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Immunotherapy biomarkers
Original research
Assessment and predictive ability of the absolute neutrophil count in peripheral blood for in vivo CAR T cells expansion and CRS
  1. Man Zhang1,
  2. Xiaolu Long2,
  3. Yi Xiao2,
  4. Jin Jin2,3,
  5. Caixia Chen2,
  6. Jiao Meng1,
  7. Wanying Liu2,
  8. Aichun Liu1 and
  9. Liting Chen2
  1. 1Department of Hematology, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, Heilongjiang, China
  2. 2Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
  3. 3Department of Hematology, Renmin Hospital of Wuhan University, Wuhan, China
  1. Correspondence to Dr Liting Chen; ltchen{at}tjh.tjmu.edu.cn; Dr Aichun Liu; 601733{at}hrbmu.edu.cn

Abstract

Background Chimeric antigen receptor (CAR) T cell therapy is an advanced and effective immunotherapy for relapsed or refractory B-cell malignancies. High expansion of CAR T cells in vivo and durable antitumor activity indicate a persistent therapeutic response. However, this treatment is linked to a high frequency of adverse events, such as cytokine release syndrome (CRS), which affects its efficacy and can even be life-threatening. At present, a variety of markers associated with clinical response and treatment toxicity after CAR T cells infusion have been reported. Although these biomarkers can act as effective indicators reflecting CAR T cells expansion as well as CRS, they fail to predict the expansion rate of CAR T cells. Hence, further investigation is urgent to find a new biomarker to fill this void.

Methods We analyzed the association between the absolute neutrophil count (ANC) and CAR expansion and CRS in 45 patients with B-cell malignancies from two clinical trials. We proposed that ANC could be a practical biomarker for CAR T cells expansion and CRS, and conducted a feasibility analysis on its predictive ability.

Results In this study, 17 B-cell hematological malignancy patients with anti-B-cell maturation antigen CAR-treated and 28 with CAR19/22 T-cell-treated were enrolled and divided into an ANC-absence group and an ANC-presence group. The results showed that ANC absence correlated positively with CAR expansion and the expansion rate. The ANC can be used as a predictive marker for CAR T cells expansion. Moreover, the patients with ANC absence experienced a more severe CRS, and ANC performed a predictive ability for CRS. In addition, the peak serum concentration of several cytokines involved in CRS was higher in patients with ANC absence.

Conclusion Thus, we suggest ANC as an evaluative and predictive biomarker for CAR expansion and CRS during CAR T cell therapy, which can help to maximize clinical efficacy, reduce treatment-related toxicity and prolong survival.

  • Immunotherapy
  • T-Lymphocytes

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/jitc-2023-007790

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Chimeric antigen receptor (CAR) T cell therapy is an advanced and effective immunotherapy for B-cell malignancies. At present, a variety of markers associated with clinical response and treatment toxicity after CAR T cells infusion have been reported. While these biomarkers can serve as indicators to reflect CAR T cell expansion and assess side effects, they do not have the ability to predict the expansion rate of CAR T cells.

    WHAT THIS STUDY ADDS

    • The positive effects of absolute neutrophil count (ANC) absence on enhanced CAR T cells expansion and severe cytokine release syndrome (CRS) were demonstrated in our study. We proposed for the first time ANC as a biomarker for evaluating and predicting CAR T cell expansion rate and CRS.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • In this study, we suggested a novel biomarker associated with therapeutic response and toxicities, which may be beneficial for evaluating the CAR T cells expansion and identifying CRS in patients with B-cell malignancies.

    Introduction

    Chimeric antigen receptor (CAR) T cell therapy is a promising and precise cellular immunotherapy.1 Genetically modified T lymphocytes to target tumor cells in vivo have been an enormous success in the field of cancer treatment, especially in hematological malignancies.2 3 Some clinical trials have reported a complete remission (CR) rate ranging from 28% to 68% and an overall response rate (ORR) ranging from 91% to 44% in patients with B-cell non-Hodgkin’s lymphoma (NHL), treated with CD19-targeted CAR T cells.4–6 Patients with B-cell acute lymphoblastic leukemia (ALL) after CAR T cells infusion has similar excellent efficacy, with CR rates of 62%–86%.7 8 Data from clinical trials of anti-B-cell maturation antigen CAR therapy for multiple myeloma (MM) have indicated a CR rate of 33%–83%, with ORR ranging from 73% to 100%.7 9 10

