CN112630438B - Antibody composition and application thereof in screening myeloid diseases and detecting immune check points - Google Patents
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Abstract
The invention provides an antibody composition and application thereof in screening myeloid diseases and detecting immune check points. The antibody compositions include anti-CD 15 antibodies, anti-CD 96 antibodies, anti-CD 33 antibodies, anti-CD 34 antibodies, anti-CD 117 antibodies, anti-CD 9 antibodies, anti-CD 45 antibodies, anti-CD 38 antibodies, anti-HLA-DR antibodies, anti-CD 13 antibodies, anti-CD 19 antibodies, anti-CD 4 antibodies, anti-CD 36 antibodies, anti-CD 7 antibodies, anti-CD 371 antibodies, anti-CD 11c antibodies, anti-CD 11b antibodies, anti-CD 200 antibodies, anti-CD 14 antibodies, anti-CD 56 antibodies, anti-CD 71 antibodies, anti-CD 2 antibodies, anti-CD 123 antibodies, and anti-CD 64 antibodies. The antibody composition of the invention can be applied to screening of myeloid diseases and detection of immune checkpoints.
Description
Technical Field
The invention relates to an antibody composition and application thereof in screening myeloid diseases and detecting immune check points, in particular to a composition containing 24 antibodies and application thereof in revealing normal myeloid development, diagnosis of myeloid tumors, research of tumor stem cells, screening of target treatment targets, research of weak cell populations, immune function and detection of immune check points, and belongs to the technical field of detection of hematological diseases.
Background
Myeloid tumors are a group of complex diseases, and are classified into Myelodysplastic syndrome (MDS), myeloproliferative neoplasms (MPN), Myelodysplastic/proliferative neoplasms (MDS/MPN), Acute Myelogenous Leukemia (AML), and several myeloid tumors classified according to disease history and genetics, according to the proportion of primitive cells and the sub-lineage where malignant clones are involved, whether proliferation is dominant or morbid hematopoiesis is dominant, and even the cause and genetic factors of the disease. According to epidemiological statistics, the natural incidence rate of leukemia in China is 3/10-4/10 ten thousand, the incidence rate of other myeloid tumors is more than 10 ten-thousandth of 10 in total, and the incidence rate tends to rise gradually with the factors such as the life-span of people and environmental pollution. Acute Myelogenous Leukemia (AML) is a common hematological malignancy, accounting for 60% -70% of adult acute leukemias. At present, the complete remission rate of the adult AML is 60-85%, but the traditional chemotherapy and hematopoietic stem cell transplantation treatment still cannot obtain satisfactory long-term survival, and the growth of 5 years is about 30-40%. The remission rate and survival rate of other myeloid tumors such as MDS are worse, and the 5-year survival rate is only 10%. With the recent medical progress, there are some new strategies for diagnosis and treatment applied to AML. For example, some targeted small molecule drugs also achieve the effect of exciting people in clinical tests, and immunotherapy represented by Chimeric Antigen receptor T cells (CAR-T) and antibody drugs such as anti-CD 33 drug SGN-CD33A provides a brand-new idea for the treatment research of acute myeloid leukemia. However, despite the endless variety of new therapies, the efficacy has been so far limited and far less than that of cellular immunotherapy represented by CD19-CAR-T in lymphoid tumors, especially acute B-lymphoblastic leukemia. On the other hand, the sensitivity and specificity of detection of minimal residual disease in myeloid tumors is far superior to that of acute T-and B-lymphocyte leukemias due to their complexity, diversity of leukemia-associated immunophenotypes, low coverage of each abnormality, high probability of antigen change after treatment, and the like.
The immune check point is another new idea proposed in recent years, the mechanism is that the human body generates gene mutation and cell malignant change at any moment, and a patient who is relieved after treatment also has trace tumor cells which are difficult to detect by the prior art in vivo, but the immune cells of the body can effectively eliminate the abnormal cell factors. When the immune state of an organism changes, the onset, the development and the relapse of tumors can occur, the detection and the regulation of immune check points are favorable for deeply disclosing the occurrence and development mechanism of the tumors, and the treatment is combined with chemotherapy and targeted therapy by enhancing anti-tumor immunity and reducing immunosuppression, so that the treatment trend is widely seen at present. CD200, CD96 are novel immune checkpoint receptor targets recently proposed after PD1, TIGIT/CD96 forms a conduction pathway similar to the CD28/CTLA-4 pathway together with the co-stimulatory receptor CD226, although the role of TIGIT/CD96 as an immune checkpoint in T cell and NK cell biology has just begun to be recognized, CD96 has been previously reported to be a highly sensitive and specific MRD marker, and therefore incorporation into the protocol can simultaneously monitor CD96 expression of tumor cells as an MRD marker and CD96 expression of T, NK cells as an immune checkpoint marker. CD200-CD200R plays an important role in regulating the tumor microenvironment and is also an MRD indicator.
Tumor stem cells are the source of tumor recurrence, but are difficult to incorporate in conventional protocols because of the very low proportion. Furthermore, the myeloid lineage has many subpopulations, the weak subpopulations such as mast cells, basophils, eosinophils, dendritic cells, etc., which are low in proportion and require the recognition of multiple markers, are often overlooked, and the role of these cells in the pathogenesis of myeloid tumors needs to be further explored. Although the theory of tumor stem cells has been proposed thirty years ago, it has long been difficult for conventional methods to simultaneously monitor these low proportion of cell populations and thus difficult to incorporate into clinical assays.
There is therefore a great need for a complex technique that covers a full spectrum of markers, and in particular allows simultaneous monitoring of the expression and synergy of multiple cells.
Flow Cytometry (FCM) is a detection means capable of realizing quantitative analysis of a single cell, has the advantages of rapidness, high precision, multiple parameters and the like, and is one of the most advanced cell quantitative analysis methods at present. FCM plays more and more important roles in the fields of diagnostics and therapeutics, especially in recent years, CAR-T is taken as the representative of targeted therapy and immunotherapy, the theory of the interrelation of immunity and tumor is widely applied in the field of oncology, and at present, FCM is not only the gold standard of clinical diagnosis of malignant diseases such as leukemia, lymphoma and the like, but also is an indispensable or even unique technical means for deeply exploring mechanisms, searching new therapies and new theories and capable of quickly achieving the purpose.
According to the investigation, no scheme report related to the FCM technology for simultaneously detecting the myeloid tumor, the tumor stem cell, the weak cell population, the immune function and the immune check point exists at present.
Disclosure of Invention
It is an object of the present invention to provide a new technology for applying FCM to tumor and immunity simultaneously.
One aspect of the invention provides an antibody composition comprising the following antibodies:
The antibody composition can be applied to screening of myeloid diseases and detection of immune check points by flow cytometry.
In the present invention, the screening for myeloid disorders and detecting immune checkpoints include, unless otherwise specified: revealing normal medullary development, medullary tumor diagnosis, tumor stem cell research, weak cell group research, target treatment target screening, immune function detection and immune check point detection.
According to a particular embodiment of the invention, in the antibody composition of the invention, each antibody is a monoclonal antibody.
According to a particular embodiment of the invention, in the antibody composition of the invention, each antibody is a fluorescein-labeled antibody. Preferably, the fluorescein labels of the anti-CD 15 antibody, anti-CD 96 antibody, anti-CD 33 antibody, anti-CD 34 antibody, anti-CD 117 antibody, anti-CD 9 antibody, anti-CD 45 antibody, anti-CD 38 antibody, anti-HLA-DR antibody, anti-CD 13 antibody, anti-CD 19 antibody, anti-CD 4 antibody, anti-CD 36 antibody, anti-CD 7 antibody, anti-CD 371 antibody, anti-CD 11c antibody, anti-CD 11b antibody, anti-CD 200 antibody, anti-CD 14 antibody, anti-CD 56 antibody, anti-CD 71 antibody, anti-CD 2 antibody, anti-CD 123 antibody, anti-CD 64 antibody are, in the order: FITC, PE-Dazle 594, PE-Cy7, PE-Cy5, PerCP-Cy5.5, PerCP-eFluor, APC-Cy7, BV421, AF532, BV605, BV480, BB515, AF700, BV570, AF647, Pacific Blue, BV750, BV650, BV510, BV785, BV 711. According to the invention, by matching different antibodies with specific fluorescein, all the fluorescein in each channel can achieve excellent dyeing effect when the antibody composition is applied to screening of myeloid diseases and detection of immune check points by flow cytometry.
