Method for predicting the evolution of an immune response in a subject and kit for immunophenotyping

Abstract

The invention relates to a method for predicting the evolution of an immune response in a subject towards an effector or suppressor response, based on cellular plasticity determined by the cytokine milieu generated after antigenic stimulation. The invention also allows for evaluating the generation of antigen-specific memory regulatory T cells in the evolution of the immune response. The invention also relates to a kit for carrying out the method according to the invention.

Description

[0001] METHOD FOR PREDICTING THE EVOLUTION OF AN IMMUNE RESPONSE IN A SUBJECT AND KIT FOR IMMUNOPHENOTYPING

[0002] DESCRIPTION

[0003] FIELD OF INVENTION

[0004] The present invention pertains to the technical field of immunophenotyping methods. More specifically, the invention relates to a method for predicting the evolution of an immune response in a subject and to a kit for carrying out said method.

[0005] BACKGROUND OF THE INVENTION

[0006] The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a global public health emergency by the World Health Organization in January 2020. To date, COVID-19 has caused hundreds of millions of infections and nearly millions of deaths worldwide. In most infected patients, the infection presents with mild symptoms, similar to those of the flu. However, approximately 15% of patients develop more severe illness.

[0007] The most effective preventive measure to avoid severe progression of COVID-19 is vaccination, which helps reduce mortality, the frequency of severe illness, and the infection rate. Since the beginning of the pandemic, multiple types of vaccines against SARS-CoV-2 have been developed and used. In addition to vaccine platforms already on the market, such as those based on inactivated viruses or viral vectors, between 2020 and 2021, different mRNA vaccines, previously used in animal research models and some clinical trials, began to be developed and administered on a large scale. Moderna's mRNA-1237 and Pfizer-BioNTech's BNT162b2 vaccines, both based on this novel technology, were the first vaccines tested and approved for human use.Although both vaccines proved to be effective and safe in initial clinical trials in the general population (around 95%), their efficacy in the most vulnerable groups, such as the elderly or solid organ transplant recipients, who had been excluded or underrepresented in these initial trials, was considerably reduced. In general, older people tend to have weaker immune systems, which can significantly reduce the response to vaccines, and in this context, immunosenescence and inflammaging appear to be key factors. Immunosenescence is defined as the age-related dysregulation of the immune system associated with the involution of the thymus, the primary lymphoid organ responsible for the production of immunocompetent T cells. As we age, the thymus involutes and loses functionality, decreasing the supply of naive T lymphocytes to the periphery.This leads to clonal expansion and accumulation of senescent and exhausted memory T lymphocytes, thereby reducing the repertoire of TCRs needed to engage de novo antigens. Furthermore, these cells exhibit a senescence-associated secretory profile, contributing to increased levels of cytokines and inflammatory proteins in the blood, thus contributing to persistent low-grade chronic inflammation, or inflammaging, also associated with aging.

[0008] On the other hand, solid organ transplant recipients undergo post-transplant immunosuppression and have a higher number of comorbidities, making them a vulnerable group for complications arising from SARS-CoV-2 infection. Although vaccines administered to this group have proven safe, their efficacy is much lower than in the general population, even after booster doses. Response rates of between 20% and 50% have been reported after the first and second doses, respectively, and around 70% after the third, indicating that the response remains inadequate.

[0009] Given the low level of vaccine response in the most vulnerable groups, new strategies are urgently needed to improve antibody titers after COVID-19 vaccination and the effectiveness of vaccination in this population. One possible strategy would involve understanding the behavior of the immune response and modifying vaccination schedules accordingly. Similar strategies have proven effective in previous experiences with vaccines administered to transplant recipients against other pathogens.

[0010] To date, methods for evaluating a subject's immune response to a stimulus are based on quantifying the expansion / reduction of regulatory T cells after antigen encounter and / or the production of cytokines in response to the antigen. See, for example, the following state-of-the-art documents: ■ ANDERSON, Jeremy, et al [OMIP-91: a 27-colorflow cytometry panel to evaluate the phenotype and function of human conventional and unconventional T-cells. Cytometry Part A, 2023, vol. 103, no. 7, pp. 543–547] discloses an immunophenotypic panel to identify conventional (CD4 and CD8) and unconventional (yo and MAIT) T cell subpopulations in human peripheral blood mononuclear cells, their frequency, and function in response to specific stimuli.This panel includes markers of Th subpopulations (including regulatory T cells (Treg) and Th17 cells, among others), activation markers (including CD69, CD137, CD40L, and OX-40), cytotoxicity markers (including perforin and granzyme-B), and pro-inflammatory cytokines (including TNFα, IL-2, IL17α, and IFNγ). However, it does not include markers of regulatory B cells (Breg) or any anti-inflammatory cytokines (IL-10, TGFP) that are fundamental for regulating the suppressor / effector balance. Specifically, TGF-β is essential for determining the differentiation of a naïve cell into a Treg (suppressor-anti-inflammatory activity) or a Th17 (effector-pro-inflammatory activity) in response to a stimulus and is therefore key in studying the cellular plasticity of these subpopulations. It also does not include IL-6, IL-21, or IL-1β, which are critical in preferential differentiation into Th17 vs.Treg from a virgin cell (IL-6), as in the reconversion of Treg into Th17, and are therefore also key in the study of the cellular plasticity of these subpopulations.

[0011] ■ GRAVES, Andrew J., PADILLA, Marcelino G., HOKEY, David A. [OMIP-022: comprehensive assessment of antigen-specific human T-cell functionality and memory. Cytometry, 2014, vol. 85, no. 7, p. 576] discloses a method for predicting a specific response to Mycobacterium tuberculosis by identifying 22 markers using cytometry. Markers were detected in cryopreserved infant peripheral blood mononuclear cells stimulated with peptide groups for various antigens of interest. This method allows for the identification of Th17 among other Th subpopulations, activation (CD154), and cell degranulation (CD107), as well as some cytokines (including IL-2, IL-17A, IL-22). However, it does not include the identification of Treg or Breg cells, anti-inflammatory cytokines, or any of the cytokines involved in the plasticity of these two subpopulations.

[0012] ■ WANG, Ya, et al. [Immunophenotyping of peripheral blood mononuclear cells in septic shock patients with high-dimensional flow cytometry analysis reveals two subgroups with differential responses to immunostimulant drugs. Frontiers in immunology, 2021, vol. 12, p. 634-127] describes a panel for immunophenotyping using flow cytometry on peripheral blood mononuclear cells from patients with sepsis. The objective of this study was to evaluate different responses to immunostimulant drugs by identifying subpopulations of T cells (CD4 and CD8, including Th17 and Treg, among other Th), B cells, NK cells, mDCs, and monocytes, as well as different cytokines (including IFNγ, TNFα, IL-6, IL-10, IL-2, IL-17A). However, although it includes IL-6, other crucial cytokines are also missing in the study of Th17 / Treg plasticity, such as IL-21, TGFb, IL-1 b, which provide non-redundant information to that of IL-6.

[0013] ■ PREGLEJ, Teresa, et al. [Advanced immunophenotyping: A powerful tool for immune profiling, drug screening, and a personalized treatment approach. Frontiers in Immunology, 2023, vol. 14, p. 1096096] describes a panel of 22 immunophenotyping markers using spectral flow cytometry for characterizing peripheral blood mononuclear cells and human T cells (CD4 and CD8, including Th17 and Treg among other Th cells), as well as activation and inhibition markers, with the aim of identifying patients with autoimmune diseases and drug-induced changes in vitro. However, it does not include any cytokines (neither anti-inflammatory nor pro-inflammatory) and, therefore, cannot address a study of cell differentiation / plasticity.

[0014] ■ LIU, Ying, et al. [30-color full spectrum flow cytometry panel for deep immunophenotyping of T cell subsets in murine tumor tissue. Journal of Immunological Methods, 2023, vol. 516, p. 113459] discloses an immunophenotypic panel for the identification of T, NKT and B cells in murine peripheral blood mononuclear cells by spectral flow cytometry. It includes markers of T cell subpopulations (Treg and effector T cell markers such as CD127, KLRG1, CXCR3), activation markers (CD44, CD69), costimulatory markers (ICOS, OX-40) and co-inhibitory markers (TIM-3, LAG-3, CTLA-4, TIGIT, PD-1), cytotoxicity markers (Perforin, Granzyme-B) and degranulation markers (CD107A), and pro-inflammatory (TNFα, IFNγ) and anti-inflammatory (IL-10) cytokines. However, in addition to being a panel optimized for mouse cells, it does not include specific analysis of Th17 cells or cytokines specifically involved in Treg / Th17 plasticity.

[0015] ■ PARK, Lily M.; LANNIGAN, Joanne; JAIMES, Maria C. [OMIP-069: forty-color full spectrum flow cytometry panel for deep immunophenotyping of major cell subsets in human peripheral blood. Cytometry Part A, 2020, vol. 97, no. 10, pp. 1044–1051] discloses a panel for immunophenotyping cell populations in human peripheral blood using spectral flow cytometry. Specifically, this panel includes the identification of T cells (CD4, CD8, and CD6; including Treg), NKT cells, B cells, monocytes, dendritic cells, innate lymphoid cells (ILCs), and basophils. It also includes some markers of cell activation and inhibition. However, it does not identify Th17 cells, nor does it include intracellular cytokines of any kind, and therefore does not address the study of Treg / Th17 cell plasticity.

[0016] ■ FERNANDEZ, Marco A., et al. [High-dimensional immunophenotyping with 37-color panel using full-spectrum cytometry. Single-Cell Protein Analysis: Methods and Protocols. New York, NY: Springer US, 2021. p. 43-60] discloses an immunophenotyping procedure using spectral cytometry that comprises a 37-color panel for identifying T cells (CD4, CD8, iO; including Treg), NK, NKT, B cells, monocytes, dendritic cells, including plasmacytoids, innate lymphoid cells (ILCs), and basophils in peripheral blood mononuclear cells from patients infected with SARS-CoV-2. It also includes some markers of cell activation and inhibition, as well as cellular senescence. However, it does not identify Th17 cells, nor does it include intracellular cytokines of any kind, and therefore does not address the study of Treg / Th17 cell plasticity.

[0017] Based on this state of the art, to achieve a deep understanding of an individual's immune response to antigens and improve the efficiency of vaccination in the population, it is necessary to develop new immunophenotyping methods that allow us to address together: the quantification of the expansion / reduction of Th17 and regulatory T cells after antigen encounter and the production of cytokines in response to the antigen; the study of cellular plasticity; and the evaluation of the generation of antigen-specific memory Treg cells in the evolution of the immune response.

[0018] DETAILED DESCRIPTION OF THE INVENTION

[0019] In view of a need identified in the prior art, the present invention relates to a method for evaluating the differentiation and plasticity of immune subpopulations in response to antigens (vaccines, allergens, pathogens, or immunomodulators), as well as the generation of antigen-specific memory Treg cells during the evolution of the immune response. The method is based on the detection of specific markers of regulatory cells (CD4 Treg, CD8 Treg, and Breg) and effector T helper 17 (Th17) cells, preferably by spectral flow cytometry, and on the identification of cytokines produced after specific antigenic stimulation. This allows for the prediction of the evolution of the immune response toward an effector or suppressor response, and thus the success or potential risks associated with the application of certain vaccines or immunomodulatory therapies.The term “Treg” refers to regulatory T cells, while the term “Breg” refers to regulatory B cells.

[0020] Thus, in a first aspect, the invention relates to a method for generating an immunophenotypic and functional profile of a subject, where the method comprises detecting specific markers of regulatory cells (CD4 Treg, CD8 Treg and Breg), specific markers of T helper 17 cells (Th17), and specific markers of associated cytokines, where the markers comprise CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1 p, TGFp-1, FoxP3, IL-10, IL-2, and a marker for determining cell viability, or where the markers comprise CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1 p, TGFp-1, CD127, IL-10, IL-2, and a marker for determining cell viability.

