A method for screening SLE patients suitable for BCMA-CD19 dual-target CAR-T therapy

Abstract

This invention discloses an in vitro detection method and kit for assisting in the screening of systemic lupus erythematosus (SLE) patients suitable for BCMA-CD19 dual-target CAR-T therapy. Based on single-cell transcriptome sequencing, this invention identifies a plasma cell subset that exhibits high XBP1 / JCHAIN ​​expression but low CD19 expression after CD19 single-target therapy. This method uses qPCR to quantitatively detect the mRNA levels of AIM2, XBP1, JCHAIN, and immunoglobulin heavy chain constant region genes in PBMCs, and calculates the BCR category switching score using an exponential operational model. Patients exhibiting high expression of AIM2 or plasma cell markers and a BCR score >1.5 (indicating IgG / IgA dominance) are considered suitable for dual-target therapy. This method effectively identifies individuals at risk of single-target therapy escape and can be used to assess the quality of immune reconstitution after treatment.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine, and specifically relates to a method for screening SLE patients suitable for BCMA-CD19 dual-target CAR-T therapy. Background Technology

[0002] Systemic lupus erythematosus (SLE) is an autoimmune disease affecting multiple organs. Its core pathological mechanism is the high activation of B cells, the massive production of pathogenic autoantibodies (such as anti-double-stranded DNA antibodies and antinuclear antibodies), and immune complex-mediated tissue damage. Although current standard treatment regimens (including glucocorticoids, immunosuppressants such as cyclophosphamide and mycophenolate mofetil, and biologics such as belimumab) benefit many patients, a significant proportion of patients do not respond well to existing therapies (refractory SLE) or cannot tolerate the toxic side effects of long-term medication.

[0003] In recent years, chimeric antigen receptor T-cell (CAR-T) immunotherapy has made groundbreaking progress in the treatment of hematologic malignancies and is beginning to be explored for the treatment of antibody-mediated autoimmune diseases. Among them, CAR-T cell therapy targeting the CD19 antigen has shown preliminary efficacy in the treatment of SLE by specifically eliminating B cells.

[0004] Although CD19-targeted CAR-T therapy has shown preliminary efficacy in the treatment of SLE, clinical observations have revealed that some patients experience relapse. Current clinical assessments primarily rely on routine flow cytometry to detect peripheral blood B cell counts (CD19+) and serum antibody titers. However, existing detection methods struggle to explain why some patients relapse after CD19+ B cell clearance, and also cannot predict which patients are at high risk of 'CD19 single-target resistance' before treatment.

[0005] Clinically, there is an urgent need for a screening method that can deeply analyze B-cell heterogeneity at the microscopic level to identify potential sources of relapse risk. This would allow for more precise recommendations of more potent regimens, such as BCMA-CD19 dual-target CAR-T therapy, which can simultaneously target B cells and plasma cells / long-lived plasma cells (LLPCs) driving SLE, potentially improving clinical outcomes. This helps avoid the risks associated with misallocation of medical resources and ineffective treatment.

[0006] References

[0007] 1. Mackensen, A., et al., Anti-CD19 CAR T cell therapy for refractorysystemic lupus erythematosus. Nat Med, 2022. 28(10): p. 2124-2132. 2. Hong, M., et al., BCMA-CD19 armored compound CAR T cells insystemic lupus erythematosus: extended follow-up of a phase 1 clinical trial. J Hematol Oncol, 2026. 19(1): p. 13. Summary of the Invention

[0008] To address the lack of methods for identifying whether systemic lupus erythematosus (SLE) patients are suitable for BCMA-CD19 dual-target CAR T therapy, and for evaluating the quality of immune reconstitution and prognosis after dual-target CAR T therapy, this application utilizes single-cell transcriptome sequencing and large-sample qPCR validation technology to analyze changes in hundreds of genes and immune receptor characteristics in PBMCs before and after treatment. The analysis revealed significant and regular changes in the expression of AIM2, XBP1, JCHAIN, and BCR isotype characteristics before and after treatment. This establishes a method for screening SLE patients suitable for BCMA-CD19 dual-target CAR T therapy and for evaluating the quality of immune reconstitution and prognosis after treatment. The specific technical solution is as follows:

[0009] I. Identification of specifically enriched pathogenic subpopulations and specifically highly expressed genes using high-resolution cluster analysis of single cells.

[0010] Five patients with refractory SLE were included in the study and received BCMA-CD19 dual-target CAR-T therapy. Single-cell data from three healthy subjects were downloaded from a public database (GSE267645) and integrated as a healthy control group. The publicly available single-target CD19 CAR-T therapy cohort (GSE263931, N=7) was integrated as a reference for cross-sectional efficacy comparison.

[0011] Venous blood was collected from SLE patients, and peripheral blood mononuclear cells (PBMCs) were extracted and sequenced.

[0012] Based on high-resolution cluster analysis of 176,182 single cells, three specifically enriched pathogenic subgroups were identified in the SLE group before BCMA-CD19 dual-target CAR T therapy:

[0013] Cluster 1 (inflammatory memory B cells): Compared to healthy controls, SLE patients specifically overexpress the AIM2 gene.

[0014] Cluster 2 and Cluster 3 (plasma cell lines): Compared to healthy controls, these two subpopulations specifically overexpress XBP1, JCHAIN, and MZB1.

[0015] By screening AIM2, XBP1, JCHAIN, and MZB1, patients with such "refractory residual lesions" in their bodies can be accurately identified, providing a scientific basis for selecting BCMA-CD19 dual-target CAR-T therapy.

[0016] BCR isotype analysis: IgG+IgA>50% can identify patients with extremely high risk of 'single-target therapy escape', providing a scientific interpretation standard for selecting BCMA-CD19 dual-target CAR-T therapy for such patients.

[0017] II. Verification of the universality of AIM2 and other genes based on qPCR technology

[0018] Twenty patients with active SLE (SLEDAI≥6) were included as the "SLE validation group" and 20 healthy volunteers were included as the "healthy control group". Venous blood was collected from both groups, and peripheral blood mononuclear cell (PBMC) samples were collected as independent validation cohorts.

[0019] Real-time quantitative PCR (qPCR) results: The average relative mRNA expression level of the AIM2 gene in the SLE validation group was 8.5 times that of the healthy control group, and it was significantly elevated in 90% of SLE patients. Compared with the healthy control group, the SLE validation group showed widespread high expression of plasma cell genes XBP1 and JCHAIN, consistent with single-cell sequencing results. BCR score: The BCR score of the SLE group was significantly higher than that of the healthy control group, suggesting that class switching is a common feature of active SLE.

[0020] III. Screening methods and criteria based on next-generation sequencing (NGS) technology

[0021] We have developed a high-throughput sequencing method for screening SLE patients suitable for BCMA-CD19 dual-target CAR-T therapy. This method is applicable to clinical scenarios where it is necessary to obtain a patient's complete immune profile. SLE patients who meet any one or more of the following criteria are suitable for BCMA-CD19 dual-target CAR-T therapy.

[0022] (1) In the gene expression matrix, the transcript abundance (TPM) of AIM2 was more than twice that of the healthy control group, and in the BCR immune repertoire data, the ratio of the sum of the number of IgG and IgA heavy chain constant region reads to the number of IgM reads was >1.5;

[0023] (2) In the gene expression matrix, the transcript abundance (TPM) of XBP1 was more than 3 times higher than that of the healthy control group, and in the BCR immune repertoire data, the ratio of the sum of the number of IgG and IgA heavy chain constant region reads to the number of IgM reads was >1.5.

