Terminal tissue differentiation and function of slan+ monocytes in cancer is largely unexplored. Our recent studies demonstrated that slan+ monocytes differentiate into a distinct subset of dendritic cells (DC) in human tonsils and that slan+ cells colonize metastatic carcinoma-draining lymph nodes. Herein, we report by retrospective analysis of multi-institutional cohorts that slan+ cells infiltrate various types of non-Hodgkin lymphomas (NHL), particularly the diffuse large B-cell lymphoma (DLBCL) group, including the most aggressive, nodal and extranodal, forms. Nodal slan+ cells displayed features of either immature DC or macrophages, in the latter case ingesting tumor cells and apoptotic bodies. We also found in patients with DLBCL that peripheral blood slan+ monocytes, but not CD14+ monocytes, increased in number and displayed highly efficient rituximab-mediated antibody-dependent cellular cytotoxicity, almost equivalent to that exerted by NK cells. Notably, slan+ monocytes cultured in conditioned medium from nodal DLBCL (DCM) acquired a macrophage-like phenotype, retained CD16 expression, and became very efficient in rituximab-mediated antibody-dependent cellular phagocytosis (ADCP). Macrophages derived from DCM-treated CD14+ monocytes performed very efficient rituximab-mediated ADCP, however, using different FcγRs from those used by slan+ macrophages. Our observations shed new light on the complexity of the immune microenvironment of DLBCL and demonstrate plasticity of slan+ monocytes homing to cancer tissues. Altogether, data identify slan+ monocytes and macrophages as prominent effectors of antibody-mediated tumor cell targeting in patients with DLBCL.

Significance: slan+ monocytes differentiate into macrophages that function as prominent effectors of antibody-mediated tumor cell targeting in lymphoma.

Graphical Abstract:http://cancerres.aacrjournals.org/content/canres/78/13/3544/F1.large.jpg. Cancer Res; 78(13); 3544–59. ©2018 AACR.

Blood monocytes are heterogeneous in terms of phenotype and function and, based on their differential expression of CD14 and CD16, are currently subdivided into classical (CD14++CD16), intermediate (CD14++CD16+), and nonclassical (CD14dim/−CD16++) monocytes. Moreover, the majority of nonclassical (CD14dimCD16++) monocytes specifically express the “slan” antigen (1), a carbohydrate modification of P-selectin glycoprotein ligand 1 (PSGL-1; ref. 2). This phenotype, coupled with functional dendritic cell (DC)-like features, led Schäkel and colleagues to originally call them as slanDCs (2, 3). However, recent unsupervised hierarchical clustering has unequivocally proved that slanDCs represent a subset of monocytes (4). slan+ monocytes are potently proinflammatory, given their capacity to produce higher amounts of IL12p70 and TNFα in response to TLR ligands than classical CD14++CD16 monocytes or CD1c+ DCs do (3). slan+ monocytes are also potent inducers of antigen-specific T-cell responses in vitro (2, 3) and induce a superior Th1/Th17 cell polarization as compared with classical CD1c+ DCs. Importantly, based on their highly specific reactivity to the very stable slan antigen, slan+ cells can be detected in tissues (including archival material) by antibodies known as DD1, DD2, and M-DC8 (1). To date, slan+ cells have been detected in inflamed tissues of patients affected by Crohn disease, rheumatoid arthritis, psoriasis, acute intestinal GVHD samples, as well as in reactive tonsils and Peyer patches (1, 3, 5, 6). Although the type of differentiation fate of slan+ monocytes in various tissues remains to be established, we have demonstrated that slan+ cells isolated from human tonsils, as well as slan+ monocytes cultured with tonsil-derived medium, show unequivocal terminal differentiation to DCs (5).

Recently, we have also reported that slan+ cells distinctively home to metastatic carcinoma draining lymph nodes (M-TDLNs), in close proximity to transformed epithelial cells (1). Our study also revealed that slan+ cells are absent in primary carcinoma and are recruited to lymph nodes following the arrival of cancer cells (1). However, the precise functional role of slan+ cells in M-TDLNs could not be defined, although our in situ analysis clearly indicated that slan+ cells efficiently engulf dead cancer cells.

In light of these observations, we pursued the hypothesis that slan+ cells could also infiltrate primary nodal lymphomas, a prediction that preliminarily turned out to be true, particularly in the case of diffuse large B-cell lymphoma (DLBCL). Thus, on the basis of the well-documented biological and clinical relevance of the immune microenvironment in DLBCL (7–10), we tested the relevance of slan+ cells in cancer by using the DLBCL as a model. In such regard, patients with DLBCL respond to antibodies targeting CD20-expressing B cells, such as rituximab (11, 12), whose biological activity is partially mediated by CD16-dependent antibody-dependent cellular cytotoxicity (ADCC) and/or antibody-dependent cellular phagocytosis (ADCP). Accordingly, we have undertaken a series of studies with the aim of defining whether slan+ monocytes/slan+ cells can perform rituximab-mediated ADCC and ADCP. We also investigated the functional importance and clinical relevance of slan+ cells associated with DLBCL. Our data show that slan+ monocytes/slan+ macrophages represent hitherto neglected cellular effectors of antibody-mediated tumor cell targeting in patients with DLBCL treated with rituximab.

Tissues

A tissue screening for slan+-cell content was performed on sections from formalin-fixed paraffin-embedded tissue blocks and included reactive (n = 67, Supplementary Table S1) and neoplastic (n = 151, Supplementary Table S2) lymph nodes from open surgical biopsies retrieved from the Department of Pathology, ASST Spedali Civili di Brescia (Brescia, Italy). Neoplastic lymph nodes included low- and high-grade WHO-defined non-Hodgkin lymphoma (NHL) B- and T-cell lymphomas, as reported in Supplementary Table S2. We also included normal bone marrow (n = 10), bone marrow localization of primary nodal DLBCL (n = 11), as well as 15 cases of primary DLBCL from various extranodal sites. The validation set was represented by three multi-institutional cohorts of newly diagnosed and previously untreated, primary DLBCL, two of which with clinical data available (Supplementary Tables S3 and S4). The study has been conducted according to the Declaration of Helsinki principles, after having obtained written informed consent from the patients, and approved by the local ethics board (NP906-WV-IMMUNOCANCERhum).

Clinical and demographic features of patients with DLBCL of the validation set

Cohort 1 (CH1) included tissue microarray (TMA) cores of 61 DLBCL (from the Haematopathology Unit, Department of Experimental, Diagnostic and Specialty Medicine - DIMES, University of Bologna, Bologna, Italy). TMAs were prepared as reported previously (13). Cohort 2 (CH2) included open surgical biopsies of 43 patients retrieved from the archive of the Department of Pathology ASST Spedali Civili di Brescia (Brescia, Italy; Supplementary Table S3). Cohort 3 (CH3) included open surgical biopsies of 51 patients retrieved from the archive of the Department of Pathology and Diagnostic, Verona University Hospital (Verona, Italy; Supplementary Table S4). For CH1, a panel of mouse mAbs toward CD10, BCL6, and MUM1/IRF4 was applied to define the cell of origin, according to Hans' algorithm (14). IHC and FISH analysis for BCL2, MYC, and BCL6 were used to subgroup “double expressor” and “double hit” DLBCL, according to the literature (15, 16)

IHC

Four-micron thick tissue sections were used for IHC staining. The panel of markers and the detection systems used for the IHC analysis are reported in Supplementary Table S5. slan+ cells were identified by IHC using DD1 or DD2 mAbs, as reported previously (1). Single immune reactions were developed using Novolink polymer (Leica Microsystems). For double IHC, the second immune reaction was visualized using Mach 4 MR-AP (Biocare Medical), followed by Ferangi Blue (Biocare Medical) as chromogen. Based on a training set of 15 cases on digitalized slides, a three-tiered score was defined as follows: score 0 ≤20 cell/mm2 (mean 4.1); score 1 ≤200 cells/mm2 (mean 145); score 2 ≥200 cells/mm2 (mean 621.6). A semiquantitative three-tiered scoring system (S0–S2) was also used for CD56 and CD16 expression analysis.