According to a particular embodiment of the invention, each antibody component of the antibody composition of the invention is commercially available. Each antibody should meet relevant industry standard requirements.
According to a particular embodiment of the invention, the antibody composition of the invention is a mixture of anti-CD 15 antibodies, anti-CD 96 antibodies, anti-CD 33 antibodies, anti-CD 34 antibodies, anti-CD 117 antibodies, anti-CD 9 antibodies, anti-CD 45 antibodies, anti-CD 38 antibodies, anti-HLA-DR antibodies, anti-CD 13 antibodies, anti-CD 19 antibodies, anti-CD 4 antibodies, anti-CD 36 antibodies, anti-CD 7 antibodies, anti-CD 371 antibodies, anti-CD 11c antibodies, anti-CD 11b antibodies, anti-CD 200 antibodies, anti-CD 14 antibodies, anti-CD 56 antibodies, anti-CD 71 antibodies, anti-CD 2 antibodies, anti-CD 123 antibodies, anti-CD 64 antibodies mixed (at substantially equivalent titers) according to the following volume ratios:
the anti-CD 15 antibody 1 which is,
the anti-CD 96 antibody 2.5,
the anti-CD 33 antibody 5, which is,
the anti-CD 34 antibody 3.5,
an anti-CD 117 antibody 1.5,
the anti-CD 9 antibody 7, which is,
the anti-CD 45 antibody 20 which is,
the anti-CD 38 antibody 1.5,
an anti-HLA-DR antibody 1 which is a human antibody,
(ii) an anti-CD 13 antibody 2,
the anti-CD 19 antibody 1 which is,
the anti-CD 4 antibody 3, which is,
0.5 of the anti-CD 36 antibody,
the anti-CD 7 antibody 1.5,
the anti-CD 371 antibody 0.3,
the anti-CD 11c antibody 5,
the anti-CD 11b antibody 1,
(ii) an anti-CD 200 antibody 5,
the anti-CD 14 antibody 1 which is,
the anti-CD 56 antibody 2.5,
0.25 of the anti-CD 71 antibody,
the anti-CD 2 antibody 1.5,
(ii) an anti-CD 123 antibody 2,
anti-CD 64 antibody 1.5.
In another aspect of the invention, a kit is provided that includes a first container containing an antibody composition of the invention. The kit can be applied to screening of myeloid diseases and detection of immune check points by flow cytometry.
According to a specific embodiment of the present invention, the kit of the present invention may further comprise other reagents and consumables for screening myeloid disorders and detecting immune checkpoints for use in flow cytometry, for example, may further comprise: one or more of a lysate of red blood cells, a buffer solution, and a flow tube used in conjunction with a flow cytometer. These reagents and consumables are commercially available. Preferably, the kit provided by the invention further comprises a second container, a third container and the like which are respectively used for accommodating erythrocyte lysate, buffer solution and the like.
The invention also provides application of the antibody composition provided by the invention in preparation of a kit for revealing normal myeloid development, diagnosis of myeloid tumors, research of tumor stem cells, target therapy target screening, weak cell population research, immune function detection and immune check point detection.
Preferably, in the application of the invention, the processes of revealing normal myeloid development, myeloid tumor diagnosis, tumor stem cell research, target therapy target screening, vulnerable cell group research, immune function detection and immune checkpoint detection comprise:
(1) adding the sample to be detected into the flow tube to make the sample be in a single cell suspension state and ensure that the cell amount is 1 multiplied by 106pipe-1X 107A pipe; the sample to be detected is bone marrow or peripheral blood;
(2) uniformly mixing the sample obtained by the step (1) with the antibody composition, and incubating at room temperature in a dark place;
(3) adding 1 Xhemolysin into the flow tube incubated in the step (2), and incubating at room temperature in a dark place;
(4) centrifuging the flow tube incubated in the step (3) to remove supernatant;
(5) adding PBS buffer solution into the flow tube in the step (4), mixing uniformly, centrifuging to remove supernatant, and resuspending cells by using the PBS buffer solution;
(6) and (5) carrying out flow cytometry detection on the resuspended cells in the step (5), and analyzing the result.
According to a particular embodiment of the invention, the reagents other than the antibody composition of the invention may be used in amounts conventionally used in the art or in accordance with the recommendations of the manufacturer.
According to a particular embodiment of the invention, the antibody composition of the invention is added in an amount of 50-100. mu.l/tube.
According to a particular embodiment of the invention, in step (1), the volume of the sample volume per tube does not generally exceed 160. mu.l.
According to a particular embodiment of the invention, in step (2), the incubation is carried out for 10 to 30 minutes.
According to a particular embodiment of the invention, in step (3), the incubation is carried out for 5 to 20 minutes.
According to an embodiment of the present invention, in step (4), the centrifugation conditions may be 300-450g for 5-10 minutes.
According to a specific embodiment of the present invention, in step (4), the amount of PBS buffer (for washing) added before centrifugation is 2-3 ml/tube, and the amount of PBS buffer for resuspension is 0.5-1 ml/tube.
In another aspect of the present invention, there is provided a device for revealing normal myeloid development, myeloid tumor diagnosis, tumor stem cell research, targeted therapy target screening, vulnerable cell population research, immune function detection, immune checkpoint detection, the device comprising a detection unit and an analysis unit, wherein:
the detection unit comprises a reagent material for detecting a bone marrow or peripheral blood sample of an individual to be detected by flow cytometry, and a detection result of the sample is obtained; the reagent material comprises an antibody composition of the invention;
the analysis unit is used for analyzing the detection result of the detection unit.
According to the embodiment of the invention, in the device for revealing normal myeloid development, myeloid tumor diagnosis, tumor stem cell research, target therapy target screening, vulnerable cell group research, immune function detection and immune checkpoint detection, the process of detecting a sample from an individual to be detected by flow cytometry comprises the following steps:
after the antibody composition is used for processing a sample to be detected, a flow cytometry sample is prepared (the specific processing process can refer to the above record); and (5) performing flow cytometry detection.
According to the specific embodiment of the invention, the device for revealing normal medullary development, medullary tumor diagnosis, tumor stem cell research, targeted therapy target screening, weak cell population research, immune function detection and immune check point detection is provided, wherein the flow cytometry is subjected to on-machine detection by setting the gate analysis according to the following modes:
setting a P1 gate to remove adherent cells;
setting a living cell gate P2 as a cell in the P1 gate;
and (3) carrying out multiple gating simultaneously in a single living cell gate P2, and detecting the expression conditions of multiple groups of cells:
in a P2 gate, CD45/SSC is gated to detect lymphocytes, monocytes, granulocytes at the differentiation stage, nucleated erythrocytes and eosinophils;
setting immature myeloid cell gate by using CD117/SSC and CD34/SSC in P2 gate, and detecting and analyzing differentiation process of myeloid series immature cells;
p2 in-gate detection of the vulnerable cell population: setting an HLA-DR/CD123 two-dimensional dot diagram to detect plasmacytoid dendritic cells and basophils, setting a CD117/SSC two-dimensional dot diagram to detect mast cells, setting a CD45/SSC two-dimensional dot diagram to detect eosinophils, setting a CD13/CD11c two-dimensional dot diagram and detecting the plasmacytoid dendritic cells by combining with the HLA-DR;
in a P2 gate, a CD19/SSC is provided with a B cell gate, and the development of B cells is detected;
within the P2 gate, the T cell and NK cell gates were set using CD 7/SSC; the following assays were performed in the CD7 positive T cells and NK cells: detecting the expression of CD56 to detect regulatory NK cells, killer NK cells and T cells; the CD56-/CD7+ T cell gates were tested in addition: detecting CD4 expression to detect CD4+ T cell, CD4-T cell and activated T cell;
wherein the selectivity during the flow cytometry on-machine detection further comprises: performing an examination of a sample of two or more individuals to screen for potential target therapy targets of immune checkpoints and/or myeloid tumors; wherein:
screening immune checkpoints includes: the P2 gate CD117/SSC gate or CD117 negative tumor uses CD34/SSC gate to detect medullary primitive cells, and CD7/SSC gate to detect T cells and NK cell gate to detect NK cells and CD96 and CD200 expression of T cells in the P2 gate, and screening immune check points;
screening for potential target treatment targets of myeloid tumors includes: CD117/SSC gating or CD117 negative tumors in a P2 gate uses CD34/SSC gating to detect the expression of myeloid tumor cells, counts the probability of the occurrence of malignant expression markers, and screens the potential target of targeted therapy of the myeloid tumors.
