Antibody composition and prediction system for lymphoma immunophenotyping based on flow cytometry

Abstract

The present invention belongs to the field of medical detection technology, and discloses an antibody composition for lymphoma immunotyping based on flow cytometry and a prediction system thereof. Based on the specificity of antigen expression in normal different types of lymphocytes, the abnormal expression of certain antibodies or antibody combinations in specific lymphomas, and the combination of factors such as the cross-lineage expression of specific antibodies, the present invention provides an antibody composition that can comprehensively, efficiently and comprehensively perform the first step of immunotyping of lymphoma in a single tube. The prediction system for lymphoma immunotyping based on flow cytometry provided by the present invention includes a data detection module and a data analysis module. The present invention predicts the immunotyping of lymphoma by using an improved flow sample preparation method and the antibody composition provided by the present invention, which can not only significantly shorten the experimental time, save antibodies, and improve work efficiency, but also provide a comprehensive, efficient and comprehensive prediction conclusion of lymphoma immunotyping, especially capable of quickly identifying mixed lineage lymphoma.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical detection, and relates to an antibody composition and a prediction system thereof for lymphoma immunophenotyping based on flow cytometry. Background Art

[0002] Flow cytometry is a method for quantitative analysis of single cells. It offers advantages such as speed, high precision, and multi-parameter capabilities, making it one of the most advanced methods for quantitative cell analysis. The hemolysis step in preparing the test solution significantly impacts test results, especially when batch processing samples. Due to the numerous manual steps involved, the hemolysis time is significantly affected by environmental factors. Furthermore, after adding the hemolysin, the sample must be incubated in the dark for approximately 15 minutes. Existing hemolysis methods are time-consuming and relatively inefficient, necessitating improvements to enhance detection efficiency.

[0003] Flow cytometry plays an important role in the diagnosis, classification, staging, and monitoring of residual lymphoma. Flow cytometry immunoassays analyze whether each individual cell in a population expresses certain specific antigens (i.e., phenotype), thereby defining the cell lineage (B or T / NK) and maturity (precursor or mature), providing a reliable basis for diagnosis. Cell phenotyping and result interpretation often require the following steps: ① Determine the maturity of a cell population, such as mature B cells or primitive / immature cells; ② Identify abnormal cells by distinguishing their antigen expression profile from that of normal cells; ③ Detailed phenotype analysis of the abnormal cell population, such as expression or absence of a specific antigen, and detailed investigation of increases or decreases in fluorescence intensity detected by a specific antibody; ④ Determine whether the information from the flow cytometry test is diagnostic; even if it is not diagnostic, it can provide advice for further testing, such as immunohistochemistry, cytogenetics, FISH, and molecular testing; ⑤ Immunophenotyping may have certain prognostic value, including identifying potential therapeutic targets. Currently, the most popular approach in the flow cytometry industry is to test only one antibody per channel. However, if the same antibody channels are used, multiple tests are often required to test them simultaneously, wasting both antibody and time. Prior art designs for first-line antibodies used in lymphoma typing often utilize two-tube assays, requiring analysis of data from both tubes. This not only wastes gating antibodies and reduces experimental efficiency, but also prevents simultaneous observation of the connections between T, NK, and B lymphocytes, and makes it impossible to distinguish the expression of cross-lineage antigens across different lymphocytes, making it impossible to make targeted screening recommendations for cross-lineage antigen expression. Summary of the Invention

[0004] In view of the above-mentioned problems existing in the prior art, the first object of the present invention is to optimize the number of tubes and antibody combinations of first-line antibodies based on flow cytometry detection, and to provide an antibody composition that can comprehensively, efficiently and comprehensively perform the first step of lymphoma immunophenotyping in a single tube.

[0005] A second objective of the present invention is to improve the hemolysis method used in flow cytometry sample preparation by optimizing the incubation conditions and hemolysin type used in the hemolysis process, significantly increasing the efficiency of test fluid preparation and thus improving detection efficiency. Furthermore, in combination with the aforementioned antibody composition for lymphoma immunophenotyping, and in conjunction with the expression of specific antibody combinations and antibody pairs, an efficient, economical, and comprehensive flow cytometry-based prediction system for lymphoma immunophenotyping is provided, which can rapidly identify mixed lymphomas.

[0006] To achieve the above-mentioned purpose, the embodiment of the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides an antibody composition for lymphoma immunophenotyping based on flow cytometry, wherein the antibody composition comprises anti-CD8 antibody, anti-CD4 antibody, anti-CD10 antibody, anti-CD3 antibody, anti-CD56 antibody, anti-CD7 antibody, anti-CD5 antibody, anti-CD34 antibody, anti-CD10 antibody, anti-CD19 antibody, anti-CD2 antibody, anti-CD20 antibody, anti-CD45 antibody, anti-kappa antibody and anti-lambda antibody; the above antibodies are all monoclonal antibodies;

[0008] The antibody compositions are mixed in the same flow cytometry tube during detection.

[0009] During the development of cells in the normal hematopoietic system, each type of cell has its own inherent pattern of antigen expression. However, in tumor states such as leukemia, lymphoma, and MM, this pattern may change in quantity or quality. Based on these changes, auxiliary diagnosis of these diseases can be performed for typing and classification. The flow cytometry detection method uses fluorescein-labeled McAbs against human cell differentiation antigens to bind to the corresponding antigens of individual cells in the sample, and uses a flow cytometer to detect the fluorescent markers bound to the cell surface, thereby analyzing the antigen expression of abnormal cell populations. Based on flow cytometry, the present invention optimizes the number of tubes and antibody combinations of first-line antibodies used for lymphoma immunotyping, and provides an antibody composition that only requires one tube to detect 15 antibody indicators, so as to achieve low sample requirements, rapid, comprehensive, and relatively accurate lymphoma immunotyping.

[0010] Preferably, the antibody is labeled with different fluorescent markers; the fluorescent markers are selected from FITC, PE, ECD, PE-CY7, PerCP-Cy TM5.5, APC, APC Alexa Fluor 700, Pacific Blue, Brilliant Violet 421, SparkViolet TM 538、APC-Cy7 TM 7.

[0011] Preferably, the labeling coordination relationship between the fluorescent marker and the antibody is as follows: the labeling coordination relationship between the fluorescent marker and the antibody is as follows: anti-Kappa antibody and anti-CD8 antibody are labeled with FTIC, anti-Lambda antibody and anti-CD4 antibody are labeled with PE, anti-CD3 antibody is labeled with ECD, and anti-CD56 antibody is labeled with PerCP-Cy TM 5.5, anti-CD7 antibody labeled with PE-Cy7, anti-CD5 antibody and anti-CD34 antibody labeled with APC, anti-CD10 antibody labeled with APC Alexa Fluor 700, anti-CD19 antibody labeled with APC-Cy7 TM 7. Anti-CD2 antibody labeled Pacific Blue, anti-CD20 antibody labeled Briliant Violet 421, anti-CD45 antibody labeled Spark Violet TM 538.

[0012] In a second aspect, the present invention provides a prediction system for lymphoma immunophenotyping based on flow cytometry, the prediction system comprising a data detection module and a data analysis module;

[0013] Wherein, the detection module is used to detect the antigen expression of the cell fluid to be tested by flow cytometry, wherein the cell fluid to be tested comprises a sample to be tested, a hemolysin composition and the antibody composition for lymphoma immunophenotyping based on flow cytometry according to any one of claims 1 to 3;

[0014] The data analysis module is used to analyze the detection results of the detection module and predict lymphoma immunophenotyping according to predetermined judgment criteria.

[0015] Preferably, the lymphoma includes B-cell lymphoma, T-cell lymphoma or NK-cell lymphoma, and mixed-lineage lymphoma of any two of the three types of cells: B cells, T cells or NK cells.

[0016] Preferably, in the detection module, the hemolysin composition comprises OPtiLyse C reagent and FACS Lysingsolution;

[0017] The preparation process of the cell fluid to be tested includes: mixing the antibody composition for lymphoma immunophenotyping based on flow cytometry with a sample to be tested, adding OPtiLyse C reagent, incubating at 18-25° C. in the dark for 2-3 minutes, adding FACS Lysing solution, and incubating at 36-38° C. in the dark for 2-3 minutes to obtain the cell fluid to be tested;

[0018] The sample to be tested includes a peripheral blood sample or a bone marrow sample.

[0019] Preferably, the data analysis module performs the following process: obtaining the result data of the data detection module, removing the adhesion and cell debris data, setting a gate with CD45-SS, and dividing the cell population into a granulocyte area, a monocyte area, a lymphocyte area, a CD45 weakly positive area, and a CD45 negative area according to the expression of CD45, and after circling the target cell population, analyzing the expression of B cells, T cells, NK cells, and different lymphocyte cross-lineage antigens within the lymphocyte gate.

