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Abstract

BACKGROUND:

Although risk stratification of mantle cell lymphoma (MCL) is most frequently performed using the simplified MCL International Prognostic Index (sMIPI), the identification of host-related factors and tumor microenvironment, including absolute monocyte counts (AMC) and peripheral blood T lymphocyte subsets, especially absolute natural killer cell counts (ANKC) has been suggested to be critical in the prediction of prognosis and the guidance of treatment.

OBJECTIVE:

This study was aimed at investigating whether peripheral blood ANKC and AMC at diagnosis had an impact on MCL prognosis.

METHODS:

A total of 92 newly diagnosed MCL patients was enrolled in this retrospective study. Flow cytometric analysis was conducted on fresh peripheral blood samples with a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA, USA).

RESULTS:

The median follow-up was 42 months (range, 2–144 months) and the median overall survival (OS) of all cases was 45 months. High AMC ( $>$ 0.6 $\times$ 10 ${}^{9}$ /L) was the parameter associated with inferior progression free survival (PFS) ( $P=$ 0.044) and poor OS ( $P=$ 0.028) while low ANKC ( $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L) was associated with unfavorable OS ( $P=$ 0.023) by univariable analysis. Multivariable analysis revealed that only low ANKC ( $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L) was statistically significant in worse OS ( $P=$ 0.009) independent of sMIPI.

CONCLUSIONS:

Low ANKC ( $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L) proved to be a significant predictor of inferior OS in patients with MCL.

Keywords

Mantle cell lymphoma absolute natural killer cell counts absolute monocyte counts prognosis

1. Introduction

Mantle cell lymphoma (MCL), a distinct subtype of B cell non-Hodgkin lymphoma (NHL), represents 3%–6% of all non-Hodgkin lymphoma. In addition to classical histology, in more than 95% cases, MCL patients have a cytogenetic feature of chromosomal translocation t (11; 14) (q13; q32), resulting in the overexpression of cyclin D1 and deregulation of cell cycle. Generally, patients with MCL experience a median overall survival (OS) of 3–5 years [1]. The currently used intensive treatment protocols including anti-CD20 antibody, high-dose cytarabine and autologous stem cell transplantation increased the response rate and remission duration but have failed to improve long-term OS so far. The simplified MCL International Prognostic Index (sMIPI), incorporating Eastern Cooperative Oncology Group (ECOG) performance status, age, leukocyte count and lactic dehydrogenase (LDH) was formulated in clinical routine to identify patient risk groups with different courses of disease [2]. Nonetheless, as sMIPI was derived from patients with advanced stage disease in the pre-rituximab era, adoption of the index has been confined since it has been shown that it inadequately separates low and intermediate risk group patients. To improve outcome and minimize treatment-related complications, additional parameters including Ki-67, TP53, serum $\beta$ 2-microglobulin ( $\beta$ 2-MG) have been assessed to enable risk-adapted treatment strategies [3, 4, 5]. Therefore, it is urgent to seek reliable and easily applicable prognostic factors for individual risk assessment in MCL.

Tumor microenvironment and host immunity are significantly associated with outcome in patients with MCL. Natural killer (NK) cells, as important components of the innate immune response, play crucial roles in eliminating viruses, regulating dendritic cells and killing malignant cells [6]. Kim et al. revealed that low NK cell counts at diagnosis are associated with poor clinical outcomes in non-germinal center (non-GC) diffuse large B-cell lymphoma (DLBCL) patients treated with R-CHOP therapy [7]. As reported by Shafer et al., low NK cell counts in peripheral blood are associated with inferior OS in patients with follicular lymphoma (FL) [8]. However, no research to date has focused on the predictive role of absolute natural killer cell counts (ANKC) in the progression of MCL.

The present study aimed to evaluate the prognostic relevance of absolute monocyte counts (AMC) and ANKC and examine whether ANKC could be served as an independent prognostic parameter for progression free survival (PFS) and OS.

