immune response to the vaccine can be performed by identifying the sequence that caused an immune reaction to the vaccine in the subject's body at the time the sample was collected, thereby not only confirming the immune reactivity to the vaccine, but also evaluating (including predicting) the scientific validity of the vaccine (e.g., whether the vaccine exerts the specified function consistent with its design). Examples of when such subjects can be selected include form [a], form [b], and form [f].

[0033] Because the immune response to a vaccine is slower than that to an infection, conventional repertoire analysis cannot confirm an immune response to a specific antigen. The method of the present invention is highly useful in that it can selectively identify an immune response to a specific antigen from repertoire data, and therefore can effectively identify an immune response to a specific antigen, even if it is an immune response to a vaccine.

[0034] The type of vaccine is not particularly limited, and specific examples include nucleic acid vaccines (mRNA vaccines, DNA vaccines), viral vector vaccines, recombinant protein vaccines, inactivated vaccines, and live vaccines. Furthermore, preferred examples of vaccines include vaccines designed against pathogens described below, and preferably vaccines designed against viruses described below, more preferably coronaviruses or influenza viruses (coronavirus vaccines or influenza virus vaccines).

[0035] The method of the present invention can identify an immune response to a specific antigen at the level of the antibody's complementarity-determining region sequence, and can also identify antigen information such as the type of strain (mutant strain, variant) or epitope (antibody-binding site) from the sequence information of the antibody's complementarity-determining region. Therefore, it is possible to determine the type of strain (mutant strain, variant) and epitope that an antibody produced by a vaccine containing the blueprint (genetic information) of a specific antigen as an active ingredient, particularly a nucleic acid vaccine, can recognize from antigen information such as epitopes linked to the complementarity-determining region sequence in a database. From this perspective, preferred examples of vaccine types include nucleic acid vaccines (mRNA vaccines, DNA vaccines), and more preferably RNA vaccines (mRNA vaccines).

[0036] 1-2-1-2. Subjects infected with a specific antigen As subjects exposed to a specific antigen, subjects infected with a specific antigen can be selected. In this case, the immune response to a specific infectious disease can be evaluated. Examples of cases in which such subjects are selected include form [c] and form [f].

[0037] The infection is not particularly limited as long as it is an infection caused by a specific antigen as a pathogen, and specific examples include infection caused by antigenic organisms such as viruses, bacteria, and fungi as pathogens.

[0038] Examples of viruses include, but are not limited to, coronaviruses, influenza viruses, cytomegaloviruses, rotaviruses, herpes viruses, human immunodeficiency viruses, dengue viruses, etc. Coronaviruses include common cold coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and novel coronavirus (SARS-CoV-2). Influenza viruses include types A (including any combination of 16 hemagglutinin (HA) H1 to H16 and 9 neuraminidase (NA) N1 to N9), B, and C.

[0039] The bacteria are not particularly limited, and examples thereof include Pseudomonas aeruginosa, Legionella, Yersinia, Escherichia coli, Vibrio, Haemophilus influenzae, gram-negative bacilli, and Mycobacterium tuberculosis.

[0040] The fungi are not particularly limited, and examples thereof include Candida and Aspergillus.

[0041] In the present invention, specific antigens that become pathogens (referring to pathogenic microorganisms) include not only antigens for which infection has currently been confirmed and for which the species and strain have been identified, but also pathogens such as mutant strains that will newly emerge in the future. According to the method of the present invention in which the subject is selected, antigen information can be identified from sequence information related to repertoire data via an existing database, so that in diagnosing infectious diseases, not only can it be identified what kind of pathogen is causing the infection, but it can also be determined whether or not existing vaccines can be applied to newly emerging pathogens.

[0042] 1-2-1-3. Subjects with high levels of other antibodies Subjects exposed to a specific antigen (subjects described in the above sections "1-2-1-1" and "1-2-1-2") may also have high levels of other antibodies at the time of specimen collection. These other antibodies refer to antibodies different from those produced by exposure to the specific antigen. Examples of cases in which such subjects are selected include forms [a] to [c] and [f].

[0043] Subjects who have high levels of other antibodies include subjects who have been administered an antibody drug, vaccinated, and / or infected. Hereinafter, subjects who have been administered an antibody drug will also be referred to as "subject (S1)," subjects who have been vaccinated will also be referred to as "subject (S2)," and subjects who have been infected will also be referred to as "subject (S3)."

[0044] The subject (S1) is not particularly limited, but specific examples include subjects undergoing immunosuppressive treatment or patients suffering from autoimmune diseases. Examples of immunosuppressive treatment include the treatments described in Section 1-2-3 below. Examples of autoimmune diseases include the diseases described in Section 1-2-4 below. The antibody drug is not particularly limited, and any antibody pharmaceutical can be used. An example of an antibody drug is an antibody pharmaceutical administered to a subject undergoing immunosuppressive treatment, for example, to counter exposure to a specific antigen. For example, when the specific antigen is the novel coronavirus, examples of antibody pharmaceuticals include tixagevimab / silgavimab, casirivimab / imdevimab, sotrovimab, etc. Other examples of antibody drugs include antibody pharmaceuticals used to treat autoimmune diseases. This antibody pharmaceutical can be selected appropriately by a person skilled in the art depending on the type of autoimmune disease.

[0045] The vaccine to be administered to the subject (S2) is not particularly limited. However, when the subject in the above item "1-2-1-1" further becomes the subject (S2), the vaccine that satisfies the condition for the subject (S2) is a different vaccine from the vaccine that satisfies the condition for the subject in the above item "1-2-1-1." Specific examples of the other vaccine include a vaccine that produces antibodies different from the antibodies produced by the vaccine that satisfies the condition for the subject in the above item "1-2-1-1" (i.e., the specific antigen), a vaccine designed to target another antigen (an antigen other than the specific antigen), and the like.

[0046] The pathogen in the subject (S3) is not particularly limited. However, when the subject in the above item "1-2-1-2" further becomes the subject (S3), the pathogen that satisfies the condition for the subject (S3) is another pathogen that is different (at least at the strain class level) from the pathogen (i.e., the specific antigen) that satisfies the condition for the subject in the above item "1-2-1-2." Specifically, the other pathogen can be appropriately selected from the pathogens listed in the above item "1-2-1-2."

[0047] Due to the administration of an antibody drug, vaccination, or infection, other antibodies (specifically, antibodies related to an antibody drug, antibodies produced in an immune response to a vaccine, or antibodies produced in an immune response to a pathogen) are present at high levels in the bodies of subjects (S1) to (S3). Furthermore, due to the long half-life of antibody proteins, these other antibodies are maintained at high levels in the bodies of subjects (S1) to (S3). Even if antibodies are produced in parallel in an immune response to a specific antigen in this state, such antibodies cannot be detected by conventional immunoassays such as repertoire analysis or ELISA because they are masked by the large amount of other coexisting antibodies. The method of the present invention can selectively identify an immune response to a specific antigen from repertoire data without being affected by the amount of antibody protein in the body. Therefore, even if a subject has high levels of other antibodies, if an immune response to a specific antigen has occurred, the immune response can be identified.

[0048] Furthermore, the relationship between the timing of antibody drug administration and the timing of antigen exposure is not particularly limited, as long as the biological sample related to the repertoire data is obtained while the antibody related to the antibody drug is retained in the body. Therefore, within the above-mentioned limits, the timing of antibody drug administration may be before, simultaneously with, or after antigen exposure, and is preferably before antigen exposure.

[0049] 1-2-2. Subjects who have undergone cancer immunotherapy In subjects who have undergone cancer immunotherapy (a treatment that enhances the body's inherent immune response against cancer), immune cells re-recognize cancer antigens to which they had previously tolerated. This re-recognition of immune cells to cancer antigens (neoantigens) is, in principle, accompanied by a change in the immune environment (activation of the immune response) similar to that observed with antigen exposure. As described above, the method of the present invention can evaluate immune responses activated by antigen exposure, and therefore can also evaluate immune responses activated by cancer immunotherapy using a similar mechanism. Therefore, subjects who have undergone cancer immunotherapy can be selected as subjects. Examples of cases in which such subjects are selected include form [d] and form [f]. A cancer antigen can be selected as the specific antigen.

[0050] Cancer immunotherapy involves treatments that remove the brakes placed on the immune system by cancer, such as the administration of immune checkpoint inhibitors, which activate cancer immunity by inhibiting immunosuppressive signaling. Examples of immune checkpoint inhibitors include anti-PD-1 antibodies, anti-PD-L1 antibodies, and anti-CTLA4 antibodies.

