A recombinant construct, CAR-T cell and construction and application thereof

Abstract

The application relates to the fields of biotechnology and targeted therapy, and particularly relates to a recombinant construct, a CAR-T cell and construction and application thereof. The application verifies the role and mechanism of THEMIS in maintaining the long-term killing of tumor cells of CAR-T through experiments. The CAR-T cell overexpressing THEMIS is constructed, compared with a control group, the proliferation capacity and memory cell formation capacity of the THEMIS-7x19 CAR-T cell are enhanced after antigen stimulation, and the cytokines are in a controllable state, the cell apoptosis and exhaustion are reduced, and the long-term tumor killing capacity can be maintained more effectively. The in-vivo experiment also proves that the THEMIS-7x19 CAR-T cell has stronger anti-tumor effect compared with the control group in a lymphoma tumor-bearing mouse model, and the survival time of the mouse is significantly prolonged.

Description

A recombinant construct, CAR-T cells, their construction and application Technical Field

[0001] This invention relates to the fields of biotechnology and targeted therapy, specifically to a recombinant construct, CAR-T cells, and their construction and application. Background Technology

[0002] In recent years, with the emergence of CAR-T therapy, cancer treatment has entered a transformative period. Currently, numerous large-scale pivotal CAR-T clinical trials, such as ZUMA-1, JULIET, TRANSCEND, and ELIANA, have demonstrated the safety and efficacy of CAR-T cell products such as axicabtagene (axi-cel), tisagenlecleucel (tisa-cel), and lisocabtagene maraleucel (liso-cel) in treating patients with relapsed or refractory B-cell lymphomas, including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), mantle cell lymphoma (MCL), and primary mediastinal large B-cell lymphoma (PMBCL). Based on these advances, CAR-T cell therapy has been expanded to treat various hematologic malignancies, including acute lymphoblastic leukemia (ALL) and chronic lymphocytic leukemia (CLL), achieving varying degrees of progress. However, within one year of receiving CAR-T cell therapy, approximately 50% of LBCL patients, 20-30% of FL patients, and 40% of MCL patients experience disease progression or relapse. On the one hand, CAR-T resistance can be attributed to antigen escape, i.e., the emergence of antigen-negative tumor cells under the pressure selection of CAR-T therapy. On the other hand, relapse can occur even with antigen positivity, suggesting intrinsic factors of CAR-T cells such as T cell exhaustion. Although CAR-T cells can initially migrate to target cells and exhibit activity, continuous antigen stimulation coupled with an immunosuppressive microenvironment induces CAR-T cell dysfunction. Functionally exhausted CAR-T cells exhibit a gradual decline in cytokine production, proliferation, and tumor-killing ability, ultimately leading to disease relapse.

[0003] With the development of emerging technologies such as multi-omics and CRISPR / Cas9 gene editing, we have more means to analyze and understand the differences in gene expression profiles, epigenetic modifications, and metabolism among different efficacy groups of CAR-T cell products, identify key factors, and use gene editing and other technologies to improve the efficacy of CAR-T cells.

[0004] Therefore, further exploring the role and mechanism of CAR-T cells in killing tumor cells, and upgrading and modifying CAR-T cells to improve their ability to accurately identify and effectively eliminate cancer cells in the long term, is currently a hot topic in the industry. Summary of the Invention

[0005] The efficacy of chimeric antigen receptor T-cell (CAR-T) therapy for hematological malignancies is limited by factors such as the heterogeneity of the patient's own T cells and antigen escape. The rapid development of multi-omics technologies in recent years has enabled us to gain a more comprehensive understanding of the heterogeneity of CAR-T cell products among different patients. Previously, our team (CellDiscovery, www.nature.com / celldisc, Lei et al. Cell Discovery (2024) 10:5)

[0006] The study (https: / / doi.org / 10.1038 / s41421-023-00625-0) demonstrated that CD19-targeted CAR-T therapy (named 7×19CAR-T) carrying interleukin-7 (IL-7) and chemokine ligand 19 (CCL19) has good efficacy in treating large B-cell lymphoma, but relapse also occurs.

[0007] THEMIS is an important regulator of thymocyte positive selection. Previous studies have found that THEMIS expression is closely related to T cell development and differentiation. Literature reports that THEMIS knockout mice exhibit defects in T cell selection, leading to a reduction in the number of single-positive cells and mature peripheral T cells. THEMIS is expressed only in T cell lineages and belongs to a small, conserved gene family in vertebrate evolution. After cross-linking with TCRs, it is phosphorylated by lymphocyte-specific protein tyrosine kinase (LCK) and possibly ZAP70. Studies have also found that CARs with a 4-1BB co-stimulatory domain can induce the recruitment of the THEMIS-SHP1 complex, reduce CD3ζ phosphorylation, and to some extent decrease T cell activation, thereby reducing cytokine secretion. However, it remains unclear whether THEMIS participates in regulating key phenotypes of CAR-T cells, such as memory stem cell characteristics, exhaustive differentiation, and apoptosis, thus affecting long-term efficacy. Therefore, further research is necessary.

[0008] This study used single-cell omics and other technologies to analyze and compare the differences in subpopulation composition, gene expression patterns, and TCR phenotypes of four generations of CAR-T cell products in different efficacy groups after tumor stimulation. It identified a key CAR-T cell subpopulation with THEMIS as a marker gene that was significantly upregulated in the complete remission group, and experimentally verified the role and mechanism of THEMIS in maintaining the long-term killing of tumor cells by CAR-T cells.

[0009] The purpose of this invention is to provide a recombinant construct, CAR-T cells, and their construction and application, in order to solve the problems mentioned in the background art.

[0010] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0011] A recombinant construct encoding a fragment or variant of a chimeric antigen receptor capable of simultaneously expressing IL-7, CCL19, and THEMIS.

[0012] Preferably, the chimeric antigen receptor is an anti-CD19 chimeric antigen receptor.

[0013] Preferably, the nucleic acid sequence of the recombinant construct is as shown in SEQ ID NO.5, or a fragment thereof or a variant thereof.

[0014] Preferably, the recombinant construct encodes an amino acid sequence as shown in SEQ ID NO.6, or a fragment thereof, or a variant thereof.

[0015] A pharmaceutical composition comprising a recombinant construct as described in any one of the foregoing descriptions and at least one pharmaceutically acceptable carrier.

[0016] A CAR-T cell, comprising a recombinant construct as described in any of the foregoing descriptions.

[0017] Preferably, the CAR-T cells are autologous, allogeneic, or xenogeneic.

[0018] The use of any of the recombinant constructs or pharmaceutical compositions described in any one of the foregoing claims, or the CAR-T cells described in any one of the foregoing claims, in the preparation of a kit for the diagnosis / treatment of malignant tumors.

[0019] The use of any of the recombinant constructs or pharmaceutical compositions described in any one of the foregoing claims, or the CAR-T cells described in any one of the foregoing claims, in the preparation of a medicament for the diagnosis / treatment of malignant tumors.

[0020] Preferably, the malignant tumor is a hematologic malignancy.

[0021] The beneficial effects of this invention are: THEMIS-7×19CAR-T cells exhibit enhanced proliferation and memory cell formation capabilities after antigen stimulation, with cytokines remaining under control, and reduced apoptosis and cell exhaustion, thus maintaining a more effective long-term tumor-killing ability. In vivo experiments also demonstrate that THEMIS-7×19CAR-T cells have a stronger anti-tumor effect in lymphoma-bearing mouse models compared to the control group, significantly prolonging the survival time of mice. Attached Figure Description

[0022] Figure 1-1 Cell subpopulation clustering analysis and differential gene display: (A) UMAP plot showing 11 cell clusters and subpopulation names in 7×19 CAR-T cell infusion product; (B) Dot plot showing the expression levels of the top 10 differentially expressed genes in different cell subpopulations across different cell types;

[0023] Figure 1-2 Differences in T cell subset distribution among different efficacy groups: (A) UMAP plot and bar chart showing the distribution preferences of each cell subset in the 7×19 CAR-T cell infusion product; (B) Number distribution of different T cell subsets among different efficacy groups; (C) Ro / e analysis showing the distribution preferences of 10 T cell subsets among different efficacy groups; Figure 1-3 Functional characteristics of T cell subsets among CAR-T products in different clinical efficacy groups: (A) Heatmap showing cell functional characteristics among different efficacy groups; (B) Heatmap showing functional characteristics among different T cell subsets; (C) Heatmap showing cytokine expression patterns among different T cell subsets;

[0024] Figure 1-4 Transcription factor expression levels and transcriptional activity among different T cell subsets: (A) Heatmap showing transcription factor expression levels among different T cell subsets; (B) Heatmap showing transcription factor regulatory activity among different T cell subsets;

[0025] Figure 1-5 Gene module analysis and enrichment analysis: (A) Heatmap showing the results of hotspot gene module analysis; (B) GO enrichment analysis results of modules 1, 7, and 11;

[0026] Figure 1-6 Metabolic characteristics among different T cell subsets: (A) Heatmap showing metabolic pathways (left) and metabolite abundance (right) among different T cell subsets; (B) Dot plot showing metabolic pathway activity among different T cell subsets;

[0027] Figure 1-7 Interaction analysis between different T cell subsets and tumor cells (B cells): (A) Interaction strength between cell subsets in different treatment groups; (B) Differences in interaction pairs between tumor cells and each T cell subset in different treatment groups;

[0028] Figure 1-8 Analysis of TCR clonal diversity among different T cell subsets: (A) Pie chart showing the TCR clonal types and numbers in different treatment groups and different T cell subsets; (B) Heatmap and bar chart showing the number of shared TCR clonal types among different T cell subsets in different treatment groups.

[0029] Figure 1-9 Analysis of the differentiation trajectories of different T cell subsets: (A) Pseudo-time trajectory diagrams projected by different T cell subsets in two-dimensional space; Left: Pseudo-time trajectory diagram, displayed according to pseudo-time values; Middle: Distribution of 7 states on the pseudo-time trajectory diagram; Right: Trajectory distribution of different T cell subsets on the pseudo-time trajectory diagram; (B) Distribution of 7 states on the pseudo-time trajectory diagrams corresponding to different T cell subsets; (C) Heatmap of representative genes along the pseudo-time axis; (D) RNA rate analysis diagram indicating the differentiation direction of different T cell subsets;

[0030] Figure 1-10 Differences in surface protein expression among different T cell subsets: (A) Violin plot showing the expression levels of 14 surface proteins among different treatment groups and different T cell subsets; (B) Differences in surface protein expression related to memory and exhaustion phenotypes among different treatment groups.

[0031] Figure 2-1 Functional characteristics analysis of the CD8+T_THEMIS subpopulation: (A) Volcano plot showing the distribution of upregulated and downregulated genes; (B) Bar chart and bubble chart showing the GO and KEGG enrichment results of upregulated and downregulated genes;

[0032] Figure 2-2 Functional analysis of the CD8+T_THEMIS subpopulation at different differentiation stages: (A) Differential gene expression and functional enrichment results; (B) Heatmap and violin plot showing functional characteristics in the early and late stages of differentiation; (C) Heatmap showing transcription factor expression levels in the early and late stages of differentiation.

[0033] Figure 2-3 Prognostic-related genes identified in the CD8+T_THEMIS subset using public databases: (A) Expression of SOS1, THEMIS, PDE3B, CDK6, and BACH2 genes in CAR-T cell products from different efficacy groups; (B) CD8+T_THEMIS gene expression in CAR-T cell products from different efficacy groups. + Expression of SOS1, THEMIS, PDE3B, CDK6, and BACH2 genes in T cells. Figure 3-1 Changes in CAR proportion after THEMIS knockout: (A) Schematic diagram of 7×19 CAR structure; (B) Flow cytometry detection of 7×19 CAR cell transduction efficiency; (C) Detection of knockout efficiency at the transcriptional and translational levels; (D) Flow cytometry detection of changes in the proportion of CAR expression in T cells before and after THEMIS knockout.

[0034] Figure 3-2 Flow cytometry analysis of CD8 / CD4 ratio in 7×19 CAR-T cells after THEMIS knockout (A) and changes in ratio (B);

[0035] Figure 3-3 Proliferation capacity of 7×19 CAR-T cells after THEMIS knockout following antigen stimulation: (A) Proliferation of 7×19 CAR-T cells with or without tumor antigen stimulation (CFSE-labeled cells showed the strongest fluorescence intensity at 0h; as cells divided, the fluorescence intensity of daughter cells gradually decreased, so the faster the proliferation, the lower the fluorescence intensity and the more the peak shifted to the left); (B) Expansion curve of 7×19 CAR-T cells under tumor antigen stimulation.

[0036] Figure 3-4 Cytotoxicity assay and cytokine secretion levels based on luciferase: (A) Killing effect of 7×19 CAR-T cells on Jeko-1 and Raji cell lines before and after THEMIS knockout at effector-to-target ratios of 20:1, 10:1, 5:1, and 2.5:1; (B) Cytokine levels in the supernatant after killing tumor cells in the two groups at an effector-to-target ratio of 20:1, *P<0.05, **P<0.01, nsP>0.05;

[0037] Figure 3-5 Long-term tumor killing ability of 7×19 CAR-T cells before and after THEMIS knockout: (A) Comparison of long-term tumor killing ability of 7×19 CAR-T cells before and after THEMIS knockout when the effector-to-target ratio is 1:2; (B) Comparison of long-term tumor killing ability of 7×19 CAR-T cells before and after THEMIS knockout when the effector-to-target ratio is 1:1.

[0038] Figure 3-6 Flow cytometry analysis of changes in memory, exhaustion, and apoptosis phenotypes in 7×19 CAR-T cells before and after THEMIS knockout following antigen stimulation: (A) Flow cytometry results of the proportion of memory phenotypes in the two groups before and after knockout with or without antigen stimulation; (B) Flow cytometry results of the proportion of exhaustion-related phenotypes in the two groups before and after knockout following repeated antigen stimulation; (C) Flow cytometry results of the proportion of apoptosis in the two groups before and after knockout following repeated antigen stimulation; (D) Comparison of the differences in the proportions of memory, exhaustion, and apoptosis phenotypes in 7×19 CAR-T cells before and after THEMIS knockout following antigen stimulation. *P<0.05, **P<0.01, nsP>0.05;

[0039] Figure 3-7 Comparison of 7×19 CAR-T cytokine secretion levels before and after THEMIS knockout under repeated antigen stimulation: (A) Cytokine secretion levels in the two groups after the first and third antigen stimulation; (B) The degree of cytokine secretion attenuation in the two groups after repeated antigen stimulation, *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001, nsP>0.05.

[0040] Figure 4-1 Validation of THEMIS expression level: (A) Schematic diagram of THEMIS-7×19CAR structure; (B) Flow cytometry detection of transduction efficiency of 7×19CAR and THEMIS-7×19CAR cells; (C) Flow cytometry detection of intracellular THEMIS protein expression level in THEMIS-7×19CAR-T group and control group.

[0041] Figure 4-2 Flow cytometry analysis of the CD8 / CD4 ratio in THEMIS-7×19 CAR-T cells (A) and changes in the ratio (B);

[0042] Figure 4-3 Proliferation capacity of 7×19 CAR-T cells after antigen stimulation following THEMIS overexpression: (A) Proliferation of 7×19 CAR-T cells in the overexpression group and control group with or without tumor antigen stimulation (CFSE); (B) Expansion curves of 7×19 CAR-T cells in the overexpression group and control group under tumor antigen stimulation.

[0043] Figure 4-4 Tumor-killing ability of 7×19 CAR-T cells after THEMIS overexpression: (A) Killing effect of 7×19 CAR-T cells in the overexpression group and control group on Jeko-1 and Raji cell lines at effector-to-target ratios of 20:1, 10:1, 5:1 and 2.5:1; (B) RTCA analysis of the long-term tumor-killing ability of 7×19 CAR-T cells after THEMIS overexpression, * indicates P<0.05, ** indicates P<0.01, *** indicates P<0.001, **** indicates P<0.0001, ns indicates P>0.05;

[0044] Figure 4-5 Flow cytometry analysis of changes in memory, exhaustion, and apoptosis phenotypes in 7×19 CAR-T cells after antigen stimulation following THEMIS overexpression: (A) Proportion of memory phenotype in 7×19 CAR-T cells in the overexpression group and control group with or without antigen stimulation; (B) Proportion of exhaustion-related phenotypes in 7×19 CAR-T cells in the overexpression group and control group under repeated antigen stimulation; (C) Proportion of apoptosis in 7×19 CAR-T cells in the overexpression group and control group under repeated antigen stimulation; (D) Differences in the proportions of memory, exhaustion, and apoptosis phenotypes in 7×19 CAR-T cells in the overexpression group and control group after repeated antigen stimulation. * indicates P<0.05, ** indicates P<0.01, *** indicates P<0.001, **** indicates P<0.0001, ns indicates P>0.05.

[0045] Figure 4-6 7×19 CAR-T cytokine secretion levels after THEMIS overexpression under repeated antigen stimulation: (A) Cytokine secretion levels in the overexpression group and control group after the first and third antigen stimulation; (B) The degree of cytokine secretion attenuation in the overexpression group and control group after repeated antigen stimulation, * indicates P<0.05, ** indicates P<0.01, *** indicates P<0.001, **** indicates P<0.0001, ns indicates P>0.05;

[0046] Figure 4-7 In vivo antitumor effect of 7×19CAR-T cells after THEMIS overexpression: A. Animal experiment flowchart; B. Mouse fluorescence imaging (7×19CAR-T as negative control); C. Quantitative results of tumor fluorescence signal and comparison of fluorescence intensity between the two groups on day 26; D. Survival analysis, *P<0.05, **P<0.01.

[0047] Figure 5-1 Target plasmid map corresponding to 7×19CAR-T pLenti-EF1a-wPRE 9723 base pairs;

[0048] Figure 5-2 Map of the THMEIS target gene THMEIS_CDS1926 base pairs;

[0049] Figure 5-3 shows the final synthesized plasmid containing THEMIS: C2020HGHG0-2,T2A+THEMIS_CAR 11,703 base pairs.

[0050] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Table 1 Abbreviations

[0053]

[0054]

[0055]

[0056] Part 1: Single-cell sequencing reveals key factors maintaining the efficacy of fourth-generation CAR-T therapy for lymphoma.

[0057] Large B-cell lymphoma (LBCL) is an aggressive hematologic malignancy, accounting for nearly 30% of all non-Hodgkin's lymphoma (NHL) cases, with nototherwise specified (NOS) DLBCL being the most common. The latest World Health Organization classification categorizes high-grade B-cell lymphoma (with MYC and BCL2 and / or BCL6 rearrangements) or nototherwise specified high-grade B-cell lymphoma as LBCL. Although most LBCL patients can be cured with standard chemotherapy, nearly 40% are refractory or relapsed (R / R). Some R / R patients can be cured with second-line treatment, but approximately 10% to 15% develop primary resistance, and most eventually die from the disease.

[0058] CAR-T cell therapy is a cell therapy approach that targets tumor antigens by expressing antibody-based fusion proteins on the T cell membrane. Initially approved products include axi-cel, tisa-cel, and liso-cel. Updated results from the pivotal single-arm phase II trials ZUMA-1, JULIET, and TRANSFORM show promising efficacy in patients with refractory / relapsed LBCL. However, approximately 50% of LBCL patients experience disease progression or relapse within one year of receiving CAR-T cell therapy. The variability in CAR-T treatment outcomes among patients prompts researchers to continuously investigate the key factors leading to poor treatment outcomes or failures. Currently, the molecular mechanisms underlying acquired resistance to CAR-T cell therapy remain unclear. While the antigen loss theory can explain some relapses following CD19 CAR-T therapy due to CD19 seroconversion, the mechanisms of relapse in CD19-positive patients remain unknown.