[0024] (3) In the gene expression matrix, the transcript abundance (TPM) of JCHAIN ​​was more than 3 times higher than that of the healthy control group, and in the BCR immune repertoire data, the ratio of the sum of the number of IgG and IgA heavy chain constant region reads to the number of IgM reads was >1.5;

[0025] IV. Clinical application verification of AIM2 and other genes in dual-target CAR-T therapy screening and prognostic assessment

[0026] Disease activity was assessed using the SLEDAI-2K scoring system. Anti-dsDNA antibody titers, complement C3 / C4 levels, and 24-hour urinary protein quantification were monitored. "Clinical remission" was defined as SLEDAI <4 and no new active disease.

[0027] Paired analyses were performed on clinical and immunological indicators of patients before (PRE) and after (POST) BCMA-CD19 dual-target therapy. Results showed that patients exhibited highly significant clinical benefits upon reaching the B-cell remodeling phase, and the clearance levels of AIM2, XBP1, and JCHAIN ​​were positively correlated with the improvement in SLEDAI levels.

[0028] Based on the above data, this application establishes a set of methods for screening suitable BCMA-CD19 dual-target CAR-T therapy regimens and determining prognosis:

[0029] BCMA-CD19 dual-target CAR-T therapy is recommended for patients who meet one or more of the following criteria:

[0030] (1) 2 -ΔΔCt_AIM2 >2 and BCR score > 1.5;

[0031] (twenty two -ΔΔCt_XBP1 >3 and BCR score > 1.5;

[0032] (3) 2 -ΔΔCt_JCHAIN >3 and BCR score > 1.5

[0033] If patient 2 after treatment -ΔΔCt_AIM2 <1.5 and 2 -ΔΔCt_XBP1 <1.5 and 2 -ΔΔCt_ JCHAIN A BCR score <1.5 and a BCR score <0.5 indicate a good prognosis.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: it establishes for the first time a method for screening systemic lupus erythematosus patients suitable for BCMA-CD19 dual-target CAR T therapy and a method for evaluating the quality of immune reconstitution and prognosis after treatment. Attached Figure Description

[0035] Figure 1 The distribution of peripheral blood B cells and plasma cell subsets in SLE patients was shown by single-cell transcriptome analysis (t-SNE plot). Among them, Cluster 1 is memory B cells with high expression of AIM2, and Cluster 2 and Cluster 3 are plasma cell lines with high expression of XBP1 / JCHAIN.

[0036] Figure 2 , 7 Violin plot of expression levels of classic B cell lineage markers in individual cell populations;

[0037] Figure 3 A pie chart showing the distribution of B cell receptor (BCR) immunoglobulin heavy chain isotypes, where...

[0038] A represents the composition of the BCR library in the healthy control group.

[0039] B represents the composition of the BCR library in SLE patients before BCMA-CD19 dual-target CAR-T therapy.

[0040] C represents the composition of the BCR library of SLE patients who received BCMA-CD19 dual-target CAR-T therapy and achieved clinical remission;

[0041] Figure 4 Expanding the sample cohort, statistical boxplots were used to examine the expression differences of genes such as AIM2 using real-time quantitative PCR.

[0042] A represents a comparison of the relative expression levels of AIM2 between healthy controls and SLE patients.

[0043] B represents a comparison of the relative expression levels of XBP1 between healthy controls and SLE patients.

[0044] C represents a comparison of the relative expression levels of JCHAIN ​​between healthy controls and SLE patients.

[0045] D represents a comparison of BCR scores between healthy controls and SLE patients;

[0046] Figure 5 , 5 Paired analysis of clinical and immunological indicators before (PRE) and after (POST) treatment in patients with refractory SLE who received BCMA-CD19 dual-target therapy;

[0047] Figure 6 A scatter plot showing the correlation between the degree of clearance of genes such as AIM2 and clinical efficacy.

[0048] A represents the correlation between the degree of AIM2 clearance and the extent of improvement in SLEDAI.

[0049] B represents the correlation between the degree of XBP1 clearance and the extent of SLEDAI improvement.

[0050] C represents the correlation between the degree of JCHAIN ​​clearance and the extent of SLEDAI improvement;

[0051] Figure 7 A schematic diagram of the logical flow of the "SLE Dual-Target CAR-T Therapy Screening and Prognostic Assessment System" based on a specific combination of molecular detection indicators. Detailed Implementation

[0052] The present application will now be described in further detail with reference to specific embodiments. The embodiments given are merely illustrative of the present application and are not intended to limit its scope. The embodiments provided below can serve as a guide for further improvements by those skilled in the art and do not constitute a limitation on the present application in any way.

[0053] Unless otherwise specified, the experimental methods in the following embodiments are conventional methods, performed in accordance with the techniques or conditions described in the literature in this field or in accordance with the product instructions.

[0054] Unless otherwise specified, all materials and reagents used in the following examples are commercially available.

[0055] This application relates to a set of key biomarkers in peripheral blood mononuclear cells (PBMCs)—melanoma deficiency factor 2 (AIM2), X-box binding protein 1 (XBP1), linker chain (JCHAIN), and B cell receptor (BCR) immunoglobulin heavy chain isotype.

[0056] Melanoma Deficiency Factor 2 (AIM2): Although AIM2 is known in the art to be a cytoplasmic double-stranded DNA sensor and involved in inflammasome assembly, the inventors of this application have discovered for the first time through single-cell sequencing that AIM2 is specifically and abnormally highly expressed in a pathological memory B cell subset (defined as Cluster 1 in this study) in SLE patients. The high activation of this subset is a key source driving the persistence of systemic inflammation.

[0057] X-box binding protein 1 (XBP1) and linker chain (JCHAIN): XBP1 is known to be a key transcription factor for plasma cell differentiation, and JCHAIN ​​is a protein essential for antibody assembly. Based on in-depth research, this application further reveals that both are specifically highly expressed in specific amplified mature antibody-secreting cell subsets (defined in this study as Cluster 2 and Cluster 3) in the peripheral blood of SLE patients. Furthermore, this application found that these subsets with high XBP1 / JCHAIN ​​expression are often accompanied by downregulation or absence of CD19 antigen, thus rendering conventional CD19 single-target CAR-T therapy ineffective in clearing it.

[0058] B cell receptor (BCR) immunoglobulin heavy chain isotypes: These refer to the constant region type of the heavy chain of B cell surface antigen receptors or secreted antibodies (such as IgM, IgG, and IgA). In healthy individuals, the peripheral blood B cell pool is usually dominated by immature IgM cells; however, in patients with active SLE, due to class switching recombination (CSR) driven by autoimmune responses, the proportion of IgG and IgA cells is often abnormally elevated.

[0059] Currently, there are no clear molecular screening criteria for choosing BCMA-CD19 dual-target CAR-T therapy in clinical practice. Based on the above-mentioned novel microscopic atlas analysis of the pathogenic mechanisms at the basal level of B cells and plasma cells, this application creatively establishes a screening and prognostic assessment system:

[0060] Screening logic: If a high abundance of AIM2+ memory B cells or an expansion of plasma cell subsets with low CD19 expression but XBP1+ / JCHAIN+ are detected in the patient's PBMCs, it indicates that the patient has a pathogenic cell subset that is difficult to eliminate with conventional CD19 single-target therapy, and therefore is an advantageous patient population for dual-target CAR-T therapy.

[0061] Prognostic logic: After treatment, if the patient's BCR immune repertoire successfully reverses from the pathological "class switching type (IgG / IgA dominance)" to the healthy "initial type (IgM dominance)", that is, "humoral reset" is achieved, indicating a good prognosis.

[0062] The following is a detailed description with reference to specific embodiments.

[0063] Example 1: Screening and identification of specific genes in SLE patients suitable for BCMA-CD19 CAR-T therapy using single-cell transcriptome sequencing and immune repertoire technology.