In some embodiments of the invention, the device for revealing normal myeloid development, myeloid tumor diagnosis, tumor stem cell research, targeted therapy target screening, vulnerable cell population research, immune function detection, immune checkpoint detection of the present invention, wherein the flow cytometric on-line detection is gated as follows:
(1) setting a P1 gate to remove adherent cells;
(2) setting a viable cell gate (P2 gate) for the cell in the P1 gate;
(3) the expression of multiple groups of cells was detected by multiple gating simultaneously in the single viable cell gate (gate P2):
setting a door of CD45/SSC in a P2 door, wherein lymphocytes (lym), monocytes (mono), granulocytes at a differentiation stage (gra), nucleated erythrocytes (P14) and eosinophils (eo) are arranged in the door; markers expressed by each of the above populations of cells can be detected.
Setting immature myeloid cell gate by using CD117/SSC and CD34/SSC in P2 gate, and detecting the differentiation process of the juvenile cells of the myeloid lineage; the MRD mainly comprises two methods for scheme design and result judgment: leukemia Associated Immunophenotyping (LAIP), a marker that is not normally expressed or that is normally expressed by a tumor cell is lost; compared with Normal differential expression (Di ff energy-from Normal, DFN), the process can design a reasonable scheme to make several Normal expression antigens form a development pattern, and if the expression intensity or composition pattern of the antigens in the sample to be tested is changed compared with the cells at the Normal stage, the antigens are DFN. In the present invention, the determination may be specifically performed in at least one of the following ways:
in case of myeloid tumor, the detection and analysis of possible abnormalities of malignant myeloid progenitor cells: such as common chaperone expression (i.e., malignant myeloid naive cells express lymphoid markers that should not be normally expressed: CD7, CD56, CD19, CD2, CD9, CD4, etc., which are common AML fleeing line expression markers), early markers coexpressed with differentiation markers at different phases (myeloid cells follow a specific rule in their development from primitive to mature stages, express specific markers at a certain stage, disappear the development stage markers to appear and reach a certain intensity as they mature during development, if the relationship is disturbed, suggesting malignancy, such as early markers CD34, CD117 coexpressed with development and maturation stage markers such as CD15, CD11b, CD64, CD11c, CD14, CD36, etc.), fluorescence intensity change of normal myeloid primitive cell expression markers, and the corresponding combined development pattern change (normal myeloid cells express markers at various stages such as CD45, CD117, CD34, CD33, CD13, DR-HLA-13, etc.) CD38, CD123, CD200, CD371, CD71, etc., not only have normal sequence but also have sequence changes in intensity, and myeloid tumors often show changes in the intensity of normally expressed markers, such as enhancement, attenuation or loss, resulting in the combination in the CD117 positive cell gate: CD34/CD117, CD34/CD33, CD33/CD13, CD34/CD13, CD34/CD38, CD34/CD123, CD34/HLA-DR, CD34/CD371, CD34/CD200 and other two-pair markers constitute a development mode change), other abnormal markers (for example, the normal medullary original cell does not express CD96, and the obtained marker is abnormal) and the like.
In the combination of the above assays, CD38-/CD34+ is the earliest myeloid stem cell, and the population of cells is normally myeloid stem cells, and in the case of myeloid tumors, it is likely to be tumor stem cells. The ratio, although low, may be the source of tumor recurrence and therefore needs to be considered.
P2 in-gate detection of the following disadvantaged clones:
setting a two-dimensional dot diagram of HLA-DR/CD123, wherein the cell group of HLA-DR +/CD123bri is Plasmacytoid Dendritic Cells (PDC), and the cell group of HLA-DR/CD123 bri is basophil (basophil).
In the CD117/SSC two-dimensional dot diagram, the CD117bri is a mast cell.
In the CD45/SSC two-dimensional dot plot, CD45bri/SSC was large and eosinophilic (eosinophil, eo).
A two-dimensional dot plot of CD13/CD11c was set, and both markers were strongly expressed, were positive for binding to HLA-DR, and were judged as Myeloid Dendritic Cells (MDC).
And fourthly, within a P2 gate, setting a B cell gate for CD19/SSC, detecting the development of the B cell, wherein the weakly expressed CD9/CD38/CD45 in the B cell gate is an early B cell, and according to a certain rule of the normal B cell from larval to mature, the expression of CD45 and CD19 is gradually enhanced, the synchronous attenuation of CD9 and CD38 disappears, and the continuous process that SSC is firstly reduced and then increased can roughly judge whether the normally proliferated B progenitor cell exists or the malignant larval B cell clone exists. Although most tumors are one lineage, <5% of acute leukemias are mixed leukemias, and furthermore, chronic myeloid leukemia may also be accelerated in the accelerated acute phase as in the B lineage. While normally proliferating B-lineage progenitor cells are a good marker of myeloproliferation, and myelogenous tumors such as myelodysplastic syndrome and the like may have B-lineage progenitor cell depletion due to myeloproliferation inhibition.
In P2 gate, setting T and NK cell gate by CD7/SSC, and in the positive T and NK cell gate of CD7, making the following differentiation:
the expression of CD56 was observed in three populations of cells: CD56 bri-regulating NK cells; CD56dim killer NK cells; CD56-/CD7+ is a T cell.
Within the CD56-/CD7+ T cell gate, the following differentiation was performed: CD56-CD7+ T cells can be further differentiated into CD4+ T cells and CD4- (mainly CD8 +) T cells according to CD4 expression; in the T cell gate of CD56-/CD7+, the expression of CD38+/HLA-DR + is an activated T cell.
(4) Following individual detection, a co-detection analysis of two or more individual (or population) samples is performed: screening the statistics of the immune check points and targets of potential target treatment of the myeloid tumor.
Detection of immune checkpoints: the expression of CD96 and CD200 was examined in myeloid progenitor cells gated with CD117/SSC (CD 34/SSC was used for CD 117-negative tumors) and in (3) NK and T cells of the fifth group. In some embodiments of the invention, 22 normal specimens and 42 myeloid tumor specimens were studied and found to have CD96 as an immune checkpoint, and the expression of various cell populations was different in myeloid tumor patient specimens compared to normal specimens: the expression of killer NK cells CD96 of CD56dim is enhanced, the expression of regulatory NK cells CD96 of CD56bri is weakened, and the expression of CD96 of malignant myeloid progenitor cells is significantly different (P values are 0.007, 0.023 and 0.000 respectively). CD200 acts as an immune checkpoint and in myeloid tumor specimens, there are differences in expression of various cell populations compared to normal specimens: t cells, CD4+ T cells, CD38+/HLA-DR + activated T cells, CD56 weakly-expressed killer NK cells, CD56 strongly-expressed regulatory NK cells, and malignant myeloid progenitor cells, wherein the CD200 expression of the cell populations is obviously enhanced and has significant difference (P values are 0.000, 0.000, 0.000, 0.000, 0.020 and 0.000 respectively).
Screening of potential targets for targeted therapy: in the process of detecting the expression of the myeloid tumor of each patient by using the (3) above, namely, CD117/SSC (using CD34/SSC in the case of CD117 negative tumor), all the detected patients are counted, if a certain malignant expression marker is found to have high probability of appearing in the patients with the myeloid tumor (see CD117 positive tumor cells, if CD117 negative is locked by CD34 or other markers), and normal cells are rarely expressed and important cells are not expressed (obtained by the expression of all blood cell populations analyzed by CD45/SSC gating detection in P2 gate in (3) — the marker is most hopeful to be a potential target of the targeted therapy of the myeloid tumor. In the course of the present invention, among all patients tested, the markers with high probability of expressing myeloid tumors include CD13 (90%), CD33 (98%), CD34 (90%), CD117 (96%), CD38 (100%), HLA-DR (85%), and CD371 (84%), but only CD38, CD34, and CD117 are rarely expressed in other cells, and in terms of importance, CD34 and CD117 cover all early myeloid cells, while CD38 has early CD38 negative cells, so CD38 is the most promising marker for myeloid-targeted therapy selected in this study.
