Use of a kit for manufacturing CAR-T cell quality control and efficacy prediction

Abstract

The present application belongs to the field of bioinformatics, and specifically relates to a use of a kit for preparing CAR-T cell quality control and efficacy prediction, and more specifically to a use of a kit for preparing CAR-T cell quality control and efficacy prediction, and a panel for efficacy prediction of CAR-T cell therapy. Using the method of the present application, the tyrosine phosphorylation proteome is creatively used as the core for predicting CAR-T cell quality control and efficacy, so that a more accurate and sensitive method for predicting CAR-T cell quality control and efficacy is provided.

Description

Technical Field

[0001] This invention belongs to the field of bioinformatics, specifically, it relates to the use of a kit for preparing CAR-T cell quality control and efficacy prediction, and more specifically, it relates to the use of a kit for preparing CAR-T cell quality control and efficacy prediction, as well as a panel for predicting the efficacy of CAR-T cell therapy. Background Technology

[0002] CAR-T cell therapy is an immunotherapy that treats cancer by genetically engineering T cells. To ensure the safety and efficacy of CAR-T cell therapy, rigorous quality control is essential. Traditional quality control methods typically focus on cell phenotype and functional testing, such as those mentioned in "Key Considerations for Quality Control Testing and Non-Clinical Studies of CAR-T Cell Therapy Products" (China National Institutes for Food and Drug Control, June 5, 2018), including cell identification, exogenous factor contamination (including non-viral and viral endogenous and exogenous factors), cell karyotype, tumorigenicity, stability, and immunoreactivity. However, these methods remain insufficient for comprehensively assessing the biological characteristics of CAR-T cells.

[0003] Distinguishing between peripheral blood mononuclear cells (PBMCs) and CAR-T cells, and comparing their biological characteristics, helps to assess and predict the clinical efficacy of CAR-T cell therapy, and provides a more rigorous, reliable, and safe standard for quality control before CAR-T infusion.

[0004] Therefore, there is a need in the art for the use of a kit for preparing a CAR-T cell therapy efficacy prediction kit, thereby assisting in the evaluation and prediction of the clinical treatment effects of CAR-T cell therapy. Summary of the Invention

[0005] In view of this, in a first aspect, the present invention provides the use of a kit for preparing CAR-T cell quality control and efficacy prediction, comprising the following steps:

[0006] S1. Obtain proteins from the samples, which are CAR-T cells and peripheral blood mononuclear cells, respectively.

[0007] S2. Perform enzymatic hydrolysis on the protein obtained in step S1;

[0008] S3. The protein obtained after enzymatic hydrolysis in step S2 is enriched with tyrosine-phosphorylated proteins to obtain a tyrosine-phosphorylated protein group.

[0009] S4. Collect the data of the tyrosine phosphorylated proteome obtained in step S3, and analyze the data using principal component analysis (PCA).

[0010] S5. Compare the PCA analysis data of the tyrosine phosphorylated proteome of CAR-T cells and monocytes. If the clustering regions of CAR-T cells and monocytes are different, it indicates that CAR-T cell construction was successful.

[0011] Furthermore, the application also includes the following steps:

[0012] S6. Identify tyrosine phosphorylation sites, wherein the tyrosine phosphorylation sites are sites where tyrosine phosphorylation occurs in both the CAR-T cells and monocytes;

[0013] S7. Predict the efficacy of CAR-T cell therapy, wherein the Z-value of step S6 and the standard is calculated according to the following formula:

[0014]

[0015] Then, the Z-values ​​of step S6 and the standard are compared by a t-test. If the median Z-value of step S6 is greater than the median Z-value of the standard and its p-value is less than 0.05, it indicates that the therapeutic effect is not good.

[0016] Furthermore, the number of tyrosine phosphorylation sites in step S6 is ≥10.

[0017] Furthermore, the sample comes from an individual with a certain lesion; more specifically, the lesion is a tumor. Even further, the lesion is acute lymphoblastic leukemia, chronic myeloid leukemia, or B-cell lymphoma.

[0018] Furthermore, CAR-T cells are CAR-T cells containing a 4-1BB co-stimulatory domain that target CD19.

[0019] Furthermore, the samples consisted of CAR-T cells and monocytes from the same individual.

[0020] Furthermore, the number of said cells is 1 × 10⁻⁶. 7 ~1×10 8 Preferably, 5×10 7 .

[0021] Furthermore, the monocytes are peripheral blood monocytes.

[0022] Further, in step S7, the standard can be an individual whose lesion has not relapsed after receiving CAR-T cell therapy. Preferably, the standard is the average value of two individuals whose lesion has not relapsed after receiving CAR-T cell therapy.