[0020] Preferably, the analysis of the expression of B cells, T cells, NK cells and different lymphocyte cross-lineage antigens within the lymphocyte gate specifically includes the following:

[0021] (1) Analyze B cells within the lymphocyte gate, including gating B cells using CD19-SS;

[0022] Observe the CD45 weakly positive area or CD45 negative area, and combine the expression of CD34 and CD20-CD10 pattern to predict the probability of B lymphoblastic leukemia;

[0023] Observe the development trend of B progenitor cells and mature B cells, and combine the proportion of mature B cells in lymphocytes to predict the probability of B cell lymphoma;

[0024] Observe the expression of Kappa-Lambda light chain on the membrane of mature B cells to predict the probability of B cell lymphoma;

[0025] (2) Analyze T cells and NK cells within the lymphocyte gate, including gating T cells and NK cells using CD3-SS;

[0026] Observe the CD45 weakly positive area or CD45 negative area, and combine it with the expression of CD34 to predict the probability of T lymphoblastic leukemia;

[0027] Observe the CD4 / CD8 ratio in T cells within the logical lymphatic gate, whether pan-T cell antigen expression is abnormal, or whether there is abnormal increase in single antigen expression in T cells to predict the probability of T cell lymphoma;

[0028] Observe NK cells within the lymphocyte gate, including circling NK cells or T cells using CD3-CD19-, observe the ratio of NK cells to lymphocytes within the logical lymphocyte gate, and combine whether the expression of antigens including CD56, CD7, CD2 or CD5 is abnormal to predict the probability of NK cell lymphoma;

[0029] (3) Based on the above analysis results of the expression of B cells, T cells, NK cells and cross-lineage antigens in the lymphocyte gate, the probability of mixed lymphoma of any two of the three types of cells: B cells, T cells or NK cells is predicted.

[0030] Preferably, in the analysis of B cells in the lymphocyte gate, when the ratio of Kappa / Lambda of the cell membrane light chain of the mature B cells does not fall within the range of 0.3 to 3.0 or when Kappa / Lambda is not expressed, the cells are determined to be abnormal mature B cells, and the probability of B cell lymphoma is predicted based on the ratio of the abnormal mature B cells;

[0031] Further according to the expression of CD5 and CD10, the prediction result is output as follows: suspected CD5 + CD10 - B-cell lymphoma, CD5 - CD10 - B-cell lymphoma, CD5 + CD10 + B-cell lymphoma or CD5 - CD10 + Any type of B-cell lymphoma;

[0032] The analysis of T cells and NK cells in the lymphocyte gate predicts the probability of T cell lymphoma when the proportion of T cells in the logical lymphocyte gate to lymphocytes is greater than 70% or when the CD4 / CD8 ratio of T cells in the logical lymphocyte gate does not fall within the range of 0.5 to 3.0;

[0033] The analysis of T cells and NK cells within the lymphocyte gate, CD3-CD19- gate, CD4+ accompanied by abnormal expression of CD56, CD5, CD7 or CD2 antigens is determined to be abnormal T cells, and the probability of T cell lymphoma is predicted based on the proportion of the abnormal T cells;

[0034] The T cells and NK cells in the lymphocyte gate are analyzed. When the proportion of NK cells in the logical lymphocyte gate is greater than 40% of the lymphocytes, or CD4- in the CD3-CD19- gate is accompanied by abnormal expression of CD56, CD5, CD7 or CD2 antigens, the probability of T cell lymphoma or NK cell lymphoma is predicted.

[0035] Preferably, the analysis of the expression of cross-lineage antigens of different lymphocytes is performed by analyzing the expression of specific antibody pairs or antibodies within the logical lymphatic gate, observing the cross-lineage expression between different lymphocytes, and outputting the prediction results for targeted subsequent screening;

[0036] The specific antibody pairs or antibody combinations include (CD5+CD34)-CD10, CD3-CD10, CD7-CD10 or CD3-CD19 or CD19-CD7 or CD19-CD56.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] The present invention comprehensively considers the mechanisms or specific lymphoma characteristics including the following seven factors and provides an antibody composition for primary screening of lymphoma immunophenotyping, wherein the seven factors are as follows: a) Normal T lymphocytes express CD3, CD5, CD2, CD7, but do not express Kappa, Lambda, CD20, and CD19; b) Normal NK lymphocytes express CD7, CD2, and CD56, but do not express CD3, Kappa, Lambda, CD20, and CD19; c) Normal B lymphocytes express Kappa, Lambda, and CD20, but do not express CD3, CD7, CD2; d). Normal lymphocytes at all maturation stages do not express CD34; e). Combinations of CD8 and Kappa, CD4 and Lambda, CD5 and CD34, CD2 and CD20 have the same fluorescent channel after corresponding fluorescent labeling; f). Abnormal expression of certain antibodies, antibody pairs or antibody combinations in specific lymphomas; g). By observing the expression of (CD5+CD34)-CD10 / CD3-CD10 / CD7-CD10 / CD3-CD19 / CD19-CD7 / CD19-CD56 and other conditions within the logical lymphatic gate, cross-lineage expression between different lymphocytes can be identified. In view of the fact that the antibody composition designed by the present invention for lymphoma immunophenotyping is more comprehensive, various antibody indicators can be reasonably applied, covering a wide range, and can accurately identify mixed lymphomas and analyze their immunophenotypes. Combining multiple judgment factors facilitates rapid result judgment and makes more comprehensive and targeted recommendations for subsequent screening.

[0039] The present invention improves the traditional flow cytometry sample preparation method by appropriately increasing the incubation temperature after adding a certain hemolysin and optimizing the type of hemolysin, shortening the incubation time after adding the hemolysin from 15 minutes in the traditional hemolysis process to 4-6 minutes, which can significantly improve the detection efficiency.

[0040] Methodological validation of the improved flow cytometric sample preparation method and the lymphoma immunophenotyping antibody composition provided by the present invention for lymphoma analysis has demonstrated that the improved flow cytometric sample preparation and analysis methods achieve superior accuracy and precision compared to conventional flow cytometric sample preparation methods and conventional two-tube analysis methods. The predictive method for lymphoma immunophenotyping provided by the present invention significantly shortens experimental time, conserves antibodies, improves work efficiency, and provides comprehensive, efficient, and integrated lymphoma immunophenotyping predictions. It is particularly effective in rapidly identifying mixed-lineage lymphomas. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 The cell to be tested in Example 2 of the present invention is cut off from the adhesion bodies and cell fragments and its CD45-SS detection diagram is as follows Figure 1 As shown, Figure 1 a) is the detection image after the adhesion bodies of the cells to be tested are cut off; Figure 1 b) is a detection image after cutting away adhesion bodies and cell fragments; Figure 1 c) The cells to be tested are CD45-SS detection images;

[0043] Figure 2 This is a diagram showing the development of B cells and their proportion of lymphocytes in Example 2 of the present invention, wherein Figure 2 a) is a detection diagram of CD19 positive cells to be tested; Figure 2 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 2 c) Detection chart of the ratio of B cells to lymphocytes;

[0044] Figure 3 This is a detection diagram of the B cell immunophenotype (expression of CD5, CD20, CD10 or cell membrane light chains Kappa and Lambda) in Example 2 of the present invention, wherein Figure 3 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 3 b) is the detection diagram of CD20 expression on B cells; Figure 3 c) CD10 expression on B cells; Figure 3 d) is the detection diagram of the expression of Kappa and Lambda light chains on the B cell membrane;

[0045] Figure 4This is a graph showing the proportion of T cells and NK cells in lymphocytes in Example 2 of the present invention, wherein Figure 4 a) is the CD3 positive cell detection diagram; Figure 4 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 4 c) Detection chart of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes;

[0046] Figure 5 This is a diagram showing the development of CD4 and CD8 in T cells in Example 2 of the present invention, wherein Figure 5 a) is the detection diagram of T cell CD4 expression; Figure 5 b) is the detection diagram of T cell CD8 expression; Figure 5 c) is a detection diagram of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells, and the proportion of CD4-CD8+T cells in T cells;

[0047] Figure 6 This is a graph showing the development of CD7, CD5, and CD2 in T cells and NK cells in Example 2 of the present invention, wherein Figure 6 a) is a graph showing the detection of CD7 expression in T cells and NK cells; Figure 6 b) is a graph showing the detection of CD5 expression in T cells and NK cells; Figure 6 c) is a graph showing the detection of CD2 expression in T cells and NK cells;

[0048] Figure 7 This is a detection diagram for observing whether different lymphocytes express across different lines in Example 2 of the present invention, wherein Figure 7 a) is the detection diagram of lymphocyte CD3 / CD19; Figure 7 b) is the detection diagram of lymphocyte CD3 / CD10 expression; Figure 7 c) is the detection graph of lymphocyte CD7 / CD10 expression; Figure 7 d) is the detection diagram of lymphocyte CD56 / CD19 expression;

[0049] Figure 8 This is a typical example of the present invention, in which the cells to be tested are cut off from the adhesion bodies and cell fragments and their CD45-SS detection diagram, wherein Figure 8 a) is the detection image after the adhesion bodies of the cells to be tested are cut off; Figure 8 b) is a detection image after cutting away adhesion bodies and cell fragments; Figure 8 c) is the detection image of CD45-SS cells to be tested;

[0050] Figure 9 This is a detection diagram of B cell development and lymphocyte ratio in target object 1 in a typical case of the present invention, where Figure 9 a) is a CD19 positive cell detection image of the cells to be tested; Figure 9 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 9 c) Detection chart of the ratio of B cells to lymphocytes;