2. Materials and methods

2.1 Patients

One hundred and thirteen consecutive subjects histologically newly diagnosed MCL patients and detailed T/NK cell subsets at admission between April 2006 and November 2017 were enrolled in this retrospective study from the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital (Nanjing, China). This study was approved by the Institutional Review Boards of our hospital. In consideration of the confounding effects of different medications, we eliminated 21 patients who took palliative care or abandon treatment or disrupt treatment for economic and other causes. Diagnosis in accordance with World Health Organization (WHO) classification 2008 should be dependent on an operative specimen, preferably a lymph node biopsy. Additionally, detection of t (11; 14) (q13; q32) and overexpression of cyclin D1 must be sufficient [9]. Laboratory measurements consisting of complete blood count (CBC), blood chemistry, imageological examination such as computed tomography (CT) and positron emission tomography (PET) of whole body as well as bone marrow aspiration and biopsy were obtained within 24 h after first admission. Baseline clinical characteristics were entirely available, including gender, age, bone marrow involvement (BMI), Ann Arbor stage, ECOG score, B symptoms, leukocyte count, serum lactic dehydrogenase (LDH), $\beta$ 2-MG as well as albumin (ALB). The experiments were undertaken with the understanding and written consent of each subject, and the study conformed with The Code of Ethics of the World Medical Association (Declaration of Helsinki), printed in the British Medical Journal (18 July 1964).

2.2 Peripheral ANKC and AMC at diagnosis

Flow cytometric analysis was conducted on fresh peripheral blood samples with a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA, USA). All murine anti-human mAbs, offered by BD Biosciences (San Jose, CA, USA), including anti-CD3-FITC, anti-CD4-PE, anti-CD8-APC, anti-CD16-PE, anti-CD19-APC and anti-CD56-APC were used to stain peripheral lymphocytes. T/NK cell subsets were counted for all patients at diagnosis. ANKC refers to CD3-CD16+ and/or CD56+ lymphocytes. Combined with the simultaneous white blood cell (WBC), the counts of NK cell subset were calculated from the percentages collected from peripheral blood flow cytometry (PBFCM). The AMCs were obtained from routine complete blood counts.

2.3 Treatment decision at diagnosis

Patients younger than 60 years old received a hyper-CVAD regimen (cyclophosphamide, doxorubicin, vincristine and dexamethasone) alternated with the MA regimen (high-dose methotrexate and cytarabine). However, patients $>$ 60 years old in good condition received a modified hyper-CVAD regimen while those in poor condition received CHOP-like (cyclophosphamide, vincristine, doxorubicin and prednisolone) regimen. In all cases, 57 (62.0%) patients received immunochemotherapy which contained rituximab, while 35 (38.0%) received chemotherapy alone. The dose of rituximab was 375 mg/m ${}^{2}$ in all rituximab-based chemoimmunotherapies. All patients received a median of 6 cycles (range, 3–8 cycles) of treatment.

2.4 Statistical analysis

For the entire cohort, the OS and the PFS were the end points for the prognostic analyses. OS was defined as the time between diagnosis and death by any cause or last follow-up. PFS was calculated as the time from the initial diagnosis to the time of progression, relapse from response, death due to any cause or last follow-up. All statistical analyses were performed using SPSS for Windows (version 21.0; IBM Corporation, Armonk, NY, USA) and Graphpad Prism 6. The best cut-off values were determined by x-tile according to OS. The distribution of OS and PFS was estimated using the Kaplan-Meier method and statistical significance was assessed using the two-sided log-rank test. The Cox proportional hazards models was established for the estimation of hazard radio and its confidence interval in both univariable and multivariable analysis. Univariable analysis was performed with each potential prognostic factor. Multivariable proportional hazards regression was performed with statistically significant factors from the univariable analysis (factors with $P$ -values less than 0.05). To ensure precise model prediction without complications caused by overlapping factors, high priority factors were entered for multivariable analysis and low priority factors were removed. Comparisons of AMC and ANKC as continuous parameters in different groups were described using Mann-Whitney U test and Kruskal-Wallis test for unpaired samples. All statistical tests were two-sided, with $P$ -values of 0.05 or less denoting statistical significance.

