Lymphocyte subpopulation and cytokine combined detection method based on flow cytometry, kit and application

Abstract

The application relates to a lymphocyte subpopulation and cytokine combined detection method, kit and application based on flow cytometry. The method constructs a parallel detection system of cell phenotypes and cytokines on the same flow platform, solves the signal interference problem by using spectrum compatible markers, and realizes synchronous analysis of immune cell subpopulations, immune checkpoints and multiple cytokines in trace blood samples. The scheme avoids system errors and sample waste caused by multi-platform detection, can provide a comprehensive atlas reflecting the synergistic state of cell immune structure and humoral immune function, and improves the accuracy and efficiency of clinical immune evaluation.

Description

Technical Field

[0001] This application relates to the field of flow cytometry detection technology, and in particular to a method, kit, and application for the combined detection of lymphocyte subsets and cytokines based on flow cytometry. Background Technology

[0002] The human immune system plays a crucial role in defending against external attacks such as viral and bacterial infections, monitoring abnormal cells such as tumor cells, and maintaining homeostasis. The functional state of the immune system is usually reflected in two dimensions: one is immune structure, which refers to the proportion and phenotypic characteristics of various immune cell subsets; the other is immune function, which refers to the level of soluble effector molecules secreted by immune cells after stimulation.

[0003] Currently, the mainstream clinical flow cytometry is mainly used for counting lymphocyte subsets. However, a normal cell count alone does not necessarily mean normal function. For example, in the tumor microenvironment, T cells may be abundant but highly express checkpoints such as PD-1, indicating a state of functional exhaustion.

[0004] On the other hand, the detection of cytokines usually relies on ELISA or liquid microarray technology and is performed as a separate experimental item on a microplate reader or a dedicated analyzer. This detection mode not only cannot be synchronized with cell phenotype data in time, but also makes it difficult to achieve functional correlation at the single-cell level.

[0005] In current practice, cell phenotype and cytokine detection are separate processes. This not only requires patients to have multiple blood draws and consumes a large amount of samples, but also results in systematic errors between the two sets of data because cell detection and factor detection are often performed on different instrument platforms, at different time windows, or even in different laboratories, making it difficult to perform accurate parallel comparisons. Summary of the Invention

[0006] To address the aforementioned issues, this application provides a flow cytometry-based method, kit, and application for the combined detection of lymphocyte subsets and cytokines, which can effectively reduce sample consumption and errors.

[0007] To achieve the above objectives, in a first aspect, this application provides a method for the combined detection of lymphocyte subsets and cytokines based on flow cytometry, comprising the following steps: Step S1: Obtain an isolated blood sample and aliquot it into cell phenotype detection components and cytokine detection components; Step S2: Use a pre-set flow cytometry antibody composition to specifically label the immune cell surface antigens in the cell phenotype detection section, and then add erythrocyte lysis buffer to perform erythrocyte lysis treatment after incubation; Step S3: The cytokine detection components are separated into plasma or serum, the target cytokines are captured using a fluorescently encoded microsphere array, and a double-antibody sandwich immune complex is formed using the detection antibody; Step S4: Using the same flow cytometer, under the uniform voltage gain setting and fluorescence compensation matrix after calibration of microspheres, collect the scatter plot data of the labeled cells in step S2 and the fluorescence intensity data of the double antibody sandwich immune complex formed in step S3, respectively. Step S5: Obtain the proportion data of immune cell subsets and cytokine concentration data of the blood sample, which are used to construct the immune status atlas of the subject.

[0008] Preferably, the flow cytometry antibody composition in step S2 comprises: Module 1: Includes specific antibodies against CD45, CD3, CD4, CD8, CD19, CD16, and CD56 for detecting lymphocyte subsets; Module 2: Includes specific antibodies against CD4, CD25, and CD127 for detecting regulatory T cells; Module 3 includes specific antibodies targeting at least one of PD-1, CTLA-4, Tim-3, LAG-3, CD154, and CD107a, used to detect immune checkpoint expression levels or T cell activation levels.

[0009] Preferably, the fluorescently encoded microsphere array in step S3 comprises microsphere populations conjugated with capture antibodies targeting the following 14 cytokines: IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17a, IL-17F, IL-22, TNF-α, IFN-γ, and TNF-β; wherein the microsphere populations are distinguished by different particle sizes and fluorescence encoding intensities.

