Open access peer-reviewed chapter

Recent Developments in Application of Multiparametric Flow Cytometry in CAR-T Immunotherapy

Written By

Hui Wang and Man Chen

Submitted: 18 October 2022 Reviewed: 02 November 2022 Published: 20 January 2023

DOI: 10.5772/intechopen.108836

From the Edited Volume

Immune Checkpoint Inhibitors - New Insights and Recent Progress

Edited by Afsheen Raza

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Abstract

In recent years, chimeric antigen receptor (CAR) modified T-cell (CAR-T) immunotherapy has achieved great success in cancer treatment, especially in some hematologic malignancies. Multiparametric flow cytometry (MFC) is a key immunologic tool and plays an important role in every step of CAR-T design, development, and clinical trials. This chapter discusses the application and new developments of MFC in CAR-T, including the selection of CAR-T targets, the enrollment of patients, the detection of minimal/measurable residual disease (MRD), the quality evaluation of CAR-T product, the detection of immune cell subsets and cytokines, and the study of immune checkpoint and immune suppressive microenvironment.

Keywords

  • chimeric antigen receptor
  • immunotherapy
  • multiparametric flow cytometry
  • hematological malignancies
  • immune

1. Introduction

Chimeric antigen receptor (CAR) modified T-cell (CAR-T) has been a remarkable achievement in the field of cancer therapy in recent years [1, 2, 3, 4, 5, 6, 7], especially for the treatment of refractory and relapsed B-cell acute lymphoblastic leukemia (ALL) [1, 2, 3]. CD19-CAR-T alone or bridging allogeneic hematopoietic stem cell transplantation (allo-HSCT) can greatly improve the complete remission (CR) rate and overall survival (OS) rate. CAR-T therapy for other malignancies is being explored as well [4, 5, 6, 7]. However, the main problem with CAR-T therapy is its high relapse rate, which involves a variety of mechanisms. Current researches focus on improving CAR-T structure, selecting new targets, and eliminating the inhibitory immune microenvironment [8, 9, 10, 11, 12, 13, 14].

Multiparametric flow cytometry (MFC) is an immunological technique developed in the 1970s and has become an indispensable methodology for clinical diagnosis and basic research [15, 16]. CAR-T is one kind of immunotherapy, and MFC plays a pivotal role in the entire process of CAR-T [3, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]. These applications involve multiple aspects of MFC, and basically can be divided into two categories, that is, protocols to detect tumor cells and/or target antigen-positive cells and those to evaluate the immune system. The previous category includes tumor cell immunophenotyping to select promising targets [17, 18], minimal residual/measurable diseases (MRD) detection [3, 19, 20], and recovery kinetics of target antigen-positive cells [3, 21, 22]. The latter category includes lymphocyte activity and function evaluation, CAR-positive cell assay [21, 22, 23, 24, 25], immune cell subsets detection [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], lymphocyte killing function assay [27], cytokines detection [26, 27, 28, 29], tumor microenvironment (TME) evaluation, and immunosuppressive signals detection [23, 26].

If according to time points, the application progress of MFC in CAR-T can be divided into four stages: CAR-T research and development, patient enrollment of clinical research, quality evaluation after product preparation, and posttreatment evaluation.

These tests involve almost all aspects of MFC, including routine clinical testing items and special research items, and are carried out repeatedly at different time points, even with some overlaps. See Table 1.

PhageAimSpecimen typeTumor or target-related assaysImmune-related assaysImportant parametersOptional parameters
CAR-T designSelection of target and prediction of side effects.Patient specimens or cell lines.Immunophenotype or MRD.Lymphocyte activity and function, immune cell subsets, and cytokinesCoverage, expression intensity, and specificity of target antigen in certain diseases. Killing efficiency related to CAR-T design.
EnrollmentThe expression rate and intensity of target antigens on tumor cells. Function and activity of patient’s lymphocytes. Enrollment possibility. The choice of raw material.BM, PB, or other sites from patient.Immunophenotype or MRD.Above and optionally TME and immune checkpoint.The proportion of tumor cells in nuclear cells, the immunophenotype of tumor cells, the expression rate, expression intensity, and specificity of potential targets in tumor cells.The killing efficacy of CAR-T cells was evaluated by coculture with tumor cells, and the inhibitory signal in the immune microenvironment was evaluated.
CAR-T productQuality control of CAR-T product.CAR-T productMRDCAR positive cells, immune cell subsets, and cytokines.Percentages and absolute counts of CAR-expressing cells, CAR-T cell components (lymphocyte and functional subsets), and residual tumor and other cells in the product were assessed.Evaluation of inhibitory and activating signals, cytokine release ability.
After CAR-T infusionEfficacy evaluation and kinetic detection of target recovery.BM, PB, or other sites from patient.MRDKinetics of target antigen recovery.MRD was used to evaluate the efficacy and recovery of CAR-T target expression in normal cells.Expression curves of CAR-T target antigens in normal and tumor cells at each time point before and after infusion.
Immune cell subsets.PB or CSF from patient.CAR T-cell detection, basic T-lymphocyte subsets, individualized immune cell subsets, and cytokine detection.Proportion and absolute count of CAR-expressing cells, CAR-T cell component, relationship between CAR-T cell peak and clinical response, basic T-lymphocyte subsets.Individualized immune cell subset, functional cytokines, immune activation or exhaustion, and aging marker expression.
Study on relapse mechanism and re-selection of targets.BM, PB, or other sites from patient.Selection of target.TME and immune checkpoint.Target positive and negative relapse, and selection of new CAR-T targets after relapse.Evaluation of TME and immune checkpoint.

Table 1.

Application of MFC in CAR-T development and study.

Note. CAR: chimeric antigen receptor, CSF: cerebrospinal fluid, MRD: minimal residual/measurable diseases, and TME: tumor microenvironment.

However, even in routine items, the special nature of CAR-T brings technical challenges. The analysis of the immunophenotype of tumor cells needs a very accurate gate setting because the coexistence of target antigen negative subclone may become the source of recurrence [9, 10, 11, 12]. The evaluation of CAR-T products before infusion and MRD detection after CAR-T immunotherapy need to be careful of the target antigen-negative malignant and benign cells [3, 19, 20]. The presence of CAR-T cells may affect the MRD detection of T lymphocytic malignancies. In the identification of CAR-T products and early immunological evaluation after treatment, it is necessary to evaluate the composition and activating status of CAR-positive and CAR-negative cells simultaneously [32, 33, 34, 35].

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2. Tumor or target antigen-expressing cells related assay

2.1 Target screening and specificity evaluation

Although the diversity of tumor cells leads to a high tumor escape rate in traditional single-target CAR-T, and new technologies are beginning to use bi-specific targets and even more complex designs, screening of specific target antigens is still the most important part of CAR-T design. MFC is the most important tool to achieve this purpose at present [3, 4, 17, 18]. The ideal CAR-T target should meet the following requirements: a high rate of occurrence in certain diseases (high availability of CAR-T), a high percentage of expression on tumor cells (covering all tumor cells to minimize relapse), a high intensity of expression (the expression intensity of target antigen on tumor cells is related to the efficacy, although there are contradictory results) [3639], and good specificity (no or little expression in normal cells will not cause serious impact on patients) [1, 2, 3, 4]. Target screening is performed on the basis of immunophenotyping or MRD, but with more stringent precautions than routine clinical diagnosis. It is necessary to accurately gate and define tumor cells, especially to cover all heterogeneous tumor cell populations. Otherwise, target-negative tumor cells will become the source of relapse. The detection of potential targets on tumor cells needs to be reported as a percentage. The mean fluorescence intensity (MFI) or median fluorescence intensity (MdFI) of target antigen expression in tumor cells and the ratio of MdFI to control cells may be used to describe the relative expression intensity. Some studies even use fluorescence microbeads for accurate quantitative detection [36, 37]. Standardization of the operation and calibration of the instrument are required for the testing process, as well as a selection of appropriate internal controls.