Table 1
Baseline clinical characteristics of 92 patients with mantle cell lymphoma

Patient characteristics	Patients	(%)
(available data/92)	( $N=$ 92)
Gender (92/92)
Male	69	75.0
Female	23	25.0
Age (92/92)
$>$ 60 years	50	54.3
$\leqslant$ 60 years	42	45.7
ECOG-PS (92/92)
0–1	78	84.8
2–4	14	15.2
B symptoms (92/92)
Yes	40	43.5
No	52	56.5
Annor Arbor stage (92/92)
I–II	6	6.5
III–IV	86	93.5
BMI (92/92)
Yes	55	59.8
No	37	40.2
sMIPI (92/92)
Low risk (0–3)	43	46.7
Intermediate risk (4–5)	27	29.3
High risk (6–11)	22	23.9
Chemotherapy (92/92)
Including rituximab	57	62.0
Not including rituximab	35	38.0
LDH (92/92)
$>$ NUV	23	25.0
$\leqslant$ NUV	69	75.0
WBC (92/92)
$>$ NUV	20	21.7
$\leqslant$ NUV	72	78.3
$\beta$ 2-MG (86/92)
$>$ NUV	67	77.9
$\leqslant$ NUV	19	22.1
ALB (91/92)
$<$ NLV	47	51.6
$\geqslant$ NLV	44	48.4

ECOG, Eastern Cooperative Oncology Group; BMI, bone marrow involvement; sMIPI, simplified mantle cell lymphoma International Prognostic Index; LDH, serum lactate dehydrogenase; NUV, normal upper value; WBC, white blood cells; $\beta$ 2-MG, serum beta-2 microglobulin level; ALB, albumin; NLV, normal lower value.

Table 2

Correlations between AMC and ANKC in patients with mantle cell lymphoma and patient characteristics

Variables	Median AMC	$P$	Median ANKC	$P$
	(range, $\times$ 10 ${}^{9}$ /L)	value	(range, $\times$ 10 ${}^{9}$ /L)	value
Gender
Male	0.50 (0.02–9.33)	0.010	0.24 (0.04–6.14)	0.404
Female	0.35 (0.02–2.44)		0.23 (0.06–4.03)
Age
$>$ 60 years	0.50 (0.02–9.33)	0.064	0.26 (0.04–6.14)	0.059
$\leqslant$ 60 years	0.38 (0.10–1.98)		0.19 (0.05–0.84)
ECOG-PS
0–1	0.45 (0.02–9.33)	0.640	0.25 (0.04–6.14)	0.268
2–4	0.53 (0.02–1.98)		0.19 (0.05–1.93)
B symptoms
Yes	0.57 (0.02–9.33)	0.002	0.30 (0.04–6.14)	0.095
No	0.38 (0.04–1.29)		0.20 (0.06–0.88)
LDH
$>$ NUV	0.58 (0.02–2.44)	0.087	0.16 (0.04–1.33)	0.394
$\leqslant$ NUV	0.40 (0.02–9.33)		0.25 (0.05–6.14)
$\beta$ 2-MG
$>$ NUV	0.48 (0.02–9.33)	0.261	0.23 (0.04–6.14)	0.767
$\leqslant$ NUV	0.37 (0.10–0.90)		0.23 (0.06–0.75)
ALB
$<$ NLV	0.53 (0.02–2.60)	0.136	0.25 (0.04–1.93)	0.256
$\geqslant$ NLV	0.40 (0.10–9.33)		0.21 (0.05–6.14)

$P$ vale $<$ 0.05 in bold is statistically significant. AMC, absolute monocyte count; ANKC, absolute natural killer cell counts; ECOG, Eastern Cooperative Oncology Group; LDH, serum lactate dehydrogenase; NUV, normal upper value; $\beta$ 2-MG, serum beta-2 microglobulin level; ALB, albumin; NLV, normal lower value.