[0064] This embodiment describes in detail how to use high-throughput sequencing technology to identify for the first time specific genes in patients with systemic lupus erythematosus who are suitable for screening BCMA-CD19 dual-target CAR-T therapy in patient samples.

[0065] 1. Subjects

[0066] This embodiment involves three data sources:

[0067] (1) Trial cohort: A total of 5 patients (P1-P5) with refractory SLE from Zhongshan People's Hospital were included and received BCMA-CD19 dual-target CAR-T therapy.

[0068] Selection criteria:

[0069] —Ages 18-65;

[0070] —Complies with the ACR / EULAR 2019 SLE classification standards;

[0071] — Refractory SLE patients who have failed or relapsed after traditional immunosuppressant therapy will undergo a BCMA-CD19 dual-target CAR-T clinical trial;

[0072] —SLEDAI score ≥6, positive anti-dsDNA antibody or decreased complement C3 / C4.

[0073] (2) Healthy baseline (external integration): Single-cell data of 3 healthy subjects were downloaded and integrated from the public database (GSE267645) as a healthy control group (HC group);

[0074] (3) Efficacy comparison (external integration): The publicly available single-target CD19 CAR-T treatment cohort (GSE263931, N=7) was integrated as a horizontal comparison reference.

[0075] The above cohort serves as a 'Discovery Set', designed to locate pathogenic targets using high-resolution single-cell atlases and to provide a theoretical basis for the expanded cohort validation in subsequent Example 2.

[0076] 2. Preparation and cryopreservation of peripheral blood mononuclear cells (PBMCs)

[0077] (1) Blood collection: 10 mL of fasting venous blood was collected from patients before receiving BCMA-CD19 dual-target CAR-T therapy, using EDTA-K2 anticoagulant tubes, and processed within 2 hours after the blood was removed from the body.

[0078] (2) Separation: Mix the blood sample with an equal volume of sterile PBS buffer (pH 7.4) to dilute it. Add 5 mL of Ficoll-Paque PLUS separation solution to a 15 mL centrifuge tube in advance, and slowly spread the diluted blood along the tube wall onto the surface of the separation solution, keeping the interface clear.

[0079] (3) Centrifugation: Set the centrifuge temperature to 20℃, centrifuge at 800g for 20 minutes, and set the acceleration and deceleration speed to the lowest level (or turn off the brake) to prevent interface disturbance.

[0080] (4) Cell collection: After centrifugation, aspirate the white membrane layer (containing PBMCs) between the plasma layer and the separation liquid layer and transfer it to a new sterile centrifuge tube. Add 10 mL of PBS to resuspend the cells, centrifuge at 400 g for 10 minutes to wash the cells, and repeat the washing twice to remove platelets.

[0081] (5) Cryopreservation: Discard the supernatant, resuspend the cells in cryopreservation solution containing 10% DMSO and 90% FBS, and adjust the density to 5×10⁶ cells / year. 6 Cells / mL were aliquoted into cryovials, placed in a programmed cooling box, and stored at -80°C overnight. The next day, the cells were transferred to liquid nitrogen for storage.

[0082] 3. Construction and sequencing of single-cell RNA and immune repertoire libraries

[0083] (1) Cell resuscitation

[0084] Frozen PBMCs were rapidly thawed in a 37°C water bath, washed with RPMI-1640 medium containing 10% FBS, and cell viability was measured to be >90%.

[0085] (2) Library construction

[0086] The 10x Genomics Chromium Next GEM Single Cell 5' Kit v2 was used.

[0087] The cell suspension was adjusted to a concentration of 1000 cells / μL and loaded onto a Chromium Chip G chip to generate water-in-oil microdroplets (GEMs). Cell lysis and reverse transcription were performed within the microdroplets to generate barcoded cDNA.

[0088] cDNA amplification and purification: After demulsification, cDNA was purified using Dynabeads MyOne Silane magnetic beads and then amplified by PCR (98℃ 45s; 98℃ 20s, 67℃ 30s, 72℃ 1min, 14 cycles; 72℃ 1min).

[0089] Library construction: The product is divided into two parts. One part is used to construct a 5' gene expression library, including fragmentation, end repair, A-tailing, adapter ligation, and indexing PCR. The other part is used to construct a BCR V(D)J enrichment library, which is enriched by nested PCR using the Human BCR Amplification Kit.

[0090] (3) Sequencing

[0091] Library fragment size distribution was detected using an Agilent 2100 Bioanalyzer, and concentrations were determined using Qubit 4.0. After mixing, the libraries were sequenced at paired ends of 150 bp (PE150) on an Illumina NovaSeq 6000 platform, with a target sequencing depth of at least 20,000 reads (GEX) and 5,000 reads (VDJ) per cell.

[0092] (4) Bioinformatics analysis and differential gene identification

[0093] Data preprocessing: The raw sequencing data were aligned to the GRCh38 human reference genome using Cell Ranger (v6.1.2) software to generate a gene expression matrix.

[0094] Quality control measures are implemented to filter out low-quality cells with mitochondrial gene content >10% or the number of genes detected <200.

[0095] Dimensionality reduction and clustering: Standardization was performed using the Seurat R package, and batch effect correction was applied to the experimental cohort data and external ensemble data using the Harmony algorithm. The top 30 principal components were selected for ensemble analysis and clustering to ensure the reproducibility of the identified pathogenic subgroups across datasets.

[0096] Differential gene screening results: Based on high-resolution cluster analysis of 176,182 single cells, three pathogenic core clusters were precisely located in the PRE (pre-treatment) group. Figure 1 and Figure 2 As shown, three specifically enriched pathogenic subsets were identified in SLE patients:

[0097] Figure 1Cluster 1 consists of memory B cells that highly express AIM2, while Clusters 2 and 3 are plasma cell lines that highly express XBP1 / JCHAIN. These three subsets are enriched in SLE patients (PRE) and are deeply depleted after dual-target CAR-T therapy (POST).

[0098] Figure 2 A violin plot showing the expression levels of classic B cell lineage markers in seven cell populations. Key markers identified different subsets; TCL1A and IGHD defined naive B cells (Cluster 0); AIM2 showed a unique pre-existing high expression pattern in memory B cells (Cluster 1); while XBP1 and JCHAIN ​​were highly co-expressed in plasma cells (Cluster 2 and 3).

[0099] Cluster 1 (inflammatory memory B cells): This subset specifically highly expresses the AIM2 gene (Log2FC>1.5 compared to healthy controls, P<0.001). AIM2 acts as a cytoplasmic dsDNA sensor, suggesting that this subset possesses high inflammatory sensing activity. Simultaneously, this subset is enriched in GPR183 molecules, which are present in CD4+ cells. + T cells exhibit strong directed chemotaxis under induction and are a key memory source driving the persistence of systemic inflammation.

[0100] Cluster 2 and Cluster 3 (plasma cell lines): These two subpopulations specifically highly express XBP1, JCHAIN, and MZB1 (Log2FC>2.0, P<0.001 compared to healthy controls), encompassing the complete functional program of plasma cells from differentiation-driven processes, antibody folding, to polymerization and secretion. Comparative analysis revealed a large number of subtypes with low CD19 expression but high BCMA expression in these cells.

[0101] In the CD19 single-target treatment cohort, due to the lack of antigen expression, this subgroup exhibits refractory residual disease or even a resurgence in proportion (e.g., the proportion of Cluster 3 increased from 6.78% to 12.19%), constituting a "molecular hidden danger" of treatment relapse.

[0102] After adopting the BCMA-CD19 dual-target CAR-T therapy strategy, the Cluster 3 proportion was deeply cleared from 9.55% at baseline to 3.12%.