Lymph node samples

Fresh lymph node samples obtained from patients with NHL (details are reported in Supplementary Table S6) were immediately minced into 4 to 5 small (3–4 mm3) fragments, placed in gentleMACS C Tubes (Miltenyi Biotec) and treated for 20 minutes at 37°C with 0.2 mg/mL Liberase Blendzyme 2 (Roche) in RPMI1640 medium (Lonza). Then, 0.5 mg/mL DNase (Worthington Biochemical Corporation) was added to lymph node pieces 5 minutes prior to their processing by gentleMACS dissociator (Miltenyi Biotec). Lymph node suspensions were then washed, filtered through a 70-μm cell strainer, suspended in PBS containing 2% fetal low-endotoxin FBS (<0.5 endotoxin U/mL, Sigma-Aldrich), and 2 mmol/L EDTA (Sigma-Aldrich). Fractions of each lymph node cell suspensions were immediately used for the phenotypic characterization of myeloid cells by flow cytometry analysis, or used to isolate neoplastic B cells. Another aliquot of lymph node suspension was instead cultured at 1 × 108/mL in RPMI1640 medium supplemented with 10% low-endotoxin FBS. After 24 hours, cell-free DLBCL-conditioned medium (DCM) was collected and stored at −20°C.

Cell isolation and culture

Peripheral blood mononuclear cells (PBMC) were isolated under endotoxin-free conditions by density centrifugation (Ficoll–Paque; GE Healthcare), of either buffy coats of healthy donors (HD), or whole blood collected in BD Vacutainer tubes with K2EDTA (BD Biosciences) from patients with DLBCL (whose clinical characteristics are reported in Supplementary Table S7). slan+ monocytes, CD14+ monocytes, natural killer (NK) cells, and neutrophils were then purified using, respectively, the slan (M-DC8)+ Monocyte Isolation Kit (Miltenyi Biotec; >96% purity), the CD14+ MicroBeads (Miltenyi Biotec; >98% pure), the EasySep Human NK Cell Enrichment Kit (Stem Cell Technologies; >96% pure) and the EasySep Human Neutrophil Enrichment Kit (Stem Cell Technologies; >99.7% purity; ref. 5). CD43 B cells from HD blood or lymphoma samples were purified from, respectively, HD PBMCs and lymph node suspensions, by using the human B Cell Isolation Kit II (Miltenyi Biotec; >98% purity). Neoplastic B cells were identified by their monoclonal expression of either the λ- or the κ-light chain, by flow cytometry. The Daudi cell line was obtained from ATCC, tested for mycoplasma negativity by PCR (using primers detecting at least 49 different mycoplasma strains: forward 5′-ACT CCT ACG GGA GGC AGC AGT A-3′; reverse 5′-TGC ACC ATC TGT CAC TCT GTT AAC CTC-3′), and cultured in RPMI1640 medium supplemented with 10% FBS. In some experiments, 0.5 × 106/mL HD and DLBCL slan+ monocytes, CD14+ monocytes, or NK cells were cultured for 5 days in RPMI1640 medium containing 10% FBS, in the presence of 20% DCM. Alternatively, HD slan+ monocytes and CD14+ monocytes were cultured for 5 days with either 30 ng/mL GM-CSF (PeproTech) plus 20 ng/mL IL4 (PeproTech) to generate slan+ DCs (5) or 100 ng/mL IL34 (R&D Systems) to generate macrophages (5).

Flow cytometry analysis

For antigen expression analysis, typically 2.5 × 105 PBMCs, 5 × 105 cells from lymph node suspensions, and 104in vitro differentiated slan+ monocytes cells were initially incubated for 10 minutes in 50 μL PBS containing 5% human serum (to prevent nonspecific binding), and then stained for 15 minutes at room temperature with fluorochrome-conjugated mAbs listed in Supplementary Table S5. Sample fluorescence was measured by an 8-color MACSQuant Analyzer (Miltenyi Biotec), while data analysis was performed by FlowJo software Version 10.1. Cell viability was analyzed by Vybrant DyeCycle Violet (Life Technologies; ref. 1). Phenotypic analysis under the various experimental conditions was performed on live cells, identified as Vybrant-negative cells (in the case of in vitro differentiated slan+ monocytes) or PI-negative cells (in the case of lymph node suspensions; ref. 5). The mean fluorescence intensity (MFI) relative to each molecule was obtained by subtracting either the MFI of the correspondent isotype control mAb, or cell autofluorescence (fmo). To count the absolute number of each specific cell population, 50 μL whole blood from HDs or patients with DLBCL was stained for 15 minutes at room temperature with fluorochrome-conjugated mAbs listed in Supplementary Table S5. Samples were then incubated for 10 minutes with the RBC Lysis Solution (Qiagen), washed and analyzed by MACSQuant Analyzer (Miltenyi Biotec). slan+ monocytes, CD14+ monocytes, and NK cells were identified, respectively, as M-DC8+/CD16+/HLA-DR+, CD14+/CD16/HLA-DR+, and CD56+/HLA-DR cells within the CD45+/CD3/CD19 cell population. Neutrophils were identified as CD16+/SShi/CD45lo cells within total CD45+ cells. The absolute number per μL of each blood cell population was calculated by multiplying their percentage within the CD45+-gated cells to the white cell counts provided by hospital laboratory of analysis.

ADCC assay

ADCC of Daudi, peripheral, and neoplastic B cells was performed and evaluated by a Calcein-Acetyoxymethyl Cytotoxicity Assay, as reported previously (17). Specifically, 1–2 × 106 target cells were initially stained with 5 μmol/L Calcein-AM (Molecular Probes) in PBS plus 2% FBS for 15 minutes at 37°C. After two washings in PBS plus 2% FBS, cells were adjusted to 106/mL in complete medium and either left untreated or coated with 5 μg/mL αCD20 rituximab (MABTHERA from Roche), for 20 minutes at 37°C. Then, 5 × 103 target cells (in 5 μL) were transferred in U-bottom 96-well plates and cocultured in a final volume of 150 μL with slan+ monocytes, NK cells, CD14+ monocytes, or neutrophils from either HDs or patients with DLBCL, at increasing E:T ratios (from 1:1 to 10:1). In selected experiments, 5 × 103 Daudi cells were cocultured with HD NK cells at 2/10:1 E:T ratios, with or without 5–10 × 103 slan+ monocytes. In other experiments, 5 × 103 Daudi, peripheral and neoplastic B cells were cultured with 5 × 104 DCM-treated slan+ monocytes and NK cells, or IL34- or GM-CSF plus IL4-treated slan+ monocytes (at a 10:1 E:T ratio). After 4 hours, duplicates of 50 μL cell-free supernatants from each well were transferred into flat-bottom 96-well plates (Corning) to measure their fluorescence by a VICTOR3 multilabel reader (PerkinElmer). Percent of specific lysis was calculated according to the formula: [(test release − spontaneous release)/(maximum release − spontaneous release)] × 100. Spontaneous and maximum release represent, respectively, calcein release from target cells in medium alone or in medium plus 2% Triton X-100. In selected experiments, the same cell samples were examined for phagocytosis by confocal microscopy.

ADCP assay

Daudi, normal peripheral, and neoplastic B cells were stained with PKH26 dye (18), using the PKH26 Red Fluorescent Cell Linker Midi Kit for General Cell Membrane Labeling (Sigma-Aldrich), according to the manufacturer's instructions. After two washings in complete medium, target cells were adjusted to 106/mL and either left untreated or coated with 5 μg/mL αCD20 rituximab for 20 minutes at 37°C. 104 PKH26-labeled target cells were then incubated with 104 effector cells in U-bottom 96-well plates, in a final volume of 100 μL. After 4-hour incubation, plates were centrifuged, supernatants collected, and cells stained by Vybrant DyeCycle Violet in PBS plus 2% FBS and 2 mmol/L EDTA for 15 minutes on ice. Immediately prior to FACS analysis, cells were incubated for additional 2 minutes with 400 μg/mL Crystal Violet (Merck KGaA), to quench extracellular fluorescence (18). By doing so, only effector cells containing engulfed targets maintain PKH26 positivity, whereas free target cells or target cell externally attached to effector cells become PKH26 negative. Finally, ADCP was determined by gating live Vybrant negative cells and, subsequently, PKH26+ cells. In selected experiments, before target cell addition, effector cells were pretreated for 30 minutes at 37°C with or without 10 μg/mL anti-CD16 (clone 3G8 from BD Biosciences), anti-CD32 (clone AT10, Bio-Rad), anti-CD64 (clone 10.1, BioLegend) mAbs, either alone or in combinations. As control, effector cells were also pretreated with 10 to 30 μg/mL mouse IgG1 isotype control antibody (clone MG1-45, BioLegend).