Figure 1.

Progression-free survival and overall survival of 92 patients with mantle cell lymphoma according to absolute monocyte counts (AMC) and absolute natural killer cell counts (ANKC) at time of diagnosis, by Kaplan-Meier estimation.

3. Results

3.1 Patient characteristics

The baseline clinical characteristics of 92 enrolled patients with MCL at admission were presented in Table 1. Of the 92 patients whose age ranged from 28 to 78 years, approximately 55% of them were over 60 years of age and 69 (75.0%) were male, which showed a striking male predominance. The majority of patients (93.5%) had advanced disease (Ann Arbor stage III–IV) and 59.8% had BMI. Elevated LDH was shown in 23 (25.0%) patients. B symptoms were found in 40 (43.5%) patients. Forty-seven (51.6%) patients had decreased ALB prior to treatment, while 67 (77.9%) patients had $\beta$ 2-MG higher than normal upper value (NUV). The low risk, intermediate risk and high risk patients based on sMIPI score accounted for 46.7%, 29.3% and 23.9%, respectively. The median AMC and ANKC were 0.47 $\times$ 10 ${}^{9}$ /L (range, 0.02–9.33 $\times$ 10 ${}^{9}$ /L) and 0.24 $\times$ 10 ${}^{9}$ /L (range, 0.04–6.14 $\times$ 10 ${}^{9}$ /L), respectively. With the use of x-tile plots, the cut-off point at 0.60 $\times$ 10 ${}^{9}$ monocyte cells/L and 0.1 $\times$ 10 ${}^{9}$ /L NK cells/L yielded the highest difference in OS. As far as our single- center was concerned, 70 patients (76.1%) had a low level of AMC ( $\leqslant$ 0.6 $\times$ 10 ${}^{9}$ /L) and 78 (84.8%) had high ANKC ( $>$ 0.1 $\times$ 10 ${}^{9}$ /L). The follow-up outcome of 92 MCL patients enrolled in our study was obtained on 1 February 2018, until which 52 (56.5%) patients progressed and 36 (39.1%) died. The median follow-up was 42 months (range, 2–144 months) and the median OS of all cases was 45 months. The 1-, 3-, and 5-year OS was 72.0%, 47.0%, and 36.0%, respectively.

3.2 Baseline patient characteristics in relation to AMC and ANKC

The baseline characteristics according to AMC and ANKC are described in Table 2. A statistically evident dominance was identified that high AMC was more likely in men ( $P=$ 0.010) and patients with B symptoms ( $P=$ 0.002). However, in contrast, no significant differences were found between high ANKC group and low ANKC group according to other clinical characteristics.

Table 3
Univariable Cox regression analysis of the main factors for PFS and OS

Variable	Univariable analysis (PFS)		Univariable analysis (OS)
	HR (95% CI)	$P$ value	HR (95% CI)	$P$ value
Sex (female)	1.161 (0.613–2.198)	0.647	1.765 (0.732–4.256)	0.206
Age $>$ 60 years	1.406 (0.808–2.444)	0.228	1.858 (0.937–3.682)	0.076
ECOG-PS $\geqslant$ 2	1.496 (0.748–2.991)	0.255	1.543 (0.636–3.747)	0.338
B symptoms (yes)	2.217 (1.272–3.863)	0.005	3.957 (1.970–7.945)	$<$ 0.001
BMI (yes)	1.383 (0.787–2.429)	0.260	2.800 (1.319–5.941)	0.007
sMIPI	1.540 (1.110–2.136)	0.010	1.778 (1.194–2.646)	0.005
Chemotherapy
Not including rituximab	1.370 (0.789–2.377)	0.263	1.616 (0.829–3.150)	0.159
LDH $>$ NUV	1.995 (1.109–3.589)	0.021	2.661 (1.344–5.268)	0.005
WBC $>$ NUV	1.558 (0.825–2.941)	0.172	2.380 (1.156–4.902)	0.019
$\beta$ 2-MG $>$ NUV	1.995 (0.892–4.462)	0.093	3.759 (1.142–12.377)	0.029
ALB $<$ NLV	1.729 (0.974–3.069)	0.062	3.787 (1.772–8.091)	0.001
AMC $>$ 0.6 $\times$ 10 ${}^{9}$ /L	1.899 (1.016–3.547)	0.044	2.347 (1.095–5.035)	0.028
ANKC $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L	1.755 (0.898–3.431)	0.100	2.525 (1.134–5.624)	0.023