[0103] By screening the above-mentioned genes, patients with such "refractory residual lesions" in their bodies can be accurately identified, providing a scientific basis for selecting BCMA-CD19 dual-target CAR-T therapy for them.

[0104] BCR isotype analysis: such as Figure 3As shown, the scRepertoire package was used to analyze BCR isotypes, and the results are as follows. Figure 3 As shown, this illustrates the structural characteristics of the immune system at different stages.

[0105] Figure 3 A shows the composition of the BCR library of the healthy control group (HC), which is dominated by immature / initial IgM (IGHM) isotypes (accounting for about 70%), indicating a healthy immune homeostasis.

[0106] Figure 3 B shows the composition of the BCR library in SLE patients before BCMA-CD19 dual-target CAR-T therapy (PRE). Significant pathological class-switching is observed, with a substantial increase in the proportion of pathogenic IgG (IGHG) and IgA (IGHA) isotypes (becoming dominant), while the proportion of IgM is significantly reduced (<50%), reflecting a highly activated humoral immune state.

[0107] Figure 3 C shows the composition of the BCR repertoire after the patient received BCMA-CD19 dual-target CAR-T therapy and achieved clinical remission (POST). It is evident that the isotype distribution underwent a fundamental reversal, returning to an IgM-dominated morphology (>80%), while the proportions of IgG and IgA were compressed to extremely low levels. This directly demonstrates that the treatment successfully achieved a "humoral reset," that is, clearing the pathogenic memory and rebuilding a new, healthy immune system.

[0108] Theoretical establishment of the BCR scoring system (based on immune repertoire sequencing data)

[0109] Based on 10x Genomics V(D)J sequencing data, the distribution of heavy chain isotypes in healthy controls (HC), pre-treatment (PRE), and post-treatment (POST) samples was analyzed. Figure 3 At the single-cell sequencing level, the isotype ratio can directly reflect the class switching status of the B cell library.

[0110] 1. Healthy baseline (HC): IgM relative expression level was approximately 70%, and IgG+IgA accounted for approximately 30%. Based on sequencing data, the isotype ratio was calculated as (IgG%+IgA%) / IgM% = 0.3 / 0.7 ≈ 0.43. Therefore, this study deduced from underlying omics data that a BCR score < 0.5 can be used as a criterion for good immune reconstitution (Humoral Reset).

[0111] 2. Disease Status (PRE): Patients exhibit a significant class shift, with IgM prevalence decreasing to <50% and IgG+IgA prevalence >50%. In typically highly active patients, IgG+IgA may reach 60%-70%. Based on sequencing data, the proportion is calculated as: 0.6 / 0.4 = 1.5. Therefore, a BCR score > 1.5 is set as the theoretical threshold for identifying highly pathogenic plasma cell / memory B cell burden and recommending dual-target therapy.

[0112] Based on the macroscopic proportion threshold established in high-throughput single-cell sequencing, the applicant further transformed it into an equivalent calculation formula based on the relative expression level of real-time quantitative PCR (qPCR) when developing a universally applicable clinical diagnostic tool: BCR score = (2 -ΔCt(IgG) +2 -ΔCt(IgA) ) / 2 -ΔCt(IgM) This formula follows the exponential kinetics principle of PCR amplification, reducing the logarithmic Ct value to a linear expression level, thus objectively reflecting the relative dominance of expression levels of each isotype transcript. This transformation allows ordinary clinical laboratories to accurately reproduce the results of expensive single-cell sequencing using only qPCR (see Example 2 for specific clinical applications).

[0113] Example 2: Verification of the universality of AIM2 and other genes based on qPCR technology and the basis for reagent kit development

[0114] To verify the universality of the biomarkers discovered in Example 1 in a larger sample size and to establish a low-cost detection method that is easy to promote in clinical practice, this example constructs a detection system based on real-time quantitative PCR (qPCR).

[0115] 1. Verification queue construction

[0116] Subjects: The study expanded to include 20 patients with active SLE (SLEDAI≥6) as the “SLE validation group” and 20 healthy volunteers as the “healthy control group”. Venous blood was collected from both SLE patients and healthy volunteers, and peripheral blood mononuclear cell (PBMC) samples were collected as independent validation cohorts.

[0117] The preparation of peripheral blood mononuclear cells (PBMCs) is described in Example 1.

[0118] 2. Total RNA extraction and reverse transcription

[0119] (1) RNA extraction

[0120] Take frozen PBMCs samples (approximately 5 × 10⁻⁶) 6Cells were lysed by repeatedly pipetting 1 mL of TRIzol reagent (Invitrogen). 200 μL of chloroform was added, and the mixture was vigorously vortexed for 15 seconds, then incubated at room temperature for 3 minutes. The cells were centrifuged at 12,000 g for 15 minutes at 4°C. The colorless aqueous supernatant was transferred to a new centrifuge tube, and 500 μL of isopropanol was added to precipitate the RNA. After centrifugation again, the precipitate was washed with 75% ethanol, dried, and dissolved in 20 μL of RNase-free water. RNA concentration and purity (A260 / A280 between 1.8 and 2.0) were determined using NanoDrop.

[0121] (2) Reverse transcription (cDNA synthesis)

[0122] Reverse transcription was performed using the PrimeScript™ RT reagent Kit (Takara), following the kit's instructions for reverse transcription (cDNA synthesis).

[0123] Reaction system (20 μL): 500 ng total RNA, 4 μL 5× PrimeScript Buffer, 1 μL PrimeScriptRT Enzyme Mix, 1 μL Oligo dT Primer, 1 μL Random 6 mers, add water to 20 μL.

[0124] Reaction procedure: 37℃ for 15 minutes, 85℃ for 5 seconds, store at 4℃.

[0125] 3. Real-time quantitative PCR (qPCR) detection

[0126] The tests were performed using the Applied Biosystems QuantStudio 5 real-time PCR system.

[0127] Reaction system (20 μL): 10 μL TB Green Premix Ex Taq II (2×), 0.8 μL forward primer (10 μM), 0.8 μL reverse primer (10 μM), 0.4 μL ROX Reference Dye, 2 μL cDNA template, 6 μL sterile water.

[0128] Primer Sequence Design: Specific primers were designed for AIM2, XBP1, JCHAIN, IGHM, IGHG1, IGHHA1, and the internal reference gene GAPDH. The primers used in this invention (SEQ ID NO: 1-14) are all specially designed, with the forward and reverse primers located at different exons and exon-exon junctions of the target gene, spanning at least one intron. This cross-intron design ensures that the PCR reaction specifically amplifies only mature mRNA cDNA, without amplifying genomic DNA (gDNA), thus guaranteeing that the Ct value accurately reflects the gene's transcriptional expression level and eliminating false-positive interference caused by gDNA contamination.

[0129] The specific primer nucleotide sequences are shown in Table 1 (SEQ ID NO:1-14).