[0051] Figure 10 This is a detection diagram of B cell immune phenotype (expression of CD5, CD10 or cell membrane light chains Kappa and Lambda) in target object 1 in a typical case of the present invention; Figure 10 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 10 b) is the expression of CD10 on the B cells to be tested; Figure 10 c) is a graph showing the expression of Kappa and Lambda light chains on the membrane of the B cells to be tested;

[0052] Figure 11 This is a detection diagram of the proportion of T cells and NK cells in lymphocytes in target object 1 in a typical case of the present invention; Figure 11 a) is the CD3 positive cell detection diagram; Figure 11 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 11 c) Detection graph of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes;

[0053] Figure 12 This is a graph showing the development of CD4 and CD8 in T cells in target subject 1 in a typical case of the present invention; Figure 12 a) is the detection diagram of T cell CD4 expression; Figure 12 b) is the detection diagram of T cell CD8 expression; Figure 12 c) is a detection graph of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells and the proportion of CD4-CD8+T cells in T cells;

[0054] Figure 13 This is a graph showing the development of CD7, CD5, and CD2 in T cells and NK cells in target object 1 in a typical case of the present invention; Figure 13 a) is the detection diagram of CD7 expression in T cells and NK cells; Figure 13 b) is a graph showing the detection of CD5 expression in T cells and NK cells; c) is a graph showing the detection of CD2 expression in T cells and NK cells;

[0055] Figure 14 This is a graph showing whether different lymphocytes express across different lines in target object 1 in a typical case of the present invention; Figure 14 a) is the detection diagram of lymphocyte CD3 / CD19; Figure 14 b) is the detection diagram of lymphocyte CD3 / CD10 expression; Figure 14c) is the detection graph of lymphocyte CD7 / CD10 expression; Figure 14 d) is the detection diagram of lymphocyte CD56 / CD19 expression;

[0056] Figure 15 This is a detection diagram of the proportion of T cells and NK cells in lymphocytes in target object 2 in a typical case of the present invention, where Figure 15 a) is the CD3 positive cell detection diagram; Figure 15 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 15 c) Detection chart of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes;

[0057] Figure 16 This is a graph showing the development of CD4 and CD8 T cells in target subject 2 in a typical case of the present invention; Figure 16 a) is the detection diagram of T cell CD4 expression; Figure 16 b) is the detection diagram of T cell CD8 expression; Figure 16 c) is a detection graph of the proportion of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells, and CD4-CD8+T cells to T cells;

[0058] Figure 17 This is a graph showing the development of CD7, CD5, and CD2 in T cells and NK cells in target object 2 in a typical case of the present invention; Figure 17 a) is the detection diagram of CD7 expression in T cells and NK cells; Figure 17 b) is the detection graph of CD5 expression in T cells and NK cells; Figure 17 c)

[0059] This is the detection diagram of CD2 expression in T cells and NK cells;

[0060] Figure 18 This is a detection diagram of B cell development and lymphocyte ratio in target object 3 in a typical case of the present invention; Figure 18 a) is a detection diagram of CD19 positive cells to be tested; Figure 18 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 18 c) Detection chart of the ratio of B cells to lymphocytes;

[0061] Figure 19 This is a detection diagram of the B cell immune phenotype and the development of CD7, CD5 and CD2 of T cells and NK cells in target object 3 in a typical case of the present invention; Figure 19 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 19 b) is the expression of CD10 on the B cells to be tested; Figure 19c) is a graph showing the expression of Kappa and Lambda light chains on the membrane of the B cells to be tested; Figure 19 d) is the detection graph of CD7 expression in T cells and NK cells; Figure 19 e) is a graph showing the detection of CD5 expression in T cells and NK cells; Figure 19 f) is a graph showing the detection of CD2 expression in T cells and NK cells;

[0062] Figure 20 This is a detection diagram of the proportion of T cells and NK cells in lymphocytes in target object 3 in a typical case of the present invention; Figure 20 a) is the CD3 positive cell detection diagram; Figure 20 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 20 c) Detection graph of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes;

[0063] Figure 21 This is a diagram of the CD45-SS detection of the cells to be tested in tube 1 of comparative example 1 of the present invention after the adhesion bodies and cell fragments are cut off. Figure 21 a) is the detection image after the adhesion bodies of the cells to be tested are cut off; Figure 21 b) is a detection image after cutting away adhesion bodies and cell fragments; Figure 21 c) is the detection image of CD45-SS cells to be tested;

[0064] Figure 22 This is a graph showing the ratio of T cells and NK cells to lymphocytes in tube 1 of comparative example 1 of the present invention, wherein Figure 22 a) is the CD3 positive cell detection diagram; Figure 22 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 22 c) Detection chart of CD3-positive T cells, NKT cells, and the ratio of NK cells to lymphocytes;

[0065] Figure 23 This is a graph showing the development of CD4 and CD8 T cells in tube 1 of comparative example 1 of the present invention, wherein Figure 23 a) is the detection diagram of T cell CD4 expression; Figure 23 b) is the detection diagram of T cell CD8 expression; Figure 23 c) is a graph showing the proportion of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells and CD4-CD8+T cells in T cells;

[0066] Figure 24 This is a graph showing the development of CD7, CD5, and CD2 of T cells and NK cells in tube 1 of comparative example 1 of the present invention, wherein Figure 24 a) is the detection diagram of CD7 expression in T cells and NK cells; Figure 24b) is the detection graph of CD5 expression in T cells and NK cells; Figure 24 c) is the detection graph of CD2 expression in T cells and NK cells;

[0067] Figure 25 This is a graph showing the development of B cells and the proportion of lymphocytes in the cells to be tested in tube 2 of comparative example 1 of the present invention, wherein Figure 25 a) is a detection diagram of CD19 positive cells to be tested; Figure 25 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 25 c) is a graph showing the ratio of B cells to lymphocytes;

[0068] Figure 26 The detection diagram of B cell immunophenotype (expression of CD5, CD20, CD10 and cell membrane light chains Kappa and Lambda) in the test cells in tube 2 of comparative example 1 of the present invention is as follows: Figure 26 As shown, Figure 26 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 26 b) is the detection diagram of CD20 expression on B cells; Figure 26 c) CD10 expression on B cells; Figure 26 d) is the detection diagram of the expression of B cell membrane light chains Kappa and Lambda. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0070] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0071] Unless otherwise specified, all materials and reagents in the following examples can be obtained from commercial sources.

[0072] The instruments used in the present invention include: Navios flow cytometer, purchased from Beckman Coulter, USA, and data were analyzed using KUALZA software;

[0073] The reagents used in the present invention include: anti-CD8 antibody, anti-CD4 antibody, anti-CD10 antibody, anti-CD3 antibody, anti-CD56 antibody, anti-CD7 antibody, anti-CD5 antibody, anti-CD34 antibody, anti-CD10 antibody, anti-CD19 antibody, anti-CD2 antibody, anti-CD20 antibody, anti-CD45 antibody, anti-kappa antibody and anti-lambda antibody, all of which were purchased from Beckman Coulter, Becton, Dickinson and Company, Biolegend and Henan Kaiprei Company;

[0074] Optilysec hemolysin was purchased from Beckman Coulter, USA;

[0075] BD FACS Lysing solution was purchased from Becton, Dickinson and Company;

[0076] The washing solution in the present invention is PBS buffer (pH 7.0-7.4) containing 1% calf serum.

[0077] The present invention uses flow cytometry to determine the series and differentiation stage of lymphoma cells in bone marrow or peripheral blood samples from clinical patients, and can be used for initial screening of lymphoma immunophenotyping. While bone marrow samples are used as an example in the present embodiments, the same processing and analysis can also be performed on peripheral blood samples, and the analysis results can be used to predict lymphoma immunophenotyping.

[0078] When analyzing data, the present invention calculates the positive ratio of antigen expression for each cell population, where the negative and positive expression of the antigen is <20%, which is defined as negative (-) or no expression; and where the positive ratio is ≥20%, which is defined as positive (+).

[0079] The x% of the predicted results are subject to the actual test results.

[0080] Example 1 An antibody composition for lymphoma immunophenotyping based on flow cytometry

[0081] This example provides an antibody composition for lymphoma immunophenotyping based on flow cytometry: the antibody composition consists of anti-CD8 antibody, anti-CD4 antibody, anti-CD10 antibody, anti-CD3 antibody, anti-CD56 antibody, anti-CD7 antibody, anti-CD5 antibody, anti-CD34 antibody, anti-CD10 antibody, anti-CD19 antibody, anti-CD2 antibody, anti-CD20 antibody, anti-CD45 antibody, anti-kappa antibody and anti-lambda antibody; all of the above antibodies are monoclonal antibodies.

[0082] After opening the bottles of different antibodies, titer verification experiments were performed, and the most suitable amount was taken for the experiment.

[0083] The above antibodies can be labeled with corresponding fluorescein according to the common knowledge of those skilled in the art. This embodiment is described using the antibodies, dosages and corresponding fluorescein labels shown in Table 1 below as examples.