[0021] This panel therefore allows the characterization of Th17 cells through two distinct phenotypes: by IL-17A expression after stimulation (CD4+ cells, IL-17A+) and by the extracellular markers CCR4 and CCR6 (CD4+, CCR4+, CCR6+). By including all markers, the panel allows for a more complete characterization of this population. Furthermore, there are two alternatives within the marker group of the panel of the present invention: in the first case, the panel evaluates FoxP3, while in the second case, the panel evaluates CD127. These variations allow for the alternative identification of regulatory T cells. In one case, regulatory T cells (CD4+, CD25) are identified. hi FoxP3+, where the superscript hi indicates high expression of the marker), and in the alternative case, regulatory T cells are identified (CD4+, CD25 hi , CD127 |OW(where the superscript "low" indicates low expression of the marker). In certain cases, the use of FoxP3 is preferable to CD127 because there is evidence that CD127 has reduced expression in activated cells (both in CD4+ cell subpopulations and in CD8+ cell subpopulations after cell activation), and therefore it should not be used in certain immunological contexts that include immune hyperactivation, such as in HIV-naive subjects or in autoimmune diseases such as rheumatoid arthritis. In the context of the invention, the expression "immunophenotypic and functional profile" refers to information on the types of immune cells that a person has in a biological sample at a given time and the relative percentages among these cell types, as well as the cytokine environment they express.This immunophenotypic and functional profile information in a subject changes over time, and it is possible to use this information from the immune system to monitor the person's health status and help diagnose infections, cancer, or other conditions more quickly, as well as autoimmune responses or atypical reactions to a vaccine stimulus.

[0022] It is important to understand that, in the time course of a normal immune response, there is an initial stage in which an effector response occurs. This effector response activates the immune system to combat the antigen (a vaccine, an allergen, a pathogen, or an immunomodulatory stimulus). The effector response is followed, in a second stage, by a suppressor response, which inhibits the immune response. This suppressor response prevents the immune system from being continuously activated. The balance between these two responses can be assessed, from a cellular perspective, by calculating ratios of cell concentrations characteristic of the effector response to those characteristic of the suppressor response. For example, the ratio of Th17 effector cells to regulatory cells can be evaluated.In individuals with alterations in the typical stages of the immune response, these ratios will be modified compared to individuals with a normal immune response. Both the effector and suppressor responses are further characterized by the production of specific cytokines, which are necessary to induce the cellular response in one direction or the other (i.e., toward an effector or a suppressor response). For example, the cytokines IL-2, IL-17A, IL-21, IL-1β, IL-6, TNF-α, and IFN-γ are pro-inflammatory cytokines that promote the effector response of the immune system, while the cytokines TGF-β1 and IL-10 are anti-inflammatory cytokines that contribute to the suppression of the immune response.

[0023] The combined detection of the markers of the invention allows for obtaining comprehensive information about the state of an individual's immune response to a stimulus. In this respect, the invention offers advantages over the separate detection of cellular (or phenotypic) markers and functional markers for determining whether an individual's response is effector or suppressor, since evaluating all the markers together allows for the observation of nuances in the types of response. That is, certain results may be insignificant for the cellular response but significant for the functional response, or vice versa (results significant for the cellular response but not significant for the functional response). In this way, the method of the invention allows for the observation of different stages of the response and the making of reliable predictions about when one type of response or another has already occurred or is about to occur.Thus, the joint evaluation of all markers allows for a more nuanced result. Therefore, in the method of the invention, it is always necessary to observe both cellular and functional markers. In any case, the application of the method(s) of the invention never results in contradictory outcomes, where the cellular response is of one type while the functional response is of the opposite type (i.e., effector-type response and suppressor-type response). By determining the immunophenotypic profile of a subject, the method of the invention allows for predicting the probability that the subject will respond to immunotherapy or a vaccine, such that alternatives can be considered for patients at risk of developing tolerance to immunotherapy or the vaccine (i.e., non-responders).

[0024] As an additional advantage, stemming from the simultaneous determination of cellular and functional markers, the method allows for savings in materials, particularly reagents, and in the amount of sample required. The savings in reagents offer a clear economic benefit, as these reagents are generally quite expensive. The reduction in sample quantity provides an operational advantage, as it simplifies patient care, particularly in cases where repeated sample collection is not always easy or feasible (e.g., pediatric patients).

[0025] In embodiments of this first aspect of the invention, the markers further comprise at least one additional marker selected from the group consisting of CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α. In one particular embodiment of the invention, the additional markers are CD24, CD38, and CD19. The incorporation of at least one, at least two, or all three markers CD24, CD38, and CD19 allows for the identification of B cells and / or regulatory B cells. These cells may be of particular significance in specific situations, such as lymphomas or in the response to specific types of vaccines, such as peptide vaccines, where antigen presentation occurs primarily through MHC class II. In one particular embodiment of the invention, the additional markers are IL-21, IFN-γ, and / or TNF-α. IL-21 analysis is relevant for the survival of Th17 cells.IFN-γ and / or TNF-α are of interest in the context of the invention, as they are quintessential effector cytokines. In a particular embodiment of the invention, the additional markers are CD24, CD38 and CD19, IL-21, IFN-γ, and TNF-α. Thus, in one embodiment within one of the alternatives of the first aspect, the invention defines a method for generating an immunophenotypic and functional profile of a subject, where the method comprises detecting specific markers of regulatory cells (CD4 Treg, CD8 Treg and Breg), specific markers of T helper 17 cells (Th17), and specific markers of associated cytokines, where the markers comprise CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, IL-21, TGFp-1, FoxP3, IL-10, IL-2, IFN-y, and TNF-a, and a marker for determining the viability of the cells in a biological sample of the subject.

[0026] In a second aspect, the invention relates to a method for predicting the evolution of an immune response in a subject towards an effector or suppressor response, wherein the method comprises: a) subjecting peripheral blood mononuclear cells (PBMCs) of the subject to specific antigenic stimulation, b) detecting specific markers of regulatory cells (CD4 Treg, CD8 Treg and Breg), specific markers of T helper 17 (Th17) cells, and specific markers of cytokines directed at determining cellular plasticity towards effector / suppressor cells, wherein the markers comprise CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1β, TGFβ-1, FoxP3, IL-10, and IL-2, or wherein the markers comprise CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, TGFp-1, CD127, IL-10, and IL-2, and where the markers further comprise a marker for determining cell viability,in the subject's PBMCs before and after specific antigenic stimulation, where,

[0027] - an increase in the ratio between Th17 cells and regulatory cells is indicative of an effector response in the subject, and where

[0028] - a decrease in the ratio between Th17 cells and regulatory cells is indicative of a suppressor response in the subject, and / or where

[0029] - an increase in at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-1p, IL-6, and / or a decrease in at least one anti-inflammatory cytokine selected from the group consisting of TGFp-1, IL-10 is indicative of an effector response in the subject, and where - a decrease in at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-1p, IL-6, and / or an increase in at least one anti-inflammatory cytokine selected from the group consisting of TGFp-1, IL-10 is indicative of a suppressor response in the subject.

[0030] The method of the invention requires the simultaneous determination of all markers, which allows for a thorough understanding of the subject's overall immune response and the prediction of its evolution. Unlike known methods in the prior art, the method of the invention not only quantifies the expansion / reduction of Th17 and regulatory T cells after antigen encounter and the production of cytokines in response to the antigen, but also allows for the evaluation of cellular plasticity through the incorporation of specific cytokines into the panel that enable the assessment of this phenomenon.

[0031] The cytokine environment generated after antigenic stimulation influences Th17 / Treg plasticity, that is, the ability of regulatory T cells and Th17 cells to change their phenotype and function according to the signals they receive from their environment. The concept of plasticity is very important, since, depending on the cytokines produced after antigenic stimulation, Treg and Th17 cells can reprogram themselves and differentiate into one another. These two cell subpopulations share the same TGF-β-mediated differentiation pathway from naive cells. In the presence of IL-6, naive lymphocytes differentiate into Th17 cells, and differentiation into Treg cells is inhibited, thus promoting an effector-type response. In turn, the presence of IL-1 promotes the re-differentiation of Treg to Th17. On the other hand, in the presence of IL-2, the differentiation of naive cells to Treg and the reconversion of Th17 cells to Treg are favored, thus favoring a suppressor-type response.Therefore, the balance of cytokines present in the immune environment can determine the fate and function of Treg and Th17 cells. Simultaneous assessment of TGF-β, IL-6, IL-1, and IL-10 is essential for evaluating the complete immune response to a specific antigen.

[0032] Another difference from the prior art is that the method of the invention allows for the evaluation of the generation of antigen-specific memory Treg cells, characterized by the expression of CCR4 on their surface. These cells have a high suppressive capacity and a rapid response after antigen re-encounters, which would begin to suppress the immune response quickly, generating immunological tolerance. In one embodiment of the invention, the ratio between Th17 cells and regulatory cells is the ratio between Th17 cells determined according to the markers CD4+, CCR4+, CCR6+, and IL-17 secretion, and CD4 Treg cells determined according to the markers CD4+ and CD25. hi FoxP3+; or determined according to the CD4+, CD25 markers hi , CD127 |OWIn another embodiment of the invention, the ratio between Th17 cells and regulatory cells is the ratio between Th17 cells determined according to the markers CD4+, CCR4+, CCR6+ and IL-17 secretion and CD8 Treg cells determined according to the markers CD8+, CD25 hi FoxP3+; or determined according to the CD8+, CD25 markers hi , CD127 |OW In another alternative embodiment of the invention, the ratio between Th17 cells and regulatory cells is the ratio between Th17 cells determined according to the markers CD4+, CCR4+, CCR6+ and IL-17 secretion and CD4 Treg and CD8 Treg cells determined according to the markers CD4+, CD25 hi , FoxP3+ (or determined according to the CD4+, CD25 markers) hi , CD127 |OW ) for CD4 Treg and with the markers CD8+, CD25 hi , FoxP3+ (or with the CD8+, CD25 markers) hi , CD127 |OW ) for CD8 Treg.

[0033] In embodiments of the second aspect of the invention, step (b) of the method further comprises detecting at least one marker selected from the group consisting of CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α, where

[0034] - an increase in the ratio between Th17 cells and regulatory B cells is indicative of an effector response in the subject, and where

[0035] - a decrease in the ratio between Th17 cells and regulatory B cells is indicative of a suppressor response in the subject, and / or where

[0036] - an increase in at least one selected pro-inflammatory cytokine from the group consisting of IL-21, TNF-α, IFN-γ is indicative of an effector response in the subject, and where

[0037] - A decrease in at least one selected pro-inflammatory cytokine from the group consisting of IL-21, TNF-α, IFN-γ is indicative of a suppressive response in the subject.

[0038] In one embodiment of the invention, the ratio between Th17 cells and regulatory B cells is the ratio between Th17 cells determined according to the markers CD4+, CCR4+, CCR6+ and IL-17 secretion and Breg cells determined according to the markers CD19+, CD24 hiCD38+. In certain embodiments of this second aspect of the invention, the ratio between Th17 cells and regulatory cells can be replaced by alternative ratios such as the Th17 cell / Breg cell ratio, or even the T cell / Z (CD8Treg+CD4Treg+Breg) ratio, so that a reduction in any of the ratios can be determined if the regulatory cell subpopulations (Breg, CD4Treg, and / or CD8Treg) increase. Furthermore, when evaluating B cell subpopulations, it must be considered that increased IL10 production by Breg cells could indicate a deficient or even absent response. Thus, the methods of the invention allow for multiple different analyses (including different ratios) to be performed on the generated data. The relevance of the different ratios will depend on the clinical context and the stimuli being evaluated.