[0023] Furthermore, in step S1, the protein in the sample can be obtained using any conventional protein extraction method in the art. In one specific embodiment, step S1 includes:

[0024] Cells were washed twice with ice-cold PBS, and 500 μL of ice-cold cell lysis buffer was added. The mixture was vortexed and kept on ice for 30 minutes for lysis. Cells were then sonicated for 2 minutes on ice using a sonicator with the sonication settings set to 5 seconds on, 5 seconds off. After sonication, the cell lysis buffer was centrifuged at 150,000 g for 10 minutes at 4°C. The supernatant was transferred to a new 15 mL centrifuge tube, and protein concentration was determined using BCA. Four volumes of ice-cold methanol were added, and the mixture was vortexed. One volume of chloroform was added, and the mixture was vortexed again. Three volumes of ice-cold H₂O were then added, and the mixture was vortexed again. The tube was then centrifuged at 11,000 g for 3 minutes at 4°C. The liquid was discarded, and four volumes of methanol were added. The protein precipitate was gently washed with a finger, and the tube was centrifuged at 11,000 g for 3 minutes at 4°C to remove as much methanol as possible. The tube was then air-dried at room temperature for 5-10 minutes.

[0025] Further, in step S2, the protein digestion can be performed using any conventional protein extraction method in the art. In some specific embodiments, the protein digestion includes protein reduction, alkylation, and enzymatic digestion. In one specific embodiment, step S2 includes:

[0026] Dissolve the protein precipitate from step S1 in urea buffer. After complete dissolution, add DTT to a final concentration of 10 mM and react the solution at 55°C for 25 minutes using a metal mixer. Add IAA to a final concentration of 30 mM and react at room temperature in the dark for 30 minutes using a metal mixer. Add DTT to a final concentration of 20 mM and continue reacting in the dark for 15 minutes. Add 7 volumes of 50 mM Tris-HCl (pH 8.5), add CaCl2 to a final concentration of 1 mM, and add Trypsin at a 1:100 ratio. Incubate overnight using a rotary mixer at 37°C. Acidify the digested peptides with 10% TFA to a pH of 2-3. Centrifuge, collect the supernatant, desalt the peptides, and lyophilize.

[0027] Preferably, the volume of urea buffer is based on adding 1 mg of protein to 200 μL of buffer for reconstitution; preferably, the concentration during protein digestion should be less than 1 mg / mL, and the final concentration of urea should be less than 2 M.

[0028] Further, in step S3, the enrichment of tyrosine-phosphorylated proteins includes enrichment of tyrosine-phosphorylated peptides (Superbinder protein) and Ti-IMAC enrichment. Preferably, Superbinder protein enrichment is performed first, followed by Ti-IMAC enrichment. In a specific embodiment, step S3 includes:

[0029] (1) Superbinder protein was bound to His agarose beads. The beads were washed with ice-cold IAP buffer, and the peptide was reconstituted with ice-cold IAP buffer and added to the His beads. The peptide was then rotated overnight on a 4-degree spin mixer. The beads were washed with ice-cold IAP buffer, followed by elution three times with PBS buffer containing 500 mM imidazole and once with 10% TFA. The four elution solutions were combined, and the pH was adjusted to 2-3 for desalting. The superbinder flow-through was retained after the above steps. Preferably, the amount of superbinder protein used was 60 μg of superbinder for every 1 mg of peptide.

[0030] (2) Ti-IMAC enrichment of tyrosine phosphorylated peptides. The tyrosine phosphorylated samples enriched in (3) were further enriched with Ti-IMAC. A C8 membrane was packed into a 200 μL pipette tip, Ti-IMAC beads were added, and the mixture was centrifuged at 2000g for 1 minute. Equilibration was performed using 80% acetonitrile and 6% TFA, followed by centrifugation at 400g for 2 minutes. The enriched sample from (3) was then added, and the mixture was centrifuged at 100-200g for 10 minutes. This process was repeated once to ensure the tyrosine phosphorylated peptides were fully bound to the Ti-IMAC beads. The mixture was washed once with 50% ACN, 6% TFA, and 200 mM NaCl solution, and twice with 30% ACN and 0.1% TFA. Elution was performed with 200 μL of 10% ammonia solution, with centrifugation at 100-200g for 10-20 minutes. Final elution was performed using 50% ACN, centrifuged at 800g for 3 minutes, and the eluates from both elutions were combined. The sample was then lyophilized. Preferably, 4 mg of Ti-IMAC beads were used per 200 μg of peptide; for amounts less than 200 μg, 4 mg of Ti-IMAC beads were used.