The technology of the invention can realize that: (1) the development patterns of various subgroups of the myeloid series are detected and analyzed in detail. Including granulocytes at the differentiation stage, monocytes, nucleated erythrocytes, myeloid progenitor cells. (2) The myeloid progenitor cells also include tens of combinations of detailed differentiation and expression patterns. (3) And simultaneously detecting and analyzing the marrow stem cells. Normal stem progenitor cells and tumor stem cells are detected simultaneously. (4) And simultaneously detecting and analyzing various weak cell populations to research the role of the weak cell populations in tumorigenesis and development. (5) Simultaneously, the immune function, lymphocyte subset and B cell development are researched. (6) Screening for promising target therapeutic targets. (7) Immune checkpoint detection is performed simultaneously, combining tumor and immunity.
In conclusion, the invention combines the research of normal development mode of the medullary system, tumor monitoring, target screening, tumor stem cell research, immune check points, lymphocyte subsets and medullary system weak cell populations, provides a set of perfect 24-color FCM solution, deeply researches normal medullary system development, thereby more sensitively and specifically discovering abnormality, accurately diagnosing, guiding treatment, detecting and following-up curative effect of Minimal Residual Disease (MRD), screening promising target points and tumor stem cells of targeted treatment, simultaneously exploring correlation between immune function and immune check point and tumor, if the method is widely popularized, the method is expected to simultaneously solve a plurality of problems which puzzle the blood field and the drug research and development field for a long time, and has a profound influence on overcoming the tumor with the highest incidence rate and the highest treatment and monitoring difficulty of the medullary tumor and improving the overall survival rate of the medullary tumor.
Drawings
FIGS. 1A and 1B show normal bone marrow specimens analyzed by the spectroflow software for multiple marker combination assays, normal myeloid development with 24 antigens, and expression of various antigens by major cell populations.
FIG. 2 shows normal bone marrow specimens analyzed for normal myeloid development using the spectroflow software for analysis of multiple marker combination assays. Wherein, the picture A is the development mode of the whole medullary system, the picture B is the development mode of the differentiation stage granulocyte, the picture C is the development mode of the monocyte, and the picture D is the expression condition of the nucleated erythrocyte.
FIGS. 3A, 3B and 3C show the analysis of differentiation patterns of naive cells of normal myeloid lineage using a spectroflow software to analyze the multiple marker combination assay. Wherein the immature myeloid cell gate is set by using CD117/SSC and CD34/SSC, and the differentiation process of the normal myeloid series naive cells is analyzed by using tens combination detection.
FIGS. 4A, 4B and 4C show myeloid tumor specimens (MRD assay after AML treatment) analyzed malignant myeloid naive cell differentiation patterns using the spectroflow software to analyze multiple marker combination assays.
FIG. 5 shows analysis of normal and malignant myeloid stem cells using the kaluza software assay. Among them, panel A shows the normal control of CD38-/CD34+ earliest myeloid stem cells, which have a low distribution in the primitive phylum. Panel B shows a specimen of a patient with myeloid tumor, in which the malignant myeloid naive cells have slightly increased tumor stem cells CD38-/CD34 +.
FIGS. 6A and 6B show that normal bone marrow specimens were examined for routine rare attention weak cell populations using the spectroflow software to analyze various marker combinations.
FIG. 7 shows the analysis of lymphocyte immune function assay using kaluza software on normal bone marrow specimen.
FIG. 8 shows detection of immune checkpoints by kaluza software. Wherein, the pictures A-F are normal marrow specimens, and the pictures G-L are myeloid tumor (AML MRD) specimens.
Figure 9 shows the difference in expression of the cellular immune checkpoint CD96 in each population of normal and myeloid tumor patients.
Figure 10 shows the difference in expression of the cellular immune checkpoint CD200 in each population of normal and myeloid tumor patients.
FIGS. 11A and 11B show the multidimensional assay of normal bone marrow specimens using flowjo and kaluza software to analyze myeloid progenitor cell expression.
Detailed Description
The technical solutions of the present invention will be described in detail below in order to clearly understand the technical features, objects, and advantages of the present invention, but the present invention is not limited to the practical scope of the present invention.
EXAMPLE 1 formulation of reagents
The antibody combinations used in this example were:
anti-CD 15-FITC antibody, anti-CD 96-PE antibody, anti-CD 33-PE-Dazle 594 antibody, anti-CD 34-PE-Cyanine7 antibody, anti-CD 117-PE-Cy5 antibody, anti-CD 9-PerCP-Cy5.5 antibody, anti-CD 45-PerCP antibody, anti-CD 38-PerCP-eFluor710 antibody, anti-HLA-DR-APC antibody, anti-CD 13-APC-Cy7 antibody, anti-CD 19-BV421 antibody, anti-CD 4-AF532 antibody, an anti-CD 36-BV605 antibody, an anti-CD 7-BV480 antibody, an anti-CD 371-BB515 antibody, an anti-CD 11c-AF700 antibody, an anti-CD 11b-BV570 antibody, an anti-CD 200-AF647 antibody, an anti-CD 14-Pacific Blue antibody, an anti-CD 56-BV750 antibody, an anti-CD 71-BV650 antibody, an anti-CD 2-BV510 antibody, an anti-CD 123-BV785 antibody, an anti-CD 64-BV711 antibody, and 24 of the above monoclonal antibody reagents were mixed in the volume ratios described in Table 1 and packaged in a first container.
The antibodies in this example are commercially available, wherein CD15-FITC, CD96-PE, CD9-PerCP-Cy5.5, CD45-PerCP, HLA-DR-APC, CD19-BV421, CD36-BV605, CD371-BB515, CD7-BV480 are products of Becton Dickinson, USA; CD 33-PE/Dazle 594, CD34-PE/Cyanine7, CD117-PE-Cy5, CD11c-AF700, CD11b-BV570, CD200-AF647, CD14-Pacific Blue, CD56-BV750, CD71-BV650, CD2-BV510, CD123-BV785 and CD64-BV711 are antibodies from Biolegend corporation, USA; CD38-PerCP-eFluor710 and CD4-AF532 are products of eBioscience, Inc. in USA; CD13-APC-Cy7 is a product of Sizheng cypress in China.
And (3) optionally adding a red blood cell lysate into a second container, adding a PBS buffer solution into a third container, wherein the red blood cell lysate and the PBS buffer solution are commercially available, the cell lysate is a product of Becton Dickinson company in the United states, and the PBS buffer solution is a product of Beckman Coulter company.
EXAMPLE 2 treatment of specimens
According to the cell counting result, heparin or EDTA anticoagulated bone marrow sample is added into the flow tube 1 to ensure that the added cell amount is about 2X 106Adding 24 cell membrane monoclonal antibody reagents marked by different fluorescein into a flow tube according to the table 1, fully mixing the reagents with cell suspension, incubating the mixture for 15 minutes at normal temperature in the dark, adding 3ml of 1 Xhemolysin, incubating the mixture for 10 minutes in the dark to crack red blood cells, centrifuging the mixture at 1500rpm for 5 minutes to remove supernatant, adding 3ml of PBS buffer solution to wash the mixture, removing the supernatant after centrifugation, and resuspending the cells by using 0.5ml of PBS buffer solution to obtain a processed sample which can be used for machine inspectionAnd (6) measuring.
TABLE 1 antibody mixtures and amounts
EXAMPLE 3 detection and analysis of samples
The samples processed in example 2 were tested on a 3-channel laser 38-channel flow cytometer (cytek, inc., usa) to obtain 10 ten thousand cells per tube, and then the data were analyzed using various flow software: spectroflow, flowjo, kaluza.