    Unlike conventional drugs, CAR T cells are considered “living drugs”, they undergo proliferation (100-fold to 100,000-fold) after antigen binding in vivo.11 Nevertheless, this process is often accompanied by certain toxicity. The most common and worrisome treatment toxicity is cytokine release syndrome (CRS).12–14 The incidence of CRS in patients with B-cell ALL and B-cell NHL treated with anti-CD19 CAR T cells has been reported to be 76%–100% and 35%–93%,15–17 with severe CRS reaching 35%–93% and 1%–27%, respectively.2 15–18

    Since the outstanding efficacy of CAR T cell therapy was established, many markers associated with clinical response and treatment toxicity have been reported. For example, CAR T cell products with a high frequency of stem central memory T (Tscm) cells and a low proportion of effector memory T cells as well as CD57+cells, inhibition of immune checkpoints such as programmed cell death protein-1 (PD-1), lymphocyte activation gene-3 (LAG-3), T cell immunoglobulin and mucin-domain containing-3 (TIM-3) and their receptors, activation of myeloid and lymphoid cells in the immune microenvironment and a variety of cytokines and chemokines are vital for a response to effective therapy and for improving expansion and persistence.19–25 CRS is a potentially life-threatening condition that results from pathologic overactivation of T cells, leading to systemic inflammation and variable clinical symptoms.26 Many biomarkers related to inflammatory cytokines, such as interleukin (IL)-6, IL-10, interferon (IFN)-γ and serum biochemical parameters (eg, C reactive protein, ferritin, lactate dehydrogenase, LDH, blood urea nitrogen) have been reported for their ability to assess and predict CRS.11 25 27 Although these biomarkers can act as effective indicators reflecting CAR T cell expansion and evaluate side effects during treatment, they fail to predict the expansion rate of CAR T cells. Hence, further investigation is urgent to find a novel biomarker to fill this void.

    Many previous studies have reported a notably high incidence of neutropenia after CAR T cell therapy. Rejeski et al identified the relationship between some biomarkers and neutropenia after CAR T cells infusion.28–31 However, few studies have reported whether such a decline in neutrophils in peripheral blood correlates with CAR expansion in vivo, and we hypothesized that neutrophil would be a biomarker for CAR expansion. The correlation between the absolute neutrophil count (ANC) and CAR copy number should be explored to test this hypothesis. In this study, we aimed to characterize the influence of neutropenia on CAR T cells expansion and CRS and to provide a biomarker for maximizing therapeutic efficacy and reducing therapeutic toxicity.

    Materials and methods

    Patients and clinical data

    This study included 18 patients from a clinical trial for relapsed or refractory MM treated with a fully human anti-B-cell maturation antigen CAR (anti-BCMA CAR), as registered with the Chinese Clinical Trial Registry (ChiCTR-OPC-16009113),32 at Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China, from October 2017 to July 2018. Twenty-eight patients with relapsed or refractory B-cell ALL/NHL treated with a murine anti-CD19 and anti-CD22 CAR T cell “cocktail” (CAR19/22) from June 2019 to December 2021 were also enrolled. This clinical trial was registered with the Chinese Clinical Trial Registry (ChiCTR-OPN-16008526)33 at Tongji Hospital. All patients in the anti-BCMA CAR cohort received lymphodepletion chemotherapy with an fludarabine and cyclophosphamide (FC) regimen (fludarabine at 25 mg/m2 and cyclophosphamide at 20 mg/kg daily) for three consecutive days (days −4 to −2) prior to CAR T cells infusion. For CAR19/22 patients were given fludarabine 25 mg/m2 and cyclophosphamide 300 mg/m2 for 3 days (days −4 to −2) as lymphodepletion chemotherapy. On the basis of the joint American Society of Clinical Oncology/Infectious Diseases Society of America consensus guidelines for cancer-related infection risk, neutropenia is defined as an ANC<1.0×10∧9/L, severe neutropenia as ANC<0.5×10∧9/L, and profound neutropenia as <0.1×10∧9/L.32 We defined ANC absence as ANC<0.01×10∧9/L for more than three consecutive days. CRS was graded according to the criteria proposed by Lee et al.33 Tumor burden was measured as the proportion of bone marrow (BM) malignant plasma cells in patients with MM, LDH levels in NHL, and the percentage of BM blasts in ALL before CAR T cells infusion.34–36

    Specimen collection

    The peripheral blood (5 mL) of patients was slowly placed in a vacuum anticoagulant collection vessel to prevent hemolysis and mixed well with the anticoagulant to prevent coagulation. The samples were uniformly stored at 4°C and processed within 24 hours to obtain ANC and CAR copy numbers. For serum collection, the blood samples were collected from the day of CAR T cells infusion using serum separator tubes and coagulated at room temperature for 30 min, and then centrifuged to remove blood cells and precipitate. The serum samples were stored at −80°C until use.