[0059] Numerous studies have demonstrated that various T cell characteristics can significantly influence the efficacy of CAR-T cell therapy, particularly T cell exhaustion. To further explore the relationship between T cell characteristics and CAR-T cell efficacy, we used scRNA-seq, TCR sequencing, and CITE-seq technologies to investigate CAR-T cell infusion products from 10 R / R LBCL patients who had received four generations of CAR-T cell therapy, aiming to explore potential key factors in maintaining long-term treatment response in the infusion products. We found a highly enriched CD8+T_THEMIS cell subset in the cell products from CR patients. This subset exhibits good cell proliferation capacity, high expression of transcription factors related to memory stemness, and unique differentiation pathways and functional characteristics. Furthermore, validation using external databases revealed that THEMIS, as a key marker gene in this subset, is correlated with CAR-T cell therapy efficacy, providing sufficient evidence for our subsequent basic experimental validation.

[0060] 1. Experimental Materials

[0061] 1.1 Cell lines and samples

[0062] 1.1.1 Cell lines

[0063] Raji: Human Burkitt's lymphoma cell line, purchased from ATCC.

[0064] 1.1.2 Patient Samples

[0065] This study was approved by the Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine. All samples came from the Phase I and extended phase clinical trials previously conducted by our team to evaluate the safety and efficacy of 7×19 CAR-T cell therapy.

[0066] 1.2 Main Experimental Reagents

[0067] Table 2

[0068]

[0069]

[0070] 1.3 Main Instruments and Equipment

[0071] Table 3

[0072]

[0073] 2 Experimental Methods

[0074] 2.1 Cell Culture

[0075] Raji cells were cultured in 1640 complete medium, and the resuscitated CAR-T cell products were cultured in X-VIVO complete medium. The medium was prepared as follows:

[0076] 1) 1640 complete medium (1% penicillin and streptomycin + 10% FBS + 1640 medium);

[0077] 2) X-VIVO complete medium (1% penicillin and streptomycin + 10% Gibco serum + 1% HEPES + 1% sodium pyruvate + 1% glutamine + 1% non-essential amino acids + 300 IU / mL rhIL-2 + 5 ng / mL IL-7 + 5 ng / mL IL-15).

[0078] 2.2 Cell resuscitation

[0079] 1) Pre-warm the culture medium in a 37℃ water bath, and at the same time prepare 15mL centrifuge tubes and add 2-3mL of pre-warmed culture medium;

[0080] 2) Remove the cells to be revived from the -80℃ freezer or liquid nitrogen, and thaw the cells quickly in a 37℃ water bath (try to control the thawing time within 2 minutes);

[0081] 3) Carefully add the cells to the prepared pre-warmed culture medium, mix thoroughly, and centrifuge at 1500 rpm for 5 min;

[0082] 4) Carefully remove the supernatant, add an appropriate amount of pre-warmed culture medium according to the cell volume, mix thoroughly, and then transfer to a 6-well plate or a T25 cell culture flask.

[0083] 5) After observation under a microscope, place in a 37℃, 5% CO2 incubator for incubation.

[0084] 2.3 CAR-T cell product antigen stimulation

[0085] 1) Based on a 1:1 effectiveness-to-target ratio, take 1×10 6 Raji cells treated with mitomycin C were co-incubated with CAR-T cell products that had been revived and adjusted for cell state at 37°C in a 5% CO2 incubator.

[0086] 2) After 24 hours, the CAR ratio and cell viability of each CAR-T cell product were measured, and single-cell sequencing analysis was performed subsequently.

[0087] 2.4 Single-cell sequencing library construction

[0088] 1) Cell preparation: Dilute the cells to an appropriate concentration, generally 2-2.5 × 10⁻⁶. 5 cells / mL;

[0089] 2) Single-cell isolation and labeling: Cell suspension is injected into SCOPE-chip TM Microfluidic chips separate individual cells based on the principle of Poisson distribution. Cells fall into specially designed microwells of the chip under gravity, ensuring only one cell falls into each well. Millions of magnetic beads carrying unique cell barcodes are then added to the microwells, ensuring only one bead falls into each well. After cell lysis, the magnetic beads with unique molecular identifiers (UMIs) capture mRNA by binding to the poly(A) tail of the mRNA, thus labeling both the cell and the mRNA.

[0090] 3) Reverse transcription and amplification: Collect the magnetic beads in the chip and reverse transcribe the mRNA captured by the magnetic beads into cDNA.

[0091] And amplify;

[0092] 4) Single-cell sequencing library construction: After cDNA fragmentation, individual libraries were diluted to 4 nM and pooled for sequencing. Sequencing was performed on an Illumina Novaseq 6000 using 150 bp paired-end reads. Raw reads were processed using fastQC and fastp to remove low-quality reads. Poly(A) tails and adapter sequences were removed using cutadapt. After quality control, reads were mapped to the reference genome GRCh38 using STAR. Gene expression levels and UMI counts were statistically analyzed using the FeatureCounts function. An expression matrix file was generated based on gene expression levels and UMI counts for subsequent analysis.

[0093] 2.5 Quality Control, Dimensionality Reduction, and Clustering

[0094] 1) Before analysis, cells were filtered by UMI counts below 30,000 and gene counts between 200 and 5,000, and cells with mitochondrial content exceeding 20% ​​were removed.

[0095] 2) After filtering, functions in Seurat (v2.3) were used for dimensionality reduction and clustering. Then, the NormalizeData and ScaleData functions were used to normalize and scale all gene expressions, and the FindVariableFeautres function was used to select the top 2000 highly variable genes for PCA analysis. For the top 20 principal components, FindClusters was used to divide them into multiple clusters. Batch effects between samples were removed using the Harnomy algorithm.

[0096] 3) Perform uniform manifold approximation and projection (UMAP) dimensionality reduction analysis for visualization.

[0097] 2.6 Differentially expressed genes (DEGs) analysis and cell type annotation

[0098] To identify differentially expressed genes, we used the FindMarkers function in the Seurat package based on the Wilcox nonparametric test to select genes expressed in more than 10% of cells within a cluster, with an average log2(FoldChange) > 0.25 as DEGs. For cell type annotation of each cluster, we combined the expression of classic markers found in the DEGs with literature data, and used heatmaps, dot plots, and violin plots generated by Seurat to display the expression of markers for each cell type, manually filtering out double cells.

[0099] 2.7 Pathway enrichment analysis

[0100] To investigate the potential functions of DEGs, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were used from the clusterProfiler package. Pathways with P < 0.05 were considered significantly enriched. GO gene sets included molecular function (MF), biological process (BP), and cellular component (CC) categories as references. Protein-protein interactions of DEGs in each cluster were predicted based on known gene interactions with relevant GO terms in StringDB v1.22.0.

[0101] 2.8 Single-cell regulatory network inference and clustering (SCENIC)

[0102] To analyze transcription factor regulatory networks, we performed SCENIC analysis on scRNA-seq expression matrices using AnimalTFDB. Regulatory networks were predicted using the GENIE3 package based on the co-expression of regulators and targets. We used the RcisTarget package to search for transcription factor binding motifs in the data. Genes involved in predicting regulatory networks were defined as a gene set, where AUC values ​​were calculated using the AUCell package to assess the activity of regulatory networks in cells.

[0103] 2.9 Analysis of Cell Development Trajectory

[0104] 2.9.1 Pseudo-Time Series Analysis

[0105] 1) We used the Monocle 2 package to analyze the developmental trajectory of T cells. Monocle 2 is mainly based on the expression patterns of selected characteristic genes, and uses machine learning to calculate gene expression changes between different cells, and sorts individual cells to simulate the dynamic changes in cell development;

[0106] 2) The total length of the cell development trajectory is defined based on the total amount of transcriptional changes the cell undergoes from its initial state to its final state. After the cells are arranged in an ordered manner, the data can be dimensionality reduced using the inverse graph embedding algorithm in Monocle 2, using the function reduceDimension.

[0107] 3) Trajectory construction is visualized using the plot_cell_trajectory function, projecting the data into a lower-dimensional space;

[0108] 4) Visualization of gene expression on a pseudo-timeline: The `plot_genes_in_pseudotime` function can plot the dynamic changes in gene expression levels on a pseudo-timeline. To further investigate genes following similar dynamic trends, the `plot_pseudotime_heatmap` function was used to create heatmaps, visualizing gene modules that change together at different time points on the pseudo-timeline. `Plot_pseudotime_heatmap` uses CellDataSetd objects (containing a subset of important genes) to generate smooth expression curves.

[0109] 2.9.2 RNA rate analysis

[0110] For RNA rate analysis, we used a BAM file containing T cells and a reference genome GRCh38 (hg38). Analysis was performed in Python using Velocyto (v0.2.3) and scVelo (v0.17.17) with default parameters. Results were projected onto a UMAP plot generated via Seurat clustering analysis to ensure consistent visualization.

[0111] 2.10 Analysis of intercellular interactions

[0112] CellPhoneDB performs cell-cell interaction analysis based on receptor-ligand interactions between two cell types. Cluster labels for all cells are randomly permuted 1000 times to calculate the null distribution of the mean ligand-receptor expression level for interacting clusters. Individual ligand or receptor expression is thresholded using cutoff values ​​based on the mean logarithmic gene expression distribution of all genes across all cell types. Significant cell-cell interactions are defined as P < 0.05. Visualization is finally performed using the circlize (v0.4.10) package.

[0113] 2.11 Metabolic Characteristic Analysis

[0114] 1) Using scMetabolism (v0.2.1) to quantify single-cell metabolic activity: Metabolic pathways were collected from the KEGG database, and enrichment scores were calculated based on the VISION algorithm. The scores of specific pathways were visualized using the FeaturePlot / VlnPlot functions and pheatmap in Seurat.

[0115] 2) Single-cell metabolic fluxome and abundance analysis (scFEA): scFEA (v1.1.2) is a computational method based on a novel probabilistic model and flux balance constraints, used to infer cellular metabolic fluxome and metabolite abundance from scRNA-seq data. In this study, scFEA was run using the Python platform to calculate the metabolic fluxome and metabolite abundance for T cell types. After estimating metabolic flux and metabolite abundance, 70 metabolic modules and all metabolites were selected and visualized using heatmaps.

[0116] 2.12 Functional Gene Module Analysis

[0117] We used the Hotspot tool to identify functional gene modules, demonstrating heterogeneity within T cell subsets. Using the "danb" model, we selected the top 500 genes with the highest autocorrelation z-scores for module identification, then used the `create_modules` function to identify modules, setting `min_gene_threshold = 15` and `fdr_threshold = 0.05`. Module scores were calculated using the `calculate_module_scores` function.

[0118] 2.13 TCR library sequencing and analysis

[0119] TCR sequence alignment and annotation were performed using the vdj pipeline of Cell Ranger (v4.0.0) with GRCh38 as the reference genome to obtain a TCR library containing clonoid frequencies and barcode information. For TCRs, only cells with one valid TCRα chain (TRA) and one valid TCRβ chain (TRB) were retained for further analysis. Each unique TRA(s)-TRB(s) combination was defined as a clonoid. Cells containing a clonoid were considered clonogenic if it was present in at least two cells, and the number of cells containing such a clonoid represented the degree of clonogenicity of that clonoid.

[0120] 2.14 CITE-seq Analysis

[0121] 1) Library Construction: Single-cell suspensions were labeled according to Biolegend's official protocol (https: / / www.biolegend.com / en-us / protocols / totalseq-a-dual-index-protocol). Cells were then diluted to appropriate concentrations using PBS. Cells were then loaded onto microarrays using the Singeron Matrix single-cell processing system. Bar beads were removed from the microarrays, and mRNA and oligonucleotides captured by the bar beads were reverse transcribed to obtain cDNA for PCR amplification. The amplified cDNA was fragmented and indexed using sequencing adapters to generate single-cell transcriptome libraries. The purified cDNA supernatant was used as a template for CITE-seq library construction. Each library was diluted to 4 nM, mixed, and subjected to 150 bp paired-end sequencing on a Novaseq 6000 (Illumina).

[0122] 2) Data Analysis: Raw data were processed using CeleScope (v1.15.0) to generate gene expression profiles. Barcodes and UMIs were extracted and corrected from R1 reads. Adapter sequences and polyadenylated tails were removed from R2 reads, and CITE-seq tags were then extracted from the R2 reads. Finally, identical reads matching the corresponding transcriptome cell barcodes were extracted. Successfully assigned reads were grouped with the same cell barcode, UMI, and CITE-seq tag to generate a CITE-seq expression matrix for further analysis.

[0123] 2.15 Data Acquisition from Public Data Queue

[0124] We downloaded gene expression data and corresponding clinical information for all samples in the GSE223655 cohort from the GEO database (https: / / www.ncbi.nlm.nih.gov / gds / ?term=GSE223655) for external database validation.

[0125] 2.16 Statistical Analysis

[0126] All data in this study were statistically analyzed using Graphpad Prism (version 10). Normality was tested for all data using the Shapiro-Wilk test, and subsequent statistical tests were selected based on whether normality was met. For normally distributed data, independent samples t-tests were used for comparisons between two groups. For non-normally distributed data, the Mann-Whitney U test was used. Paired t-tests were used for comparisons of different conditions within the same group. For comparisons among multiple groups, one-way ANOVA and the Bonferroni post-hoc test were used for normally distributed data. For non-normally distributed data, the Kruskal-Wallis test and the Dunn post-hoc test were used. P < 0.05 was considered statistically significant, * for P < 0.05, ** for P < 0.01, *** for P < 0.001, **** for P < 0.0001, and ns for P > 0.05.

[0127] 3 Experimental Results

[0128] 3.1 Single-cell multi-omics analysis of the characteristics of 7×19 CAR-T infusion products from B-cell lymphoma patients

[0129] 3.1.1 Sample Information and Preprocessing

[0130] To investigate the key factors maintaining the long-term efficacy of fourth-generation CAR-T cell therapy (7×19CAR-T) in patients with CD19-positive LBCL, we performed in vitro tumor antigen stimulation and single-cell sequencing analysis on CAR-T cell infusion products from 10 adult patients (median age: 58.50 years, range: 42–72 years) who participated in previous phase I and extended clinical trials of 7×19CAR-T cell therapy for refractory and relapsed LBCL. Patient information is shown in Table 1. Based on the evaluation results at 3 months after CAR-T therapy, patients were divided into two groups: 8 patients achieved complete or partial response (PR) after treatment and were classified as responders; while the other 2 patients experienced disease progression and were classified as non-response (NR). Responders were further divided into patients who achieved durable complete response (CR, n=4) and patients who relapsed during the trial (RL, n=4). Our goal was to identify key cell subsets that can maintain the long-term efficacy of fourth-generation CAR-T cell therapy and to analyze the core genes closely related to clinical efficacy within these subsets. Since baseline data from 7×19 CAR-T cell products alone cannot fully elucidate the early response mechanisms of cells after activation, we combined 7×19 CAR-T cell products with CD19 at a 1:1 effector-target ratio in vitro. +Raji cells were co-cultured for 24 hours to induce antigen-specific activation. Subsequently, we performed scRNA-seq analysis on the CAR-T cell infusion products from these patients using microplate assays, and combined with CITE-seq technology, analyzed 14 surface protein markers, including T cell markers (CD4 and CD8), differentiation and subtype markers (CD45RO, CD45RA, CCR7, and CD62L), activation markers (HLA-DR, CD69, CD38, and 4-1BB), and co-inhibitory markers (PD-1, CTLA-4, LAG-3, and TIGIT).

[0131] Table 4. Basic information and treatment response of included adult patients

[0132]

[0133] 3.1.2 Single-cell sequencing reveals the main cell types of the 7×19 CAR-T infusion product

[0134] After excluding low-quality cells and potential double-celled organisms, we analyzed the gene expression profiles of 126,813 cells and used UMAP to perform dimensionality reduction clustering on differentially expressed genes, thus grouping all cells into subpopulations. Following this grouping, we obtained a list of differentially expressed genes for each subpopulation. Based on existing literature reports and gene definitions, we analyzed the functions of several genes with the most significant differences in each subpopulation, thereby accurately identifying and naming each cell subpopulation.

[0135] First, we removed batch effects among the 10 samples using the Harnomy algorithm. Then, based on the clustering and differentially expressed genes, we identified 11 distinct cell clusters (Figure 1-1A), primarily consisting of two main cell types: B cells (50,213 Raji cells in the co-culture system) and T cells (76,600 cells). Based on the differential gene expression of each subpopulation, we further subdivided the T cells into 10 subpopulations with different transcriptional characteristics, naming each subpopulation according to the most significantly different and functionally relevant specific genes. To evaluate the gene expression patterns of different T cell subpopulations after tumor cell stimulation with the 7×19 CAR-T infusion product in different treatment groups, we plotted a dot plot showing the top 10 differentially expressed genes for each cell subpopulation (Figure 1-1B).

[0136] 3.1.3 Differences in T cell subset distribution among different clinical efficacy groups

[0137] To further explore the key factors for maintaining the long-term efficacy of 7×19 CAR-T therapy, we compared the differences in the distribution ratios of cell subsets among different clinical efficacy groups. Results showed that the proportions and numbers of CD8+T_THEMIS, CD8+T_MKI67, and CD8+T_GZMA subsets were higher in the CR group, while the proportions and numbers of CD4+T_IL2 and CD4+T_CTLA4 subsets were increased in the RL and NR groups (Figures 1-2A and B). Due to sample size limitations, traditional statistical methods did not observe the differences in the proportions of these subsets (P>0.05). Therefore, we further employed Ro / e analysis to assess the distribution characteristics of the target cell populations in tissues. We aimed to quantify the enrichment or depletion of specific cell clusters in specific groups by comparing the observed cell number with the expected cell number (i.e., the Ro / e index; Ro / e>1 indicates enrichment of the cell cluster in the subgroup; Ro / e<1 indicates depletion). The results showed that the CD8+T_THEMIS subset was highly enriched in the CR group, and may be the most relevant special T cell subset affecting the efficacy of 7×19 CAR-T therapy (Figure 1-2C).

[0138] 3.1.4 Assessment of functional characteristics among different clinical efficacy groups and T cell subsets

[0139] After assessing the distribution preferences of T cell subsets among different efficacy groups based on the Ro / e index, we further used the Ucell scoring method to systematically analyze the gene expression patterns and functional enrichment characteristics of different efficacy groups and each T cell subset to identify key subsets. The results showed that the CR group had higher scores for cell proliferation, tissue retention, and lipid metabolism with the 7×19 CAR-T infusion product, while the RL group, although exhibiting more prominent T cell toxicity and inflammatory effects, had higher T cell exhaustion scores, which may reveal the mechanism of disease relapse after cell therapy. Furthermore, consistent with clinical efficacy, the NR group showed significant immunosuppression and T cell exhaustion characteristics (Figure 1-3A). To further elucidate the key subpopulations that may have led to the above results, we evaluated the functional enrichment characteristics of each T cell subset. The results showed that the CD8+T_TEHMIS subset, which was highly enriched in the CR group, exhibited superior cell proliferation capacity and was significantly enriched with the activity of signaling pathways related to T cell proliferation and effector activity, such as FOXO, IL2-Stat, TCR, and MAPK. In contrast, the CD4+T_IL2 and CD4+T_CTLA4 subsets, which were enriched in the RL and NR groups, had good cell proliferation and antigen response capabilities, but the cells were also more prone to apoptosis (Figure 1-3B).

[0140] To clarify the functional characteristics of these T cell subsets at the transcriptional level from multiple perspectives, we further compared the expression levels of key immune-related molecules in each subset, including effector (GZMB, IFNG, CCL3, PRF1, TNF), regulatory (IL-4, IL-10, IL-13, IL-22), stimulatory (CSF2, IL-2, IL-5, IL-8, IL-9, IL-21), inflammatory (IL-17A, IL-17F), and chemokine (CCL4, CCL5, CCL20, CXCL10) related factors. The results showed that the CD8+T_THEMIS subset enriched in the CR group had higher expression levels of cytokines such as TNF, IL-13, and IL-15, but lower expression levels of cytokine genes such as IFNG and CSF2 (Figure 1-3C). It is worth noting that the CD4+T_CTLA4 subset enriched in the RL and NR groups, although the expression levels of most effector and regulatory cytokines are upregulated, excessive or prolonged high levels of IL-10 and IFNG secretion can drive T cells toward exhaustion phenotype. This may be one of the reasons why this subset has high apoptosis and exhaustion characteristics.