The flow cytometry detection analysis process comprises the use of a two-dimensional point diagram and a dimension reduction diagram.
Two-dimensional dot diagram analysis process and detection analysis index:
(1) a P1 gate was set using forward scatter Area (FSC-A) and forward scatter height (FSC-H) to remove adherent cells, with individual cells within the P1 gate.
(2) Cells in P1 Gate A Living cell Gate (P2 Gate) was set using FSC-A and side scatter area (SSC-A).
(3) Cells within the P2 gate were analyzed while the following gating was performed:
in P2 gate, CD45/SSC gate set lymphocyte (lym), monocyte (mono), differentiation stage granulocyte (gra), nucleated erythrocyte (P14), eosinophil (eo) gate, detection analysis of the above groups of cell expression markers. The normal case detection analyzes the differentiation patterns of granulocytes, monocytes and nucleated erythrocytes, and the myeloid tumor may have abnormal differentiation patterns of one or more of the above three cell populations and abnormal expression of other detection markers. CD38bri is plasma cell, CD45-/CD71bri/CD36+ is nucleated red blood cell.
Setting a marrow-line naive cell gate by using CD117/SSC and CD34/SSC in the P2 gate, and detecting and analyzing the differentiation process of normal marrow-line naive cells; in the case of myeloid tumors, various possible abnormalities of malignant myeloid naive cells are detected and analyzed: CD34/CD117 relationship, abnormal expression of lymphoid lineage markers, abnormal expression of maturation stage markers, abnormal acquisition of normal expression markers, normal expression of markers fluorescence intensity changes and associated combined expression pattern changes, these are the diagnosis of myeloid tumors and MRD monitoring. More specifically, the expression of the common chaperones (i.e., malignant myeloid naive cells express the lymphoid markers that should not be expressed normally: CD7, CD56, CD19, CD2, CD9, CD4, etc., which are common AML fleeing line expression markers), the coexpression of the early markers and the differentiation markers at different phases (the developmental process of myeloid cells from the primary to the mature stage follows a specific rule, a certain stage expresses specific markers, and as the cells mature, the early markers disappear from the developmental stage and reach a certain intensity, if the relationship is disturbed, it indicates malignancy, such as the early markers CD34, CD117, coexpression of the developmental and mature stage markers, such as CD15, CD11b, CD64, CD11c, CD14, CD36, etc.), the fluorescence intensity of the expression markers of the normal myeloid primary cells is changed, and the corresponding combined developmental pattern is changed (the expression markers of the normal myeloid cells at various stages, such as CD45, CD117, CD34, CD 35, CD13, HLA-3683, CD33, and the corresponding combined developmental pattern is changed, CD38, CD123, CD200, CD371, CD71, etc., not only have normal sequence but also have sequence changes in intensity, and myeloid tumors often show changes in the intensity of normally expressed markers, such as enhancement, attenuation or loss, resulting in the combination in the CD117 positive cell gate: CD34/CD117, CD34/CD33, CD33/CD13, CD34/CD13, CD34/CD38, CD34/CD123, CD34/HLA-DR, CD34/CD371, CD34/CD200 and other two-pair markers constitute a development mode change), other abnormal markers (for example, the normal medullary original cell does not express CD96, and the obtained marker is abnormal) and the like.
Meanwhile, in a marrow-line naive cell gate obtained by setting a gate for analyzing CD117/SSC, CD38-/CD34+ is the earliest marrow-line stem cell, and a marrow-line primary cell CD38-/CD34+ of a marrow-line tumor patient is often a tumor stem cell.
③ detection of a population of normal, rarely noticed, weak cells within a single living cell (P2) door at the same time:
setting a two-dimensional dot diagram of HLA-DR/CD123, wherein the cell group of HLA-DR +/CD123bri is Plasmacytoid Dendritic Cells (PDC), and the cell group of HLA-DR/CD123 bri is basophil (basophil).
In the CD117/SSC two-dimensional dot diagram, the CD117bri is a mast cell.
In the CD45/SSC two-dimensional dot plot, CD45bri/SSC was large and eosinophilic (eosinophil, eo).
In the CD13/CD11c two-dimensional dot-plot, both markers were strongly expressed and bound to HLA-DR to positively judge Myeloid Dendritic Cells (MDC).
And fourthly, within a P2 gate, setting a B cell gate for CD19/SSC, detecting the development of the B cell, wherein the weakly expressed CD9/CD38/CD45 in the B cell gate is an early B cell, and according to a certain rule of the normal B cell from larval to mature, the expression of CD45 and CD19 is gradually enhanced, the synchronous attenuation of CD9 and CD38 disappears, and the continuous process that SSC is firstly reduced and then increased can roughly judge whether the normally proliferated B progenitor cell exists or the malignant larval B cell clone exists. Although most tumors are one lineage, <5% of acute leukemias are mixed leukemias, and furthermore, chronic myeloid leukemia may also be accelerated in the accelerated acute phase as in the B lineage. While normally proliferating B-lineage progenitor cells are a good marker of myeloproliferation, and myelogenous tumors such as myelodysplastic syndrome and the like may have B-lineage progenitor cell depletion due to myeloproliferation inhibition.
In P2 gate, setting T and NK cell gate by CD7/SSC, and in the positive T and NK cell gate of CD7, making the following differentiation:
the expression of CD56 was observed in three populations of cells: CD56 bri-regulating NK cells; CD56dim killer NK cells; CD56-/CD7+ is a T cell.
Within the CD56-/CD7+ T cell gate, the following differentiation was performed: CD56-CD7+ T cells can be further differentiated into CD4+ T cells and CD4- (mainly CD8 +) T cells according to CD4 expression; in the T cell gate of CD56-/CD7+, the expression of CD38+/HLA-DR + is an activated T cell.
(4) Following individual detection analysis, a common detection analysis is performed for two or more individuals (or populations): statistics of immune checkpoints and target screening for potential targeted therapy of myeloid tumors.
Detection of immune checkpoints: detecting and analyzing the expression of CD96 and CD200 of myeloid primitive cells gated by CD117/SSC (CD 34/SSC is used for CD117 negative tumors) in (3) and NK and T cells in (3) the fifth group.
Screening of potential targets for targeted therapy: in the process of detecting the expression of the myeloid tumor of each patient by using the (3) above, namely, CD117/SSC (using CD34/SSC in the case of CD117 negative tumor), all the detected patients are counted, if a certain malignant expression marker is found to have high probability of appearing in the patients with the myeloid tumor (see CD117 positive tumor cells, if CD117 negative is locked by CD34 or other markers), and normal cells are rarely expressed and important cells are not expressed (obtained by the expression of all blood cell populations analyzed by CD45/SSC gating detection in P2 gate in (3) — the marker is most hopeful to be a potential target of the targeted therapy of the myeloid tumor.
In the analysis process, the criteria for judging the abnormal myeloid lineage can be seen in table 2.
TABLE 2 criteria for judging abnormalities in the medullary system
Attention is paid to: go on according to 2017 version WHO or other professional diagnostic criteria (such as consensus promulgated by the european leukemia working group in 2012); ② marrow cell activation can occur in infected and stressed marrow, which shows that marrow lineage primitive, granulocyte and monocyte can all have CD56 expression up-regulation, so need to combine clinical manifestations, including and paying attention to normal value and background; ③ the pattern change comprises the change of the distribution of the developmental stages and/or the change of the antigen expression level; because hemolysin affects red blood cells, the erythroid proportion may be underestimated; the following factors affect the judgment of granulocytes, such as dilution of the specimen, improper preparation and storage of the specimen (reduced expression of CD11b during apoptosis), genetic polymorphism, and other diseases (loss of expression of CD14 in abnormal clones during nocturnal paroxysmal nocturnal hemoglobinuria).
The detection of myeloid naive cells is the key point of diagnosis and post-treatment monitoring of myeloid tumors: the immature myeloid cell gate is set by using CD117/SSC and CD34/SSC conventionally, and the proportion, the differentiation process and the abnormal expression of the normal myeloid series naive cells are detected and analyzed. If the proportion of juvenile cells of the marrow line is obviously increased, the method is an extremely important basis for judging the marrow-line tumor, the tumor rarely occurs more than 5 percent under the normal condition, but the proportion of primitive cells of the marrow line is increased after infection, chemotherapy and G-CSF stimulation, but under the conditions, the differentiation mode is normal and continuous. 5-10% of myeloid tumors do not express CD34 and CD117, as judged with the aid of CD 45/HLA-DR.