[0031] Furthermore, in step S4, the data of the tyrosine phosphorylated proteome obtained in step S3 is acquired by mass spectrometry analysis.

[0032] Using the method of this invention, tyrosine phosphorylated proteome is creatively used as the core for predicting CAR-T cell quality control and efficacy, providing a more accurate and sensitive method for predicting CAR-T cell quality control and efficacy.

[0033] In a second aspect, the present invention provides a panel for predicting the efficacy of CAR-T cell therapy of tyrosine-phosphorylated proteins, comprising:

[0034] ACTB_Y198, EEF1A1P5_Y141, PTPN11_Y62, TXK_Y75, CD3D_Y76.

[0035] The above panel analysis can more accurately predict the efficacy of CAR-T cell therapy. When all protein sites in the panel show changes in tyrosine phosphorylation levels (log2_intensity>10), relapse will inevitably occur after treatment with this CAR-T product.

[0036] Thirdly, the present invention provides the use of the above-described panel in preparing a kit for predicting the efficacy of CAR-T cell therapy.

[0037] Fourthly, the present invention provides a therapeutic device for predicting CAR-T cell quality control and efficacy, comprising:

[0038] S1, Protein Acquisition Module, used to acquire proteins from samples, including CAR-T cells and monocytes;

[0039] S2, Protein hydrolysis module, used for enzymatic hydrolysis of the protein obtained in step S1;

[0040] S3, Tyrosine phosphorylated protein enrichment module, is used to enrich the protein after enzymatic hydrolysis in step S2 with tyrosine phosphorylated proteins to obtain a tyrosine phosphorylated protein group.

[0041] S4. Data acquisition module, used to acquire data of the tyrosine phosphorylated proteome obtained in step S3, and analyze the data using principal component analysis (PCA).

[0042] S5, Quality Control Analysis Module, is used to compare PCA analysis data of tyrosine phosphorylated proteomes of CAR-T cells and monocytes. If the results are positive, it indicates that CAR-T cell construction was successful.

[0043] S6, Tyrosine phosphorylation site identification module, used to identify tyrosine phosphorylation sites, wherein the tyrosine phosphorylation sites are sites where tyrosine phosphorylation occurs in both CAR-T cells and monocytes;

[0044] S7, Efficacy Prediction Module, used to predict the efficacy of CAR-T cells, wherein the Z-value of step S6 and the standard is calculated according to the following formula:

[0045]

[0046] Then, the Z values ​​calculated in step S6 and the standard are compared by a t-test. If the median Z value in step S6 is greater than the median Z value in the standard and its p value is less than 0.05, it indicates that the therapeutic effect is not good.

[0047] Fifthly, the present invention provides an apparatus comprising:

[0048] At least one processor; and

[0049] A memory communicatively connected to at least one of the processors; wherein,

[0050] The memory stores instructions executable by the processor to implement the following methods for predicting CAR-T cell quality control and efficacy:

[0051] S1. Obtain the protein from the samples, which are CAR-T cells and monocytes, respectively;

[0052] S2. Perform enzymatic hydrolysis on the protein obtained in step S1;

[0053] S3. The protein obtained after enzymatic hydrolysis in step S2 is enriched with tyrosine-phosphorylated proteins to obtain a tyrosine-phosphorylated protein group.

[0054] S4. Collect the data of the tyrosine phosphorylated proteome obtained in step S3, and analyze the data using principal component analysis (PCA).

[0055] S5. Compare the PCA analysis data of the tyrosine phosphorylated proteome of CAR-T cells and monocytes. If the results are positive, it indicates that CAR-T cell construction was successful.

[0056] S6. Identify tyrosine phosphorylation sites, wherein the tyrosine phosphorylation sites are sites where tyrosine phosphorylation occurs in both the CAR-T cells and monocytes;

[0057] S7. Predict the efficacy of CAR-T cell therapy, wherein the Z-scores of step S6 and the standard are calculated according to the following formula to form a Z-score set:

[0058]

[0059] Then, a t-test is performed to compare the Z-value sets calculated in step S6 and the standard. If the Z-value of step S6 is greater than the Z-value of the standard and its p-value is less than 0.05, it indicates that the therapeutic effect is not good.

[0060] In some embodiments, the device further includes at least one input device and at least one output device; in the device, the processor, memory, input device, and output device are connected via a bus.

[0061] In a sixth aspect, a storage medium is provided that stores computer instructions for execution by the computer to implement the methods described above for predicting CAR-T cell quality control and efficacy.