2.1.1 Overview of the CAR-T targets in various tumors

The target selection of ALL is relatively consistent. Generally, lineage markers with high coverage are preferred, such as CD19 [1, 2, 3, 36, 40, 41], CD22 [42], or CD19/CD22 dual targets [37, 43] for B-ALL and CD7-CAR-T by genetic engineering technology [4, 44, 45] for T-ALL. Although some clinical studies have selected markers expressed in subgroups of ALL, such as CD20 [46] and CRLF2 [31] for B-ALL, and TRBC1 and CD1a for T-ALL [47, 48]. As to lymphoproliferative disease (LPD), other studies have tried to select lineage markers expressed by mature lymphocytes beside CD19 and CD22 [6, 37], for example, CD20, CD37, and BAFFR for B-LPD, CD5, CD4, TRBC1 for T-LPD, and CD38, BCMA or other markers for multiple myeloma (MM) [9, 10, 49, 50, 51]. Special subtypes of lymphoma have selected corresponding specific antigens as targets, such as CD30 for anaplastic large cell lymphoma (ALCL) and Hodgkin lymphoma (HL) [52, 53, 54]. Acute myeloid leukemia (AML) is a highly heterogeneous tumor, and there are a lot of studies on its targets, including CD33, CD123, CLL1 (CD371), CD25, CD117, Tim3, NKG2D, CD44, CD96, and CD38, or the combination of the above targets [5, 12, 17, 18, 55, 56, 57, 58, 59, 60]. Although studies on solid tumors have made some achievements, searching for solid tumor-specific or associated antigens is still an interesting field for researchers. Therefore, current researches focus on immunosuppressive TME and modified CAR-T design [9, 10, 61, 62].

2.1.2 Standardized evaluation of target antigen expression

Although some studies have shown that the efficacy of CAR-T is highly dependent on the density of target antigen expression [36, 37], and clinical trials has found that high tumor burden is a high-risk factor to relapse [40, 41], more detailed data remains unclear. For example, the percentage and numbers of antigen expressed on tumor cells and the expression intensity that can activate CAR-T to obtain the best response rate and longest survival rate; the suitable target antigen expression in tumor cells that allows the patient to be enrolled in the CAR-T study; the corresponding relations between absolute counts of target positive tumor cells or antigens on total tumor cells and dose of CAR-T needed for treatment [63, 64], etc. On the other side, the efficacy, stability, and difference of CAR detection antibody, qualitative and quantitative heterogeneity of antigen expression on tumor cells in the same disease, differences in antigen expression intensity caused by different fluorescence, and the influence factors in the process of antibody staining, can lead to significant intra-lab and inter-lab differences. Thus, the accurate relationship between the expression of CAR-T target antigens and the efficacy/side effects/survival rate is not comparable in different studies, which is more obvious in studies of weakly expressed target antigens. Given the diversity of CAR-T products and the multiple factors affecting MFC testing, uniform standard operating procedures (SOPs) may not be available in a short time. However, we hope to make the technique relatively stable and objective by standardizing the process of MFC detection, which will be helpful in exploring the most ideal target, accurately evaluating the efficacy and side effects of CAR-T, studying the complex relapse mechanism and promoting the update of CAR-T products to obtain the best effect for individual study [21, 22, 23, 24, 25]. To do this, the same protocol should be used in a study, especially in a multicenter study, including antibody clone and fluorescein combination; titration and inter-batch comparison of the antibodies are required. Use the same instrument as far as possible, accurate comparisons are required if different instruments are used, and daily calibration and regular maintenance is also mandatory; residual normal counterparts in the specimen are good controls to evaluate the expression of target antigen with high or moderate intensity, such as CD19, CD22, and CD7, and we can describe target antigen as dim (dimmer than normal) or bright (brighter than normal) besides percentage; MFI/MdFI or quantitative fluorescence microbeads need to use to determine the expression of target antigen with very low intensity [37, 38, 39].

2.1.3 Evaluation of the specificity of target antigen

The ideal target antigen has been described above, where the specificity is evaluated by the expression of the antigen in normal cells, which is very important for CAR-T target selection. Because CAR-T is a very powerful and specific targeted therapy, most cells expressing the target will be killed, whether normal or malignant. Killing tumor cells is effective, while killing normal cells is toxic, not to say this effect lasts 1–3 months [3, 4, 34, 35, 36, 37].

An ideal target is only specifically expressed in tumor cells but not in normal cells, or in normal cells the expression rate is low or the functions of these cells can be replaced by other cells or drugs. Unfortunately, almost no antigen is absolutely specific or low expressed in normal cells [9, 10] except those associated with B cells and plasma cells. Fortunately, with the development of modern life science, more and more gene modification methods and other technologies are overcoming this problem, such as the emergence of gene knockout or selecting CD7-CAR-T [4, 44, 45]. MFC plays an important role during the process. Accurate analysis of the target antigen expression on different cells can predict the toxicity and side effects, and help researchers to modify CAR-Ts.

2.2 MRD

MRD is an important indicator for evaluating efficacy and is closely related to prognosis [1, 2, 3, 4, 19, 65]. MRD monitoring after CAR-T therapy is difficult due to tumor adaptation and off-target effects. The issues that need to be paid attention to are gating with multiple markers and recognizing malignant or normal cell loss target antigens [3, 19, 20].

2.2.1 Selection of gating markers

CD19-CAR-T is the most used immunotherapy, and MRD detection after CD19-CAR-T in B-ALL is also the focus of researchers. Because all or part of CD19 expression is lost or weak in 7.4–62.5% of B-cell malignancies after CD19-CAR-T treatment, CD19 gating cannot be the only rough B gating marker [3, 19, 20, 36, 37]. As for the selection of alternative gate markers, some laboratories chose CD22+ and/or CD24+/CD66b− [19], while we and some laboratories chose multiparameter synchronous gate setting by cytoplasmatic (c) CD79a combined with CD19 and lymphoblast markers [1, 2, 3, 20]. The reasons are as follows: 10–20% of B-ALL cases do not express CD24, especially in cases with MLL-related fusion genes [3, 19]. After the failure of CD19-CAR-T therapy, the choice of CD19/CD22 bi-specific CAR-T or CD22-CAR-T, coupled with the weak expression of CD22 in B lymphoblasts, all determine that this is not an ideal rough B gating marker [3, 38]. Although studies have found that CD22dim/-MRD did not appear after CD22-CAR-T treatment [37], further studies are needed because of the small number of cases. Therefore, we used cCD79a as the main B marker in MRD detection after CD19-CAR-T or CD19/CD22 combined CAR-T treatment, and achieved good clinical evaluation results [3]. Besides the biggest advantage of cCD79a panel is that we can use the same panel for all MRD detection after any B marker CAR-T treatment in the future because it is an intracellular antigen not for CAR-T target [51].

The same idea was adopted in CD7-CAR-T for T-ALL, other lineage markers are added in the MRD panel, such as cCD3, CD5, and CD2, as well as blast markers, such as TdT, CD34, CD99bri, and CD1a [4].

2.2.2 Changes in phenotype and observation methods

When selecting cCD79a combined panel to detect MRD after CD19 and/or CD22-CAR-T therapy in B-ALL, the following should be noted: (1) the expression intensity of some antigens may change after the intracellular operation. (2) Recognize the immunophenotype of normal CD19-negative hematogones, most of which are the earliest stage of CD34+ B progenitor cells. They are different from the CD19 positive counterpart in that weaker CD10 expression and larger SSC, and may be misdiagnosed as MRD; (3) in fact, CD19-negative hematogones exist in normal BM but are ignored, because most of them are rare and CD19 is routinely used for gating. A significant decrease in the proportion of CD19 positive B progenitors with CD19-CAR-T results in a relative increase in the proportion of CD19-negative B progenitors, which together with changes in gate setting and most importantly the focus on CD19-negative B cells, made this population prominent [3, 19, 20].

Given that the heterogeneity of tumor cells is obvious after CAR-T therapy, even with the use of alternative gate markers, detection will be difficult, not to say the rare use of cytoplasmatic markers in cerebrospinal fluid (CSF) specimens. After CAR-T, multiple gates by multiple markers will be helpful in MRD detection by MFC. For example, SSC/cCD79a, SSC/CD19, SSC/CD10,SSC/CD34, and SSC/TdT in B-ALL, CD99bri/SSC, cCD3/CD45dim, CD5/CD45dim, CD34and/or CD1a/SSC, and TdT/SSC in T-ALL, CD229/CD45dim and CD138/CD45dim in MM. CD45dim/CD10 positive and/or CD34 positive and/or CD38 positive cells are not present in normal CSF samples, so CD34 and/or CD10 and/or CD38 combined with CD45 gate method was used for identification of CD19-negative B-ALL MRD. See Figure 1.