[0039] In view of the foregoing, in a preferred embodiment, the invention relates to a method for predicting the evolution of an immune response in a subject towards an effector or suppressor response, wherein the method comprises: a) subjecting peripheral blood mononuclear cells (PBMCs) of the subject to specific antigenic stimulation, b) detecting specific markers of regulatory cells (CD4 Treg, CD8 Treg and Breg), specific markers of T helper 17 (Th17) cells, and specific markers of cytokines aimed at determining cellular plasticity towards effector / suppressor cells, wherein the markers comprise CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1β, IL-21, TGF-β, FoxP3, IL-10, IL-2, IFN-γ, and TNF-α, and a marker for determining viability of the cells, in the subject's PBMCs, before and after specific antigenic stimulation, where

[0040] - an increase in the ratio between Th17 cells and regulatory cells is indicative of an effector response in the subject, and where

[0041] - a decrease in the ratio between Th17 cells and regulatory cells is indicative of a suppressor response in the subject, and / or where

[0042] - an increase in at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1, IL-6, TNF-α, IFN-γ and / or a decrease in at least one anti-inflammatory cytokine selected from the group consisting of TGFκP-1, IL-10 is indicative of an effector response in the subject, and where - a decrease in at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1κP, IL-6, TNF-α, IFN-γ and / or an increase in at least one anti-inflammatory cytokine selected from the group consisting of TGFκP-1, IL-10 is indicative of a suppressor response in the subject.

[0043] As is evident to anyone skilled in the art, in the context of the present invention, predicting an effector response does not necessarily mean that 100% of subjects will respond to, for example, immunotherapy or a vaccine stimulus. Thus, in embodiments of the invention, predicting an effector response may indicate that at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, or at least 99% of subjects will respond to, for example, immunotherapy or a vaccine stimulus. In other words, it determines the risk that the subject may or may not develop tolerance to the immunotherapy or vaccine stimulus, such that the immunotherapy or vaccine stimulus may be ineffective or even harmful.

[0044] In the present invention, the increase and / or decrease in the ratio between Th17 cells and regulatory cells is verified by comparing the ratio value obtained before and after subjecting the subject's peripheral blood mononuclear cells (PBMCs) to specific antigenic stimulation. The ratio value before specific antigenic stimulation is used as a reference value. Once this reference value is established, the Th17 cell-to-regulatory cell ratio can be compared to this reference value, and a level of "increased" or "decreased" can be assigned if differences are observed that could be considered statistically significant using methods known to those skilled in the art.In particular embodiments of the invention, an increase in the ratio value after specific antigenic stimulation above the reference value of at least 1.1 times, 1.5 times, 5 times, 10 times, 20 times, 30 times, 40 times, 50 times, 60 times, 70 times, 80 times, 90 times, 100 times, or even more compared to the reference value is considered an "increased" ratio. Conversely, a decrease in the ratio value after specific antigenic stimulation below the reference value of at least 0.9 times, 0.75 times, 0.2 times, 0.1 times, 0.05 times, 0.025 times, 0.01 times, 0.005 times, or even less compared to the reference value is considered a "decreased" expression level.

[0045] Similarly, the increase and / or decrease of at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1β, IL-6, TNF-α, IFN-γ and / or at least one anti-inflammatory cytokine selected from the group consisting of TGF-β1, IL-10 is assessed by comparing the values ​​of these cytokines obtained before and after subjecting the subject's peripheral blood mononuclear cells (PBMCs) to specific antigenic stimulation. The expression value of at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1β, IL-6, TNF-α, IFN-γ and / or at least one anti-inflammatory cytokine selected from the group consisting of TGF-β1, IL-10 before specific antigenic stimulation is used as a reference value.Once this reference value has been established, the expression value of at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1, IL-6, TNF-α, IFN-γ and / or at least one anti-inflammatory cytokine selected from the group consisting of TGFκ-1, IL-10 after specific antigenic stimulation can be compared with this reference value, and thus assign a level of "increased" or "decreased" if differences are observed that may be significant using statistical methods known to the expert in the field.In particular embodiments of the invention, an increase in the expression value of at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1p, IL-6, TNF-α, IFN-γ and / or of at least one anti-inflammatory cytokine selected from the group consisting of TGFκ-1, IL-10 following specific antigenic stimulation above the reference value by at least 1.1 times, 1.5 times, 5 times, 10 times, 20 times, 30 times, 40 times, 50 times, 60 times, 70 times, 80 times, 90 times, 100 times or even more compared to the reference value is considered a ratio with an "increased" value.On the other hand, a decrease in the expression value of at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-21, IL-1p, IL-6, TNF-α, IFN-γ and / or of at least one anti-inflammatory cytokine selected from the group consisting of TGFκ-1, IL-10 after specific antigenic stimulation below the reference value of at least 0.9 times, 0.75 times, 0.2 times, 0.1 times, 0.05 times, 0.025 times, 0.01 times, 0.005 times or even less compared to the reference value is considered a "decreased" expression level.

[0046] As used herein, an “effector response” relates to an inflammatory response of the body, primarily aimed at eliminating an infectious agent, allergen, or vaccine antigen. In the context of the invention, whether a subject is a “responder” is determined by titrating antibodies against the stimulus, or by any equally effective method known to a person skilled in the art. From the perspective of the method of the invention, a “responder” exhibits a predominantly effector response to a stimulus, where at least 50%, 60%, 70%, 80%, 90%, or 100% of the markers are indicative of an effector response. A “suppressor response,” on the other hand, relates to immunological tolerance and the control of the intensity and duration of inflammatory responses in the body.The suppressive response serves to prevent collateral damage that could result from excessive inflammation following an antigenic encounter. In the context of the invention, a subject is determined to be a “non-responder” by titrating antibodies against the stimulus, or by any equally effective method known to a person skilled in the art. From the perspective of the method of the invention, a “non-responder” exhibits a predominantly suppressive response to a stimulus, where at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or 100% of the markers are indicative of a suppressive response.

[0047] The expert in the field understands that the correspondence between a "responder" with an effector response and a "non-responder" with a suppressor response may not be 100% accurate, as indicated in the previous paragraph, due to the inherent temporal nature of the immune response, where an initial effector phase is followed by a subsequent suppressor phase. Therefore, the observed markers will depend, in part, on the point in time at which the analysis is performed.Thus, in “responder” subjects, evidence of a suppressive response can be observed if the analysis is performed in the later stages of the immune response, while in “non-responder” subjects with alterations in the normal temporal development of the immune response, a weak effector response can be detected in the early stages of the immune response, in combination with a cytokine environment already indicative of cellular differentiation toward lymphocytes typical of a suppressive response. In both cases, it is possible to compare the immunophenotypic and functional profile of the subject of interest, and in particular the Th17 / Treg ratio, with the immunophenotypic and functional profile of control subjects, which can be used as a reference value. As used in this document, the reference value refers to laboratory values ​​used as a benchmark against values ​​obtained by examining samples from the subjects of interest.The reference value can be an absolute value, a relative value, a value with an upper and / or lower limit, a range of values, an average value, a median value, or a baseline value. The reference value can be based on a value from an individual control subject or on a large number of control subject samples. For example, populations of subjects within a group of specific age ranges. Several factors must be considered when determining the reference value, such as the age, weight, sex, and general physical condition of the control subjects. In this way, comparing the immunophenotypic and functional profile of a subject of interest, and in particular the Th17 / Treg ratio, with the immunophenotypic and functional profile of the reference value can reveal significant alterations.

[0048] In the context of the present invention, the term “subject” or “patient” refers to a human being of any age or race. In a preferred embodiment, the subject is not receiving, or has not received, immunosuppressive treatment at the time of performing the method of the invention. In particular embodiments, the subject has not received a solid organ transplant at least one month, two months, three months, or six months prior to performing the method of the invention.

[0049] As used herein, "sample" or "biological sample" means biological material isolated from a subject. The biological sample may contain any biological material suitable for determining the markers CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, TGFp-1, FoxP3, IL-10, and IL-2, and at least one additional marker: CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α. Thus, in one embodiment, the biological sample may contain any biological material suitable for determining the markers CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, IL-21, TGFp-1, FoxP3, IL-10, IL-2, IFN-γ, and TNF-α. In the context of the invention, the sample is a sample containing immune cells.The sample can be isolated from any suitable biological tissue or fluid such as, for example, blood, preferably peripheral blood, more preferably peripheral blood mononuclear cells (PBMCs) isolated from peripheral blood.

[0050] The markers CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, IL-21, TGFp-1, FoxP3 (or CD127), IL-10, IL-2, IFN-γ, and TNF-α can be used, in the context of the present invention, to identify CD4 T lymphocytes, CD8 T lymphocytes, and B cells, thereby also allowing the identification of subpopulations with regulatory function (regulatory CD4 T cells, regulatory CD8 T cells, and regulatory B cells) and T helper 17 (Th17) cells. For a more detailed characterization of these subpopulations, the marker panel includes a selection of activation and differentiation markers, as well as chemokine receptors and both pro- and anti-inflammatory cytokines, as shown in Table 1.

[0051] Table 1. Main populations and identification of specific markers and cytokines

[0052] The superscript “h” means high intensity. The superscript “low” means low intensity.

[0053] In view of the identification of the subpopulations according to the markers of the invention, in particular embodiments the ratio between Th17 cells and regulatory cells is the Th17 / Treg CD4 ratio or the Th17 / Treg CD8 ratio.

[0054] The detection step of the methods of the invention can be carried out by flow cytometry. Thus, in particular embodiments, the detection step is performed by conventional flow cytometry or by spectral flow cytometry. In a preferred embodiment of the invention, the detection step is performed by spectral flow cytometry. In an alternative embodiment, the invention can be implemented by another complex cytometry technique, called CyTOF (time-of-flight cytometry), which allows for a wide combination of markers using a similar technology. The invention can be implemented by any suitable technique known to a person skilled in the art. Thus, single-cell RNA sequencing analysis could be used, although, being based on RNA expression, it would not reveal actual protein production. The same would apply to Cite-RNAseq.However, any single-cell massive sequencing approach would be less valid for phenotypic, and especially functional, screening, more expensive, and much more complex to perform and analyze than flow cytometry, particularly spectral flow cytometry. The markers of the present invention can be configured as a panel to generate an immunophenotypic and functional profile of a subject. Thus, in another aspect, the invention relates to an immunophenotyping panel comprising the markers CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1, TGFβ-1, FoxP3, IL-10, and IL-2. The panel further includes a marker for determining cell viability.In embodiments of the invention, the markers further comprise at least one additional marker selected from the group consisting of CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α. In one embodiment, the invention relates to an immunophenotyping panel comprising the markers CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-10, IL-21, TGFκB1, FoxP3, IL-10, IL-2, IFN-γ, and TNF-α.

