Use of tigit inhibitors in the preparation of anti-tuberculosis drugs

Abstract

The application discloses application of a TIGIT inhibitor in preparation of an anti-tuberculosis drug, belongs to the technical field of biological medicines, and enhances the killing ability of NK cells to Mtb infected macrophages through a TIGIT blocking strategy, mainly through up-regulation of TRAIL and TNF-alpha expression, while protecting uninfected macrophages; reveals the influence of inhibiting TIGIT on NK cell immune synapse assembly and cell adhesion; enhances early effector-target cell binding, improves the killing efficiency of effector cells, and enhances the death of macrophages caused by Mtb infection of lymphocytes of TB patients, and after blocking TIGIT on the surface of NK cells, the killing ability of NK cells to macrophages infected by Mycobacterium tuberculosis can be significantly enhanced, and the macrophages uninfected by Mycobacterium tuberculosis are not affected, and blocking TIGIT can enhance the killing ability of immune cells in peripheral blood of tuberculosis patients to macrophages.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to the application of TIGIT inhibitors in the preparation of anti-tuberculosis drugs. Background Technology

[0002] Approximately one-quarter of the global population carries Mycobacterium tuberculosis (Mtb), of whom 5–10% of latent TB infections develop into active TB, while the majority control the infection through a robust cellular immune response. In this context, assessing immune checkpoints in peripheral blood immune cells of TB patients is crucial for developing personalized immunotherapies.

[0003] Immune cells in tuberculosis patients may experience exhaustion, characterized by decreased secretion of IFN-γ, TNF-α, and IL-2, accompanied by increased expression of immune checkpoints such as PD-1, LAG-3, and TIM-3. Although PD-1 checkpoint inhibitors have shown some efficacy in primates and tuberculosis patients, the effects are limited, and in vitro PD-1 blockade is insufficient to restore T cell function. Therefore, further investigation is needed into the involvement of other immune checkpoints in the pathogenesis of tuberculosis and immunotherapies targeting these checkpoints.

[0004] Natural killer (NK) cells are key effector cells in the innate immune response, accounting for 10-20% of lymphocytes in humans and mice, and playing a crucial role in tuberculosis. NK cell activity is regulated by both NK cell surface activation and inhibitory receptors, determining their phenotype. Immune checkpoint receptors themselves exert inhibitory functions; blocking these receptors can reactivate NK cell function.

[0005] TIGIT is an extensively studied immune checkpoint in tumors. Its main function on NK cells is to inhibit immune cell activity, participate in immunosuppression, and play a crucial role in tumor immune escape. Specifically, TIGIT downregulates NK cell function by binding to its main ligand, CD155, including inhibiting NK cell degranulation, cytokine production, and CD155 inhibition. + TIGIT exhibits cytotoxicity in tumor cells. However, little research has been conducted on its mechanism of action in tuberculosis. Summary of the Invention

[0006] Technical problems to be solved:

[0007] This application addresses the limitations of existing technologies, such as the limited efficacy of PD-1 checkpoint inhibitors, the insufficient ability of in vitro PD-1 blockade to restore T cell function, and the lack of research on the mechanism of action of TIGIT in tuberculosis. It provides the application of TIGIT inhibitors in the preparation of anti-tuberculosis drugs. By using immune checkpoint TIGIT inhibitors or neutralizing antibodies to inhibit TIGIT on the surface of NK cells, the ability of NK cells to kill macrophages infected with Mycobacterium tuberculosis can be enhanced, while having no effect on macrophages not infected with Mycobacterium tuberculosis.

[0008] Technical solution:

[0009] To achieve the above objectives, this application provides the following technical solution:

[0010] Application of TIGIT inhibitors in the preparation of anti-tuberculosis drugs.

[0011] Furthermore, the anti-tuberculosis drug is either an injectable or non-injectable formulation.

[0012] Furthermore, the anti-tuberculosis drug is an injection, tablet, capsule, powder, pill, granule, solution, suspension, syrup, suppository, or inhaler.