    ANC and cytokine measurements

    Routine blood tests were performed by using an automatic hematology analyzer, and the absolute neutrophil count was recorded and sorted. We used Bio-Plex Pro Human Cytokine Screening Panel, 48-Plex (Bio-Rad, Hercules, California, USA), to perform multiplex screening of 48 cytokines for all patients. Levels of serum cytokines were determined according to the manufacturer’s protocols.

    Quantification of CAR transgene copy numbers and expansion rate

    DNA was extracted from the obtained blood samples using a DNA Blood Mini Kit (catalog number 51104; Qiagen, Valencia, California, USA) and stored at −20°C after estimating the concentration and quality. DNA templates, Droplet Digital PCR Supermix, fluorescently labeled primers and probes were mixed with standards and processed using the Quantalife QX200 Droplet Digital PCR system (Bio-Rad). The droplet reader software (QX200 droplet reader (Bio-Rad)) results were represented as copies/µg gDNA for CAR. According to the clinical data of CAR copies, we calculated the expansion rate (ρ) of CAR T cells by adapting a published model.37 38

    Statistical methods

    The area under a receiving operating characteristic (ROC) curve (AUC) was obtained to assess performance in the prediction of ANC for CAR expansion and CRS. AUC is intuitive for assessing predictive power, ranging from 0 (worst outcome) to 1 (perfect outcome). The Youden Index (maximum sensitivity+specificity −1) is a summary statistic of the ROC curve used to interpret and evaluate biomarkers. The optimal cut-off is the point that optimizes the biomarker’s differentiating ability.39 Continuous variables were examined using the Student’s t-test for normally distributed data and with the Mann-Whitney U test (for independent samples) or the Wilcoxon signed-rank test (for paired samples) for non-normally distributed variables. Unordered categorical variables were analyzed via Fisher’s exact test, and ordered categorical variables were examined using a non-parametric test. Non-linear regression analysis was performed to investigate the correlation between ANC and CAR expansion rate. A p value equal to or less than 0.05 was considered significant. Statistical analyses were performed with GraphPad Prism V.9 and IBM SPSS Statistics V.25, and Adobe Illustrator 2021 was used to integrate and design figures.

    Results

    Baseline characteristics and patient grouping

    A total of 46 patients from two clinical trials in our center were invited to participate in the present study, and 1 patient who died due to a severe inflammatory response caused by bacterial infection became ineligible for the study. Seventeen patients were treated with fully human anti-BCMA CAR T cells (anti-BCMA CAR), and the other 28 patients were treated with a murine anti-CD19 and anti-CD22 CAR T cell “cocktail” (CAR19/22). Among the patients in the anti-BCMA CAR cohort, the median age was 53 years (range, 38–66), and 35.3% were 60 years of age or older. Ten patients were men, and seven patients were women (58.8% vs 41.2%). A total of 94.1% had stage III disease, and four and six had previous CAR T cell and autologous hemopoietic stem cell transplantation (auto-HSCT) treatment, respectively. 88.2% had a dose of <4×10∧6 CAR T cells/kg. A total of 94.1% of all 17 patients experienced CRS, with 70.6% suffering grade 1–2 and 23.5% grade ≥3. Among the patients in the CAR19/22 cohort (median age, 51.5 years, range, 17–69), 22 were younger than 60 years of age, and 11 were men. Among all 28 patients, 18 had diffuse large B-cell lymphoma, 1 had mantle cell lymphoma, 2 had Burkitt lymphoma, and 7 had ALL. 53.6% had stage IV disease, and 60.1% had a dose of <4×10∧6 CAR T cells/kg. None had previously undergone CAR T cell treatment, but one was given auto-HSCT treatment. A total of 21 (75.0%) patients experienced CRS, with 60.7% experiencing low-grade CRS (grade 1–2) and 14.3% grade ≥3 CRS (table 1). In the two cohorts, a total of 53.3% of patients suffered a high tumor burden. All patients were grouped according to their tumor burden level. The results showed that there was no significant difference in ANC, maximum concentration (Cmax) or CRS between patients with different tumor burden (all p>0.05) (online supplemental table S1).