[0010] Preferably, step S2 further includes the detection of circulating tumor cells: After erythrocyte lysis, epithelial-derived cells are identified using a combination of antibodies targeting CD45, CD326, CD44, and CD54. The cell population that is CD45 negative and CD326 positive is identified as circulating tumor cells, and the expression of CD44 and CD54 is used to perform auxiliary identification or adhesion molecule characterization analysis on the circulating tumor cells.

[0011] Preferably, in step S4, the cell phenotype detection and cytokine detection use a spectrally compatible fluorescent labeling system; the method further includes: using calibrators to calibrate the photomultiplier tube voltage and fluorescence compensation matrix of the flow cytometer to correct signal crosstalk of microsphere fluorescence to the cell detection channel, and setting a scattered light threshold to eliminate interference from cell debris to the microsphere detection area, thereby achieving synchronous acquisition of the data.

[0012] Preferably, step S5 further includes: correlation analysis of the expression level data obtained by module three with the concentration data of the cytokines to provide assessment data reflecting the state of T lymphocyte depletion or the risk of cytokine storm.

[0013] Secondly, this application provides a flow cytometry assay kit for assessing immune status, the kit comprising: The first reagent component comprises a combination of fluorescently labeled antibodies for labeling lymphocyte subsets, regulatory T cells, and immune checkpoint proteins, wherein the immune checkpoint proteins include at least one of PD-1, CTLA-4, Tim-3, LAG-3, CD154, and CD107a. The second reagent component includes a fluorescently encoded microsphere suspension conjugated with antibodies targeting multiple cytokines, and a corresponding mixture of biotinylated or fluorescently labeled detection antibodies.

[0014] Preferably, the antibody in the first reagent component and the fluorescent label used for the microspheres in the second reagent component have fluorescence emission spectra that are independent of each other or can be distinguished by fluorescence compensation, and the kit also contains calibration microspheres or cytokine standards suitable for flow cytometry.

[0015] Thirdly, this application provides the use of the kit as described in the second aspect in the preparation of a detection reagent for assessing the immune system function of a subject.

[0016] This application presents a flow cytometry-based method, kit, and application for the joint detection of lymphocyte subsets and cytokines. By constructing a parallel detection system for cell phenotypes and cytokines on the same flow cytometry platform and utilizing spectrally compatible markers to resolve signal interference issues, it achieves simultaneous analysis of immune cell subsets, immune checkpoints, and multiple cytokines in trace blood samples. This approach avoids systematic errors and sample waste caused by multi-platform detection and provides a comprehensive atlas reflecting the synergistic state of cellular immune structure and humoral immune function, thus improving the accuracy and efficiency of clinical immune assessment. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of the method for combined detection of lymphocyte subsets and cytokines based on flow cytometry as described in the embodiments of this application.

[0018] Figure 2 This is a flow cytometry scatter plot for detecting peripheral blood lymphocyte subsets using module one described in the embodiments of this application.

[0019] Figure 3 To detect flow cytometry scatter plots of regulatory T cells using module two described in the embodiments of this application.

[0020] Figure 4 This is a flow scatter plot used to detect the expression levels of immune checkpoints CTLA-4 and Tim-3 in different T cell subsets using Module 3 as described in the embodiments of this application.

[0021] Figure 5 This is a flow scatter plot used to detect the expression levels of immune checkpoints LAG-3 and PD-1 in different T cell subsets using Module 3 as described in the embodiments of this application.

[0022] Figure 6 Flow cytometry data for identifying circulating tumor cell-related phenotypes using the CTCs detection module described in this application embodiment.

[0023] Figure 7 This document describes a flow cytometry gating strategy and analysis diagram for the simultaneous detection of 14 cytokines using the dual-encoded microsphere array described in the embodiments of this application. Detailed Implementation

[0024] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application.

[0025] Example 1.

[0026] This embodiment provides a flow cytometry assay kit for assessing immune status, which is designed to achieve combined detection of cell phenotype and cytokines using the same flow cytometer.

[0027] Specifically, the kit includes a first reagent component and a second reagent component that are independent of each other.

[0028] In this embodiment, the first reagent component is used for cell detection and contains a combination of fluorescently labeled antibodies for labeling lymphocyte subsets, regulatory T cells, and immune checkpoint proteins, wherein the immune checkpoint proteins include at least one of PD-1, CTLA-4, Tim-3, LAG-3, CD154, and CD107a.