Figure 1.

BM from one B-ALL patient for MRD detection by MFC, the title of each dot plot was the gate where the subplot showed the cell. A, before CD19-CAR-T immunotherapy. The cells in red color were malignant B lymphoblasts with 7.66% of live cells. They were positive for CD19, CD10, CD81, TdT, and CD34part, negative for CD45. B, 30d after CD19-CAR-T. No CD10 or cytoplasmatic (c)CD79a-positive cells were observed. C, relapsed 4 months after CD19-CAR-T. the blast was 3.22% of live cells and consisted of four subsets. The cells in red color were the major subset, positive for CD10, CD38, CD81, TdT, and cCD79a part, negative for CD45, CD34, and CD19. The cells in dark green color were the minor subset 1, positive for CD10, CD19, CD38, and cCD79a, negative for CD45and CD34, not known for CD81 and TdT. The cells in dark brown color were the minor subset 2, positive for CD10, CD38, and CD81, negative for CD45, CD34, TdT, cCD79a, and CD19. The cells in sapphire color were the minor subset 3, positive for CD10, CD34, TdT, and cCD79a, negative for CD38, CD81, CD45, and CD19. Normal B cells (fluorescent green color) and plasma cells (magenta color) were all CD19 partially positive.

In addition, special attention should be paid to myeloid conversion after CAR-T in ALL patients [66]. After CD7-CAR-T cell therapy, MRD detection may be affected due to interference of CAR-T cells. In the case of targeted therapy with CD38, CD123, and other markers of progenitors, attention should be paid to the phenotypic changes of the normal blast caused by the loss of these markers during MRD detection.

2.3 Kinetics of target antigen recovery

After injection, CAR-T cells expand more than 10,000 times in vivo. The number of amplifications and duration of presence in vivo largely determine the efficacy and side effects of CAR-T. The recovery of cells expressing the target antigen can indirectly reflect the recovery kinetics of CAR-T [3, 19, 20, 34, 35, 67]. Target antigen recovery is not evaluated alone, generally detected as part of MRD or immunoassay [3, 19, 20, 34, 35, 67].

The recovery dynamics decide the choice of detection time points. Besides CAR-T products, the efficacy depends largely on in vivo CAR-T cell proliferation. The target expression cells begin to recover 1–3 months after treatment, and commonly BM, CSF, or other involved sites are selected as specimens. BM should ideally be tested once a month for the first 6 months and at least once every 3 months for the first 6 to 12 months [1, 2, 3, 4, 19, 20, 21, 22, 32]. Generally, PB or CSF of patients is selected as specimens for CAR-T cell assay and cytokines detection. Before infusion on day 0, and after infusion on other time points, PB-related assays are frequent in the first month, such as 4 d, 7 d (optional 10 d or 11 d), 14 d, 28 d, 2 m, 3 m, and 6 m [1, 2, 3, 4, 32, 33, 34, 35, 36, 37]. The detection of CAR-expressing cells can be stopped after the detected values are lower than the limit of detection (LOD) for two consecutive times. MRD and CAR-T cell detection of CSF are performed at the appropriate time point. PB is selected for immune assay, at least once a month for the first 6 months, and once every 3–6 months after 6 months [32, 33, 34, 35, 36, 37].

Taking CD19-CAR-T treatment for B-ALL as an example, the duration of B-cell deficiency varies greatly among different studies, generally lasting 2–3 months. The recovery of B cells in PB is a signal of CD19-CAR-T dysfunction. In pediatric B-ALL, recovery of B cells at 3 months suggests a high risk of relapse, possibly due to CAR-T depletion [36, 37, 40, 41, 42, 43].

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3. Immune-related assays

There will be an overlap of parameters in these assays. The panels are recombined for different time points. For example, in CAR-T product evaluation and samples were drawn at earlier time points after CAR-T, CAR-expressing cells and other immune subsets may be detected in the same panel. If CAR-T cells continuously decrease and are lower than LOD twice in a row, the MFC method will no longer be used to detect CAR-T cells and the protocol will be changed to immune function and cytokine assays without CAR-T cell detection.

3.1 Evaluation of lymphocyte activity and function

The detection of lymphocyte activity and function by MFC mainly includes release of cytotoxic proteins (granzyme, perforin), degranulation (CD107a), expression of surface activation markers (PD1, CD25, CD38, HLA-DR, CD69, etc.) [15, 27, 36, 37], killing ability assays through apoptotic cells detection, expression of death signal molecules (Fas-L or TRAIL) [36, 37], new kinds of nuclear dye to stain dead and live cells in a high throughput format [36, 37, 68], and production of various inflammatory cytokines [4, 25, 26, 27, 28, 29, 30, 36, 37].

These tests mainly involve the selection of the cell source for CAR-T and the quality evaluation of the product after successful preparation. Each study may apply a different method, and some studies do not choose MFC method. The advantage of MFC is that it can evaluate cell subsets and effector targets simultaneously [4, 25, 26, 27, 28, 29, 30, 36, 37].

The choice of autologous or allogeneic cells for CAR-T has its own advantages and disadvantages. Compared to allogeneic CAR-T cells, autologous CAR-T cells are safer. However, CAR-T cell preparation may be compromised when patients have the following conditions: elderly patients, high tumor load, multiple treatments, low number and poor viability of lymphocytes, etc., in which case other immunotherapeutic products may be chosen [4, 41].

After successful CAR-T preparation, not only the proportion of CAR-positive cells affects the efficacy, but also the killing activity of lymphocytes [34, 35, 36, 37].

3.2 Detection of CAR-positive cells

This test needs to be repeated as it involves CAR-T product quality evaluation and dynamics assay at different time points. After successful preparation of CAR-T, quality evaluation should be carried out before the infusion. The proportion and count of CAR-positive cells are the most important parts of them [1, 2, 3, 4, 21, 22, 23, 24, 25, 26, 27, 34, 35]. Values detected by MFC and qPCR are well consistent [22]. Compared with the qPCR method, MFC may have a lower sensitivity [34]. However, MFC has unique advantages. Through multicolor and gating technology, MFC can clearly mark the proliferate, activated, or suppressive subgroups of CAR-T cells [36, 37, 69, 70, 71, 72, 73, 74, 75]. In rare cases, MFC can identify CAR-positive transduced leukemic cells [76, 77]. In addition, quality testing can also be carried out to detect other cells in the CAR-T product. The high speed, simplicity, and low cost of MFC facilitate its application in CAR-T studies because these assays need to be repeated.

3.2.1 Selection of CAR detection antibodies

CAR-positive cells can be detected by MFC using direct or indirect fluorescein-labeled antibodies against their extracellular domain (ECD). Initial clinical studies used sheep anti-mice IgG (polyclonal anti-IgG antibodies), which was not suitable for humanized CAR-T. Anti-idiotype monoclonal antibodies, antigen-Fc, protein L-based assays, and anti-linkers antibodies are commonly used CAR detection methods as well. Each method has different properties and shortcomings. For example, the anti-IgG antibodies and protein L have higher reagent stability but lower specificity to CAR, and antigen-Fc and anti-idiotype antibodies can detect CARs with very high specificity [36, 37, 69, 70, 71, 72, 73, 74, 75].

At present, most CAR protein detection antibodies are customized by CAR-T companies resulting in a lack of standardization in the assay. Therefore, an extremely strict quality control is needed for MFC. Firstly, since CAR is an unknown antigen and CAR-positive cells may have a high background because CAR-T cells are often large activated cells, the effect of compensation and fluorescence spillover should be eliminated by fluorescence minus one (FMO) in panel design. Secondly, fluorescence with high brightness should also be selected to reduce the possible false negative results caused by dim fluorescence. Third, in addition to the traditional isotype negative control, a group of cells processed with the same method but without transduction should be added as biological control, while successfully constructed CAR-T cells as a positive control, especially for those with low fluorescence intensity or without a gap between negative and positive cells. Fourth, the exclusion of dead cells and nonspecific binding are carried out by different methods, such as using dead/living cell dyes to exclude dead cells, CD14 to exclude monocytes, and Fc receptors blocking reagent or serum/IgG to eliminate nonspecific binding of IgG1 and IgG2a to Fc fragments. Fifth, the performance of new lots/shipments of antibodies and reagents should be compared with old ones to minimize inter-lot and even inter-shipment differences, which is more important for polyclonal antibodies. Sixth, in addition to strict quality control of MFC, it should also be compared with the qPCR method at the beginning of the study. Last but not the least, it is necessary to use the same antibody panel in one study [21, 22, 23, 24, 25, 26, 27, 36, 37, 69, 70, 71, 72, 73, 74, 75].