[0051] By evaluating the immune response of a subject who has undergone cancer immunotherapy, it is possible to determine whether the cancer immunotherapy is exerting its intended function (i.e., the effectiveness of the cancer immunotherapy). Furthermore, when the subject is selected, the method of the present invention can identify antigens that match the T cell receptor database as clinically significant T cell receptor sequences from sequence information related to the T cell receptor repertoire data of a sample collected after cancer immunotherapy, and therefore antigens (typically peptides) that bind to the T cell receptor sequences can be identified as true neoantigens.

[0052] 1-2-3. Subjects receiving immunosuppressive treatment Subjects receiving immunosuppressive treatment can be selected as subjects. Examples of cases in which such subjects are selected include case b4 of form [b] and form [f]. A vaccine can be selected as the specific antigen.

[0053] Immunosuppressive treatments include, but are not limited to, hematopoietic stem cell transplantation, administration of B cell depletion therapy (chemotherapy), etc. When used to evaluate the immune response of a subject who has undergone immunosuppressive treatment, for example, it can be determined whether or not the immune response that has been weakened by the immunosuppressive treatment has recovered due to antigen stimulation (vaccination, etc.) after the immunosuppressive treatment.

[0054] When selecting such a subject, it is sufficient that the subject receives antigenic stimulation with a specific antigen after immunosuppressive treatment; the subject may or may not receive stimulation with an antigen (this antigen may be the same as the specific antigen, or may be a different antigen from the specific antigen) before immunosuppressive treatment. Even if the subject receives stimulation with the same antigen as the specific antigen before immunosuppressive treatment, the immune system is reset by the immunosuppressive treatment. For this reason, in the method of the present invention, even if the subject receives stimulation with the same antigen as the specific antigen before immunosuppressive treatment, the reaction due to stimulation with the specific antigen received after immunosuppressive treatment is considered to be the primary immune response (see Figure 22A).

[0055] 1-2-4. Subjects with an Autoimmune Disease Subjects with an autoimmune disease can be selected as subjects. Examples of cases in which such subjects are selected include form [e] and form [f]. An autoantigen can be selected as the specific antigen.

[0056] Autoimmune diseases are not particularly limited, and examples include myasthenia gravis (autoantigen: acetylcholine receptor), immune thrombocytopenia (ITP) (autoantigen: platelets), and type 1 diabetes (autoantigen: β cells).

[0057] According to the method of the present invention, when the subject is selected, the onset or progression of an autoimmune disease can be evaluated by identifying a sequence that matches a database of immune cell receptors for autoantigens that cause the autoimmune disease from sequence information related to immune cell receptor repertoire data obtained from the subject.

[0058] Furthermore, when the subject is selected, the method of the present invention can also be used to evaluate side effects after drug administration. In this case, a database group for autoantigens is constructed, and the off-target effects of the drug can be evaluated by confirming that drug administration increases the number of matching sequences in the database for targets other than the drug's designed target. For example, if a SARS-CoV-2 vaccine is administered, and repertoire analysis reveals an increase in matching sequences in the myocardium database rather than in the SARS-CoV-2 database among the numerous databases that make up the database group, myocarditis can be assessed as a side effect. This enables screening to predict the occurrence of unexpected side effects (antibodies reactive to autoantigens) for new drugs, thereby enabling the development of safer new drugs.

[0059] 1-3. Timing of Repertoire Data Acquisition The timing of acquiring repertoire data from a subject (i.e., the timing of collection of a biological sample that serves as the source of repertoire data) is not particularly limited and can be selected from any time period during which an immune response needs to be evaluated. Preferably, a time period that coincides with the activation time of the mRNA of an immune cell receptor for a specific antigen (i.e., the time of clonal proliferation of immune cells that have responded to a specific antigen in the repertoire) is selected. Specific times of mRNA activation are independent of the type of specific antigen, and include, for example, 4 to 18 days after immune stimulation with a specific antigen. More specifically, when evaluating a primary immune response (for example, when evaluating immunity following infection, initial vaccination, or cancer immunotherapy), the time period can be, for example, 11 to 20 days or 11 to 18 days, preferably 12 to 16 days, and more preferably 13 to 15 days, after antigen stimulation for the primary response; when evaluating a secondary, tertiary, ..., or nth-order response (where n is an integer representing the number of immune responses; these secondary and subsequent responses are also collectively referred to as "secondary and subsequent responses") (for example, when evaluating booster vaccination of a vaccine or cancer immunotherapy), the time period can be, for example, 3 to 10 days or 4 to 10 days, preferably 5 to 9 days, and more preferably 6 to 8 days, after antigen stimulation for the secondary, tertiary, ..., or nth-order response, respectively.

[0060] 2. Step B In step B, a database of sequences of antigen recognition sites for specific antigens [corresponding to Figure 1 (iii)] is compared with the repertoire data [corresponding to Figure 1 (ii)], and sequences that are identical to the sequences included in the database at the amino acid sequence level or that are identical except for two or less amino acid residues [corresponding to "sequences matching the database" in Figure 1] are detected from the repertoire data.

[0061] 2-1. Database The database contains sequences of antigen recognition sites for specific antigens. The specific antigens are the same as the specific antigens described above in "1-2. Subjects." The sequences of the antigen recognition sites are as explained above as the sequences of the antigen recognition sites in "1-1. Repertoire Data."

[0062] In addition to information on the sequence of the antigen recognition site for a specific antigen, the database may also contain additional information (hereinafter simply referred to as "additional information") such as antibody sequences, nanobody sequences, and variable region sequences for the specific antigen, whether or not the antibody has neutralizing activity, epitope regions in the specific antigen, and the species and strain (mutant strain, variant) of the antigenic organism.

[0063] 2-1-1. Public Databases An example of such a database is CoV-AbDab (a database managed by the Oxford Protein Informatics Group at the Department of Statistics, University of Oxford). CoV-AbDab contains information on beta coronaviruses such as SARS-CoV-2, SARS-CoV-1, and MERS-CoV, including the sequences of antibodies capable of binding to each beta coronavirus, nanobody sequences, and variable region sequences, as well as the neutralizing activity of the antibodies, epitope regions, and the species and strains (mutants and variants) of each beta coronavirus.

[0064] 2-1-2. Originally Created Database In the present invention, a database may be a publicly available database containing the above information, or may be a database created by independently collecting data for each specific antigen. The sequences of antigen recognition sites for specific antigens to be included in the database can be appropriately obtained using known methods. Methods for collecting data include the following methods [1] to [3]. To collect the database, any of the methods [1] to [3] may be used, or two or more methods may be used in combination. [1] Collection from existing literature and / or public databases [2] Collection of sequences through in vitro experiments [3] Collection of sequences through in silico

[0065] In the method [1] above, the sequences of known antigen recognition sites for a specific antigen are selected from existing literature and / or public databases, and further known additional information is associated as needed, thereby enabling the information to be included in the database to be compiled.

[0066] The method [2] above includes, for example, a step of preparing a labeled protein by labeling a protein synthesized from an antigen sequence, a step of sorting cells that bind to the labeled protein from a population of immune cells, and a step of acquiring the sequences of the sorted cells as information to be collected in a database.

[0067] In the method [3] above, antigen / antigen receptor binding prediction using machine learning can be used to collect the sequence of the antigen recognition site of the immune cell receptor. Examples of such binding prediction include antigen / epitope binding analysis using a protein language model (e.g., Bioinformatics, Volume 37, Issue Supplement_1, July 2021, Pages i237-i244, and Bioinformatics, Volume 39, Issue 1, January 2023, btac820), and protein structure analysis and binding analysis using a diffusion model (e.g., Nature. 2024 May 8. doi: 10.1038 / s41586-024-07487-w).

[0068] Furthermore, in the method combining the above [2] and [3], immune cells capable of binding to a specific antigen are obtained from a group of subjects in which an immune reaction has occurred due to the specific antigen, and sequences of antigen recognition sites of immune cell receptors can be collected by repertoire analysis. The method combining the above [2] and [3] preferably includes the following steps: - Collecting repertoire data from a sample of each of the subjects in question, the repertoire data including a group of sequences of antigen recognition sites of the immune cell receptors, and the repertoire data including sequences of activation times T of the mRNA of the immune cell receptors against the specific antigen. ex , before the activation time T bf , and T after the activation period af a step of acquiring repertoire data in time series at the activation time T ex a step of selecting sequences of antigen recognition sites of immune cell receptors in which proliferation is observed in the target cells as information to be collected in the database.