[0013] Furthermore, the anti-tuberculosis drug includes a TIGIT inhibitor and pharmaceutically acceptable excipients.

[0014] Furthermore, the excipients include one or more of the following: diluents, excipients, fillers, binders, wetting agents, disintegrants, absorption promoters, surfactants, adsorbent carriers, and lubricants.

[0015] Beneficial effects:

[0016] This application provides the application of TIGIT inhibitors in the preparation of anti-tuberculosis drugs, which has the following advantages compared with the prior art:

[0017] 1. Improve the efficiency of NK cell immune response against Mycobacterium tuberculosis (Mtb) in tuberculosis patients, especially the enhanced immune cell function regulated by TIGIT expression level and the improved clearance ability of Mtb-infected macrophages;

[0018] 2. This invention aims to enhance the killing ability of NK cells against Mtb-infected macrophages through a TIGIT blocking strategy, mainly by upregulating TRAIL and TNF-α expression while protecting uninfected macrophages; revealing the effects of inhibiting TIGIT on NK cell immune synaptic assembly and cell adhesion; enhancing early effector-target cell binding and improving effector cell-mediated killing efficiency; and enhancing the response of lymphocytes from TB patients to Mtb-induced macrophage death.

[0019] 3. Using immune checkpoint TIGIT inhibitors or neutralizing antibodies to inhibit TIGIT on the surface of NK cells can enhance the ability of NK cells to kill macrophages infected with Mycobacterium tuberculosis, while having no effect on macrophages not infected with Mycobacterium tuberculosis. These strategies aim to improve the treatment effect of tuberculosis patients and enhance the body's immune defense against Mtb.

[0020] 4. Blocking TIGIT on the surface of NK cells can significantly enhance the ability of NK cells to kill macrophages infected with Mycobacterium tuberculosis; it has no effect on macrophages not infected with Mycobacterium tuberculosis; blocking TIGIT can enhance the ability of immune cells in the peripheral blood of tuberculosis patients to kill macrophages. Attached Figure Description

[0021] Figure 1 This is a graph showing TIGIT expression in peripheral blood cells of tuberculosis patients and healthy controls in this application; where A represents the result of flow cytometry showing CD56. dim CD16 + TIGIT in subgroup lo and TIGIT hi Cell proportion diagram; B represents the statistical results of flow cytometry CD56. dim CD16 + TIGIT in subgroup lo and TIGIT hi Cell proportions; C represents the CD56 content of human peripheral blood mononuclear cells analyzed by flow cytometry 24 hours after infection with Mtb(H37RvΔleuD). dim CD16 + TIGIT in subgroup hi and TIGIT lo Percentage of cells; D represents the flow cytometry results of human peripheral blood mononuclear cells 24 hours after infection with Mtb(H37RvΔleuD) to determine CD56 content. dim CD16 + TIGIT in subgroup hi and TIGIT lo Percentage chart of cells;

[0022] Figure 2 TIGIT in tuberculosis patients in this application hi and TIGIT lo Expression analysis of CD2, CD11a, NKG2A, NKG2D, CD107a, and IFN-γ in subpopulations, where A represents flow cytometry analysis showing TIGIT expression. hi and TIGIT lo Expression maps of CD2 and CD11a in subpopulations; B shows TIGIT expression as revealed by flow cytometry analysis. hi and TIGITlo Statistical graph of CD2 and CD11a expression in subpopulations; C represents flow cytometry analysis of TIGIT. hi and TIGIT lo Expression of NKG2A and NKG2D in subpopulations; D represents flow cytometry analysis of TIGIT. hi and TIGIT lo Statistical graphs of NKG2A and NKG2D expression in subpopulations; E represents flow cytometry analysis of TIGIT. hi and TIGIT lo Expression of CD107a and IFN-γ in subpopulations; F represents flow cytometry analysis of TIGIT. hi and TIGIT lo Statistical graph of CD107a and IFN-γ expression in subgroups;

[0023] Figure 3 This is a graph showing the effect of TIGIT inhibition on NK cell killing of THP-1 cells. In the graph, A is a schematic diagram of the experimental procedure; B is a graph showing the inhibition efficiency of TIGIT expression in NK cells using TIGIT neutralizing antibodies; C is a graph showing the percentage of NK-92 cells killing Mtb-infected macrophages analyzed by flow cytometry; and D is a statistical graph showing the percentage of NK-92 cells killing Mtb-infected macrophages analyzed by flow cytometry.