[0062] In some implementations, the storage medium is a computer-readable storage medium. Attached Figure Description

[0063] Figure 1 This is an exemplary schematic diagram of the method of the present invention;

[0064] Figure 2 This is a graph showing the results of PCA analysis on healthy human samples according to the present invention;

[0065] Figure 3 This is a graph showing the results of PCA analysis of 5 clinical patients in this invention;

[0066] Figure 4 This is a diagram illustrating the results of using the method of the present invention to predict CAR-T cell therapy.

[0067] Figures 5-9 This is a graph showing the results of using the panel of this invention to predict therapeutic efficacy. Detailed Implementation

[0068] The present invention will be described in detail below with reference to specific implementation schemes and embodiments, thereby making the advantages and various effects of the present invention more clearly apparent. Those skilled in the art should understand that these specific implementation schemes and embodiments are for illustrative purposes only and are not intended to limit the present invention.

[0069] Example 1: Instruments, reagents, and materials used in this invention

[0070] QE-HFX mass spectrometer (Thermo Fisher Scientific, USA)

[0071] C18 membrane was purchased from MEmpore, USA; BCAProtein Assay Kit was purchased from Thermo Fisher Scientific; ammonia (28%), formic acid (FA, HPLC grade), methanol (MeOH, HPLC grade), acetonitrile (ACN, HPLC grade), and urea were all purchased from Sigma-Aldrich, USA; protease inhibitors and phosphatase inhibitors were purchased from Roche, USA; and ultrapure water (18 MΩcm) was prepared using a MilliQ system (Millipore).

[0072] Cell lysis buffer formulation (5 mL as an example):

[0073] Weigh 2.4228g Tris + 30mL H2O, adjust the pH to 8.5 with concentrated hydrochloric acid, and then bring the volume to 40mL to prepare a 500mM Tris-HCl stock solution; use a Pasteur pipette to measure 1mL Triton X-100 into a clean 15mL centrifuge tube, add 9mL H2O and mix well to prepare a 10% Triton X-100 stock solution; weigh 4.199mg NaF, use a pipette to measure 500μL H2O to prepare a 200mM NaF stock solution; weigh 20mg NV, use a pipette to measure 500μL H2O to prepare a 100mM NV stock solution. Take a clean 15mL centrifuge tube, add 500μL of 500mM Tris-HCl, weigh 2.4g of urea, pipette 500μL of 10% Triton X-100, measure 250μL of 200mM NaF and 50μL of Na3VO4, and add protease inhibitor and phosphatase inhibitor (according to the instructions). Add H2O to a final volume of 5mL, mix well, and this is your cell lysis buffer. The reagent volume can be adjusted proportionally according to experimental requirements.

[0074] IAP buffer preparation method: The IAP buffer consists of 50 mM MOPS, pH 7.2, 10 mM Na2HPO4, and 50 mM NaCl. Weigh 4.18 g of MOPS (propanesulfonic acid) into a clean 50 mL centrifuge tube, dissolve it in 30 mL of H2O, adjust the pH to 7.2 with NaOH, and bring the volume to 40 mL to prepare a 0.5 M MOPS buffer stock solution. Take a clean 50 mL centrifuge tube, pipette 4 mL of 0.5 M MOPS stock solution, 0.0568 g of NHP, and 0.11688 g of NaCl into the centrifuge tube, dissolve them in H2O, and bring the volume to 40 mL. The volume can be adjusted by adding the appropriate reagents in proportion according to the experimental requirements.

[0075] Example 2: The method of the present invention for predicting CAR-T cell quality control and efficacy.

[0076] The exemplary method of the present invention is as follows: Figure 1 As shown. The samples used were PBMCs and CAR-T cells constructed based on those PBMCs.

[0077] Step S1, Protein Extraction. Wash cells twice with ice-cold PBS, add 500 μL of ice-cold cell lysis buffer, vortex, and lyse on ice for 30 minutes. Then, sonicate on ice for 2 minutes using an ultrasonic sonicator with the sonication settings set to 5 seconds on, 5 seconds off. After sonication, centrifuge the cell lysis buffer at 4°C, 150,000g, for 10 minutes. Transfer the supernatant to a new 15mL centrifuge tube and analyze protein concentration using BCA. Add 4 volumes of ice-cold methanol, vortex, add 1 volume of chloroform, vortex, then add 3 volumes of ice-cold H2O, vortex. Centrifuge at 11,000g, 4°C for 3 minutes, discard the liquid, add 4 volumes of methanol, gently tap the protein precipitate with your finger to wash, centrifuge at 11,000g, 4°C for 3 minutes to remove as much methanol as possible, and air dry at room temperature for 5-10 minutes.