Laser confocal microscopy

After being cultured for ADCC assay, DCM-treated slan+ monocytes and calcein-labeled Daudi cells were gently collected and rapidly cytospun on Polysine Adhesion slides (Thermo Fisher Scientific) at 500 rpm for 5 minutes (Shandon CytoSpin III Cytocentrifuge). Cytospins of cultured cells were then fixed with 4% (w/v) paraformaldehyde for 20 minute and then permeabilized with 0.1% Triton X-100 for 30 minutes at room temperature. Nuclear staining was done with DAPI (Sigma-Aldrich). Thereafter, samples were washed twice with PBS. Preparations were mounted in antibleaching medium and visualized by confocal laser scanning microscopy (LSM 510; Zeiss) equipped with argon and helium-neon lasers. Image analysis was performed with LSM 5 Image Browser software (Zeiss).

Phenotype and function of HD and DLBCL slan+ monocytes

HD or DLBCL blood slan+ monocytes were cultured at 0.25 × 106/mL in U-bottom 96-well plates, in a final volume of 100 μL. slan+ monocytes were stimulated for 24 hours with or without 100 ng/mL LPS (Ultra Pure Escherichia coli LPS; 0111:B4 strain, from InvivoGen), 100 U/mL IFNγ (R&D Systems), and 5 μmol/L R848 (InvivoGen), alone or in combinations. Cytokine levels in cell-free supernatants were measured by specific ELISA kits for human TNFα and IL6 (eBioscience, Affymetrix). Analysis of membrane markers was performed by flow cytometry on live Vybrant-negative cells using the following mAbs: anti-human CD83 PE and CD14 APC (from Miltenyi Biotec), CD16 PerCP-Cy5.5, and HLA-DR ACP/Cy7 (from BioLegend).

Statistical analysis

Pairwise correlation coefficients between markers were computed using different statistics depending on the type of variable considered. Accordingly, “polyserial” correlation was computed between numeric and ordinal variables, whereas “polychoric” correlation was used when both variables were ordinal. Association between markers and qualitative variables (sex, stage, revised International Prognostic Index; ref. 19) were performed using nonparametric tests, namely Wilcoxon rank sum test for two-level variables, as well as Kruskal–Wallis test followed by Nemenyi–Damico–Wolfe–Dunn test for all-pairwise comparisons (approximate with Monte Carlo resampling, B = 50000) for multiple levels predictors. Times to event data were modeled using Cox proportional hazard models. All analyses were performed using R (version 3.3.2), assuming a significant level of 5%. For in vitro cellular assays, data are expressed as mean ± SEM of the number of experiments indicated in each figure legend. Statistical analysis, including two-tailed Student t test, one-way or two-way ANOVA, was performed by Prism Version 5.0 software (GraphPad).

slan+ cells infiltrate NHL, particularly nodal DLBCL

Based on our previous results (1), we hypothesized that lymph node accumulation of slan+ cells might occur also in nodal lymphomas. We first obtained preliminary results of slan+-cell infiltration in various nonneoplastic lymph nodes by staining 67 cases of lymphadenitis with various reactive patterns (Supplementary Table S1). By using a three-tiered density score (see Materials and Methods for details), we detected slan+ cells in 79.1% of the cases (with score 1 or 2), even though they were particularly abundant (equal to score 2) in a limited fraction (16.4%) of the cases only (LD in Fig. 1A; Supplementary Fig. S1A–S1H; Supplementary Table S1). The slan antigen confirmed its specificity being slan-negative the large majority of lymphoid and stromal cells, sinus macrophages, Langerhans cell–derived interdigitating DCs (Supplementary Fig. S1I) and granuloma-forming macrophages (Supplementary Fig. S1J–S1L). These latter findings confirm our previous observations revealing that the slan marker is not expressed by most of the specialized tissue-resident mononuclear cells (1).

Figure 1.

slan+ cells infiltrate nodal and extranodal DLBCL. A–C, Graphs report the frequency of the cases containing slan+ cells at the indicated score in LD, in B- (NHBCL), and T (NHTCL)-non-Hodgkin lymphoma, nodal (NDLBCL), and extranodal (EDLBCL) DLBCL. S0, S1, and S2 stand for, respectively, slan score = 0, = 1, and = 2 (see Materials and Methods for details). Sections are from lymph nodes (D–F), bone marrow (G–L), thyroid (M–O), and skin (P–R), infiltrated by primary nodal (D–L) and primary extranodal (M–R) DLBCL, stained as labeled. CD20 and slan sections were counterstained with Meyer's hematoxylin. Original magnification, ×40 (G, J, and M; scale bar, 500 μm), ×100 (D and P; scale bar, 200 μm); ×200 (E–F, H–I, K–L, N–O, and Q–R; scale bar, 100 μm).

Figure 1.

slan+ cells infiltrate nodal and extranodal DLBCL. A–C, Graphs report the frequency of the cases containing slan+ cells at the indicated score in LD, in B- (NHBCL), and T (NHTCL)-non-Hodgkin lymphoma, nodal (NDLBCL), and extranodal (EDLBCL) DLBCL. S0, S1, and S2 stand for, respectively, slan score = 0, = 1, and = 2 (see Materials and Methods for details). Sections are from lymph nodes (D–F), bone marrow (G–L), thyroid (M–O), and skin (P–R), infiltrated by primary nodal (D–L) and primary extranodal (M–R) DLBCL, stained as labeled. CD20 and slan sections were counterstained with Meyer's hematoxylin. Original magnification, ×40 (G, J, and M; scale bar, 500 μm), ×100 (D and P; scale bar, 200 μm); ×200 (E–F, H–I, K–L, N–O, and Q–R; scale bar, 100 μm).

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We then screened a large cohort of NHL (Fig. 1A), including 125 cases of B-cell lymphoma (NHBCL) and 26 cases of T-cell lymphoma (NHTCL). In NHL, the slan antigen reacts with cells of the microenvironment (Supplementary Fig. S2A–S2P), but not with the B (Supplementary Fig. S2Q and S2R) and T (Supplementary Fig. S2S and S2T) lymphoid neoplastic cells. We could detect slan+ cells (score 1 or 2) in 58.4% of NHBCL and in 53.9% of NHTCL (Fig. 1A and B; Supplementary Table S2). By subgroup analysis (Supplementary Table S2), slan+ cells were rarely found in B-cell chronic lymphocytic leukemia (B-CLL)/small lymphocytic lymphoma, nodal marginal zone lymphoma and ALK+-anaplastic large cell lymphoma. In contrast, slan+ cells were particularly abundant in DLBCL, showing a score 2 in 33.3% of the cases. We therefore extended our findings on nodal DLBCL, by analyzing a validation set of primary nodal WHO-defined DLBCL from three independent cohorts, including 155 cases in total. Specifically, for CH1 (n = 61), the analysis was performed on TMA cores, whereas the entire nodal section was available for the analysis of CH2 (n = 43) and CH3 (n = 51). By staining of CH1, we could confirm infiltration of slan+ cells in 49.1% (30/61) of the cases. For CH2 and CH3, we employed a three-tiered density score and data are detailed in Supplementary Tables S3 and S4 and summarized in Fig. 1C and Supplementary Table S8. Briefly, the analysis on the entire nodal section confirmed a high frequency of DLBCL cases (70.22%) containing slan+ cells (Fig. 1D–F), with nonsignificant differences between the two cohorts (65.1% for CH2 vs. 74.5% for CH3, Supplementary Table S8). Remarkably, 26.6% of the DLBCL cases (Supplementary Table S8) were score 2 for slan+-cell infiltration. slan+-cell distribution displayed spatial heterogeneity (Supplementary Fig. S3A–S3D), thus explaining the significantly lower frequency of DLBCL cases containing slan+ cells in the TMA-based CH1. slan+ cells were observed in the majority of bone marrow localizations of primary nodal DLBCL (77.8%; Fig. 1G–L, Supplementary Table S2), as well as in cases of primary DLBCL from various extranodal sites (80%, Fig. 1C; Supplementary Table S2) including thyroid (Fig. 1M–O) and skin (Fig. 1P–R).