[0024] Figure 4 This is a graph showing the effect of TIGIT inhibition on NK cell clearance of intracellular bacteria. A shows the intracellular Mtb load in macrophages co-cultured with NK-92 cells analyzed by flow cytometry; B shows the statistical results of intracellular Mtb load in macrophages co-cultured with NK-92 cells analyzed by flow cytometry; C shows the intracellular bacterial survival rate of THP-1 cells assessed using a colony-forming unit (CFU) assay; D shows the statistical results of intracellular bacterial survival rate of THP-1 cells assessed using a colony-forming unit (CFU) assay; and E shows the ratio of macrophages with or without intracellular Mtb mediated by NK-92 cells.

[0025] Figure 5 This is a diagram illustrating the effect of this application on the release of cytokines and cytotoxic particles in a co-culture environment caused by TIGIT.

[0026] Figure 6 This application shows the inhibition of TIGIT's effect on the expression of the death ligand TRAIL in a co-culture environment; where A is a Western blot analysis of the expression of MPEG1 and TRAIL in Jurkat cells and NK-92 cells in a co-culture environment; and B is a Western blot analysis of the expression of MPEG1 and TRAIL in THP-1 cells in a co-culture environment.

[0027] Figure 7 This is a diagram showing the inhibition of TIGIT-induced cytotoxic particle release in a co-culture environment, where A is a flow cytometry analysis diagram and B is a quantitative result diagram.

[0028] Figure 8 This is a schematic diagram of the bioinformatics analysis and functional verification experimental process of this application;

[0029] Figure 9 This application is used to depict the pathways and related genes enriched in the turquoise module obtained from WGCNA analysis;

[0030] Figure 10 This application is used to depict the pathways and related genes enriched in the brown module obtained from WGCNA analysis.

[0031] Figure 11 This application presents a GO-GSEA analysis diagram showing the relationship between all genes and specific pathways;

[0032] Figure 12 This application presents a KEGG-GSEA analysis diagram showing the relationship between all genes and specific pathways;

[0033] Figure 13 This is a validation diagram showing the gene expression levels of differentially expressed genes CXCL8, CXCL1, CSF1R, and MEF2C identified in this application from enrichment analysis at specific time points after Mtb infection;

[0034] Figure 14 This is a graph showing the effect of TIGIT on the binding rate of NK-92 cells and THP-1 cells in this application. A is a schematic diagram of the experimental procedure; B is a graph showing the cell binding rate as a representative flow cytometry result; C is a quantitative statistical graph of cell binding rate from at least three independent experiments; and D is a graph showing the time-dependent killing rate of NK-92 cells against Mtb-infected macrophages.

[0035] Figure 15This application presents a graph illustrating the toxic effects of TIGIT on the surface of primary human NK cells on Mtb infection of THP-1 cells and intracellular bacteria. A represents a flow cytometry graph showing the mortality rate of macrophages co-cultured with primary human NK cells; B is a quantitative graph showing the macrophage mortality rate of macrophages co-cultured with primary human NK cells; C shows the percentage of intracellular Mtb in human NK cells analyzed by flow cytometry; D shows a statistical analysis of the percentage of intracellular Mtb in human NK cells; E shows the percentage of macrophages killed by human NK cells with or without intracellular Mtb; F shows macrophages as observed by flow cytometry after 24 hours of pretreatment with IgG or α-TIGIT by peripheral blood mononuclear cells (PBMCs) isolated from tuberculosis patients with Mtb infection; G shows the mortality rate of these macrophages after TIGIT inhibition as shown by flow cytometry analysis; and H shows a statistical analysis of the mortality rate of macrophages in peripheral blood of tuberculosis patients after TIGIT inhibition. Detailed Implementation

[0036] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, but this should not be construed as limiting the present invention. Any modifications or substitutions made to the methods, steps, or conditions of the present invention without departing from the spirit and substance of the invention are within the scope of the present invention. Experimental methods and reagents not specifically described in the embodiments are performed according to conventional conditions in the art.