3.2.2 Cellular kinetics at different time points

After infusion, CAR-T kinetic detection is an important indicator to evaluate its effectiveness and safety. Although a big variety exists in different CAR-T and different studies, regular changes in CAR-T kinetics can be observed. For example, CAR-T cells begin to proliferate in vivo 4 days after CD19-CAR-T treatment, peak at 7–19 days, and most of them recover around 28–60 days [1, 2, 3, 4, 21, 22]. The indicators reflecting CAR-T cell kinetics include direct (the proportion and number of CAR-positive cells, and concentration of corresponding cytokines) and indirect one (the recovery kinetics of target antigens on cells mentioned in 2.3 above).

At present, data from many clinical trials show that CAR-T proliferation in vivo is significantly related to the therapy effect. Compared with patients with ineffective treatment, patients with effective treatment have a much higher CAR-T cell proliferation peak and the area under the curve (AUC) within one month of CAR-T infusion [32, 33, 34, 35, 36, 37]. CAR-T < LOD is associated with B-cell recovery, and the consistent result of MFC and PCR has been verified in many studies [21, 22, 23, 24, 25, 26, 33, 34, 35, 36, 37].

3.2.3 Composition of CAR-positive cells

MFC can detect the subsets of CAR-T cells (CD4 or CD8), including differentiation (naive, memory, and effector), activation (expression of activation markers), and inhibitory receptors (PD1, Tim3, LAG3, CTLA-4, and TIGIT). These markers may correlate with clinical responses. However, the results of testing the proportion and number of CAR-positive cells in patients at different time points vary greatly. Therefore, the panel varies according to them.

Generally, a relatively detailed panel is chosen when the quality of the product is evaluated before infusion and when the proportion of CAR-positive cells is high in the early post-CAR-T infusion period. However, the basic panel may be chosen for the consideration of price, sample size, and the low concentration of CAR-positive cells. Taking CD19-CAR-T as an example, the basic panel may include CD4, CD8, CD3, CD19, CD16 + CD56, CD45, CAR, and CD14, to evaluate the common lymphocyte composition, CD4/CD8 ratio, residual CD19-positive cells, and recovery kinetics, in addition to accurate detection of CAR-positive cells. Further assays include CD25/CD127 for CD25dim/CD127+ regulatory T cells (Treg) and CD25 high-activated cells. The different effector and memory T subsets are evaluated by using CCR7 (CD197) and CD45 RA, such as naive T cells (TN, CD197+/CD45RA+), central memory T cells (TCM, CD197+/CD45RA−), effector memory T cells (TEM, CD197−/CD45RA−), and effector T cells (TEFF, CD197−/CD45RA+).

If further evaluated, CD38/HLA-DR assay for activated T cells will be added, and CD38+ or HLA-DR + or double-positive (DP) activated subsets can be acquired. Stem cell memory-like T cells (TSCM) expressing markers, such as CD45RA, CCR7 (optional CD62L), CD95, CD27, CD28, CD127, CD11adim, and lacking CD45RO, these cells can be detected by simply adding CD95 to CD197/CD45RA panel. Studies have shown that TSCM has the ability to self-renew and differentiate [22, 23, 24, 25, 26, 27, 78]. The immune composition of CAR-T products is associated with antitumor efficacy, and CAR-T cells with TN, TSCM, and TCM phenotypes have been found to have longer in vivo persistence and higher antitumor efficacy [32, 33, 34, 35, 36, 37]. After infusion, CAR-positive cells are mainly TEM in the expansion phase, which will last in a long term, and TN begins to appear later [22].

It has been found that specific populations of the donor T cells identified by MFC can predict the prognosis, especially T subsets that co-express certain suppressive signals. Finney [36] found that increased frequency of LAG-3+/TNF-αlow CD8+ T cells in PB apheresis product was related to relapse of pediatric B-ALL patients treated with anti-CD19 CAR-T.

High expression of target antigens by tumor cells can effectively stimulate CAR-T cell proliferation [36, 37], but high tumor load is in turn a poor prognostic factor for CAR-T [40, 41], the paradox may be caused by the expansion of certain CAR-T subpopulations expressing inhibitory signals hindering CAR-T cell expansion in vivo [36, 37, 77, 78].

3.2.4 Detection of other cells

At present most CAR-T cells are derived from the patient’s own immune cells, and although most patients’ tumor cells will die during in vitro culture, there will be some cases in which the tumor cells remain alive or even survive off-target [75, 76, 77]. Therefore, a rigorous MRD test of tumor cells should be performed in the quality evaluation of the product. The MRD panel and data analysis should be performed according to the method described in 3.2 above.

3.2.5 Absolute counts of CAR-positive cells

Absolute counting of CAR-T cells can be performed using either a single- or dual-platform method, where the single-platform can be done using the volumetric method or the absolute counting microbeads method [79].

The single-platform method is considered to be more accurate than the dual-platform method and requires less sample volume. However, since the single platform method cannot be washed, there may be a high background signal or failure to correctly detect some antibodies or fluorescent dyes. Therefore, any method can be chosen, but use the same method in a total clinical study, including multicenter studies.

The quality control of CAR-T cell enumeration is referenced to that of CD34+ hematopoietic stem cells [15, 79], with a minimum collection of 100 positive cells, and the LOD and lower limit of quantitation (LLOQ) for MRD assays should be verified. Mostly more than 1,000,000 events are recommended to acquire for detailed analysis of CAR-T cells when the percentages are high, and for accurate enumeration at later time points when the percentages may be down to less than 10−4 [15, 16, 19, 20]. In the lymphocyte ablation phase, as many as possible cells are acquired, and a minimum of 100,000 cells is recommended [15, 22, 23, 24, 25, 26].

3.3 Immune cell subsets

Immune cell subset detection has many similarities and overlaps with CAR-T cell detection. Therefore CAR-positive cells can be detected along with the immune cell subset detection before infusion and early days after CAR-T treatment. When CAR expression cells cannot be detected twice in a row, immune subset detection will last for a longer time without CAR antibody [15, 22, 23, 24, 25, 26].

Because CAR-T is a kind of immunotherapy, including the specific killing of target antigen-positive cells and nonspecific killing of CAR-negative cells, there is a positive and negative regulation balance between efficacy and side effects. Nowadays 8 or more colors panel are recommended to analyze detailed subsets in CAR positive and negative parts with a similar panel [15, 22, 23, 24, 25, 26].

The titration of all monoclonal antibodies is highly recommended before performing actual experiments. An isotype control should be used at the same concentration of the antibody of interest. DAPI or 7AAD or other dye to distinguish live or dead cells may be added. In addition, with the development of immunology, the different configuration of instruments, and the intersection of various antigens, the antibody combination to define the same functional subgroups in different studies maybe not the same, and the detection panels are also very heterogeneous [15, 22, 23, 24, 25, 26]. Therefore, it is necessary to adopt a consistent panel in a study, especially a multicenter study.

3.4 Cytokine detection

3.4.1 Cytokines

Due to different processes and cell sources of CAR-T, different cytokines may be produced. For example, CAR-T from PB CD3+ T cells may lead to the formation of multiple cytokines. CD4+ T cell-related factors are IL-2, IL-4, IL-5, IL-10, IL −13, and IL-17, while CAR-T from CD8+ T cells mainly produces IFN-γ, TNF-α, perforin, and granzyme B. CAR-T proliferation and efficacy are related to most important cytokines, so cytokine detection is an important assay for quality evaluation of the product in development process and CAR-T efficacy evaluation after the immunotherapy [26, 27, 28, 29, 30, 36, 37, 80, 81].