[0029] To meet the needs of different clinical scenarios, the first reagent component is designed to include the following three optional detection modules. The antibodies in each module are labeled with spectrally compatible fluorescent markers (such as FITC, PE, APC, PerCP-Cy5.5, PE-Cy7, APC-Cy7, etc.): Module 1 (Basic Immunophenotyping): Contains specific antibodies against CD45, CD3, CD4, CD8, CD19, CD16, and CD56. This module is mainly used to detect the proportions of T cells (CD3+), B cells (CD19+), NK cells (CD16+CD56+), and T subsets (CD4+ / CD8+).

[0030] Module 2 (Immune Regulation): Contains specific antibodies against CD4, CD25, and CD127. This module is used to identify regulatory T cells (Tregs), whose typical phenotype is CD4+CD25+CD127low / -.

[0031] Module 3 (Checkpoints and Activation): Contains specific antibodies against PD-1, CTLA-4, Tim-3, LAG-3, CD154, and CD107a. This module is used to assess the exhaustion status (e.g., PD-1+ / Tim-3+) or activation potential of T cells.

[0032] In some embodiments, the CTCs detection module includes an antibody combination targeting CD45, CD326 (EpCAM), CD44, and CD54 for recognizing CD45-negative and CD326-positive epithelial-derived circulating tumor cells.

[0033] In this embodiment, the second reagent component is used for factor detection. This component is based on a fluorescently encoded microsphere array and includes: The capture microsphere suspension comprises microsphere populations conjugated with capture antibodies targeting 14 cytokines: IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17a, IL-17F, IL-22, TNF-α, IFN-γ, and TNF-β. These microsphere populations exhibit different particle sizes (e.g., 4 μm and 5 μm) and varying intrinsic fluorescence encoding intensities, thereby forming a distinguishable microsphere array matrix on the red / near-infrared channel of a flow cytometer.

[0034] The detection antibody mixture contains biotinylated or fluorescently labeled (such as PE-labeled) detection antibodies against the above 14 cytokines, used to form a "microsphere-antigen-antibody" double-antibody sandwich immune complex.

[0035] In some embodiments, the kit also includes calibration microspheres suitable for flow cytometry (for photomultiplier tube voltage calibration), lyophilized cytokine standards (for plotting standard curves), and erythrocyte lysis buffer.

[0036] In this embodiment, the antibody (mainly labeling the cell surface) in the first reagent component and the fluorescent label used by the microspheres (mainly encoding in the red / near-infrared region, PE channel detection report signal) in the second reagent component are screened to have fluorescence emission spectra that are independent of each other or can be distinguished by fluorescence compensation, ensuring that the two do not interfere with each other under the general configuration of the same instrument.

[0037] Example 2.

[0038] like Figure 1 As shown, this embodiment details the entire process of combined detection of immune indicators using the aforementioned kit. This method enables parallel data acquisition within the same detection cycle using the same hardware platform.

[0039] Step S1: Sample preprocessing and dispensing.

[0040] Peripheral venous blood was collected from the subjects (using EDTA or heparin anticoagulation), and the ex vivo blood samples were aliquoted into two parts: Sample A (cell phenotype detection component): Take 50-100 μL of whole blood and place it in flow cytometry tube A.

[0041] Sample B (cytokine detection component): Centrifuge the remaining whole blood at 3000 rpm for 10 minutes, collect the supernatant plasma (or use serum), and place 25-50 μL into flow cytometry tube B.

[0042] Step S2: Cell phenotype immunomarking.

[0043] S21: Add the first reagent component to flow cytometer A. Module one, two, or three, or a combination of CTCs, can be selected according to requirements. For example, add a combination of CD45 / CD3 / CD4 / CD8 / PD-1 / Tim-3 antibodies.

[0044] S22: Incubate at room temperature in the dark for 15-20 minutes to allow the antibody to specifically label the surface antigens of immune cells.

[0045] S23: Add red blood cell lysis buffer and incubate at room temperature for 10 minutes to remove red blood cells.

[0046] S24: After washing, centrifuging and discarding the supernatant, resuspend the cells in PBS to prepare a cell suspension ready for use.

[0047] In this embodiment, if CTCs detection is performed, a combination of CD45-PerCP-Cy5.5, CD326-PE, CD44-FITC and CD54-APC antibodies can be used to stain the hemolyzed sample.