[0078] Step S2: Protein reduction, alkylation, and enzymatic digestion. Dissolve the protein precipitate from S1 in urea buffer. After complete dissolution, add DTT to a final concentration of 10 mM and react the solution at 55°C for 25 minutes using a metal mixer. Add IAA to a final concentration of 30 mM and react at room temperature in the dark for 30 minutes using a metal mixer. Add DTT to a final concentration of 20 mM and continue reacting in the dark for 15 minutes. Add 7 volumes of 50 mM Tris-HCl (pH 8.5), add CaCl2 to a final concentration of 1 mM, and add Trypsin at a 1:100 ratio. Incubate overnight at 37°C using a rotary mixer. Acidify the digested peptides with 10% TFA to a pH of 2-3. Centrifuge, collect the supernatant, desalt the peptides, and lyophilize.

[0079] Step S3: Superbinder protein enrichment of tyrosine phosphorylated peptides. The Superbinder protein used for enriching tyrosine phosphorylated peptides was bound to His agarose beads. The beads were washed with ice-cold IAP buffer, the peptides were reconstituted with ice-cold IAP buffer, and added to His beads and rotated overnight. The beads were washed with ice-cold IAP buffer, then eluted three times with PBS buffer containing 500 mM imidazole, and once with 10% TFA. The four elution solutions were combined, the pH was adjusted to 2-3, and desalted. The flow-through of the superbinder was retained after the above steps. Ti-IMAC enrichment of tyrosine phosphorylated peptides. The tyrosine phosphorylated samples enriched in (3) were further enriched with Ti-IMAC. A C8 membrane was placed in a 200 μL pipette tip, Ti-IMAC beads were added, and the membrane was centrifuged at 2000g for 1 minute. Equilibrate with 80% acetonitrile and 6% TFA, centrifuge at 400g for 2 minutes, add the enriched sample from step (3), and centrifuge at 100-200g for 10 minutes. Repeat once to ensure the tyrosine phosphorylated peptides are fully bound to the Ti-IMAC beads. Wash once with 50% ACN, 6% TFA, and 200mM NaCl solution, wash twice with 30% ACN and 0.1% TFA, elute with 200 μL of 10% ammonia solution at 100-200g for 10-20 minutes. Finally, elute with 50% ACN at 800g for 3 minutes, and combine the two eluents. The sample was then lyophilized.

[0080] Step S4: All samples were analyzed using an Easy-nLC 1200 system and a Q-Exactive HF-X system. The liquid chromatography separation system consisted of a C4 (3μm / 0.5-0.8cm, Dr.Maisch GmbH) and C18 (1.9μm / The analytical column consisted of a 19-20 cm (Dr. Maisch GmbH) resin-filled capillary column with a spray nozzle. Separation was achieved using a dual-phase system consisting of phase A, an aqueous solution of 0.1% FA, and phase B, an acetonitrile solution containing 0.1% FA. The flow rate was set to 250 nL / min. The gradient was set to an 80-minute gradient, specifically: 4-8% (v / v) phase B for 2 min, 8-28% (v / v) phase B for 55 min, 28-40% (v / v) phase B for 5 min, 40-97% (v / v) phase B for 2 min, and 90% (v / v) phase B for 16 min. The full mass spectrometry scan range was m / z 350–1550, and the mass spectrometry resolution was 120,000. MS / MS data were acquired using data-dependent acquisition mode (DDA) via high-energy collision fragmentation, with a planned collision energy (NCE) of 25%, a separation window of 1.4 Da, a maximum ion implantation time of 50 ms, and a dynamic exclusion time of 30 s. Raw mass spectrometry data were obtained by searching the human uniprot fasta database (downloaded on March 37, 2018) using MaxQuant (version 1.614). Search parameters were: Oxidation (M), Deamidation (N), and Phospho (STY) were set to variable modifications; Carbamidomethyl (C) was set to a fixed modification; the error rate (FDR) for peptide identification was set to 0.01; the LFQ parameter was set to TRUE; and the Isobaric weightexponent was set to 0.75. The searched files were then further filtered, analyzed, and plotted using Perseus (Version 2.0.6) and R software (Version 4.2.2). The main steps and tools used are as follows:

[0081] Step S5: Import the MaxQuant search results into Perseus software. Perform database inversion and decontamination on the data, and set the localization probability to x>0.75. Group the PBMCs of primary cells from healthy individuals and the three replicates of CAR-T cells into one group each. Group the PBMCs of four patients into one group and the CAR-T cells into another. Each group should have at least three valid data points. Add annotations for the KEGG and GO cellular pathways. Perform a Student's-test on the two groups of data, and generate principal component analysis (PCA) plots and volcano plots. Alternatively, export the data to R language for plotting. For intensity comparisons of specific sites, plot the selected sites and their intensities using GraphPad Prism software.