    Supplemental material

    View this table:
    Table 1

    Clinical data for baseline characteristics

    To explore the association between neutropenia and CAR T cells expansion, the ANC of patients in the two cohorts from day 0 to day 14 after infusion is shown in figure 1A,B. The median onset time of ANC<0.01×10∧9/L was 3 and 4, and the median duration was 4 and 5 in the two cohorts, respectively (as shown by the dark red line in figure 1A,B). Subsequently, the patients from the two cohorts were allocated to the ANC-absence group (ANC<0.01×10∧9/L for more than three consecutive days) (anti-BCMA CAR, n=13, CAR19/22, n=5) and the ANC-presence group (ANC<0.01×10∧9/L for less than three consecutive days or not occurred) (anti-BCMA CAR, n=4, CAR19/22, n=23). The ANC level of the patients after grouping at serial time points is depicted as a line chart in figure 1C. Except for patients with CRS (anti-BCMA CAR, p=0.01, CAR19/22, p=0.002), none of the baseline factors, including age, gender, disease, disease stage, previous CAR T cell treatment, previous auto-HSCT treatment or dose of CAR T cells infusion, reached statistical significance (all p>0.05) (table 1).

    Figure 1
    Figure 1

    ANC levels after CAR T cell therapy and the influence of ANC absence on CAR expansion. (A, B) The ANC of all patients within 14 days after CAR T cell therapy, as represented by different colors bar charts; NA means not available; the patient number in red represents the ANC-absence group, and blue represents the ANC-presence group. (C) Peripheral blood ANC levels of patients from two cohorts after grouping. The mean values at each time point were represented by numerical values. (D, E) High expansion of CAR T cells (Cmax, AUC0–28d) for patients in the ANC-absence group. (F) Bar plots showing a comparison of the Tmax of CAR T cells in the ANC-absence group and ANC-presence group. (Data were statistically analyzed by Mann-Whitney tests; *, p<0.05; **, p<0.01, ***, p<0.001, ****, p<0.0001, ns, not significant.). ANC, absolute neutrophil count; AUC, area under the curve; BCMA, B-cell maturation antigen; CAR, chimeric antigen receptor; Cmax, maximum concentration.

    Sustained ANC absence was associated with high expansion of CAR T cells

    To explore the association between ANC absence and CAR expansion, we compared the peak value of CAR copies (maximum concentration, Cmax) and the AUC of CAR copies during the first 28 days after infusion (AUC0–28d) between the two groups. The Cmax and AUC0–28d in the ANC-absence group were significantly higher than those in the ANC-presence group (figure 1D,E, anti-BCMA CAR, p=0.003, p=0.03, CAR19/22, p=0.04, p=0.03), indicating that patients with sustained ANC absence had high CAR expansion. The time elapsed until the peak value appeared (Tmax) did not show a significant difference between the two groups in either cohort (figure 1F). In summary, compared with the ANC-presence group, patients with sustained ANC absence exhibited better CAR T cells expansion.

    Prediction of CAR T cells expansion rate by ANC

    To identify ANC as a predictive biomarker for CAR T cells expansion rate (ρ), we studied the association between them. A negative correlation was found between ANC and ρ via non-linear regression analysis (p<0.0001, figure 2A,B). We performed ROC analyses to identify and test the discriminatory capacity of ANC according to measures of performance. The ROC curve had an AUC of 0.73 (95% CI: 0.6565 to 0.8102, p<0.0001) in the anti-BCMA CAR cohort and 0.63 (95% CI: 0.5084 to 0.7505, p<0.05) in the CAR19/22 cohort. The results showed that the predictive ability of ANC concerning CAR expansion was confirmed (figure 2C,D). The cut-off values were 0.125 and 0.225, which maximized the Youden Index to differentiate ρ value (ρ>0 vs ρ<0) in both cohorts, with a sensitivity of 55.08% and specificity of 85.96% and a sensitivity of 50.79% and specificity of 72.41%, respectively. CAR expansion increased when ANC≤0.125×10∧9/L was observed in the anti-BCMA CAR cohort, as it was when ANC≤0.225×10∧9/L in the CAR19/22 cohort (figure 2E,F). In contrast, when ANC was less than the critical value, the rate of CAR expansion showed a downward trend. Together, these findings highlight the utility of ANC as a biomarker for identifying patients who are likely to have a high expansion rate of CAR T cells.