[0069] A conceptual diagram of an example of creating a database using this method is shown in Figure 2. As mentioned above in "1-3. Timing of acquiring repertoire data," it has been found that the activation period of immune cell receptor mRNA (i.e., the period of clonal proliferation of immune cells that have responded to a specific antigen in the repertoire) occurs during a predetermined period after stimulation with a specific antigen. Therefore, based on the predetermined period after antigen stimulation (clonal proliferation period) mentioned above in "1-3. Timing of acquiring repertoire data," the period before the activation (T bf : before clonal expansion), the activation period (T ex : clonal expansion phase), and after activation (T af It is possible to obtain time-series immune cell receptor repertoire data, including the following: (after clonal expansion: shrinkage of the expanded clones). Bulk repertoire analysis generates a huge amount of data (e.g., approximately 200,000 reads) from each specimen. By analyzing the increase or decrease in the number of reads in this time-series data or cluster analysis of similar sequences using information science techniques, including machine learning, it is possible to select a group of sequences that recognize antigens for specific antigens.

[0070] 2-1-3. Comprehensive Database By comprehensively collecting information on the sequences of antigen recognition sites for antigens involved in all immune reactions (infection, cancer immunotherapy, autoimmune reactions, etc.) and additional information from the above-mentioned public databases and independently created databases, it is possible to construct a large-scale dataset group as shown schematically in Figure 3. By preparing such a large-scale dataset group, it is possible to use the antigen receptor repertoire as a biosensor to comprehensively capture all immune reactions occurring in the body (infection, cancer immunotherapy, autoimmune reactions, etc.) using a small amount of sample. An example of the use of such a large-scale dataset group is form [f].

[0071] 2-2. Sequences that are identical at the amino acid sequence level or identical in parts other than two or less amino acid residues (matching sequences) A ​​database of sequences of antigen recognition sites for specific antigens [corresponding to Figure 1 (iii)] is compared with the repertoire data [corresponding to Figure 1 (ii)] to detect sequences that are identical at the amino acid sequence level or identical in parts other than two or less (preferably one or less) amino acid residues (corresponding to "sequences matching the database" in Figure 1) to sequences contained in the database. A sequence that is identical at the amino acid sequence level or identical in parts other than two or less amino acid residues is, in other words, a sequence that is completely identical to a sequence in the database or an amino acid sequence with a mismatch of one to two residues (preferably one residue) (similar sequence).

[0072] Any method capable of comparing amino acid sequences can be used to detect matching sequences. A specific example of such a method is the Levenshtein distance method. The Levenshtein distance method can detect amino acid sequences whose Levenshtein distance (edit distance, i.e., the minimum number of single-character substitutions, insertions, and deletions required to make one string match another) is 0 to 2 (preferably 0 to 1). Therefore, among matching sequences, the Levenshtein distance of a completely identical sequence is 0, and the Levenshtein distance of a similar sequence is 1 to 2 (preferably 1).

[0073] 3. Step C In step C, the number (corresponding to "Number of matching sequences (clones)" in Figure 1) and / or frequency (corresponding to "Proportion of matching sequences" in Figure 1) in the repertoire data of the sequences identified in step B is derived. In the present invention, step C can be optionally included regardless of the purpose of application of the method of the present invention.

[0074] That is, in step C, the number of sequences detected as identical or similar to sequences in the database (matching sequences) contained in the repertoire data and / or the frequency at which they appear are derived. The number and / or frequency can be derived appropriately based on known methods. It can be said that the greater the number and / or frequency of sequences identified as identical or similar to sequences in the database (matching sequences) in the repertoire data, the stronger and / or more frequently an immune response to a specific antigen occurs.

[0075] If the number and / or frequency of cases where an immune response to a specific antigen has not occurred for the matching sequence is known by common general knowledge or from information contained in a database, it is possible to determine whether the immune response has occurred. In other words, in this case, an immune response can be evaluated using only one data point. Preferred examples of such cases include form [b], form [c], case e1 of form [e], form [f], etc.

[0076] 4. Step D In step D, changes over time in the number and / or frequency of sequences matching the database obtained in step C are confirmed. Examples of cases in which the present invention includes step D include form [a], form [b], form [d], case e2 and case e3 of form [e], and form [f]. When the method of the present invention is applied to case e1 of form [c] or form [e], step D is not required.

[0077] When evaluating the immune response for repertoire data of a subject exposed to a specific antigen (e.g., form [a], form [b], form [f], etc.), it is confirmed whether the number and / or frequency level obtained in step C has increased compared to the number and / or frequency level before the antigen exposure. When evaluating the immune response for repertoire data of a subject who has undergone cancer immunotherapy (e.g., form [d], form [f], etc.), it is confirmed whether the number and / or frequency level obtained in step C has increased compared to the number and / or frequency level before the cancer immunotherapy. Furthermore, when evaluating the immune response due to vaccination for repertoire data of a subject who has undergone immunosuppressive treatment (e.g., case b4 of form [b], form [f], etc.), it is confirmed whether the number and / or frequency level obtained in step C has increased or decreased compared to the number and / or frequency level before the immunosuppressive treatment. When evaluating immune responses in repertoire data of a subject suffering from an autoimmune disease (for example, case e1, case e2, and form [f] of form [e]), it is confirmed whether the number and / or frequency level obtained in step C is increased compared to the number and / or frequency level in a sample collected at a different time from the same subject.

[0078] As described above in "1-3. Timing of Acquisition of Repertoire Data," it has been found that the activation period of immune cell receptor mRNA (i.e., the period of clonal proliferation of immune cells that responded to a specific antigen in the repertoire) occurs within a predetermined period after stimulation with a specific antigen. Specifically, the activation period after antigen stimulation for a primary response is, for example, 11 to 20 days or 11 to 18 days, preferably 12 to 16 days, and more preferably 13 to 15 days, while the activation period after antigen stimulation for a secondary or subsequent response is, for example, 3 to 10 days or 4 to 10 days, preferably 5 to 9 days, and more preferably 6 to 8 days. Therefore, by confirming whether the period when an increase in the number and / or frequency of sequences matching the database is observed corresponds to either the activation period after antigen stimulation for a primary response or the activation period after antigen stimulation for a secondary or subsequent response, it is possible to determine whether stimulation with a specific antigen caused a primary or secondary response. Specifically, if an increase in the number and / or frequency of sequences matching the database is observed 11 to 20 or 11 to 18 days (preferably 12 to 16 days, more preferably 13 to 15 days) after stimulation with a specific antigen, the immune response caused by the stimulation can be determined to be a primary response. If an increase in the number and / or frequency of sequences matching the database is observed 3 to 10 days (preferably 5 to 9 days, more preferably 6 to 8 days) after stimulation with a specific antigen, the immune response caused by the stimulation can be determined to be a secondary or subsequent response.

[0079] 5. Steps E, E', F, and G When the method of the present invention includes the above-described steps A to D, it may further include other steps as long as the effects of the present invention are not impaired. The other steps can be determined depending on the application purpose of the method of the present invention.

[0080] 5-1. Step E and Step E' When evaluating immune responses to repertoire data of subjects vaccinated with a nucleic acid vaccine, the method of the present invention may further include step E and / or step E'. Examples of cases in which step E is included include cases a1 to a3 of form [a] and form [f]. Examples of cases in which step E' is included include case a4 of form [a] and form [f].

[0081] In step E, the scientific validity of the nucleic acid vaccine is evaluated by checking the information contained in the database for sequences for which an increase in the number and / or frequency of sequences matching the database over time has been confirmed. The information contained in the database is selected from the group consisting of: [1] information on the presence or absence of neutralizing activity against an antigen, [2] information on the species or strain of the antigen, and [3] information on the epitope. The evaluation of scientific validity is selected from the group consisting of: [1] evaluating the nucleic acid vaccine as having clinical efficacy in producing antibodies with neutralizing activity if the neutralizing activity is confirmed; [2] evaluating the nucleic acid vaccine as being compatible with the target antigen if the species or strain is confirmed to be the same as the species or strain of the target antigen for which the nucleic acid vaccine was designed; and [3] evaluating the nucleic acid vaccine as being compatible with the target epitope if the epitope is confirmed to be the same as the target epitope for which the nucleic acid vaccine was designed. The above case [1] corresponds to case a1 of form [a], the above case [2] corresponds to case a2 of form [a], and the above case [3] corresponds to case a3 of form [a].

[0082] Step E allows confirmation of the scientific validity of a nucleic acid vaccine containing the blueprint (genetic information) of a specific antigen as an active ingredient, that it can produce antibodies with neutralizing activity in vivo, that it can produce antibodies that can recognize the target antigen (species or strain) as designed, or that it can produce antibodies that can recognize the target epitope as designed.

[0083] In step E', if the sequence for which an increase in the number and / or frequency of sequences matching the database over time has been confirmed is identical (i.e., a perfect match) to the sequence contained in the database at the amino acid sequence level, the scientific validity of the nucleic acid vaccine is evaluated as having the ability to produce antibodies whose antigen recognition site perfectly matches that of antibodies acquired through infection. According to the present invention, a large number of sequences that perfectly match the sequence of the antigen recognition site of an immune cell receptor can be detected. If the amino acid sequence of the antigen recognition site is, for example, a sequence consisting of 10 amino acids, there are 20 different amino acids, so theoretically, 20^10 different sequences would be required to find a perfect match. Considering this, the ability of the present invention to detect a large number of perfect match sequences is recognized as surprisingly efficient.