[0082] Step S6: Screen the tyrosine phosphorylation sites of CAR-T cells and monocytes to identify sites that show tyrosine phosphorylation in both.

[0083] Step S7: Calculate the Z-value of the tyrosine phosphorylation sites obtained in Step S6 and the standard according to the following formula:

[0084]

[0085] The obtained Z values ​​are then compared using a t-test. If the median Z value in step S6 is greater than the median Z value of the standard and its p value is less than 0.05, it indicates that the therapeutic effect is poor.

[0086] Example 3: The method of the present invention is used to predict the quality control of CAR-T cells in clinical patients.

[0087] Information on the 5 clinical patients (numbered 1-5) who need to be predicted is shown in Table 1 below.

[0088] Table 1

[0089] Patient number gender age lesion type 1 female 59 Acute lymphoblastic leukemia 2 male 20 Chronic myeloid leukemia 3 female 33 B-cell lymphoma 4 female 24 B-cell lymphoma 5 female 71 Acute lymphoblastic leukemia

[0090] To assess the differences between CAR-T cells and PBMCs, predictions were made according to the method described in Example 2. A systematic analysis of the tyrosine phosphorylated proteome was performed, and principal component analysis (PCA) was used to reduce the dimensionality of the data. The PCA analysis results showed significant differences in the distribution of the tyrosine phosphorylated proteome between CAR-T cells and PBMCs. Specifically, the PCA plot showed that CAR-T cell samples were clearly clustered on one side of the plot, while PBMC samples were clustered on the other side, with a significant distance between them and no overlap.

[0091] This invention first collected PBMC samples and their corresponding CAR-T cell products from healthy individuals, and then performed PCA analysis on the tyrosine phosphorylation proteomics data of these samples. The results are as follows: Figure 2 As shown in the analysis, the CAR-T cell samples clearly clustered on the left side of the PCA plot, while the corresponding PBMC samples clustered on the right side. The distance between the two was significant, and there was no overlap between the samples. Furthermore, the contribution values ​​of the PCA plots showed that PC1 contributed 26.76%, and PC2 contributed 21.73%, for a combined contribution of 48.49%. This high contribution value indicates that the first two principal components effectively captured the major variability of the tyrosine phosphorylated proteome, thus demonstrating a significant difference between CAR-T cells and PBMCs in terms of tyrosine phosphorylated proteome characteristics. This indicates that the CAR-T cell construction was successful.

[0092] This invention collected PBMC samples and their corresponding CAR-T cell products from clinical patients 1-5 mentioned above, and performed PCA analysis on the tyrosine phosphorylation proteomics data of these samples. The results are as follows... Figure 3 As shown in the figure, the analysis results show that the CAR-T cell samples from clinical patients are clearly clustered on the left side of the PCA diagram, while the corresponding PBMC samples are clustered on the right side. The distance between the two is significant and there is no overlap between the samples. Therefore, it is indicated that the CAR-T cells of patients 1 to 5 above were successfully constructed.

[0093] Furthermore, the contribution values ​​of PCA were PC1: 55.98% and PC2: 18.93%, with a combined contribution value of 74.91%. This high contribution value indicates that the first two principal components effectively captured the major variability of the tyrosine phosphorylated proteome, thus demonstrating a significant difference between CAR-T cells and PBMCs in terms of tyrosine phosphorylated proteome characteristics. The 55.98% contribution value of PC1 further validates the significant difference between CAR-T cells and PBMCs and indicates that this difference is consistent across CAR-T products used in different clinical patients.

[0094] Example 4: The method of the present invention is used to predict the efficacy of CAR-T cell therapy in clinical patients.

[0095] This invention first selects CAR-T and corresponding PBMC samples from patients 1 to 5, and screens for sites where the identification level of all tyrosine phosphorylation sites is greater than 0. For each screened tyrosine phosphorylation site, the ratio of its tyrosine phosphorylation level in the CAR-T and PBMC samples is calculated, and the absolute value of the log2 of this ratio is obtained. Subsequently, this value is used as the change value for each site, and the change values ​​of all screened sites constitute the observed value Z of the patient's tyrosine phosphorylated proteome (i.e., if n sites are screened, then the patient's tyrosine phosphorylated proteome has n observed values ​​Z).