    Figure 2
    Figure 2

    Correlation between ANC and the CAR expansion rate. (A, B) The exponential decay model shows a negative correlation between ANC and CAR expansion rate (ρ) (p<0.0001, anti-BCMA CAR, R2=0.30, CAR19/22, R2=0.25). (C, D) Receiving operating characteristic curve using the ANC signature to predict CAR expansion (anti-BCMA CAR, AUC=0.73, p<0.0001, cut-off value=0.125, CAR19/22, AUC=0.63, p<0.05, cut-off value=0.225). (E, F) The diagnostic cut-off value has good discrimination in ANC prediction of CAR expansion. ANC, absolute neutrophil count; AUC, area under the curve; BCMA, B-cell maturation antigen; CAR, chimeric antigen receptor.

    Patients in the ANC-absence group with a higher grade and longer duration of CRS

    Although the emergence of CAR T cell treatment has dramatically improved response rates in B-cell malignancies, its utility is hampered by a unique toxicity profile. Thus, much attention has been given to such novel immune-related adverse events, especially CRS.25 40–42 To explore the CRS experienced after CAR T cells infusion and its association with ANC, we analyzed the grade, onset time, end time and duration of CRS. The patients in the ANC-absence group experienced a significantly higher CRS grade than those in the ANC-presence group (anti-BCMACAR, p<0.01, CAR19/22, p<0.01, figure 3A). The patients in the ANC-absence group experienced earlier CRS onset times and later end times. There were significant differences between the two groups in the CAR19/22 cohort and the anti-BCMA CAR cohort (p<0.01, p<0.05, figure 3B,C). In addition, there was a significantly longer CRS duration in patients in the ANC-absence group (anti-BCMA CAR, p<0.05, CAR19/22, p<0.01, figure 3D). The period to experience CRS seemed to parallel ANC<0.01×10∧9/L, and high-grade CRS (grade ≥3) often occurred after the onset of ANC<0.01×10∧9/L (figure 3E).

    Figure 3
    Figure 3

    Comparison of CRS after CAR T cells infusion in the two groups. (A) Severe CRS in the ANC-absence group. (B, C, D) Early onset time, late end time and long duration for patients in the ANC-absence group. (E) Bar graphs showing the period of ANC<0.01×10∧9/L and CRS. (F, G) Receiving operating characteristic curves for ANC predicting CRS occurrence and severe CRS suggest good performance in both cohorts (CRS occurrence, anti-BCMA CAR, AUC=0.82, p<0.0001, CAR19/22, AUC=0.67, p<0.0005, severe CRS, anti-BCMA CAR, AUC=0.68, p<0.05, CAR19/22, AUC=0.76, p<0.05). (H) The red lines represent the optimal ANC levels for maximal CAR expansion and minimal CRS in the two cohorts. Red dots represent the ANC value. ANC, absolute neutrophil count; AUC, area under the curve; BCMA, B-cell maturation antigen; CAR, chimeric antigen receptor; CRS, cytokine release syndrome.

    Therefore, we hypothesized that ANC is predictive of CRS in the same way as CAR T cells expansion. To confirm this hypothesis, correlation analysis between ANC and CRS grade was performed in both cohorts. The ROC curve of ANC predicting CRS showed an AUC of 0.82 (95% CI: 0.7646 to 0.8797, p<0.0001) in the anti-BCMA CAR cohort and 0.67 (95% CI: 0.5777 to 0.7528, p<0.0005) in the CAR19/22 cohort (figure 3F). The results showed the predictive ability of ANC to CRS. The cut-off values for the two cohorts were 0.531 and 0.303, respectively. Thus, when ANC was less than or equal to the cut-off value, a diagnosis of CRS could be made.