[0055] The term “CD3,” also known as cluster of differentiation 3, refers to a T-cell protein and coreceptor complex involved in the activation of both cytotoxic T cells (naive CD8+ T cells) and helper T cells (naive CD4+ T cells). The CD3 complex is composed of four distinct chains. In mammals, the complex contains one CD3y chain, one CD35 chain, and two CD3E chains. In humans, the CD3y protein (T-cell surface glycoprotein CD3 gamma chain) has the reference number P09693 in the UniProt database, the CD35 protein (T-cell surface glycoprotein CD3 delta chain) has the reference number P04234 in the UniProt database, and the CD3E protein (T-cell surface glycoprotein CD3 epsilon chain) has the reference number P07766 in the UniProt database. The term “CD4”, also known as cluster of differentiation 4, refers to a glycoprotein that serves as a co-receptor for the T cell receptor (TCR).In humans, the CD4 protein (T-cell surface glycoprotein CD4) has the reference number P01730 in the UniProt database. The term “CD8,” also known as cluster of differentiation 8, refers to a transmembrane glycoprotein that serves as a coreceptor for the T-cell receptor (TCR). Functionally, CD8 forms a dimer consisting of a pair of CD8 chains. The most common form of CD8 is composed of a CD8-a chain and a CD8-0 chain. In humans, the CD8a protein (T-cell surface glycoprotein CD8 alpha chain) has the reference number P01732 in the UniProt database, and the CD8b protein (T-cell surface glycoprotein CD8 beta chain) has the reference number P10966 in the UniProt database. The term “CD24,” also known as cluster of differentiation 24, signal transducer CD24, or heat-stable antigen CD24 (HSA), is a cell adhesion molecule. In humans, the CD24 protein has the reference number P25063 in the UniProt database.The term “CD38,” also known as cluster of differentiation 38 or cyclic ribose ADP hydrolase, is a glycoprotein found on the surface of many immune cells. In humans, the CD38 protein has the reference number P28907 in the UniProt database. The term “CD19,” also known as cluster of differentiation 19, B-lymphocyte surface antigen B4, T-cell surface antigen Leu-12, and CVID3, is a transmembrane protein expressed on B cells. In humans, the CD19 protein has the reference number P15391 in the UniProt database. The term “CCR4,” CC chemokine receptor type 4, also known as “CD194,” cluster of differentiation 194, is a protein belonging to the G protein-coupled receptor family. In humans, the CCR4 protein has the reference number P51679 in the UniProt database.The term “CCR6,” CC chemokine receptor type 6, also known as “CD196,” cluster of differentiation 196, is a protein belonging to the G protein-coupled receptor family. In humans, the CCR6 protein has the reference number P51684 in the UniProt database. The term “CD25,” cluster of differentiation 25, also known as IL2RA, interleukin-2 receptor alpha chain, IDDM10, TCGFR, p55, or IMD41, is a protein involved in the assembly of the high-affinity interleukin-2 receptor, which consists of the alpha (IL2RA), beta (IL2RB), and gamma (IL2RG) chains. In humans, the CD25 protein has the reference number P01589 in the UniProt database. The term “IL-17A,” interleukin 17A, refers to a pro-inflammatory cytokine produced by activated T cells. In humans, the IL-17A protein has the reference number Q16552 in the UniProt database.The term “IL-6,” interleukin 6, also known as BSF2, HGF, HSF, IFNB2, IL-6, BSF-2, CDF, or IFN-beta-2, refers to a protein that can function as a pro-inflammatory cytokine or as an anti-inflammatory myokine. In humans, the IL-17A protein has the reference number P05231 in the UniProt database. The term “IL-1p,” interleukin 1 beta, also known as leukocyte pyrogen, leukocyte endogenous mediator, mononuclear cell factor, or lymphocyte-activating factor, refers to a cytokine that acts as a mediator of the inflammatory response. In humans, the IL-1 protein has the reference number P01584 in the UniProt database. The term “IL-21”, interleukin 21, also known as CVID11, IL-21, Za11, refers to a cytokine with a regulatory effect on cells of the immune system, and which induces proliferation in its target cells. In humans, the IL-21 protein has the reference number Q9HBE4 in the UniProt database.The term “TGF-β1,” transforming growth factor beta 1, or TGF-β1, is a protein belonging to the transforming growth factor beta superfamily of cytokines. In humans, the TGF-β1 protein has the reference number P01137 in the UniProt database. The term “FoxP3,” forkhead box protein P3, refers to a transcriptional regulator that is crucial for the development and inhibitory function of regulatory T cells (Tregs). In humans, the FoxP3 protein has the reference number Q9BZS1 in the UniProt database. The term “CD127,” cluster of differentiation 127, is also known as the alpha subunit of the interleukin-7 receptor, IL-7R alpha subunit, IL-7R-alpha, or IL-7RA. In humans, the CD127 protein has the reference number P16871 in the UniProt database.The term “IL-10,” interleukin-10, also known as cytokine synthesis inhibitory factor (CSIF), is a cytokine with anti-inflammatory properties capable of inhibiting the synthesis of pro-inflammatory cytokines by T lymphocytes and macrophages. In humans, the IL-10 protein has the reference number P22301 in the UniProt database. The term “IL-2,” interleukin-2, refers to a cytokine produced by activated CD4+ T helper cells, which acts as a T lymphocyte growth factor and activates B lymphocyte proliferation. In humans, the IL-2 protein has the reference number P60568 in the UniProt database. The term “IFN-γ,” interferon-gamma, also called immune interferon or type II interferon, refers to a type of cytokine produced by CD4+ T lymphocytes and natural killer (NK) cells. In humans, the IFN-y protein has the reference number P01579 in the UniProt database.The term “TNF-α”, tumor necrosis factor alpha, refers to a cytokine capable of stimulating the acute phase of the inflammatory response. In humans, the protein IFN-γ has the reference number P01375 in the UniProt database.

[0056] The panel also includes a marker for determining cell viability and / or cell death. Markers for determining cell viability and / or cell death are known to those skilled in the art. By way of example, suitable markers for determining cell viability in the methods of the present invention are Thermo Fisher's "LIVE / DEAD™" flow cytometry fixable viability dyes, such as "Live Dead Red," which is laser-excitable at a wavelength of 561 nm and has a peak emission at 615 nm.

[0057] In embodiments of the invention, each individual marker is uniquely associated with a fluorophore selected from the group consisting of:

[0058] - A laser-excitable fluorophore at a wavelength of 633nm and with a maximum emission at 810nm, such as APC Fire 810.

[0059] - A laser-excitable fluorophore at a wavelength of 488nm with a maximum emission at 540nm, such as Spark-Blue 550. A laser-excitable fluorophore at a wavelength of 405nm with a maximum emission at 786nm, such as BV786.

[0060] A laser-excitable fluorophore at a wavelength of 488nm and with a maximum emission at 515nm, such as BB515.

[0061] A laser-excitable fluorophore at a wavelength of 561 nm and with an emission maximum at 695 nm, such as PE Cy5.5.

[0062] A laser-excitable fluorophore at a wavelength of 488nm and with a maximum emission at 780nm, such as RB780.

[0063] A laser excitable fluorophore at a wavelength of 405nm and with a maximum emission at 510nm, such as BV510.

[0064] A laser-excitable fluorophore at a wavelength of 405nm and with a maximum emission at 711nm, such as BV711.

[0065] A laser-excitable fluorophore at a wavelength of 561 nm and with a maximum emission at 667 nm, such as PE-Cy5.

[0066] A laser-excitable fluorophore at a wavelength of 405nm and with a maximum emission at 603nm, such as BV605.

[0067] A laser-excitable fluorophore at a wavelength of 561 nm and with a maximum emission at 610 nm, such as PE-Dazzle 594.

[0068] A laser-excitable fluorophore at a wavelength of 633nm and with a maximum emission at 665nm, such as AF647.

[0069] A laser-excitable fluorophore at a wavelength of 633nm and with a maximum emission at 660nm, such as APC.

[0070] A laser excitable fluorophore at a wavelength of 633nm and with a maximum emission at 775nm, such as AF750.

[0071] A laser-excitable fluorophore at a wavelength of 561 nm and with a maximum emission at 578 nm, such as PE.

[0072] A laser-excitable fluorophore at a wavelength of 405nm and with a maximum emission at 450nm, such as eFluor450.

[0073] A laser-excitable fluorophore at a wavelength of 405nm and with an emission maximum at 421 nm, such as BV421.

[0074] A laser-excitable fluorophore at a wavelength of 488nm and with a maximum emission at 695nm, such as BB700.

[0075] A laser-excitable fluorophore at a wavelength of 405nm and with a maximum emission at 645nm, such as BV650. Thus, in the panel of the invention, each individual marker is associated with a single fluorophore according to the indicated excitation and emission spectra, in such a way as to minimize the overlap between the signal of the different fluorophores and allow the simultaneous detection of all markers.

[0076] In embodiments of the invention, each marker is uniquely associated with a fluorophore selected from the group consisting of APC Fire 810, Spark-Blue 550, BV786, BB515, PE Cy5.5, RB780, BV510, BV711, PE-Cy5, BV605, PE-Dazzle 594, AF647, APC, AF750, PE, eFluor450, BV421, BB700, and BV650. In a preferred embodiment of the invention, each marker is uniquely labeled with a specific fluorophore according to the following table:

[0077] In an alternative embodiment, where CD127 is evaluated instead of FoxP3, CD127 is labeled with the PE fluorophore. In a further aspect, the invention relates to an immunophenotyping kit comprising reagents for detecting the markers CD3, CD4, CD8, CCR4 (CD194), and CCR6.

[0078] (CD196), CD25, IL-17A, IL-6, IL-1 p, TGFp-1, FoxP3, IL-10, and IL-2, or comprising reagents aimed at detecting the markers CD3, CD4, CD8, CCR4 (CD194), CCR6

[0079] (CD196), CD25, IL-17A, IL-6, IL-1p, TGFp-1, CD127, IL-10, and IL-2, wherein the kit further comprises a reagent targeting a marker for determining cell viability and / or cell death. In certain embodiments, the kit further comprises reagents for detecting at least one additional marker selected from the group consisting of CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α. In one particular embodiment, the invention defines an immunophenotyping kit comprising reagents for detecting the markers CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, IL-21, TGFp-1, FoxP3, IL-10, IL-2, IFN-γ, and TNF-α. In one particular embodiment of the present invention, each marker corresponds to a single reagent for its detection. In the kit of the invention, each reagent for detecting its specific marker is linked to a unique and distinctive fluorophore.In one embodiment of the invention, each reagent targeting each marker is independently selected from the group consisting of an antibody, an antibody derivative, a lectin, an aptamer, and combinations thereof.

[0080] In one particular embodiment of the invention, the kit further comprises a marker-targeted reagent for determining cell viability and / or cell death. In one particular embodiment of the invention, each marker-targeted reagent is uniquely labeled with a fluorophore selected from the group consisting of APC Fire 810, Spark-Blue 550, BV786, BB515, PE Cy5.5, RB780, BV510, BV711, PE-Cy5, Live Dead Red, BV605, PE-Dazzle 594, AF647, APC, AF750, PE, eFluor450, BV421, BB700, and BV650.

[0081] In embodiments, reagents suitable for detecting the markers CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, IL-21, TGFp-1, FoxP3, IL-10, IL-2, IFN-γ, TNF-α, and viability comprise at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 55%, or at least 60%, at least 65%, at least 70%, at least 75%, or at least 80%, at least 85%, at least 90%, at least 95%, or at least 96%, at least 97%, at least the 98%, at least 99% of the total reagents present in the kit. In the context of the present invention, the term "kit" is to be interpreted as referring to a product or device comprising the various reagents necessary to carry out the method of the invention, packaged in a way that allows for their storage and transport.

[0082] All the terms and embodiments described above are applicable to any aspect and embodiment of the invention. According to the present invention, the singular term “the,” “a,” “one,” or “an” refers equally to its plural equivalent “the,” unless it is clear from the context that the term refers to a single species in the singular. The term “comprises” or “comprising,” as used herein, also describes “consisting of” or “consisting of” in accordance with generally accepted patent practice.

[0083] EXAMPLES

[0084] The following invention is described by means of the following examples, which should be interpreted as merely illustrative and not limiting to the scope of the invention.

[0085] The behavior of the immune response depends on a precise and delicate balance between immunity and suppression, which determines the development and persistence of immune responses against pathogens and vaccine antigens. Immunological alterations in this balance, described in elderly individuals and solid organ transplant recipients, could explain their difficulty responding to vaccine antigens. Th17 (inflammatory) cells and regulatory lymphocyte subpopulations (primarily CD4+ and CD8+ regulatory T cells, and regulatory B cells) play a fundamental role in this context.