[0130] Primer name code name Nucleotide sequence (5' to 3') AIM2 forward primer SEQ ID NO:1 ATGTTCGGTACTATGGAGCCG AIM2 reverse primer SEQ ID NO:2 GTCACAACATTTGCCTGCTC XBP1s cleavage-type forward primer SEQ ID NO:3 CTGAGTCCGCAGCAGGTG XBP1s cleavage-type reverse primer SEQ ID NO:4 TCCAGAATGCCCAACAGG JCHAIN ​​forward primers SEQ ID NO:5 GTTAATCTTTCAGTCGTGCAGA JCHAIN ​​reverse primer SEQ ID NO:6 CTCAGGGTAGCAAGTGGC GAPDH internal control forward primer SEQ ID NO:7 GTCTCCTCTGACTTCAACAGCG GAPDH internal reference reverse primer SEQ ID NO:8 ACCACCCTGTTGCTGTAGCCAA IgM heavy chain constant region forward primer ★ SEQ ID NO:9 AAGTCAGCCAACATGGCCAT IgM heavy chain constant region reverse primer SEQ ID NO:10 GTTCTCGTGCCTCTCAGGTC Pan-IgG heavy chain constant region forward primer ◆ SEQ ID NO:11 TCCACCAAGGGCCCATCGG Pan-IgG heavy chain constant region reverse primer SEQ ID NO:12 GTTGTCCACCTTGGTGTTGC Pan-IgA heavy chain constant region forward primer ■ SEQ ID NO:13 CAGCACCTACCTGGTGATCG Pan-IgA heavy chain constant region reverse primer SEQ ID NO:14 CCTGGGCACGCTGGTACT

[0131] ★IgM heavy chain constant region forward primer: specifically binds to the Cμ domain of the human IGHM constant region.

[0132] ◆Pan-IgG heavy chain constant region forward primer: designed to bind to the conserved constant region of human IgG subtypes (IgG1-4).

[0133] ■ Pan-IgA heavy chain constant region forward primer: designed to bind to the conserved constant region of human IgA subtypes (IgA1 / 2).

[0134] Reaction program: Pre-denaturation 95℃ for 30 seconds; Cycling stage (40 cycles): 95℃ for 5 seconds, 60℃ for 34 seconds; Melting curve stage: 95℃ for 15 seconds, 60℃ for 1 minute, 95℃ for 15 seconds.

[0135] 4. Data Analysis and Results

[0136] BCR scores were calculated based on the mRNA transcript levels of the IGHM, IGHG, and IGHA genes; the distribution of BCR immunoglobulin heavy chain isotypes was assessed using the BCR scores.

[0137] The BCR score, designed to assess the isotype distribution of B-cell immunoglobulin heavy chains, is based on the B-cell class switching mechanism: IGHM represents the naïve B cell state without class switching, while IGHG and IGHA represent the pathogenic memory B cell or plasma cell state that has undergone class switching. The BCR score, as the ratio of these two [(IgG+IgA) / IgM], indicates that a higher score indicates a more pathogenic class-switched B-cell pool in the patient (i.e., a 'high-load' state suitable for dual-target therapy); a lower score indicates that the immune system is closer to a healthy, naïve initial state dominated by IgM (i.e., a state of successful 'immune reset').

[0138] The BCR score is defined as the ratio of the sum of IgG and IgA transcripts to IgM transcripts, calculated using the following formula:

[0139] BCR score = (2 -ΔCt(IgG) +2 -ΔCt(IgA) ) / 2 -ΔCt(IgM) ;

[0140] ΔCt(IgG) = Ct(IgG) - Ct(GAPDH)

[0141] ΔCt(IgA)=Ct(IgA)-Ct(GAPDH)

[0142] ΔCt(IgM) = Ct(IgM) - Ct(GAPDH)

[0143] GAPDH is an internal reference gene;

[0144] ΔCt(IgG) represents the relative expression level of IGHG heavy chain constant region mRNA; ΔCt(IgA) represents the relative expression level of IGHG heavy chain constant region mRNA; ΔCt(IgM) represents the relative expression level of IGHM heavy chain constant region mRNA.

[0145] The relative mRNA expression levels of AIM2, XBP1, and JCHAIN ​​genes were 2, respectively. -ΔΔCt_AIM2 2 -ΔΔCt_XBP1 2 -ΔΔCt_JCHAIN The calculation formula is as follows:

[0146] ΔΔCt=ΔCt(Target)-ΔCt(Healthy_Avg)

[0147] ΔCt(Target)=Ct(Target)-Ct(GAPDH)

[0148] ΔCt(Healthy_Avg)=Ct(Healthy_Avg)-Ct(GAPDH)

[0149] Target refers to the mRNA of AIM2, XBP1, and JCHAIN ​​genes in PBMCs of SLE patients in qPCR reaction, GAPDH is the mRNA of the internal reference gene, Healthy_Avg refers to the arithmetic mean of the relative expression levels of AIM2, XBP1, and JCHAIN ​​genes in PBMCs of healthy individuals in qPCR reaction, and ΔCt(Healthy_Avg) is used as the baseline to calculate the fold change of patient samples relative to healthy individuals.

[0150] The results analysis is as follows: Figure 4 .

[0151] Figure 4 A shows the relative expression level (Fold Change) of the inflammatory marker AIM2. The AIM2 mRNA level in the SLE patient group was significantly higher than that in the healthy control group (P<0.0001), and the expression level in most patients was more than 5 times that of the control group, which verified the universality of AIM2 as an indicator of inflammatory memory B cell burden.

[0152] Figure 4 B shows the relative expression level of plasma cell differentiation factor XBP1, which was significantly higher in the SLE patient group (P<0.0001), suggesting the presence of abnormally expanded plasma cell lineages in the patients.

[0153] Figure 4 C shows the relative expression level of the antibody linker chain JCHAIN, and its expression trend is highly consistent with that of XBP1, further confirming the high load state of pathogenic antibody-secreting cells.

[0154] Figure 4 D shows the BCR score, which was significantly higher in the SLE patient group than in the healthy control group, directly reflecting that pathological antibody class-switching is a common molecular feature of active SLE.

[0155] Example 3: Screening method and judgment criteria based on high-throughput sequencing (NGS) technology

[0156] In addition to the qPCR method detailed in Example 2, this invention also establishes screening criteria based on high-throughput sequencing. This method is suitable for clinical scenarios requiring simultaneous acquisition of a patient's comprehensive immune profile. The sequencing data basis of this example is consistent with that of Example 1, and the subpopulation distribution characteristics of its raw data are shown in Figures 1 and 2, while the BCR isotype distribution characteristics are shown in Figure 3. This example further transforms the above graphical characteristics into clinically executable quantitative judgment criteria (TPM and Ratio).

[0157] 1. Library construction and sequencing

[0158] Total RNA was extracted from patient PBMCs, and a 5' gene expression library containing UMI (molecular tag) and a BCR V(D)J enriched library were constructed (the specific library construction and sequencing steps are the same as in Example 1). Sequencing was performed on the Illumina sequencing platform, and it is recommended that the sequencing depth be no less than 20M reads / sample to ensure the sensitivity for detecting low-abundance plasma cell subsets.

[0159] 2. Data standardization

[0160] The raw sequencing data were aligned to the GRCh38 human reference genome. Unlike the cluster analysis in Example 1, this example directly calculated the normalized expression level of the target gene, specifically using TPM (Transcripts Per Million) as the unit of measurement to eliminate the influence of sequencing depth and gene length on the quantification results.

[0161] 3. Filtering and Judgment Algorithm

[0162] This invention establishes a quantification formula applicable to sequencing data:

[0163] (1) Determination of inflammation / plasma cell load:

[0164] Calculate the ratio Ratio_AIM2 = TPM_patient / TPM_healthy_avg.

[0165] Wherein, TPM_patient is the TPM value of the target gene in the sample of the patient to be tested; TPM_healthy_avg is the mean value of the healthy control group.

[0166] Judgment criteria:

[0167] This invention establishes a quantification formula applicable to sequencing data:

[0168] (1) Determination of inflammation / plasma cell load:

[0169] Calculate the ratio Ratio_AIM2 = TPM_patient / TPM_healthy_avg.

[0170] Wherein, TPM_patient is the TPM value of the target gene in the patient sample to be tested; TPM_healthy_avg is the mean value of the healthy control group, and the target genes are AIM2, XBP1, and JCHAIN.