[0084] Step E', as shown in Figure 4, confirms the scientific validity that the nucleic acid vaccine administered to a healthy subject can produce antibodies in the body of the healthy subject that completely match the antibodies (having sequences included in the database) that the patient acquires upon infection with an antigen such as a virus.

[0085] 5-2. Step F When evaluating the immune response using repertoire data from a subject who has been inoculated with a vaccine (i.e., a specific antigen) and who has a high level of other antibodies (i.e., antibodies different from those produced by inoculation with the vaccine as a specific antigen) in their bodies at the time of specimen collection, the method of the present invention can further include step F. Examples of cases in which step F is included include cases b1 to b3 of form [b] and form [f].

[0086] In this case, the subject can be selected from subjects (S1) to (S3) described above in "1-2-1-3. Subjects with high levels of other antibodies." Specifically, this includes subjects who have been vaccinated with a specific antigen, who have also been administered an antibody drug, who have been vaccinated with another vaccine, and / or who have been infected.

[0087] In step F, the vaccine is determined to be functional if the number and / or frequency of sequences matching the database increase over time. As described above in "1-2-1-3. Subjects with High Levels of Other Antibodies," other antibodies (specifically, antibodies related to antibody drugs, antibodies produced in immune responses to other vaccines, or antibodies produced in immune responses to pathogens) are present at high levels in the bodies of subjects (S1) to (S3) due to the administration of antibody drugs, inoculation with other vaccines, or infection. Furthermore, due to the long half-life of antibody proteins, these other antibodies are maintained at high levels in the bodies of subjects (S1) to (S3). Even if antibodies are produced in parallel in an immune response to a vaccine as a specific antigen in this state, such antibodies cannot be detected by conventional immunological assays such as repertoire analysis or ELISA because they are masked by the large amount of other coexisting antibodies. The method of the present invention can selectively identify an immune response to a specific antigen from repertoire data without being affected by the amount of antibody protein in the body. Therefore, even if a subject has high levels of other antibodies, if an immune response to a vaccine as a specific antigen has occurred, the immune response can be selectively identified.

[0088] 5-3. Step G When evaluating immune responses using repertoire data from subjects who have undergone immunosuppressive treatment such as hematopoietic stem cell transplantation or B cell depletion therapy, the method of the present invention may further include step G. Examples of cases in which step G is included include case b4 of form [b] and form [f].

[0089] Step F may further include step G of determining whether or not immune function has recovered based on whether or not there has been an increase in the change over time in the number and / or frequency of sequences that match the database. For example, when an increase in the number and / or frequency of sequences that match the database is observed in repertoire data of a subject who has received a vaccine as a specific antigen after undergoing immunosuppressive treatment, it is possible to confirm that immune function that had been weakened by the immunosuppressive treatment has recovered.

[0090] 6. Step H When the repertoire data prepared in step A is obtained from specimens of subjects who were vaccinated with a vaccine (existing vaccine) against a virus strain ST1 that has emerged in the past, and the database used for matching in step B contains a group of sequences of antigen recognition sites of immune cell receptors against a virus strain ST2 (e.g., a mutant strain of virus strain ST1) for which the effectiveness of the vaccine (existing vaccine) is unknown, the present invention can further include step H of evaluating that the vaccine (existing vaccine) is also effective against virus strain ST2 if a sequence detected in step B is present. In this case, it becomes possible to determine that the existing vaccine can be effectively used against the newly emerged virus strain. Conversely, when no sequence is detected in step B, it becomes possible to determine that a new vaccine needs to be developed.

[0091] The present invention will be explained in more detail below by showing examples, but the present invention is not limited to these examples.

[0092] [Test Example 1] [Materials and Methods] Patients To evaluate immune responses after SARS-CoV-2 infection, peripheral blood samples were collected serially from three COVID-19 patients at Kobe University Hospital between August 2020 and December 2020. All patients were classified as having mild symptoms and were not receiving immunosuppressants. COVID-19 was confirmed by quantitative reverse transcription-polymerase chain reaction assay (rtPCR) for SARS-CoV-2.

[0093] Healthy volunteers were enrolled between May 2021 and December 2022 to evaluate immune responses after mRNA SARS-CoV-2 vaccination. All participants received either monovalent BNT162b2 [B.1.1.529], bivalent BNT162b2 [WT / OMI BA.4-5], or monovalent mRNA-1273 SARS-CoV-2 mRNA vaccines. Participants were confirmed to be SARS-CoV-2 naive by measuring anti-SARS-CoV-2 nucleocapsid protein IgG antibodies before vaccination. Blood samples were collected serially before and after vaccination.

[0094] To investigate the anti-SARS-CoV-2 spike antibody titers in serum samples after administration of the neutralizing antibody drugs tixagevimab / silgavimab for COVID-19 prevention, we enrolled 19 patients with hematological malignancies for whom tixagevimab / silgavimab was indicated (17 patients in Figure 1 and 2 hematopoietic stem cell transplant patients whose BCR repertoires were analyzed in Figures 4A and 4B). Blood samples were collected sequentially before and after administration of tixagevimab / silgavimab.

[0095] Sample Collection and Processing: Peripheral blood samples were collected using heparin-containing tubes. Peripheral blood mononuclear cells (PBMCs) were isolated from blood by density gradient centrifugation using Ficoll-Paque Plus (GE Healthcare, Little Chalfont, UK) and SepMate-50 tubes (STEMCELL Technologies, Vancouver, Canada) according to the manufacturer's protocol (STEMCELL Technologies). PBMC samples were stored at -80°C in CELLBANKER (ZENOGEN PHARMA, Fukushima, Japan) until analysis. Total RNA was extracted with TRIzol LS (Thermo Fisher Scientific, Waltham, MA, USA) and purified using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol. RNA quantity and purity were measured using an Agilent 2200 TapeStation (Agilent Technologies, Santa Clara, CA, USA). Serum samples were obtained by centrifuging blood samples at 1000 xg for 10 minutes at room temperature and immediately transferring them to a freezer maintained at -80°C.

[0096] SARS-CoV-2-Specific Immunoglobulin Antibody Assays Three fully automated commercially available immunoassays were used. The Abbott SARS-CoV-2 IgG II Quant (Abbott Laboratories, Sligo, Ireland) is a chemiluminescent microparticle immunoassay (CMIA) designed for the quantitative measurement of IgG antibodies against the receptor-binding domain (RBD) of the S1 subunit of the SARS-CoV-2 spike protein. Tests were performed on an Abbott Architect i2000SR system (Abbott Laboratories). The Roche Elecsys anti-SARS-CoV-2 S (Roche Diagnostics, Basel, Switzerland) is an electrochemiluminescent immunoassay (ECLIA) for the quantitative measurement of total Ig antibodies against the RBD of the SARS-CoV-2 spike protein. Tests were performed on a Roche Cobas e601 system (Roche Diagnostics). The Atellica IM SARS CoV-2 IgG (Siemens Healthcare Diagnostics, Erlangen, Germany) is a chemiluminescent immunoassay (CLIA) designed to quantitatively measure IgG antibodies against the RBD of the S1 subunit of the spike protein of SARS-CoV-2. The test was performed on an Atellica IM automated analyzer (Siemens Healthcare Diagnostics).

[0097] Antibody titers against nucleocapsid protein were measured using the QuaResearch COVID-19 Human IgM IgG ELISA Kit (nucleocapsid protein) (Cellspect, Inc., RCOEL961-N, Iwate, Japan). This kit detects antibody titers based on the indirect ELISA method and comes with immobilized antigenic proteins. The ELISA kit (nucleocapsid protein) plate contains immobilized full-length recombinant SARS-CoV-2 nucleocapsid protein expressed in Escherichia coli. Nucleocapsid protein in serum samples was measured according to the manufacturer's protocol.

[0098] Flow cytometry analysis. PBMCs were stained for 20 minutes at 4°C with the following anti-human antibodies for T cell lines: CD3 APC, CD4 BV510, and CD8 BV711 (all BD Biosciences, San Diego, CA, USA); and for B cell lines: CD19 BV510, CD27 BV421, IgD BV711, and CD38 BV510 (all Biolegend, San Diego, CA, USA). Isotype-matched antibodies were used as controls. Flow cytometry analysis was performed using a BD FACSAria III instrument (BD Biosciences). CD3+CD4+ cells were defined as helper T cells. CD19+CD27+IgD- cells were defined as class-switched B cells. CD19+CD27+CD38+ cells were defined as plasmablasts.