[0096] Specifically, for example, the observed sites of the tyrosine phosphorylation proteome in patient number 3 (n=31) are: EMG1_Y16, GSK3A_Y197, CD247_Y123, CD247_Y142, CD247_Y111, HCLS1_Y103, CD3E_Y193, PIK3CD_Y548, IQGAP1_Y938, HIPK2_Y354, TSEN2_Y7, LYN_Y473, PGAM1_Y92, PIK3R1_Y452. PIK3R1_Y467, PTPN6_Y564, FCER1G_Y76, FCER1G_Y65, HNRNPH3_Y296, DYRK1A_Y321, SLAMF6_Y309, SLAMF6_Y285 , HIPK3_Y359, PAG1_Y227, CD84_Y296, CD46_Y63, CDK1_Y15, MAPK14_Y105, CDK2_Y15, PDHA1_Y20, SLAMF1_Y281.

[0097] The calculated set of Z values ​​is: Z = {1.46, 1.20, 6.14, 5.00, 2.77, 3.42, 5.63, 1.09, 3.68, 5.71, 0.07, 2.54, 3.57, 2.49, 0.10, 0.52, 4.78, 3.19, 2.03, 4.65, 4.78, 0.79, 3.90, 3.33, 2.76, 0.16, 1.18, 3.39, 1.18, 1.49, 2.17}.

[0098] Meanwhile, the median Z-value of the standard was 1.744 (n=91), which was calculated by combining data from two patients without recurrence. Therefore, the median value of the observations in the standard dataset was 1.744 (n=91).

[0099] Furthermore, the observational data of all patients were imported into Prism GraphPad software to calculate the median of the observed values ​​of the tyrosine phosphorylated protein group for each patient. Using the standard dataset as a control, t-tests were performed on the tyrosine phosphorylated protein group of each patient from P1 to P5. The judgment criteria were: (1) if the median was significantly higher than the standard central mean, and (2) if the p-value was less than 0.05, then the CAR-T sample of that patient was deemed to have failed quality control, and it was speculated that the patient had a high probability of relapse after reinfusion therapy.

[0100] Specifically, the median values ​​of the tyrosine phosphorylated protein group observed in patients P1-P5 were calculated to be 1.722 (n=65), 1.729 (n=68), 3.194 (n=31), 3.087 (n=29), and 4.034 (n=22), respectively. Among them, the variation values ​​of the tyrosine phosphorylated protein group in relapsed patients P3-P5 were greater than 3, significantly higher than the standard median value of 1.744.

[0101] Furthermore, the t-test p-values ​​between patients P1-5 and the standard control were 0.8754, 0.5684, 0.0056, 0.0445, and <0.0001, respectively. Figure 4 As shown, P1 or P2 showed no significant difference compared to the standard set (p>0.05); while the p values ​​for patients 3 to 5 all met the criteria of p<0.05, thus predicting a higher likelihood of relapse after CAR-T infusion.

[0102] The final clinical outcomes are shown in Table 2 below. It is evident that the outcomes predicted by the method of this invention are highly consistent with the actual clinical treatment results, demonstrating the accuracy of the method.

[0103] Table 2

[0104] Patient number Clinical status 1 No recurrence 2 No recurrence 3 relapse 4 relapse 5 relapse

[0105] Example 4: The panel of the present invention is used to predict the quality control and efficacy of CAR-T cells in clinical patients.

[0106] Using the method of this invention, the applicant identified a series of sites for use as a predictive panel. The applicant found that when all sites in this panel showed significant differences in tyrosine phosphorylation levels in CAR-T cells and monocytes (log2 intensity change > 10), treatment with this CAR-T product inevitably resulted in relapse. Therefore, the applicant further used the aforementioned clinical cases for validation, specifically verifying the tyrosine phosphorylation levels of ACTB_Y198, EEF1A1P5_Y141, PTPN11_Y62, TXK_Y75, and CD3D_Y76, with results as follows: Figures 4-8As shown in the figure, patients numbered 1-2 did not show significant differences in tyrosine phosphorylation levels of the panel described in this invention; therefore, it was determined that they would not relapse. However, patients numbered 3-5 showed significant differences in tyrosine phosphorylation levels of the panel described in this invention; therefore, it was determined that they would relapse. The final clinical outcomes are shown in Table 2 above. This demonstrates that the prediction using the panel of this invention is highly consistent with actual clinical treatment outcomes, indicating the accuracy of the panel. Specifically, when the tyrosine phosphorylation levels at all sites of the panel described above show the aforementioned significant differences in CAR-T cells and monocytes, treatment with this CAR-T product will inevitably result in relapse.