[0086] Among these populations:

[0087] • Regulatory T lymphocytes (Treq) are a group of CD4 T lymphocytes that have a suppressor function; that is, they control the intensity and duration of pro-inflammatory responses aimed at eliminating the infectious agent to prevent the collateral damage that excessive inflammation could cause. To perform their function, they produce anti-inflammatory cytokines such as IL-10 and TGF-β, and require IL-2 for their stability and survival. Deficiencies in their generation and / or anti-inflammatory function are associated with various inflammatory and autoimmune diseases. • Th17 lymphocytes also constitute a subpopulation of CD4 T lymphocytes, but with a pro-inflammatory role directed at eliminating the infectious agent, and they primarily produce IL-17, IL-21, IL-22, and IL-23.IL-17 is involved in the recruitment of neutrophils and macrophages, which induces the production of pro-inflammatory cytokines by other cell types, such as IL-6, responsible for symptoms of systemic inflammation and fever, and TNF-α, which increases vascular permeability and infiltration. IL-22, along with IL-17 and TNF-α, induces antimicrobial peptides in mucous membranes and increases the expression of mucins, fibrinogen, and anti-apoptotic proteins, among others. Therefore, in addition to their pro-inflammatory and effector functions against pathogens, alterations in Th17 lymphocytes can also lead to autoimmune inflammatory diseases.

[0088] Because these two cell subpopulations share the same TGF-β-mediated differentiation pathway from naive cells, there is enormous plasticity between Th17 and Treg cells (Figure 1A). In the presence of IL-6, naive lymphocytes differentiate into Th17 cells, and differentiation into Treg cells is inhibited. In inflammatory environments and in the presence of IL-1β, Treg cells can redifferentiate into Th17 lymphocytes. Th17 cells, in turn, upon exposure to IL-12, can acquire a pathogenic phenotype that considerably increases systemic hyperinflammation. Thus, the cytokine environment generated after antigenic stimulation influences Th17 / Treg plasticity, that is, the ability of regulatory T cells and Th17 cells to change their phenotype and function according to the signals they receive from their environment. Therefore, the balance of cytokines present in the immune environment can determine the fate and function of Treg and Th17 cells, thus modulating the immune response.In the specific case of subjects who mount an immune response against pathogens and / or vaccine antigens (responders), the cytokine environment in the early stages of the immune response (e.g., approximately 18 hours after exposure to the stimulus) favors differentiation into Th17 cells, resulting in increased Th17 / CD4 and CD8 Treg ratios (Figure 1B). Conversely, in subjects who have difficulty responding to pathogens and / or vaccine antigens (non-responders), the cytokine environment in the early stages of the immune response (e.g., approximately 18 hours after exposure to the stimulus) favors differentiation into Treg cells. Therefore, although the Th17 / CD4 Treg ratio increases, it does not increase significantly, and the Th17 / CD8 Treg ratio does not increase (Figure 1C).

[0089] The balance between these subpopulations (Th17 / Treg) is therefore essential for maintaining immune homeostasis. This balance is vital in the outcome of inflammatory processes caused by infectious agents, which depends on the balance between immunity and tolerance. In the context of COVID-19 infection, the imbalance in the Th17 / Treg ratio is implicated in the hyperinflammation process that causes collateral damage and greater severity in at-risk populations. In the context of vaccination, in elderly subjects, who also exhibit Treg cell expansion, the vaccine response could be conditioned by which subpopulation expands more in response to the vaccine antigen and, therefore, by how the Th17 / Treg ratio is shifted. In transplant recipients and, therefore, immunosuppressed subjects, the Th17 / Treg ratio is reduced, mainly due to an increase in Treg cells.Therefore, the hypothesis of the present work is that the Th17 / Treg ratio could be involved in the vaccine response against COVID-19 in vulnerable populations that present alterations of this relationship, such as the elderly or kidney transplant recipients.

[0090] In view of this hypothesis, the present invention relates to the design of a panel and the development of a protocol for immunophenotyping analysis by spectral flow cytometry of PBMC samples, such that the method allows for the evaluation of the differentiation and plasticity of immune subpopulations in response to antigens (vaccines, allergens, pathogens, or immunomodulators). The method is based on the detection of specific markers of regulatory cells (CD4 Treg, CD8 Treg, and Breg) and T helper 17 (Th17) cells by spectral flow cytometry, and on the identification of cytokines produced after specific antigenic stimulation. This allows for the prediction of the evolution of the immune response toward an effector or suppressor response based on its plasticity, and thus the success or potential risks involved in the application of certain vaccines or immunomodulatory therapies.

[0091] To demonstrate the efficacy of the panel and the spectral flow cytometry immunophenotyping analysis protocol of PBMC samples with said panel, the present invention shows an analysis of the functional response of lymphocytes after the third dose of the vaccine, in kidney transplant patients, or after the fourth dose, in elderly subjects, in response to overlapping peptides of the SARS-CoV-2 virus S protein (vaccine antigen) in the presence or absence of thymosin-a1, by means of in vitro functional studies and spectral flow cytometry, to see how it affects the Th17 / Treg ratio, and other related parameters.

[0092] The use of thymosin-a1 is due to the fact that, in relation to vulnerable groups, higher levels of Tal in the elderly have been observed to increase the durability of the vaccine response, i.e., antibody titers (see Pozo-Balado, M. del M., et al., (2023). Higher plasma levels of thymosin-a1 are associated with a lower waning of humoral response after CO VID-19 vaccination: an eight-month follow-up study in a nursing home. Immunity & Ageing : I & A, 20(1), 9), while, in kidney transplant patients, plasma concentration of Tal and greater baseline thymic activity have been associated with a greater humoral response (see Bulnes-Ramos, Á., et al., (2023). Factors associated with the humoral response after three doses of COVID19 vaccination in kidney transplant recipients. Frontiers in Immunology, 14).

[0093] Flow cytometry is a technique that allows the rapid analysis of individual cells or particles as they pass through one or more lasers. Each particle undergoes analysis that evaluates its visible light scattering and one or more fluorescence parameters. It is highly efficient with applications in diverse disciplines, such as immunology, virology, molecular biology, cancer biology, and infectious disease surveillance. Spectral flow cytometry, unlike conventional flow cytometry, allows the complete emission spectrum of each fluorophore to be distinguished across all lasers, rather than identifying only the emission peak. Therefore, fluorophores with similar emission peaks but distinct spectral signatures can be included on the same panel, allowing for greater flexibility in panel design and the simultaneous detection of a larger number of fluorophores.Maximizing the amount of information that can be obtained from a single sample not only provides a deeper characterization, but also helps to address the problem of limited sample availability.

[0094] In the context of the invention, a Cytek Biosciences Aurora flow cytometer was used, equipped with four lasers (violet 405 nm, blue 488 nm, yellow-green 561 nm, and red 640 nm) and 48 detection channels for fluorescence. Data analysis was performed using version

[0095] 3.1 of SpectroFlow software (Cytek Biosciences).

[0096] 2.1 Panel Design

[0097] The panel for immunophenotyping analysis by spectral flow cytometry of PBMC samples must allow for the precise identification of study populations through specific markers. To design the panel, markers were selected that would allow for the identification of CD4+ T lymphocytes, CD8+ T lymphocytes, and B cells, and specific markers were included for the identification of subpopulations with regulatory function (regulatory CD4+ T cells, regulatory CD8+ T cells, and regulatory B cells) and T helper 17 (Th17) cells. For a more in-depth characterization of these subpopulations, a selection of activation and differentiation markers, as well as chemokine receptors and both pro- and anti-inflammatory cytokines, were included (Table 2).

[0098] Table 2. Main populations and identification of specific markers and cytokines

[0099] The superscript “h¡” means high intensity, that is, it is expressed with high intensity.

[0100] The markers to be included in the panel were therefore antigens expressed both extracellularly (9 markers: CD3, CD4, CD8, CD24, CD38, CD19, CCR4, CCR6, CD25) and intracellularly (7 pro-inflammatory cytokines: IL-1β, IL-2, IL-6, IL-17, IL-21, IFN-γ, and TNF-α; 2 anti-inflammatory cytokines: TGF-β and IL-10; and 1 transcription factor: FoxP3). A viability marker was also included for accurate marker identification. Thus, the final number of markers is 20, requiring 20 fluorophores to be assigned.

[0101] 2.2 Fluorochrome Assignment

[0102] The next step was to identify the best possible combination of fluorochromes for the 20 markers to be studied, applying the following criteria:

[0103] - Selecting fluorochromes with unique spectra: The spectra of more than 65 fluorochromes currently available on the market were analyzed, identifying both fluorochromes with emission peaks in different channels and those that, despite sharing the same emission peak, had a different spectrum. The uniqueness of the spectral signature of these fluorochromes was then determined by comparing the complete spectrum in the 48 detectors and quantified using the Similarity Index.

[0104] - Analyze the overall compatibility of the fluorochrome combination: For this evaluation, the Complexity Index is used, which measures the interference between a specific combination of fluorochromes and predicts the impact on the autofluorescence distribution of the spectrum.

[0105] These two indices together provide a measure of the degree of overall interference due to scattering between fluorochromes. Based on these criteria, 20 fluorochromes were selected (Figure 2), avoiding the inclusion of fluorochrome pairs with higher Similarity indices, and aiming for the lowest Complexity index (Figure 3). The Similarity index matrix measures the similarity between two spectra. A value of "1" indicates that there is practically no difference between two fluorochromes, while a value of "0" indicates that two fluorochromes are completely unique. The graph shows the numerical value for each pair of fluorochromes identified for use in the panel. Similarity indices < 0.98 indicate that the fluorochromes are sufficiently different to be used together if appropriate reference controls are employed.At the bottom of the matrix is ​​the complexity index (in blue), a metric for assessing the complexity of the entire fluorochrome combination. The lower the complexity index, the greater the likelihood that the fluorochrome combination will work well together and provide high-resolution data due to reduced dispersion.

[0106] Finally, the spillover or overlap of fluorescence emitted by the fluorochromes in secondary channels is evaluated by constructing a spillover spread matrix (Figure 4). The spillover matrix is ​​calculated for all fluorochromes in the panel. The spillover values ​​are color-coded as follows: white: <3, pink: 3–9, and red: >9. Low values ​​are preferred, as they indicate little cross-interference between channels. This is important for minimizing compensation error. The evaluation of similarity and complexity indices, and the construction of the spillover spread matrix (SSM), were performed using the website https: / / cytekbio.com / pages / cytek-cloud and the SpectroFlow software, developed by Cytek Biosciences.

[0107] The basic principles for panel design used for conventional flow cytometry were then followed. Antigens were classified as primary, secondary, and tertiary based on their expression level, and their co-expression was assessed by investigating the expression of each marker in the subsets of interest. Fluorochrome assignment was performed in the following order:

[0108] 1. Allocation of fluorochromes with limited availability: Fluorochromes with the lowest availability on the market were allocated first for different markers.

[0109] 2. Assignment of fluorochromes based on the classification of the antigen according to brightness and co-expression:

[0110] - To minimize dispersion, the faintest fluorochromes were assigned to primary antigens with high expression and / or a high level of co-expression with other markers.

[0111] - With the help of previously published information on clones and panel performance, the brightest fluorochromes were assigned to tertiary markers, trying as far as possible to choose fluorochromes whose signals were not severely affected by scattering from other fluorochromes.

[0112] - Finally, for the allocation of the remaining markers, mainly secondary antigen markers, the possible sources of dispersion that could affect the resolution were taken into account.

[0113] The design of the final theoretical panel with the distribution of the finally selected fluorochromes is summarized in Table 3.