[0037] Example 1

[0038] The application of TIGIT inhibitors in the preparation of anti-tuberculosis drugs is as follows:

[0039] 1. Peripheral blood mononuclear cells (PBMCs) were isolated from healthy donor blood using Ficoll density gradient centrifugation. The peripheral blood was transferred to a 15 ml centrifuge tube, Ficoll separation solution was added, and the mixture was centrifuged at 500 × g for 30 minutes. The PBMC layer was collected, washed with PBS, and centrifuged at 300 × g for 10 minutes. The PBMCs were resuspended in RPMI-1640 medium containing 10% fetal bovine serum (FBS), 1% penicillin-streptomycin, IL-2 10 ng / ml, and M-CSF 50 ng / ml.

[0040] 2. PBMCs were co-cultured with Mycobacterium tuberculosis (Mtb, H37Rv△leuD or H37Rv△leuD-mScarlet) at a 1:1 multiple of infection (MOI) for 24 hours, then treated with Brefeldin A (10 μg / ml) and Monensin (3 μM) for 4 hours. The cells were then stained with antibodies against CD2, CD3, CD4, CD8, CD16, CD56 and TIGIT. After live / dead cell identification using a FixableViability Stain 700, the cells were fixed / infiltrated. NK-92 cells were labeled with CFSE and then stained for intracellular CD107a, GZMA, GZMB, IFN-γ, PRF1, and TNFα (Thermofisher). Staining included Fc blocking, identification of live / dead cells using Fixed Viability Stain 700 (1:1000 dilution, 30 min, 4°C), and Cytofix / Cytoperm staining. TM The solution was subjected to fixation / osmosis treatment (30 minutes, room temperature), and data acquisition was performed at BD LSRFortessa. TM The analysis was performed using FlowJo software v10.

[0041] 3. NK-92 cytotoxicity activity assay:

[0042] First, THP-1 cells were labeled with CFSE (5 μM, 565082, BD Biosciences) and then induced to differentiate for 24 hours using PMA (10 ng / ml). After co-infection with Mycobacterium tuberculosis (Mtb, MOI = 1) for 4 hours, the adhered cells were co-cultured with NK-92 cells in a co-culture system using either IgG or the neutralizing antibody αTIGIT (effective cell to target cell ratio of 4:1) for 24 hours. After the co-culture phase, the cells were washed and then incubated with FVS-700 in a dark room for 30 minutes. After removing the FVS-700, the cells were transferred to tubes for analysis using a CytoFLEX S instrument.

[0043] 4. Western Blot experiment:

[0044] First, sample preparation was performed. After culturing and treating cells, NK-92 cells were collected and washed 2-3 times with pre-chilled PBS. The cells were then lysed on ice for 30 minutes with RIPA lysis buffer containing a protease-phosphatase inhibitor. After centrifugation, the supernatant was collected as the protein sample and aliquoted for storage at -80℃. Next, protein content was determined. A standard curve was prepared using the BCA or Bradford method. The sample was diluted and mixed with reagents. The absorbance was measured using a microplate reader, and the protein concentration was calculated. After adjusting the sample to the same concentration, SDS loading buffer was added, and the sample was boiled for denaturation. Then, SDS-polyacrylamide gel electrophoresis was performed. Separating and stacking gels were prepared according to the target protein molecular weight. 20 μg / well of protein was loaded, and pre-stained markers were added. Electrophoresis was performed at a constant voltage (80V-120V) until bromophenol blue reached the bottom of the gel. The protein was transferred from the gel to a PVDF membrane (350mA, 2h), blocked with 5% skim milk for 1 hour, and primary antibody (TRAIL 1:1000, 27064-1-AP, Proteintech; β-actin) was added. Incubate overnight at 4°C with 1:5000, 60008-1-Ig, proteintech) and wash with TBST. Add horseradish peroxidase (HRP)-labeled secondary antibody and incubate at room temperature for 1 hour. After washing again, add ECL developing solution and react for 30 seconds to 1 minute. Acquire signals using a chemiluminescence imaging system and analyze the band gray values ​​using ImageJ to calculate the relative expression levels of the target protein and the internal control.