slan+ cells infiltrate aggressive forms of DLBCL

DLBCL is a heterogeneous form of lymphoma that includes subgroups defined by clinical, histologic, and molecular features. By gene expression profiling, DLBCL are subdivided in germinal center B-cell (GBC) DLBCL and activated B-cell DLBCL, the latter showing a poorer outcome (20). The distinction between GBC and non-GBC DLBCL can be obtained by using a surrogate IHC panel on archival material (14). In CH1, slan+ cells infiltrated both the GBC (n = 13/26; 50%) and non-GBC cases (n = 17/35; 48.5%), with no significant differences between the two subgroups (P > 0.5). Another subgroup of DLBCL with clinical relevance is the so-called “double hit” DLBCL (DHL; refs. 15, 21). DHL, now viewed as a new category under the umbrella of “high-grade B-cell lymphoma, with MYC and BCL2 and/or BCL6 translocations” (21), are characterized by a combination of translocation activating MYC, BCL2, and, less commonly, BCL6 (21), identifiable by FISH analysis. Along the same line, double-expressor lymphomas (DEL) show overexpression of the Myc and Bcl2 proteins by IHC (16, 22). In both DHL and DEL, CHOP and R-CHOP regimens are less effective treatments and patients have shorter progression-free survival (PFS) and overall survival (21). By combining Myc and Bcl2 immunostaining, we analyzed CH2 and CH3 and defined DEL as reported by Green and colleagues (16). In line with the literature (22), we found that a large fraction of the cases showed Bcl2 (respectively 60.5% for CH2; 60.8% for CH3; mean 60.6%) or Myc overexpression (respectively 46.5% for CH2; 47.1% for CH3; mean 46.8%), but only a minor fraction of the cases corresponded to DEL (25.6% for CH2; 31.4% for CH3; mean 28.7%), with minor differences between CH2 and CH3 (Supplementary Table S8). Remarkably, no differences in the frequency of cases containing slan+ cells were observed in the four (BCL2/MYC; BCL2+/MYC; BCL2/MYC+; BCL2+/MYC+) subgroups defined by the BCL2 or Myc reactivity (P = 0.33; Fig. 2A and B; Supplementary Table S8). Furthermore, a sizeable fraction of cases (66.7%) containing slan+ cells (score 1 or 2) was observed also in DEL (Fig. 2C–F). We expanded this observation at the molecular level by analyzing a group of 12 DHL showing BCL2 and MYC rearrangements by FISH analysis (Fig. 2C, G–I). The fraction of DHL cases containing slan+ cells (score 1 or 2) was 58% (7/12), slightly lower than those of unselected DLBCL (70.22%; Fig. 2C). Together, these findings indicate that slan+-cells infiltrate also aggressive forms of DLBCL.

Figure 2.

slan+ cells infiltrate DEL and DHL. The frequency of the cases containing slan+ cells at the indicated score is reported for BCL2+- and MYC+-DLBCL in CH2 (A) and CH3 (B) cohorts, as well as in DEL and DHL DLBCL subgroups compared with all the DLBCLs (C). S0, S1, and S2 stand for, respectively, slan score = 0, = 1, and = 2 (see Materials and Methods for details). Sections are from a nodal “double-expressor” DLBCL (DEL; D–F) and a “double hit” DLBCL (DHL; G–I), and stained as labeled. FISH analysis of DHL (H and I) shows split (red–green) signals. Sections were counterstained with Meyer's hematoxylin (D–G) or DAPI (H–I). Original magnification, ×200 (D–G; scale bar, 100 μm); ×1,000 (H and I, scale bar, 20 μm).

Figure 2.

slan+ cells infiltrate DEL and DHL. The frequency of the cases containing slan+ cells at the indicated score is reported for BCL2+- and MYC+-DLBCL in CH2 (A) and CH3 (B) cohorts, as well as in DEL and DHL DLBCL subgroups compared with all the DLBCLs (C). S0, S1, and S2 stand for, respectively, slan score = 0, = 1, and = 2 (see Materials and Methods for details). Sections are from a nodal “double-expressor” DLBCL (DEL; D–F) and a “double hit” DLBCL (DHL; G–I), and stained as labeled. FISH analysis of DHL (H and I) shows split (red–green) signals. Sections were counterstained with Meyer's hematoxylin (D–G) or DAPI (H–I). Original magnification, ×200 (D–G; scale bar, 100 μm); ×1,000 (H and I, scale bar, 20 μm).

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Morphology and phenotype of slan+ cells in DLBCL

By morphology, slan+ cells in DLBCL were large and with a dendritic-like form (Supplementary Fig. S4A–S4L) or, more rarely, small and monocytoid (Supplementary Fig. S4M–S4T). Remarkably, the latter slan+ cell type was also observed around HEV or within their vessel lumen, even transmigrating (Supplementary Fig. S4M). As previously observed in tonsils (5), and tumor-draining lymph nodes (1), slan+ cells infiltrating DLBCL were negative for markers of B cells (PAX5), T cells (CD3), plasmacytoid DCs (CD303), and Langerhans cells (CD1a; Supplementary Fig. S4A–S4D). In contrast, slan+ cells coexpressed, although at various frequency, a set of myeloid markers including S100 protein, CD11c, CD68, CSF1R, lysozyme, and CD16 (n = 6; Supplementary Fig. S4E–S4I). This pattern of reactivity was also observed in the smaller slan+-monocytoid cells with only slight differences (Supplementary Fig. S4M–S4T). Specifically, small slan+-monocytoid cells were negative for S100 protein (Supplementary Fig. S4Q).

We also observed that a fraction of DLBCL displays intratumoral slan+ cells that closely interact with neoplastic B cells (Fig. 3A–H). More importantly, some intratumoral slan+ cells are engulfed of apoptotic bodies (Fig. 3C and D), or contain PAX5+ (Fig. 3E and F), and MYC+ nuclei (Fig. 3G and H), all features suggesting efficient phagocytosis of lymphoma cells along with a macrophage-like differentiation. Accordingly, we found that nodal slan+ cells in DLBCL also coexpress the macrophage marker CD163 (Fig. 3I–K), at variance with slan+ cells in human tonsils (5). However, we expanded this observation on DLBCL cases highly infiltrated by slan+ cells (score 2), documenting two almost mutually exclusive phenotypic patterns based of CD163 and slan reactivity. In the first pattern, slan+ cells coexpress CD163 and were admixed to CD163+slan macrophages (Fig. 3I–K). In the second pattern, the large majority of slan+ cells were negative for CD163 (Fig. 3L–N); of note, within this latter subgroup, CD163+ slan macrophages were either coexisting (Fig. 3L), found in a distinct area (Fig. 3M), or totally absent (Fig. 3N). Finally, CD163slan+ resulted substantially negative for CD83, CD208, and CCR7 expression, indicating a likely immature DC status (Supplementary Fig. S4J–S4L).

Figure 3.

Phagocytosing intratumoral slan+ cells coexpress CD163, the macrophage marker. Sections are from human nodal DLBCL and stained as labeled. Top, intratumoral slan+ cells are enlarged and contain intracytoplasmic apoptotic bodies (A and B) expressing active caspase-3 (C and D) and containing intracytoplasmic PAX5+/MYC+ nuclei (E–H). Bottom, representative nodal DLBCL cases containing CD163+/slan+ macrophage-like cells (I–K) and others with CD163/slan+ DC-like cells (L–N). Sections were counterstained with Meyer's hematoxylin. Original magnification, ×100 (L–N; scale bar, 200 μm) and ×200 (I–K; scale bar, 100 μm). High-power view was obtained at ×600 magnification (A–H and insets in I–N).

Figure 3.

Phagocytosing intratumoral slan+ cells coexpress CD163, the macrophage marker. Sections are from human nodal DLBCL and stained as labeled. Top, intratumoral slan+ cells are enlarged and contain intracytoplasmic apoptotic bodies (A and B) expressing active caspase-3 (C and D) and containing intracytoplasmic PAX5+/MYC+ nuclei (E–H). Bottom, representative nodal DLBCL cases containing CD163+/slan+ macrophage-like cells (I–K) and others with CD163/slan+ DC-like cells (L–N). Sections were counterstained with Meyer's hematoxylin. Original magnification, ×100 (L–N; scale bar, 200 μm) and ×200 (I–K; scale bar, 100 μm). High-power view was obtained at ×600 magnification (A–H and insets in I–N).