$P$ value $<$ 0.05 in bold is statistically significant. PFS, progression-free survival; OS, overall survival; ECOG, Eastern Cooperative Oncology Group; BMI, bone marrow involvement; sMIPI, simplified mantle cell lymphoma International Prognostic Index; LDH, serum lactate dehydrogenase; NUV, normal upper value; WBC, white blood cells; $\beta$ 2-MG, serum beta-2 microglobulin level; ALB, albumin; NLV, normal lower value; AMC, absolute monocyte count; ANKC, absolute natural killer cell counts.

Table 4

Multivariable Cox regression analysis of the main factors for PFS and OS

Variable	Multivariable analysis (PFS)		Multivariable analysis (OS)
	HR (95% CI)	$P$ value	HR (95% CI)	$P$ value
sMIPI	1.454 (1.025–2.063)	0.036	1.720 (1.103–2.683)	0.017
AMC $>$ 0.6 $\times$ 10 ${}^{9}$ /L	1.495 (0.774–2.889)	0.232	1.637 (0.705–3.800)	0.251
ANKC $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L	–	–	2.930 (1.309–6.651)	0.009

$P$ value $<$ 0.05 in bold is statistically significant. PFS, progression-free survival; OS, overall survival; sMIPI, simplified mantle cell lymphoma International Prognostic Index; AMC, absolute monocyte count; ANKC, absolute natural killer cell counts.

3.3 Prognostic impact of AMC, ANKC and clinical outcomes in MCL

In the current study, high AMC, low ANKC and other relevant variables were subjected to Cox regression analyses for further research of their prognostic significance. In patients with low AMC, the median PFS and OS were 29 months (range, 2–83 months) and 53 months (range, 2–109 months) respectively, which were significantly better compared to patients with high AMC, in whom the median PFS was 17 months (range, 1–56 months) and median OS was 18 months (range, 4–56 months) ( $P=$ 0.039, $P=$ 0.023) (Fig. 1A and B). As for patients with lower ANKC ( $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L), they had a remarkably shorter OS than those with higher ANKC ( $>$ 0.1 $\times$ 10 ${}^{9}$ /L) ( $P=$ 0.018) even though the effect of ANKC on PFS was not statistically evident, with a $P$ value of 0.092 indicating a tendency toward significance (Fig. 1C and D). The 3-year OS was 51.0% in patients with low AMC group ( $<$ 0.6 $\times$ 10 ${}^{9}$ /L) vs. 39.0% in those with high AMC group ( $\geqslant$ 0.6 $\times$ 10 ${}^{9}$ /L). With respect to ANKC, the The 3-year OS was 25.0% in patients with low ANKC group ( $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L) vs. 50.0% in those with high ANKC group ( $>$ 0.1 $\times$ 10 ${}^{9}$ /L).

Figure 2.

Subgroup survival analysis of sMIPI grades (A), age (B) for overall survival (OS). sMIPI, simplified mantle cell lymphoma International Prognostic Index.

Figure 3.

Progression-free survival and Overall survival of 57 patients taking rituximab-containing regimens with mantle cell lymphoma according to ANKC at time of diagnosis, by Kaplan-Meier estimation.

Figure 4.

Progression-free survival and Overall survival of 92 patients with mantle cell lymphoma according to ANKC to AMC ratio (NKMR) at time of diagnosis, by Kaplan-Meier estimation.