[0084] Table 1

[0085] Antibody name / dosage Fluorescein labeling Anti-kappa antibody (2.5 μL) + anti-CD8 antibody (5 μL) FITC Anti-Lambda antibody (2.5 μL) + anti-CD4 antibody (5 μL) PE Anti-CD3 antibody (5 μL) ECD Anti-CD56 antibody (2.5 μL) <![CDATA[PerCP-Cy TM 5.5]]> Anti-CD7 antibody (2.5 μL) PE-CY7 Anti-CD5 antibody (1.25 μL) + anti-CD34 antibody (1.25 μL) APC Anti-CD10 antibody (1.25 μL) APC Alexa Fluor 700 Anti-CD19 antibody (2.5 μL) <![CDATA[APC-Cy7 TM 7]]> Anti-CD2 antibody (1.25 μL) + anti-CD20 antibody (1.25 μL) Pacific Blue and Briliant Violet 421 Anti-CD45 antibody (1.25 μL) <![CDATA[Spark Violet TM 538]]>

[0086] Example 2 A prediction system for lymphoma immunophenotyping based on flow cytometry

[0087] This embodiment provides a prediction system for lymphoma immunophenotyping based on flow cytometry, which includes a data detection module and a data analysis module.

[0088] The detection module includes detecting the antigen expression of the cell fluid to be tested by flow cytometry, wherein the cell fluid to be tested is prepared by mixing the antibody composition and the hemolysin composition described in Example 1 with the bone marrow sample to be tested to prepare the cell fluid to be tested;

[0089] The data analysis module is used to analyze the detection results of the detection module and predict lymphoma immunophenotyping according to predetermined judgment criteria.

[0090] 1. The detection module includes the preparation of the cell fluid to be tested and the on-machine detection. The specific operation process is as follows:

[0091] (1) Take 2 mL of human bone marrow sample and immediately place it in a heparin anticoagulant tube. Mix well to prevent the sample from coagulating to obtain the test sample.

[0092] (2) Cell counting: Take 10 μL of the above sample and add it to 150 μL of PBS, mix well, and count the number of cells per microliter. According to the test results, the number of cells per tube is controlled at 1×10 6 ~2×10 6 indivual;

[0093] (3) Add 100 μL of the antibody composition in Table 1 of Example 1 and the cell solution adjusted for cell concentration in step (2) to each test tube, gently rotate the test tube, and incubate at room temperature (18°C to 25°C) for 15 min under the conditions specified in the antibody data sheet;

[0094] (4) Add 0.5 mL of OPtiLyse C reagent and immediately vortex and incubate at room temperature (18°C to 25°C) in the dark for 2.5 min; dilute FACS Lysing solution (10X) with distilled water to FACS Lysing solution (1×), add 2 mL of room temperature FACS Lysing solution (1×) to each tube, immediately mix at low speed, and incubate in a 37°C water bath in the dark for 2.5 min;

[0095] (5) Centrifuge at 300 g for 5 min at room temperature;

[0096] (6) Discard the supernatant, leaving about 50 μL of liquid in the test tube to avoid damaging the cell pellet;

[0097] (7) Mix at low speed and resuspend the cells in PBS buffer containing 1% calf serum. Add 2 mL of PBS containing 0.1% sodium azide to each tube to wash the cells, mix at low speed, and centrifuge at 300 g for 5 min at room temperature.

[0098] (8) Aspirate the supernatant, leaving about 50 μL of liquid in the test tube to avoid damaging the cell cluster; mix at low speed, resuspend the cells in PBS buffer containing 1% calf serum, add 500 μL of PBS to each tube, and mix at low speed.

[0099] (10) Cap the processed sample tube to obtain the cell suspension to be tested. Store the cell suspension in the dark at 2-8°C until ready for testing. It is best to analyze the sample within 24 hours after staining. Mix the suspension thoroughly before loading to prevent cell aggregation.

[0100] (11) Turn on the Navios flow cytometer and preheat the machine for at least 20 minutes. Test the internal quality control sample to ensure that all test values ​​are within the control range. Load the AL-PANEL and collect data. According to the set instrument conditions, obtain 300,000 cells per tube.

[0101] Second, the data analysis module is used to analyze the detection results of the detection module and predict lymphoma immunophenotyping based on predetermined judgment criteria. Specifically, it uses KUALZA software to analyze data, set gates for analysis, and output prediction results according to the following method. The specific contents are as follows:

[0102] S1. Establishing CD45-SS Map

[0103] Select the live single cell gate, use the FS INT and FS PEAK combination to judge the removal of adhesions, CD45-FS to remove cell debris, and establish a CD45-SS graph. The cell population after the cell debris is removed is roughly divided into five gates: Granulocyte, Monocytes, Lymphocytes, CD45dim, and CD45neg. In normal bone marrow, lymphocytes account for 20-40%, monocytes 2-8%, granulocytes 40-60%, nucleated red blood cells 2-15%, and immature cells less than 5%. Among them, the cells to be tested after the adhesions and cell debris are removed and the CD45-SS detection graph is shown as follows Figure 1 As shown, Figure 1 a) is the detection image after the adhesion bodies of the cells to be tested are cut off; Figure 1 b) is a detection image after cutting away adhesion bodies and cell fragments; Figure 1 c) The cells to be tested are CD45-SS detection diagram.

[0104] S2. Analysis of B cells within the lymphocyte gate

[0105] The CD19-SS gate was used to circle out B cells with CD3-CD7- in the CD19+ gate. The lymphoid B cell gate included B lymphocytes, B progenitor cells, and plasma cells.

[0106] (1) In the CD45dim or CD45neg gate, if CD34 is positive and the CD20-CD10 pattern is abnormal, it is determined to be abnormal primitive / immature B cells. When the proportion of abnormal primitive / immature B cells in B cells is greater than 20%, the prediction result is output as: suspected B lymphoblastic leukemia; when the proportion of abnormal primitive / immature B cells is less than or equal to 20%, the prediction result is output as: x% abnormal primitive / immature B cells are visible. The x% is subject to the actual test results, the same below.

[0107] (2) Observe the development trend of B progenitor cells and mature B cells. Observe the proportion of mature B cells in lymphocytes (CD19 + CD20 + The proportion of B lymphocytes in normal lymphocytes is 10-20%. If the development of B progenitor cells and mature B cells is abnormal, and the proportion of mature B cells in lymphocytes exceeds 20%, the prediction system outputs a suspected B-cell lymphoma.

[0108] Using a logical lymphocyte gate, we observe the expression of CD5, CD10, CD20, or CD34 on B lymphocytes. Among normal lymphocytes, mature B cells express CD20 and CD19, a small amount of CD5, and no CD34 or CD10. If observations reveal increased CD5 expression, abnormal CD10 expression, increased CD20 expression, or decreased CD20 expression, and the proportion of abnormal B cells exceeds 20%, the prediction system outputs a suspected B-cell lymphoma.

[0109] Among them, the detection chart of B cell development and lymphocyte ratio is as follows Figure 2 As shown, where: Figure 2 a) is a detection diagram of CD19 positive cells to be tested; Figure 2 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 2 c) Detection chart of the ratio of B cells to lymphocytes.

[0110] (3) Through the logical B cell gate, observe the expression of Kappa-Lambda, the light chain of mature B cells. The Kappa:Lambda ratio of normal B cell membrane light chain expression is 0.3 to 3. If the Kappa:Lambda ratio of B cell membrane light chain expression does not fall within the range of (0.3, 3) or neither Kappa nor Lambda is expressed, it is judged as an abnormal mature B cell. If the proportion of abnormal mature B cells in B cells is greater than 20%, the output prediction result is: suspected B cell lymphoma; if the proportion of abnormal mature B cells in B cells is less than or equal to 20%, the output prediction result is: x% abnormal mature B cells are visible.

[0111] If the prediction result is suspected B-cell lymphoma, CD5+10- B-cell lymphoma, CD5+CD10+ B-cell lymphoma, CD5-CD10- B-cell lymphoma and CD5-CD10+ B-cell lymphoma can be preliminarily screened according to the expression of CD5 and CD10; the output prediction result is CD5+CD10- B-cell lymphoma, CD5-CD10- B-cell lymphoma, CD5+CD10+ B-cell lymphoma or CD5-CD10+ B-cell lymphoma, and the corresponding prediction result is output.

[0112] Among them, the B cell immunophenotype (CD5, CD20, CD10 or cell membrane light chain Kappa and Lambda expression) is shown in the figure below. Figure 3 As shown, Figure 3 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 3 b) is the detection diagram of CD20 expression on B cells;

[0113] Figure 3c) CD10 expression on B cells; Figure 3 d) is the detection diagram of the expression of B cell membrane light chains Kappa and Lambda.

[0114] S3. Analysis of T cells and NK cells within the lymphocyte gate

[0115] Normal T cells account for 50-70%, NKT cells account for 20-30%, and NK cells account for 10-40%. T-cell lymphoma and NK-cell lymphoma will show an increase in the corresponding lymphocyte ratio.

[0116] Through the logical lymphocyte gate, observe the CD3 / CD56 graph, where CD3+CD19- is T cells, CD3+CD56+ is NKT cells, CD3-CD56+ is NK cells, and CD3-CD19- is NK cells or abnormal T cells. The ratio of cells in the gate is displayed to observe lymphocyte T cells and NK cells. The details are as follows:

[0117] (1) Observe the proportion of T cells to lymphocytes in the lymphocyte gate through the logical lymphocyte gate CD3+CD19-.