Claims

1. The use of a panel of tyrosine-phosphorylated proteins for the preparation of a kit for CAR-T cell quality control and efficacy prediction, comprising the following steps: S1. Obtain the proteins from the samples respectively, where, The samples were CAR-T cells and peripheral blood mononuclear cells, respectively. S2. Perform enzymatic hydrolysis on the protein obtained in step S1; S3. The protein obtained after enzymatic hydrolysis in step S2 is enriched with tyrosine-phosphorylated proteins to obtain a tyrosine-phosphorylated protein group. S4. Collect the data of the tyrosine phosphorylated proteome obtained in step S3, and analyze the data using principal component analysis. S5. Compare the PCA analysis data of the tyrosine phosphorylated proteome of CAR-T cells and monocytes. If the clustering regions of CAR-T cells and monocytes are different, it indicates that CAR-T cells have been successfully constructed. The panel includes: ACTB_Y198, EEF1A1P5_Y141, PTPN11_Y62, TXK_Y75 and CD3D_Y76.

2. The use according to claim 1, characterized in that, The application also includes the following steps: S6. Identify tyrosine phosphorylation sites, wherein the tyrosine phosphorylation sites are sites where tyrosine phosphorylation occurs in both the CAR-T cells and monocytes; S7. Predict the efficacy of CAR-T cell therapy, wherein the Z-value of step S6 and the standard is calculated according to the following formula: Then, the Z-values ​​of step S6 and the standard are compared by a t-test. If the median Z-value of step S6 is greater than the median Z-value of the standard and its p-value is less than 0.05, it indicates that the therapeutic effect is not good.

3. The use according to claim 2, characterized in that, In step S6, the number of tyrosine phosphorylation sites is ≥10.

4. The use according to any one of claims 1 to 3, characterized in that, The samples were taken from individuals with a certain lesion.

5. The use according to claim 4, characterized in that, The lesion is a tumor.

6. The use according to claim 5, characterized in that, The lesion is either leukemia or lymphoma.

7. The use according to any one of claims 4 to 6, characterized in that, The enzymatic hydrolysis in step S2 includes protein reduction, alkylation, and enzymatic hydrolysis.

8. The use according to claim 2, characterized in that, In step S7, the standard is an individual whose lesion has not relapsed after receiving CAR-T cell therapy.

9. The use according to claim 8, characterized in that, The standard is the average of two individuals whose lesions did not relapse after receiving CAR-T cell therapy.

10. A panel for predicting the efficacy of CAR-T cell therapy, comprising the following biomarkers: ACTB_Y198, EEF1A1P5_Y141, PTPN11_Y62, TXK_Y75, and CD3D_Y76.

11. Use of the panel as described in claim 10 for preparing a kit for predicting the efficacy of CAR-T cell therapy.

12. A panel of tyrosine-phosphorylated proteins for predicting CAR-T cell quality control and efficacy, comprising: S1, Protein Acquisition Module, used to acquire proteins from samples, including CAR-T cells and monocytes; S2, Protein hydrolysis module, used for enzymatic hydrolysis of the protein obtained in step S1; S3, Tyrosine phosphorylated protein enrichment module, is used to enrich the protein after enzymatic hydrolysis in step S2 with tyrosine phosphorylated proteins to obtain a tyrosine phosphorylated protein group. S4. Data acquisition module, used to acquire data of the tyrosine phosphorylated proteome obtained in step S3, and analyze the data using principal component analysis (PCA). S5, Quality Control Analysis Module, is used to compare PCA analysis data of tyrosine phosphorylated proteomes of CAR-T cells and monocytes. If the clustering regions of CAR-T cell and monocyte samples are different, it indicates that CAR-T cell construction was successful. The panel consists of the following markers: ACTB_Y198, EEF1A1P5_Y141, PTPN11_Y62, TXK_Y75, and CD3D_Y76.

13. The apparatus according to claim 12, characterized in that, Further includes: S6, Tyrosine phosphorylation site identification module, used to identify tyrosine phosphorylation sites, wherein the tyrosine phosphorylation sites are sites where tyrosine phosphorylation occurs in both CAR-T cells and monocytes; S7, Efficacy Prediction Module, used to predict the efficacy of CAR-T cells, wherein the Z-value of step S6 and the standard is calculated according to the following formula: Then, the Z values ​​calculated in step S6 and the standard are compared by a t-test. If the median Z value in step S6 is greater than the median Z value in the standard and its p value is less than 0.05, it indicates that the therapeutic effect is not good.

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