    High expansion of CAR T cells is clinically beneficial, but severe CRS is not. Finding ANC levels as a biomarker for the optimal outcome of maximal CAR expansion and minimal CRS is crucial for treatment response and outcome in patients. In addition, to evaluate whether ANC could be used to predict severe CRS, the predictive accuracy was assessed by calculating the AUC of the ROC curve. The results showed the predictive ability of ANC to grade ≥3 CRS in both cohorts (anti-BCMA CAR, AUC=0.68, CAR19/22, AUC=0.76, p<0.05, figure 3G). The cut-off value was 0.01 in both cohorts, which indicated that ANC<0.01×10∧9/L was usually coincident with severe CRS. According to our results, the range of ANC levels as a biomarker for maximizing CAR expansion and minimizing CRS was 0.01 to 0.125×10∧9/L in the anti-BCMA CAR cohort and 0.01 to 0.225×10∧9/L in the CAR19/22 cohort (figure 3H).

    Elevated cytokines were associated with sustained ANC absence

    Previous studies have shown that peak serum concentrations of distinct cytokines after CAR T cells infusion differ in patients with severe CRS.42 We therefore evaluated cytokine biomarkers to determine the association between ANC absence and serum concentrations of cytokines. Forty-eight cytokines were detected and quantified from 243 biological samples of 17 patients from the anti-BCMA CAR cohort. In univariable analyses, serum concentrations of cytokines were higher in patients who experienced sustained ANC absence. Among them, 15 cytokines showed a significant link to ANC absence (figure 4A, p<0.05). For these cytokines, we identified 10 involved in CRS based on previous literature,43 including IFN-γ, IL-2, IL-6, IL-10, IL-8, Interferon-inducible protein (IP)-10, monocyte chemotactic protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, MIP-1β and tumor necrosis factor (TNF)-α and focused on them (table 2). In addition, the results indicated that the trough of ANC in peripheral blood was in sync with the peak of serum cytokines and rapid CAR T cells expansion (figure 4B,C and D). We performed a pictorial presentation via a radar map for the peak time of 10 cytokine serum concentrations based on the above results (figure 4E). The median peak time was 6.8 (range, 5.8 to 7.1) days. Furthermore, CRS had the earliest onset time (median, 2 days), followed by ANC < 0.01*10∧9/L (median, 4 days) and the peak time of cytokines, all of which preceded the peak of CAR expansion (median, 12 days). Overall, ANC absence appeared to have a promoting effect on cytokines associated with CRS depending on the chronological order.

    Figure 4
    Figure 4

    Serum cytokine secretion levels after CAR T cells reinfusion. (A) A panel of 48 cytokines and a heatmap showing the p value indicating whether cytokines were significantly different between the two groups. (B, C, D) ANC levels, CAR copy numbers and cytokine serum concentrations in peripheral blood after CAR T cells infusion. (E) Radar map showing the peak time of 10 cytokine serum concentrations, and Tmax of CAR expansion, duration of CRS and ANC<0.01×10∧9/L. ANC, absolute neutrophil count; B-NGF,nerve growth factor; CAR, chimeric antigen receptor; CRS, cytokine release syndrome; FGF, fibroblast growth factor; G-CSF, granulocyte colony-stimulating factor; GRO, growth related oncogene; HGF, hepatocyte growth factor; IFN, interferon; IL, interleukin; LIF, leukemia inhibitory factor; MCP, monocyte chemotactic protein; M-CSF, macrophage colony-stimulating factor; MIF, macrophage migration inhibitory factor; MIG, monokine induced by interferon-γ; MIP, macrophage inflammatory protein; PDGF-BB, platelet-derived growth factor BB; SCF, stem cell factor; SDF, stromal cell-derived factor; Tmax, time of maximum concentration; TNF, tumor necrosis factor; VEGF,vascular endothelial growth factor.

    View this table:
    Table 2

    Peak serum concentrations of cytokines associated with cytokine release syndrome

    Our results showed that ANC absence was positively correlated with patients’ CAR expansion. The patients with ANC absence experienced a higher CRS grade, earlier CRS onset time and later end time after CAR T cells infusion. The results indicated that the peak serum concentration of several cytokines involved in CRS was higher in patients with ANC absence. In addition, our study showed the predictive capability of ANC for CAR T cells expansion and CRS. Thus, we suggest ANC as a biomarker for evaluating and predicting the CAR T cells expansion as well as assessing CRS during CAR T cell therapy.