[0099] B cell receptor repertoire analysis was performed using a non-biased next-generation sequencer developed by Repertoire Genesis, Inc. Briefly, cDNA was synthesized from total RNA using a polyT18 primer (BSL-18E) and Superscript III reverse transcriptase (Invitrogen, CA, USA). After double-stranded (ds)-cDNA synthesis, a P10EA / P20EA dsDNA adapter was ligated and digested with NotI restriction enzyme. Nested PCR was performed using IgG constant region-specific primers (CG1 and CG2) and P20EA using KAPA HiFi DNA Polymerase (Kapa Biosystems, Woburn, MA, USA). An amplicon library was prepared by amplifying the second PCR product using P22EA-ST1 and CG-ST1-R. Index (barcode) sequences were added by amplification using the Nextera XT Index Kit v2 Set A (Illumina, San Diego, CA, USA). Sequencing was performed using an Illumina MiSeq paired-end platform (2 × 300 bp). BCR sequences were analyzed using repertoire analysis software developed by Repertoire Genesis Co., Ltd. (Osaka, Japan) using the international ImMunoGeneTics information system. (R) (IMGT) database (http: / / www.imgt.org) based on identity to reference sequences.

[0100] Metric calculation and network analysis. Data analysis and graphing were performed using packages implemented in R software (version 4.0.2). Levenshtein distance (edit distance) was calculated using the stringdist 0.9.10 package. Network analysis was performed using igraph 1.2.6 (https: / / igraph.org / r / ) implemented in R. The 1,000th most frequent BCR clonotype (node) was connected by edges defined by a Levenshtein distance of ≤1 amino acid sequence or ≤1 amino acid sequence of CDR3. The network was constructed using the force-directed layout algorithm proposed by Fruchterman and Reingold. Graphics were drawn using ggplot2 version 3.3.2. Probability of generation (pGen) values ​​for human IGH sequences were calculated using the OLGA package (Sethna Z, Elhanati Y, Callan CG, Walczak AM, Mora T. OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs. Bioinformatics. 2019;35(17):2974-2981.).

[0101] Database and COVID-19-specific sequence search COVID-19-specific antibody sequences were downloaded from CoV-AbDab (http: / / opig.stats.ox.ac.uk / webapps / covabdab / ). Data updated on December 20, 2022, containing 12,004 entries, was used as reference. Unpaired antibody sequences reported from 2011 to 2021 were downloaded from The Observed Antibody Space database (OAS, http: / / opig.stats.ox.ac.uk / webapps / oas / ) based on the "heavy chain" and "IGHG" attributes. A total of 260,856,092 sequences were used to validate the method. A total of 1,259,140 IgG antibody sequences from 12 healthy volunteers before the COVID-19 pandemic have already been reported (Kitaura K, Yamashita H, Ayabe H, Shini T, Matsutani T, Suzuki R. Different Somatic Hypermutation Levels among Antibody Subclasses Disclosed by a New Next-Generation Sequencing-Based Antibody Repertoire Analysis. Front Immunol. 2017;8:389.). Sequences with identical V and J gene names to the query sequence but with CDR3 amino acid sequence differences of 0–2 (Levenshtein distance, "CDR3AA Distance") were retrieved from the database. Among CoV-AbDab sequences, sequences with "Binds to" or "Neutralizing Vs" attributes for SARS-CoV2 were considered SARS-CoV-2 specific, regardless of variants. In addition, sequences with the "Neutralizing Vs" attribute of SARS-CoV2 were classified as neutralizing antibodies (Neut+), and sequences that did not contain SARS-CoV-2 in the "Neutralizing Vs" attribute and contained SARS-CoV-2 in the "Not Neutralizing Vs" attribute were classified as non-neutralizing antibodies (Neut-).

[0102] [Results] Effect of tixagevimab / silgavimab administration on anti-SARS-CoV-2 spike IgG antibody measurement by ELISA. To examine the effect of tixagevimab / silgavimab on anti-SARS-CoV-2 spike antibody measurement, antibody measurements were performed over time before and after administration using three representative automated quantitative anti-SARS-CoV-2 spike immunoassays (Abbott Laboratories, Roche Diagnostics, and Siemens Healthcare Diagnostics) using different ELISA methods. Seventeen patients with hematologic malignancies eligible for tixagevimab / silgavimab were enrolled (B-cell depletion therapy, n = 8; hematopoietic stem cell transplant, n = 6; chemotherapy, n = 3). As expected, antibody titers were extremely high in all patients after administration and remained high for a long period of time (Figure 1).

[0103] Analysis of the OAS public database using CoV-AbDab We verified the usefulness of CoV-AbDab using previously published repertoire data from before and after the COVID-19 pandemic. From the 12,004 CoV-AbDab data obtained, a lookup table with 8,977 identical V and J gene names and CDR3 amino acids of human sequences was used to search for SARS-CoV-2-specific sequences in public databases and data from the above patient cohort (Figure 2A). First, a total of 260,856,092 sequences published between 2011 and 2021 in the OAS public database were analyzed using CoV-AbDab. Perfect sequence matches for V and J gene names and CDR3 amino acid sequences were rare in pre-pandemic data (only 132 of 67,856,692 sequences (0.00019%)). However, many more were detected after 2020 (0.022%, 1,817 of 8,441,259 sequences) (Table 1, Frequency of occurrence (%) of SARS-CoV-2-specific sequences in the OAS database. Numbers in parentheses indicate data from samples classified as SARS-CoV-2). To detect sequences similar to SARS-CoV-2-specific sequences, we searched for antibody sequences with a CDR3 amino acid difference of 1 or 2 at a Levenshtein (LV) distance. Similar sequences with an LV distance of 1 were found 4,641 (0.0068%) before 2019 and 12,251 (0.15%) after 2020. Similar sequences with an LV distance of 2 were detected 59,356 times (0.087%) before 2019 and 27,484 times (0.33%) after 2020. The best S / N ratios, calculated as the detection rate after 2020 compared to before 2019, were 110.6 for the perfectly matched sequence (LV0), 21.2 for LV1, and 3.7 for LV2. Sensitivity and S / N ratio varied depending on the distance between the CDR3 sequences. These results demonstrate that a computational approach using the CoV-AbDab reference sequence is effective for detecting SARS-CoV-2-specific antibody sequences from antibody repertoire data.

[0104]

[0105] Next, we independently analyzed data from healthy individuals pre-COVID-19 pandemic. A total of 1,259,140 in-frame sequences from 12 healthy individuals (age: 37 ± 11.7 [mean ± SD], gender: 11:1 [male:female]) were analyzed using CoV-AbDab. The percentage frequencies of these sequences in each sample were 0.000075 ± 0.00026% (LV = 0), 0.00043 ± 0.00076% (LV = 1), and 0.0065 ± 0.0032% (LV = 2). These results suggest that SARS-CoV-2-specific sequences are rarely detected in uninfected healthy individuals, and even if detected, their frequency is quite low (Table 2, Frequency (%) of SARS-CoV-2-specific sequences in healthy individuals pre-pandemic).

[0106]

[0107] Analysis of BCR repertoire data from COVID-19 patients using CoV-AbDab We attempted to examine the immune response after SARS-CoV-2 infection using BCR repertoire analysis using CoV-AbDab. We performed BCR repertoire analysis on 17 blood samples collected from three patients with primary COVID-19. A total of 4,768,753 sequences were obtained, of which 2,858,278 in-frame sequences with V and J gene and CDR3 amino acid assignments were used. We then analyzed whether any of the CDR3 sequences were identical to those of CoV-AbDab (Figure 2B). As expected, several sequences matching the CDR3 sequences of CoV-AbDab were detected in the patient samples. While no matching sequences were detected immediately after the onset of symptoms, they gradually increased after the onset, peaking approximately 2 weeks later (Figure 2B).

[0108] We also analyzed the network formed by SARS-CoV-2-specific BCR clonotypes. Similar SARS-CoV-2-specific sequences bound to each other and formed clusters. Furthermore, BCR clusters rapidly formed and grew, reaching their maximum size approximately 2 weeks after symptom onset. Thereafter, the clusters rapidly disappeared (Fig. 2B).

[0109] Analysis of BCR repertoire data from healthy volunteers who received mRNA SARS-CoV-2 vaccine using CoV-AbDab To verify whether BCR repertoire analysis using CoV-AbDab can detect immune responses after vaccination, we analyzed BCR repertoires from blood samples from healthy volunteers who received the first and second doses of mRNA SARS-CoV-2 vaccine (monovalent BNT162b2 [B.1.1.529], Pfizer).

[0110] First, we focused on dominant clonal types using BCR repertoire data without using CoV-AbDab, but no significant changes were detected before and after vaccination (Figure 7).