[0141] Based on the above, we evaluated the functional characteristics and differences in cytokine expression patterns among different clinical efficacy groups and T cell subsets.

[0142] 3.1.5 Differences in transcription factor expression among different T cell subsets

[0143] To delve deeper into the key "driver genes" influencing long-term efficacy of 7×19 CAR-T cell products and lay the foundation for further exploration of molecular mechanisms, we used SCENIC analysis to analyze the expression levels and regulatory activities of transcription factors in various T cell subsets, ultimately screening out transcription factors with significant regulatory strength and core roles. The results showed that the expression levels (Figure 1-4A) and regulatory activities (Figure 1-4B) of transcription factors PBX3, FOXO1, BACH1, MEF2A, CERS6, and FOXP1 were all higher in the CD8+T_THEMIS subset than in other subsets. Notably, except for FOXP1, all of the above transcription factors were highly expressed and transcribed only in the CD8+T_THEMIS subset. In the CD4+_CTLA4 subset, transcription factors GATA3, MAF, and RORC are relatively highly expressed. Interestingly, GATA3 is a characteristic transcription factor of Th2 cells. Combined with the high expression of cytokines such as IL-4, IL-5, IL-10, and IL-13 in the CD4+_CTLA4 subset shown in Figure 1-3C, we found that this subset is highly similar to the gene expression pattern of Th2 cells.

[0144] In summary, we compared the differences in transcription factor expression and activity among different T cell subsets at the single-cell transcriptome level. We found that FOXO1 and FOXP1, which are related to CAR-T cell stemness and expansion, are highly expressed in the CD8+T_THEMIS subset, while the CD4+_CTLA4 subset highly expresses the Th2 cell characteristic transcription factor GATA3.

[0145] 3.1.6 Analysis of T-cell gene modules in 7×19 CAR-T cell products

[0146] To further explore the gene regulatory network among T cells in the 7×19 CAR-T cell product, we used the hotspot method to analyze gene co-expression patterns.

[0147] After transforming and clustering the gene relationships, we obtained 13 functional modules (Figure 1-5A). Among them, three modules (modules 1, 7, and 11) were rich in genes related to T cell function. We then performed GO gene enrichment analysis on these three modules to determine their functions. The results showed that module 1 was closely related to T cell development, activation, and differentiation, while modules 7 and 11 were associated with the secretion and response of cytokines and chemokines, as well as the Jak-Stat pathway (Figure 1-5B).

[0148] Based on the above, we used the hotspot method to discover three gene modules that are related to T cell development, activation, and effector function, and may play an important role in 7×19 CAR-T cell killing of tumors.

[0149] 3.1.7 Metabolic characteristics of different T cell subsets

[0150] Different T cell subsets can adapt their metabolism according to their energy needs and the surrounding microenvironment, for example... T cells rely on mitochondrial pathways with minimal nutrient uptake, such as the tricarboxylic acid cycle and oxidative phosphorylation. Upon activation, effector T cells undergo metabolic reprogramming, shifting from mitochondrial responses to glycolysis and glutamine breakdown. Various metabolic pathways involve the uptake of different nutrients to support T cell function and survival. Therefore, we analyzed changes in metabolic flux and metabolite abundance using scMetabolism and scFEA to further understand metabolic regulation and microenvironmental factors among different therapeutic groups and T cell subsets, revealing potential metabolic regulatory points. Figure 1-6A (left) shows that the adenosine monophosphate (AMP) to adenine conversion pathway is more active in the CD8+T_THEMIS subset than in other subsets, while the glutathione (GSH) to glutamate conversion pathway is downregulated compared to other subsets. Furthermore, overall analysis reveals that, compared to the RL and NR groups, the CR group showed more active acetyl-CoA to farnesyl pyrophosphate (FPP) metabolism in each T cell subset. Correspondingly, Figure 1-6A (right) shows that the CD8+T_THEMIS subset exhibits higher abundances of glucose-6-phosphate (G6P) and glutathione compared to other subsets, while the abundance of glutamate metabolism is relatively lower, consistent with changes in its metabolic pathway. Figure 1-6B similarly reveals enhanced D-glutamine and D-glutamate metabolism in the CD8+T_THEMIS subset.

[0151] In summary, we analyzed the metabolic characteristics of different T cell subsets and found that the CD8+T_THEMIS subset differs from other subsets in its glutamate metabolism pathway.

[0152] 3.1.8 Interaction analysis of different cell subpopulations

[0153] In CAR-T cell therapy, the function of each T cell subset is often influenced by other subsets and tumor cells. Therefore, in-depth analysis of cell communication (based on receptor-ligand pairs) between T cell subsets and with tumor cells is of great significance. Figure 1-7A shows that the interactions between B cells (i.e., tumor cells) and various T cell subsets are not significantly different across different treatment groups, but there are differences in the communication interactions between different T cell subsets. In the CR group, the communication interaction between CD8+T_GNLY and other subsets is the most significant; in the RL and NR groups, the communication interaction between CD4+T_CTLA4 and the other subsets is the strongest. These results are consistent with our previous analysis of the distribution preferences of each subset across different treatment groups (Figure 1-2C).

[0154] Furthermore, we analyzed ligand pairs between tumor cells and different T cell subsets, and selected the top 10 most significant ligand pairs for presentation. The results showed that tumor cells mainly interact with T cell receptors such as CD2, CD27, and HLA-C on the surface of T cells through their surface receptors CD58, CD70, and FAM3C (Figure 1-7B). We also found that compared to the RL and NR groups, the CR group exhibited more significant interactions with ligands CCL22_DPP4, CXCL11_DPP4, FAM3C_LAMP1, and CD58_CD2, and these interaction pairs are related to T cell recruitment and activation.

[0155] Based on the above, we comprehensively analyzed the T cell subsets with the most significant interactions among different therapeutic groups, and found that in the NR and RL groups, the interaction pairs related to T cell recruitment and activation were reduced. This may reveal the potential mechanism of tumor recurrence after cell therapy and provide important ideas for subsequent basic experimental research.

[0156] 3.1.9 Analysis of TCR diversity among different T cell subsets

[0157] Although CAR-T cells primarily function by binding tumor antigens and transducing signals through their CAR structure, the TCRs on their surface also play a role in recognizing antigenic peptides and triggering downstream pathways to activate T cells. To further elucidate the immune mechanisms of fourth-generation CAR-T cell therapy for B-cell lymphoma patients and the possible escape mechanisms leading to relapse / ineffectiveness, we simultaneously performed TCR sequencing analysis on CAR-T products to explore the characteristics and differences in TCR clonal types among different T cell subsets. Figure 1-8A shows that the number and diversity of TCR clones in each T cell subset of the CR group were higher than those in the RL and NR groups, especially the CD8+T_GNLY and CD8+T_THEMIS subsets, which may be related to their more effective and durable tumor immune clearance capabilities. In addition, we also noted that the 7×19 CAR-T cell products from patients in the RL group also exhibited a greater number of medium and large TCR clone types after short-term stimulation by tumor cells, which is consistent with the good immune response results in the early stages of treatment in this group of patients. In contrast, in the NR group, the number of TCR clones in each T cell subset was relatively small, and a large proportion of them were monoclonal TCRs, suggesting that the immune response of these T cells was in a relatively inefficient state. The T cell population was not effectively expanded or activated under antigen stimulation, and ultimately could not effectively eliminate tumor cells.

[0158] From the perspective of T cell subsets, we found that the CD8+T_GNLY and CD8+T_MKI67 subsets, which are markers of cytotoxicity and proliferation, had a higher number and greater diversity of TCR clones compared to other subsets, especially the former. These subsets were mainly enriched in the CR group (Figure 1-2C). It should be noted that although the CD8+T_THEMIS subset, which is highly enriched in the CR group, has some clonal diversity, its clone number is less than other subsets, especially in the RL and NR groups. We also analyzed the number of shared TCR clones among different T cell subsets in different treatment groups. The results showed that in the CR group, the CD8+T_GZMA and CD8+T_MKI67 subsets had the highest number of shared TCR clones, indicating a strong correlation between them, which may be closely related to the anti-tumor immune response. In the RL and NR groups, the CD8+T_XCL2 and CD8+T_CCL4, and CD8+T_GZMA and CD4+T_LTB subsets had the highest number of shared TCR clones, respectively. It is worth noting that CD8+T_GNLY, which has a large number and diversity of TCR clones, and the CD8+T_THEMIS subset, which is highly enriched in the CR group, share the fewest TCR clone types across different treatment groups, exhibiting a certain unique TCR expression pattern (Figure 1-8B).

[0159] Based on the above, we used TCR sequencing to understand the TCR expression patterns among different T cell subsets and found that the CR group had a greater number and diversity of TCR clones. The CD8+T_GNLY and CD8+T_THEMIS subsets have unique TCR expression patterns.

[0160] 3.1.10 Analysis of the differentiation trajectories of different T cell subsets

[0161] T cells differentiated from the same cell line often share the same TCR clonal type. In the above analysis, we examined the TCR expression patterns among different T cell subsets in different therapeutic groups. Although unique TCRs predominate in each subset, varying degrees of shared TCR clonal types exist, suggesting that these two T cells may share a common progenitor cell origin. Therefore, to further investigate the differentiation and evolution of T cells in fourth-generation CAR-T cell products, we employed pseudo-temporal analysis and RNA rate analysis to simulate the dynamic evolution of cells, thereby clarifying the direction and state of cell development. The pseudo-temporal trajectory diagrams in Figures 1-9A and 1-9B show that in the early stages of cell differentiation, CD8... + The T subset is mainly composed of cell subpopulations marked by cytotoxicity and proliferation-related genes, such as CD8+T_GZMA, CD8+T_MKI67, and CD8+T_GNLY; similarly, CD4... +The T cell subset is primarily characterized by CD4+T_LTB, an inflammatory response gene. This indicates that T cells rapidly enter a state of proliferation and inflammation in the early stages of the immune response, which is closely related to anti-tumor capacity and effector function. In the mid-differentiation phase, T cell subsets associated with cytokines and immune effectors (such as CD8+T_CCL4 and CD8+T_IL5) are predominantly distributed, suggesting that cytokine secretion is the primary driver of the immune response during this period. At the end of differentiation, T cells enter a period of exhaustion, dominated by the CD4+T_CTLA4 and CD8+_THEMIS subsets. The former highly expresses exhaustion marker genes, while the latter is mainly enriched in the CR group in our previous analysis. Interestingly, the CD8+T_THEMIS subset exists in every stage of the pseudo-timeline trajectory, especially in the early and late stages of differentiation. For this reason, we simultaneously performed RNA rate analysis (Figure 1-9D). The results showed that the CD8+T_THEMIS subset is different from other subsets and has an independent differentiation pathway, suggesting that this subset may have a special self-renewing cell pool in CAR-T cell products.

[0162] In addition, we analyzed the dynamic changes of genes during cell differentiation (Figure 1-9C), and obtained a total of 7 gene modules with different expression trends. Among them, 8 genes related to T cell function were identified. Among them, the effector and activation-related genes GNLY, STAT1, CD52, IFI6 and LCK were most significantly expressed in the early stage of differentiation, while the chemokines XCL1 and XCL2 were mainly expressed in the middle stage of differentiation. The Treg cell activation marker gene TNFRSF9, which is related to exhaustion, was highly expressed in the late stage of differentiation. These results are consistent with our previous analysis.

[0163] Based on the above, through cell differentiation trajectory analysis, we clarified the evolution of T cells from an initial activated state to an immune-exhausted state during the immune response of four generations of CAR-T cells, as well as the dominant T cell subsets at each differentiation stage. Furthermore, we found that the CD8+T_THEMIS subset possesses unique differentiation pathways and functional characteristics, which may be one of the reasons why it is a key subset for maintaining the long-term efficacy of CAR-T cells. Further exploration of its underlying mechanisms may provide insights and directions for improving the sustained tumor-killing ability of CAR-T cells in the future.

[0164] 3.1.11 Analysis of surface proteins of different T cell subsets

[0165] To comprehensively understand the characteristics of 7×19 CAR-T cell products in different efficacy groups, we simultaneously performed CITE-seq, analyzing 14 surface proteins using antibody-derived DNA tags (ADTs), including T cell markers (CD4 and CD8), differentiation and memory-related markers (CD45RO, CD45RA, CCR7, and CD62L), activation markers (HLA-DR, CD69, CD38, and 4-1BB), and immune checkpoints (PD-1, CTLA-4, LAG-3, and TIGIT). The analysis showed that CD45RO and CD62L, associated with memory phenotypes, were mainly expressed in T cell subsets marked by chemokines and proliferation, such as CD8+T_MKI67 and CD8+T_CCL4. Notably, both subsets also highly expressed LAG-3 protein (Figure 1-10A). Consistent with the cell enrichment results, the CD4+T_LTB, CD4+T_IL2, and CD4+T_CTLA4 subsets, which were distributed in higher proportions in the RL and NR groups, were upregulated, as were PD-1 and TIGIT proteins related to cell exhaustion and immunosuppression (Figure 1-10A).

[0166] Previous studies have shown that memory T cells can rapidly proliferate and produce effects after being restimulated by antigens, which is key to maintaining the long-term efficacy of CAR-T cell therapy. Immunosuppressed and exhausted T cells are important factors in tumor recurrence and escape. Figure 1-10B shows an analysis of the overall protein expression in different efficacy groups. The results show that, compared to the NR group, memory-related proteins CD45RO and CD62L were highly expressed in the CR group (P<0.05). Furthermore, compared to the CR group, the expression of the immunosuppression and exhaustion-related protein PD-1 was upregulated in the NR group (P<0.05), while CTLA-4 protein expression showed an upregulated trend in the RL group (RL vs CR, P>0.05).

[0167] The CITE-seq results revealed that memory T cell markers were highly expressed in the CR group, while immunosuppression and exhaustion markers were upregulated in the RL and NR groups.

[0168] 3.2 Functional analysis of CD8+ T_THEMIS subsets and their relationship with the long-term efficacy of 7×19 CAR-T cell therapy

[0169] 3.2.1 Functional Characteristic Analysis of the CD8+T_THEMIS Subpopulation

[0170] In the previous section, Ro / e analysis revealed that the CD8+T_THEMIS subset was highly enriched in the CR group and possessed unique gene expression characteristics. To further explore the function of this special T cell subset and clarify its potential mechanism for improving the long-term efficacy of CAR-T cell therapy, we performed functional enrichment analysis on 2977 differentially expressed genes (1982 upregulated genes and 995 downregulated genes) in this subset (Figure 2-1A). The results showed that the upregulated genes in the CD8+T_THEMIS subset were closely related to T cell differentiation, activation, and proliferation, and were also associated with epigenetic modifications such as ubiquitination and methylation. Mechanistically, these genes were closely related to the MAPK signaling pathway, and also involved signaling pathways such as TCR, Jak-Stat, and FOXO, which have been widely proven to be closely related to T cell activation and effector functions. Analysis of the downregulated genes revealed that most were related to oxidative phosphorylation and the mitochondrial respiratory chain. Importantly, we also found that genes related to promoting apoptosis pathways were downregulated in this subset (Figure 2-1B).

[0171] Based on the above, we found through gene function enrichment analysis that the expression of genes related to T cell differentiation and proliferation was upregulated in the CD8+_THEMIS subset, while the expression of genes related to oxidative phosphorylation and apoptosis was downregulated.

[0172] 3.2.2 Functional differences of CD8+T_THEMIS subpopulation at different differentiation stages

[0173] In our pseudo-time series analysis, we noted that the CD8+T_THEMIS subset exhibits an independent cell differentiation pathway. To fully understand its functional changes during cell differentiation, we further compared gene expression differences between the early differentiation stage (state 2) and the late differentiation stage (state 6) of this subset, and systematically evaluated the functional characteristics and transcription factor expression differences between the two differentiation stages. Figure 2-2A shows that in the early differentiation stage, T cell activation and immune response-related genes are actively expressed in this subset, while in the late differentiation stage, genes related to protein transcription and translation activity are actively expressed. Ucell scoring showed that the CD8+T_THEMIS subset in the early differentiation stage had a higher cytotoxicity score (P<0.05), indicating that the cells rapidly entered an immune response state. Interestingly, this subset exhibited higher ferroptosis (P<0.05) and cell exhaustion score (P<0.05) in the late differentiation stage, while also having a higher cell proliferation score (P<0.05) (Figure 2-2B). Furthermore, comparing the differences in transcription factor expression between the two stages revealed that this subset showed upregulation of the exhaustion-related transcription factor IRF4 in late differentiation, while also highly expressing cell proliferation and exhaustion precursor T cell-related transcription factors MYC, Stat5A, and JUND (Figure 2-2C). These results suggest that the CD8+T_THEMIS subset may maintain a certain proportion of stem cell-like exhaustion precursor T cells (Tpex) in late differentiation.

[0174] Based on the above, by comparing the gene expression patterns of the CD8+T_THEMIS subset in the early and late stages of differentiation, we found that the early cells have good activation and immune response functions. Although the late subset will enter a state of exhaustion, it may maintain a certain proportion of Tpex cells. This type of T cell has been shown in studies to be closely related to the long-term efficacy of CAR-T cell therapy.

[0175] 3.2.3 Identification of prognostic genes in the CD8+T_THEMIS subset

[0176] To further identify key genes related to clinical efficacy in the CD8+T_THEMIS subset, we downloaded gene expression data and clinical information of CAR-T cell products from the GSE223655 cohort from the GEO database and analyzed the top 15 differentially expressed genes in the subset. The results showed that compared to the progressive disease (PD) group, SOS1 (P<0.05), THEMIS (P<0.01), PDE3B (P<0.05), CDK6 (P<0.01), and BACH2 (P<0.05) genes were all upregulated in the CR group (Figure 2-3A). Subsequently, we further analyzed CD8+T_THEMIS genes in different efficacy groups. + The expression of the above genes in T cells still showed that THEMIS (P<0.01), SOS1 (P<0.05) and CDK6 (P<0.05) were upregulated in the CR group (Figure 2-3B).

[0177] Based on the above, we identified the CAR-T cell product CD8 through public databases. + The expression levels of THEMIS, SOS1, and CDK6 genes in T cells are related to their therapeutic effects.

[0178] 4 Discussion

[0179] B-cell lymphoma is the most common type of non-HL. Although the current standard regimen for treating DLBCL, represented by R-CHOP (cyclophosphamide, doxorubicin hydrochloride, vincristine sulfate, and prednisone) combined with rituximab and chemotherapy, has achieved cure rates of 70% and 40% for germinal center B-cell and activated B-cell types, respectively, 30%-45% of patients still experience relapse or progression. In recent years, the emergence of CAR-T cell therapy has made a cure possible for R / RB-cell lymphoma. Currently reported results from large-scale multicenter clinical trials show CR rates of 39-66% for R / R LBCL, 79-94% for FL, and 67-82% for MCL. However, nearly half of the patients still relapse within one year of treatment. Therefore, further research into the differences in CAR-T cell products among patients with different treatment outcomes and identifying key factors for maintaining long-term efficacy is of great significance.