[0171] Judgment criteria:

[0172] A. Ratio_AIM2>2 (i.e., AIM2 expression level is more than 2 times higher than the mean of healthy control group) is judged as positive, and BCR category switching is dominant (positive).

[0173] B. Ratio_XBP1>3 (i.e., XBP1 expression level is more than 3 times higher than the mean of healthy control group) is judged as positive, and BCR category switching is dominant (positive).

[0174] C. Ratio_JCHAIN>3 (i.e., JCHAIN ​​expression level is more than 3 times higher than the mean of healthy control group) is judged as positive, and BCR category switching is dominant (positive).

[0175] Determination of BCR category conversion:

[0176] The raw sequence counts aligned to the constant region of the immunoglobulin heavy chain were extracted from the BCR V(D)J library data.

[0177] Calculate the sequencing score: Score_seq = (Count_IgG + Count_IgA) / Count_IgM.

[0178] Among them, Count_IgG, Count_IgA, and Count_IgM represent the total number of reads that were matched to the IGHG, IGHA, and IGHM constant region genes, respectively.

[0179] Judgment criteria:

[0180] If Score_seq > 1.5, BCR is determined to be a class-transformation dominance type (positive).

[0181] If the sample to be tested meets any one or more of the above conditions, then the SLE patient is determined to be a suitable candidate for BCMA-CD19 dual-target CAR-T therapy.

[0182] Based on the single-cell transcriptome characteristics revealed in Example 1, the NGS screening criteria constructed in this example converts the relative abundance of genes such as AIM2 into standardized TPM and Reads ratios. Theoretically, this judgment logic is based on the same biological basis as the qPCR method in Example 2, and therefore can serve as an effective alternative or supplementary solution to qPCR detection in clinical scenarios requiring a comprehensive assessment of the patient's immune profile.

[0183] Terminology definitions and parameter descriptions:

[0184] TPM (Transcripts Per Million): refers to the number of transcripts per million transcripts. It is a unit of measurement for gene expression levels that is dually standardized by gene length and sequencing depth to ensure data comparability between different samples.

[0185] Reads count: refers to the number of original sequences read that are specifically mapped to a specific region of the target gene (specifically the IGH constant region in this invention) during high-throughput sequencing data alignment.

[0186] The mean TPM of healthy controls (TPM_healthy_avg) refers to the arithmetic mean of the TPM values ​​of the target gene measured from a group (e.g., n≥3) of healthy volunteers' PBMCs samples under the conditions of using the same sequencing platform and library preparation method.

[0187] Example 4: Clinical application verification of genes such as AIM2 in CAR-T therapy screening and prognostic assessment

[0188] This embodiment focuses on verifying the correlation between the aforementioned AIM2 and other genes and the clinical efficacy of dual-target CAR-T therapy, demonstrating the effectiveness of the screening method based on AIM2 and other genes.

[0189] Clinical efficacy assessment criteria: Disease activity was assessed using the SLEDAI-2K scoring system. Anti-dsDNA antibody titers, complement C3 / C4 levels, and 24-hour urinary protein quantification were monitored. "Clinical remission" was defined as SLEDAI <4 and no new active lesions.

[0190] Three months after treatment, all five patients with refractory SLE achieved clinical remission.

[0191] Correlation analysis of AIM2 and other genes with efficacy can be found in [link to relevant analysis]. Figure 5 ,

[0192] Figure 5 This is a paired analysis of clinical and immunological parameters before (PRE) and after (POST) treatment in 5 patients with refractory SLE who received BCMA-CD19 dual-target therapy. Figure 5 All subplots were presented using box-violin plots, where the boxes represent the interquartile range and median, the violin plots represent the density distribution, and the red dots represent the means of each group. The results showed that patients receiving dual-target therapy who reached the B-cell remodeling phase exhibited highly significant clinical benefits, as follows:

[0193] (1) Significant decrease in disease activity: The SLEDAI-2K score decreased significantly from a baseline mean of 9.6 to 2.4 (P<0.05);

[0194] (2) Serological indicators turned negative or normalized: all pathogenic anti-dsDNA antibodies turned negative (from high titer at baseline to 0 IU / mL), ANA (antinuclear antibody) titer and total IgA level decreased significantly, and complement C3 / C4 level returned to normal rapidly within 1 month;

[0195] (3) Significant repair of damaged organ function: The core indicator reflecting kidney damage, UACR (urine protein / creatinine ratio), showed a significant decrease.

[0196] (4) Physical clearance of cell subpopulations: The proportion of characteristic pathogenic cell subpopulations (Cluster 1, Cluster 2 / 3) defined by AIM2, XBP1, and JCHAIN ​​genes in Example 1 has basically disappeared, which is highly consistent with the deep clearance of characteristic pathogenic cell subpopulations (Cluster 1, Cluster 2 / 3) defined by AIM2, XBP1, and JCHAIN ​​genes in Example 1 at the physical level.

[0197] All the above statistics were performed using paired t-tests, and p-values ​​were corrected using the Holm method. Figure 5 This study directly validated the high degree of consistency between the clearance of pathogenic cells defined by the AIM2, XBP1, and JCHAIN ​​genes and macroscopic clinical remission and organ function repair.

[0198] Correlation statistics and causal association verification (see) Figure 6 ):

[0199] To determine whether the clinical benefit is indeed driven by the clearance of the genes described in this application, we have defined a measure of change:

[0200] Define ΔMetric as: Pre-treatment expression level - Post-treatment expression level.

[0201] Define ΔSLEDAI = pre-treatment score - post-treatment score.

[0202] like Figure 6 As shown, we constructed a scatter plot of the correlation between the degree of AIM2, XBP1, and JCHAIN ​​gene clearance and clinical efficacy.

[0203] Figure 6 A showed the correlation between the degree of AIM2 clearance and the extent of improvement in SLEDAI. Pearson correlation analysis showed a significant positive correlation between the two (r>0.9, P<0.05), indicating that the more thorough the clearance of inflammatory memory B cells, the more significant the relief of patients' inflammatory symptoms.

[0204] Figure 6B showed the correlation between the degree of XBP1 clearance and the extent of improvement in SLEDAI (r>0.9, P<0.05), indicating that the reduction in plasma cell load directly drove the improvement in the condition.

[0205] Figure 6 C demonstrated a positive correlation between the degree of JCHAIN ​​clearance and the extent of improvement in SLEDAI, further supporting the above conclusion. This result statistically establishes that "AIM2, XBP1, and JCHAIN ​​gene clearance" is a necessary condition for clinical remission, rather than a concomitant phenomenon.

[0206] Based on the above data, we established a set of methods for screening suitable BCMA-CD19 dual-target CAR-T therapy regimens and determining prognosis: the establishment of the screening and prognostic assessment process is described in [link to documentation]. Figure 7 , Figure 7 The entire process from sample input to clinical decision output is clearly demonstrated: Screening stage: The system receives the patient's PBMC sample test data. If it is determined that the conditions of "high expression of AIM2 or XBP1 or JCHAIN" and "BCR showing IgG / IgA dominance" are met, the system outputs the decision suggestion of "recommending dual-target CAR-T therapy", thereby accurately identifying the beneficiary population.

[0207] Prognostic assessment phase: At the post-treatment follow-up point (1-6 months), the differential gene levels before and after treatment are systematically compared. If the dual criteria of "AIM2 / XBP1 / JCHAIN ​​expression returning to healthy baseline" and "BCR repertoire returning to IgM dominance (>80%)" are met, the assessment result of "Successful Humoral Reset" is output; otherwise, "Risk of Molecular Relapse" is indicated. This flowchart provides clinicians with standardized guidelines for companion diagnostic procedures, and prognostic assessment can be used during the B-cell remodeling phase (any time from 1 to 6 months after treatment).