[0048] Step S3: Cytokine capture response.

[0049] S31: Add the fluorescently encoded microsphere array suspension to flow cytometer B and vortex to mix.

[0050] S32: Add the plasma / serum to be tested or the standard, and incubate at room temperature in the dark with shaking for 1-2 hours to allow the microspheres to capture the target cytokines.

[0051] S33: Add biotinylated or fluorescently labeled detection antibody mixture and continue incubation for 30 minutes to form a double-antibody sandwich immune complex (e.g., microspheres-IL-6-anti-IL-6 antibody-PE).

[0052] S34: After washing and centrifugation, the microspheres are resuspended in PBS to prepare a microsphere suspension ready for use in the instrument.

[0053] Step S4: Same-platform streaming data acquisition S41: Establish a unified detection template using the same flow cytometer (equipped with 488nm and 633nm lasers).

[0054] S42: Calibrate the photomultiplier tube (PMT) voltage of the flow cytometer using calibrators to ensure that the voltages of the cell detection channels (e.g., FITC, APC), microsphere coding channels (e.g., APC-Cy7), and reporter channels (PE) are within the linear range. Lock this voltage gain setting and fluorescence compensation matrix, and use them without adjustment for data acquisition of the cell suspension prepared in step S2 and the microsphere suspension prepared in step S3, respectively, to ensure signal comparability. S43: Import a fluorescence compensation matrix to correct signal crosstalk in the cell detection channel caused by the intrinsic fluorescence of the microspheres themselves (usually in the long wavelength channel), and vice versa.

[0055] S44: When collecting cell data, set the FSC (forward scattering) threshold to exclude interference from low FSC cell debris and free microspheres (if any).

[0056] S45: When collecting microsphere data, although the microspheres and cells are physically separated (in different tubes), the same PMT settings are used to select only the microsphere distribution area through FSC / SSC gating logic to eliminate background noise.

[0057] S46: Sequentially load and collect the cell suspension prepared in step S2 to obtain cell scatter plot data, and the microsphere suspension prepared in step S3 to obtain microsphere fluorescence intensity data.

[0058] Step S5: Data analysis and map construction.

[0059] S51: Fine typing of T cell subsets and analysis of regulatory T cells.

[0060] The cell data collected in step S4 were subjected to gating analysis using existing analysis software.

[0061] Basic fractals: See Figure 2 First, lymphocyte populations were gated using CD45 / SSC (P1 gate). Based on this, CD3+ T cells accounted for 75.31%. Further subset analysis showed that helper T cells (CD3+CD4+, Q1-4 region) accounted for 42.22%, and cytotoxic T cells (CD3+CD8+, Q2-4 region) accounted for 48.28%. At the same time, NK cells (CD16+CD56+) accounted for 8.93%, and B cells (CD19+) accounted for 12.11%.

[0062] Treg identification: See below Figure 3 Based on the basic typing and lymphocyte delineation, the CD4+ helper T cell population (R1 phylum, accounting for 30.92%) was first delineated. Then, the cells in the R1 phylum were further analyzed using a two-parameter scatter plot of CD25 (vertical axis) and CD127 (horizontal axis). The regulatory T cell population with high CD25 expression and low CD127 expression (CD25+CD127low / -) was clearly identified, namely the population shown in the P2 phylum in the figure, which accounts for 6.32% of the CD4+ T cells.

[0063] S52: Assessment of T cell activation potential and function.

[0064] Module 3 was used to perform multidimensional screening of T cell activation markers and immune checkpoints.

[0065] Activation potential analysis: Using the specific antibody in the first reagent component, the expression of the T cell surface co-stimulatory molecule CD154 (CD40L) and the degranulation marker CD107a is detected. Under specific antigen stimulation or strong immune response, T cells will transiently upregulate CD154 or expose CD107a to the cell surface through degranulation. This kit assesses the immune response initiation ability and cytotoxic killing potential of the subject's T cells by detecting the positive rate of the above markers.

[0066] CTLA-4 and Tim-3 testing: See Figure 4In total CD3+ T cells, the proportion of CTLA-4 positive group (R1 group) was 0.15%; the proportion of Tim-3 positive group (R4 group) was 0.05%; further typing showed that CTLA-4 was mainly expressed in the CD4+ subset (R2 group, 0.12%), while Tim-3 was also detected in the CD8+ subset (R6 group, 0.04%).