In the marrow-line naive phylum, attention was paid to the detection and analysis of early stem cells: the earliest marrow stem cell of CD38-/CD34+, and the marrow primary cell CD38-/CD34+ is usually tumor stem cell. It has been widely accepted by researchers for many years that tumor stem cells are the source of tumor recurrence.
Target screening for targeted therapy: in the process of detecting the expression of the myeloid tumor, the marker which has high occurrence probability of tumor cells, less expression of normal cells and no expression of important cells is the most hopeful potential target for the target therapy of the myeloid tumor. Combining positive rate and normal cell expression, the study of the present invention can find that CD38 is a relatively ideal target. Other markers, including CD371, CD117, CD33, CD96 and CD123 in the current international clinical trials, have large potential side effects due to factors such as low coverage rate, excessive normal expression cells or important cell expression, and the like, and prospective prediction may cause various problems in clinical use.
The positive rate of antigen expression during the assay is shown in Table 3.
TABLE 3 Positive rate of antigen expression
While detecting the normal rare-paying weak cell population: plasmacytoid dendritic cells, basophils, mast cells, eosinophils, myeloid dendritic cells. The simultaneous detection of B cells and plasma cells, and the judgment of the existence of malignant B-lineage clones accompanied at the same time, and the reduction or absence of B progenitor cells are also one of the auxiliary judgment indexes of myeloid tumors such as MDS.
Monitoring of immune checkpoints was performed simultaneously: the scheme of the invention can distinguish the lymphocytes in detail, can simultaneously monitor the immune state represented by the lymphocyte subpopulation and can monitor the expression conditions of immune check points of original cells and various lymphocyte populations. Comparing the difference between normal and tumor patients, it is likely to be an important basis for auxiliary diagnosis, prognosis, treatment guidance and immune regulation.
FIGS. 1A to 11B show a part of an example and a control example of a specimen to be detected by the method of the present embodiment.
Fig. 1A and 1B: normal bone marrow samples were analyzed for normal myeloid development and expression of major cell populations using the spectroflow software for analysis of multiple marker combination assays. FSC-A/FSC-H set P1 gate to remove adherent cells. Cells in the P1 Gate set the viable cell gate (P2 gate) using FSC-A/SSC-A. The cells in the P2 gate were analyzed, and the SSC-A/CD45 gates were set to provide the gates of lymphocyte (lym), monocyte (mono), differentiation stage granulocyte (gra), nucleated red blood cell (P14), and eosinophil (eo). The expression of 24 antigens from the main cell population in normal bone marrow samples was studied.
FIG. 2: and (3) analyzing the normal myeloid specimen by using a spectroflow software to analyze the combination of multiple markers for detecting and analyzing normal myeloid development, wherein a picture A is a development mode of the whole myeloid, a picture B is a differentiation stage granulocyte development mode, a picture C is a monocyte development mode, and a picture D is the expression condition of nucleated red blood cells.
Fig. 3A, 3B and 3C: normal marrow specimen, analyzing the differentiation mode of normal marrow line juvenile cells by using the spectroflow software to analyze the combination of multiple markers. Setting immature myeloid cell gate by using CD117/SSC and CD34/SSC, and combining two detection markers to form tens of combination detection and analysis of the differentiation process of normal myeloid series naive cells.
Fig. 4A, 4B, and 4C: myeloid tumor specimens (MRD detection after AML treatment), malignant myeloid naive cell differentiation pattern of myeloid tumors was analyzed by analyzing various marker combinations using the spectroflow software. Immature myeloid cell gates were set using CD117/SSC and CD34/SSC, and abnormal expression of malignant myeloid naive cells was analyzed using tens of combined assays. The main abnormalities are abnormal expression of CD56, CD96, CD11c, CD36, CD64, CD9, CD15, CD34, CD200, CD371, increased expression intensity of HLA-DR, reduced expression of CD13 and CD33, and change of expression pattern of two-dimensional dot expression of the combination of the markers.
FIG. 5: normal and malignant myeloid stem cells were analyzed using the kaluza software assay. In the graph A, which is a normal control sample, the distribution of the earliest myeloid stem cells of CD38-/CD34+ is low. Panel B shows a specimen of a patient with myeloid tumor, in which the malignant myeloid naive cells have slightly increased tumor stem cells CD38-/CD34 +.
Fig. 6A and 6B: normal bone marrow specimens were examined for routine rare attention weak cell populations using the spectroflow software for analysis of multiple marker combinations: setting a two-dimensional dot diagram of HLA-DR/CD123, wherein the cell group of HLA-DR +/CD123bri is Plasmacytoid Dendritic Cells (PDC), and the cell group of HLA-DR/CD123 bri is basophil (basophil). In the CD117/SSC two-dimensional dot diagram, the CD117bri is a mast cell. In the CD45/SSC two-dimensional dot plot, CD45bri/SSC was large and eosinophilic (eosinophil, eo). CD13/CD11c were expressed doubly and bound to HLA-DR to judge Myeloid Dendritic Cells (MDC). Meanwhile, CD19/SSC is used for setting a B cell gate, common marker combinations such as CD9/CD38 and the like are detected and analyzed, the development of B cells is detected, whether malignant B-series clone accompanied with the B cell is existed or not is judged, and the myeloproliferation condition is judged through normal B progenitor cells.
FIG. 7: normal bone marrow specimen, kaluza software analysis lymphocyte immune function detection, CD45/SSC detection analysis lymphocyte gate T, B, NK ratio, CD7/SSC set T and NK cell gate, according to CD56 expression, roughly divided into: CD56 bri-regulating NK cells, CD56dim killer NK cells, CD56-/CD7+ T cells. In CD56-/CD7+ T cells, CD56-/CD7+ T cells can be distinguished into CD4+ T cells and CD4- (mainly CD8 +) T cells according to CD4 expression, and double positive activated T cells are selected according to CD38/HLA-DR expression.
FIG. 8: the kaluza software performed the detection of immune checkpoints. Wherein, the pictures A-F are normal marrow specimens, and the pictures G-L are myeloid tumor (AML MRD) specimens. Two adjacent pictures show the expression of CD96/CD7 and CD200/CD7 in the same population of cells. Panel a, panel G are normal and malignant CD117+ myeloid lineage naive cell immune checkpoint CD96, CD200 expression, respectively; panel B, panel H are normal and myeloid tumor patients T cell immune checkpoint CD96, CD200 expression, respectively; panel C, panel I are normal and myeloid tumor patients CD4+ T cell immune checkpoint CD96, CD200 expression, respectively; panel D, panel J show expression of the activated T cell immune checkpoints CD96, CD200 in normal and myeloid tumor patients, respectively; panel E, panel K are CD56briNK cell immune checkpoint CD96, CD200 expression in normal and myeloid tumor patients, respectively; panel F, panel L are CD56dimNK cell immune checkpoints CD96, CD200 expression in normal and myeloid tumor patients, respectively.
FIG. 9: differential expression of the immune checkpoint CD 96. In 22 normal specimens and 42 myeloid tumor specimens, CD96 was found as an immune checkpoint, and the expression of various cell populations was different between the normal specimens and the myeloid tumor specimens: compared with the normal sample, in the tumor patient sample, the expressions of the killer NK cells CD96 with weak expression of CD56, the regulatory NK cells CD96 with strong expression of CD56 are weakened, and the expression of the malignant myeloid progenitor cells CD96 is enhanced, which have significant differences (P values are 0.007, 0.023 and 0.000 respectively).
FIG. 10: differential expression of the immune checkpoint CD 200. In 22 cases of normal specimens and 42 cases of myeloid tumor specimens, CD200 was found as an immune checkpoint, and the expression of various cell populations was different between the normal specimens and the myeloid tumor specimens: compared with the normal sample, in the marrow tumor patient sample, the CD200 expressions of T cells, CD4+ T cells, activated T cells, killer NK cells with weak expression of CD56, regulatory NK cells with strong expression of CD56 and malignant marrow primary cells are obviously enhanced and have significant difference (P values are 0.000, 0.000, 0.000, 0.000, 0.020 and 0.000 respectively).