[0045] 5. Quantitative reverse transcription polymerase chain reaction (qRT-PCR)

[0046] Differentiated THP-1 cells infected with Mtb and co-cultured with NK-92 cells were collected and used for RNA extraction using Trizol reagent (catalog number B511311, Sangon Biotech). Reverse transcription was performed using the HiScript III kit (R312, Vazyme). Procedures were followed according to the instructions included with each kit. qPCR analysis was performed on a StepOne / StepOnePlus real-time PCR system using SYBR-Green (Q711, Vazyme). Primers used are listed in the table below.

[0047]

[0048]

[0049] 6. Cell binding assay:

[0050] NK-92 cells were first labeled with CFSE (5 μM, 565082, BD Biosciences). THP-1 cells were labeled by stable transfection with the mCherry fluorescent plasmid (pLVX-CMV-mCherry-PGK-Puro). PMA-differentiated macrophages were infected with Mycobacterium tuberculosis (Mtb) and subsequently detached using a cell scraper to obtain a single-cell suspension. CFSE-labeled NK-92 cells and macrophages were mixed at a 2:1 effector-target cell ratio, with αTIGIT neutralizing antibody (250 ng / mL) or IgG added as a control to form effector-target cell conjugates. The NK-92-macrophage mixture was centrifuged at 1,000 rpm for 1 min and then incubated at 37°C at specific time points. After incubation, the cell mixture was gently resuspended and fixed with 2% formaldehyde. Samples were analyzed using flow cytometry, and the binding ratio was calculated as the proportion of FITC / mCherry double-positive events among CFSE-positive events.

[0051] 7. Isolation and culture of human natural killer (NK) cells and monocytes:

[0052] Human natural killer (NK) cells are derived from freshly prepared peripheral blood mononuclear cells (PBMCs) using EasySep. TM Human NK cell isolation kit (#17955, STEMCELL™) was used to isolate cells according to the manufacturer's instructions. The isolated NK cells were cultured in RPMI 1640 medium supplemented with 10 ng / mL interleukin-2 (IL-2), 10% heat-inactivated human AB serum, 10 mM HEPES buffer, 1% penicillin-streptomycin, 1% non-essential amino acids, sodium pyruvate, and L-glutamine. The medium was changed every 48 hours.

[0053] Human mononuclear cells were prepared from freshly prepared PBMCs using EasySep. TM Human monocyte isolation kit (#19359, STEMCELL™) was used to isolate cells according to the manufacturer's instructions. The isolated CD14+CD16- monocytes were cultured in intact RPMI 1640 medium (10% FBS and 1% penicillin-streptomycin). Monocytes were differentiated into macrophages by adding M-CSF (50 ng / ml). All primary cells were maintained in a humidified incubator at 37°C and 5% CO2, with the medium changed every 48–72 hours to ensure optimal cell growth and viability.

[0054] 8. NK cell-mediated macrophage killing in the peripheral blood of tuberculosis patients:

[0055] Peripheral blood mononuclear cells (PBMCs) were isolated from blood samples of patients diagnosed with pulmonary tuberculosis and cultured in RPMI-1640 containing 10% fetal bovine serum (FBS), 1% penicillin-streptomycin, IL-2 (10 ng / ml), and M-CSF (50 ng / ml). PBMCs were then pretreated with α-TIGIT (250 ng / mL) or IgG. Cells were collected 24 hours after infection with Mtb and stained with CD68-PE or FVS-700. The killing effect of Mtb-infected mononuclear macrophages was analyzed using flow cytometry.