[0114] Table 3. Antibody panel for staining and spectral cytometry

[0115] EE: Extracellular expression; EI: Intracellular expression; Detection channels: V: Violet;

[0116] B: Blue; YG: Yellow-Green; A: Network

[0117] 2.3 Panel Test

[0118] Once the theoretical design was completed, the panel test was carried out, with the preparation of the samples, antibody titration and selection of reference controls and spectral unmixing being key.

[0119] • Sample preparation for titration: Pools of peripheral blood mononuclear cells (PBMCs) from healthy volunteers, preserved to viability and collected specifically for this purpose, were used, given the high cell requirement for technique optimization. Titration optimization requires strict adherence to the same protocols, both initially for optimization and subsequently for sample treatment (stimulation and general staining). Antibody titration for markers whose expression does not change after stimulation was performed on unstimulated cells. Titration of cytokines and markers (both extracellular and intracellular) with variable expression after stimulation was performed on cells stimulated with PMA (phorbol-12-myristate-13-acetate)-ionomycin, which represents the condition of maximum stimulation.

[0120] • Antibody titration: Antibody titration is critical for optimizing spectral cytometry panels, as it allows for determining the optimal antibody concentration for each sample type while reducing the amount of antibody required. When the antibody concentration is not saturating, there is insufficient staining. However, when the concentration is super-saturating, it can lead to non-specific binding and poor resolution of the results. Therefore, using the optimal antibody concentration reduces background signal, allowing for accurate sample comparison (Figure 5). Five serial dilutions of each antibody (1 / 2 dilution) were performed individually, starting from the volume recommended by the vendor or from 1000 ng if the recommended concentration was given in pg / ml (Table 4).In addition to the single-stained (SS) samples with serial antibody dilutions, two unstained negative controls were used, one with stimulated cells and one with unstimulated cells.

[0121] • Stain Index. The Stain Index allows the identification of the optimal concentration of each antibody for specific sample types. To calculate it, the first step is to select the positive (stained) and negative (unstained) populations (by selecting lymphocytes and singlets). The Stain Index was calculated based on the following formula (Equation 1) using the Statistics tool of the SpectroFlow® software for all dilutions of each individual fluorochrome. (Equation 1)

[0122] (Equation 1): Formula for calculating the Stain Index. MFIpos: median of the positive fluorescence index; MFInegag: median of the negative fluorescence index; rSD: robust standard deviation.

[0123] In theory, the optimal antibody concentration is the one with the highest Stain Index. However, the final selected titer was not necessarily the optimal titer (Table 4).

[0124] Table 4. Antibody dilutions for titration and selected concentrations

[0125] The titration was performed on cells stimulated with markers that are internalized after stimulation. *Concentrations with a higher Stain Index **During panel tests, the antibody concentration was optimized, so the final concentration used does not always correspond to a higher Stain Index.

[0126] Finally, reference controls were prepared and the panel as a whole was evaluated to ensure the correct separation of the contribution of each fluorophore in a multicolor sample, by spectral unmixing:

[0127] • Reference controls: Reference controls correspond to single-stained (SS) samples for each antibody at their optimal concentration, using stimulated or unstimulated cells depending on the marker. To prepare the reference controls, as well as for the titration, pools of PBMCs from healthy volunteers were used, strictly following the same general stimulation and staining protocol described above. However, for markers with lower expression where the number of events using cells was insufficient, beads were used (FoxP3, CCR4, IL-11, IL-6, IL-21, TGF-β1, and IL-10). Unstained PBMCs (stimulated for SS samples with stimulation and unstimulated for SS samples without stimulation) or unstained beads were used as negative controls. For the viability marker, a mixture of stained and unstained dead cells (killed for 10 minutes at 65°C followed by ice shock) was used.

[0128] • Spectral unmixing: Full-spectrum flow cytometry allows the detection of even minute differences in fluorochrome emission, making the quality of reference controls and their ability to accurately represent their spectra in the multicolor stain critical. Once the optimal concentrations for each antibody are determined, the full emission spectrum of each SS sample can be used as a reference control to determine the contribution or signal of each fluorophore in a multicolor (MC) sample by unmixing. Unmixing was performed using SpectroFlow v3.1 software, which applies an ordinary least squares algorithm. To verify the accuracy of the MC tube unmixing, the data were cleaned (singlettes, live cells, scatter gate, and aggregate exclusion), and NxN plot permutations were selected.Although unmixing was very accurate for most markers, the concentration of some antibodies (viability, IFN-y, CD25 and CD38) had to be adjusted to minimize their dispersion in other channels (Table 3).

[0129] 2.4 Statistical analysis

[0130] Continuous variables are represented as medians and interquartile ranges, and categorical variables as numbers and percentages. Longitudinal comparisons between paired continuous variables were performed using the Wilcoxon signed-rank test, and for multiple variables, the Friedman test. Cross-sectional comparisons between groups were performed using the Mann-Whitney U test. Correlations between independent quantitative variables were explored using Spearman's rank correlation coefficient. A p-value <0.05 was considered statistically significant. Statistical analysis was performed using SPSS (version 26.0, Chicago, IL), and graphs were generated using Prism software (GraphPad Software version 8.4.2).

[0131] Example 3. Study of immunological response in vulnerable patients

[0132] The immunophenotyping panel of the present invention was used to conduct a longitudinal, collaborative, and multicenter study, framed within the FIS project (PI21 / 00357) “Study of the immune response in immunization against SARS-CoV-2 in two different scenarios: in infection and in vaccination.”

[0133] 3.1 Study design and participants

[0134] The inclusion of subjects began in January 2021, with the administration of the first doses of the COVID-19 vaccines, and they were followed over time, with samples collected before and after the administration of successive vaccine doses. This study investigates the immune response (both humoral and cellular) to the COVID-19 vaccine in vulnerable groups, specifically the response to the fourth dose in a cohort of elderly individuals (Caridad cohort) and the response to the third dose in a cohort of kidney transplant recipients (Renal Transplant cohort).

[0135] • Charity Cohort: Made up of 43 male residents of the Hospital Residencia Hogar de la Santa Caridad in Seville with samples available before and one month after receiving the fourth dose of the Pfizer-BioNTech vaccine (BNT162b2) who were not on immunosuppressive treatment at the time of inclusion.

[0136] • Renal Transplant Cohort: Made up of 54 kidney transplant recipients, who received the transplant at least six months before receiving the first dose of the Moderna vaccine (mRNA-1273), recruited in the transplant unit of the Nephrology Service of the Virgen del Rocío University Hospital, with samples available before and one month after receiving the third dose of the vaccine.

[0137] The main characteristics of the cohorts are detailed in Table 5.

[0138] Table 5. Demographic parameters, thymic activity and total antibody titers of each cohort before and after the fourth dose (Charity Cohort) and third dose (Transplant Cohort).

[0139] Medians and interquartile ranges are reported for continuous variables, while categorical variables are expressed as n and frequency (%). Antibody titers are expressed as 10g. Gains represent the log increase in total antibody titers after dosing compared to pre-dose levels (log post-titers / log pre-titers). *Only responders (>33.8 BAU / ml) are included in these variables. Longitudinal comparison of antibody titers was performed using the non-parametric Wilcoxon test, and p-values ​​< 0.05 were considered statistically significant (p < 0.001).

[0140] The study was approved by the Research Ethics Committee of the Virgen del Rocío and Virgen Macarena University Hospitals. All participants were informed and signed the consent form. All procedures in this study were conducted in accordance with the Declaration of Helsinki of the World Medical Association.

[0141] 3.2 Sampling and storage

[0142] The vaccination and blood sampling protocol for each cohort is detailed in Figure 6. Sample collection was performed 2–3 days prior to the fourth dose of the BNT162b2 vaccine in the Charity cohort and 7–10 days prior to the third dose of the mRNA-1237 vaccine in the Renal Transplant cohort. For both cohorts, post-vaccination samples were collected one month after administration.

[0143] Peripheral blood mononuclear cells (PBMCs) were isolated using density gradient centrifugation (Ficoll-Paque) in the case of kidney transplant patients, and from Vacutainer CPT® in the case of the Caridad cohort, in pre- and post-vaccination samples, and cryopreserved to viability in liquid nitrogen until use. Sera and plasma from both study points were separated and cryopreserved at -80°C. 3.3 Preliminary Quantifications

[0144] Prior to phenotyping analysis using the panel of the invention, the total antibodies against SARS-CoV-2 and the concentration of thymosin-a1 are quantified:

[0145] • Quantification of total antibody titers: Specific IgG antibodies against the trimeric conformation of the SARS-CoV-2 spike protein were quantified in serum samples (pre- and post-vaccination dose) by chemiluminescence (LIAISON SARS-CoV-2 TrimericS IgG, Diasorin SpA, Saluggia, Italy) using the DiaSorin LIAISON XL platform (DiaSorin, Stillwater, USA). Although the autoanalyzer calculates the antibody concentration in Arbitrary Units (AU), the result is automatically expressed in Arbitrary Binding Units (BAU / ml) (conversion factor AU / ml*2.6=BAU / ml), with titers >33.8 BAU / ml considered positive.

[0146] • Thymosin-α1 quantification: Thymosin-α1 was quantified in plasma samples (pre-vaccine dose) using the commercial Human Thymosin-α1 competitive ELISA kit (MyBiosuce®) following the manufacturer's instructions. The detection limit of the technique was 1 ng / ml. Absorbance was measured on a CLARIOstar® microplate reader (BMG labtech, Ortenberg, Germany) at 450 nm.

[0147] The results of the antibody titer and Tal level measurements are included in Table 5. All participants in the Candad Cohort responded to the fourth dose of the vaccine, showing a significant increase in total antibody titers (Figure 7A). However, although the increase in total antibodies was also significant (p<0.001) in the Renal Transplant Cohort (Figure 7B), 19 patients (35.2%) in this group still did not respond to the third dose of the vaccine.

[0148] Although all subjects in the Canada Cohort seroconverted after the first two doses (complete vaccination protocol for this population), and even after receiving the third dose, 58.1% contracted COVID-19 between the third and fourth doses of the vaccine. However, no significant differences were found between antibody titers of subjects who had recovered from the infection, either pre-dose (p=0.115) or post-dose (p=0.672), but there was a difference in antibody gain, with those previously infected obtaining higher titers (p=0.017).

[0149] On the other hand, post-vaccine total antibody titers correlated positively with pre-vaccine Tal levels, but only in the Renal Transplant Cohort (r=0.369, p=0.041), suggesting that it could have a potential positive effect on the vaccine response.

[0150] 3.2. Cellular immunophenotyping in the vaccine context

[0151] For this part of the study, cryopreserved PBMCs were used from 13 subjects from Caridad and 11 patients from the Transplant cohort, 6 responders (>33.8 BAU / rnl) and 5 non-responders (<33.8 BAU / rnl), and all of them without prior COVID-19 infection.

[0152] Cryopreserved PBMCs were thawed, washed, and resuspended in cold R10 medium (RPMI 1640 medium supplemented with 10% fetal bovine serum, 1.7 mM glutamine, 100 pL / mL streptomycin, and 100 U / mL penicillin (Thermo Fisher Scientific, USA)), to which 10 U / mL DNase I (Sigma-Aldrich, USA) had been added, and incubated for 1 hour in a standard incubator (37 °C, humidified, 5% CO2 atmosphere). After pretreatment with DNase I, the number of viable cells was counted (Trypan Blue), and the volume of R10 medium was adjusted to resuspend them at a final concentration of 5 x 10⁻⁵ 6PBMCs / ml. The PBMCs were seeded in 96-well U-bottom plates, at a concentration of 1 x 10 6PBMCs per well (200 pl) were left to rest in the incubator for 3 more hours. After the incubation time, the specific cellular response against the SARS-CoV-2 S protein and the effect of Tal on this response were studied, under three different stimulation conditions: i) 10 pg / mL of a pool of overlapping peptides of the SARS-CoV-2 Spike glycoprotein, consisting of a set of 15 amino acid sequences with 11 of them overlapping that covered the immunodominant sequence domains of the Spike glycoprotein of the classic Wuhan strain of SARS-CoV-2 (provided by the NIH), together with 1 pg / mL of the peptide sequences of the mutant regions of the micron vahant B1.1.529 and BA.5 (Pep Thvator® SARS-CoV-2 Prot S B.1.1.529 / BA.5 Mutation Pool, Miltenyi Biotec); i) 50 ng / mL of Tal (MyBioSource, USA) and iii) SARS-CoV-2 peptides and Tal at the concentrations indicated above.