[0067] LAG-3 and PD-1 detection: See [link / reference] Figure 5 The proportion of LAG-3 positive population (R1 group) in CD3+ T cells was 0.12%; the proportion of PD-1 positive population (R4 group) was 0.07%; among them, the positive rate of LAG-3 in CD8+ subset (R3 group, 0.09%) was significantly higher than that in CD4+ subset (R2 group, 0.02%).

[0068] Based on the above checkpoint data, if a patient shows widespread high expression of inhibitory receptors such as PD-1 / TIM-3 / LAG-3 (significantly higher than baseline) and accompanied by a decrease in the secretion of effector factors, it can be determined that T cells are in a state of deep exhaustion.

[0069] S53: Multidimensional identification of circulating tumor cells (CTCs).

[0070] A comprehensive interpretation of the data from the CTCs detection module is performed, such as... Figure 6 As shown: Leukocyte exclusion: First, circle the CD45-positive leukocyte population (P2 group, accounting for 14.44%) in the SSC / CD45 scatter plot. CTCs are theoretically located in the CD45-negative region.

[0071] Epithelial marker identification: A distinct CD326 (EpCAM) positive signal peak (M1 gate) was detected in the histogram, with this cell population accounting for 0.82%, indicating the presence of epithelial-derived cells in the sample.

[0072] Adhesion molecule-assisted recognition: Further analysis revealed a specific cell population (P1 phylum) with double positive expression of CD44 and CD54 in the sample, accounting for 1.27%. High expression of CD44 and CD54 suggests that these circulating tumor cells possess strong adhesion and invasive potential. Using CD44 / CD54 expression as an auxiliary recognition indicator can effectively distinguish interference from non-tumor cells of epithelial origin, improving the specificity of CTC identification.

[0073] Based on the above CD45- / CD326+ / CD44+ / CD54+ phenotypic characteristics, specific capture of microcirculating tumor cells was achieved.

[0074] S54: Multiple quantitative analysis of cytokines.

[0075] Decode and analyze the microsphere data collected in step S4, see [reference]. Figure 7 : Dual encoding and decoding: First, based on the physical characteristics of forward scattered light (FSC) and side scattered light (SSC), the captured microsphere array was separated into two independent particle size groups: P2 gate (small-sized microspheres, 56.48%) and P3 gate (large-sized microspheres, 43.43%). Further analysis on the APC fluorescence channel revealed seven clear fluorescence intensity levels in each of the P2 and P3 gates, thus successfully distinguishing all 14 target cytokines.

[0076] Concentration calculation: The average fluorescence intensity (MFI) of the above 14 microsphere populations on the PE channel was measured and substituted into the preset standard curve to calculate the specific concentration values ​​(pg / mL) of 14 cytokines such as IL-2, IL-6, and IFN-γ.

[0077] S55: Comprehensive map construction.

[0078] The cell phenotype data (such as PD-1 / Tim-3) obtained from Module 3 detection are integrated with the factor function data obtained from S54: if the expression rate of PD-1 / TIM-3 is significantly increased in S52 and the concentrations of IFN-γ and TNF-α in S54 are lower than the lower limit of the normal reference value, the subject's T cells are determined to be in the functional exhaustion period; if the concentration of IL-6 in S54 is abnormally increased and accompanied by a sharp decrease in lymphocyte count in S51, a cytokine storm (CRS) warning is issued.

[0079] Example 3.

[0080] This embodiment describes the application of the above-described kit in assessing the immune system function of subjects, particularly as a companion diagnostic reagent for tumor immunotherapy.

[0081] The methods, kits, and applications for the combined detection of lymphocyte subsets and cytokines based on flow cytometry provided in this application construct a parallel detection system for cell phenotypes and cytokines on the same flow cytometry platform. By utilizing spectrally compatible markers to resolve signal interference issues, it achieves simultaneous analysis of immune cell subsets, immune checkpoints, and multiple cytokines in trace blood samples. This approach avoids systematic errors and sample waste caused by multi-platform detection and provides a comprehensive atlas reflecting the synergistic state of cellular immune structure and humoral immune function, improving the accuracy and efficiency of clinical immune assessment.