[0111] Next, we analyzed the number and percentage frequency of matched sequences in BCR repertoire analysis using CoV-AbDab. We found that the number of matched sequences increased two weeks after the first vaccination and then rapidly decreased (Fig. 3A). Meanwhile, the number of matched sequences increased more rapidly (1 week) after the second vaccination (Fig. 3A). Similar results were also observed for booster shots of other mRNA vaccines (bivalent BNT162b2 [WT / OMI BA.4-5, Pfizer] and monovalent mRNA-1273 [Moderna]) (Fig. 3B and 3C). Thus, BCR repertoire analysis using CoV-AbDab detected post-vaccination immune responses in healthy volunteers after vaccination, as well as in COVID-19 patients.

[0112] Responsiveness to mRNA SARS-CoV-2 vaccination in patients after tixagevimab / silgavimab administration Responsiveness to mRNA SARS-CoV-2 vaccination after tixagevimab / silgavimab (T / C) administration was evaluated using BCR repertoire analysis with CoV-AbDab in two patients with hematological malignancies who underwent allogeneic hematopoietic stem cell transplantation.

[0113] Case 1 (T / C Patient 1): A 63-year-old woman with acute myeloid leukemia (AML) with myelodysplasia-associated changes underwent umbilical cord blood transplantation (CBT). Tixagevimab / silgavimab was administered 338 days after CBT, and the fourth dose (second dose after CBT) of mRNA vaccine (bivalent BNT162b2) was administered 348 days after CBT. Case 2 (T / C Patient 2): A 40-year-old man with B-cell acute lymphoblastic leukemia underwent unrelated bone marrow transplantation (u-BMT). Tixagevimab / silgavimab was administered 212 days after u-BMT, and the first dose of mRNA vaccine (monovalent BNT162b2) was administered 218 days after u-BMT.

[0114] Vaccination responses after hematopoietic stem cell transplantation depend on T cell and B cell reconstitution. At the time of vaccination, flow cytometry analysis was performed to assess T cell and B cell reconstitution. The presence of helper T cells (CD3+CD4+), class-switched B cells (CD19+CD27+IgD-), and plasmablasts (CD19+CD27+CD38+) was confirmed (Figures 4A and 4B). BCR repertoire analysis using CoV-AbDab clearly detected responses to mRNA SARS-CoV-2 vaccination even after tixagevimab / silgavimab administration (Figures 4A, 4B, and 8).

[0115] Characteristics of SARS-CoV-2-specific sequences in infected and vaccinated individuals Finally, we characterized the SARS-CoV-2-specific sequences. First, we determined their neutralizing or non-neutralizing potential based on the attributes of the reference sequence (Figure 5A). The neutralizing potential of the induced antibodies differed between groups, with vaccinated individuals showing a higher incidence of neutralizing antibodies and a lower incidence of non-neutralizing antibodies in the few infected individuals. We examined the frequency of individual SARS-CoV-2-specific sequences in each sample and found that the frequency of perfectly matched sequences was significantly higher than that of sequences with one or two amino acid mismatches (mean ± SD: 0.029 ± 0.088 for LV0, 0.0079 ± 0.034 for LV1, and 0.0074 ± 0.041 for LV2; Kruskal-Wallis test and Dunn-Bonferroni post hoc test; LV0 vs. LV1: p<0.0001, LV0 vs. LV2: p<0.0001, LV2 vs. LV3: not significant) (Fig. 5B). We also examined the CDR3 length and V / J combination usage of matched antibody sequences (Fig. 5C, D). The most perfectly matched sequence was IGHV4-59 / IGHJ4, followed by IGHV3-33 / IGHJ4. Sequences with a single amino acid mismatch frequently contained IGHV1-8 / IGHJ4, IGHV3-30-3 / IGHJ4 or IGHJ6, IGHV3-9 / IGHJ4, or IGHV3-33 / IGHJ4. These SARS-CoV-2-specific sequences were detected in multiple individuals and showed common antibody characteristics (Tables 3A and 3B, SARS-CoV-2-specific sequences in infected and vaccinated individuals (perfect matches)). Only 86 sequences were detected as SARS-CoV-2-specific. The majority of perfect matches were found to be short CDR3 sequences of 8 amino acids and IGHV4-59 / IGHJ4 sequences (Figure 6A). Among known SARS-CoV-2-specific sequences, sequences with a high probability of generation (pGen) were frequently found in infected and vaccinated individuals (Figure 6B). These patterns were similar to those found in the OAS database search results, demonstrating the validity of the method used in this study (Figures 9-12).

[0116]

[0117]

[0118] [Effectiveness of the Invention] In this study, we evaluated mRNA SARS-CoV-2 vaccine responses at the level of mRNA expression rather than protein expression using BCR repertoire data and a database of BCR sequences that bind to target antigens. In fact, this method of quantifying antigen-specific antibody sequences clearly demonstrated responses to mRNA SARS-CoV-2 vaccination even after administration of tixagevimab / silgavimab (Figures 4A and 4B). Circulating variants change over time in individual regions. In the United States, tixagevimab / silgavimab was confirmed to be ineffective against more than 90% of currently circulating variants, and the FDA revised its emergency use authorization for tixagevimab / silgavimab in January 2023. Currently, various anti-SARS-CoV-2 monoclonal antibodies against new variants, including the Omicron strain, other than tixagevimab / silgavimab, are under development. The type of antibody preparation applicable in each country varies depending on the virus mutation, but it can be inferred that the method of this example can be applied after administration of any type of anti-SARS-CoV-2 antibody.

[0119] The establishment of this method for detecting vaccine responses after antibody administration is of great clinical significance. Furthermore, because antigens developed in mRNA vaccines may generate large amounts of antibodies, some experts have expressed concern that the presence of pre-existing antibodies may inhibit the response to vaccination. However, the method used in this example clearly confirmed the presence of a vaccine response after administration of tixagevimab / silgavimab (Figures 4A and 4B).

[0120] Previously, we reported that in COVID-19 patients, mRNA expression of multiple BCR clonotypes surged two weeks after onset and then decreased within one week (Funakoshi Y, Ohji G, Yakushijin K, et al. Massive surge of mRNA expression of clonal B-cell receptor in patients with COVID-19. Heliyon. 2021;7(8):e07748.). This report suggested that analyzing BCR repertoire analysis immediately after SARS-CoV-2 infection is important for measuring overall humoral immune activity. However, our method revealed that the frequency of SARS-CoV-2-specific sequences was only 0.1–2% around two weeks after onset (Figure 2B). These results demonstrate that it is virtually impossible to determine specific immune responses to SARS-CoV-2 from the total BCR repertoire data using conventional repertoire analysis.

[0121] The majority of early changes in the total repertoire in infected individuals may be the result of infection-associated inflammation or secondary immune responses. In contrast, no significant changes based on the total BCR repertoire data were observed in vaccinated volunteers (Figure 7). However, the method used in this example, first, focused on the activation period of humoral immunity in the primary or secondary immune response (several days to two weeks after antigen exposure) and collected multiple blood samples over a short period. Second, by analyzing the BCR repertoire data using a database of BCR sequences that bind to target antigens, we were able to, for the first time, clarify the individual BCR repertoire-based vaccination response.

[0122] We also investigated the characteristics of SARS-CoV-2-specific sequences based on our results and public databases. SARS-CoV-2-specific sequences frequently contained IGHV4-59 and short CDR3 amino acids. These sequences were most frequently detected in multiple individual and post-pandemic samples, as shown in our results. However, some were also detected, albeit at a much lower frequency, in pre-pandemic samples from 2019. IGHV4-59 sequences pair with the light chain of IGKV3-20 / IGKJ1, but no neutralizing activity has been reported. Additionally, some reports have suggested that public IGHV4-59 / IGKV3 antibodies bind to the S2 domain and cross-react with SARS-CoV-1. This sequence has the potential to react with a wide range of coronavirus strains. Known SARS-CoV-2-specific sequences are characterized by short CDR3 sequences and high pGen values. Since sequences with high pGen values ​​among known SARS-CoV-2-specific sequences increase significantly after infection or vaccination, it is believed that the initial immune response upon exposure to unknown COVID-19 antigens is often mediated by more abundant, common SARS-CoV-2-specific sequences.The method of this example makes it possible to reliably detect the early infection immune response by utilizing the abundant, known, high-pGen SARS-CoV-2-specific sequences in any individual.

[0123] Compared with the conventional method of evaluating vaccine responses by measuring antibody titers using ELISA, the method of this example has the following advantages.

[0124] First, while antibodies measured using conventional methods have a long half-life, remaining in the blood for several months after production, the activity of mRNA measured in this method is short-lived and therefore not affected by SARS-CoV-2 vaccination, infection, antibody therapy, etc., making it possible to monitor activity on an ongoing basis.