[0118] If CD45 dim or CD45 is negative and CD34+, it is determined to be abnormal primitive / immature T cells. When the proportion of abnormal primitive / immature T cells is greater than 20%, the prediction result is output as: suspected acute T-lymphocytic leukemia; when the proportion of abnormal primitive / immature T cells is less than or equal to 20%, the prediction result is output as: x% abnormal primitive / immature T cells are visible;

[0119] If CD45+CD34- is present, it is considered a T cell. Abnormal T cells are determined based on the CD4 / CD8 ratio, the percentage of CD4+CD8+ cells in T cells, the percentage of CD4-CD8- cells in T cells, abnormal pan-T cell antigen expression, or abnormally elevated expression of a single antigen in T cells. If the percentage of abnormal T cells is greater than 20%, the prediction output is: Suspected T-cell lymphoma; if the percentage of abnormal T cells is less than or equal to 20%, the prediction output is: X% abnormal T cells are visible.

[0120] The system analyzes the expression of CD4-CD8 in T lymphocytes, such as the ratio of CD4 to CD8. If a significant imbalance in the CD4 / CD8 ratio is observed in normal T cells, such as a CD4 / CD8 ratio greater than 10:1 or less than 1:10, these cells are considered abnormal. If the proportion of these abnormal T cells exceeds 20%, the prediction is: suspected T-cell lymphoma.

[0121] If CD5, CD7, or CD2 antigens are expressed abnormally (e.g., absent, enhanced, or weakened) compared to normal cells, or if CD10 antigen expression is abnormally elevated, these cells are considered abnormal T cells. If the proportion of these abnormal T cells is greater than 20%, the diagnosis is suspected of T-cell lymphoma.

[0122] It is important to observe the CD4 / CD8 ratio. If the CD4 / CD8 ratio is unbalanced, greater than 10:1 or less than 1:10, a large expansion of CD8+ T cells accompanied by downregulation of CD7 expression can be seen during viral infection, so pay attention to identification;

[0123] Among abnormal pan-T cell antigen expression, abnormal expression of CD3, CD5, and CD7 is more common, while abnormal expression of CD2 is relatively rare. Antigen expression is often reduced or absent, and a small number of patients may show upregulated antigen expression;

[0124] The expression of certain antigens in T cells is abnormally elevated, such as CD10.

[0125] (2) Observe the CD3-CD19- logic gate

[0126] If CD56+, further combined with whether the expression of antigens including CD7, CD2 or CD5 is abnormal, the probability of NK cell lymphoma is predicted;

[0127] If CD4+ cells are accompanied by abnormal expression of CD56, CD5, CD7, or CD2 antigens, or if the expression of certain antigens (such as CD10) is abnormal, they are considered abnormal T cells. If the proportion of abnormal T cells is greater than 20%, the prediction result is output as: suspected T-cell lymphoma; if the proportion of abnormal T cells is less than or equal to 20%, the prediction result is output as: x% abnormal T cells are visible.

[0128] If CD4- is accompanied by abnormal expression of CD56, CD5, CD7, or CD2 antigens, it is diagnosed as abnormal T cells or abnormal NK cells. If the proportion of abnormal T cells or abnormal NK cells is greater than 20%, the prediction result is output as: suspected T cell or NK cell lymphoma; if the proportion of abnormal T cells or abnormal NK cells is less than or equal to 20%, the prediction result is output as: x% abnormal T cells or NK cells are visible.

[0129] Among them, the proportion of T cells and NK cells in lymphocytes is shown in the figure below. Figure 4 As shown, Figure 4 a) is the CD3 positive cell detection diagram; Figure 4 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 4 c) Detection chart of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes.

[0130] Figure 4 shows the development detection of CD4 and CD8 in T cells. Figure 5 As shown, Figure 5 a) is the detection diagram of T cell CD4 expression; Figure 5 b) is the detection diagram of T cell CD8 expression; Figure 5 c) is a detection diagram of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells, and the proportion of CD4-CD8+T cells in T cells;

[0131] The development detection of CD7, CD5 and CD2 in T cells and NK cells is shown in the figure Figure 6 As shown, Figure 6 a) is a graph showing the detection of CD7 expression in T cells and NK cells; Figure 6 b) is a graph showing the detection of CD5 expression in T cells and NK cells; Figure 6 c) is the detection diagram of CD2 expression in T cells and NK cells.

[0132] S4. Analysis of the expression of different lymphocyte cross-lineage antigens in lymphocytes

[0133] Logical lymphocyte gate, through the expression of antigens such as (CD5+CD34)-CD10 / CD3-CD10 / CD7-CD10 / CD3-CD19 / CD19-CD7 / CD19-CD56, observes the cross-lineage expression between different lymphocytes. The flow analysis method provided by the present invention can more clearly detect the cross-lineage expression of abnormal cells, making subsequent screening more targeted. For example: abnormal T cells lose membrane CD3 / CD3 expression weakens, and express CD10 at the same time. The output prediction result is: suspected angioimmunoblastic lymphoma, it is recommended to combine bone marrow biopsy and IHC examination for further screening; if abnormal B cells express CD7, the output prediction result is: suspected B cell lymphoma combined with T cell lymphoma, it is recommended to combine second-line antibody cCD3 for further screening; if abnormal T cells express CD19, the output prediction result is: suspected T cell lymphoma accompanied by B cell lymphoma, it is recommended to combine second-line antibodies cCD79a and CD22 for further screening.

[0134] Observe whether different lymphocytes express across different lines. Figure 7 As shown, Figure 7 a) is the detection diagram of lymphocyte CD3 / CD19; Figure 7 b) is the detection diagram of lymphocyte CD3 / CD10 expression; Figure 7 c) is the detection graph of lymphocyte CD7 / CD10 expression; Figure 7 d) is the detection diagram of lymphocyte CD56 / CD19 expression.

[0135] S5. Based on the above analysis results of the expression of B cells, T cells or NK cells and cross-lineage antigens in the lymphocyte gate, predict whether it is a mixed lymphoma of any two of the three types of cells: B cells, T cells or NK cells.

[0136] The prediction system for lymphoma immunophenotyping based on flow cytometry provided in this embodiment has the following advantages:

[0137] (1) The present invention improves the traditional flow cytometry sample preparation method by adding two hemolysins and improving the incubation temperature. The incubation time after adding the hemolysins is shortened from 15 minutes in the traditional hemolysis process to 4.5 minutes, which can significantly reduce the flow cytometry sample preparation time and significantly improve the detection efficiency.

[0138] (2) The single-tube combination can simultaneously observe T lymphocytes, B lymphocytes, and NK lymphocytes, avoiding duplication of gating antibodies, saving reagents, and improving work efficiency;

[0139] (3) It is more advantageous for observing certain mixed lymphomas and can quickly identify different clonal proliferation populations in the same patient, such as patients with clonal proliferation of mature T lymphocytes and clonal proliferation of mature B lymphocytes at the same time;

[0140] (4) It can quickly identify different stages of clonal proliferation populations in the same patient, such as patients with clonally proliferating mature T lymphocytes and clonally proliferating primitive B lymphocytes, patients with clonally proliferating mature B lymphocytes and clonally proliferating primitive T lymphocytes, and discover some other primitive stage cells that do not express T and B lineages.

[0141] Example 3 A prediction system for lymphoma immunophenotyping based on flow cytometry

[0142] This example provides a prediction system for lymphoma immunophenotyping based on flow cytometry. The prediction system is substantially the same as the prediction system provided in Example 2, with the only difference being that: the detection module includes a preparation process of the cell fluid to be tested, followed by adding OPtiLyse C reagent and incubating at room temperature (18°C to 25°C) in the dark for 2.0 min; adding 2 mL of room temperature FACS Lysing solution (1×) and incubating in a 37°C water bath in the dark for 2.0 min. The remaining steps, parameters, analysis methods, and prediction methods are the same.

[0143] Example 4 A prediction system for lymphoma immunophenotyping based on flow cytometry

[0144] This example provides a prediction system for lymphoma immunophenotyping based on flow cytometry. The prediction system is substantially the same as the prediction system provided in Example 2, with the only difference being that: the detection module includes a preparation process for the cell fluid to be tested, followed by adding OPtiLyse C reagent and incubating at room temperature (18°C to 25°C) in the dark for 3 minutes; adding 2 mL of room temperature FACSLing solution (1×), followed by incubation in a 37°C water bath in the dark for 3 minutes. The remaining steps, parameters, analysis methods, and prediction methods are the same.

[0145] Typical Cases

[0146] Case 1: Target subject 1 is tested using the flow cytometry-based prediction system for lymphoma immunophenotyping provided in Example 2 of the present invention. The test module performs on-machine testing and the data analysis module performs analysis. The analysis details are as follows:

[0147] S1. Establishing CD45-SS Map

[0148] In the target sample 1, the cells to be tested are cut off from the adhesion bodies and cell fragments and the CD45-SS detection diagram is as follows Figure 8 As shown. Figure 8 a) is the detection image after the adhesion bodies of the cells to be tested are cut off; Figure 8 b) is a detection image after cutting away adhesion bodies and cell fragments; Figure 8 c) is the detection diagram of CD45-SS cells to be tested.