However, the toxicity of CAR-T is always along with its effectiveness. The most common toxic side effects are cytokine release syndrome (CRS). CRS is caused by the release of a large number of inflammatory factors by activated immune cells. IL-6, IL-1, and IFN-γ are all related to CRS. Any CAR-T or other immune cells that cause IFN-γ to elevate will aggravate CRS, which is more obvious in CRS level ≥ 3 [26, 27, 36, 37, 41]. Each CAR-T study uses cytokines to evaluate the activation characteristics of T cells, and basically includes IL-6, IFN-γ, TNF-α, and IL-2. The selection of other cytokines varies from study to study, including IL-1RA, IL-1β, IL-4, IL-5, IL-8, IL-10, IL-12, IL-13, IL-15, IL-17, IL-18, IL-21, IL-22, IL-23, IL-31, IL-36, monocyte chemoattractant protein (MCP)-1, perforin, granzyme B, erythropoietin, granulocyte/macrophage colony-stimulating factor (GM-CSF), soluble CD25, (sCD25), ferritin, CCL20, REG3a, ST-2, TNFRI, and elafin [1, 4, 26, 27, 28, 29, 30, 36, 37, 80, 81].

3.4.2 Cytokine detection method

Although some studies used enzyme-linked immune sorbent assay (ELISA) [31, 34] or ELISpot assay [82], recently MFC has been used in CAR-T cytokine detection with requirements for more cytokines, or subsets that secrete cytokines. Cytometric bead array (CBA) [28] or couple intracellular cytokines staining [29, 30, 36, 37] are two main kinds of cytokines assay methods by MFC, and each has its own advantages and disadvantages. The advantages of CBA are fast, simple, sensitive, repeatable, flexible, and high throughput, which can detect dozens of cytokines in a short time with rare samples [28]. However, the unique advantage of intracellular cytokines staining lies in the simultaneous detection of cellular immunophenotyping and intracellular cytokines, and it is the only one to allocate cytokines to subsets without the help of cell isolation [29, 30, 36, 37].

Clinical studies can choose one of them, but a complete study, especially a multicenter study, should use the same method from beginning to end because there is a lack of comparability between different methods.

3.5 Tumor microenvironment and immune checkpoint detection

TME is a complex network of local immune cells, stromal cells, signaling molecules and cytokines secreted by these cells. In the study of solid tumors, signal networks represented by PD1 and PDL1 have achieved remarkable results in mechanism research and immunotherapy [13, 14, 36, 37, 54]. The immune microenvironment of hematologic malignancies is more complicated. MFC can detect a variety of immune cells and immune signals, so it has become the main research tool in this field in recent years [22, 23, 24, 25, 26, 27, 36, 37].

The biggest problem of CAR-T is resistance and relapse [1, 2, 3, 4, 5, 6, 7], involving a variety of complex mechanisms [8, 9, 10, 11, 12, 13, 14, 34, 35, 40, 41, 66, 67, 72, 73, 74, 75, 76, 77, 78], among which the study of immune-suppressive signals and immune microenvironment has been the focus of attention in recent years: (1) T-cell exhaustion, effector T-cell reduction, and the increased expression of inhibiting receptors. The high expression of LAG-3 and PD-1 and low expression of TNF-α in CD8+ T cells are associated with CAR-T loss of function, which will reduce the antitumor ability of CAR-T cells and lead to CD19-positive relapse. Target expression cell recovery in PB is a signal of the weakening of CAR-T cell function. CAR-T exhaustion is one of the factors. In some studies, exhaustion-related signals, such as PD1 (CD279), LAG-3(CD223), CTLA-4(CD152), and Tim3 (CD366), are included in the CAR-T detection panel, hoping to find the role of immune checkpoints, and trying to relieve the inhibitory signals by targeted drugs, such as PD1 monoclonal antibody or PDL1-CAR-T, to acquire long-term OS [13, 14, 54, 72, 73, 74, 75, 76, 77, 78]. (2) Immune aging and age-related T-cell quality. With the introduction of theories about immune age and immunosenescence, as well as the discovery of age-related CAR-T cell phenotypes, studies begin to include immunosenescence-related markers. Senescent T cells exhibit some phenotypes, including downregulation of CD27, CD28, and upregulation of CD57, KLRG-1, Tim-3, TIGIT, and CD45RA [83]. The emergence of these phenotypes is a signal of the weakening of CAR-T cells [22, 23, 24, 25, 26, 27]. (3) Other signaling-related studies on the antagonization of the CAR-T function. When CD19-negative tumor recurrences, tumor cells may have high expression of CD123, and CD123-CAR-T cell therapy may be effective; it may be related to the increased expression of Bcl-2. Thus, monitoring Bcl-2 in tumor cells and Bcl-2 antagonist treatment in Bcl-2 highly expressed patients may be effective [72, 73, 74, 75, 76, 77, 78]. (4) Inhibitive BM microenvironment. Myeloid-derived suppressor cells (MDSC), TAMs, and Treg inhibit CAR-T cell proliferation and function. Detecting these inhibitory signals through MFC contributes to the CAR-T mechanism research. Blocking these signals can restore lymphocyte function. Combined CD30-CAR-T and anti-PD-1 therapy have showed promising results in CD30-positive lymphomas [54].

Similar to immune subsets, there are also some differences in the panels of TME and immune checkpoints. CD15/CD33/CD11b/HLA-DR/CD16/CD4/CD14/CD45 is one recommended panel to detect MDSC subgroups, and CD27, CD28, CD57, and PD1 (optional LAG-3, CTLA-4, and Tim3) may be simple supplements to common immune subsets panel for immune checkpoints and immunosenescence [22, 23, 24, 25, 26, 27]. CD123 and Bcl-2 should be added to MRD panel. Similar to the previous requirements, it is necessary to perform quality control, stick to same panel, and keep a high degree of standardization, stability, and good reproducibility.

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4. Advancement in MFC promote CAR-T study

As technology advances, MFC evolves toward more and more channels, of which mass cytometry and full spectral flow cytometry are two major trends [27, 84]. The traditional MFC is limited by fluorescence channels, so the tumor-related and immune-related assays are basically carried out separately. In future, with the introduction of more than 20 or even 40 multiparameter MFC, it will realize one complicated panel to simultaneously finish the above-related assays, saving costs and samples, and more importantly, obtaining geometric growth of big data information [27, 84].

Other MFC-related latest advances, such as single-cell sequencing, high-dimensional data analysis, and artificial intelligence, will also enter the field of CAR-T research with the application of MFC in CAR-T. These new advances will certainly promote the realization of MFC-assisted CAR-T efficacy-related factor analysis and obtain standardized treatment formula.

Therefore, with the improvement of more clinical information and more detailed MFC data, it is possible for us to obtain a formula for the best performance of CAR-T. We can obtain the prediction of each patient by bringing the number of malignant cells in different patients with different tumors, the sum of all tumor antigen expressions, immunosuppressive signals, and the immune-stimulative and immune-suppressive components of CAR-T subsets into the formula. If the corrective strategies of various inhibitory factors are added to the formula, it is expected that in future we will provide a standardized prediction of prognosis and treatment guidance for obtaining the best curative effect of CAR-T therapy.

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5. Conclusion

MFC plays a pivotal role in every step of the clinical and development process of CAR-T. The repeated validation of MFC assays with clinical efficacy may obtain the best data in future, which will promote the CAR-T study, to obtain the longest in vivo proliferation and duration of CAR-T, the best CR rate, the lowest side effects, and the highest survival rate.

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Conflict of interest

The authors declare no conflict of interest.