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By flow cytometry analysis of a broad panel of markers, we could analyze and compare the phenotypes of slan+ cells with those of other myeloid cell populations present in fresh lymph nodes obtained from another cohort of patients with NHBCL (see Supplementary Table S6 for their clinical features). By doing so, we calculated that the slan+ cells account for about 7% of the total HLA-DR+CD11c+ myeloid cells in DLBCL samples (n = 7). We could also confirm the existence of two mutually exclusive slan+-cell phenotypes in nodal NHBCL (Fig. 4A). Specifically, we found a CD163hi/CD14hi/CD64hi/CD16hi macrophage phenotype (Fig. 4A, blue circles), which resembles that displayed by the nodal CD14+CD11b+ population (Fig. 4A, orange circles), or a CD163low/CD14low/CD64low/CD16low DC phenotype (Fig. 4A, green circles), which instead resembles that exhibited by the nodal CD1c+ and CD141+ DC populations (Fig. 4A, gray and red circles respectively). Examples of the macrophage and DC profiles of nodal DLBCL slan+ cells are also shown in Fig. 4B. When compared with circulating slan+ monocytes from either HDs (Fig. 4C) or unmatched patients with DLBCL, nodal DLBCL slan+ macrophages expressed significantly increased levels of CD14, CD163, CD32, CD64, and CD80 (Fig. 4C, blue columns), whereas nodal DLBCL slan+ DCs completely downmodulated CD16 (Fig. 4C, green columns). These findings indicate that slan+ monocytes homing to lymph nodes of NHBCL, and more specifically, patients with DLBCL, are skewed toward two mutually exclusive distinct differentiation programs.

Figure 4.

Phenotypes of nodal NHL and DLBCL slan+ cells and other myeloid cells. A, Nodal slan+ cells, CD14+CD11b+ macrophages, CD1c+ DCs, and CD141+ DCs were identified by flow cytometry analysis as, respectively, M-DC8+, CD14+/CD11b+, CD1c+, and CD141+ cells within HLA-DR+/CD11c+/LIN myeloid cells in NHL or DLBCL lymph nodes (LN; see Materials and Methods). Each filled circle in the dot plots stands for the expression levels of CD14, CD16, CD64, and CD163 by the cell populations found in each lymph node sample, as indicated. Blue and green circles in each dot plot indicate nodal samples that, according to the phenotype, belong to the same group since display, in a mutually exclusive manner, either a macrophage (blue circles) or a DC (green circles) phenotype. Values indicate the MFI for each antigen. B, The two panels illustrate representative phenotypes displayed by nodal DLBCL slan+ macrophages (left) or slan+ DCs (right), based on their CD14, CD16, CD64, and CD163 expression. MFI values for every marker and isotype control mAbs are shown on the right side of each panel. C, Bars show the expression (mean ± SEM) of the indicated markers analyzed in HD slan+ monocytes (n = 6–12) and in nodal DLBCL slan+ cells displaying either a macrophage (blue columns; n = 3–4) or a DC (green columns; n = 3–4) phenotype. Statistical significance: *, P < 0.05; **, P < 0.01; and ***, P < 0.001 by one-Way ANOVA; §, P < 0.05; §§, P < 0.01 by two-tailed Student t test and comparing slan+ monocytes with slan+ DCs.

Figure 4.

Phenotypes of nodal NHL and DLBCL slan+ cells and other myeloid cells. A, Nodal slan+ cells, CD14+CD11b+ macrophages, CD1c+ DCs, and CD141+ DCs were identified by flow cytometry analysis as, respectively, M-DC8+, CD14+/CD11b+, CD1c+, and CD141+ cells within HLA-DR+/CD11c+/LIN myeloid cells in NHL or DLBCL lymph nodes (LN; see Materials and Methods). Each filled circle in the dot plots stands for the expression levels of CD14, CD16, CD64, and CD163 by the cell populations found in each lymph node sample, as indicated. Blue and green circles in each dot plot indicate nodal samples that, according to the phenotype, belong to the same group since display, in a mutually exclusive manner, either a macrophage (blue circles) or a DC (green circles) phenotype. Values indicate the MFI for each antigen. B, The two panels illustrate representative phenotypes displayed by nodal DLBCL slan+ macrophages (left) or slan+ DCs (right), based on their CD14, CD16, CD64, and CD163 expression. MFI values for every marker and isotype control mAbs are shown on the right side of each panel. C, Bars show the expression (mean ± SEM) of the indicated markers analyzed in HD slan+ monocytes (n = 6–12) and in nodal DLBCL slan+ cells displaying either a macrophage (blue columns; n = 3–4) or a DC (green columns; n = 3–4) phenotype. Statistical significance: *, P < 0.05; **, P < 0.01; and ***, P < 0.001 by one-Way ANOVA; §, P < 0.05; §§, P < 0.01 by two-tailed Student t test and comparing slan+ monocytes with slan+ DCs.

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slan+ monocytes from patients with DLBCL are increased in frequency and efficiently perform a rituximab-mediated ADCC

We subsequently analyzed the frequency and functional status of blood slan+ monocytes in newly diagnosed patients with DLBCL (see Supplementary Table S7 for their clinical features) and age-matched HDs. For comparison, we also analyzed autologous NK cells, CD14+ monocytes, and neutrophils. We found that, within similar WBC counts (Supplementary Fig. S5A), blood slan+ monocytes are significantly increased in patients with DLBCL as compared with age-matched HDs, in terms of either absolute number (Fig. 5A, top) or percentage within the PBMC fraction (Fig. 5A, bottom). In contrast, NK cells of patients with DLBCL were significantly decreased, at least in terms of absolute number (Fig. 5B, top), whereas CD14+ monocytes followed a trend similar to slan+ monocytes in terms of percentage within PBMCs (Fig. 5C, bottom). DLBCL neutrophils were significantly increased as compared with their age-matched HD counterpart (Supplementary Fig. S5B), whereas total PBMCs were diminished (Supplementary Fig. S5C). In addition to their selective increased frequency, DLBCL slan+ monocytes normally responded to IFNγ plus LPS or R848, in terms of either modulation of CD16, CD14, CD83, and HLA-DR expression (Supplementary Fig. S5D–S5G), or TNFα and IL6 production (Supplementary Fig. S5H and S5I). Furthermore, no expression of surface PD-L1 was detected in both CD14+ and slan+ monocytes, when freshly isolated from either HDs or patients with DLBCL.

Figure 5.

slan+ monocytes are significantly augmented in the blood of patients with DLBCL and, ex vivo, perform an efficient rituximab-dependent ADCC of B cells. A–C, Dot plots show the absolute number (top), and the percentage within PBMCs (bottom), of blood slan+ monocytes (A), NK cells (B), and CD14+ monocytes (C) in HDs (white circles) and in newly diagnosed patients with DLBCL (red circles). **, P < 0.01 and ***, P < 0.001 by two-tailed Student t test. D and E, Blood NK cells, slan+ monocytes, CD14+ monocytes, and neutrophils isolated from HDs (D) or patients with DLBCL (E) were cultured with Daudi cells, previously treated with or without 5 μg/mL αCD20 mAbs at a 10:1 E:T ratio. After 4 hours, cytotoxicity by effector cells was investigated and calculated as specified in Materials and Methods. P < 0.05; **, P < 0.01; and ***, P < 0.001 by one-way ANOVA. For HDs in D, n = 23 for NK cells, n = 22 for slan+ monocytes, n = 12 for CD14+ monocytes, and n = 4 for neutrophils. For patients with DLBCL in E, n = 15 for NK cells, n = 13 for slan+ monocytes, n = 9 for CD14+ monocytes, and n = 4 for neutrophils. F, A total of 104–5 × 104 NK cells from HDs were cocultured for 4 hours with 5 × 103 Daudi, alone (white columns) or in the presence of 5 × 103 (light gray columns) or 104 (dark gray columns) HD slan+ monocytes. Bar graph reports the percentage (mean ± SEM; n = 3) of the specific lysis of αCD20-coated tumor cells after subtraction of the percentage of lysis of untreated tumor cells (net lysis). *, P < 0.05 and ***, P < 0.001 by one-way ANOVA. G and H, A total of 5 × 104 slan+ monocytes (G) and NK cells (H) from HDs (gray columns) or patients with DLBCL (red columns) were cultured with 5 × 103 healthy or neoplastic B cells isolated from NHL samples, previously treated with or without 5 μg/mL αCD20 mAbs. ADCC was then determined after 4 hours of coculture. n = 4 for normal blood B cells and n = 17 for nodal neoplastic B cells as target cells for HD slan+ monocytes (G) or NK cells (H); n = 3 for nodal neoplastic B cells as target cells for DLBCL slan+ monocytes (G) or NK cells (H). n.d., not done.