[0180] In this study, we used scRNA-seq, TCR sequencing, and CITE-seq technologies to analyze the biological characteristics of CAR-T cell infusion products in R / R LBCL patients with different efficacy outcomes after fourth-generation CAR-T cell therapy, in order to explore the key factors maintaining the long-term efficacy of fourth-generation CAR-T cells. We analyzed in depth the differences in biological characteristics of CAR-T cell products among different efficacy groups, including cell subset distribution, functional characteristics, cytokine expression, transcription factor expression profiles, metabolic characteristics, and cell-cell interactions. Through dimensionality reduction clustering, we identified 10 T cell subsets with different gene expression patterns, and Ro / e analysis revealed a CD8+T_THEMIS subset highly enriched in the CR group. Further, using the Ucell scoring system to systematically evaluate the functional characteristics of different treatment groups and different T cell subsets, we found that the infusion product in the CR group had better cell proliferation, tissue retention, and lipid metabolism capabilities, while the RL group, although showing more prominent cytotoxicity and inflammatory effects, also exhibited higher exhaustion characteristics. Functional assessment of cell subsets revealed that the CD8+T_THEMIS subset exhibited superior cell proliferation capacity consistent with the overall assessment of the CR group. Recent research has found that the cytotoxic capacity of CAR-T cells with 4-1BB as a co-stimulatory domain is related to their proliferation capacity. Although the killing rate of individual cells is slower, their strong proliferative capacity and synergistic killing properties give them a more effective and sustained tumor-killing ability, which may be one of the important factors that enable this subset to maintain the long-term efficacy of CAR-T therapy. Further transcription factor expression analysis revealed significantly upregulated expression levels and activities of FOXO1 and FOXP1 in the CD8+T_THEMIS subset. Recently, multiple studies have demonstrated that FOXO1 and FOXP1 can promote the expansion of CAR-T cells and maintain their stemness, limiting excessive differentiation of effector cells, thereby resisting exhaustion and improving the long-term efficacy of CAR-T cell therapy. On the other hand, we also analyzed the metabolic characteristics of various T cell subsets, finding that the CD8+T_THEMIS subset mainly differs in the glutamate metabolism pathway, exhibiting higher GSH metabolic abundance. Previous studies have reported that GSH can maintain T cell homeostasis and promote their proliferation after stimulation. A decrease in GSH will impair the normal glycolysis and glutamine metabolism of T cells and affect cell proliferation.

[0181] Furthermore, analysis of ligand-receptor interactions between different T cell subsets and tumor cells across different treatment groups revealed more significant interactions in the CR group involving CCL22_DPP4, CXCL11_DPP4, FAM3C_LAMP1, and CD58_CD2 ligands. Researchers have found that CCL22, as a factor coupled with B cell antibody affinity, can act as a marker to transmit B cell affinity information to T cells, while also positively promoting the recruitment of more T cells to highly affinity B cells, thereby killing tumor cells. Similarly, CXCL11 (also known as IFN-induced T cell α-chemokine) can chemotactically attract and recruit activated T cells, thereby regulating the migration and differentiation of immune cells. In addition, CD58, as a co-stimulatory receptor, has its natural ligand CD2 primarily expressed on the surface of T / NK cells. Multiple studies have shown that the intact CD58-CD2 axis is essential for effective lysis of cancer cells mediated by tumor-infiltrating lymphocytes, and disruption of this specific ligand-receptor pair can lead to tumor immune escape.

[0182] Interestingly, when analyzing the TCR of various T cell subsets, we found that the CD8+T_THEMIS subset exhibited a unique TCR expression pattern, sharing the fewest TCR clone types with other subsets. Cell differentiation trajectory analysis further suggested that it has an independent differentiation pathway, all of which indicate that this subset may possess a unique self-renewing cell pool. To further analyze the functional and gene expression evolution of this subset during differentiation, we compared the differences between early and late differentiation stages. We found that in the early stage, genes related to T cell activation and immune response were actively expressed, demonstrating good effector function. In the late stage, however, this cell subset exhibited high exhaustion characteristics while also showing some proliferative capacity. Further comparison of transcription factor expression profiles revealed that in the late stage of differentiation, it not only highly expressed the exhaustion-related transcription factor IRF4 but also highly expressed Tpex-related transcription factors MYC, Stat5A, and Jun. Recent studies have found that under chronic antigen exposure conditions, Stat5 expression in exhausted T cells can directly promote the formation of exhausted intermediate cells and restart some effector biological functions, enhancing anti-tumor potential. In conclusion, the CD8+T_THEMIS subset may play a key role in maintaining the long-term efficacy of fourth-generation CAR-T cell therapy through its unique functional characteristics and transcription factor expression.

[0183] To further identify representative genes in the CD8+T_THEMIS subset associated with CAR-T cell therapy, we used external databases to validate the findings of CAR-T cell infusion product CD8+T_THEMIS. + The expression of SOS1, THEMIS, and CDK6 genes in T cells is correlated with the therapeutic effect of CAR-T cells, providing a basis for further exploration of the mechanism.

[0184] In summary, this study identified a key specific subset, CD8+T_THEMIS, that maintains the long-term efficacy of fourth-generation CAR-T cells. This subset is characterized by active proliferation and high expression of transcription factors related to T cell stemness. Furthermore, this subset exhibits an independent differentiation pathway, highly expressing transcription factors that can reverse the function of exhausted T cells in late differentiation. The THEMIS gene, as a marker gene for this subset, has been found to be correlated with the efficacy of CAR-T cells. Recent studies have also revealed its association with peripheral T cell homeostasis, and in CAR-T cells with a 4-1BB co-stimulatory domain, the THEMIS-SHP1 complex can reduce CAR-CD3ζ phosphorylation, thereby weakening T cell activation and ultimately reducing cytokine secretion. However, the regulatory mechanisms of the THEMIS gene on CAR-T cell phenotypes such as memory, exhaustion, and apoptosis remain unclear, and its impact on the long-term efficacy of CAR-T cells, especially fourth-generation CAR-T cells, is still ambiguous. Therefore, further research on this gene is necessary.

[0185] 5. Results and Conclusions

[0186] Results: (1) The infusion product in the complete remission (CR) group had higher Ucell scores in terms of cell proliferation, tissue retention, and lipid metabolism, while the relapse (RL) group had higher exhaustion scores; (2) Dimensionality reduction clustering and single-cell tissue preference analysis (the ratio of observed to expected cell numbers, Ro / e) revealed that the CD8+T_TEHMIS subset was highly enriched in the CR group, exhibiting better cell proliferation capacity and high expression of memory stem-related transcription factors; (3) The CD8+T_THEMIS subset had a unique TCR expression pattern and differentiation pathway; (4) Validation using public databases revealed that the expression of thymocyte-expressed molecule involved in selection (THEMIS) genes in CAR-T cell products in the complete remission group was higher than that in the disease progression group (P<0.01).

[0187] Conclusions: 1) The CAR-T cell products in the CR group showed better cell proliferation and tissue retention characteristics, while the RL group showed obvious exhaustion characteristics; 2) The CD8+T_THEMIS subset was highly enriched in the CAR-T cell products in the CR group and is a key subset for maintaining long-term efficacy; 3) High expression of the THEMIS gene is associated with good efficacy of CAR-T cells.

[0188] Part Two: The Mechanism of THEMIS Gene Regulation in the Killing of B-cell Lymphoma by Fourth-Generation CAR-T Cells

[0189] THEMIS is an evolutionarily conserved T cell-specific gene that encodes a protein containing 636 and 641 amino acids in mice and humans, respectively. Multiple studies, using gene knockout models and N-ethyl-N-nitrosourea-induced mutations, have revealed the crucial role of THEMIS in thymocyte development. Notably, all mutant models showed that thymocytes exhibited CD4+-related abnormalities. + CD8 + Significant blockade occurred during the double-positive phase. These mutations were widely distributed throughout the entire THEMIS protein sequence, including frameshift mutations at sites such as Y489X and T512P in mouse models. THEMIS participates in TCR signaling by constitutively binding to the adaptor protein Grb2 and the tyrosine phosphatase SHP1. Grb2 mediates the recruitment of phosphorylated LAT molecules by the THEMIS-SHP1 complex. Although multiple studies have confirmed the regulatory role of THEMIS in SHP1 activity, the specific direction of its regulation of TCR signaling (activation or inhibition) during thymocyte development remains controversial. For example, the results of studies on THEMIS / SHP1 double knockout mice were divergent: one group showed complete phenotypic recovery, while the other group showed no significant changes. Therefore, further in-depth investigation is needed into the effects of the THEMIS gene on T cells and its molecular mechanisms.

[0190] Recent studies have revealed the important functions of THEMIS in peripheral mature T cells. Gascoigne's team demonstrated that THEMIS promotes CD8 cell growth by integrating cytokine signaling and interacting with TCR-ligands at low affinity. + T cell homeostasis is maintained. Another research team has verified the effects of THEMIS on IL-2 and IL-15-driven CD8+ using both mouse models and in vitro experiments. + T cell proliferation is essential. Similarly, studies have found that knockout of THEMIS cells can lead to CD4+ cloning. + T cell developmental defects and regulatory T cell dysfunction. THEMIS has also been found to be involved in the development and progression of various diseases. Genome-wide association studies (GWAS) have found that THEMIS is significantly associated with autoimmune diseases such as celiac disease and inflammatory bowel disease. In addition, THEMIS is also involved in the HTLV-1 infection mechanism: viral bZIP factors can induce abnormal T cell proliferation by binding to THEMIS.

[0191] In CAR-T cell therapy research, researchers have discovered that CARs using 4-1BB as a co-stimulatory molecule can recruit the THEMIS-SHP1 complex to the CAR signaling system via the 4-1BB intracellular domain, inhibiting CAR-CD3ζ phosphorylation. Knockout of THEMIS or SHP1 enhances basal phosphorylation levels, but its regulatory role in tumor killing function remains unclear. These findings highlight the potential value of THEMIS as a functional regulatory target in CAR-T cell therapy.

[0192] Based on single-cell sequencing results, we discovered that the CD8+T_THEMIS subset possesses unique functional characteristics and roles, and its marker gene THEMIS is associated with the prognosis of CAR-T therapy. In this study, we constructed two models to investigate the regulation of fourth-generation CAR-T function by THEMIS: 1) knocking out THEMIS in CAR-T cells using electroporation combined with CRISPR / Cas9 gene editing technology; 2) linking the CDS sequence of THEMIS to the CAR structure to construct a fourth-generation CAR structure expressing THEMIS, and preparing novel fourth-generation CAR-T cells overexpressing THEMIS (named THEMIS-7×19CAR-T) via lentiviral vector transfection. This section aims to investigate the regulatory role of THEMIS on the killing function, memory, exhaustion phenotype, and cytokine secretion of fourth-generation CAR-T cells, providing new strategies for CAR-T cell enhancement and CAR structure modification.

[0193] Previous literature has reported that THEMIS plays an important role in CAR-T cells with 4-1BB as a co-stimulatory domain, and the fourth-generation CAR structure we studied also uses 4-1BB as a co-stimulatory domain. Building on this, we further conducted related preclinical studies to investigate the impact of THEMIS on the efficacy of fourth-generation CAR-T cells. The results showed that after THEMIS knockout, the CD8 / CD4 ratio of CAR-T cells was downregulated, and cell proliferation and memory cell formation after antigen stimulation were limited. Cytokine secretion was excessive, leading to greater depletion and apoptosis. Furthermore, we found that THEMIS knockout primarily affected the long-term tumor-killing function of CAR-T cells rather than their short-term killing effect. Compared to the control group, THEMIS-7×19 CAR-T cells showed enhanced proliferation and memory cell formation after antigen stimulation, with controlled cytokine activity, reduced apoptosis and depletion, and maintained a more effective long-term tumor-killing capacity. Therefore, these results further reveal the previously undiscovered relationship between THEMIS and the stemness and long-term killing function of CAR-T cells, and also provide new ideas for subsequent modification of CAR-T cells to improve efficacy.

[0194] 1. Experimental Materials

[0195] 1.1 Cell lines and plasmids

[0196] 1.1.1 Cell lines

[0197] 1) Jurkat: Human T-lymphoblastic leukemia cell line, purchased from ATCC;

[0198] 2) Raji: Human Burkitt's lymphoma cell line, purchased from ATCC;

[0199] 3) Jeko-1: Human mantle cell lymphoma cell line, purchased from ATCC;

[0200] 4) 3T3: Mouse embryonic fibroblast cell line, purchased from ATCC;

[0201] 5) HEK-293T / 17: Human embryonic kidney cell line, purchased from ATCC;

[0202] 1.1.2 Primary cells

[0203] This study was approved by the Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine. Before peripheral blood or bone marrow collection, the consent of healthy volunteers or patients was obtained and informed consent forms were signed.

[0204] 1) Normal human mononuclear cells: obtained from peripheral blood of healthy volunteers by gradient density centrifugation.

[0205] 2) T cells from healthy volunteers: Bone marrow from healthy volunteers was subjected to gradient density centrifugation and CD3... + Obtained by magnetic bead sorting.

[0206] 1.1.3 Plasmids

[0207] Lentiviral packaging plasmids pMDLg / pRRE, pRSV-Rev, and pMD2.G were purchased from Addgene (https: / / www.addgene.org / ), and the expression vector plasmid pLenti7.3 / V5-DEST was used. TM Purchased from Thermo Fisher Scientific China Co., Ltd. (Shanghai, China).

[0208] 1.2 Main Experimental Reagents

[0209] Table 5

[0210]

[0211]

[0212] 1.3 Preparation of main reagents:

[0213] 1) Cell cryopreservation solution (serum:DMSO = 9:1): Add 1mL of DMSO to 9mL of fetal bovine serum, mix well, and prepare fresh before use.

[0214] 2) Virus preservation solution (1% HEPES X-VIVO): Add 0.1 mL HEPES to 9.9 mL X-VIVO culture medium, mix the two well, and store at 4℃ for later use.

[0215] 3) LB liquid medium: Dissolve 5g of LB broth medium in 200mL of deionized water, place it in a 300mL Erlenmeyer flask and seal it with aluminum foil. After high temperature and high pressure sterilization, restore it to room temperature and store it in a refrigerator at 4℃ for later use.

[0216] 4) LB solid medium: Dissolve 5g of LB broth agar in 200mL of deionized water, place it in a 300mL Erlenmeyer flask and seal it with aluminum foil. After autoclaving, restore the temperature to 30-50℃, add 400μL of 100mg / mL ampicillin and mix thoroughly. Dispense the mixture into 10mL / plates into 10cm cell culture dishes. After solidification, seal the flasks with sealing film and store them upside down in a refrigerator at 4℃ for later use.

[0217] 5) Flow cytometry wash buffer (2% serum PBS): Add 1 mL of PAN serum to 49 mL of PBS and store at 4°C for later use.

[0218] 6) Magnetic bead sorting buffer: Add 1 mL of PAN serum and 2 mM EDTA to 49 mL of PBS and store at 4 °C.

[0219] 7) 10% ammonium persulfate (APS): Dissolve 1g of APS in 10ml of double-distilled water, then dispense into EP tubes and store at -20℃ for later use.

[0220] 8) Electrophoresis buffer (1× and 10×): Dissolve 144g glycine, 30.3g Tris, and 10g SDS in double-distilled water, and bring the total volume to 1L until fully dissolved. Take 100mL of 10× electrophoresis buffer, add 200mL methanol and 800mL deionized water, mix thoroughly to prepare 1× electrophoresis buffer for later use.

[0221] 9) TBST solution (1×): Dilute 20× TBST 20 times with deionized water.

[0222] 10) Blocking solution (5%): Take 2.5g of skim milk powder, add 50mL of 1×TBST solution, shake well to dissolve, and use immediately.

[0223] 11) Secondary antibody solution: Add 1 μL of horseradish peroxidase-labeled goat anti-rabbit IgG to 5 mL of 5% skim milk and mix thoroughly. Prepare and use immediately.

[0224] 12) SDS polyacrylamide gel: Gels of different concentrations are prepared according to the molecular weight of the protein. See Table 6 for the formulation details.

[0225] Table 6. Preparation schemes for SDS-polyacrylamide gels of different concentrations

[0226]

[0227] 1.4 Main Instruments and Equipment

[0228] Table 7

[0229]

[0230]

[0231] Experimental methods

[0232] 2.1 Cell Culture

[0233] Jurkat, Raji, and Jeko-1 cells were cultured in 1640 complete medium; HEK-293T / F17 and 3T3 cells were cultured in DMEM complete medium; and CAR-T cells were cultured in X-VIVO complete medium. All cell lines were tested for mycoplasma every two weeks, and those that tested positive were discarded. The culture media were prepared as follows:

[0234] 1) 1640 complete medium: 1% penicillin and streptomycin + 10% FBS + 1640 medium;

[0235] 2) DMEM complete medium: 1% penicillin and streptomycin + 10% FBS + DMEM medium;

[0236] 3) X-VIVO complete medium: 1% penicillin and streptomycin + 10% Gibco serum + 1% HEPES + 1% sodium pyruvate + 1% glutamine + 1% non-essential amino acids + 300 IU / mL rhIL-2 + 5 ng / mL IL-7 + 5 ng / mL IL-15.

[0237] 2.2 Cell cryopreservation

[0238] 1) Collect cells, centrifuge at 1500 rpm for 5 min, discard the supernatant, resuspend in PBS, and count by flow cytometry;

[0239] 2) After counting, centrifuge at 1500 rpm for 5 min, discard the supernatant, and then press 1×107 Add cryopreservation solution per mL of cells, mix thoroughly, and then add to cryovials.

[0240] 3) First, place the cryovials in a programmed cooling box and put them in a -80°C freezer. After 24 hours, take them out and put them in a -80°C freezer for short-term storage or transfer them to a liquid nitrogen tank for long-term storage.

[0241] 2.3 Cell resuscitation

[0242] 1) Preheat the culture medium in advance, and at the same time prepare the corresponding number of 15mL centrifuge tubes and add 4-5mL of preheated culture medium;

[0243] 2) Remove the cells to be revived from the -80℃ freezer or liquid nitrogen tank and place them in a 37℃ water bath for rapid thawing;

[0244] 3) Use a pipette to add the cells to the prepared centrifuge tube, mix thoroughly, and centrifuge at 1500 rpm for 5 min;

[0245] 4) Carefully remove the supernatant, add an appropriate amount of preheated culture medium, mix well, and transfer to a 6-well plate or T25 cell culture flask;

[0246] 5) Observe the cell state under a microscope, and place at 37℃ with 5% CO2. 2 Incubator culture.

[0247] 2.4 Lentiviral Packaging

[0248] 2.4.1 Transformation

[0249] 1) Take one competent cell from a -80℃ freezer and thaw it on ice;

[0250] 2) Add 20 μL of competent cells to a 1.5 mL EP tube, then add 1 μL of the target plasmid, gently tap to mix, incubate on ice for 30 min, heat shock in a 42℃ metal bath for 90 s, and then incubate on ice again for 2 min.

[0251] 3) Add 900 μL of ampicillin-free liquid LB broth medium, mix well by pipetting, and incubate at 37°C and 235 rpm for 45 min on a shaker.

[0252] 4) Centrifuge at 6000 rpm for 5 min, discard 700 μL of supernatant and resuspend the precipitate;

[0253] 5) Take 50 μL and drop it onto an LB broth agar plate containing ampicillin. Spread it evenly with an L-shaped spatula. Incubate upright in a 37°C incubator for 1 hour, then invert and incubate for 12-16 hours.

[0254] 2.4.2 Plasmid Extraction

[0255] Take the plasmid transformed the previous day, pick a single colony and place it in a test tube containing 5 mL of LB liquid medium. Add 5 μL of ampicillin (100 mg / mL) and incubate at 37°C and 235 rpm for 6-8 hours. After 6-8 hours, pour 5 mL of the bacterial-containing LB medium into 200 mL of LB liquid medium, add 200 μL of ampicillin, and incubate at 37°C and 235 rpm for 12-15 hours. Then perform large-scale plasmid extraction.

[0256] 1) Dispense 200 mL of bacterial culture into 50 mL centrifuge tubes, centrifuge at 8000 rpm for 3 min, and discard the supernatant;

[0257] 2) Use 8 mL of P1 solution to resuspend the bacteria in the four centrifuge tubes and concentrate them into one 50 mL centrifuge tube. Vortex to completely suspend the bacteria.

[0258] 3) Add 8 mL of P2 solution, invert 6 times to mix the cells thoroughly and lyse them, and let stand at room temperature for 5 min; then add 8 mL of P4 solution, invert 6 times to mix until a white flocculent precipitate is observed, and let stand at room temperature for 10 min.