[0153] The plates containing the specifically stimulated PBMCs were incubated for 18 hours in the incubator. In addition, for each study sample, a negative control without stimulation and a positive control consisting of PBMCs non-specifically stimulated with 20 ng / ml of phorbol-12-mihstatin 13-acetate (PMA) and 1 pg / ml of ionomycin (Sigma-Aldrich, USA) and incubated for 5 hours were performed. The last 5 hours of incubation of all wells, including the positive and negative controls, were carried out in the presence of 10 pg / ml of Brefeldin A (eBioscience), which inhibits vesicle transport in the endoplasmic reticulum and allows cytokine accumulation (Table 6). After the stimulation time had elapsed, they were transferred to 96-well V-bottom plates for phenotypic characterization by spectral flow cytometry.

[0154] Table 6. Stimulation conditions for PBMC cultures

[0155] 10 pg / ml of original S peptides + 1 pg / ml of mutant S peptides.

[0156] The PBMCs from the stimulation plate were transferred to 96-well V-bottom plates, washed with Stain Buffer (Ca- and Mg-free PBS and 2% fetal bovine serum), and stained extracellularly with the surface markers listed in Table 3 for 30 minutes in the dark. After two washes, they were fixed and permeabilized using the Foxp3 / Transcription Factor Staining Buffer Set (eBioscience™) according to the manufacturer's instructions. Once fixed and permeabilized, they were stained intracellularly using antibodies targeting both intracellular markers (cytokines and transcription factors) and those internalized during stimulation (CD3 and CD4). After two washes with Stain Buffer, the PBMCs were transferred to flow cytometry tubes and immediately acquired on a Cytek Aurora spectral cytometer.

[0157] Following panel optimization and acquisition of the study samples, a gating strategy was designed to allow for the precise identification of the subpopulations of interest, as detailed in Figures 8-10. These figures show a representation of the manual gating strategy for identifying the described subpopulations, where the arrows indicate the relationships between the different cell types. Once doublets and dead cells were excluded, lymphocytes were separated based on FSC-A / SSC-A properties. In Figures 8 and 9, CD4+ and CD8+ T lymphocytes were identified by CD3+ co-expression, and cytokine-producing cells were identified individually in both subpopulations (IL-17A, IL-6, IL-1β, IL-21, TGFκB-1, IL-10, IL-2, IFN-γ, and TNF-α).Treg cells were characterized by the co-expression of CD25 and FoxP3 from CD4+ T lymphocytes (CD4 Tregs) and CD8+ T lymphocytes (CD8 Tregs), and their functionality was determined by quantifying their IL-10 and / or TGF-β1 production capacity. Memory CD4 Treg cells were classified as memory / effector based on CCR4 / CCR6 expression. Th17 cell quantification was performed on CD4+ T lymphocytes based on both CCR4 and CCR6 co-expression (CD4+, CCR4+, CCR6+) and IL-17 production capacity (CD4+IL-17A+). In Figure 10, after the exclusion of doublets and dead cells, and the characterization of lymphocytes based on FSC-A / SSC-A, B cells (CD3-, CD19+) were identified, and their cytokine production capacity was analyzed individually.Breg cells were quantified from B cells by expressing CD24 and CD38 (CD3-, CD19+, CD24h1, CD38+), and their functionality was determined by expressing IL-10 and / or TGF-β1.

[0158] Example 4. Immunophenotyping results for the Charity Cohort

[0159] The main populations of CD4 and CD8 T lymphocytes and B lymphocytes were practically unaffected by the different study conditions. A significant increase in the percentage of CD4 cells was observed as a result of stimulation with the vaccine peptides (p=0.046) (Figure 11A). No difference was observed in CD8 T lymphocytes (data not shown). On the other hand, the combined effect of the peptides with the Tal significantly reduced the frequency of B lymphocytes (p=0.033) (Figure 11B).

[0160] Few differences were observed in the main cytokine-producing cell populations. Tal caused a significant decrease in the percentage of CD4 lymphocytes producing TNF-α (p=0.039) (Figure 12A) and IFN-γ (p=0.041) (Figure 12B). Peptides administered with Tal significantly decreased CD4 lymphocytes producing IL-21 (p=0.046) (Figure 12C), an inflammatory cytokine responsible for the differentiation and survival of Th17 cells, compared to peptides alone. Together, both stimuli also showed a tendency to increase the percentage of CD4 lymphocytes producing IL-6 (p=0.101) (Figure 12D) and CD8 lymphocytes producing IL-6 (p=0.039) (Figure 12E), also responsible for differentiation into Th17 cells.With the administration of the peptides alone, a tendency to increase the frequency of IL-6 producing CD8 lymphocytes was observed (p=0.087), which, in this case, could contribute to an environment that would favor differentiation to a Th17 effector response.

[0161] Regarding the different Treg subpopulations, peptides alone significantly reduced the total number of CD4 Tregs (p=0.042) (Figure 13), without significant changes in cytokine production.

[0162] Despite not producing differences in the frequency of CD8+ Tregs, cytokine production in this cell type was affected in such a way that the peptides reduced the percentage of CD8+ Tregs producing IL-10 + TGF-β (p=0.093) (Figure 9A) and TGF-β (p=0.017) (Figure 14B), which could translate into an increased effector response due to the lower inhibitory activity of IL-10 and TGF-β. Stimulation with Tal alone significantly decreased the frequency of IL-10-producing CD8+ Tregs (p=0.038) (Figure 14C), and Tal in conjunction with the peptides reduced the percentage of CD8+ Tregs producing IL-10 (p=0.018), TGF-β (p=0.050), and IL-10 + TGF-β (p=0.093). In summary, peptides primarily affect cytokine production by CD8 Tregs and, in conjunction with Tal, reduce their ability to produce IL-10, which is important because it is the main inhibitory cytokine.

[0163] The IL-17 / CD8 Treg ratio did increase significantly with peptide stimulation (p=0.012) and with peptide + Tal (p=0.010) (Figure 15), suggesting a greater effector response. However, Th17 lymphocytes did not show variations with respect to the different stimulation conditions (p=0.861).

[0164] Example 5. Immunophenotyping results for the Renal Transplant Cohort

[0165] The main cell populations showed no significant differences between subgroups (responder -R- and non-responder -NR-) or between different stimulation conditions.

[0166] Among the effector-type cytokines, we found that, in R patients, the peptides significantly reduced the frequency of IL-2 producing CD8 T lymphocytes (p=0.046) (Figure 16A), necessary for survival and differentiation to Treg, but increased IFN-y producing CD8 T lymphocytes (p=0.068) (Figure 16B). Regarding Tal, when administered with the peptides, it had a positive effect on the frequency of IFN-γ producing CD4 T lymphocytes (p=0.080) (Figure 16C) and IL-2 producing CD8 T lymphocytes (p=0.042) in NR, which could improve the effector response, and Tal alone significantly decreased the percentage of IL-2 producing CD8 T lymphocytes (p=0.043) in R patients. Even so, the sum of effector cytokines did not confirm that the peptides or Tal had a tendency to increase the overall effector response.

[0167] In R patients, peptides significantly increased the percentage of TGF-β producing CD4 T lymphocytes (p=0.046) (Figure 17A), and peptides + Tal reduced TGF-β producing CD8 T lymphocytes (p=0.046) (Figure 17B), TGF-β being necessary for the differentiation of naive cells into effector or suppressor responses. In NR patients, we observed a higher frequency of IL-10 producing CD8 T lymphocytes caused by peptides (p=0.043) and by peptides + Tal (p=0.043) (Figure 17C), which could have an unfavorable impact on the effector response. Furthermore, peptides + Tal tended to reduce IL-10 producing CD4 T lymphocytes (p=0.068) (Figure 17D).

[0168] Focusing on cytokines that promote differentiation toward a Th17 effector response, we find that, in the R group, peptides significantly increased the frequency of IL-1p producing CD4 T lymphocytes (p=0.018) (Figure 18A) and IL-6 producing CD4 T lymphocytes (p=0.028) (Figure 18B), as well as IL-6 producing CD8 T lymphocytes (p=0.028) (Figure 18C), but reduced IL-21 producing CD4 T lymphocytes (p=0.028) (Figure 18D). Peptides and Tal together promoted a greater expansion of IL-6 producing CD4 T lymphocytes (p=0.028) and IL-1p producing CD8 T lymphocytes (p=0.027) (Figure 18E) and IL-6 producing CD8 T lymphocytes (p=0.028). In the NR group, IL-6 producing CD4 T lymphocytes increased with peptides (p=0.080), and with peptides + IL-1 p producing CD4 T lymphocytes (p=0.080) and IL-6 producing CD4 T lymphocytes (p=0.080), and IL-6 producing CD8 T lymphocytes (p=0.080) tended to increase.

[0169] This cohort presented interesting results regarding Treg cells. The two study subgroups started with a similar frequency of CD4 Tregs (p=1.000) (Figure 19A), and the peptides produced a significant decrease in this subpopulation in the R patients (p=0.028) and showed a tendency to reduce them in the NR patients (p=0.080). Peptides + Tal also produced a significant reduction in the percentage of CD4 Tregs in the R patients (p=0.018). CD8 Tregs (Figure 19B) showed a similar dynamic in response to the peptides, which significantly decreased their frequency in both subgroups (p=0.043 and p=0.042), while peptides + Tal reduced their frequency in the NR patients, although to a lesser extent than the peptides alone.It is also interesting that the peptides significantly increased the percentage of memory Treg lymphocytes in the NR subgroup (p=0.043) (Figure 19C), thus expanding more suppressor-type memory through repeated dosing, which could further hinder response in those patients who did not respond to previous doses.

[0170] If we delve deeper into the cytokine-producing CD4 and CD8 Tregs, which showed the most differences, we find that, in the NR group, IL-10-producing CD8 Tregs expanded in the presence of the peptides (p=0.003) (Figure 20A). This would explain the lower effector response in the NR group, as it would be inhibited by IL-10. Meanwhile, the R group showed a significant increase in TGF-β-producing CD4 Tregs with the peptides (p=0.043) (Figure 20B). The peptides + Tal had opposing effects on IL-10-producing CD4 Tregs between the subgroups (Figure 20C); while in the NR group they tended to increase them (p=0.080), in the R group they significantly decreased them (p=0.046).

[0171] As in the other cohort, there were no significant differences in Th17 lymphocytes. However, with the peptides, a significant increase in the Th17 / CD4 Treg ratio was observed in both subgroups (p=0.028 and p=0.043) (Figure 21A), as well as in the Th17 / CD8 Treg ratio (p=0.048 and p=0.043) (Figure 21B), likely due to the previously described decrease in the percentage of CD4 and CD8 Tregs. No beneficial effect of Tal was observed because, although when administered together with the peptides it increased the Th17 / CD4 and CD8 Treg ratio in both R and NR groups, it did so to a lesser degree than the peptides alone. In summary, in this entire cohort, the administration of the vaccine peptides appears to promote a greater effector response.