[0056] 9. RNA sequencing and bioinformatics data analysis:

[0057] NK-92 cells were co-cultured with Mtb-infected THP-1 cells for 24 hours. CFSE-labeled NK-92 cells were sorted using flow cytometry. Total RNA was extracted using TRIzol (Invitrogen Life Technologies, USA). Transcriptome sequencing of the extracted total RNA was performed on an Illumina Novaseq 6000 platform by GeneDenovo Biotechnology Co. (Guangzhou, China). As a quality control measure, adapter sequences and low-quality raw reads were removed and converted into clean reads. After data processing, the clean reads were mapped to a reference genome using TopHat2 software. The mapped reads were annotated and further analyzed to identify detectable genes.

[0058] RNA sequencing expression matrices were used for gene set enrichment analysis (GSEA) using the clusterProfiler R package. Data sets were ranked by fold change and default settings were applied. Gene sets with adjusted p-values ​​<0.05 were considered significantly enriched, providing insights into relevant biological pathways and processes.

[0059] RNA-seq data were analyzed using the limmaR package to identify differentially expressed genes (DEGs) between groups. Genes with an adjusted p-value < 0.05 and a fold change (FC) value > |1.5| were considered DEGs.

[0060] Weighted Gene Co-expression Network (WGCNA) analysis was performed using the WGCNAR package to analyze gene relationships and classify them into multiple modules. Genes with high connectivity (>0.80) and significant phenotypic associations in different modules were defined as hub genes (p<0.05).

[0061] Following WGCNA analysis, the three significant modules (turquoise, brown, and green) were intersected with DEGs. The resulting genes were 892 in the turquoise module, 167 in the brown module, and 76 in the green module. KEGG and GO enrichment analyses were then performed on the genes in the turquoise and brown modules. Enrichment analysis was performed using the clusterProfiler R package to identify significantly enriched biological pathways and gene ontology terms. Gene sets with adjusted p-values ​​<0.05 were considered significantly enriched.

[0062] For visualization, the GOplot R package was used to display the most significantly enriched pathways in the turquoise and brown modules. These plots allow for a visual representation of the relationships between genes and their associated pathways. All plots, including chord plots, were created in R to clearly and comprehensively present the enrichment results.

[0063] 10. Statistical Analysis:

[0064] The normality of the data was assessed using the Shapiro-Wilk test. For two groups, the Student's t-test (for normally distributed data) or the Mann-Whitney U test (for unpaired samples and non-normal distribution) was used for between-group comparisons; for multiple groups, one-way ANOVA or the Kruskal-Wallis test (for unpaired samples and non-normal distribution) was used for between-group comparisons. p < 0.05 was considered significant.

[0065] The results are as follows Figure 1 The image shows the expression of TIGIT in peripheral blood cells of tuberculosis patients and healthy controls. Figure 1 China A and Figure 1 Flow cytometry results from the B-cell imaging panel showed CD56 dim CD16 + TIGIT in subgroup lo and TIGIT hi The proportion of cells. Figure 1 C and Figure 1 Flow cytometry analysis was performed on human peripheral blood mononuclear cells 24 hours after infection with Mtb(H37RvΔleuD). dim CD16 + TIGIT in subgroup hi and TIGIT lo Percentage of cells. Statistical analysis was performed to determine TIGIT. hi and TIGIT lo Percentage of cells. Statistical significance was determined using the unpaired Mann-Whitney U test, with p < 0.05 indicating significance.

[0066] Figure 2 TIGIT in tuberculosis patients in this application hi and TIGIT lo Expression analysis of CD2, CD11a, NKG2A, NKG2D, CD107a, and IFN-γ in subpopulations. Figure 2 China A and Figure 2 Flow cytometry analysis of the middle B-cell matrix showed TIGIT hi and TIGIT lo Expression of CD2 and CD11a in subgroups. Figure 2 C and Figure 2 TIGIT was analyzed by flow cytometry in a medium-sized image. hi and TIGIT lo Expression of NKG2A and NKG2D in subgroups. Figure 2 China E and Figure 2 TIGIT was analyzed by flow cytometry in the middle F-cell region. hi and TIGIT lo Expression of CD107a and IFN-γ in subgroups. Statistical significance was determined using an unpaired Mann-Whitney U test, with a p-value less than 0.05 indicating significance.