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Appendices and nomenclature

ALCL

anaplastic large cell lymphoma

ALL

acute lymphoblastic leukemia

allo-HSCT

allogeneic hematopoietic stem cell transplantation

AML

acute myeloid leukemia

AUC

area under the curve

CAR

chimeric antigen receptor

CAR-T

chimeric antigen receptor-modified T-cell

CBA

cytometric bead array

CR

complete remission

CRS

cytokine release syndrome

CSF

cerebrospinal fluid

DP

double positive

ECD

extracellular domain

ELISA

enzyme-linked immune sorbent assay

FMO

fluorescence minus one

GM-CSF

granulocyte/macrophage colony-stimulating factor

HL

Hodgkin lymphoma (HL)

LLOQ

lower limit of quantitation

LOD

lower limit of detection

LPD

lymphoproliferative disease

MdFI

median fluorescence intensity

MDSC

myeloid-derived suppressor cells

MFC

multiparametric flow cytometry

MFI

mean fluorescence intensity

MRD

minimal residual/measurable diseases

OS

overall survival

SOPs

standard operating procedures

TCM

central memory T cells

TEFF

effector T cells

TEM

effector memory T cells

TME

tumor microenvironment

TN

naive T cells

Treg

regulatory T cells

TSCM

stem cell memory-like T cells

References

  1. 1. Zhang X, Lu XA, Yang J, et al. Efficacy and safety of anti-CD19 CAR T-cell therapy in 110 patients with B-cell acute lymphoblastic leukemia with high-risk features. Blood Advances. 2020;4(10):2325-2338. DOI: 10.1182/bloodadvances.2020001466
  2. 2. Zhao YL, Liu DY, Sun RJ, et al. Integrating CAR T-cell therapy and transplantation: Comparisons of safety and long-term efficacy of allogeneic hematopoietic stem cell transplantation after CAR T-cell or chemotherapy-based complete remission in B-cell acute lymphoblastic leukemia. Frontiers in Immunology. 2021;12:605766. DOI: 10.3389/fimmu.2021.605766
  3. 3. Chen M, Fu M, Wang A, et al. Cytoplasmic CD79a is a promising biomarker for B lymphoblastic leukemia follow up post CD19 CAR-T therapy. Leukemia & Lymphoma. 2021;21:1-9. DOI: 10.1080/10428194.2021.1980214
  4. 4. Lu P, Liu Y, Yang J, et al. Naturally selected CD7 CAR-T therapy without genetic manipulations for T-ALL/LBL: First-in-human phase 1 clinical trial. Blood. 2022;140(4):321-334. DOI: 10.1182/blood.2021014498
  5. 5. Marofi F, Rahman HS, Al-Obaidi ZMJ, et al. Novel CAR T therapy is a ray of hope in the treatment of seriously ill AML patients. Stem Cell Research & Therapy. 2021;12(1):465. DOI: 10.1186/s13287-021-02420-8
  6. 6. Jain T, Bar M, Kansagra AJ, et al. Use of chimeric antigen receptor T cell therapy in clinical practice for relapsed/refractory aggressive B cell non-Hodgkin lymphoma: An expert panel opinion from the American Society for Transplantation and Cellular Therapy. Biology of Blood and Marrow Transplantation. 2019;25(12):2305-2321. DOI: 10.1016/j.bbmt.2019.08.015
  7. 7. Straathof K, Flutter B, Wallace R, et al. Antitumor activity without on-target off-tumor toxicity of GD2-chimeric antigen receptor T cells in patients with neuroblastoma. Science Translational Medicine. 2020;12:eabd6169
  8. 8. Keshavarz A, Salehi A, Khosravi S, et al. Recent findings on chimeric antigen receptor (CAR)-engineered immune cell therapy in solid tumors and hematological malignancies. Stem Cell Research & Therapy. 2022;13(1):482. DOI: 10.1186/s13287-022-03163-w
  9. 9. Pearson AD, Rossig C, Mackall C, et al. Paediatric strategy forum for medicinal product development of chimeric antigen receptor T-cells in children and adolescents with cancer: ACCELERATE in collaboration with the European medicines agency with participation of the Food and Drug Administration. European Journal of Cancer. 2022;160:112-133. DOI: 10.1016/j.ejca.2021.10.016
  10. 10. Wei J, Han X, Bo J, et al. Target selection for CAR-T therapy. Journal of Hematology & Oncology. 2019;12(1):62. DOI: 10.1186/s13045-019-0758-x
  11. 11. Xu X, Huang S, Xiao X, et al. Challenges and clinical strategies of CAR T-cell therapy for acute lymphoblastic leukemia: Overview and developments. Frontiers in Immunology. 2021;11:569117. DOI: 10.3389/fimmu.2020.569117
  12. 12. Marvin-Peek J, Savani BN, Olalekan OO, et al. Challenges and advances in chimeric antigen receptor therapy for acute myeloid leukemia. Cancers (Basel). 2022;14(3):497. DOI: 10.3390/cancers14030497
  13. 13. Hou AJ, Chen LC, Chen YY. Navigating CAR-T cells through the solid-tumour microenvironment. Nature Reviews. Drug Discovery. 2021;20(7):531-550. DOI: 10.1038/s41573-021-00189-2
  14. 14. Lemoine J, Ruella M, Houot R. Born to survive: How cancer cells resist CAR T cell therapy. Journal of Hematology & Oncology. 2021;14(1):199. DOI: 10.1186/s13045-021-01209-9
  15. 15. Piccoli S, Mehta D, Vitaliti A, et al. 2019 white paper on recent issues in bioanalysis: FDA immunogenicity guidance, gene therapy, critical reagents, biomarkers and flow cytometry validation (part 3 - recommendations on 2019 FDA immunogenicity guidance, gene therapy bioanalytical challenges, strategies for critical reagent management, biomarker assay validation, flow cytometry validation & CLSI H62). Bioanalysis. 2019;11(24):2207-2244. DOI: 10.4155/bio-2019-0271
  16. 16. Riva G, Nasillo V, Ottomano AM, et al. Multiparametric flow cytometry for MRD monitoring in hematologic malignancies: Clinical applications and new challenges. Cancers (Basel). 2021;13(18):4582. DOI: 10.3390/cancers13184582
  17. 17. Bras AE, de Haas V, van Stigt A, et al. CD123 expression levels in 846 acute leukemia patients based on standardized immunophenotyping. Cytometry. Part B, Clinical Cytometry. 2019;96(2):134-142. DOI: 10.1002/cyto.b.21745
  18. 18. Haubner S, Perna F, Köhnke T, et al. Coexpression profile of leukemic stem cell markers for combinatorial targeted therapy in AML. Leukemia. 2019;33(1):64-74. DOI: 10.1038/s41375-018-0180-3
  19. 19. Cherian S, Miller V, McCullouch V, et al. A novel flow cytometric assay for detection of residual disease in patients with B-lymphoblastic leukemia/lymphoma post anti-CD19 therapy. Cytometry. Part B, Clinical Cytometry. 2018;94(1):112-120. DOI: 10.1002/cyto.b.21482
  20. 20. Mikhailova E, Semchenkova A, Illarionova O, et al. Relative expansion of CD19-negative very-early normal B-cell precursors in children with acute lymphoblastic leukaemia after CD19 targeting by blinatumomab and CAR-T cell therapy: Implications for flow cytometric detection of minimal residual disease. British Journal of Haematology. 2021;193(3):602-612. DOI: 10.1111/bjh.17382
  21. 21. Sarikonda G, Pahuja A, Kalfoglou C, et al. Monitoring CAR-T cell kinetics in clinical trials by multiparametric flow cytometry: Benefits and challenges. Cytometry. Part B, Clinical Cytometry. 2021;100(1):72-78. DOI: 10.1002/cyto.b.21891
  22. 22. Peinelt A, Bremm M, Kreyenberg H, et al. Monitoring of circulating CAR T cells: Validation of a flow cytometric assay, cellular kinetics, and phenotype analysis following Tisagenlecleucel. Frontiers in Immunology. 2022;13:830773. DOI: 10.3389/fimmu.2022.830773
  23. 23. Maryamchik E, Gallagher KME, Preffer FI, et al. New directions in chimeric antigen receptor T cell [CAR-T] therapy and related flow cytometry. Cytometry. Part B, Clinical Cytometry. 2020;98(4):299-327. DOI: 10.1002/cyto.b.21880