[0149] S2. Analysis of B cells within the lymphocyte gate

[0150] In the sample of target subject 1, the development of B cells and the proportion of lymphocytes are detected as follows Figure 9 shown; Figure 9 a) is a CD19 positive cell detection image of the cells to be tested; Figure 9 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 9 c) Detection chart of the ratio of B cells to lymphocytes.

[0151] In the sample of target object 1, the B cell immune phenotype (CD5, CD10 or cell membrane light chain Kappa and Lambda expression) is detected as shown in the figure Figure 10 As shown, Figure 10 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 10 b) is the expression of CD10 on the B cells to be tested; Figure 10 c) is a graph showing the expression of Kappa and Lambda light chains on the membrane of the B cells to be tested.

[0152] S3. Analysis of T cells and NK cells within the lymphocyte gate

[0153] In the sample of target subject 1, the ratio of T cells and NK cells to lymphocytes is shown in the figure below: Figure 11 shown; Figure 11 a) is the CD3 positive cell detection diagram; Figure 11 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 11 c) Detection chart of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes.

[0154] In the sample of target subject 1, the development detection diagram of CD4 and CD8 in T cells is as follows Figure 12 shown; Figure 12 a) is the detection diagram of T cell CD4 expression; Figure 12 b) is the detection diagram of T cell CD8 expression; Figure 12 c) is a detection diagram of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells and the proportion of CD4-CD8+T cells in T cells.

[0155] In the sample of target object 1, the development detection of CD7, CD5 and CD2 in T cells and NK cells is shown in the figure below. Figure 13 shown; Figure 13 a) is the detection diagram of CD7 expression in T cells and NK cells; Figure 13 b) is the detection graph of CD5 expression in T cells and NK cells; Figure 13 c) is the detection diagram of CD2 expression of T cells and NK cells.

[0156] S4. Analysis of the expression of different lymphocyte cross-lineage antigens in lymphocytes

[0157] Observe whether different lymphocytes express across different lines in the target object 1 sample. Figure 14 shown; Figure 14 a) is the detection diagram of lymphocyte CD3 / CD19; Figure 14 b) is the detection diagram of lymphocyte CD3 / CD10 expression; Figure 14 c) is the detection graph of lymphocyte CD7 / CD10 expression; Figure 14 d) is the detection diagram of lymphocyte CD56 / CD19 expression.

[0158] S5. Based on the above analysis results of the expression of B cells, T cells, NK cells and cross-lineage antigens in the lymphocyte gate, predict whether it is a mixed lymphoma of any two of the three types of cells: B cells, T cells or NK cells.

[0159] Analysis revealed that abnormal B cells in Subject 1's sample accounted for approximately 97.40% of the lymphocytes (an increased proportion), with no expression of Kappa and Lambda, accompanied by increased expression of CD5 and decreased expression of CD20. T cells and NK cells showed no abnormalities. The predicted result was: suspected B-cell lymphoma.

[0160] The target subject was further clinically screened and diagnosed with B-cell lymphoma.

[0161] Case 2: Target Subject 2 was tested using the flow cytometry-based prediction system for lymphoma immunophenotyping provided in Example 2 of the present invention. The test module performed on-device testing and the data analysis module performed analysis. Analysis revealed that abnormal T cells in Target Subject 2's sample accounted for approximately 93.61% of lymphocytes (a significantly increased proportion of lymphocytes), with a CD4:CD8 ratio less than 10:1, accompanied by decreased expression of CD2, CD5, and CD7. No abnormalities were observed in B cells or NK cells. The prediction result was: suspected T-cell lymphoma. Further clinical screening confirmed that this target subject had B-cell lymphoma.

[0162] In this case, only the detection graphs with abnormal expression are provided, and the detection graphs without obvious abnormalities are not repeated. Among them, the detection graph of the proportion of T cells and NK cells in lymphocytes in the target object 2 sample is as follows Figure 15 shown; Figure 15 a) is the CD3 positive cell detection diagram; Figure 15 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 15 c) Detection chart of CD3 positive T cells, NKT cells, and the proportion of NK cells in lymphocytes. In the sample of target subject 2, the detection chart of T cell CD4 and CD8 development is as follows Figure 16 shown; Figure 16 a) is the detection diagram of T cell CD4 expression; Figure 16 b) is the detection diagram of T cell CD8 expression; Figure 16 c) is a detection chart of the proportion of T cells CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells, and CD4-CD8+T cells in T cells. In the sample of target object 2, the development detection chart of T cells and NK cells CD7, CD5, and CD2 is as follows Figure 17 shown; Figure 17 a) is the detection diagram of CD7 expression in T cells and NK cells; Figure 17 b) is the detection graph of CD5 expression in T cells and NK cells; Figure 17 c) is the detection diagram of CD2 expression of T cells and NK cells.

[0163] Case 3: Target subject 3 was tested using the flow cytometry-based prediction system for lymphoma immunophenotyping provided in Example 2 of the present invention. The test module performed on-device testing and the data analysis module performed analysis. Analysis revealed a high proportion of abnormal B cells in the sample of target subject 3, with a B cell membrane Kappa:Lambda ratio greater than 3; accompanied by abnormal T cells, with absent CD3 antigen expression and diminished CD2 antigen expression in T cells; and no abnormalities in NK cells. The prediction result was: suspected mixed B-cell / T-cell lymphoma. Further clinical screening confirmed that the target subject had B-cell lymphoma with concomitant T-cell lymphoma.

[0164] In this case, only the detection graphs with abnormal expression are provided, and the detection graphs without obvious abnormalities are not repeated. Among them, the detection graphs of B cell development and lymphocyte ratio in target object 3 sample are as follows Figure 18 shown; Figure 18 a) is a detection diagram of CD19 positive cells to be tested; Figure 18 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 18 c) Detection chart of the ratio of B cells to lymphocytes. In the sample of target subject 3, the detection chart of B cell immune phenotype and the development of CD7, CD5 and CD2 of T cells and NK cells is as follows Figure 19 Shown among them Figure 19 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 19 b) is the expression of CD10 on the B cells to be tested; Figure 19 c) is a graph showing the expression of Kappa and Lambda light chains on the membrane of the B cells to be tested; Figure 19 d) is the detection graph of CD7 expression in T cells and NK cells; Figure 19 e) is a graph showing the detection of CD5 expression in T cells and NK cells; Figure 19 f) is the detection diagram of CD2 expression of T cells and NK cells.

[0165] In the sample of target object 3, the ratio of T cells and NK cells to lymphocytes is shown in the following figure: Figure 20 shown; Figure 20 a) is the CD3 positive cell detection diagram; Figure 20 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 20 c) Detection chart of CD3-positive T cells, NKT cells, and the proportion of NK cells in lymphocytes.

[0166] Comparative Example 1

[0167] This comparative example provides a method for predicting lymphoma immunophenotyping using traditional flow cytometry samples plus traditional two-tube analysis. The specific process is as follows:

[0168] 1. The detection module includes the preparation of the cell fluid to be tested and the on-machine detection. The specific operation process is as follows:

[0169] (1) Take 2 mL of human bone marrow sample and immediately place it in a heparin anticoagulant tube. Mix well to prevent the sample from coagulating to obtain the test sample.

[0170] (2) Cell counting: Take 10 μL of the above sample and add it to 150 μL of PBS, mix well, and count the number of cells per microliter. According to the test results, the number of cells in each tube is controlled at 1×10 6 ~2×10 6 indivual;

[0171] (3) Add the antibody composition listed in Table 2 below and 100 μL of the cell solution adjusted for cell concentration in step (2) to each test tube, gently rotate the test tube, and incubate at room temperature (18°C to 25°C) for 15 min under the conditions specified in the antibody data sheet.

[0172] Table 2

[0173] Tube 1 Antibody-Fluorescein / Dosage Tube 2 Antibody-Fluorescein / Dosage Anti-CD8 antibody-FITC (5 μL) Anti-Kappa antibody-FITC (2.5 μL) Anti-CD4 antibody-FE (5 μL) Anti-Lambda antibody-PE (2.5 μL) Anti-CD3 antibody-ECD (5 μL) Anti-CD34 antibody-ECD (5 μL) <![CDATA[Anti-CD56 antibody-PerCP-Cy TM 5.5 (2.5 μL)]]> <![CDATA[Anti-CD19 antibody-PerCP-Cy TM 5.5 (2.5 μL)]]> Anti-CD7 antibody-PE-CY7 (2.5 μL) Anti-CD10 antibody-PE-CY7 (2.5 μL) Anti-CD5 antibody-APC (1.25 μL) Anti-CD5 antibody-APC (1.25 μL) Anti-CD2 antibody-Pacific Blue (1.25 μL) Anti-CD20 antibody-Briliant Violet 421 (1.25 μL) <![CDATA[Anti-CD45 antibody - Spark Violet TM 538 (1.25 μL)]]> <![CDATA[Anti-CD45 antibody - Spark Violet TM 538 (1.25 μL)]]>

[0174] (4) Add 0.5 mL of OPtiLyse C reagent and immediately vortex, incubate at room temperature (18°C to 25°C) in the dark for 10 min; add 0.5 mL of PBS and stir, incubate at room temperature (18°C to 25°C) in the dark for at least 5 min;

[0175] (5) Centrifuge at 300 g for 5 min at room temperature;

[0176] (6) Discard the supernatant, leaving about 50 μL of liquid in the test tube to avoid damaging the cell pellet;

[0177] (7) Mix at low speed and resuspend the cells in PBS buffer containing 1% calf serum. Add 2 mL of PBS containing 0.1% sodium azide to each tube to wash the cells, mix at low speed, and centrifuge at 300 g for 5 min at room temperature.