Figure 5.

slan+ monocytes are significantly augmented in the blood of patients with DLBCL and, ex vivo, perform an efficient rituximab-dependent ADCC of B cells. A–C, Dot plots show the absolute number (top), and the percentage within PBMCs (bottom), of blood slan+ monocytes (A), NK cells (B), and CD14+ monocytes (C) in HDs (white circles) and in newly diagnosed patients with DLBCL (red circles). **, P < 0.01 and ***, P < 0.001 by two-tailed Student t test. D and E, Blood NK cells, slan+ monocytes, CD14+ monocytes, and neutrophils isolated from HDs (D) or patients with DLBCL (E) were cultured with Daudi cells, previously treated with or without 5 μg/mL αCD20 mAbs at a 10:1 E:T ratio. After 4 hours, cytotoxicity by effector cells was investigated and calculated as specified in Materials and Methods. P < 0.05; **, P < 0.01; and ***, P < 0.001 by one-way ANOVA. For HDs in D, n = 23 for NK cells, n = 22 for slan+ monocytes, n = 12 for CD14+ monocytes, and n = 4 for neutrophils. For patients with DLBCL in E, n = 15 for NK cells, n = 13 for slan+ monocytes, n = 9 for CD14+ monocytes, and n = 4 for neutrophils. F, A total of 104–5 × 104 NK cells from HDs were cocultured for 4 hours with 5 × 103 Daudi, alone (white columns) or in the presence of 5 × 103 (light gray columns) or 104 (dark gray columns) HD slan+ monocytes. Bar graph reports the percentage (mean ± SEM; n = 3) of the specific lysis of αCD20-coated tumor cells after subtraction of the percentage of lysis of untreated tumor cells (net lysis). *, P < 0.05 and ***, P < 0.001 by one-way ANOVA. G and H, A total of 5 × 104 slan+ monocytes (G) and NK cells (H) from HDs (gray columns) or patients with DLBCL (red columns) were cultured with 5 × 103 healthy or neoplastic B cells isolated from NHL samples, previously treated with or without 5 μg/mL αCD20 mAbs. ADCC was then determined after 4 hours of coculture. n = 4 for normal blood B cells and n = 17 for nodal neoplastic B cells as target cells for HD slan+ monocytes (G) or NK cells (H); n = 3 for nodal neoplastic B cells as target cells for DLBCL slan+ monocytes (G) or NK cells (H). n.d., not done.

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Patients with DLBCL are usually treated with R-CHOP (rituximab-cyclophosphamide, doxorubicin, vincristine, and prednisone) or R-CHOP–like immunochemotherapy regimens (11). Rituximab is a humanized mAb targeting CD20 expressed by B cells. Rituximab-dependent clinical activity is based on various mechanisms, including ADCC and ADCP (23, 24). It is commonly accepted that NK cells, via the engagement of their FcγRIIIA/CD16, represent the most relevant effector cells of rituximab-mediated ADCC of target B cells (25, 26). Nonetheless, given that also CD16+ monocytes/slan+ monocytes have been reported to perform ADCC activities toward tumor cells via CD16 (27, 28), we tested their ability to exert a rituximab-dependent ADCC of CD20-expressing cells, as compared with other effector immune cells (Supplementary Fig. S6A–S6D). We found that slan+ monocytes purified from HDs (Fig. 5D; Supplementary Fig. S6A, left) and patients with DLBCL (Fig. 5E; Supplementary Fig. S6A, right) performed a very efficient and comparable rituximab-dependent ADCC of Daudi cells, being much more potent than CD14+ monocytes (Fig. 5D and E; Supplementary Fig. S6C). As expected, NK cells from either HDs (Fig. 5D; Supplementary Fig. S6B, left) or patients with DLBCL (Fig. 5E; Supplementary Fig. S6B, right) exerted the strongest rituximab-mediated ADCC, whereas neutrophils were completely inefficient (Fig. 5D and E; Supplementary Fig. S6D). In addition, rituximab-mediated ADCC was more efficient when suboptimal numbers of slan+ monocytes were cocultured with optimal numbers of NK cells (Fig. 5F). Importantly, HD and DLBCL slan+ monocytes (Fig. 5G) and NK cells (Fig. 5H) were found to also perform a rituximab-dependent ADCC of either primary tumor B cells directly isolated from DLBCL lymph node samples or normal autologous/heterologous B cells. Altogether, data reveal that blood slan+ monocytes from newly diagnosed and untreated patients with DLBCL are, in most cases, expanded, functionally unaltered and able to display efficient rituximab-mediated ADCC activities.

DCM induces slan+ monocytes to differentiate into macrophages displaying an effective rituximab-mediated ADCP

As in vitro surrogate of nodal DLBCL-associated slan+ cells (that were impossible to purify in working numbers), we examined DLBCL-conditioned slan+ monocytes. The latter cells were obtained by incubating HD slan+ monocytes in DCM for 5 days, similarly to the approach previously used to generate tonsil-like slan+ DCs (5). By flow cytometry, DCM-treated slan+ monocytes increase 2/3-fold in size and reproducibly display a macrophage-like phenotype, at least in terms of CD11b, CD14, CD16, CD32, CD40, CD64, CD80, CD86, and CD163 expression (Supplementary Fig. S7A). Also slan+ monocytes from patients with DLBCL treated with DCM (n = 3) displayed a macrophage phenotype, based on CD16, CD32, CD64, HLA-DR, CD86, and CD163 marker expression. DCM-conditioned slan+ cells significantly decreased their ability to perform rituximab-mediated ADCC of Daudi cells, lymph node tumor B cells, or normal blood B cells (Fig. 6A), as opposed to matched DCM-conditioned NK cells, which maintained a potent rituximab-mediated ADCC capacity toward any type of B-cell target (Fig. 6A). When slan+ cells and NK cells obtained from tonsils, or IL34- and IL4 plus GM-CSF–treated slan+ monocytes (differentiated to, respectively, macrophage-like or DC-like cells) were tested for rituximab-mediated ADCC, only tonsil NK cells were effective.

Figure 6.

ADCC, ADCP, and expression of FcγRs by the various slan+ cell types under investigation. A, A total of 5 × 104 slan+ monocytes (left part of the graph) or 5 × 104 NK cells (right part of the graph) treated with DCM were cultured with 5 × 103 calcein-labeled healthy (n = 3), neoplastic B cells (n = 4–7), or Daudi cells (n = 6–8), in the absence (white columns) or the presence (black columns) of αCD20 to perform ADCC. B, A total of 5 × 104 slan+ monocytes from HDs untreated (left part of the graph; n = 2) or treated with DCM (right part of the graph) were cultured with 5 × 103 PKH26-labeled normal (n = 3–4), neoplastic B cells (n = 3–4), or Daudi cells (n = 5–11) in the absence (white columns) or in the presence (black columns) of αCD20. ADCP was then determined after 4 hours of coculture as detailed in Materials and Methods. C, Confocal images (from two independent experiments) showing ADCP of calcein-labeled Daudi cells by DCM-treated slan+ cells. Light blue nuclei (by DAPI staining) of slan+ macrophages and green Daudi cells (by calcein staining) are included as either single or merged fluorescent images. D, A total of 5 × 104 slan+ monocytes from HDs treated with 100 ng/mL IL34 (left part of the graph) or 30 ng/mL GM-CSF plus 20 ng/mL IL4 (right part of the graph) were cultured with 5 × 103 PKH26-labeled normal, neoplastic B cells or Daudi cells in the absence (white columns) or in the presence (gray columns) of αCD20 for ADCP performance. E and F, CD16, CD32, and CD64 expression were analyzed by flow cytometry either in slan+ monocytes (E; white columns) and NK cells (E; black columns) gated within freshly isolated PBMCs from HDs (n = 5–9), or in slan+ monocytes from HDs treated with DCM (F; striped columns; n = 4–5), IL34 (F; black columns; n = 3), and GM-CSF plus IL4 (F; gray columns; n = 3). Values for each FcγR are reported as MFI after subtracting the fluorescence given by the respective isotype control mAb. G, Bar graph shows the effect of 10 μg/mL anti FcγR-blocking antibodies (clone 3G8 for CD16; clone AT10 for CD32; clone 10.1 for CD64; and clone MG1–45 for irrelevant isotype control antibodies) on ADCP of PKH26-labeled B-cell targets by DCM-treated slan+ monocytes (n = 4–6). Data are expressed as percentage inhibition of ADCP.