[0125] Furthermore, while conventional methods involve a time lag between the activation of B cells as humoral immunity and the increase in antibodies to detectable levels in serum, the method of this example allows for direct observation of B cell activity in humoral immune responses in real time. These features enable the method of this example to accurately evaluate humoral immunity, including primary and secondary responses. According to this example, B cells were activated approximately two weeks after the initial vaccination or initial exposure via infection as a primary immune response. Furthermore, B cells were activated approximately one week after a booster vaccination as a secondary immune response.

[0126] Furthermore, while conventional serological tests cannot evaluate individual specific antibodies induced after infection, the method of this example can provide useful information about individual antibodies. For example, the method of this example can obtain useful information about the characteristics of multiple antibodies with neutralizing and non-neutralizing activity. The frequency of neutralizing antibody sequences varies depending on the sample, and is expected to serve as an indicator of the immune defense of infected individuals. Furthermore, because the appearance of antibodies with non-neutralizing activity is associated with the severity of infection in infected patients, the detection of non-neutralizing antibodies is also a noteworthy indicator. In recent years, an ELISpot assay has been developed to measure in vitro the number of human IgG-secreting B cells stimulated with R-848 and IL-2 as a method for evaluating B cell responses after infection or vaccination. However, this ELISpot assay cannot report immune responses in real time or provide additional information.

[0127] The utility of the method of this example is not limited to confirming vaccine responses after antibody drug administration. It can also be used, for example, to estimate the degree of immune reconstitution after hematopoietic stem cell transplantation. Immune reconstitution after hematopoietic stem cell transplantation has been evaluated using total lymphocyte counts, lymphocyte subset analysis, and cytokine profile analysis, but these assays are not accurate biomarkers. Generally, almost all hematopoietic stem cell transplant patients receive an mRNA SARS-CoV-2 vaccine 3–6 months after transplantation. The method of this example can evaluate humoral immune reconstitution at the time of vaccination, without being affected by prior infection, vaccination, or antibody therapy. The method of this example can also be used to evaluate humoral immune reconstitution after B cell depletion therapy.

[0128] These results demonstrate that BCR repertoire analysis using CoV-AbDab can quantify antigen-specific antibody sequences to evaluate responses to SARS-CoV-2 vaccination. This example demonstrates that responses to mRNA SARS-CoV-2 vaccination persist even after administration of tixagevimab / silgavimab. This method can be applied to elucidating disease mechanisms and developing therapeutic drugs in the field of antigen-antibody reactions.

[0129] [Test Example 2] The BCR / antibody sequences in CoV-AbDab are linked to information about strains (mutant strains and variants). For the BCR repertoires of healthy volunteers 1 to 3, sequences matching the database immediately before and 7 and 14 days after administration of the mRNA vaccine against SARS-CoV-2 (antibody sequences with a Levenshtein distance of 0 amino acid difference in CDR3 and antibody sequences with a Levenshtein distance of 1 or less) were analyzed in the same manner as in Test Example 1 to identify strains (mutant strains and variants of the Omicron strain) to which antibodies produced by the vaccine bind. The results are shown in Figures 17A to 17C.

[0130] As shown in Figures 17A to 17C, it was possible to identify the strains (mutant strains and variants of the Omicron strain) to which the antibodies produced by the vaccine bind. If a new vaccine designed and developed to target a new mutant strain or variant is used in place of the vaccine used in this test example and analyzed in the same manner, the new vaccine can also be used to evaluate the function of whether it binds to known mutant strains or variants.

[0131] [Test Example 3] The same subject received multiple doses of mRNA vaccine against SARS-CoV-2. The first and second doses were the original strain vaccine, the fifth dose was the bivalent vaccine of the original strain and BA.4 / 5, and the sixth dose was the Omicron XBB vaccine. Sequences matching the database were analyzed in the BCR repertoire immediately before the first dose, 7 and 14 days after the first dose, immediately before the second dose (21 days after the first dose), 3 and 7 days after the second dose (24 and 28 days after the first dose), immediately before the fifth dose, 3 and 7 days after the fifth dose, immediately before the sixth dose, and 7 and 12 days after the sixth dose, as in Test Example 1, to identify strains (mutant strains and Omicron strain variants) to which antibodies produced by the vaccine bind. The results are shown in Figure 18.

[0132] As shown in Figure 18, an increase in matching sequences was observed after each vaccination. Analysis of each compatible variant revealed an increase in the number of antibody sequences capable of binding to Omicron strains (indicated by the solid arrows in the "Strains" column in the figure) and an increase in the number of antibody sequences capable of binding to XBB variants of Omicron strains (indicated by the solid arrows in the "Omicron sublineages" column in the figure) after the sixth vaccination with the Omicron XBB vaccine. This confirmed the scientific validity of the administered Omicron XBB vaccine (i.e., its validity for the target antigen strains (specifically, mutant strains and variants)).

[0133] Furthermore, as shown in Figure 18, vaccination with the original strain vaccine increased the number of antibody sequences capable of binding to subsequently emerging Omicron strains (increase indicated by the dotted arrows in the "Strains" column in the figure) and also increased the number of antibody sequences capable of binding to Omicron XBB variants (increase indicated by the dotted arrows in the "Omicron sublineages" column in the figure). This confirmed that previously administered vaccines were also capable of producing antibodies capable of binding to subsequently emerging strains (mutant strains or variants). In other words, it was confirmed that the efficacy of previous vaccines also applies to some extent to mutant strains that emerge for the first time. Furthermore, since vaccination with the Omicron XBB vaccine yielded a greater number of sequences matching the Omicron XBB variants than vaccination with the original strain vaccine, it was also confirmed that the Omicron XBB vaccine is more effective against Omicron XBB variants.

[0134] [Test Example 4] The spike protein targeted by vaccines is composed of S1 and S2 segments, and the RBD region within S1 is known to be important for infection. BNT-162b2 (Pfizer) and mRNA-1273 (Moderna) are mRNA vaccines that target the entire S1 and S2 spike proteins of SARS-CoV-2, while MAFB-7256a (Daiichi Sankyo Vaccine), approved in Japan in 2024, is an mRNA vaccine targeting the RBD. Epitope information is linked to the BCR / antibody sequence within CoV-AbDab. The BCR repertoire immediately before vaccination and 7 and 14 days after vaccination was analyzed in the same manner as in Test Example 1 for sequences matching the database to identify epitopes. The results are shown in Figure 19. In Figure 19, solid arrows indicate sequences whose epitope is RBD (the target of BNT-162b2 and MAFB-7256a), dotted arrows indicate sequences whose epitope is S2 (the target of BNT-162b2), and dashed arrows indicate sequences whose epitope is another site (which may be RBD).

[0135] As shown in Figure 19, the sequences that increased on day 7 after BNT162b2 vaccination were related to various regions of the spike protein, such as S1, RBD, and S2, while the sequences that increased on day 7 after MAFB-7256a vaccination were related to the RBD. Therefore, the scientific validity of the mRNA vaccine (validity for the type of target epitope) was confirmed.

[0136] [Test Example 5] [1] Timing of clonal proliferation of immune cells due to infection, initial vaccination, or booster vaccination For each of exposure to a specific antigen (SARS-CoV-2) due to infection, exposure to a specific antigen (vaccine against SARS-CoV-2) due to initial vaccination, and exposure to a specific antigen (various vaccines against SARS-CoV-2) due to second or subsequent vaccination (booster vaccination), sequences matching the database in the BCR repertoire (antibody sequences with a Levenshtein distance of 0 for CDR3 amino acid difference, and antibody sequences with a Levenshtein distance of 1 or less) were analyzed in chronological order in the same manner as in Test Example 1. The results are shown in Figure 20A (primary response due to infection or initial vaccination) and Figure 20B (secondary or subsequent response due to booster vaccination).

[0137] [2] The timing of clonal proliferation of immune cells due to cancer immunotherapy We classified B cell subsets and confirmed that activated B cells (CD21low B cells, class-switched B cells, plasmablasts, and plasma cells) that lead to antibody production increase at the same time.

[0138] As shown in Figure 21A (explanation of B cell subset classification), activated B cells (CD21low B cells, class-switched B cells, plasmablasts, and plasma cells) that lead to antibody production were analyzed. As shown in Figures 21B and 21C, activated B cells were confirmed to increase 7 days after cancer immunotherapy (booster immunization). As shown in Figure 21D, activated B cells increased 7 days after cancer immunotherapy (booster immunization), and a greater increase was observed in patients who developed irAEs (side effects: autoimmune diseases following the administration of immune checkpoint inhibitors) (specifically, patients 1, 2, 6, 10, and 11).