[0178] (8) Aspirate the supernatant, leaving about 50 μL of liquid in the test tube to avoid damaging the cell cluster; mix at low speed, resuspend the cells in PBS buffer containing 1% calf serum, add 500 μL of PBS to each tube, and mix at low speed.

[0179] (10) Cap the processed sample tube to obtain the cell suspension to be tested. Store the cell suspension in the dark at 2-8°C until ready for testing. It is best to analyze the sample within 24 hours after staining. Mix the suspension thoroughly before loading to prevent cell aggregation.

[0180] (11) Turn on the Navios flow cytometer and preheat the machine for at least 20 minutes. Test the internal quality control sample to ensure that all test values ​​are within the control range. Load the AL-PANEL and collect data. According to the set instrument conditions, obtain 300,000 cells per tube.

[0181] 2. Data analysis, the specific contents are as follows:

[0182] 1. Analyze the expression of relevant antigens in tube 1

[0183] (1) FS INT and FS PEAK were combined to remove adhesions, CD45-FS was used to remove cell fragments, and CD45-SS was used to roughly divide the cells to be tested into five gates: Granulocytes, Monocytes, Lymphocytes, CD45dim, and CD45neg.

[0184] (2) Preliminary observation of CD3 / CD4 / CD8 / CD56 expression in CD3+ T lymphocytes and NK lymphocytes. For example, the ratio of CD4 to CD8 in T cells is observed. Normal T cell CD4 to CD8 is 0.5-3.0. If the ratio of CD4 to CD8 in the T cells of the cells to be tested does not fall within the range of (0.5, 3.0), it is judged as suspected abnormality.

[0185] It is important to observe the CD4 / CD8 ratio. If the CD4 / CD8 ratio is unbalanced, greater than 10:1 or less than 1:10, a large expansion of CD8+ T cells accompanied by downregulation of CD7 expression can be seen during viral infection, so pay attention to identification;

[0186] (3) Observe the expression of CD5 / CD7 / CD2 in CD3+T lymphocytes and NK lymphocytes through CD3 / CD5 / CD7 / CD2.

[0187] Among abnormal pan-T cell antigen expression, abnormal expression of CD3, CD5, and CD7 is more common, while abnormal expression of CD2 is relatively rare. Antigen expression is often reduced or absent, and a small number of patients may show upregulated antigen expression;

[0188] (4) Observe the ratio of T lymphocytes / NK lymphocytes to lymphocytes, the ratio of different T lymphocyte subsets CD4+CD8+ / CD4-CD8- / CD4-CD8+ / CD4+CD8-, and the ratio of CD3+CD4+T lymphocytes / CD3+CD8+T lymphocytes through the lymphocyte gate.

[0189] Normally, T cells account for 50-70%, NKT cells 20-30%, and NK cells 10-40%. This proportion may be elevated in T-NHL and NK-NHL. Using a logical lymphocyte gate, observe the CD3 / CD56 graph, where CD3+ indicates T cells, CD3+CD56+ indicates NKT cells, and CD3-CD56+ indicates NK cells, displaying the proportion of cells within the gate.

[0190] Among them, the cells to be tested were cut off from the adhesion bodies and cell fragments and the CD45-SS detection diagram was as follows Figure 21 As shown, Figure 21 a) is the detection image after the adhesion bodies of the cells to be tested are cut off; Figure 21 b) is a detection image after cutting away adhesion bodies and cell fragments; Figure 21 c) is the CD45-SS detection diagram of the cells to be tested. The detection diagram of the proportion of T cells and NK cells in lymphocytes is as follows Figure 22 As shown, Figure 22 a) is the CD3 positive cell detection diagram; Figure 22 b) is the detection diagram of the proportion of CD3 positive cells in lymphocytes; Figure 22 c) Detection chart of CD3 positive T cells, NKT cells, and the proportion of NK cells in lymphocytes. Detection chart of T cell CD4 and CD8 development as shown Figure 23 As shown, Figure 23 a) is the detection diagram of T cell CD4 expression; Figure 23 b) is the detection diagram of T cell CD8 expression; Figure 23 c) is a detection chart of the proportion of CD4+CD8+T cells, CD4+CD8-T cells, CD4-CD8+T cells and CD4-CD8+T cells in T cells. The detection chart of CD7, CD5 and CD2 development of T cells and NK cells is as follows Figure 24 As shown, Figure 24 a) is the detection diagram of CD7 expression in T cells and NK cells; Figure 24 b) is the detection graph of CD5 expression in T cells and NK cells; Figure 24 c) is the detection diagram of CD2 expression of T cells and NK cells.

[0191] 2. Analyze the expression of related antigens in tube 2

[0192] (1) FS INT and FS PEAK were combined to remove adhesions, CD45-FS was used to remove cell fragments, and CD45-SS was used to roughly divide the cells to be tested into five gates: Granulocytes, Monocytes, Lymphocytes, CD45dim, and CD45neg.

[0193] (2) Circle the CD19+ population using the CD19+SS plot. Use the CD20-CD10 plot in the CD19+ gate to circle CD10-CD20+ mature B cells and CD10+CD20- B progenitor cells. Use the CD19+CD20+ lymphocyte gate to observe the proportion of B lymphocytes in the lymphocyte population. B progenitor cells are the precursors of mature B lymphocytes, meaning that B progenitor cells later develop into mature B lymphocytes.

[0194] (3) The overall Kappa / Lambda graph and the lymphocyte gate Kappa / Lambda graph were used to observe the expression of B lymphocyte membrane light chains, and the CD19-FS gate was set to observe the proportion of B lymphocytes in lymphocytes.

[0195] Normal B cells exhibit polyclonal expression of membrane light chains, with a Kappa / Lambda ratio of approximately 1 / 3-3, and the cell size is consistent with other lymphocytes. Abnormal B cells exhibit monoclonal expression of membrane light chains, with a Kappa / Lambda ratio outside the 1 / 3-3 range, and the cell size may appear larger than other lymphocytes.

[0196] (4) Using the CD19 / CD10 / CD20 / CD5 antibody combination, we observed the expression and development of CD10 / CD5 / CD20 on B lymphocytes.

[0197] Normal mature B lymphocyte phenotype is CD19 + CD20 + CD10 - CD5 - , may be accompanied by a small amount of CD5+ expression. Abnormal B cells will have abnormal expression of CD10 and CD5 and increased and decreased expression of CD20 / CD19. The normal B progenitor cell immunophenotype is CD19 + CD10 + CD20 - .

[0198] If the Kappa:Lambda ratio of B cells is <0.3 or the Kappa:Lambda ratio of B cells is >3.0, CD5+10-NH-B, CD5+CD10+NHL-B, CD5-CD10-NHL-B, and CD5-CD10+NHL-B can be preliminarily screened based on the expression of CD5 and CD10; the prediction results can be output as: suspected CD5+CD10- B-cell lymphoma, CD5-CD10- B-cell lymphoma, CD5+CD10+ B-cell lymphoma, or CD5-CD10+ B-cell lymphoma.

[0199] The development of B cells and the proportion of lymphocytes in the cells to be tested are shown in the figure below. Figure 25As shown, Figure 25 a) is a detection diagram of CD19 positive cells to be tested; Figure 25 b) is a diagram for detecting the developmental patterns of CD10 and CD20 in B progenitor cells and B cells; Figure 25 c) is a test chart for the ratio of B cells to lymphocytes. The test chart for B cell immunophenotype (expression of CD5, CD20, CD10 and cell membrane light chains Kappa and Lambda) in the cells to be tested is shown in the figure below. Figure 26 As shown, Figure 26 a) is a graph showing the expression of CD5 in B cells to be tested; Figure 26 b) is the detection diagram of CD20 expression on B cells; Figure 26 c) CD10 expression on B cells; Figure 26 d) is the detection diagram of the expression of B cell membrane light chains Kappa and Lambda.

[0200] Compared with the prediction system provided in Example 2, the prediction system provided in this comparative example has the following limitations:

[0201] (1) Analysis tube 1 can only observe T lymphocytes and NK lymphocytes, but not B lymphocytes. Analysis tube 2 can only observe B lymphocytes, but not T lymphocytes and NK lymphocytes. Therefore, when predicting lymphoma immunophenotyping, the single-tube solution of this comparative example can only observe one type or category of disease.

[0202] (2) Traditional two-tube analysis method: two tubes are repeatedly gated for antibodies CD45 and cross-antigen antibodies abnormally expressed by B and T lineages, such as CD5 / CD10.

[0203] (3) Only the expression of CD5 / CD10 / CD20 / CD19 in the CD34-positive population can be observed, and it cannot be combined with the expression of T-lineage-related antibodies CD2 / CD7 / CD56.

[0204] Effect Examples

[0205] In order to investigate the practicability of the flow cytometry sample preparation method and data analysis method in the prediction system provided in Example 2, a methodological investigation was conducted by comparing them with the traditional flow cytometry sample preparation method and data analysis method provided in Comparative Example 1.