Fig. 11A and 11B: normal bone marrow samples were analyzed for myeloid progenitor cell expression using flowjo and kaluza software multidimensional assays. FIG. 11A shows that CD34+ antigen of CD117+ myeloid progenitor cells gradually decreases and differentiates in two directions through trimap dimension reduction analysis of CD117+ myeloid progenitor cell population, mainly including CD117+ CD71+ CD 33-cells developing towards the nucleated red stage and CD117+ CD33+ CD 71-myeloblast progenitor cells developing towards the granulometric lineage. FIG. 11B Using the kaluza analysis software radar map, a consistent developmental pattern of the analysis can still be detected.
In the present invention, 22 normal specimens and 42 myeloid tumor specimens were examined, and it was found that CD96 was an immune checkpoint and that expression of various cell populations was different in the myeloid tumor patient specimens compared to the normal specimens: the expression of killer NK cells CD96 of CD56dim is enhanced, the expression of regulatory NK cells CD96 of CD56bri is weakened, and the expression of CD96 of malignant myeloid progenitor cells is significantly different (P values are 0.007, 0.023 and 0.000 respectively). CD200 acts as an immune checkpoint and in myeloid tumor specimens, there are differences in expression of various cell populations compared to normal specimens: t cells, CD4+ T cells, CD38+/HLA-DR + activated T cells, CD56 weakly-expressed killer NK cells, CD56 strongly-expressed regulatory NK cells, and malignant myeloid progenitor cells, wherein the CD200 expression of the cell populations is obviously enhanced and has significant difference (P values are 0.000, 0.000, 0.000, 0.000, 0.020 and 0.000 respectively). CD96 and CD200 are newly discovered important immune checkpoints. The detection and analysis of CD96 and CD200 expression of original myeloid line, NK and T cells of each group, and comparison of the difference between normal and tumor patients may be used as important basis for auxiliary diagnosis, prognosis, treatment guidance and immunoregulation.
In the detection process of the invention, in all detected patients, the markers with high expression probability of the myeloid tumor are CD13 (90%), CD33 (98%), CD34 (90%), CD117 (96%), CD38 (100%), HLA-DR (85%), and CD371 (84%), but only CD38, CD34 and CD117 are rarely expressed in other cells, and in terms of importance, CD34 and CD117 cover all early cells of the myeloid line, while CD38 has early cells negative to CD38, so CD38 is the most promising target therapeutic marker of the myeloid line selected in the embodiment of the invention.
Claims (10)
1. An antibody composition for flow cytometry screening for myeloid disorders and detection of immune checkpoints comprising the following antibodies:
anti-CD 15 antibody, anti-CD 96 antibody, anti-CD 33 antibody, anti-CD 34 antibody, anti-CD 117 antibody, anti-CD 9 antibody, anti-CD 45 antibody, anti-CD 38 antibody, anti-HLA-DR antibody, anti-CD 13 antibody, anti-CD 19 antibody, anti-CD 4 antibody, anti-CD 36 antibody, anti-CD 7 antibody, anti-CD 371 antibody, anti-CD 11c antibody, anti-CD 11b antibody, anti-CD 200 antibody, anti-CD 14 antibody, anti-CD 56 antibody, anti-CD 71 antibody, anti-CD 2 antibody, anti-CD 123 antibody, and anti-CD 64 antibody.
2. The antibody composition of claim 1, wherein each antibody in the antibody composition is a monoclonal antibody.
3. The antibody composition of claim 1, wherein each antibody is a fluorescein-labeled antibody;
anti-CD 15 antibody, anti-CD 96 antibody, anti-CD 33 antibody, anti-CD 34 antibody, anti-CD 117 antibody, anti-CD 9 antibody, anti-CD 45 antibody, anti-CD 38 antibody, anti-HLA-DR antibody, anti-CD 13 antibody, anti-CD 19 antibody, anti-CD 4 antibody, anti-CD 36 antibody, anti-CD 7 antibody, anti-CD 371 antibody, anti-CD 11c antibody, anti-CD 11b antibody, anti-CD 200 antibody, anti-CD 14 antibody, anti-CD 56 antibody, anti-CD 71 antibody, anti-CD 2 antibody, anti-CD 123 antibody, anti-CD 64 antibody, in that the sequence of their fluorescein labels are: FITC, PE-Dazle 594, PE-Cy7, PE-Cy5, PerCP-Cy5.5, PerCP-eFluor, APC-Cy7, BV421, AF532, BV605, BV480, BB515, AF700, BV570, AF647, Pacific Blue, BV750, BV650, BV510, BV785, BV 711.
4. The antibody composition according to any one of claims 1 to 3, which is a mixture of an anti-CD 15 antibody, an anti-CD 96 antibody, an anti-CD 33 antibody, an anti-CD 34 antibody, an anti-CD 117 antibody, an anti-CD 9 antibody, an anti-CD 45 antibody, an anti-CD 38 antibody, an anti-HLA-DR antibody, an anti-CD 13 antibody, an anti-CD 19 antibody, an anti-CD 4 antibody, an anti-CD 36 antibody, an anti-CD 7 antibody, an anti-CD 371 antibody, an anti-CD 11c antibody, an anti-CD 11b antibody, an anti-CD 200 antibody, an anti-CD 14 antibody, an anti-CD 56 antibody, an anti-CD 71 antibody, an anti-CD 2 antibody, an anti-CD 123 antibody, an anti-CD 64 antibody in the following volume ratios:
the anti-CD 15 antibody 1 which is,
the anti-CD 96 antibody 2.5,
the anti-CD 33 antibody 5, which is,
the anti-CD 34 antibody 3.5,
an anti-CD 117 antibody 1.5,
the anti-CD 9 antibody 7, which is,
the anti-CD 45 antibody 20 which is,
the anti-CD 38 antibody 1.5,
an anti-HLA-DR antibody 1 which is a human antibody,
(ii) an anti-CD 13 antibody 2,
the anti-CD 19 antibody 1 which is,
the anti-CD 4 antibody 3, which is,
0.5 of the anti-CD 36 antibody,
the anti-CD 7 antibody 1.5,
the anti-CD 371 antibody 0.3,
the anti-CD 11c antibody 5,
the anti-CD 11b antibody 1,
(ii) an anti-CD 200 antibody 5,
the anti-CD 14 antibody 1 which is,
the anti-CD 56 antibody 2.5,
0.25 of the anti-CD 71 antibody,
the anti-CD 2 antibody 1.5,
(ii) an anti-CD 123 antibody 2,
anti-CD 64 antibody 1.5.
5. A kit for flow cytometry screening for myeloid disorders and detecting immune checkpoints, comprising a first container holding the antibody composition of any one of claims 1-4.
6. The kit of claim 5, further comprising: one or more of a lysate of red blood cells, a buffer solution, and a flow tube used in conjunction with a flow cytometer.
7. Use of an antibody composition according to any one of claims 1 to 4 for the preparation of a kit for revealing normal myeloid development, myeloid tumour diagnosis, tumour stem cell studies, targeted therapeutic target screening, vulnerable cell population studies, immune function tests and immune checkpoint tests.
8. The use of claim 7, wherein the process of revealing normal myeloid development, myeloid tumor diagnosis, tumor stem cell research, targeted therapy target screening, vulnerable cell population research, immune function detection and immune checkpoint detection comprises:
(1) adding the sample to be detected into the flow tube to make the sample be in a single cell suspension state and ensure that the cell amount is 1 multiplied by 106pipe-1X 107A pipe; the sample to be detected is bone marrow or peripheral blood;
(2) mixing the sample obtained by the step (1) with the antibody composition of any one of claims 1 to 4, and incubating at room temperature in a dark place;
(3) adding 1 Xhemolysin into the flow tube incubated in the step (2), and incubating at room temperature in a dark place;
(4) centrifuging the flow tube incubated in the step (3) to remove supernatant;
(5) adding PBS buffer solution into the flow tube in the step (4), mixing uniformly, centrifuging to remove supernatant, and resuspending cells by using the PBS buffer solution;
(6) and (5) carrying out flow cytometry detection on the resuspended cells in the step (5), and analyzing the result.