Tables 3 and 4 summarize the univariable and multivariable Cox regression analyses of PFS and OS for potential risk predictors in MCL. In consideration of the limited data, only six cases in our cohort had stage I/II disease, so we did not evaluate the influence of staging. Univariable Cox regression analysis showed that B symptoms ( $P=$ 0.005), high sMIPI score ( $P=$ 0.010), LDH $>$ NUV ( $P=$ 0.021) and AMC $>$ 0.6 $\times$ 10 ${}^{9}$ /L ( $P=$ 0.044) were related to inferior PFS. In terms of OS, parameters including B symptoms ( $P<$ 0.001), BMI ( $P=$ 0.007), high sMIPI score ( $P=$ 0.005), LDH $>$ NUV ( $P=$ 0.005), WBC $>$ NUV ( $P=$ 0.019), $\beta$ 2-MG $>$ NUV ( $P=$ 0.029), ALB $<$ NLV ( $P=$ 0.001), AMC $>$ 0.6 $\times$ 10 ${}^{9}$ /L ( $P=$ 0.028) and ANKC $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L ( $P=$ 0.023) had adverse effects according to univariable analysis results (Table 3). In multivariable Cox regression analysis, we enrolled sMIPI, AMC and ANKC in order to avoid multicollinearity. High sMIPI score (HR $=$ 1.720, 95% CI: 1.103–2.683, $P=$ 0.017), and ANKC $\leqslant$ 0.1 $\times$ 10 ${}^{9}$ /L (HR $=$ 2.930, 95% CI: 1.309–6.651, $P=$ 0.009) were independent risk factors for inferior OS while only high sMIPI score (HR $=$ 1.454, 95% CI: 1.025–2.063, $P=$ 0.036) was still statistically evident for poorer PFS (Table 4).

3.4 Subgroup evaluation of ANKC in MCL combined with poor prognostic factors

We investigated the influence of ANKC at diagnosis combined with sMIPI and age for MCL patients. In subgroup analysis of sMIPI score, we separated our 92 MCL patients into two categories: 70 in the low- to intermediate-risk group (sMIPI 0–5) and 22 in the high- risk group (sMIPI 6–11). We conducted a survival analysis for OS based on specific prognostic risk, as is illustrated in Fig. 2. Obviously, low ANKC was a significant risk predictor for patients in low- to intermediate-risk group ( $P=$ 0.005, Fig. 2A), but was not related to worse OS in high-risk MCL patients ( $P=$ 0.817, Fig. 2A), indicating that ANKC may serve as a vital role in determining risk stratification of patients at low- to intermediate-risk. To accurately identify the prognostic value of ANKC, we also analyzed the role of ANKC in subgroups identified by age. In 42 patients with age $<$ 60 years old, OS was significantly superior in those with high ANKC ( $>$ 0.1 $\times$ 10 ${}^{9}$ /L) ( $P<$ 0.001, Fig. 2B). To sum up, as mentioned above, even if patients were classified as low- to intermediate-risk or age $<$ 60 years, the OS remained shorter in the low ANKC group.

Moreover, as is reflected in Fig. 3, patients who received chemotherapy including rituximab obtained a better OS in high ANKC group compared to low ANKC group ( $P=$ 0.024, Fig. 3B). We further investigated the impact of the ANKC to AMC ratio (NKMR) for MCL patients. The cut-off value of NKMR caculated by x-tile was 0.2. Kaplan-Meier curves revealed that high ANKC to AMC ratio was significantly associated with superior OS ( $P=$ 0.026, Fig. 4) with a median OS of 53 months (range, 2–109 months).