Figure 6.

ADCC, ADCP, and expression of FcγRs by the various slan+ cell types under investigation. A, A total of 5 × 104 slan+ monocytes (left part of the graph) or 5 × 104 NK cells (right part of the graph) treated with DCM were cultured with 5 × 103 calcein-labeled healthy (n = 3), neoplastic B cells (n = 4–7), or Daudi cells (n = 6–8), in the absence (white columns) or the presence (black columns) of αCD20 to perform ADCC. B, A total of 5 × 104 slan+ monocytes from HDs untreated (left part of the graph; n = 2) or treated with DCM (right part of the graph) were cultured with 5 × 103 PKH26-labeled normal (n = 3–4), neoplastic B cells (n = 3–4), or Daudi cells (n = 5–11) in the absence (white columns) or in the presence (black columns) of αCD20. ADCP was then determined after 4 hours of coculture as detailed in Materials and Methods. C, Confocal images (from two independent experiments) showing ADCP of calcein-labeled Daudi cells by DCM-treated slan+ cells. Light blue nuclei (by DAPI staining) of slan+ macrophages and green Daudi cells (by calcein staining) are included as either single or merged fluorescent images. D, A total of 5 × 104 slan+ monocytes from HDs treated with 100 ng/mL IL34 (left part of the graph) or 30 ng/mL GM-CSF plus 20 ng/mL IL4 (right part of the graph) were cultured with 5 × 103 PKH26-labeled normal, neoplastic B cells or Daudi cells in the absence (white columns) or in the presence (gray columns) of αCD20 for ADCP performance. E and F, CD16, CD32, and CD64 expression were analyzed by flow cytometry either in slan+ monocytes (E; white columns) and NK cells (E; black columns) gated within freshly isolated PBMCs from HDs (n = 5–9), or in slan+ monocytes from HDs treated with DCM (F; striped columns; n = 4–5), IL34 (F; black columns; n = 3), and GM-CSF plus IL4 (F; gray columns; n = 3). Values for each FcγR are reported as MFI after subtracting the fluorescence given by the respective isotype control mAb. G, Bar graph shows the effect of 10 μg/mL anti FcγR-blocking antibodies (clone 3G8 for CD16; clone AT10 for CD32; clone 10.1 for CD64; and clone MG1–45 for irrelevant isotype control antibodies) on ADCP of PKH26-labeled B-cell targets by DCM-treated slan+ monocytes (n = 4–6). Data are expressed as percentage inhibition of ADCP.

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As mentioned above, rituximab is known to also mediate ADCP (24). Accordingly, we found that HD slan+ monocytes are efficient in performing rituximab-mediated ADCP, but only of normal (small) B cells from HDs, and not of B cells of larger size such as Daudi or tumor B cells from nodal DLBCL (Fig. 6B). In contrast, DCM-treated slan+ cells were highly efficient in performing rituximab-mediated ADCP of B cells of any size (Fig. 6B), as also confirmed by confocal microscopy experiments showing that DCM-treated slan+ cells engulf calcein-labeled Daudi cells in the presence of rituximab (Fig. 6C). Consistent with their macrophage-like differentiation (5), also IL34-treated slan+ monocytes were found very efficient in performing rituximab-mediated ADCP of normal/tumor B cells, as well as Daudi cells (Fig. 6D), as opposed to the GM-CSF plus IL4-treated slan+ monocytes (Fig. 6D). As expected, no rituximab-dependent ADCP was performed by NK cells, either if freshly isolated from the blood, or if treated with DCM. Altogether, data suggest that, although slan+ monocytes exert a potent rituximab-mediated ADCC, DCM- or IL34-derived slan+ macrophages display instead an efficient RTX-ADCP of lymphoma cells, but completely lack ADCC competence.

Expression of FcγRIII/CD16, FcγRII/CD32, and FcγRI/CD64 by slan+ cells

Because FcγRs play an essential role in mediating both ADCC and ADCP (29, 30), we investigated CD16, CD32, and CD64 surface expression in slan+-cells and, as comparison, in NK cells, obtained under our various experimental conditions. We found that CD16 is highly expressed in slan+ monocytes and NK cells from either HDs or patients with DLBCL (Fig. 6E), consistent with their strong ADCC capacity. CD32 was expressed by slan+ monocytes only, whereas CD64 was absent in both populations (Fig. 6E). Compared with slan+ monocytes, DCM- and IL34-treated slan+ monocytes were found to upregulate the expression of both CD16 and CD32 and to de novo express CD64 (Fig. 6F), thus displaying an FcγR expression pattern mirroring the DLBCL slan+ macrophages (Fig. 4C, blue columns). In contrast, GM-CSF plus IL4-treated slan+ monocytes were found to maintain the expression of CD32, but to lose CD16 (Fig. 6F), similarly to the DLBCL slan+ DCs (Fig. 4C, green columns). Remarkably, experiments using specific FcγR-neutralizing mAbs demonstrated that particularly CD16, yet in cooperation with both CD64 and CD32, is involved in rituximab-dependent ADCP of B-cell targets by DCM- and IL34-treated slan+ monocytes (Fig. 6G). Altogether, data indicate that DCM- and IL34-treated slan+ monocytes switch into ADCP-effector cells dependent on the combined action of CD16 with CD64 and CD32.

DCM-treated CD14+ monocytes exert a rituximab-mediated ADCP equivalent to that by DCM-treated slan+ monocytes, but using different FcγRs

In comparative experiments, CD14+ and slan+ monocytes incubated with either DCM or IL34 were found to perform equivalent levels of rituximab-mediated ADCP of Daudi cells (Supplementary Fig. S7B), but no significant rituximab-mediated ADCC (Supplementary Fig. S7C). Moreover, CD14+ monocytes incubated with DCM were found to express higher CD32 and CD64, but lower CD16, levels than DCM-treated slan+ monocytes (Supplementary Fig. S7D). Accordingly, neutralization assays performed in DCM-treated CD14+ monocytes uncovered that CD32 and CD64 represent the FcγRs mostly responsible of rituximab-dependent ADCP of B-cell targets (Supplementary Fig. S7E).

Heterogeneity and clinical significance of CD16-expressing cells in DLBCL

DLBCL is an aggressive, heterogeneous B-cell malignancy that includes different biological subtypes. Accordingly, patients with DLBCL might be cured, relapse, or be resistant to standard R-CHOP (31, 32). We could not detect significant differences in slan+-cell density by subgrouping CH2 and CH3 for major clinical and demographic variables (Supplementary Table S8). In addition, no differences were observed in term of PFS, based on the slan+-cell content, in patients homogeneously treated with R-CHOP o R-CHOP–like regimens (Supplementary Table S9). We expanded our IHC analysis to cells potentially involved in RTX-ADCC/ADCP by including all CD16+ cells, as well as CD56+-NK cells. Based on a three-tiered density score, we uncovered that the large majority of DLBCL samples contained CD16+ cells (respectively 95.6% for CH2; 76.5% for CH3; mean 85.1%) with a large fraction of cases showing score 2 (respectively 72.1% for CH2; 41.2% for CH3; mean 55.3%) (Fig. 7A–N; Supplementary Table S8). Significantly, a higher density of CD16+ cells was associated with a more advanced disease stage (P = 0.0096; Supplementary Table S8). In contrast, DLBCL cases containing CD56+ NK cells represented a minor fraction of DLBCL (respectively 25.6% for CH2; 58.8% for CH3; mean 43.7%), with only 7.5% (respectively 0% for CH2; 13.7% for CH3) of the cases showing score 2 (Fig. 7A–C; Supplementary Table S8). None of the biomarkers tested (e.g., slan, CD16 and CD56) was able, alone or in combination, to predict a better outcome to rituximab-containing regimens (Supplementary Table S9).