[0259] 4) Centrifuge at 8000 rpm for 10 min to collect the flocculent material to the bottom of the tube, pour all the supernatant into CS1, and push the handle to collect the filtrate;

[0260] 5) Add 0.3 times the volume of isopropanol to the filtered bacterial solution and mix by inverting.

[0261] 6) Prepare the adsorption column CP6, add 3 mL of equilibration buffer BL to fully wet the filter membrane, centrifuge at 8000 rpm for 3 min, and discard the waste liquid in the collection tube;

[0262] 7) Add 8 mL of the bacterial culture with added isopropanol to CP6, centrifuge at 8000 rpm for 3 min, discard the waste liquid in the collection tube, and put the adsorption column back into the collection tube;

[0263] 8) Repeat step 7) until all bacterial solutions have passed through the column;

[0264] 9) Add 10 mL of rinsing solution (already containing anhydrous ethanol), centrifuge at 8000 rpm for 2 min, discard the waste liquid in the collection tube, and put the adsorption column back into the collection tube;

[0265] 10) Repeat step 9) once;

[0266] 11) Add 3 mL of anhydrous ethanol to the adsorption column, centrifuge at 8000 rpm for 2 min, discard the waste liquid in the collection tube, and put the adsorption column back into the collection tube.

[0267] 12) Centrifuge at 8000 rpm for 5 min to completely remove the washing solution from the adsorption column;

[0268] 13) Place the adsorption column CP6 into a new collection tube, open the cap and let it air for 5 minutes to allow the anhydrous ethanol to evaporate completely;

[0269] 14) Add 500 μL-1 mL of TB elution buffer to the center of the filter membrane of the adsorption column in a rotating manner. Let it stand at room temperature for 10 min, then centrifuge at 8000 rpm for 5 min. The liquid collected in the tube is the plasmid we need.

[0270] 15) Use a Nanodrop micro spectrophotometer to detect the concentration and OD 260 / 280, and store at -20℃ for later use.

[0271] 2.4.3 Lentiviral Packaging

[0272] 1) Prepare 1×10 1 day in advance 7 293T cells were cultured in a 10cm dish;

[0273] 2) Replace the cell culture medium with pre-warmed 10% FBS Opti-MEM medium 2 hours in advance;

[0274] 3) Plasmid preparation: Add 500 μL of Opti-MEM medium to a 15 mL centrifuge tube. Add plasmid at a molar ratio of pMDLg / pRRE:pRSV-Rev:pMD2.G:target plasmid = 1:1:0.5:2, and add plasmid at a rate of 10 μg / plate. Calculate the required mass and volume of each packaged plasmid and the target plasmid. Add the plasmid to the Opti-MEM medium, mix thoroughly, and incubate at room temperature for 5 min.

[0275] 4) Add 10 μL of Neofectamine, mix well, and incubate at room temperature for 17 min. After incubation, add to the supernatant at 293T.

[0276] 5) Collect the supernatant after 48 hours, add 10 mL / plate of 10% FBS Opti-MEM medium, and collect the supernatant again after 72 hours;

[0277] 6) Centrifuge the collected supernatant at 1500 rpm for 5 min and filter it using a 0.45 μm filter membrane;

[0278] 7) Centrifuge at 4000g, 4℃ for 12 hours;

[0279] 8) After centrifugation, discard the supernatant, resuspend the virus precipitate in virus preservation solution (concentrated at 1:250), aliquot and store at -80℃.

[0280] 2.4.4 Virus titer determination

[0281] 1) After cell counting, press 2 × 10⁻⁶ cells per well. 5Cells were harvested using four gradients and two replicates of Jurkat cells. Considering cell loss, Jurkat cells were harvested in 10-well batches, i.e., 2 × 10⁻⁶ cells per well. 6 cell;

[0282] 2) Centrifuge at 1500 rpm for 5 min, discard the supernatant, resuspend in 1640 complete culture medium, and add 2 μL of polybrene, adding 100 μL to each well of a 96-well plate.

[0283] 3) Add 90 μL of virus preservation solution to 10 μL of original virus solution, and dilute 10 times;

[0284] 4) Add the virus stock solution, preservation solution, and 1640 medium according to the system in Table 8 below to determine the titer:

[0285] Table 8

[0286]

[0287] 5) Centrifuge at 1200g for 1.5 hours at 32℃;

[0288] 6) After centrifugation, place at 37℃ and 5% CO2. 2 Incubate in an incubator for 4 hours;

[0289] 7) After 4 hours, centrifuge at 1500 rpm for 5 minutes, remove the supernatant, and resuspend in 2 mL of 1640 complete culture medium in a 24-well plate;

[0290] 8) Positive rate detected by flow cytometry after 48 hours, titer = [(2×10⁻⁶) / 2. 5 [×Positive rate) / 0.2]×Dilution factor.

[0291] 2.5 Cell line construction

[0292] The Raji-luc-GFP and Jeko-1-luc-GFP used in this paper are both luciferase-P2A-GFP overexpressions, and CD19-3T3-GFP is a CD19-P2A-GFP overexpression. The construction methods are as follows:

[0293] 1) Take 1×10 6 Wild-type tumor cells / 3T3 cells, centrifuged at 1500 rpm for 5 min;

[0294] 2) Use 100 μL of luciferase-P2A-GFP / CD19-P2A-GFP lentivirus stock solution (titer: 1×10⁻⁶). 7 Resuspend cells in pfu / ml solution, add 100 μL of 1640 complete culture medium, add 0.2 μL of polybrene, and place in a 96-well plate;

[0295] 3) Centrifuge at 1200g for 1.5 hours at 32℃;

[0296] 4) 37℃, 5% CO 2 Incubate for 4 hours;

[0297] 5) Centrifuge at 1500 rpm for 5 min, carefully discard the supernatant, and resuspend in a 24-well plate with 2 mL of 1640 complete culture medium. Incubate at 37°C with 5% CO2. 2 Incubate for 48 hours;

[0298] 6) Flow cytometry was used to detect GFP expression;

[0299] 7) After 72 hours, GFP-positive cells were separated by flow cytometry and treated with 2% Streptomyces penicillin + 10% FBS.

[0300] After culturing in 1640 / DMEM medium for 48 hours, the medium was replaced with 1640 / DMEM complete medium. The GFP positivity rate was confirmed to be 100% before being used in subsequent experiments. The GFP positivity rate was monitored regularly in the later stages, and the GFP positivity rate remained at 100% for a long period.

[0301] 2.6 CAR-T cell preparation

[0302] 2.6.1 Isolation of human peripheral blood mononuclear cells (PBMCs)

[0303] 1) Add 10-20 mL of peripheral blood from a healthy person to an equal volume of PBS and mix thoroughly;

[0304] 2) Prepare two 50mL centrifuge tubes and add 20mL of human peripheral blood lymphocyte separation medium.

[0305] 3) Carefully and slowly layer the diluted peripheral blood along the tube wall onto the surface of the human peripheral blood lymphocyte separation solution;

[0306] 4) Centrifuge at 800g, speed 1, speed 0, room temperature for 20 minutes;

[0307] 5) Prepare two 15mL centrifuge tubes, add 5-8mL of PBS, carefully pipette the white membrane layer (i.e., PBMC) into the PBS, and mix thoroughly.

[0308] 6) Centrifuge at 1500 rpm for 5 minutes;

[0309] 7) Carefully discard the supernatant, and freeze the cell clumps with cell cryopreservation solution for later use or use them directly.

[0310] 2.6.2 Separating CD3 + T cells

[0311] 1) Resuspend PBMCs in 50 mL of X-VIVO complete medium, mix thoroughly by pipetting, and then add to a T225 flask;

[0312] 2) 37℃, 5% CO 2 Let it stand in the incubator for at least 6 hours, then carefully turn the culture flask over.

[0313] 3) After 2 hours, carefully stand the culture flask upright with its side as the base. In a biosafety cabinet, pour the cell suspension along the side into a new T225 flask and place it at 37°C with 5% CO2. 2 Incubator cultivation;

[0314] 4) Carefully flip the culture flask every 2 hours. Once both sides are fully covered, replace it with a new T225 flask. After completing 2-3 T225 flasks, observe the proportion of adherent cells under a microscope. When the proportion of adherent cells is <10%, take a small number of cells for CD3 detection. + >90% can then undergo T cell activation;

[0315] 2.6.3 T cell activation

[0316] 1) Collect the CD3 obtained in the previous step + >90% of T cells, centrifuged at 1500 rpm for 5 min;

[0317] 2) Carefully discard the supernatant, resuspend the cell clumps in an appropriate amount of X-VIVO complete culture medium, mix thoroughly, and then count the cells.

[0318] 3) Calculate the required CD3 / CD28 Dynabeads volume based on the number of cells, i.e., 30% × total cell number / CD3 / CD28 Dynabeads density, and centrifuge the cell suspension at 1500 rpm for 5 min.

[0319] 4) Cleaning CD3 / CD28 Dynabeads: Prepare a 15mL centrifuge tube, add 1mL PBS, then add the CD3 / CD28 Dynabeads calculated in the previous step, and place it on a magnetic rack to stand for 5 minutes;

[0320] 5) Remove 15 mL of PBS from the centrifuge tube and discard it (keep the 15 mL centrifuge tube on a magnet);

[0321] 6) Remove the 15mL centrifuge tube from the magnetic rack. You can see the iron-red CD3 / CD28 Dynabeads on the tube wall.

[0322] 7) Soak the cell clumps in X-VIVO complete medium at a concentration of 4-6 × 10⁻⁶. 6 / mL resuspended;

[0323] 8) Add the cell suspension to the washed CD3 / CD28 Dynabeads, mix well by pipetting, and incubate on a rotating shaker for 30 min to ensure that the cells are in full contact with the CD3 / CD28 Dynabeads;

[0324] 9) After rotation, place the 15mL centrifuge tubes into the magnetic rack and let stand for 5 minutes;

[0325] 10) Be careful not to abandon Shangqing;

[0326] 11) Remove the 15mL centrifuge tube and use X-VIVO medium at a CD3 / CD28 Dynabeads ratio of 1-3 × 10⁻⁶. 6 Resuspend the precipitate in mL and incubate in a T25 flask for at least 8 hours. Name it D0 at this point.

[0327] 2.6.4 Lentiviral transfection

[0328] 1) Collect the activated T cells obtained in the previous step and centrifuge at 1500 rpm for 5 min;

[0329] 2) After resuspending the cells in an appropriate amount of X-VIVO complete culture medium, perform cell counting;

[0330] 3) Take 1×10 6 Activate T cells, centrifuge at 1500 rpm for 5 min, and use the remaining cells as control T cells (CT);

[0331] 4) Carefully discard the supernatant, add fourth-generation CD19-CAR or CD19-CAR-THEMIS lentivirus at 30 moi (multiplicity of infection), bring the system to 200 μL with X-VIVO blank medium, add 0.2 μL of polybrene (8 mg / mL) to one well of a 96-well plate, and carefully seal the 96-well plate with sealing film;

[0332] 5) Centrifuge at 1200g, 32℃ for 1.5h;

[0333] 6) After centrifugation, centrifuge at 37℃ and 5% CO2. 2 Incubate for 4 hours;

[0334] 7) Centrifuge at 1500 rpm for 5 min, carefully discard the supernatant, resuspend the cells in 2 mL of X-VIVO complete medium in a 24-well cell culture plate and culture them, naming them D1.

[0335] 2.6.5 CAR-T cell culture

[0336] 1) On day 3, the transduction efficiency was detected by flow cytometry, and 8 mL of X-VIVO medium was added before transferring the cells to a T25 flask for further culture.

[0337] 2) After thoroughly mixing the cell suspension by pipetting on day 4, transfer it to a 15 mL centrifuge tube, place it on a magnetic rack and let it stand for 5 min to remove CD3 / CD28 Dynabeads. Collect the supernatant to obtain the desired cells. CT cells are processed in the same way.

[0338] 3) During the D3-10 culture period, add an equal volume of X-VIVO complete culture medium to the existing culture system every other day. Depending on the culture system, transfer the medium to T75 and T175 bottles in sequence, or freeze some of it for later use.

[0339] 4) D11-14 are used for in vitro or animal experiments.

[0340] 2.7 Electroporation CRISPR / Cas9 Gene Editing

[0341] 2.7.1 Preparations before electro-spinning

[0342] 2.7.1.1 sgRNA Preparation

[0343] After briefly centrifuging 1.5 nmol sgRNA dry powder tubes, add 10 μL of DEPC water to make the final

[0344] The concentration is 150 pmol / μL.

[0345] All sgRNAs used in this study were purchased from GenScript (https: / / www.genscript.com.cn / ), and their sequences are as follows:

[0346] Table 9

[0347]

[0348] 2.7.1.2 Cell Preparation

[0349] 1) Change the culture medium (X-VIVO complete medium) for cells every 2 days;

[0350] 2) After ensuring the cells are in good growth condition, remove a portion of the cells and transfer them to a new culture flask as cells to be transfected, adjusting the density to 1×10^ 5 cells / mL;

[0351] 3) When the cell density reaches 4-5 × 10^ 5 Electroporation can be performed at a rate of cells / mL;

[0352] 4) On the day of electroporation, prepare a 12-well plate, add 200 μL of blank opti-MEM to each sample, and preheat it in an incubator;

[0353] 5) Prepare one sterile EP tube, and prepare the ionization solution according to the number of samples (20 μL / sample). Add the supplement reagent to the solution reagent at a ratio of 1:4.5.

[0354] 6) Count the cells to be electroporated using a flow cytometer and calculate the cell density;

[0355] 7) Using 1×10^ for each sample 6 Calculate the number of cells and extract the required cell volume;

[0356] 8) Centrifuge at 300g for 5 minutes at room temperature, and aspirate the supernatant after centrifugation;

[0357] 9) Repeat step 8) once more with PBS preheated to 37°C.

[0358] 2.7.1.3 Preparation of Ribonucleoprotein (RNP) Complex

[0359] 1) Based on the number of samples to be transfected, slowly add Cas9 protein to sgRNA in an RNase-free EP tube. Specific dosage:

[0360] Table 10

[0361]

[0362] 2) Incubate at room temperature for 10 minutes.

[0363] 2.7.2 Electrical Transfer

[0364] 1) On the day of electroporation, turn on the electroporator and set the “nucleocuvette” type and “celltypeprogram” to be used;

[0365] 2) Using the required amount of 17 μL of ionization solution for each sample, gently resuspend the cells in the prepared ionization solution, being careful not to generate air bubbles;

[0366] 3) Prepare an electroporation system by adding the RNP complex according to the table below:

[0367] Table 11

[0368]

[0369] 4) Carefully add the prepared electroporation system into the electrode strips, and gently tap to ensure the sample fills the bottom of the container;

[0370] 5) Place the electrode strips into the electroporator. Immediately after electroporation, resuspend the cells in 200 μL of preheated blank Opti-MEM into a 24-well plate and incubate at 37°C with 5% CO2. 2 Incubator;

[0371] 6) After standing for 20 minutes, add 500 μL of preheated X-VIVO complete medium and incubate at 37°C with 5% CO2. 2 The incubator was used for subsequent experimental verification.

[0372] 2.8 Flow cytometry detection

[0373] 1) Collect 1×10 5 -1×10 6 Centrifuge the cells to be tested at 1500 rpm for 5 min and carefully discard the supernatant;

[0374] 2) Wash twice with 500μL of flow cytometry solution;

[0375] 3) Preparation of staining system: 50 μL of flow cytometry wash buffer + 0.25 μL of flow cytometry antibody for each sample. If multiple antibodies need to be stained at the same time, they can be added to the same 50 μL of flow cytometry wash buffer for simultaneous staining after the fluorescence spectra of the antibodies are staggered.

[0376] 4) Add 50 μL of the staining system to the cell clump, mix well by pipetting, and resuspend the cells thoroughly;

[0377] 5) Incubate at 4℃ in the dark for 20 minutes;

[0378] 6) Add 500 μL of flow cytometry wash buffer and centrifuge at 1500 rpm for 5 min;

[0379] 7) Repeat step 6) and wash again;

[0380] 8) After resuspending the cell clumps in 200 μL of flow cytometry wash buffer, add 1 μL of 7-AAD and perform analysis after 5 min.

[0381] 2.9 Western blot (WB)

[0382] 2.9.1 Cell protein extraction and quantitative detection

[0383] 1) Collect 1×10 6 Transfer cells to EP tubes, centrifuge at 1000g for 5 min at room temperature, and discard the supernatant;

[0384] 2) Wash twice with pre-cooled PBS, 1000g, 5min, then discard the supernatant;

[0385] 3) Add RIPA lysis buffer containing 1% phenylmethanesulfonyl fluoride (PMSF) to the cell pellet, shake to mix, and then place on ice for lysis for 30 min.

[0386] 4) Centrifuge at 13000g, 4℃ for 15 minutes, and discard the supernatant;

[0387] 5) Take 10 μL of supernatant for protein concentration measurement using the BCA method;

[0388] 6) Add 0.25 times the volume of 5× protein loading buffer to the remaining protein supernatant in the EP tube, vortex to mix, heat at 100°C for 10 min in a metal bath, briefly separate, and place on ice for later use or store in a -80°C freezer.

[0389] 2.9.2 WB Detection

[0390] 1) Preparation of SDS-polyacrylamide gel: Install the gel plate on the special gel preparation rack, check the airtightness, and prepare the separating gel and the stacking gel according to the formula in Table 1.3.1;

[0391] 2) Install the gel plate: Place the prepared gel plate into the electrophoresis tank, add 1× electrophoresis solution to submerge the gel plate, and carefully remove the comb;

[0392] 3) Sample loading: Accurately add the adjusted sample volume and protein marker into the sample wells one by one;

[0393] 4) Electrophoresis: Start with a constant voltage of 80V for about 25 minutes. When the dye enters the separating gel and forms a straight line, or when the marker disperses, increase the voltage to 120-140V until the bromophenol blue reaches the bottom of the separating gel and then stop the electrophoresis.

[0394] 5) Transfer: Pre-cool the prepared 1× transfer solution on ice. Activate the polyvinylidene fluoride (PVDF) membrane by immersing it in methanol for 10-15 seconds. Then, arrange the membrane in a "sandwich" structure, from positive to negative electrode: positive electrode, one layer of sponge, two layers of filter paper, PVDF membrane, gel, two layers of filter paper, one layer of sponge, and finally the negative electrode. Ensure all air bubbles are removed. After assembling the transfer clamp, place the transfer apparatus in an ice bath, then connect the power supply and transfer at a constant current of 220mA for 90-120 minutes.

[0395] 6) Blocking: After the transfer is complete, remove the PVDF membrane and immerse it in 1×TBST solution containing 5% skim milk powder. Incubate slowly on a shaker at room temperature for 40-50 minutes. After the transfer, wash the membrane three times with the 1×TBST solution, 10 minutes each time.

[0396] 7) Primary antibody incubation: Cut the membrane according to the position of the band, and then put the cut membrane into 50mL centrifuge tubes containing primary antibody solution, close to the tube wall, and incubate overnight on a shaker at 4℃ to allow the antigen and antibody to fully bind.

[0397] 8) Secondary antibody incubation: Remove the PVDF membrane and wash it three times with 1×TBST, 10 min each time. Place it in a 50 mL centrifuge tube containing the secondary antibody solution, gently shake on a shaker, and incubate at room temperature for 40-50 min. After incubation, wash it four times with 1×TBST, 10 min each time.

[0398] 9) Development: Prepare the development solution in advance and store it away from light. After thoroughly mixing the strip and development solution, expose the image. Set the machine to continuous, interval exposure and save the high-resolution original image.