4. Discussion

To our knowledge, the host immune system and tumor microenvironment covering lymphoma cells, stromal cells, monocytes/macrophages and immune cells play extremely vital parts in the pathogenesis and progress of lymphoma. As far as monocyte is concerned, von Hohenstaufen et al. defined 0.5 $\times$ 10 ${}^{9}$ /L as cut-off value for AMC, and found elevated circulating AMC ( $>$ 0.5 $\times$ 10 ${}^{9}$ /L) was a negative prognostic marker in MCL [10]. As long ago as 1939, Ebert and Florey reported the discovery that monocytes emigrated from blood vessels and developed into macrophages in the tissues [11]. Tumor-associated macrophages (TAM) have been reported to have an influence on tumor progression as a part of the tumor microenvironment in many neoplasms, including classic Hodgkin’s lymphoma (cHL) and peripheral T-cell lymphoma (PTCL) [12, 13]. TAMs in the tumor microenvironment are recruited from tumors and differentiated into polarized M2 macrophages that produce numerous cytokines, chemokines and growth factors, resulting in cancer progression and suppression of anti-tumor immune system [14, 15]. Besides, multiple studies have shown that massive aggregation of TAMs in the tumor site is associated with aggressive features and declining survival outcomes in hematological malignancies [16] though only B symptoms and males were found linked to high AMC in our study. Nevertheless, rarely has any study to date investigated the association between lymphocyte counts and MCL, especially ANKC. Recent evidence has described that NK cells, in addition to direct cytolytic effect against tumor cells, may also shape the adaptive immune response toward a T helper 1 (Th1) profile, which is favorable for antitumor responses [17]. As a matter of fact, NK cells can be divided according to differential cell-surface expression of CD16 and CD56 into two subsets, defined as CD56 ${}^{\text{dim}}$ and CD56 ${}^{\text{bright}}$ cells respectively. CD16+CD56 ${}^{\text{dim}}$ NK cells make up approximately 90% of NK cells in the blood, whereas the remainders are CD16-CD56 ${}^{\text{bright}}$ NK cells [18]. Various functions were performed in these two NK-cell subsets: CD16-CD56 ${}^{\text{bright}}$ NK cells generate a greater amount of cytokines such as interferon (IFN), tumor necrosis factor (TNF), interleukin-13 (IL-13) and interleukin-10 (IL-10), while CD16+CD56 ${}^{\text{dim}}$ NK cells are abundant in intracellular perforin and exert enhanced cytotoxicity [19, 20]. Thus, a better recognition of NK cell subset may contribute to our better understanding of the crosstalk between NK cells and MCL.

Given the importance of NK cells in the tumor microenvironment, great concern has been focused on allogeneic NK cell therapy in several preclinical or clinical trials targeting breast, ovarian, non-Hodgkin lymphoma and non-small cell lung cancer [21, 22]. Iliopoulou et al. revealed that repetitive infusions of allogeneic, in vitro activated and expanded with interleukin-15 (IL-15)/hydrocortisone (HC) NK cells, in combination with chemotherapy are safe and potentially clinically effective in non-small cell lung cancer [22]. Additionally, Ishikawa et al. demonstrated that NK cell-rich effector cells could be expanded ex vivo from peripheral blood mononuclear cells (PBMCs) in patients with recurrent malignant glioma and that NK cell therapy was safe and partially effective in patients suffering this malignancy [23]. Thus, appropriate NK cell therapy might be applied in MCL in future with more clinical evidence.