[0206] 1. Accuracy experiment: In order to determine the accuracy of the results and evaluate the size of the systematic error, the following experiment was conducted: bone marrow specimens from healthy people were selected and measured using two different techniques. The experimental results were recorded and the differences were calculated. The specific results are shown in Table 3 below.

[0207] Table 3

[0208] Process / cell ratio Example 2 Comparative Example 1 Difference Lymphocyte percentage 14.73 15.22 -0.49 T subgroup percentage 71.98 70.79 1.19 % of subgroup B 12.82 12.18 -1.36 NK subpopulation percentage 8.52 8.45 0.07

[0209] 2. Precision test: In order to evaluate the magnitude of random errors in the measurement results, the following experiments were performed: (1) Intra-batch repeat tests and inter-batch repeat tests, as follows:

[0210] (1) Intra-batch repeat test: Anticoagulated blood samples from bone marrow of healthy subjects were tested 10 times in a row using two different processes within the same time period. Details are shown in Tables 4-1 and 4-2 below.

[0211] Table 4-1

[0212]

[0213] Table 4-2

[0214]

[0215] (2) Repeated testing: Anticoagulated bone marrow samples from healthy individuals were tested once daily using both methods at the same time of day for 10 consecutive days. Details are shown in Tables 5-1 and 5-2 below.

[0216] Table 5-1

[0217]

[0218] Table 5-2

[0219]

[0220] 3. Stability test: After the specimen is prepared, detect abnormalities every 8 hours. The analysis results at different storage times within 24 hours can be examined, as shown in Table 6.

[0221] Table 6

[0222]

[0223] Methodological investigations have shown that compared with traditional flow cytometry sample preparation and traditional two-tube analysis, the improved flow cytometry sample preparation and single-tube analysis methods provided by the present invention have better precision and stability, as well as good accuracy. This prediction method can significantly shorten experimental time, save antibodies, and improve work efficiency.

[0224] Further investigation revealed that the repeatability and stability of the improved flow sample preparation process and single-tube analysis method provided in Examples 3 and 4 of the present invention were similar to those of the method provided in Example 2, and thus the present invention will not elaborate on them.

[0225] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions or improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. Use of an antibody composition for non-disease diagnosis of lymphoma immunophenotyping based on flow cytometry, characterized in that: The antibody composition consists of anti-CD8 antibody, anti-CD4 antibody, anti-CD3 antibody, anti-CD56 antibody, anti-CD7 antibody, anti-CD5 antibody, anti-CD34 antibody, anti-CD10 antibody, anti-CD19 antibody, anti-CD2 antibody, anti-CD20 antibody, anti-CD45 antibody, anti-Kappa antibody and anti-Lambda antibody; The antibody composition is mixed in the same flow cytometry tube during detection; Among them, anti-kappa antibody and anti-CD8 antibody are labeled with FTIC, anti-Lambda antibody and anti-CD4 antibody are labeled with PE, anti-CD3 antibody is labeled with ECD, and anti-CD56 antibody is labeled with PerCP-Cy TM 5.5, anti-CD7 antibody labeled with PE-Cy7, anti-CD5 antibody and anti-CD34 antibody labeled with APC, anti-CD10 antibody labeled with APC Alexa Fluor 700, anti-CD19 antibody labeled with APC-Cy7 TM 7. Anti-CD2 antibody labeled Pacific Blue, anti-CD20 antibody labeled Briliant Violet 421, anti-CD45 antibody labeled SparkViolet TM 538.

2. A flow cytometry-based prediction system for lymphoma immunophenotyping, characterized by: The prediction system includes a data detection module and a data analysis module; Wherein, the detection module is used to detect the antigen expression of the cell fluid to be tested by flow cytometry, wherein the cell fluid to be tested comprises the sample to be tested, the hemolysin composition and the antibody composition described in claim 1; The data analysis module is used to analyze the detection results of the detection module and predict lymphoma immunophenotyping according to predetermined judgment criteria; The hemolysin composition includes OPtiLyse C reagent and FACS Lysing solution; The preparation process of the cell fluid to be tested comprises: mixing the antibody composition for lymphoma immunophenotyping based on flow cytometry with a sample to be tested, adding OPtiLyse C reagent, incubating at 18-25° C. in the dark for 2-3 minutes, adding FACSLysing solution, and incubating at 36-38° C. in the dark for 2-3 minutes to obtain the cell fluid to be tested; The sample to be tested is a peripheral blood sample.

3. The flow cytometry-based prediction system for lymphoma immunophenotyping according to claim 2, wherein: The lymphoma includes B-cell lymphoma, T-cell lymphoma or NK-cell lymphoma, and mixed lymphoma of any two of the three types of cells: B cells, T cells or NK cells.

4. The flow cytometry-based prediction system for lymphoma immunophenotyping according to claim 2, wherein: The data analysis module performs the following process: obtaining the result data of the data detection module, removing the adhesion and cell debris data, setting a gate with CD45-SS, and dividing the cell population into a granulocyte area, a monocyte area, a lymphocyte area, a CD45 weakly positive area, and a CD45 negative area according to the expression of CD45, circle the target cell population, and analyze the expression of B cells, T cells, NK cells, and different lymphocyte cross-lineage antigens within the lymphocyte gate.

5. The prediction system for lymphoma immunophenotyping based on flow cytometry according to claim 4, characterized in that: The analysis of the expression of B cells, T cells, NK cells and different lymphocyte cross-lineage antigens within the lymphocyte gate specifically includes the following: (1) Analyze B cells within the lymphocyte gate, including gating B cells using CD19-SS; Observe the CD45 weakly positive area or CD45 negative area, and combine the expression of CD34 and CD20-CD10 pattern to predict the probability of B lymphoblastic leukemia; and / or Observe the developmental trends of B progenitor cells and mature B cells, and based on the proportion of mature B cells in lymphocytes, predict the probability of B cell lymphoma; and / or Observe the expression of Kappa-Lambda light chain on the membrane of mature B cells to predict the probability of B cell lymphoma; (2) Analyze T cells and NK cells within the lymphocyte gate, including setting a gate based on CD3-SS to identify T cells and NK cells; Observe the CD45 weakly positive area or CD45 negative area, and combine it with the CD34 expression to predict the probability of T lymphoblastic leukemia; and / or Observe the CD4 / CD8 ratio in T cells within the logical lymphoid gate, whether pan-T cell antigen expression is abnormal, or whether there is abnormally elevated expression of a single antigen in T cells to predict the probability of T cell lymphoma; and / or Observe NK cells within the lymphocyte gate, including circling NK cells or T cells using CD3-CD19-, observe the ratio of NK cells to lymphocytes within the logical lymphocyte gate, and combine whether the expression of antigens including CD56, CD7, CD2 or CD5 is abnormal to predict the probability of NK cell lymphoma; (3) Based on the analysis results of the expression of B cells, T cells, NK cells and cross-lineage antigens in the above lymphocyte gate, the probability of mixed lymphoma of any two of the three types of cells, B cells, T cells or NK cells, is predicted.

6. The flow cytometry-based prediction system for lymphoma immunophenotyping according to claim 5, characterized in that: The B cells in the lymphocyte gate are analyzed, and when the ratio of Kappa / Lambda of the cell membrane light chain of the mature B cells does not fall within the range of 0.3 to 3.0 or when Kappa / Lambda is not expressed, the cells are determined to be abnormal mature B cells, and the probability of B cell lymphoma is predicted based on the ratio of the abnormal mature B cells; and / or further based on the expression of CD5 and CD10, the prediction result is output as any one of suspected CD5+CD10- type B cell lymphoma, CD5-CD10- type B cell lymphoma, CD5+CD10+ type B cell lymphoma or CD5-CD10+ type B cell lymphoma; and / or The analysis of T cells and NK cells within the lymphocyte gate predicts the probability of T cell lymphoma when the proportion of T cells in the logical lymphocyte gate to lymphocytes is greater than 70% or when the CD4 / CD8 ratio of T cells in the logical lymphocyte gate does not fall within the range of 0.5 to 3.0; and / or The analysis of T cells and NK cells within the lymphocyte gate, within the CD3-CD19- gate, CD4+ with abnormal expression of CD56, CD5, CD7 or CD2 antigens is determined to be abnormal T cells, and the probability of T cell lymphoma is predicted based on the proportion of the abnormal T cells; and / or The analysis of T cells and NK cells in the lymphocyte gate is performed. When the proportion of NK cells in the logical lymphocyte gate is greater than 40% of the lymphocytes, or CD4- in the CD3-CD19- gate is accompanied by abnormal expression of CD56, CD5, CD7 or CD2 antigens, the probability of T cell lymphoma or NK cell lymphoma is predicted.

7. The prediction system for lymphoma immunophenotyping based on flow cytometry according to claim 6, characterized in that: The analysis of the expression of cross-lineage antigens of different lymphocytes within the lymphocyte gate is performed by analyzing the expression of specific antibody pairs or antibody combinations within the logical lymphocyte gate, observing the cross-lineage expression between different lymphocytes, and outputting the prediction results of targeted subsequent screening; The specific antibody pairs or antibody combinations include (CD5+CD34)-CD10, CD3-CD10, CD7-CD10 or CD3-CD19 or CD19-CD7 or CD19-CD56.

Images