    Discussion

    With the widespread application of live-cell-based CAR T cell therapy in hematologic malignancies, effective responses and manageable toxicity have received increasing interest among researchers in recent years. To improve clinical success, we sought to provide a novel biomarker to evaluate and predict CAR T cells expansion as well as CRS during treatment, thereby improving patient benefit.

    Rejeski et al reported that patients with B-cell lymphoma experienced neutropenia after CAR T cell therapy, and they emphasized that neutropenia was strongly association with the preconditioning regimen.28 In our study, ANC showed a dramatic decline (days 0–2) before the CAR T cell exponential expansion (days 2–8). All patients were divided into an ANC-absence group and an ANC-presence group. Then, we observed that patients with ANC absence had higher expansion of CAR T cells. The results showed that a sustained decrease in ANC indicated a rapid expansion rate. The AUC of the ROC curve indicated good performance for ANC in predicting the expansion rate of CAR T cells. In summary, a brief low level of ANC or moderate neutropenia detected in the peripheral blood may indicate poor expansion, which will help doctors make a quick diagnosis within a transient treatment window. Chong et al have reported that the patients with B-cell lymphoma had re-expansion of CAR T cells in peripheral blood and achieved clinical responses after receiving anti-PD-1 therapy. Perhaps anti-PD-1 therapy could be an appropriate intervention regimen for patients with moderate neutropenia.44

    The predictive effect of ANC on CAR expansion was indicated in our study, and the results showed that the patients with ANC absence had higher CAR T cells expansion. However, there is no direct evidence that ANC absence could promote CAR T cells expansion. Low neutrophil has been reported to indicate a suppressed and unrecovered BM,45 which bears some resemblance to aplastic anemia, a syndrome of hematopoietic failure caused by autoimmune BM damage. In addition, the increased Tscm cells and reduced regulatory T cell (Treg) and monocytic myeloid-derived suppressor cells (M-MDSC) have been reported in patients with acquired aplastic anemia.46–48 Previous studies have demonstrated that the addition of Tscm cells to CAR products was associated with enhanced CAR T cells expansion in patients with B-cell malignancies,49 and the presence of Tregs or M-MDSC could markedly hinder the expansion and antitumor efficacy of CAR T cells.48 50 Based on these reports, we hypothesized that ANC absence may promote CAR expansion by influencing the percentage of Treg, M-MDSC and Tscm in the circulation. However, it is possible that the ANC absence is not directly related to CAR T cells expansion but rather is just a biomarker for immune suppression and that the mechanism is related to suppressive cell populations that are dysregulated in these subjects.

    According to our findings, ANC absence is positively associated with severe CRS, and the ROC curve of ANC for predicting CRS showed good performance. Thus, patients with long-term decreased ANC are prone to earlier and more severe CRS, clinicians should pay more attention to diagnosis and perform symptomatic treatment quickly. Consequently, our results showed that ANC may increase the occurrence of CRS by increasing the peak serum concentrations of cytokines. Regrettably, the underlying pathophysiologic mechanism remains unclear. We hypothesized that sustained ANC absence after CAR T cells infusion leads to a negative feedback mechanism to promote cytokine secretion. Although this hypothesis was not tested in this study, it will be the focus of subsequent research.

    We highlight the clinical potential of ANC as a novel biomarker for evaluating CAR T cells expansion and predicting the expansion rate as well as assessing CRS during treatment. Further investigations are warranted to establish a thorough understanding of the mechanisms with the objective of benefiting more patients with cancer. In summary, a suitable biomarker might contribute to improving therapeutic efficacy and toxicity management.

    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study was approved by the medical ethics committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. ChiCTR-OPC-16009113; ChiCTR-OPN-16008526. Participants gave informed consent to participate in the study before taking part.

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    Supplementary materials

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    Footnotes

    • MZ, XL and YX contributed equally.

    • Correction notice This article has been corrected since it was first published online. Man Zhang, Xiaolu Long and Yi Xiao have now been listed as equal contributors and Aichun Liu and Liting Chen have been listed as co-corresponding authors.

    • Contributors MZ supplemented data collection, analyzed the data and wrote, revised and approved the manuscript. XL and YX conducted preliminary data collection. JJ, CC, WL and JM participated in collating data and giving advice. AL and LC provided advice, supervised study and approved submission to the journal. All the authors read and approved the manuscript and agreed to be responsible for all aspects of this work. AL and LC agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

    • Funding This work was supported by the National Natural Science Foundation of China (82270238).

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.