[0139] [3] Results As shown in Figure 20A, after infection or initial vaccination, sequences matching the database in the BCR repertoire increased in about two weeks. As shown in Figure 20B, after booster vaccination, sequences matching the database in the BCR repertoire increased in about one week. Furthermore, as shown in Figures 21B and 21D, activated B cells also increased in about one week after cancer immunotherapy (booster immunization). In other words, it was confirmed that the timing of clonal proliferation of immune cells is commonly about two weeks after antigen stimulation in the case of primary immune responses, and about one week after antigen stimulation in the case of secondary immune responses.

[0140] [Test Example 6] The immune response to vaccination was evaluated in patients 1 to 3 after hematopoietic stem cell transplantation. Figures 22A and 22B show the background and analysis results of patients 1 to 3.

[0141] Patient 1 underwent hematopoietic stem cell transplantation after one SARS-CoV-2 infection and was subsequently vaccinated against SARS-CoV-2 (specific antigen). Patient 2 underwent hematopoietic stem cell transplantation after two SARS-CoV-2 infections and was subsequently vaccinated against SARS-CoV-2 (specific antigen). Patient 3 underwent hematopoietic stem cell transplantation after two SARS-CoV-2 infections and was subsequently vaccinated against SARS-CoV-2 (specific antigen). Sequences matching the database (antibody sequences with a Levenshtein distance of 0 for CDR3 amino acid difference and antibody sequences with a Levenshtein distance of 1 or less) were analyzed in the same manner as in Test Example 1 for the BCR repertoire obtained from samples collected at the time points marked with "*" in Figures 22A and 22B.

[0142] As shown in Figure 22A, regardless of the antigenic stimulation and the number of times thereof before hematopoietic stem cell transplantation, the first antigenic stimulation (vaccination) after hematopoietic stem cell transplantation increased the number of matching sequences two weeks after the first antigenic stimulation. Furthermore, as shown in Figure 22B, regardless of the antigenic stimulation before hematopoietic stem cell transplantation, the second or subsequent antigenic stimulation (vaccination) after hematopoietic stem cell transplantation increased the number of matching sequences one week after the second or subsequent antigenic stimulation. This confirms that the immunity acquired by antigenic stimulation before hematopoietic stem cell transplantation is reset by hematopoietic stem cell transplantation. Therefore, the timing of clonal proliferation of immune cells (increase in matching sequences) due to antigenic stimulation after hematopoietic stem cell transplantation can also be used to determine whether the immune response being analyzed is due to the first antigenic stimulation or the second or subsequent antigenic stimulation after hematopoietic stem cell transplantation. In other words, if the timing is approximately two weeks after the antigen stimulation after hematopoietic stem cell transplantation, it can be determined that the immune response being analyzed is due to the first antigen stimulation after hematopoietic stem cell transplantation, and if the timing is approximately one week after the antigen stimulation after hematopoietic stem cell transplantation, it can be determined that the immune response being analyzed is due to the second or subsequent antigen stimulation after hematopoietic stem cell transplantation.

[0143] [Test Example 7] By citing literature, we independently collected approximately 1,300 sequences of antigen recognition sites of B cell receptors capable of binding to influenza HA antigens and created a database. Using this database, we analyzed the BCR repertoire of immune responses after inactivated influenza vaccination (because the subjects had previously been infected with influenza, the immune response due to the vaccination was a secondary or subsequent response). As a result, as shown in Figure 23A, we confirmed that matching sequences increased one week after vaccination (an immune response due to stimulation by influenza HA antigen). Furthermore, we collected sequences through an in vitro experiment as shown in Figure 23B, and further expanded this database. The database, which continues to expand as sequences are collected, can similarly be used to evaluate the immune response.

Claims

1. A method for evaluating an immune response comprising: a step A of preparing repertoire data obtained from a specimen of a subject, the repertoire data comprising a group of sequences of antigen recognition sites of immune cell receptors; and a step B of comparing the repertoire data with a database comprising a group of sequences of antigen recognition sites of immune cell receptors for specific antigens, and detecting from the repertoire data a sequence which is identical to the sequence contained in the database at the amino acid sequence level or which is identical in a portion other than two or less amino acid residues.

2. The method according to claim 1, further comprising a step C of deriving the number and / or frequency in the repertoire data of the sequences detected by the step B.

3. The method of claim 2, further comprising step D of determining changes in said number and / or frequency over time.

4. The method according to claim 3, wherein in step D, it is confirmed whether the time period during which an increase is observed as a change over time corresponds to 11 to 20 days or 3 to 10 days after stimulation with the specific antigen.

5. The method according to any one of claims 1 to 4, wherein the subject is a subject that has been exposed to the specific antigen.

6. The method of claim 5, wherein the exposure to a specific antigen is by vaccination.

7. The method of claim 6, wherein the vaccine is a nucleic acid vaccine.

8. The method of claim 6, wherein the vaccine is a coronavirus vaccine or an influenza vaccine.

9. The method of claim 7, further comprising a step E of evaluating the scientific validity of the nucleic acid vaccine by checking additional information included in the database for the sequences for which an increase in the number and / or frequency over time has been confirmed, wherein the additional information is selected from the group consisting of: [1] information on the presence or absence of neutralizing activity against an antigen, [2] information on the species or strain of the antigen, and [3] information on the epitope, and the evaluation of the scientific validity is selected from the group consisting of: [1] evaluating the nucleic acid vaccine as having clinical efficacy in producing antibodies with neutralizing activity when it is confirmed that the neutralizing activity is present; [2] evaluating the nucleic acid vaccine as being compatible with the target antigen when it is confirmed that the species or strain is the same as the species or strain of the target antigen for which the nucleic acid vaccine was designed; and [3] evaluating the nucleic acid vaccine as being compatible with the target epitope when it is confirmed that the epitope is the same as the target epitope for which the nucleic acid vaccine was designed.

10. The method according to claim 7, further comprising a step E' of evaluating, when the sequence whose number and / or frequency has been confirmed to increase over time is identical to the sequence contained in the database at the amino acid sequence level, the scientific validity of the nucleic acid vaccine as being capable of producing antibodies whose antigen recognition site is completely identical to that of antibodies acquired by infection.

11. The method of claim 5, wherein the exposure to a specific antigen is an infection.

12. The method of claim 11, wherein the specific antigen is a coronavirus or an influenza virus.

13. The method of claim 5, wherein the subject is a subject who has been administered an antibody drug, vaccinated, and / or infected, and the antibody drug, the vaccine, and the pathogen of the infection cause the subject's body to possess antibodies other than those produced by exposure to the specific antigen.

14. The method of claim 13, further comprising the step F of determining that the vaccine is functional if the number and / or frequency increases over time, wherein the specific antigen is a vaccine.

15. The method of claim 5, wherein the sample is taken at the time of activation of immune cell receptor mRNA for the specific antigen.

16. The method of claim 15, wherein the activation time is 11 to 20 days or 3 to 10 days after the exposure.

17. The method according to any one of claims 1 to 3, wherein the subject is a subject undergoing cancer immunotherapy.

18. The method of claim 16, wherein the sample is taken at the time of activation of immune cell receptor mRNA for the specific antigen.

19. The method according to claim 17, wherein the activation period is 11 to 20 days or 3 to 10 days after the cancer immunotherapy.

20. The method of any one of claims 1 to 4, wherein the subject is a subject undergoing immunosuppressive treatment.

21. The method of claim 20, wherein said immunosuppressive treatment is hematopoietic stem cell transplantation or administration of B cell depletion therapy.

22. The method according to claim 21, wherein the immunosuppressive treatment is hematopoietic stem cell transplantation or B cell depletion therapy, and further comprises step G of determining whether or not the immune function has been restored based on whether or not the change in the number and / or frequency over time has increased.

23. The method according to any one of claims 1 to 4, wherein the subject is an autoimmune disease patient.

24. The method according to claim 1, further comprising a step H of evaluating that the vaccine is effective against the virus strain ST2 when the detected sequence is present, wherein the repertoire data is obtained from samples of subjects who were vaccinated against a virus strain ST1 that has previously emerged, the specific antigen is a virus strain ST2 for which the effectiveness of the vaccine is unknown, and 25. The method according to claim 1, wherein the database includes sequences of the antigen recognition site of the immune cell receptor for the specific antigen collected from a group of subjects in which an immune reaction has occurred due to the specific antigen, and is obtained by the following steps: collecting repertoire data including a group of sequences of the antigen recognition site of the immune cell receptor from a sample of each of the subjects in the study, and a group of sequences of the activation time T of the mRNA of the immune cell receptor for the specific antigen. ex , before the activation time T bf and T after said activation time af A step of acquiring repertoire data in a time series manner at the activation time T ex selecting sequences of antigen recognition sites of immune cell receptors in which proliferation is observed as information to be collected in said database.

26. Activation period T ex is 11 to 20 days or 3 to 10 days after stimulation with the specific antigen.

27. The method of claim 1, wherein the immune cell is a T cell or a B cell.

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