[0399] 2.10 Luciferase Cytotoxicity Assay Based on Fluorescent Substrate Method

[0400] 1) Calculate the number of target cells and effector cells: seed 1×10⁻⁶ cells per well. 4 For target cells, four gradient effector-to-target ratios were set (20:1, 10:1, 5:1, 2.5:1), with each gradient calculated in 5 replicates. The required number of target cells was 1 × 10⁻⁶. 4 ×[5 (complex holes) × 4 (gradients) × 2 (groups) + 5 (minimum lethal holes) + 5 (maximum lethal holes)] = 5 × 10 5 Resuspend the target cells in 100 μL of X-VIVO complete medium per well, requiring a total medium volume of 5 mL; the required number of effector cells is 1 × 10⁻⁶. 4 ×20 (maximum efficiency target ratio is 20:1) × 5 (duplicate wells) × 2 (gradient dilution) = 2 × 10 6 The required culture medium volume for cell resuspension is 1 mL;

[0401] 2) Take the target cells and effector cells according to the calculated cell volume above, and resuspend the target cells and effector cells in 10% Gibco X-VIVO medium of the calculated volume above.

[0402] 3) Effector cell gradient dilution: Prepare three 15mL centrifuge tubes and add 500μL of 10% Gibco X-VIVO medium to each tube, naming them 10:1, 5:1, and 2.5:1 respectively. Take 500μL of the resuspended effector cells (20:1) and add it to the 10:1 tube. Mix thoroughly, then add 500μL to the 5:1 tube, mix thoroughly, and then add 500μL to the 2.5:1 tube. Mix thoroughly by pipetting to create a concentration gradient.

[0403] 4) Plate planting: Seed 100 μL of target cells into a 96-well opaque white microplate, and then seed effector cells of each dilution gradient into the corresponding wells at 100 μL / well.

[0404] 5) Add 100 μL of culture medium to the minimum kill well (Kmin), and add 2.5 μL of 10% Triton-X-100 and 97.5 μL of culture medium to each of the maximum kill wells (Kmax);

[0405] 6) 37℃, 5% CO 2 Incubate for 4 hours;

[0406] 7) After the culture is complete, centrifuge at 400g for 5 minutes and carefully discard the supernatant;

[0407] 8) Add 100 μL of potassium fluorescein (1.5 mg / mL) to each well, mix thoroughly, and incubate at 37°C in the dark for 10 min;

[0408] 9) Detect fluorescence intensity using a fluorescence microplate reader;

[0409] 10) Killing efficiency calculation method: Kmin-K (fluorescence value of a certain well) / Kmin-Kmax.

[0410] 2.11 Cytokine Detection

[0411] This experiment used the Human Cytokine Flex Kit (BD Biosciences) to detect cytokines in the supernatant via flow cytometry bead array (CBA). The specific steps are as follows:

[0412] 1) Prepare the standard curve according to the instructions;

[0413] 2) Prepare the Beads mixture: Calculate the number of samples to be tested, add 5 μL of each type of Bead for each sample, and mix the A1-A6 Beads together;

[0414] 3) Prepare several flow cytometry tubes. Add 25 μL of the mixed Beads mixture to each tube, then add 25 μL of the sample to be tested, and finally add 25 μL of PE detection reagent. Mix thoroughly and incubate in the dark for 3 hours.

[0415] 4) Add 500 μL of Wash Buffer to each tube and centrifuge at 300g for 5 min;

[0416] 5) Carefully discard the supernatant, resuspend the cells and magnetic beads in 200 μL Wash Buffer, and run the instrument under the same voltage and other conditions as the standard curve.

[0417] 6) Use FCAP (v3.0) software to calculate the concentration of each cytokine in each sample.

[0418] 2.12 CFSE proliferation experiment

[0419] 1) Collect target cells, centrifuge at 1500 rpm for 5 min, and then rinse with PBS at 1×10⁻⁶. 7 Resuspend in 1 mL, add 1.2 μL mitomycin, and incubate at 37°C for 3 h;

[0420] 2) Collect effector cells, centrifuge at 1500 rpm for 5 min, and then rinse with PBS at 1×10⁻⁶. 6 Resuspend cells at 1 μL / mL, add 1 μL CFSE dye (5 mM), and incubate at 37°C in the dark for 20 min;

[0421] 3) After the effector cells and target cells have been treated, wash the cells twice with PBS, and then rinse the cells with 10% PBS.

[0422] Gibco X-VIVO medium resuspended to 5 × 10⁻⁶ 5 / mL, seed 100μL of effector cells and target cells into each well, i.e., an effector-to-target ratio of 1:1, with 5×10⁶ effector cells and 5×10⁶ target cells. 4 / well, 200μL system plate;

[0423] 4) Collect cells at 0h, 24h, 48h, 72h, and 96h to detect CFSE fluorescence intensity. During the culture period, supplement with 10% Gibco X-VIVO medium according to cell density, and transfer them into 12-well plates, 6-well plates, and T25 cell culture flasks for culture in sequence.

[0424] 2.13 In vitro repeated antigen stimulation experiment

[0425] 1) Using a 1:1 effective-to-target ratio, take 5 × 10⁻⁶ samples each. 5 Tumor cells (pretreated with mitomycin C) and effector cells were co-cultured at 37°C for 24 hours.

[0426] 2) After incubation overnight, collect the supernatant and re-inoculate the same number of mitomycin-treated tumor cells into the incubation system and culture for another 24 hours.

[0427] 3) Repeat steps 2);

[0428] 4) Collect CAR-T cells daily for flow cytometry analysis. The supernatant is analyzed using the Human Cytokine Flex Kit (BD Biosciences) via flow cytometry bead array (CBA), following the manufacturer's instructions.

[0429] 2.14 Animal Experiments

[0430] This study was approved by the Animal Ethics Committee of the Second Affiliated Hospital of Zhejiang University School of Medicine. On day 3 (D-3), female NSG mice aged 6-8 weeks were injected via the tail vein with 5×10⁻⁶ mg / L of animal protein. 4 A tumor model was established using Raji-luc-GFP. On day D-1, 3 mg of luciferin potassium salt was injected intraperitoneally. Ten minutes later, the tumor-bearing mice were confirmed using an IVIS lumina II small animal in vivo imaging system. The mice were then randomly divided into two groups (7×19 CAR-T and THEMIS-7×19 CAR-T), with 5 mice in each group. On day D0, 5×10 mg of luciferin potassium salt was administered via the tail vein. 5 7×19-CAR-T and THEMIS-7×19-CAR-T cells were used for treatment. Tumor growth in mice was then monitored twice weekly using quantitative fluorescence, and mouse survival time was observed.

[0431] 2.15 Statistical Analysis

[0432] All data in this study were statistically analyzed using Graphpad Prism (version 10). Normality was tested for all data using the Shapiro-Wilk test, and subsequent statistical tests were selected based on whether normality was met. For normally distributed data, independent samples t-tests were used for comparisons between two groups. For non-normally distributed data, the Mann-Whitney U test was used. Paired t-tests were used for comparisons of different conditions within the same group. For comparisons among multiple groups, one-way ANOVA and the Bonferroni post-hoc test were used for normally distributed data. For non-normally distributed data, the Kruskal-Wallis test and the Dunn post-hoc test were used. P < 0.05 was considered statistically significant, * for P < 0.05, ** for P < 0.01, *** for P < 0.001, **** for P < 0.0001, and ns for P > 0.05.

[0433] 3 Experimental Results

[0434] 3.1 Functional changes of fourth-generation CAR-T cells after THEMIS knockout

[0435] 3.1.1 Knockout of THEMIS does not affect CAR expression in fourth-generation CAR-T cells.

[0436] In the first part of our study, our multi-omics analysis of fourth-generation CAR-T cell products suggested that the T cell subset marked by THEMIS is a key subset for maintaining the long-term efficacy of fourth-generation CAR-T cells. External databases also demonstrated high expression of THEMIS in the CR group, indicating that THEMIS may be a key factor determining the efficacy of CAR-T. Our team previously constructed fourth-generation CAR-T cells, namely 7×19CAR-T (Figure 3-1A), using the CD19 monoclonal antibody scFv as the antigen-binding domain, 4-1BB as the co-stimulatory domain, and introducing cytokines and chemokines (IL-7 and CCL19), and completed clinical trials. To verify the impact of THEMIS on the function of fourth-generation CAR-T cells, we also constructed 7×19CAR-T cells as the research object in this study. We successfully prepared 7×19CAR-T cells through lentiviral transfection, with a CAR content of over 70% (Figure 3-1B), and used untransfected activated T cells as the control group.

[0437] We used electroporation combined with CRISPR-Cas9 gene editing technology to knock out the THEMIS gene in 7×19 CAR-T cells on days 6-8, with the AAVS1 safe harbor locus knockout group serving as a control. We verified the knockout efficiency at the transcriptional and translational levels on days 11-14 (Figure 3-1C). To further evaluate the effects of electroporation and THEMIS knockout on CAR expression, we measured and compared the CAR ratio in the AAVS1 KO group and the THEMIS KO group (Figure 3-1D). The results showed that, compared with the negative control group, electroporation and THEMIS knockout did not affect CAR expression (P>0.05).

[0438] 3.1.2 The CD8 / CD4 ratio of fourth-generation CAR-T cells was downregulated after THEMIS knockout.

[0439] Furthermore, we further evaluated the changes in the CD8 / CD4 ratio in 7×19 CAR-T cells after THEMIS knockout (Figure 3-2A). The results showed that the CD8 / CD4 ratio was downregulated in the THEMIS knockout group compared with the control group (P<0.05) (Figure 3-2B), suggesting that THEMIS may be related to maintaining CD8 / CD4 homeostasis in T cells.

[0440] 3.1.3 The proliferation and expansion capacity of fourth-generation CAR-T cells with THEMIS knockout after antigen stimulation is limited.

[0441] To assess the proliferation of 7×19 CAR-T cells after THEMIS knockout under both antigen-free and antigen-stimulated conditions, we labeled 7×19 CAR-T cells in the AAVS1 KO group and the THEMIS KO group with CFSE. The antigen-stimulated groups were then co-incubated with CD19-3T3 cells at a 1:1 effector-target ratio. The CFSE fluorescence intensity of the two groups was monitored at different time points. As shown in Figure 3-3A, there was no difference in cell proliferation between the two groups under antigen-free conditions. However, 96 h after antigen stimulation, the proliferation of 7×19 CAR-T cells in the THEMIS KO group was slower than that in the AAVS1 KO group (peak right-biased).

[0442] To further simulate the tumor antigen-stimulated environment, we co-incubated the two cell groups with mitomycin C-treated Raji cells at a 1:1 effector-to-target ratio and counted the cells in both groups daily. As shown in Figure 3-3B, there was no significant difference in the total cell count between the two groups on days 1-2 after co-incubation. However, from days 3-5, the difference in the total cell count between the THEMIS KO group and the AAVS1 KO group gradually increased, with the most significant difference on day 5 (P<0.001).

[0443] As shown above, the proliferation capacity of 7×19 CAR-T cells after THEMIS knockout was limited after antigen stimulation.

[0444] 3.1.4 THEMIS knockout does not affect the short-term tumor killing effect and cytokine secretion of fourth-generation CAR-T cells.

[0445] To further investigate the effect of THEMIS knockout on the killing of B-cell lymphoma cells by 7×19 CAR-T cells, we selected Jeko-1 and Raji cell lines as target cells for evaluation. We overexpressed luciferase-P2A-GFP in both B-cell lymphoma lines and constructed Jeko-1-luc-GFP and Raji-luc-GFP cell lines expressing luciferase and GFP genes via flow cytometry for luciferase killing experiments. We co-incubated 7×19 CAR-T cells from the AAVS1KO and THEMIS KO groups with different target cells at different gradient effector-target ratios for 4 hours and then tested their killing ability. The results showed almost no difference in killing effect between the two groups, even at high effector-target ratios (20:1 or 10:1), the difference in the killing rate ratio between the two groups was small (Figure 3-4A). Meanwhile, we used the Multiplex Bead Assay kit based on flow cytometry to detect cytokines in the supernatant after tumor cell killing in the two groups at a high target ratio (20:1). As shown in Figures 3-4B, there was no difference in the secretion levels of IL-2, IL-4, IL-6, TNF-α, and IFN-γ in the supernatant after 4 hours of tumor cell killing between the two groups (P>0.05). Only the secretion level of IL-10 was higher in the THEMIS KO group than in the AAVS1 KO group (P<0.05).

[0446] From the above, we found that the knockout of THEMIS had virtually no significant effect on the short-term tumor killing effect of 7×19 CAR-T cells or the level of cytokine secretion.

[0447] 3.1.5 Knockout of THEMIS limited the long-term tumor-killing ability of fourth-generation CAR-T cells.

[0448] In the preceding section, we found that THEMIS knockout had almost no impact on the short-term killing function of 7×19 CAR-T cells against B-cell lymphoma. However, considering that the eventual relapse of treated patients is closely related to the long-term killing function of CAR-T cells, we further evaluated the long-term tumor-killing ability of 7×19 CAR-T cells after THEMIS knockout. We selected CD19-3T3 cells as target cells and co-incubated 7×19 CAR-T cells from the AAVS1 KO group and the THEMIS KO group with them at low effector-target ratios (1:2 and 1:1), and monitored long-term killing function using the RTCA system. As shown in Figure 3-5A, under the effector-target ratio of 1:2, there was no significant difference in the target cell killing ability between the two groups within 10 hours of co-incubation (within 20 hours of the start of the experiment). With the co-incubation time extended to 20 hours, we found that the killing ability of 7×19 CAR-T cells in the THEMIS KO group gradually weakened, while the AAVS1 KO group maintained a sustained killing effect, with a maximum difference in killing ability exceeding 30% (P<0.0001). Similarly, we obtained consistent results under the effector-target ratio of 1:1 (Figure 3-5B, P<0.0001). These results indicate that although the knockout of THEMIS does not affect the short-term killing ability of 7×19 CAR-T cells, it significantly limits their long-term tumor-killing function.

[0449] 3.1.6 After THEMIS knockout, the ability of fourth-generation CAR-T cells to respond to repeated antigen stimulation is weakened.

[0450] In the above experiments, we have already shown that THEMIS knockout weakens the long-term killing ability of 7×19 CAR-T cells. To further investigate the effects of THEMIS knockout on the memory, exhaustion, and apoptotic phenotypes of 7×19 CAR-T cells under persistent antigen stimulation, we administered multiple antigen stimulations to the knockout group and the control group, and used flow cytometry to detect the memory (CD45RO, CD62L), exhaustion (TIGIT, TIM3), and apoptotic phenotypes of the two groups. We co-incubated 7×19 CAR-T cells from the AAVS1 KO group and the THEMIS KO group with mitomycin C-treated Raji cells at a 1:1 effector-target ratio, and detected the relevant phenotypes of the two groups after 24 hours. The same number of tumor cells were then added again, and the stimulation was repeated three times. The results showed that, after the first antigen stimulation, the memory T cell subset (CD45RO, CD62L) was significantly different between the two groups. + CD62L +There was no significant difference in the proportion of CAR-T cells (P>0.05); however, after three rounds of tumor antigen stimulation, the proportion of the 7×19 CAR-T cell memory T cell subset in the THEMIS KO group was significantly lower than that in the AAVS1 KO group (P<0.05, Figure 3-6A). Furthermore, after three rounds of tumor antigen stimulation, the proportion of the exhaustion-associated T cell subset (TIGIT) in the THEMIS KO group increased. + Or TIM3 + The proportion of CAR-T cells (P<0.05, Figure 3-6B) and the apoptosis rate were significantly higher than those of the AAVS1 KO group (P<0.01, Figure 3-6C, D), suggesting that after THEMIS knockout, the 7×19 CAR-T cells had a weakened ability to form memory stem T cells under repeated tumor antigen stimulation, and were more prone to exhaustion and apoptosis.

[0451] 3.1.7 THEMIS knockout will cause excessive secretion and depletion of fourth-generation CAR-T cytokines.

[0452] Previous studies have reported that the THEMIS-SHP1 complex can reduce cytokine secretion to some extent. Therefore, we hypothesized that the increased likelihood of exhaustion and apoptosis in 7×19 CAR-T cells induced by THEMIS knockout under repeated tumor antigen stimulation might be related to excessive cytokine secretion. To investigate this, we collected supernatants from both the first (Stim1) and third (Stim3) antigen stimulation groups and detected six inflammation-related cytokines (IL-2, IL-4, IL-6, IL-10, TNF, and IFN-γ). As shown in Figure 3-7A, upon initial stimulation with tumor antigens, the secretion levels of IL-2 (P<0.0001), IL-4 (P<0.01), IL-6 (P<0.01), IL-10 (P<0.0001), TNF (P<0.01), and IFN-γ (P<0.0001) in 7×19 CAR-T cells of the THEMIS KO group were all higher than those of the AAVS1 KO group.

[0453] It is noteworthy that, as shown in Figure 3-6D, the THEMIS KO group exhibited a higher rate of 7×19 CAR-T cell exhaustion and apoptosis after three antigen stimulations. Consistent with this, we found that after three antigen stimulations, compared to the AAVS1 KO group, the secretion of IL-2 (P<0.001), IL-4 (P<0.0001), IL-6 (P<0.01), IL-10 (P<0.01), TNF (P<0.01), and IFN-γ (P<0.0001) in the THEMIS KO group of 7×19 CAR-T cells was significantly reduced (Figure 3-7B). The secretion levels of IL-2 (1425.0±40.0 vs 2430.8±433.7, P<0.05) and IL-4 (38.6±5.3 vs 71.4±5.3, P<0.001) were even lower than those in the AAVS1 group. KO group (Figure 3-7A).

[0454] As shown above, we found that the knockout of THEMIS causes excessive secretion of inflammatory cytokines during the initial immune response of 7×19 CAR-T cells, and excessive cytokine secretion may also lead to premature depletion and apoptosis in response to repeated antigen stimulation.

[0455] 3.2 Functional changes in four generations of CAR-T cells after THEMIS overexpression

[0456] 3.2.1 Construction and preparation of 7×19 CAR-T cells overexpressing THEMIS

[0457] In the previous section, we verified that THEMIS knockout downregulates the CD8 / CD4 ratio in 7×19 CAR-T cells and limits their proliferation after antigen stimulation. We also found that while THEMIS knockout does not affect the short-term tumor-killing ability of 7×19 CAR-T cells, it significantly limits their long-term killing effect and reduces their ability to respond to repeated antigen stimulation. Under repeated antigen stimulation, THEMIS-KO 7×19 CAR-T cells exhibit impaired memory stem T cell formation and excessive cytokine secretion under initial stress, leading to premature exhaustion and apoptosis. Therefore, THEMIS is closely related to the differentiation, proliferation, and sustained anti-tumor activity of fourth-generation CAR-T cells. Thus, we plan to construct 7×19 CAR-T cells overexpressing THEMIS, namely THEMIS-7×19CAR-T, to further explore the synergistic effect of this gene on the anti-B-cell lymphoma activity of fourth-generation CAR-T cells.

[0458] In this study, using 7×19CAR as a control, we linked the coding sequence (CDS) of the THEMIS protein downstream of the CD3ζ signaling domain of CAR via the alternative splicer T2A. A schematic diagram of the THEMIS-7×19CAR structure is shown in Figure 4-1A. After peripheral blood underwent gradient density centrifugation and CD3 magnetic bead sorting, we obtained T cells. These cells were then activated by co-incubation with CD3 / CD28 magnetic beads for 12-24 hours. On day 2, activated T cells were separated using a magnetic bead sorting column. Activated T cells were transfected with THEMIS-7×19CAR lentivirus containing VSVG envelope protein. On day 5, the magnetic beads were removed, and transduction efficiency was measured. As shown in Figure 4-1B, the transduction efficiency of both THEMIS-7×19CAR and 7×19CAR reached over 50%. To further clarify the overexpression of THEMIS in THEMIS-7×19CAR-T cells, we performed fixation and perforation staining, used a THEMIS-specific antibody to bind to the THEMIS protein in the cells, and then used a specific fluorescent secondary antibody for labeling and flow cytometry detection. The results showed that the expression level of THEMIS protein in T cells transfected with THEMIS-7×19CAR was higher than that in the control group (P<0.05, Figure 4-1C).