[0172] BRIEF DESCRIPTION OF THE DRAWINGS

[0173] Figure 1 Representation of cellular plasticity between Th17 and Treg (A), where the predominant differentiation pathway is indicated in the case of responding subjects (B) versus non-responding subjects (C).

[0174] Figure 2 Spectral signature of the 20 selected fluorochromes visualized with Cytek

[0175] Spectral Viewer.

[0176] Figure 3: Similarity Index Matrix Results. A value of "1" indicates that there is virtually no difference between two fluorochromes, while a value of "0" indicates that two fluorochromes are completely unique. The complexity index is shown at the bottom of the matrix (in blue).

[0177] Figure 4 Spillover matrix calculated for all fluorochromes in the panel. The scattering values ​​are color-coded as follows: white: <3, pink: 3-9, and red: >9.

[0178] Figure 5 Representation of the relationship between antibody concentration and Stain

[0179] Index.

[0180] Figure 6: Study design including the vaccination schedule for each cohort and the collection of samples that have been used for the development of this work.

[0181] Figure 7 Longitudinal dynamics of total antibody titers in (A) Charity Cohort and (B) Renal Transplant Cohort. Antibody titers are expressed as Iog10.

[0182] Figure 8 Crawling strategy for CD4 T lymphocyte classification and cytokine production, as well as the identification of Th17 cells, CD4 Treg and functional capacity, and the identification of memory CD4 Treg based on CCR4 expression.

[0183] Figure 9 Crawling strategy for CD8 T lymphocyte classification and cytokine production, as well as the identification of CD8 Treg and their functional capacity.

[0184] Figure 10 Crawling strategy for identification of B lymphocytes and their cytokine production, as well as identification and functionality of Breg cells.

[0185] Figure 11: Percentages of the main cell populations under different stimulation conditions. (A) CD4 T lymphocytes (CD4+, CD3+) (B) B lymphocytes (CD19+) **p<0.05 Unst: No stimulation; P: peptides; Tal: thymosin-α1.

[0186] Percentages of the main cytokine-producing populations under different stimulation conditions. (A) TNF-α CD4 (CD3+, CD4+, TNF-α+) (B) IFN-γ CD4 (CD3+, CD4+, IFN-γ+) (C) IL-21 CD4 (CD3+, CD4+, IL-21+) (D) IL-6 CD4 (CD3+,

[0187] CD4+, IL-6+) (E) IL-6 CD8 (CD3+, CD8+, IL-6+) *p<0.15, **p<0.05, Unst: No stimulation;

[0188] P: peptides; Tal: thymosin-a1. Figure 13: Total CD4 Treg lymphocytes (CD4+, CD25+, FoxP3+) *p<0.100, **p<0.05, llnst: Without stimulation; P: peptides; Tal: thymosin-a1.

[0189] Figure 14: Percentages of cytokine-producing CD8 Treg populations under different stimulation conditions. (A) IL-10 + TGF-β CD8 Treg (CD8+, CD25+, FoxP3+, TGF-β+, IL-10+) (B) TGF-β CD8 Treg (CD8+, CD25+, FoxP3+, TGF-β+) (C) IL-10 CD8 Treg (CD8+, CD25+, FoxP3+, IL-10+), *p<0.100 **p<0.05, llnst: No stimulation; P: peptides; Tal: thymosin-α1

[0190] Figure 15: IL-17 / Treg CD8 ratio. IL-17 (CD4+, IL-17), Treg CD8 (CD8+, CD25+, FoxP3+) *p<0.100, **p<0.05, llnst: No stimulation; P: peptides; Such: thymosin-a1

[0191] Figure 16: Percentages of the main effector cytokine producing populations under different stimulation conditions. (A) IL-2 CD8 (CD3+, CD8+, IL-6+) (B) IFN-γ CD8 (CD3+, CD8+, IFN-γ+) (C) IFN-γ CD4 (CD3+, CD4+, IFN-γ+) *p<0.100 **p<0.05, R: responders; NR: non-responders; Unst: No stimulation; P: peptides; Tal: thymosin-α1; solid lines are for paired comparisons of R and dashed lines for paired comparisons of NR.

[0192] Figure 17: Percentages of the main anti-inflammatory cytokine-producing populations under different stimulation conditions. (A) TGF-p CD4 (CD3+, CD4+, TGF-+) (B) TGF-p CD8 (CD3+, CD8+, TGF-P+) (C) IL-10 CD8 (CD3+, CD8+, IL-10+) (D) IL-10 CD4 (CD3+, CD4+, IL-10+) *p<0.100 **p<0.05. R: responders, NR: non-responders; Unst: No stimulation; P: peptides; Tal: thymosin-α1; solid lines are for paired comparisons of R and dashed lines for paired comparisons of NR.

[0193] Figure 18: Percentages of main cytokine-producing populations in the different stimulation conditions. (A) I L-1 p CD4 (CD3+, CD4+, I L-1 p+) (B) IL-6 CD4 (CD3+, CD4+, IL-6+) (C) IL-6 CD8 (CD3+, CD8+, IL-6+) (D) IL-21 CD4 (CD3+, CD4+, IL- 21+) (E) IL-1 p CD8 (CD3+, CD8+, IL-1 P+) *p<0.100 **p<0.05, R: responders, NR: non-responders; Unst: No stimulation; P: peptides; Such: thymosin-a1; Solid lines represent paired comparisons of R and dashed lines represent paired comparisons of NR. Percentages of Treg subpopulations under different stimulation conditions. (A) CD4 Treg lymphocytes (CD4+, CD25+, FoxP3+) (B) CD8 Treg lymphocytes

[0194] (CD8+, CD25+, FoxP3+) (C) CD4 Memory Treg Lymphocytes (CD4+, CD25+, FoxP3+, CCR4+) *p<0.100 **p<0.05, R: responders, NR: non-responders; llnst: No stimulation; P: peptides; Tal : thymosin-a1 ; solid lines are for paired comparisons of R and dashed lines for paired comparisons of NR.

[0195] Percentages of cytokine-producing Treg populations under different stimulation conditions. (A) IL-10 CD8 Treg (CD8+, CD25+, FoxP3+, IL-10+) (B) TGF-β CD4 Treg (CD4+, CD25+, FoxP3+, TGF-β+) (C) IL-10 CD4 Treg (CD4+, CD25+, FoxP3+, IL-10+) *p<0.100 **p<0.05, R: responders, NR: non-responders; llnst: No stimulation; P: peptides; Tal: thymosin-α1; solid lines are for paired comparisons of R and dashed lines for paired comparisons of NR

[0196] Figure 21 Th17 / Treg CD4 relationships (A); Th17 (CD4+, IL-17+), Treg CD4 (CD4+, CD25+,

[0197] FoxP3+) (B) Th17 / Treg CD8; Th17 (CD4+, IL-17+), Treg CD8 (CD8+, CD25+, FoxP3+)

[0198] *p<0.100 **p<0.05, R: responders, NR: non-responders; llnst: No stimulation; P: peptides; Tal: thymosin-α1; solid lines are for paired comparisons of R and dashed lines are for paired comparisons of NR.

Claims

CLAIMS 1. A method for predicting the evolution of an immune response in a subject towards an effector or suppressor response, wherein the method comprises: a) subjecting peripheral blood mononuclear cells (PBMCs) of the subject to specific antigenic stimulation, b) detecting, in the subject's PBMCs before and after specific antigenic stimulation, specific markers of regulatory cells (CD4 Treg, CD8 Treg and Breg), specific markers of T helper 17 (Th17) cells, and specific markers of cytokines directed at determining cellular plasticity towards effector / suppressor cells, wherein the markers comprise CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1β, TGFβ-1, FoxP3, IL-10, and IL-2, or wherein the markers comprise CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1 p, TGFp-1, CD127, IL-10, and IL-2,and where the markers further comprise a marker for determining cell viability and at least one marker selected from the group consisting of CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α, c) comparing the ratio value between Th17 cells and regulatory cells before and after subjecting the subject's PBMCs to specific antigenic stimulation, where, - an increase in the ratio between Th17 cells and regulatory cells is indicative of an effector response in the subject, and where - a decrease in the ratio between Th17 cells and regulatory cells is indicative of a suppressive response in the subject, and (d) compare the value of specific cytokine markers before and after subjecting the subject's PBMCs to specific antigenic stimulation, where - an increase in at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-1 p, IL-6, IL-21, TNF-a, IFN-y and / or a decrease in at least one anti-inflammatory cytokine selected from the group consisting of TGFp-1, IL-10 is indicative of an effector response in the subject, and where - a decrease in at least one pro-inflammatory cytokine selected from the group consisting of IL-2, IL-17A, IL-1 p, IL-6, IL-21, TNF-α, IFN-γ and / or an increase in at least one anti-inflammatory cytokine selected from the group which consists of TGFp-1, IL-10 is indicative of a suppressor response in the subject.

2. The method according to claim 1, wherein the ratio of Th17 cells to regulatory cells used in step (c) is: the ratio of Th17 cells to CD4 Treg cells; or the ratio of Th17 cells to CD8 Treg cells; or the ratio of Th17 cells to Breg cells; or the ratio of Th17 cells to the sum of CD4 Treg and CD8 Treg cells; or the ratio of Th17 cells to the sum of CD8 Treg, CD4 Treg, and Breg cells; wherein the Th17 cells are determined according to the markers CD4+, CCR4+, CCR6+, and IL-17 secretion; wherein the CD4 Treg cells are determined according to the markers CD4+, CD25 hi , FoxP3+ or according to the CD4+, CD25 markers hi , CD127 |OW ; where CD8 Treg cells are determined according to the CD8+, CD25 markers hi , FoxP3+ or according to the CD8+, CD25 markers hi , CD127 |OW; and where Breg cells are determined according to the CD19+, CD24 markers hi , CD38+.

3. The method according to any of claim 1 or 2, wherein step b) comprises detecting in the subject's PBMCs, before and after specific antigenic stimulation, specific regulatory cell markers (CD4 Treg, CD8 Treg and Breg), specific T helper 17 (Th17) cell markers, and specific cytokine markers directed at determining cell plasticity towards effector / suppressor cells, wherein the markers comprise CD3, CD4, CD8, CD24, CD38, CD19, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, IL-21, TGFp-1, FoxP3, IL-10, IL-2, IFN-y, and TNF-a, and a marker for determining cell viability.

4. The method according to any one of claims 1 to 3, further comprising a step of identifying CD4 Treg memory cells comprising evaluating CCR4 expression.

5. The method according to any one of claims 1 to 4, wherein the detection step (b) is performed by spectral flow cytometry.

6. An immunophenotyping kit comprising reagents for detecting the markers CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, TGFp-1, FoxP3, IL-10, and IL-2, or comprising reagents for detecting the markers CD3, CD4, CD8, CCR4 (CD194), CCR6 (CD196), CD25, IL-17A, IL-6, IL-1p, TGFp-1, CD127, IL-10, and IL-2, wherein the kit further comprises: a reagent for detecting a marker for determining cell viability and / or cell death, and reagents for detecting at least one additional marker selected from the group consisting of CD24, CD38, CD19, IL-21, IFN-γ, and TNF-α.

7. The kit according to claim 6, wherein the marker-targeting reagents are selected from the group consisting of an antibody, an antibody derivative, a lectin, an aptamer, and combinations thereof.

8. The kit according to any one of claims 6 or 7, wherein each reagent directed to a marker is uniquely labeled with a fluorophore selected from the group consisting of APC Fire 810, Spark-Blue 550, BV786, BB515, PE Cy5.5, RB780, BV510, BV711, PE-Cy5, Live Dead Red, BV605, PE-Dazzle 594, AF647, APC, AF750, PE, eFluor450, BV421, BB700, and BV650.

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