[0067] Figure 3 This is a graph showing the effect of TIGIT inhibition on NK cell killing of THP-1 cells, as described in this application. Figure 3 Figure A shows a schematic diagram of the experimental procedure. CFSE-labeled THP-1 cells differentiated from PMA were infected with Mtb(H37RvΔleuD)-mScarlet. These macrophages were co-cultured with NK-92 cells pretreated with IgG or αTIGIT for 24 hours. Cell viability was assessed using FVS-700 staining, and CFU assays were performed to quantify intracellular bacterial load. Figure 3 Figure B shows the inhibition efficiency of TIGIT expression in NK cells using a TIGIT neutralizing antibody. Figure 3 C and Figure 3 The figure shows the percentage of Mtb-infected macrophages killed by NK-92 cells, as analyzed by flow cytometry.

[0068] Figure 4 This is a graph showing the effect of TIGIT inhibition on NK cell clearance of intracellular bacteria, as described in this application. Figure 4 China A and Figure 4 The image shows the intracellular Mtb load in macrophages co-cultured with NK-92 cells, analyzed by flow cytometry. Figure 4 C and Figure 4 The D-test showed that CFU assays and quantitative analysis were used to assess the intracellular bacterial viability of THP-1 cells. Figure 4The graph in the middle represents the ratio of macrophages with or without intracellular Mtb mediated by NK-92 cells. Statistical analysis was performed using the unpaired Mann-Whitney U test. A p-value less than 0.05 was considered statistically significant. The effector cell to target cell (E:T) ratio was 4:1.

[0069] Figure 5 This diagram illustrates the effect of TIGIT inhibition on the release of cytokines and cytotoxic particles in a co-culture environment. In THP-1 and NK-92 cells infected with Mtb, inhibition of TIGIT led to altered mRNA expression of TNFα, GZMA, GZMB, TRAIL, and MPEG1.

[0070] Figure 6 This is a diagram illustrating the inhibition of TIGIT's influence on the expression of the dead ligand TRAIL in a co-culture environment; in which... Figure 6 China A and Figure 6 In Figure B, Western blot analysis was performed on the expression of MPEG1 and TRAIL in Jurkat cells, NK-92 cells A, and THP-1 cells B in a co-culture environment.

[0071] Figure 7 This is a graph showing the effect of TIGIT inhibition on the release of cytotoxic particles in a co-culture environment. In the graph, A is a flow cytometry analysis graph and B is a quantitative result graph, showing the changes in the expression of TNFα, CD107a, GZMA and GZMB proteins caused by TIGIT inhibition after co-culturing NK-92 cells and Mtb-infected THP-1 cells. Statistical analysis was performed using the unpaired Mann-Whitney U test. A p-value less than 0.05 indicates a statistically significant result (ratio of effector cells to target cells, E:T = 4:1).

[0072] Figure 8 This is a schematic diagram of the bioinformatics analysis and functional verification experimental workflow of this application. PMA-differentiated macrophages were infected with Mtb(H37RvΔleuD) and then co-cultured with NK-92 cells pretreated with IgG or αTIGIT for 24 hours. Viable NK-92 cells were sorted by flow cytometry according to FVS-700 staining. RNA was extracted from the sorted cells and RNA sequencing was performed.

[0073] Figure 9 This application is used to depict the pathways and related genes enriched in the turquoise module obtained from WGCNA analysis;

[0074] Figure 10 This application is used to depict the pathways and related genes enriched in the brown module obtained from WGCNA analysis.