[0459] 3.2.2 Overexpression of THEMIS upregulated the CD8 / CD4 ratio in fourth-generation CAR-T cells

[0460] Similarly, we used flow cytometry to detect CD8+ in THEMIS-7×19 CAR-T cells and the control group. + T and CD4 + The proportion of T cells (Figure 4-2). The results showed that the CD8 / CD4 ratio was upregulated in THEMIS-7×19 CAR-T cells compared with the control group (P<0.05), which clarified that THEMIS is associated with T cell differentiation.

[0461] 3.2.3 Overexpression of THEMIS enhances the proliferation capacity of fourth-generation CAR-T cells after antigen stimulation.

[0462] In section 3.1.3, we found that the knockout of THEMIS cells limited the proliferation of 7×19CAR-T cells after antigen stimulation. Therefore, to further clarify the relationship between THEMIS and the proliferation of 7×19CAR-T cells, we measured the proliferation of THEMIS-7×19CAR-T cells and the control group (7×19CAR-T) in the same manner, both without and under antigen stimulation. As shown in Figure 4-3A, there was no difference in cell proliferation between the two groups without CD19-3T3 antigen stimulation, while the antigen-stimulated group showed stronger proliferation of THEMIS-7×19CAR-T cells (i.e., the THMEIS OE group in the figure) than the control group after 96 h (peak left-skewed).

[0463] Simultaneously, we co-incubated both groups of cells with mitomycin C-treated Raji cells to simulate a real tumor antigen stimulation environment and counted them daily. As shown in Figure 4-3B, there was no significant difference in the total number of cells between the two groups on day 1 (P>0.05), but from day 3 to 5, the difference in the total number of cells between the overexpression group and the control group gradually became significant (P<0.01).

[0464] From the above, we have clearly demonstrated that THEMIS overexpression can promote the proliferation and expansion of 7×19 CAR-T cells after antigen stimulation, and also proved that THEMIS expression is related to the proliferation of fourth-generation CAR-T cells.

[0465] 3.2.4 THEMIS overexpression mainly enhances the long-term tumor-killing ability of fourth-generation CAR-T cells.

[0466] In section 3.1, we found that THEMIS knockout primarily limited the long-term tumor-killing ability of fourth-generation CAR-T (7×19CAR-T) cells. To further verify the relationship between THEMIS and the killing function of 7×19CAR-T cells, we also evaluated the short-term and long-term killing functions of 7×19CAR-T cells in the THEMIS overexpression group and the control group. Consistent with section 3.1.4, we used Jeko-1-luc-GFP and Raji-luc-GFP cell lines as target cells, and co-incubated the two groups of cells with different target cells at different gradient effector-target ratios for 4 hours before detecting the killing ability. As shown in Figure 4-4A, there was almost no difference in short-term killing effect between the two groups (P>0.05). Even at the high-efficiency effect target ratio (20:1) in the Jeko-1-luc-GFP group, there was a difference in killing ability (P<0.01), but the absolute killing rate difference between the two groups was less than 5%.

[0467] Similarly, we used CD19-3T3 cells as target cells and co-incubated THEMIS-7×19CAR-T cells with 7×19CAR-T cells at an effector-to-target ratio of 1:1, and monitored long-term killing function using the RTCA system. As shown in Figure 4-4B, there was no significant difference in target cell killing ability between the two groups within 10 hours of co-incubation (within the first 20 hours of the experiment). However, with the extension of co-incubation time, THEMIS-7×19CAR-T cells maintained strong killing ability, while the tumor cell killing effect of the control group gradually decreased compared to the overexpression group, with the most significant difference observed after 30 hours of co-incubation (P<0.0001). These results demonstrate that THEMIS overexpression mainly enhances the long-term tumor killing ability of fourth-generation CAR-T cells rather than the short-term killing ability, and also verify the important role of THEMIS in the sustained tumor killing effect of fourth-generation CAR-T cells.

[0468] 3.2.5 THEMIS overexpression enhances the ability of fourth-generation CAR-T cells to respond to sustained antigen stimulation.

[0469] Furthermore, we investigated the effects of THEMIS overexpression on the memory, exhaustion, and apoptosis phenotypes of fourth-generation CAR-T cells under prolonged antigen stimulation. We subjected both cell groups to three rounds of tumor antigen stimulation and used flow cytometry to detect the memory (CD45RO, CD62L), exhaustion (TIGIT, TIM3), and apoptosis phenotypes of the two cell groups. Figures 4-5A and 4-5D show that there was no significant difference in the proportion of memory T cell subsets between the two groups after the first antigen stimulation (P>0.05); however, after three rounds of tumor antigen stimulation, the proportion of memory T cell subsets in the overexpression group was significantly higher than that in the control group (P<0.05), while the proportion of exhaustion-related T cell subsets (P<0.05, Figure 4-5B) and the apoptosis rate (P<0.001, Figure 4-5C) were significantly lower in the overexpression group than in the control group. These results indicate that THEMIS overexpression promotes the formation of memory stem T cells in fourth-generation CAR-T cells under repeated tumor antigen stimulation, enhancing their resistance to exhaustion and apoptosis.

[0470] 3.2.6 Overexpression of THEMIS can effectively control the secretion of cytokines by fourth-generation CAR-T cells.

[0471] In section 3.1, we found that the knockout of THEMIS cells led to excessive cytokine secretion in fourth-generation CAR-T cells under repeated stimulation by tumor antigens, resulting in cell exhaustion. To further verify the relationship between THEMIS and cytokine secretion in fourth-generation CAR-T cells, we analyzed the cytokines in the supernatant after the first and third antigen stimulation in the overexpression group and the control group. As shown in Figure 4-6A, under the first antigen stimulation, the secretion levels of IL-2 (P<0.01), IL-4 (P<0.001), IL-6 (P<0.05), TNF (P<0.0001), and IFN-γ (P<0.0001) in THEMIS-7×19 CAR-T cells were all lower than those in the control group. However, as demonstrated in section 3.2.4, there was no significant difference in short-term tumor-killing ability between the two groups, suggesting that the control group was in a state of excessive cytokine secretion.

[0472] In Figure 4-6A, we further found that after three antigen stimulations, except for IL-10, the overexpression group was still able to maintain a certain level of cytokine secretion. The degree of cytokine secretion depletion was significantly lower than that of the control group (Figure 4-6B), especially IL-2 (P<0.0001), TNF (P<0.0001) and IFN-γ (P<0.0001). After multiple antigen stimulations, the secretion level of the control group had significantly decreased and was lower than that of the overexpression group.

[0473] As shown above, we have demonstrated that overexpression of THEMIS can keep the secretion of inflammatory cytokines during the initial immune response of fourth-generation CAR-T cells under control, and further illustrate the close relationship between the THEMIS gene and CAR-T cytokine secretion.

[0474] 3.2.7 Overexpression of THEMIS can enhance the in vivo tumor-killing ability of fourth-generation CAR-T cells.

[0475] In the experiments described above, we demonstrated that 7×19 CAR-T cells overexpressing THEMIS exhibited superior long-term tumor-killing ability in vitro and were able to secrete cytokines to a limited extent. To further evaluate whether THEMIS-7×19 CAR-T cells possess even better anti-tumor effects in vivo, we administered 5×10 CAR-T cells via tail vein injection. 4 A mouse model of lymphoma was established using Raji cells carrying the luciferase gene (Raji-luc-GFP). After successful model establishment was confirmed by fluorescence imaging analysis, the two groups of mice were injected with 5 × 10⁵ cells via the tail vein. 57×19CAR-T and THEMIS-7×19CAR-T cells were used, and tumor cell growth in mice was monitored by fluorescence imaging. Survival time was observed to assess the in vivo antitumor effect of THEMIS-7×19CAR-T cells (Figure 4-7A). Results showed that tumor signaling in the overexpression group was significantly lower than in the control group. Early tumor signaling was significantly suppressed in the overexpression group, but recurrence and progression occurred later (Figure 4-7B / 7C). However, the overall survival time of the overexpression group was significantly longer than that of the control group, with a statistically significant difference (P<0.01). Furthermore, the median survival time of the overexpression group was 64 days, longer than the 48 days of the control group.

[0476] discuss

[0477] The advent of CAR-T cell therapy has ushered in a new era in cancer treatment. However, although multiple clinical trials have shown that CAR-T cell therapy offers hope for a cure for patients with relapsed and / or refractory lymphoma, some patients still face the problem of relapse. In addition, the most common CAR-T cell-specific side effects in clinical trials, namely cytokine release syndrome and neurotoxicity, occur in 42-100% and 2-4% of patients, respectively. Severe cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) (≥ grade 3) can occur in 46% and 50% of treated patients, respectively. Therefore, further identification of the key factors for maintaining the long-term efficacy of CAR-T cell therapy, and thereby improving its efficacy and reducing its side effects, is crucial.

[0478] In the first part of this study, single-cell sequencing analysis identified the CD8+T_THEMIS subset and identified THEMIS, a key marker gene associated with T cell function and CAR-T cell efficacy. To further verify the regulatory role of this gene in the function of fourth-generation CAR-T cells, this part of the study used electroporation combined with CRISPR-Cas9 technology to knock out the THEMIS gene in 7×19 CAR-T cells. Furthermore, THEMIS-7×19 CAR-T cells overexpressing THEMIS were constructed to explore the mechanism by which this gene improves the long-term efficacy of fourth-generation CAR-T cells and reduces treatment side effects.

[0479] Previous studies have reported that in CAR-T cells with 4-1BB as a co-stimulatory domain, the THEMIS-SHP1 complex can be recruited to the CAR signaling body via the intracellular domain of 4-1BB, inhibiting CAR-CD3ζ phosphorylation. Knocking out THEMIS or SHP1 can enhance basal phosphorylation levels, leading to increased cytokine secretion. However, the specific effects and mechanisms of THEMIS on CAR-T cell memory, exhaustion, apoptosis, and cytokines, especially in fourth-generation CAR-T cells, remain unclear. Our results indicate that in fourth-generation CAR-T cells with 4-1BB as a co-stimulatory molecule, THEMIS can regulate T cell differentiation, affecting the CD8 / CD4 ratio and proliferative capacity after antigen stimulation. Fourth-generation CAR-T cells overexpressing this gene (THEMIS-7×19CAR-T) proliferate more rapidly upon antigen stimulation. Literature reports that the killing ability of CAR-T cells with 4-1BB as a co-stimulatory domain is related to their proliferative capacity; although the killing rate of individual cells is relatively slow, their strong proliferative capacity and synergistic killing properties give them a more effective and sustained tumor-killing ability. Furthermore, our results demonstrate that THEMIS's effect on the effector function of fourth-generation CAR-T cells is primarily manifested in long-term tumor killing rather than short-term killing ability. CAR-T cells overexpressing THEMIS were able to maintain long-term tumor killing ability more effectively. In vivo experiments also demonstrated that THEMIS-7×19 CAR-T cells had a stronger anti-tumor effect and significantly prolonged the survival time of mice in a lymphoma-bearing mouse model compared to the control group.

[0480] T cells, as the most crucial immune cells in the anti-tumor immune response, produce cytokines with chemotactic, pro-inflammatory, and immunoprotective effects to coordinate the adaptive immune system and exert direct cytotoxic responses against tumor cells. Current research has found that high levels of serum IL-2, IL-6, TNF, and IFN-γ secretion during CAR-T therapy are associated with the risk of severe CRS and ICANS, especially IL-6. Our study found that fourth-generation CAR-T cells with THEMIS knockout excessively secrete IL-2, IL-4, IL-6, TNF, and IFN-γ, but the secretion levels rapidly decline after repeated antigen stimulation. Overexpression of this gene effectively controlled the secretion of these inflammatory cytokines in fourth-generation CAR-T cells without affecting short-term tumor killing; in fact, it promoted long-term tumor killing ability. Furthermore, various characteristics of T cells have been found to significantly influence the efficacy of CAR-T cell therapy, particularly T cell exhaustion, which is closely related to tumor recurrence. Our findings show that knocking out THEMIS leads to impaired memory cell formation in fourth-generation CAR-T cells under continuous antigen stimulation, making them more prone to expressing immunosuppressive receptors and undergoing apoptosis. In contrast, overexpression of THEMIS significantly enhances their ability to adapt to continuous antigen stimulation, enabling them to form a higher proportion of memory T cell populations that are less susceptible to exhaustion and apoptosis.

[0481] In summary, we discovered that knocking out and overexpressing THEMIS regulates the long-term killing ability of fourth-generation CAR-T cells. Furthermore, this gene can effectively control the cytokine secretion of CAR-T cells without affecting tumor-killing activity, which may improve the severe cytokine side effects during clinical CAR-T cell therapy.

[0482] Of course, our current results do not reveal the specific molecular mechanisms by which the expression regulation of the THEMIS gene relates to CAR-T cell memory stemness and exhaustion levels. By conducting in-depth analysis of data from bulk RNA sequencing (bulk RNA-seq) and single-cell transcriptome sequencing, we are attempting to identify candidate downstream molecules of the THEMIS protein that may influence the exhaustion and long-term killing of fourth-generation CAR-T cells.

[0483] 5. Results and Conclusions

[0484] Results: (1) Knockout of the THEMIS gene reduced the CD8 / CD4 ratio in fourth-generation CAR-T cells, while overexpression increased this ratio. (2) The short-term tumor-killing ability of fourth-generation CAR-T cells overexpressing the THEMIS gene was not significantly changed, but the long-term tumor-killing effect was more persistent, the proportion of memory phenotype was increased, and the proportion of exhaustion phenotype and apoptosis was reduced. Knockout of the gene showed the opposite effect. (3) Under single antigen stimulation, the secretion of inflammatory cytokines in fourth-generation CAR-T cells overexpressing the THEMIS gene was reduced, but the degree of attenuation under repeated stimulation was lower than that of the control group (P<0.01). Knockout of the gene had the opposite effect. (4) The overall survival time of mice in the fourth-generation CAR-T cell group overexpressing the THEMIS gene was significantly longer than that of the control group, with a statistically significant difference (P<0.01). The median survival time was 64 days, which was longer than that of the control group (48 days).

[0485] Conclusions: 1) The THEMIS gene is involved in maintaining the CD8 / CD4 ratio in fourth-generation CAR-T cells; 2) The THEMIS gene can promote the proliferation of fourth-generation CAR-T cells after antigen stimulation and enhance their ability to cope with repeated antigen stimulation; 3) The THEMIS gene can regulate the long-term tumor-killing ability of fourth-generation CAR-T cells; 4) The THEMIS gene can regulate the limited secretion of cytokines by fourth-generation CAR-T cells; 5) Compared with the control group, THEMIS-7×19 CAR-T cells have a stronger anti-tumor effect and significantly prolong the survival time of mice in a lymphoma-bearing mouse model.

[0486] Part Three: Target Sequence, Target Plasmid, CAR-T Cell Construction and Corresponding Sequence

[0487] (I) CAR-T cell preparation process

[0488] 1. Lentiviral Packaging

[0489] 1.1 Transformation

[0490] 1) Take one competent cell from a -80℃ freezer and thaw it on ice;

[0491] 2) Add 20 μL of competent cells to a 1.5 mL EP tube, then add 1 μL of the target plasmid, gently tap to mix, incubate on ice for 30 min, heat shock in a 42℃ metal bath for 90 s, and then incubate on ice again for 2 min.

[0492] 3) Add 900 μL of ampicillin-free liquid LB broth medium, mix well by pipetting, and incubate at 37°C and 235 rpm for 45 min on a shaker.

[0493] 4) Centrifuge at 6000 rpm for 5 min, discard 700 μL of supernatant and resuspend the precipitate;

[0494] 5) Take 50 μL and drop it onto an LB broth agar plate containing ampicillin. Spread it evenly with an L-shaped spatula. Incubate upright in a 37°C incubator for 1 hour, then invert and incubate for 12-16 hours.

[0495] 1.2 Plasmid Extraction

[0496] Take the plasmid transformed the previous day, pick a single colony and place it in a test tube containing 5 mL of LB liquid medium. Add 5 μL of ampicillin (100 mg / mL) and incubate at 37°C and 235 rpm for 6-8 hours. After 6-8 hours, pour 5 mL of the bacterial-containing LB medium into 200 mL of LB liquid medium, add 200 μL of ampicillin, and incubate at 37°C and 235 rpm for 12-15 hours. Then perform large-scale plasmid extraction.

[0497] 1) Dispense 200 mL of bacterial culture into 50 mL centrifuge tubes, centrifuge at 8000 rpm for 3 min, and discard the supernatant;

[0498] 2) Use 8 mL of P1 solution to resuspend the bacteria in the four centrifuge tubes and concentrate them into one 50 mL centrifuge tube. Vortex to completely suspend the bacteria.

[0499] 3) Add 8 mL of P2 solution, invert 6 times to mix the cells thoroughly and lyse them, and let stand at room temperature for 5 min; then add 8 mL of P4 solution, invert 6 times to mix until a white flocculent precipitate is observed, and let stand at room temperature for 10 min.

[0500] 4) Centrifuge at 8000 rpm for 10 min to collect the flocculent material to the bottom of the tube, pour all the supernatant into CS1, and push the handle to collect the filtrate;

[0501] 5) Add 0.3 times the volume of isopropanol to the filtered bacterial solution and mix by inverting.

[0502] 6) Prepare the adsorption column CP6, add 3 mL of equilibration buffer BL to fully wet the filter membrane, centrifuge at 8000 rpm for 3 min, and discard the waste liquid in the collection tube;

[0503] 7) Add 8 mL of the bacterial culture with added isopropanol to CP6, centrifuge at 8000 rpm for 3 min, discard the waste liquid in the collection tube, and put the adsorption column back into the collection tube;

[0504] 8) Repeat step 7) until all bacterial solutions have passed through the column;

[0505] 9) Add 10 mL of rinsing solution (already containing anhydrous ethanol), centrifuge at 8000 rpm for 2 min, discard the waste liquid in the collection tube, and put the adsorption column back into the collection tube;

[0506] 10) Repeat step 9) once;

[0507] 11) Add 3 mL of anhydrous ethanol to the adsorption column, centrifuge at 8000 rpm for 2 min, discard the waste liquid in the collection tube, and put the adsorption column back into the collection tube.

[0508] 12) Centrifuge at 8000 rpm for 5 min to completely remove the washing solution from the adsorption column;

[0509] 13) Place the adsorption column CP6 into a new collection tube, open the cap and let it air for 5 minutes to allow the anhydrous ethanol to evaporate completely;

[0510] 14) Add 500 μL-1 mL of TB elution buffer to the center of the filter membrane of the adsorption column in a rotating manner. Let it stand at room temperature for 10 min, then centrifuge at 8000 rpm for 5 min. The liquid collected in the tube is the plasmid we need.

[0511] 15) Use a Nanodrop micro spectrophotometer to detect the concentration and OD 260 / 280, and store at -20℃ for later use.

[0512] 1.3 Lentiviral Packaging

[0513] 1) Prepare 1×10 1 day in advance 7 293T cells were cultured in a 10cm dish;

[0514] 2) Replace the cell culture medium with pre-warmed 10% FBS Opti-MEM medium 2 hours in advance;

[0515] 3) Plasmid preparation: Add 500 μL of Opti-MEM medium to a 15 mL centrifuge tube. Add plasmid at a molar ratio of pMDLg / pRRE:pRSV-Rev:pMD2.G:target plasmid = 1:1:0.5:2, and add plasmid at a rate of 10 μg / plate. Calculate the required mass and volume of each packaged plasmid and the target plasmid. Add the plasmid to the Opti-MEM medium, mix thoroughly, and incubate at room temperature for 5 min.

[0516] 4) Add 10 μL of Neofectamine, mix well, and incubate at room temperature for 17 min. After incubation, add to the supernatant at 293T.