9. A device for revealing normal myeloid development, myeloid tumor diagnosis, tumor stem cell research, targeted therapy target screening, vulnerable cell population research, immune function detection and immune checkpoint detection, the device comprising a detection unit and an analysis unit, wherein:
the detection unit comprises a reagent material for detecting a bone marrow or peripheral blood sample of an individual to be detected by flow cytometry, and a detection result of the sample is obtained; the reagent material comprises an antibody composition of any one of claims 1-4;
the analysis unit is used for analyzing the detection result of the detection unit.
10. The apparatus of claim 9, wherein:
the process of detecting a sample from an individual to be tested by flow cytometry comprises: preparing a flow-cytometric sample after treating a test sample with the antibody composition of any one of claims 1 to 4; performing flow cytometry on the machine for detection;
wherein, when the flow cytometry is detected on the machine, the gate analysis is set according to the following modes:
setting a P1 gate to remove adherent cells;
setting a living cell gate P2 as a cell in the P1 gate;
and (3) carrying out multiple gating simultaneously in a single living cell gate P2, and detecting the expression conditions of multiple groups of cells:
in a P2 gate, CD45/SSC is gated to detect lymphocytes, monocytes, granulocytes at the differentiation stage, nucleated erythrocytes and eosinophils;
setting immature myeloid cell gate by using CD117/SSC and CD34/SSC in P2 gate, and detecting and analyzing differentiation process of myeloid series immature cells;
p2 in-gate detection of the vulnerable cell population: setting an HLA-DR/CD123 two-dimensional dot diagram to detect plasmacytoid dendritic cells and basophils, setting a CD117/SSC two-dimensional dot diagram to detect mast cells, setting a CD45/SSC two-dimensional dot diagram to detect eosinophils, setting a CD13/CD11c two-dimensional dot diagram and detecting the plasmacytoid dendritic cells by combining with the HLA-DR;
in a P2 gate, a CD19/SSC is provided with a B cell gate, and the development of B cells is detected;
within the P2 gate, the T cell and NK cell gates were set using CD 7/SSC; the following assays were performed in the CD7 positive T cells and NK cells: detecting the expression of CD56 to detect regulatory NK cells, killer NK cells and T cells; the CD56-/CD7+ T cell gates were tested in addition: detecting CD4 expression to detect CD4+ T cell, CD4-T cell and activated T cell;
wherein the selectivity during the flow cytometry on-machine detection further comprises: performing an examination of a sample of two or more individuals to screen for potential target therapy targets of immune checkpoints and/or myeloid tumors; wherein:
screening immune checkpoints includes: the P2 gate CD117/SSC gate or CD117 negative tumor uses CD34/SSC gate to detect medullary primitive cells, and CD7/SSC gate to detect T cells and NK cell gate to detect NK cells and CD96 and CD200 expression of T cells in the P2 gate, and screening immune check points;
screening for potential target treatment targets of myeloid tumors includes: CD117/SSC gating or CD117 negative tumors in a P2 gate uses CD34/SSC gating to detect the expression of myeloid tumor cells, counts the probability of the occurrence of malignant expression markers, and screens the potential target of targeted therapy of the myeloid tumors.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1284568A (en) * | 1999-08-13 | 2001-02-21 | 杨梦甦 | Disease detecting method utilizing leucocyte disserentiating antigen gene chip |
| CN101601610A (en) * | 2008-07-15 | 2009-12-16 | 乐普（北京）医疗器械股份有限公司 | A kind of novel biological antibody medical device and preparation method thereof |
| CN104142315A (en) * | 2013-05-07 | 2014-11-12 | 中国科学院理化技术研究所 | Surface plasma resonance sensing chip used for tumor cell detection, preparing method thereof and applications of the chip |
| CN109655616A (en) * | 2018-12-19 | 2019-04-19 | 广州金域医学检验中心有限公司 | Detect the composite reagent and system of acute myeloid leukemia cell |
| CN109912683A (en) * | 2017-12-13 | 2019-06-21 | 杭州多禧生物科技有限公司 | A kind of cytotoxic molecule, conjugate and its preparation method and application |
| CN110192140A (en) * | 2016-11-16 | 2019-08-30 | 华盛顿大学 | System and method for recycling fluorescence imaging |
| WO2020102721A1 (en) * | 2018-11-16 | 2020-05-22 | Rapa Therapeutics, Llc | Immune monitoring of neuro-inflammatory amyotrophic lateral sclerosis (als) |
| CN111808946A (en) * | 2020-07-06 | 2020-10-23 | 浙江大学 | Myelodysplastic syndrome marker and kit thereof |
| CN111888474A (en) * | 2013-09-13 | 2020-11-06 | 安进股份有限公司 | Combination of epigenetic factors and bispecific compounds targeting CD33 and CD3 for the treatment of myeloid leukemia |
| CN111971091A (en) * | 2018-04-13 | 2020-11-20 | 柏林化学股份公司 | anti-BST 1 antibodies for prevention or treatment of myelodysplastic syndrome |
| WO2021013932A1 (en) * | 2019-07-23 | 2021-01-28 | Deutsches Krebsforschungszentrum | Polypeptides for treatment of aml |
| CN112292147A (en) * | 2018-06-19 | 2021-01-29 | 南京传奇生物科技有限公司 | Engineered cells and uses thereof |
-
2021
- 2021-03-08 CN CN202110249801.1A patent/CN112630438B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1284568A (en) * | 1999-08-13 | 2001-02-21 | 杨梦甦 | Disease detecting method utilizing leucocyte disserentiating antigen gene chip |
| CN101601610A (en) * | 2008-07-15 | 2009-12-16 | 乐普（北京）医疗器械股份有限公司 | A kind of novel biological antibody medical device and preparation method thereof |
| CN104142315A (en) * | 2013-05-07 | 2014-11-12 | 中国科学院理化技术研究所 | Surface plasma resonance sensing chip used for tumor cell detection, preparing method thereof and applications of the chip |
| CN111888474A (en) * | 2013-09-13 | 2020-11-06 | 安进股份有限公司 | Combination of epigenetic factors and bispecific compounds targeting CD33 and CD3 for the treatment of myeloid leukemia |
| CN110192140A (en) * | 2016-11-16 | 2019-08-30 | 华盛顿大学 | System and method for recycling fluorescence imaging |
| CN109912683A (en) * | 2017-12-13 | 2019-06-21 | 杭州多禧生物科技有限公司 | A kind of cytotoxic molecule, conjugate and its preparation method and application |
| CN111971091A (en) * | 2018-04-13 | 2020-11-20 | 柏林化学股份公司 | anti-BST 1 antibodies for prevention or treatment of myelodysplastic syndrome |
| CN112292147A (en) * | 2018-06-19 | 2021-01-29 | 南京传奇生物科技有限公司 | Engineered cells and uses thereof |
| WO2020102721A1 (en) * | 2018-11-16 | 2020-05-22 | Rapa Therapeutics, Llc | Immune monitoring of neuro-inflammatory amyotrophic lateral sclerosis (als) |
| CN109655616A (en) * | 2018-12-19 | 2019-04-19 | 广州金域医学检验中心有限公司 | Detect the composite reagent and system of acute myeloid leukemia cell |
| WO2021013932A1 (en) * | 2019-07-23 | 2021-01-28 | Deutsches Krebsforschungszentrum | Polypeptides for treatment of aml |
| CN111808946A (en) * | 2020-07-06 | 2020-10-23 | 浙江大学 | Myelodysplastic syndrome marker and kit thereof |
Non-Patent Citations (2)
| Title |
|---|
| Molecular and cytogenetic abnormalities in acute myeloid leukemia: review and case studies;Elvira Deolinda Rodrigues Pereira Velloso 等;《einstein.》;20111231;第9卷;摘要，第186页右栏"方法"部分 * |
| Universal monitoring of minimal residual disease in acute myeloid leukemia;Elaine Coustan-Smith等;《JCI Insight.》;20180503;第3卷(第9期);摘要 * |
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