[0082] In the description of this application, it should be noted that the terms "vertical", "up", "down", "horizontal", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0083] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0084] Finally, it should be noted that the above descriptions are merely preferred embodiments of this application and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for combined detection of lymphocyte subsets and cytokines based on flow cytometry, characterized in that, Includes the following steps: Step S1: Obtain an isolated blood sample and aliquot it into cell phenotype detection components and cytokine detection components; Step S2: Use a pre-set flow cytometry antibody composition to specifically label the immune cell surface antigens in the cell phenotype detection section, and then add erythrocyte lysis buffer to perform erythrocyte lysis treatment after incubation; Step S3: The cytokine detection components are separated into plasma or serum, the target cytokines are captured using a fluorescently encoded microsphere array, and a double-antibody sandwich immune complex is formed using the detection antibody; Step S4: Using the same flow cytometer, under the uniform voltage gain setting and fluorescence compensation matrix after calibration of microspheres, collect the scatter plot data of the labeled cells in step S2 and the fluorescence intensity data of the double antibody sandwich immune complex formed in step S3, respectively. Step S5: Obtain the proportion data of immune cell subsets and cytokine concentration data of the blood sample, which are used to construct the immune status atlas of the subject.

2. The method for combined detection of lymphocyte subsets and cytokines based on flow cytometry according to claim 1, characterized in that, The flow cytometry antibody composition in step S2 includes: Module 1: Includes specific antibodies against CD45, CD3, CD4, CD8, CD19, CD16, and CD56 for detecting lymphocyte subsets; Module 2: Includes specific antibodies against CD4, CD25, and CD127 for detecting regulatory T cells; Module 3 includes specific antibodies targeting at least one of PD-1, CTLA-4, Tim-3, LAG-3, CD154, and CD107a, used to detect immune checkpoint expression levels or T cell activation levels.

3. The method for combined detection of lymphocyte subsets and cytokines based on flow cytometry according to claim 1, characterized in that, The fluorescently encoded microsphere array in step S3 includes microsphere populations conjugated with capture antibodies against the following 14 cytokines: IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17a, IL-17F, IL-22, TNF-α, IFN-γ, and TNF-β; wherein the microsphere populations are distinguished by different particle sizes and fluorescence encoding intensities.

4. The method for combined detection of lymphocyte subsets and cytokines based on flow cytometry according to claim 1, characterized in that, Step S2 also includes the detection of circulating tumor cells: After erythrocyte lysis, epithelial-derived cells are identified using a combination of antibodies targeting CD45, CD326, CD44, and CD54. The cell population that is CD45 negative and CD326 positive is identified as circulating tumor cells, and the expression of CD44 and CD54 is used to perform auxiliary identification or adhesion molecule characterization analysis on the circulating tumor cells.

5. The method for combined detection of lymphocyte subsets and cytokines based on flow cytometry according to claim 1, characterized in that, In step S4, the cell phenotype detection and cytokine detection use a spectrally compatible fluorescent labeling system; the method further includes: using calibrators to calibrate the photomultiplier tube voltage and fluorescence compensation matrix of the flow cytometer to correct signal crosstalk of microsphere fluorescence to the cell detection channel, and setting a scattered light threshold to eliminate interference from cell debris to the microsphere detection area, thereby achieving synchronous acquisition of the data.

6. The method for combined detection of lymphocyte subsets and cytokines based on flow cytometry according to claim 2, characterized in that, Step S5 further includes: correlation analysis of the expression level data obtained by module three with the concentration data of the cytokines to provide assessment data reflecting the T lymphocyte depletion state or the risk of cytokine storm.

7. A flow cytometry assay kit for assessing immune status, characterized in that, The kit includes: The first reagent component comprises a combination of fluorescently labeled antibodies for labeling lymphocyte subsets, regulatory T cells, and immune checkpoint proteins, wherein the immune checkpoint proteins include at least one of PD-1, CTLA-4, Tim-3, LAG-3, CD154, and CD107a. The second reagent component includes a fluorescently encoded microsphere suspension conjugated with antibodies targeting multiple cytokines, and a corresponding mixture of biotinylated or fluorescently labeled detection antibodies.

8. The flow cytometry assay kit for assessing immune status according to claim 7, characterized in that, The antibody in the first reagent component and the fluorescent label used for the microspheres in the second reagent component have fluorescence emission spectra that are independent of each other or can be distinguished by fluorescence compensation, and the kit also contains calibration microspheres or cytokine standards suitable for flow cytometry.

9. The use of the kit according to claim 7 or 8 in the preparation of a test reagent for assessing the immune system function of a subject.

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