In our cohort, the majority of MCL patients took rituximab-containing regimens, which give us a feasible interpretation for the possible connection between low ANKC and poor OS. As previously stated, the OS was better in the high ANKC group among patients took rituximab-containing regimens. Rituximab, is a well-known murine/human chimeric monoclonal antibody (mAb) that binds to CD20 on the surface of human B cells. Substantial evidences have described that rituximab exerts excellent anti-neoplastic effect in malignant B cell lymphomas, involving four signaling pathways: antibody-dependent cell-mediated cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), direct signaling triggering apoptosis, and increased sensitivity to chemotherapy [24]. Among these pathways, ADCC seems to have overwhelming advantage at anti-tumor activity, by which rituximab recruits NK cells towards malignant B cells via CD16, and the NK cells subsequently kill the malignant cells. Besides, CD16 can activate NK cells locally, producing cytokines which enhance ADCC mediated by other receptors and other cells [25]. Veeramani et al. also confirmed that NK activation occurs within 4 hours of rituximab infusion in subjects with the high-affinity CD16 polymorphism but not those with the low-affinity CD16 polymorphism [26]. Therefore, it makes sense theoretically that higher ANKC and rituximab-induced cytotoxicity are more associated with the preferable OS. These results may remind us many new agents and combinations targeting the activation of NK cells, such as lenalidomide and ibrutinib. Lenalidomide is reported to be an immunomodulatory agent clinically beneficial for patients with relapsed or refractory MCL. Hagner et al. demonstrated that lenalidomide enhanced NK cell-mediated cytotoxicity against MCL cells primarily via increased lytic immunological synapse formation and secretion of granzyme B instead of direct cytotoxic effects against MCL cells [27]. Furthermore, several studies have proved that lenalidomide and ibrutinib play a vital role in augmenting rituximab-dependent NK cell-mediated cytotoxicity [28, 29], which may provide beneficial strategies for MCL patients.

In this retrospective study, our findings suggested that the ANKC value 0.1 $\times$ 10 ${}^{9}$ /L was the most discriminative cut-off value. A low level of ANKC was correlated with inferior OS and it was an independent negative prognostic marker for OS. In subgroup analyses, the OS was still poorer in the low ANKC group among patients with age $<$ 60 years or at low- to intermediate-risk. Since low ANKC was not a significant risk predictor for inferior OS in high risk grade (sMIPI 6–11) disease and in patients with $>$ 60 years, we can not rule out the possibility that for patients in high risk group (sMIPI 6–11) and with age $>$ 60 years, the OS tended to be more influenced by the lymphoma effect, whereas the OS of patients in low- to intermediate-risk grade (sMIPI 0–5) and with age $<$ 60 years, were more likely to be influenced by non-lymphoma effects, including tumor microenvironment and host-related elements. On the other hand, another possible explanation may be owing to the limited number of patients with low ANKC in sMIPI 6–11 and age $>$ 60 years groups. Besides, based on our research, high AMC were significantly associated with shorter survival by univariable analysis, but not maintained the prognostic values in multivariable analysis, which might be related to the small sample size of the present research, relatively short follow-up or different cut-offs.

In conclusion, we aimed to demonstrate that a low ANKC ( $<$ 0.1 $\times$ 10 ${}^{9}$ /L) was associated with inferior OS in MCL. The baseline peripheral blood ANKC acquired at diagnosis may serve as a novel and effective biomarker in clinical practice in terms of host immune homeostasis and the tumor microenvironment in MCL. Probably one of the biggest limitations of our study is its retrospective nature and small sample size. Further large-scale, multi-centre and multi-racial prospective studies are needed to confirm these findings and clarify the efficacy of ANKC in MCL.

Footnotes

Acknowledgments

This study was supported by National Natural Science Foundation of China (81470328, 81600130, 81770166, 81720108002), Jiangsu Province’s Medical Elite Programme (ZDRCA2016022), Project of National Key Clinical Specialty, National Science and Technology Pillar Program (2014BAI09B12), Jiangsu Provincial Special Program of Medical Science (BL2014086 and BE2017751) and National Science and Technology Major Project (2017ZX09304032).

Conflict of interest

The authors declare no conflict of interest.

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Low absolute NK cell counts in peripheral blood are associated with inferior survival in patients with mantle cell lymphoma

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Materials and methods

2.1 Patients

2.2 Peripheral ANKC and AMC at diagnosis

2.3 Treatment decision at diagnosis

2.4 Statistical analysis

Table 1 Baseline clinical characteristics of 92 patients with mantle cell lymphoma

3.1 Patient characteristics

3.2 Baseline patient characteristics in relation to AMC and ANKC

Table 3 Univariable Cox regression analysis of the main factors for PFS and OS

4. Discussion

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Baseline clinical characteristics of 92 patients with mantle cell lymphoma

Table 3
Univariable Cox regression analysis of the main factors for PFS and OS