  24. 24. Demaret J, Varlet P, Trauet J, et al. Monitoring CAR T-cells using flow cytometry. Cytometry. Part B, Clinical Cytometry. 2021;100(2):218-224. DOI: 10.1002/cyto.b.21941
  25. 25. Sarikonda G, Mathieu M, Natalia M, et al. Best practices for the development, analytical validation and clinical implementation of flow cytometric methods for chimeric antigen receptor T cell analyses. Cytometry. Part B, Clinical Cytometry. 2021;100(1):79-91. DOI: 10.1002/cyto.b.21985
  26. 26. Blache U, Weiss R, Boldt A, et al. Advanced flow cytometry assays for immune monitoring of CAR-T cell applications. Frontiers in Immunology. 2021;12:658314. DOI: 10.3389/fimmu.2021.658314
  27. 27. Michelozzi IM, Sufi J, Adejumo TA, et al. High-dimensional functional phenotyping of preclinical human CAR T cells using mass cytometry. STAR protocols. 2022;3(1):101174. DOI: 10.1016/j.xpro.2022.101174
  28. 28. He P, Tan Z, Wei Z, et al. Co-expressing LRP6 with anti-CD19 CAR-T cells for improved therapeutic effect against B-ALL. Frontiers in Oncology. 2020;10:1346. DOI: 10.3389/fonc.2020.01346
  29. 29. Xu C, Yin Y. Measuring chimeric antigen receptor T cells (CAR T cells) activation by coupling intracellular cytokine staining with flow cytometry. Methods in Molecular Biology. 2020;2108:159-165. DOI: 10.1007/978-1-0716-0247-8_14
  30. 30. Hombach A, Barden M, Hannappel L, et al. IL12 integrated into the CAR exodomain converts CD8+ T cells to poly-functional NK-like cells with superior killing of antigen-loss tumors. Molecular Therapy. 2022;30(2):593-605. DOI: 10.1016/j.ymthe.2021.10.011
  31. 31. Qin H, Cho M, Haso W, et al. Eradication of B-ALL using chimeric antigen receptor-expressing T cells targeting the TSLPR oncoprotein. Blood. 2015;126(5):629-639. DOI: 10.1182/blood-2014-11-612903
  32. 32. Kansagra AJ, Frey NV, Bar M, et al. Clinical utilization of chimeric antigen receptor T cells in B cell acute lymphoblastic leukemia: An expert opinion from the European Society for Blood and Marrow Transplantation and the American Society for Blood and Marrow Transplantation. Biology of Blood and Marrow Transplantation. 2019;25(3):e76-e85. DOI: 10.1016/j.bbmt.2018.12.068
  33. 33. Castella M, Caballero-Baños M, Ortiz-Maldonado V, et al. Point-of-care CAR T-cell production (ARI-0001) using a closed semi-automatic bioreactor: Experience from an academic phase I clinical trial. Frontiers in Immunology. 2020;11:482. DOI: 10.3389/fimmu.2020.00482
  34. 34. Maude SL, Frey N, Shaw PA, et al. Chimeric antigen receptor T cells for sustained remissions in leukemia. The New England Journal of Medicine. 2014;371(16):1507-1517. DOI: 10.1056/NEJMoa1407222 Erratum in: The New England Journal of Medicine 2016;374(10):998
  35. 35. Faude S, Wei J, Muralidharan K, et al. Absolute lymphocyte count proliferation kinetics after CAR T-cell infusion impact response and relapse. Blood Advances. 2021;5(8):2128-2136. DOI: 10.1182/bloodadvances.2020004038
  36. 36. Finney OC, Brakke HM, Rawlings-Rhea S, et al. CD19 CAR T cell product and disease attributes predict leukemia remission durability. The Journal of Clinical Investigation. 2019;129(5):2123-2132. DOI: 10.1172/JCI125423
  37. 37. Spiegel JY, Patel S, Muffly L, et al. CAR T cells with dual targeting of CD19 and CD22 in adult patients with recurrent or refractory B cell malignancies: A phase 1 trial. Nature Medicine. 2021;27(8):1419-1431. DOI: 10.1038/s41591-021-01436-0
  38. 38. Rosenthal J, Naqvi AS, Luo M, et al. Heterogeneity of surface CD19 and CD22 expression in B lymphoblastic leukemia. American Journal of Hematology. 2018;93(11):E352-E355. DOI: 10.1002/ajh.25235 PMID: 30058145
  39. 39. Pillai V, Muralidharan K, Meng W, et al. CAR T-cell therapy is effective for CD19-dim B-lymphoblastic leukemia but is impacted by prior blinatumomab therapy. Blood Advances. 2019;3(22):3539-3549. DOI: 10.1182/bloodadvances.2019000692
  40. 40. Anagnostou T, Riaz IB, Hashmi SK, et al. Anti-CD19 chimeric antigen receptor T-cell therapy in acute lymphocytic leukaemia: A systematic review and meta-analysis. The Lancet Haematology. 2020;7(11):e816-e826. DOI: 10.1016/S2352-3026(20)30277-5
  41. 41. Zhang X, Yang J, Li J, et al. Factors associated with treatment response to CD19 CAR-T therapy among a large cohort of B cell acute lymphoblastic leukemia. Cancer Immunology, Immunotherapy. 2022;71(3):689-703. DOI: 10.1007/s00262-021-03009-z
  42. 42. Fry TJ, Shah NN, Orentas RJ, et al. CD22-targeted CAR T cells induce remission in B-ALL that is naive or resistant to CD19-targeted CAR immunotherapy. Nature Medicine. 2018;24(1):20-28. DOI: 10.1038/nm.4441
  43. 43. Qin H, Ramakrishna S, Nguyen S, et al. Preclinical development of bivalent chimeric antigen receptors targeting both CD19 and CD22. Molecular Therapy - Oncolytics. 2018;11:127-137. DOI: 10.1016/j.omto.2018.10.006
  44. 44. Gomes-Silva D, Srinivasan M, Sharma S, et al. CD7-edited T cells expressing a CD7-specific CAR for the therapy of T-cell malignancies. Blood. 2017;130(3):285-296. DOI: 10.1182/blood-2017-01-761320
  45. 45. Li S, Wang X, Yuan Z, et al. Eradication of T-ALL cells by CD7-targeted universal CAR-T cells and initial test of Ruxolitinib-based CRS management. Clinical Cancer Research. 2021;27(5):1242-1246. DOI: 10.1158/1078-0432.CCR-20-1271
  46. 46. Shah NN, Johnson BD, Schneider D, et al. Bispecific anti-CD20, anti-CD19 CAR T cells for relapsed B cell malignancies: A phase 1 dose escalation and expansion trial. Nature Medicine. 2020;26(10):1569-1575. DOI: 10.1038/s41591-020-1081-3
  47. 47. Scherer LD, Brenner MK, Mamonkin M. Chimeric antigen receptors for T-cell malignancies. Frontiers in Oncology. 2019;9:126. DOI: 10.3389/fonc.2019.00126
  48. 48. Mamonkin M, Rouce RH, Tashiro H, et al. A T-cell directed chimeric antigen receptor for the selective treatment of T-cell malignancies. Blood. 2015;126(8):983-992. DOI: 10.1182/blood-2015-02-629527
  49. 49. Ou Z, Qiu L, Rong H, et al. Bibliometric analysis of chimeric antigen receptor-based immunotherapy in cancers from 2001 to 2021. Frontiers in Immunology. 2022;13:822004. DOI: 10.3389/fimmu.2022.822004
  50. 50. Miao L, Zhang J, Zhang Z, et al. A bibliometric and knowledge-map analysis of CAR-T cells from 2009 to 2021. Frontiers in Immunology. 2022;13:840956. DOI: 10.3389/fimmu.2022.840956
  51. 51. Mihályová J, Hradská K, Jelínek T, et al. Promising immunotherapeutic modalities for B-cell lymphoproliferative disorders. International Journal of Molecular Sciences. 2021;22(21):11470. DOI: 10.3390/ijms222111470
  52. 52. Ramos CA, Ballard B, Zhang H, et al. Clinical and immunological responses after CD30-specific chimeric antigen receptor-redirected lymphocytes. The Journal of Clinical Investigation. 2017;127(9):3462-3471. DOI: 10.1172/JCI94306
  53. 53. Ramos CA, Grover NS, Beaven AW, et al. Anti-CD30 CAR-T cell therapy in relapsed and refractory Hodgkin lymphoma. Journal of Clinical Oncology. 2020;38(32):3794-3804. DOI: 10.1200/JCO.20.01342
  54. 54. Sang W, Wang X, Geng H, et al. Anti-PD-1 therapy enhances the efficacy of CD30-directed chimeric antigen receptor T cell therapy in patients with relapsed/refractory CD30+ lymphoma. Frontiers in Immunology. 2022;13:858021. DOI: 10.3389/fimmu.2022.858021