[0517] 5) Collect the supernatant after 48 hours, add 10 mL / plate of 10% FBS Opti-MEM medium, and collect the supernatant again after 72 hours;

[0518] 6) Centrifuge the collected supernatant at 1500 rpm for 5 min and filter it using a 0.45 μm filter membrane;

[0519] 7) Centrifuge at 4000g, 4℃ for 12 hours;

[0520] 8) After centrifugation, discard the supernatant, resuspend the virus precipitate in virus preservation solution (concentrated at 1:250), aliquot and store at -80℃.

[0521] 1.4 Virus titer determination

[0522] 1) After cell counting, press 2 × 10⁻⁶ cells per well. 5 Cells were harvested using four gradients and two replicates of Jurkat cells. Considering cell loss, Jurkat cells were harvested in 10-well batches, i.e., 2 × 10⁻⁶ cells per well. 6 cell;

[0523] 2) Centrifuge at 1500 rpm for 5 min, discard the supernatant, resuspend in 1640 complete culture medium, and add 2 μL of polybrene, adding 100 μL to each well of a 96-well plate.

[0524] 3) Add 90 μL of virus preservation solution to 10 μL of original virus solution, and dilute 10 times;

[0525] 4) Add the virus stock solution, preservation solution, and 1640 medium according to the system in the table below to determine the titer:

[0526] Table 12

[0527]

[0528] 5) Centrifuge at 1200g for 1.5 hours at 32℃;

[0529] 6) After centrifugation, place at 37℃ and 5% CO2. 2 Incubate in an incubator for 4 hours;

[0530] 7) After 4 hours, centrifuge at 1500 rpm for 5 minutes, remove the supernatant, and resuspend in 2 mL of 1640 complete culture medium in a 24-well plate;

[0531] 8) Positive rate detected by flow cytometry after 48 hours, titer = [(2×10⁻⁶) / 2. 5 [×Positive rate) / 0.2]×Dilution factor.

[0532] 2. CAR-T cell preparation

[0533] 2.1 Isolation of human peripheral blood mononuclear cells (PBMCs)

[0534] 1) Add 10-20 mL of peripheral blood from a healthy person to an equal volume of PBS and mix thoroughly;

[0535] 2) Prepare two 50mL centrifuge tubes and add 20mL of human peripheral blood lymphocyte separation medium.

[0536] 3) Carefully and slowly layer the diluted peripheral blood along the tube wall onto the surface of the human peripheral blood lymphocyte separation solution;

[0537] 4) Centrifuge at 800g, speed 1, speed 0, room temperature for 20 minutes;

[0538] 5) Prepare two 15mL centrifuge tubes, add 5-8mL of PBS, carefully pipette the white membrane layer (i.e., PBMC) into the PBS, and mix thoroughly.

[0539] 6) Centrifuge at 1500 rpm for 5 minutes;

[0540] 7) Carefully discard the supernatant, and freeze the cell clumps with cell cryopreservation solution for later use or use them directly.

[0541] 2.2 Separating CD3 + T cells

[0542] 1) Resuspend PBMCs in 50 mL of X-VIVO complete medium, mix thoroughly by pipetting, and then add to a T225 flask;

[0543] 2) 37℃, 5% CO 2 Let it stand in the incubator for at least 6 hours, then carefully turn the culture flask over.

[0544] 3) After 2 hours, carefully stand the culture flask upright with its side as the base. In a biosafety cabinet, pour the cell suspension along the side into a new T225 flask and place it at 37°C with 5% CO2. 2 Incubator cultivation;

[0545] 4) Carefully flip the culture flask every 2 hours. Once both sides are fully covered, replace it with a new T225 flask. After completing 2-3 T225 flasks, observe the proportion of adherent cells under a microscope. When the proportion of adherent cells is <10%, take a small number of cells for CD3 detection. + >90% can then undergo T cell activation;

[0546] 2.3 T cell activation

[0547] 1) Collect the CD3 obtained in the previous step + >90% of T cells, centrifuged at 1500 rpm for 5 min;

[0548] 2) Carefully discard the supernatant, resuspend the cell clumps in an appropriate amount of X-VIVO complete culture medium, mix thoroughly, and then count the cells.

[0549] 3) Calculate the required CD3 / CD28 Dynabeads volume based on the number of cells, i.e., 30% × total cell number / CD3 / CD28 Dynabeads density, and centrifuge the cell suspension at 1500 rpm for 5 min.

[0550] 4) Cleaning CD3 / CD28 Dynabeads: Prepare a 15mL centrifuge tube, add 1mL PBS, then add the CD3 / CD28 Dynabeads calculated in the previous step, and place it on a magnetic rack to stand for 5 minutes;

[0551] 5) Remove 15 mL of PBS from the centrifuge tube and discard it (keep the 15 mL centrifuge tube on a magnet);

[0552] 6) Remove the 15mL centrifuge tube from the magnetic rack. You can see the iron-red CD3 / CD28 Dynabeads on the tube wall.

[0553] 7) Soak the cell clumps in X-VIVO complete medium at a concentration of 4-6 × 10⁻⁶. 6 / mL resuspended;

[0554] 8) Add the cell suspension to the washed CD3 / CD28 Dynabeads, mix well by pipetting, and incubate on a rotating shaker for 30 min to ensure that the cells are in full contact with the CD3 / CD28 Dynabeads;

[0555] 9) After rotation, place the 15mL centrifuge tubes into the magnetic rack and let stand for 5 minutes;

[0556] 10) Be careful not to abandon Shangqing;

[0557] 11) Remove the 15mL centrifuge tube and use X-VIVO medium at a CD3 / CD28 Dynabeads ratio of 1-3 × 10⁻⁶. 6 Resuspend the precipitate in mL and incubate in a T25 flask for at least 8 hours. Name it D0 at this point.

[0558] 2.4 Lentiviral transfection

[0559] 1) Collect the activated T cells obtained in the previous step and centrifuge at 1500 rpm for 5 min;

[0560] 2) After resuspending the cells in an appropriate amount of X-VIVO complete culture medium, perform cell counting;

[0561] 3) Take 1×10 6 Activate T cells, centrifuge at 1500 rpm for 5 min, and use the remaining cells as control T cells (CT);

[0562] 4) Carefully discard the supernatant, add fourth-generation CD19-CAR or CD19-CAR-THEMIS lentivirus at 30 moi (multiplicity of infection), bring the system to 200 μL with X-VIVO blank medium, add 0.2 μL of polybrene (8 mg / mL) to one well of a 96-well plate, and carefully seal the 96-well plate with sealing film;

[0563] 5) Centrifuge at 1200g, 32℃ for 1.5h;

[0564] 6) After centrifugation, centrifuge at 37℃ and 5% CO2. 2 Incubate for 4 hours;

[0565] 7) Centrifuge at 1500 rpm for 5 min, carefully discard the supernatant, resuspend the cells in 2 mL of X-VIVO complete medium in a 24-well cell culture plate and culture them, naming them D1.

[0566] 2.5 CAR-T cell culture

[0567] 1) On day 3, the transduction efficiency was detected by flow cytometry, and 8 mL of X-VIVO medium was added before transferring the cells to a T25 flask for further culture.

[0568] 2) After thoroughly mixing the cell suspension by pipetting on day 4, transfer it to a 15 mL centrifuge tube, place it on a magnetic rack and let it stand for 5 min to remove CD3 / CD28 Dynabeads. Collect the supernatant to obtain the desired cells. CT cells are processed in the same way.

[0569] 3) During the D3-10 culture period, add an equal volume of X-VIVO complete culture medium to the existing culture system every other day. Depending on the culture system, transfer the medium to T75 and T175 bottles in sequence, or freeze some of it for later use.

[0570] 4) D11-14 are used for in vitro or animal experiments.

[0571] (II) Construction of the target plasmid

[0572] 1. The construction process specifically includes the following operations based on the already constructed 7×19 target plasmid and the specific enzyme digestion information (as shown in Figure 5-1): 1) Insert the THEMIS_CDS sequence after 7×19 in the target plasmid (MluI single restriction site); 2) Link the THEMIS_CDS sequence (as shown in Figure 5-2) with the 7×19 sequence in the CAR plasmid using T2A, and the constructed target plasmid is shown in Figure (5-3); 3) Codon optimization.

[0573] The specific corresponding sequence is shown below:

[0574] 2.1: The 7×19 CAR DNA sequence is shown in SEQ ID NO.3:

[0575] gctagccccggggccaccatggccctgcctgtgaccgctctgctgctccctctggccctgctgctgcacgctgccaggcctgatatccagatg

[0576] acccagaccacctccagcctgtccgcctccctcggcgatagggtgaccatcagctgcagggccagccaggacatcagcaagtatctgaactg

[0577] gtaccagcagaagcccgacggcaccgtgaaactgctcatctaccatacctccaggctccacagcggcgtgccttccaggtttagcggctccg

[0578] gctccggcaccgactattccctcaccatcagcaatttagaacaagaggatatcgccacctatttctgccagcagggcaacaccctgccctacac

[0579] ctttggcggcggcaccaagctggagattacaggaggcggcggctccggaggcggaggctccggcggcggaggaagcgaagtgaagctg

[0580] caggaaagcggacctggactcgtggcccctagccagagcctgagcgtgacatgtaccgtgtccggcgtgtccctgcctgactacggagtctc

[0581] ctggatcaggcaaccccctagaaagggtttagaatggctcggcgtgatttggggcagcgagaccacctactacaacagcgccctgaagagca

[0582] gactgaccatcatcaaggacaactccaagtcccaggtgtttctgaagatgaactccctgcagaccgacgataccgccatctactactgcgccaa

[0583] gcactactactatggcggctcctacgccatggactactggggacaaggaacctccgtgacagtgtccagcaccaccacccctgctcctagacc

[0584] ccctacccctgctcccacaattgccagccagcctctgagcctgagacccgaagcctgcagacctgctgccggaggagccgtgcacaccagg

[0585] ggcctggacttcgcctgcgacatctacatttgggctcccctcgctggaacctgtggcgtgctgctgctgtccctggtgattaccctgtactgcaag

[0586] aggggcaggagaagctgctgtacatcttcaaacagcccttcatgagacccgtgcagaccacccaagaagaggatggctgcagctgcagatt

[0587] cccgaagaggaggagggaggctgcgagctgagggtgaagtttagcagaagcgccgacgctcccgcttaccagcagggacagaaccagc

[0588] tgtataacgagctgaacctcggcagaagagaggagtacgacgtgctggataagaggggcagagaccctgagatggcggcaagccta

[0589] ggagaaaaacccccaggagggactgtacaatgagctgcagaaagataagatggccgaggcctagatcgagatcggaatgaagggcgaa

[0590] aggagaggggcaagggacacgacggcctgtaccagggcctctccacagccaccaaggacacctacgacgccctcatatgcaggccct

[0591] gcctcctaggggcagcggcgccaccaacttttctttactgaagcaagccggtgacgtggaggagaaccccggccccatgttccacgtgtcctt

[0592] cagatacatcttcggtttaccccctctcattttagtgctgctgcccgttgccagcagcgactgcgacatcgaaggcaaagacggcaagcagtatg

[0593] aaagcgtgctgatggtgtccatcgaccagctgctcgactccatgaaggagatcggcagcaactgtttaaacaacgaattcaacttcttcaagag

[0594] gcacatctgtgacgccaacaaggagggcatgtttttattcagagccgctcgtaagctgaggcagtttttaaaaatgaactccaccggcgacttcg

[0595] atttacatctgctgaaggtgtccgagggcaccaccattttactgaattgcaccggccaagttaagggaagaaagcccgctgctttaggcgaagc

[0596] ccagcccacaaagtctttagaggagaacaaatctttaaaggagcagaagaagctgaacgacctctgctttttaaaaaggctgctgcaagaaatc

[0597] aagacatgctggaacaagattttaatgggcaccaaagaacacggctccggcgaaggcagaggctctttactgacttgtggagacgtggaaga

[0598] gaaccccggtcccatggctctgctgctcgctttatctttactggtgctgtggacaagccccgcccctactttaagcggaaccaacgacgccgag

[0599] gactgctgtttaagcgtgacccaaaagcccatccccggttacatcgtgaggaactttcactacttattaatcaaggatggctgtcgtgtgcccgct

[0600] gtggtgttcaccactttaagaggcagacagctgtgcgctcctcccgaccagccttgggtggagagaatcatccagaggctgcagaggaccag

[0601] cgctaagatgaagaggaggagctcctga

[0602] 2.2: The amino acid sequence of 7×19 CAR is shown in SEQ ID NO.4:

[0603] ASPGATMALPVTALLLPLALLLHAARPDIQMTQTTSSLSASLGDRVTISCRASQDISKYLNWYQQKPDGTVKLLIYHTSRLHSGVPSRFSGSGSGTDYSLTISNLEQEDIATYFCQQGNTLPYTFGGGTKLEITGGGGSGGGGSGGGGSEVKLQESGPGLVAPSQSLSVTCTVSGVSLPDYGVSWIRQPPRKGLEWLGVIWGSETTYYNSALKSRLTIIKDNSKSQVFLKMNSLQTDDTAIYYCAKHYYYGGSYAMDYWGQGTSVTVSSTTTPAPRPPTPAPTIASQPLSLRPEACRPAAGGAVHTRGLDFACDIYIWAPLAGTCGVLLLSLVITLYCKRGRKKLLYIFKQPFMRPVQTTQEEDGCSCRFPEEEEGGCELRVKFSRSADAPAYQQGQNQLYNELNLGRREEYDVLDKRRGRDPEMGGKPRRKNPQEGLYNELQKDKMAEAYSEIGMKGERRRGKGHDGLYQGLSTATKDTYDALHMQALPPRGSGATNFSLLKQAGDVEENPGPMFHVSFRYIFGLPPLILVLLPVASSDCDIEGKDGKQYESVLMVSIDQLLDSMKEIGSNCLNNEFNFFKRHICDANKEGMFLFRAARKLRQFLKMNSTGDFDLHLLKVSEGTTILLNCTGQVKGRKPAALGEAQPTKSLEENKSLKEQKKLNDLCFLKRLLQEIKTCWNKILMGTKEHGSGEGRGSLLTCGDVEENPGPMALLLALSLLVLWTSPAPTLSGTNDAEDCCLSVTQKPIPGYIVRNFHYLLIKDGCRVPAVVFTTLRGRQLCAPPDQPWVERIIQRLQRTSAKMKRRSS*

[0604] 2.3: THE THEMIS-7×19 CAR DNA sequence is shown in SEQ ID NO.5:

[0605]

[0606] 2.4: The amino acid sequence of THEMIS-7×19CAR is shown in SEQ ID NO.6:

[0607] ASPGATMALPVTALLLPLALLLHAARPDIQMTQTTSSLSASLGDRVTISCRASQDISKYLNWYQQKPDGT

[0608] VKLLIYHTSRLHSGVPSRFSGSGSGTDYSLTISNLEQEDIATYFCQQGNTLPYTFGGGTKLEITGGGGSGG

[0609] GGSGGGGSEVKLQESGPGLVAPSQSLSVTCTVSGVSLPDYGVSWIRQPPRKGLEWLGVIWGSETTYYNS

[0610] ALKSRLTIIKDNSKSQVFLKMNSLQTDDTAIYYCAKHYYYGGSYAMDYWGQGTSVTVSSTTTPAPRPPTP

[0611] APTIASQPLSLRPEACRPAAGGAVHTRGLDFACDIYIWAPLAGTCGVLLLSLVITLYCKRGRKKLLYIFKQP

[0612] FMRPVQTTQEEDGCSCRFPEEEEGGCELRVKFSRSADAPAYQQGQNQLYNELNLGRREEYDVLDKRRGR

[0613] DPEMGGKPRRKNPQEGLYNELQKDKMAEAYSEIGMKGERRRGKGHDGLYQGLSTATKDTYDALHMQA

[0614] LPPRGSGATNFSLLKQAGDVEENPGPMFHVSFRYIFGLPPLILVLLPVASSDCDIEGKDGKQYESVLMVSI

[0615] DQLLDSMKEIGSNCLNNEFNFFKRHICDANKEGMFLFRAARKLRQFLKMNSTGDFDLHLLKVSEGTTIL

[0616] LNCTGQVKGRKPAALGEAQPTKSLEENKSLKEQKKLNDLCFLKRLLQEIKTCWNKILMGTKEHGSGEG

[0617] RGSLLTCGDVEENPGPMALLLALSLLVLWTSPAPTLSGTNDAEDCCLSVTQKPIPGYIVRNFHYLLIKDGC

[0618] RVPAVVFTTLRGRQLCAPPDQPWVERIIQRLQRTSAKMKRRSSEGRGSLLTCGDVEENPGPMALSLEEFV

[0619] HSLDLRTLPRVLEIQAGIYLEGSIYEMFGNECCFSTGEVIKITGLKVKKIIAEICEQIEGCESLQPFELPMNFP

[0620] GLFKIVADKTPYLTMEEITRTIHIGPSRLGHPCFYHQKDIKLENLIIKQGEQIMLNSVEEIDGEIMVSCAVAR

[0621] NHQTHSFNLPLSQEGEFYECEDERIYTLKEIVEWKIPKNRTRTVNLTDFSNKWDSTNPFPKDFYGTLILKP

[0622] VYEIQGVMKFRKDIIRILPSLDVEVKDITDSYDANWFLQLLSTEDLFEMTSKEFPIVTEVIEAPEGNHLPQS

[0623] ILQPGKTIVIHKKYQASRILASEIRSNFPKRHFLIPTSYKGKFKRRPREFPTAYDLEIAKSEKEPLHVVATKA

[0624] FHSPHDKLSSVSVGDQFLVHQSETTEVLCEGIKKVVNVLACEKILKKSYEAALLPLYMEGGFVEVIHDKK

[0625] QYPISELCKQFRLPFNVKVSVRDLSIEEDVLAATPGLQLEEDITDSYLLISDFANPTECWEIPVGRLNMTVQ

[0626] LVSNFSRDAEPFLVRTLVEEITEEQYYMMRRYESSASHPPPRPPKHPSVEETKLTLLTLAEERTVDLPKSPKRHHVDITKKLHPNQAGLDSKVLIGSQNDLVDEEKERSNRGATAIAETFKNEKHQK*

[0627] 2.5: The DNA sequence corresponding to the original THEMIS-7×19CAR-T plasmid is shown in SEQ ID NO.7:

[0628]

[0629] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A recombinant construct, characterized in that, The encoding is a chimeric antigen receptor that can be used in fourth-generation CAR-T cells to simultaneously express IL-7, CCL19, and THEMIS; the chimeric antigen receptor is an anti-CD19 chimeric antigen receptor; the fourth-generation CAR-T cells comprise a structure consisting of: activated T cell nuclear factor NFAT, cytokine IL-7, linker T2A, chemokine CCL19, promoter EF1α, antigen-binding domain CD19 monoclonal antibody scFv, hinge region CD8αHinge, co-stimulatory domain 4-1BB, and intracellular domain CD3ζ, in sequence.

2. The recombinant construct according to claim 1, characterized in that, The nucleic acid sequence of the recombinant construct is shown in SEQ ID NO.

5.

3. The recombinant construct according to claim 2, characterized in that, The amino acid sequence encoded by the recombinant construct is shown in SEQ ID NO.

6.

4. A pharmaceutical composition, characterized in that: It includes a recombinant construct as described in any one of claims 1 to 3 and at least one pharmaceutically acceptable carrier.

5. A CAR-T cell, characterized in that, Includes a recombinant construct as described in any one of claims 1 to 3.

6. A CAR-T cell according to claim 5, characterized in that, The CAR-T cells mentioned are autologous, allogeneic, or xenogeneic.

7. Use of a recombinant construct according to any one of claims 1 to 3, a pharmaceutical composition according to claim 4, or a CAR-T cell according to any one of claims 5 to 6 in the preparation of a kit for the treatment of B-cell lymphoma.

8. Use of a recombinant construct according to any one of claims 1 to 3, a pharmaceutical composition according to claim 4, or a CAR-T cell according to any one of claims 5 to 6 in the preparation of a medicament for the treatment of B-cell lymphoma.

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