[0208] Input: qPCR Ct values ​​of patient PBMCs.

[0209] Filtering and interpretation: If (2 -ΔΔCt_AIM2 >2 or 2 -ΔΔCt_XBP1 >3 or 2 -ΔΔCt_JCHAIN >3) If the BCR score is >1.5, output "Recommended dual-target therapy".

[0210] Prognostic assessment: If 2 days after treatment -ΔΔCt_AIM2 <1.5 and 2 -ΔΔCt_XBP1 <1.5 and 2 -ΔΔCt_JCHAIN If the score is <1.5 and the BCR score is <0.5 (i.e., IgM dominance), the output will be "Humoral immune reset successful, good prognosis".

[0211] In summary, this application, through rigorous experimental design, large-sample validation, and clinical correlation analysis, demonstrates that methods based on the detection of AIM2, XBP1, JCHAIN, and BCR isotypes can serve as a basis for recommending dual-target CAR-T therapy for SLE. It not only provides a patient screening protocol for dual-target CAR-T therapy for SLE but also defines the molecular criteria for "cure," possessing significant clinical application value.

[0212] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. In addition, those skilled in the art should understand that the quantitative thresholds (such as TPM ratio, Ct difference, etc.) involved in the above claims and embodiments are obtained based on the specific detection platform (high-throughput single-cell sequencing and qPCR system) and specific sample cohort (such as the median time point of peripheral B cell remodeling) used in the embodiments of the present invention. Due to the systematic error of the detection instrument and individual differences, the values ​​may have reasonable fluctuations in actual clinical applications (e.g., ±10% or ±1 Ct value). However, the biological trend of "reversal from pathogenicity class conversion state to primary healthy state" reflected by the value constitutes the essential inventive point of the present invention, and any numerical fine-tuning based on this inventive concept should fall within the protection scope of this application. Furthermore, those skilled in the art should understand that, in addition to the qPCR and sequencing technologies detailed in the embodiments, gene chip (microarray) technology can also be used to implement screening methods based on the teachings of this invention. Based on the sequence information of AIM2, XBP1, JCHAIN, and immunoglobulin heavy chain constant region genes disclosed in this invention, those skilled in the art can routinely design specific hybridization probes and prepare solid-phase chips using known techniques. The specific implementation process includes: extracting total RNA from patient PBMCs and reverse transcribing it into fluorescently labeled cDNA or cRNA (such as Cy3 / Cy5 labeling); hybridizing the labeled product with a chip containing the above-mentioned gene-specific probes; and scanning the fluorescence signal intensity after eluting unbound molecules. By comparing the signal intensity, the fold change in expression level relative to healthy controls can be calculated, and the determination logic is consistent with the qPCR and sequencing methods described in this invention.

Claims

1. An in vitro detection method for screening systemic lupus erythematosus (SLE) patients suitable for BCMA-CD19 dual-target chimeric antigen receptor T-cell (CAR-T) immunotherapy, characterized in that, Includes the following steps: (1) Obtain peripheral blood mononuclear cell (PBMC) samples from the SLE patients to be tested; (2) Detect the mRNA expression levels of AIM2, XBP1, and JCHAIN ​​genes, as well as the mRNA expression levels of the immunoglobulin heavy chain constant region encoding genes (IGHM, IGHG, IGHA) in the sample; (3) Compare the test data with the baseline of healthy controls; (4) If one or more of the following conditions are met, the patient is deemed suitable for BCMA-CD19 dual-target CAR-T therapy: a) AIM2 expression levels were significantly higher than in healthy controls; b) XBP1 and / or JCHAIN ​​expression levels were significantly higher than in healthy controls; c) Based on BCR score assessment, the immunoglobulin heavy chain constant region showed an IgG or IgA expression advantage, that is, the sum of IgG and IgA expression levels was higher than IgM expression level; The detection steps can employ real-time quantitative PCR (qPCR), high-throughput transcriptome sequencing (RNA-seq), single-cell transcriptome sequencing (scRNA-seq), or gene chip technology; BCR refers to the B-cell receptor, AIM2 to melanoma deficiency factor 2, XBP1 to X-box binding protein 1, and JCHAIN ​​to the antibody linker chain; the BCR score is defined as the ratio of the sum of IgG and IgA transcripts to IgM transcripts. BCR score = (2 -ΔCt(IgG) +2 -ΔCt(IgA) ) / 2 -ΔCt(IgM) ; IGHM, IGHG, and IGHA refer to the heavy chain constant region encoding genes of immunoglobulins M, G, and A (IgM, IgG, and IgA), respectively. In this invention, the isotype distribution of B cells is assessed by detecting the mRNA transcript levels of these genes. In the BCR scoring formula: ΔCt(IgG) represents the relative expression level of IGHG heavy chain constant region mRNA measured using primers SEQ ID NO: 11-12; ΔCt(IgA) represents the relative expression level of IGHA heavy chain constant region mRNA measured using primers SEQ ID NO: 13-14; ΔCt(IgM) represents the relative expression level of IGHM heavy chain constant region mRNA measured using primers SEQ ID NO: 9-10. The design principle of the BCR score is based on the B cell class switching mechanism: IGHM represents naïve B cells that have not undergone class switching. The B cell count (IgG+IgA) represents the state of pathogenic memory B cells or plasma cells that have undergone class switching. The BCR score, which is the ratio of the two ((IgG+IgA) / IgM), indicates that the higher the value, the more the patient's B cell pool is biased towards a pathogenic class-switched state (i.e., a 'high-load' state suitable for dual-target therapy). The lower the value, the closer the immune system is to the healthy initial state dominated by IgM (i.e., a state of successful 'immune reset'). Use 2 -ΔΔCt The relative mRNA expression levels of AIM2, XBP1, and JCHAIN ​​were calculated using the following formula: ΔCt=Ct(Target)-Ct(GAPDH) ΔΔCt=ΔCt(Sample)-ΔCt(Healthy_Avg) The relative expression level of AIM2 mRNA was 2. -ΔΔCt_AIM2 The relative expression level of XBP1 mRNA is 2. -ΔΔCt_XBP1 The relative mRNA expression level of JCHAIN ​​is 2. -ΔΔCt_JCHAIN The term "Target" refers to the target gene to be detected in this qPCR reaction, specifically selected from AIM2, XBP1, JCHAIN, IGHM, IGHG, or IGHA. The GAPDH mentioned is an internal reference gene; The "Sample" refers to a peripheral blood mononuclear cell (PBMC) sample from an SLE patient to be tested. The Healthy_Avg refers to the average ΔCt value of the target gene in the Healthy Control sample (i.e., the arithmetic mean of (Target) - Ct(GAPDH); this value is used as a baseline to calculate the fold change of the patient sample relative to healthy individuals.