[0075] Figure 11This application presents a GO-GSEA analysis diagram showing the relationship between all genes and specific pathways;

[0076] Figure 12 This application presents a KEGG-GSEA analysis diagram showing the relationship between all genes and specific pathways;

[0077] Figure 13 This is a validation graph showing the gene expression levels of differentially expressed genes CXCL8, CXCL1, CSF1R, and MEF2C identified in this application from enrichment analysis at specific time points after Mtb infection; statistical analysis was performed using the unpaired Mann-Whitney U test. A p-value less than 0.05 was considered statistically significant.

[0078] Figure 14 This is a graph showing the effect of TIGIT on the binding rate of NK-92 and THP-1 cells in this application. Figure 14 A diagram in the image shows the experimental procedure. THP-1 cells were stably transfected with a lentiviral plasmid carrying the mCherry tag and differentiated into macrophages using PMA. Four hours after macrophage infection with Mtb(H37RvΔleuD), they were separated using trypsin and then co-cultured with CFSE-labeled NK-92 cells for a specified time. NK-92 cells were pretreated with IgG or α-TIGIT. After co-culture, the cells were fixed with 2% formaldehyde and analyzed by flow cytometry for double-positive (FITC) results. + PE + The percentage of cells; Figure 14 Figure B shows a representative flow cytometry result of cell binding rate; Figure C shows a quantitative graph of cell binding rate from at least three independent experiments; Figure D shows a time-dependent killing rate of NK-92 cells against Mtb-infected macrophages. Statistical analysis was performed using an unpaired Mann-Whitney U test. A p-value less than 0.05 was considered statistically significant.

[0079] Figure 15 This diagram illustrates the toxic effects of TIGIT on the surface of primary human T / NK cells in this application on Mtb infection of THP-1 cells and intracellular bacteria. Figure 15 China A and Figure 15 In the middle, B represents the flow cytometry graph A showing the mortality rate of macrophages co-cultured with human primary NK cells, and B shows the quantitative macrophage mortality rate. Figure 15 C and Figure 15 The percentage of intracellular Mtb in human NK cells was statistically analyzed using the D-display method. Figure 15E shows the percentage of macrophages killed by human NK cells with or without intracellular Mtb; F shows the macrophage map displayed by flow cytometry 24 hours after peripheral blood mononuclear cells (PBMCs) isolated from tuberculosis patients were pretreated with IgG or αTIGIT and infected with Mtb. Figure 15 The graph in G shows the mortality rate of these macrophages after TIGIT inhibition, as analyzed by flow cytometry. Figure 15 Figure H shows the mortality rate of macrophages in peripheral blood of tuberculosis patients after TIGIT inhibition. Paired Wilcoxon signed-rank test was used for statistical analysis, and a p-value less than 0.05 was considered statistically significant. The effector cell to target cell (E:T) ratio was 4:1.

[0080] The embodiments selected in the above materials are for ease of understanding and not for limiting the process method. Those skilled in the art can easily modify the process flow or transfer it to other cases without inventive change. If these modifications also fall under the category of similar claims or similar technology of this invention, then the intent of this invention also includes these modifications.

Claims

1. Application of TIGIT inhibitors in the preparation of anti-tuberculosis drugs.

2. The application of the TIGIT inhibitor according to claim 1 in the preparation of anti-tuberculosis drugs, characterized in that: The anti-tuberculosis drug may be in injectable or non-injectable form.

3. The application of the TIGIT inhibitor according to claim 1 in the preparation of anti-tuberculosis drugs, characterized in that: The anti-tuberculosis drugs are in the form of injections, tablets, capsules, powders, pills, granules, solutions, suspensions, syrups, suppositories, or inhalers.

4. The application of the TIGIT inhibitor according to claim 1 in the preparation of anti-tuberculosis drugs, characterized in that: The anti-tuberculosis drug includes a TIGIT inhibitor and pharmaceutically acceptable excipients.

5. The application of the TIGIT inhibitor according to claim 4 in the preparation of anti-tuberculosis drugs, characterized in that: The excipients include one or more of the following: diluent, excipient, filler, binder, wetting agent, disintegrant, absorption promoter, surfactant, adsorbent carrier, and lubricant.

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