  55. 55. Maucher M, Srour M, Danhof S, et al. Current limitations and perspectives of chimeric antigen receptor-T-cells in acute myeloid leukemia. Cancers (Basel). 2021;13(24):6157. DOI: 10.3390/cancers13246157
  56. 56. Mardiros A, Santos CD, McDonald T, et al. T cells expressing CD123-specific chimeric antigen receptors exhibit specific cytolytic effector functions and antitumor effects against human acute myeloid leukemia. Blood. 2013;122(18):3138-3148. DOI: 10.1182/blood-2012-12-474056
  57. 57. Bonifant CL, Szoor A, Torres D, et al. CD123-engager T cells as a novel immunotherapeutic for acute myeloid leukemia. Molecular Therapy. 2016;24(9):1615-1626. DOI: 10.1038/mt.2016.116
  58. 58. Qin H, Yang L, Chukinas JA, et al. Systematic preclinical evaluation of CD33-directed chimeric antigen receptor T cell immunotherapy for acute myeloid leukemia defines optimized construct design. Journal for Immunotherapy of Cancer. 2021;9(9):e003149. DOI: 10.1136/jitc-2021-003149
  59. 59. Pollard JA, Loken M, Gerbing RB, et al. CD33 expression and its association with Gemtuzumab Ozogamicin response: Results from the randomized phase III Children's oncology group trial AAML0531. Journal of Clinical Oncology. 2016;34(7):747-755. DOI: 10.1200/JCO.2015.62.6846
  60. 60. Willier S, Rothämel P, Hastreiter M, et al. CLEC12A and CD33 coexpression as a preferential target for pediatric AML combinatorial immunotherapy. Blood. 2021;137(8):1037-1049. DOI: 10.1182/blood.2020006921
  61. 61. Miao L, Zhang Z, Ren Z, et al. Obstacles and coping strategies of CAR-T cell immunotherapy in solid tumors. Frontiers in Immunology. 2021;12:687822. DOI: 10.3389/fimmu.2021.687822
  62. 62. Kast J, Nozohouri S, Zhou D, et al. Recent advances and clinical pharmacology aspects of chimeric antigen receptor (CAR) T-cellular therapy development. Clinical and Translational Science. 2022;15(9):2057-2074. DOI: 10.1111/cts.13349
  63. 63. Dasyam N, George P, Weinkove R. Chimeric antigen receptor T-cell therapies: Optimising the dose. British Journal of Clinical Pharmacology. 2020;86(9):1678-1689. DOI: 10.1111/bcp.14281
  64. 64. Clé DV, Hirayama AV, Alencar AJ, et al. Associação Brasileira de Hematologia, Hemoterapia e Terapia Celular consensus on genetically modified cells. I: Structuring centers for the multidisciplinary clinical administration and management of CAR-T cell therapy patients. Hematology, Transfusion and Cell Therapy. 2021;43(Suppl 2):S3-S12. DOI: 10.1016/j.htct.2021.09.001
  65. 65. Hay KA, Gauthier J, Hirayama AV, et al. Factors associated with durable EFS in adult B-cell ALL patients achieving MRD-negative CR after CD19 CAR T-cell therapy. Blood. 2019;133(15):1652-1663. DOI: 10.1182/blood-2018-11-883710
  66. 66. Khan M, Maker AV, Jain S. The evolution of Cancer immunotherapy. Vaccines (Basel). 2021;9(6):614. DOI: 10.3390/vaccines9060614
  67. 67. Strati P, Varma A, Adkins S, et al. Hematopoietic recovery and immune reconstitution after axicabtagene ciloleucel in patients with large B-cell lymphoma. Haematologica. 2021;106(10):2667-2672. DOI: 10.3324/haematol.2020.254045
  68. 68. Rabinovich PM, Zhang J, Kerr SR, et al. A versatile flow-based assay for immunocyte-mediated cytotoxicity. Journal of Immunological Methods. 2019;474:112668. DOI: 10.1016/j.jim.2019.112668
  69. 69. Xu Y, Zhang M, Ramos CA, et al. Closely related T-memory stem cells correlate with in vivo expansion of CAR.CD19-T cells and are preserved by IL-7 and IL-15. Blood. 2014;123(24):3750-3759. DOI: 10.1182/blood-2014-01-552174
  70. 70. Turtle CJ, Hanaf LA, Berger C, et al. CD19 CAR-T cells of defined CD4+:CD8+ composition in adult B cell ALL patients. The Journal of Clinical Investigation. 2016;126(6):2123-2138. DOI: 10.1172/JCI85309
  71. 71. Sommermeyer D, Hudecek M, Kosasih PL, et al. Chimeric antigen receptor-modified T cells derived from defined CD8+ and CD4+ subsets confer superior antitumor reactivity in vivo. Leukemia. 2016;30(2):492-500. DOI: 10.1038/leu.2015.247
  72. 72. Locke FL, Rossi JM, Neelapu SS, et al. Tumor burden, inflammation, and product attributes determine outcomes of axicabtagene ciloleucel in large B-cell lymphoma. Blood Advances. 2020;4(19):4898-4911. DOI: 10.1182/bloodadvances.2020002394
  73. 73. Yan ZX, Li L, Wang W, et al. Clinical efficacy and tumor microenvironment influence in a dose-escalation study of anti-CD19 chimeric antigen receptor T cells in refractory B-cell non-Hodgkin's lymphoma. Clinical Cancer Research. 2019;25(23):6995-7003. DOI: 10.1158/1078-0432.CCR-19-0101
  74. 74. de Azevedo JTC, Mizukami A, Moço PD, et al. Immunophenotypic analysis of CAR-T cells. Methods in Molecular Biology. 2020;2086:195-201. DOI: 10.1007/978-1-0716-0146-4_14
  75. 75. Deng Q , Han G, Puebla-Osorio N, et al. Characteristics of anti-CD19 CAR T cell infusion products associated with efficacy and toxicity in patients with large B cell lymphomas. Nature Medicine. 2020;26(12):1878-1887. DOI: 10.1038/s41591-020-1061-7
  76. 76. Ruella M, Xu J, Barrett DM, et al. Induction of resistance to chimeric antigen receptor T cell therapy by transduction of a single leukemic B cell. Nature Medicine. 2018;24(10):1499-1503. DOI: 10.1038/s41591-018-0201-9
  77. 77. Song MK, Park BB, Uhm JE. Resistance mechanisms to CAR T-cell therapy and overcoming strategy in B-cell hematologic malignancies. International Journal of Molecular Sciences. 2019;20(20):5010. DOI: 10.3390/ijms20205010
  78. 78. Tantalo DG, Oliver AJ, von Scheidt B, et al. Understanding T cell phenotype for the design of effective chimeric antigen receptor T cell therapies. Journal for Immunotherapy of Cancer. 2021;9(5):e002555. DOI: 10.1136/jitc-2021-002555
  79. 79. Murugesan M, Nair CK, Nayanar SK, et al. Flow cytometric enumeration of CD34+ hematopoietic stem cells: A comparison between single- versus dual-platform methodology using the International Society of Hematotherapy and Graft Engineering protocol. Asian Journal of Transfusion Science. 2019;13(1):43-46. DOI: 10.4103/ajts.AJTS_83_18
  80. 80. Jin J, Cheng J, Huang M, et al. Fueling chimeric antigen receptor T cells with cytokines. American Journal of Cancer Research. 2020;10(12):4038-4055
  81. 81. Lee DW, Santomasso BD, Locke FL, et al. ASTCT consensus grading for cytokine release syndrome and neurologic toxicity associated with immune effector cells. Biology of Blood and Marrow Transplantation. 2019;25(4):625-638. DOI: 10.1016/j.bbmt.2018.12.758
  82. 82. Ma N, Liu H, Zhang Y, et al. Identification of CD8+ T-cell epitope from multiple myeloma-specific antigen AKAP4. Frontiers in Immunology. 2022;13:927804. DOI: 10.3389/fimmu.2022.927804
  83. 83. Lian J, Yue Y, Yu W, et al. Immunosenescence: A key player in cancer development. Journal of Hematology & Oncology. 2020;13(1):151. DOI: 10.1186/s13045-020-00986-z
  84. 84. Chen M, Fu M, Zhao W, Wang A, Wu X, Gong M, et al. Full spectral flow cytometry analysis of the bone marrow immune cells in patients with myelodysplastic syndrome. International Journal of Laboratory Hematology. 11 Aug 2022. DOI: 10.1111/ijlh.13945. PMID: 35950633 [Epub ahead of print]

Written By

Hui Wang and Man Chen

Submitted: 18 October 2022 Reviewed: 02 November 2022 Published: 20 January 2023