2. An in vitro detection method for predicting the prognosis of SLE patients after receiving BCMA-CD19 dual-target CAR-T therapy, characterized in that, Includes the following steps: (1) Obtain PBMCs samples from SLE patients in the B-cell remodeling phase after treatment; (2) Detect the mRNA expression levels of AIM2, XBP1, and JCHAIN ​​genes and the transcript levels of IgG, IgA, and IgM in the sample; (3) Compare the test data with the baseline of healthy controls; The detection methods can also include qPCR, RNA-seq, scRNA-seq, or gene chip technology; AIM2 is melanoma deficiency factor 2, XBP1 is X-box binding protein 1, and JCHAIN ​​is an antibody linker chain. (4) The following conditions are met for SLE patients to have a good prognosis. The relative mRNA expression level of AIM2 was <1.5 and the relative mRNA expression level of XBP1 was <1.5, and the BCR score was <0.5; Or the relative mRNA expression level of AIM2 is <1.5 and the relative mRNA expression level of JCHAIN ​​is <1.5 and the BCR score is <0.5; The BCR mentioned above refers to the B cell receptor, and the BCR score is defined as the ratio of the sum of IgG and IgA transcripts to IgM transcripts. BCR score = (2 -ΔCt(IgG) +2 -ΔCt(IgA) ) / 2 -ΔCt(IgM) ; IGHM, IGHG, and IGHA refer to the heavy chain constant region encoding genes of immunoglobulins M, G, and A (IgM, IgG, and IgA), respectively. In this invention, the isotype distribution of B cells is assessed by detecting the mRNA transcript levels of the above genes. In the BCR scoring formula: ΔCt(IgG) represents the relative expression level of IGHG heavy chain constant region mRNA measured using primers SEQ ID NO: 11-12; ΔCt(IgA) represents the relative expression level of IGHA heavy chain constant region mRNA measured using primers SEQ ID NO: 13-14; ΔCt(IgM) represents the relative expression level of IGHM heavy chain constant region mRNA measured using primers SEQ ID NO: 9-10. Use 2 -ΔΔCt The relative mRNA expression levels of AIM2, XBP1, and JCHAIN ​​were calculated using the following formula: ΔCt=Ct(Target)-Ct(GAPDH) ΔΔCt=ΔCt(Sample)-ΔCt(Healthy_Avg) The relative expression level of AIM2 mRNA was 2. -ΔΔCt_AIM2 The relative expression level of XBP1 mRNA is 2. -ΔΔCt_XBP1 The relative mRNA expression level of JCHAIN ​​is 2. -ΔΔCt_JCHAIN The term "Target" refers to the target gene to be detected in this qPCR reaction, specifically selected from AIM2, XBP1, JCHAIN, IGHM, IGHG, or IGHA. The GAPDH mentioned is an internal reference gene; The "Sample" refers to a peripheral blood mononuclear cell (PBMC) sample from an SLE patient to be tested. The Healthy_Avg refers to the average ΔCt value of the target gene in the Healthy Control sample (i.e., the arithmetic mean of (Target) - Ct(GAPDH); this value is used as a baseline to calculate the fold change of the patient sample relative to healthy individuals.

3. The method as described in any one of claims 1 or 2, characterized in that, The reagents for qPCR detection in (3) include: AIM2 forward primer, the nucleotide sequence of which is shown in SEQ ID NO:1; AIM2 reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:2; XBP1s cleavage type forward primer, the nucleotide sequence of which is shown in SEQ ID NO:3; XBP1s cleavage type reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:4; JCHAIN ​​forward primer, the nucleotide sequence of which is shown in SEQ ID NO:5; JCHAIN ​​reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:6; GAPDH internal control forward primer, the nucleotide sequence of which is shown in SEQ ID NO:7; GAPDH internal control reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:8; IgM heavy chain constant region forward primer, the nucleotide sequence of which is shown in SEQ ID NO:9; IgM heavy chain constant region reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:10; Pan-IgG heavy chain constant region forward primer, the nucleotide sequence of which is shown in SEQ ID NO:

10. As shown in NO:11; the reverse primer for the Pan-IgG heavy chain constant region, the nucleotide sequence of which is shown in SEQ ID NO:12; the forward primer for the Pan-IgA heavy chain constant region, the nucleotide sequence of which is shown in SEQ ID NO:13; and the reverse primer for the Pan-IgA heavy chain constant region, the nucleotide sequence of which is shown in SEQ ID NO:

14.

4. A kit for screening SLE patients suitable for BCMA-CD19 dual-target CAR-T therapy, characterized in that, The SLE patients mentioned refer to patients with systemic lupus erythematosus. The kit includes: (1) a reagent for specifically detecting the relative expression level of AIM2 gene mRNA; (2) a reagent for specifically detecting the relative expression level of XBP1 and / or JCHAIN ​​genes mRNA; and (3) a reagent for specifically detecting the transcripts of IgG, IgA, and IgM.

5. A kit for predicting the prognosis of SLE patients after BCMA-CD19 dual-target CAR-T therapy, characterized in that, The SLE patients mentioned refer to patients with systemic lupus erythematosus. The kit includes: (1) a reagent for specifically detecting the relative expression level of AIM2 gene mRNA; (2) a reagent for specifically detecting the relative expression level of XBP1 and / or JCHAIN ​​genes mRNA; and (3) a reagent for specifically detecting the transcripts of IgG, IgA, and IgM.

6. The kit according to any one of claims 4 or 5, characterized in that, The reagents described in (1) include: AIM2 forward primer, the nucleotide sequence of which is shown in SEQ ID NO:1; AIM2 reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:2; the reagents described in (2) include: XBP1s cleavage type forward primer, the nucleotide sequence of which is shown in SEQ ID NO:3; XBP1s cleavage type reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:4; JCHAIN ​​forward primer, the nucleotide sequence of which is shown in SEQ ID NO:5; JCHAIN ​​reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:6; the reagents described in (3) include: IgM heavy chain constant region forward primer, the nucleotide sequence of which is shown in SEQ ID NO:9; IgM heavy chain constant region reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:10; Pan-IgG heavy chain constant region forward primer, the nucleotide sequence of which is shown in SEQ ID NO:11; Pan-IgG heavy chain constant region reverse primer, the nucleotide sequence of which is shown in SEQ ID NO:

11. As shown in NO:12; the forward primer for the Pan-IgA heavy chain constant region, the nucleotide sequence of which is shown in SEQ ID NO:13; the reverse primer for the Pan-IgA heavy chain constant region, the nucleotide sequence of which is shown in SEQ ID NO:

14.

7. An in vitro detection method for assisting in the screening of systemic lupus erythematosus (SLE) patients suitable for BCMA-CD19 dual-target CAR-T therapy, characterized in that, Includes the following steps: (1) Obtain peripheral blood mononuclear cell (PBMC) samples from the SLE patients to be tested; (2) Detect the mRNA expression levels of AIM2, XBP1, and JCHAIN ​​genes in the sample, as well as the mRNA expression levels of the genes encoding the constant region of the immunoglobulin heavy chain (IGHM, IGHG, and IGHA); (3) Compare the test data with the baseline of healthy controls, and calculate the relative expression fold and immunoglobulin isotype ratio; (4) If one or more of the following conditions are met, the patient is deemed suitable for BCMA-CD19 dual-target CAR-T therapy: a) The mRNA expression level of AIM2 was more than twice that of the healthy control group, and the BCR score was > 1.5; b) The mRNA expression levels of XBP1 and / or JCHAIN ​​were more than 3 times higher than the mean of the healthy control group, and the BCR score was >1.5; The BCR score is the ratio of the sum of the abundance of detected IgG and IgA transcripts to the abundance of IgM transcripts. The detection step (2) uses a method selected from: high-throughput transcriptome sequencing (RNA-seq), single-cell transcriptome sequencing (scRNA-seq), or gene chip technology.

8. The method according to claim 7, characterized in that, When using high-throughput transcriptome sequencing (RNA-seq) methods, the judgment criteria include: (1) In the gene expression matrix, the transcript abundance of AIM2 (such as TPM or FPKM value) is more than twice the mean of the healthy control group, and in the BCR immune repertoire data, the ratio of the sum of the number of IgG and IgA heavy chain constant region reads to the number of IgM reads is >1.5; (2) In the gene expression matrix, the transcript abundance of XBP1 or JCHAIN ​​was more than 3 times higher than the mean of the healthy control group; (3) In the BCR immune repertoire data, the ratio of the sum of the number of IgG and IgA heavy chain constant region reads to the number of IgM reads (BCR score) is > 1.5.

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