Figure 7.

Characterization of CD16+ and CD56+ cells in DLBCL. Frequency of the cases containing slan+ cells, CD56+ NK cells and CD16+ cells in CH2 (A), CH3 (B), and CH2/CH3 (C) DLBCL cohorts (S0, S1, and S2 stand for, respectively, score = 0, = 1, and = 2, as indicated in the Materials and Methods section). Sections are from three human nodal DLBCL cases (respectively, D–F; G–I; and J–L) representing recurrent patterns of expression of CD16 (D, G, and J), CD56 (E, H, and K), slan (F, I, and L), CD68 (O), and CSF1R (O), as labeled. Double staining for CD16 and the slan marker (M and N) illustrates DLBCL cases containing a dominant component of slan+/CD16 (M) or slan+/CD16+ (N). slan+/CD16+ also coexpress CD163, as shown by slan/CD163 double stain (inset in N). Most of CD68+-macrophages in DLBCL coexpress CSF1R, as shown in a representative case (O). Sections are counterstained with Meyer's hematoxylin. Original magnification, ×100 (D–L; scale bar, 200 μm), ×200 (M and N; scale bar, 100 μm), ×400 (O; scale bar, 50 μm), ×600 (insets).

Figure 7.

Characterization of CD16+ and CD56+ cells in DLBCL. Frequency of the cases containing slan+ cells, CD56+ NK cells and CD16+ cells in CH2 (A), CH3 (B), and CH2/CH3 (C) DLBCL cohorts (S0, S1, and S2 stand for, respectively, score = 0, = 1, and = 2, as indicated in the Materials and Methods section). Sections are from three human nodal DLBCL cases (respectively, D–F; G–I; and J–L) representing recurrent patterns of expression of CD16 (D, G, and J), CD56 (E, H, and K), slan (F, I, and L), CD68 (O), and CSF1R (O), as labeled. Double staining for CD16 and the slan marker (M and N) illustrates DLBCL cases containing a dominant component of slan+/CD16 (M) or slan+/CD16+ (N). slan+/CD16+ also coexpress CD163, as shown by slan/CD163 double stain (inset in N). Most of CD68+-macrophages in DLBCL coexpress CSF1R, as shown in a representative case (O). Sections are counterstained with Meyer's hematoxylin. Original magnification, ×100 (D–L; scale bar, 200 μm), ×200 (M and N; scale bar, 100 μm), ×400 (O; scale bar, 50 μm), ×600 (insets).

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A significant fraction of DLBCL cases contained CD16+ cells not coexpressing slan (Fig. 7; Supplementary Table S5; Supplementary Fig. S8A–S8T), as also proved by serial sections of two DLBCL cases (Supplementary Fig. S8A–S8H and S8K–S8R, respectively) and double staining (Fig. 7M–N; Supplementary Fig. S8I, S8J, S8S and S8T). We further characterized these CD16+ cells and found that most of them colocalize with macrophages on serial sections (Supplementary Fig. S8F–S8H and S8P–S8R) and coexpress the macrophage markers CD68 (Supplementary Fig. S8I and S8S), CD163 (Supplementary Fig. S8J and S8T), and CSF1R (Fig. 7O). A minor CD16+ component was represented by round to oval cells (Fig. 7J and inset) and polymorphs (Fig. 7G and inset). Significantly, as verified in nine DLBCL cases, the observed macrophage-like phenotype of slan-expressing cells, such as the coexpression of CD163, was restricted to CD16+/slan+ cells (n = 9; Fig. 7N and inset), whereas CD16/slan+ cells were largely negative for CD163, likely corresponding to the DC-like counterpart. By double IHC for the slan antigen and CD163, we extended this analysis subgrouping DLBCL samples based on the dominant polarization of slan+ cells, respectively, in CD163+ slan+ macrophages (n = 21) and CD163 slan+ DCs (n = 45). We could not detect significant differences in terms of patient survival between the two subgroups (Supplementary Table S9). Of note, the two slan+ populations were found in DLBCL cases, irrespectively of their clinical and molecular features (Supplementary Table S10). Together, these findings suggest that cofactors other than the density of cells involved in ADCC/ADCP interfere with the rituximab-mediated clinical response.

In this study, we report that slan+ cells are detectable in nodal and extranodal localizations of several types of NHL, especially DLBCL. We were stunned by the high density of slan+ cells in a remarkable fraction of DLBCL cases, in which intratumoral slan+ cells closely interact with lymphoma cells and, with our surprise, displayed recurrent patterns of lymphoma cell phagocytosis. Thus, we investigated the DLBCL as a model to get insights on the role of slan+ monocytes, and their tissue-differentiated counterparts, in cancer. By using in vitro systems, as well as analyzing peripheral blood and lymph node tissues from patients with DLBCL, we uncovered a dichotomous, mutually exclusive fate of slan+ monocytes in lymphoma tissues, differentiating into either DCs or macrophages. Finally, we could substantiate their relevant ADCC and ADCP capacity.

Based on morphology, clinical presentation, and molecular features, DLBCL encompasses a highly heterogeneous disease spectrum, as clearly indicated by the recent literature (31–33). Our data demonstrate that slan+ cells are observed across any DLBCL subtype (14, 16, 21, 22). The high slan+-cells' density observed in a substantial fraction of DLBCL supports the notion of a steady recruitment of slan+ monocytes from the circulation. Based on in situ analysis of lymph node sections of DLBCL, we could detect a population of smaller slan+ cells, with monocytoid morphology. This slan+ population was localized within and around the high endothelial venules, suggesting recent cell immigration from the blood, fueled by an increased marrow output (6). Accordingly, slan+ monocytes in patients with DLBCL are significantly increased as compared with HDs. It is conceivable that their increase in the circulation, followed by nodal and extranodal tissue infiltration, contribute to sustain the high proinflammatory stromal-derived signatures documented in DLBCL (7, 8). Consistently, we have reported that localization of slan+ cells in metastatic lymph nodes of patients with colon cancer is paralleled by a slight increase in the frequency of slan+ monocytes in the patients' blood, as well as the maintenance of their proinflammatory functions (1).

Most of the patients with DLBCL are treated with rituximab-containing regimens (11, 12). Rituximab is an mAb targeting CD20-expressing B cells. Rituximab activity is dependent on the blockade of the CD20 signaling on tumor cells but also on immune-dependent elimination of lymphoma cells by ADCC and ADCP. NK cells are the main effectors of rituximab-mediated ADCC via their CD16 (25, 26). Although data are still limited, the involvement of nonclassical monocytes as effector cells in ADCC, by virtue of their CD16 expression, has started to be recognized in solid tumors (34). Moreover, data indicate that circulating CD16+ monocytes from HDs and patients with B-CLL exert ADCC activities toward Burkitt lymphoma (Raji), lung (A549), and breast (SKBR3) adenocarcinoma cell lines (28). Remarkably, also slan+ monocytes have been shown to perform some level of ADCC toward cancer cell lines via CD16 and CD32, although this observation was limited to a single study (27). Here, we have significantly extended this finding by showing that slan+ monocytes from both HDs and patients with DLBCL are highly efficient in rituximab-mediated ADCC toward a variety of CD20-expressing B-cell targets, including freshly purified lymphoma cells. Furthermore, by comparative analysis, slan+ monocytes are significantly more efficient than CD14+ monocytes or neutrophils in rituximab-mediated ADCC. In addition, slan+ monocytes and NK cells cooperate in performing rituximab-mediated ADCC, in agreement with their reciprocal activation, in terms of IFNγ production or tumoricidal activities in the case of NK cells (35), or IL12p70 production in the case of slan+ monocytes (36). Together with these previous observations (35, 36), our new findings expand the role of slan+ monocytes as effector cells in various clinical settings in which ADCC might play a significant role. We would speculate that, in addition to perform ADCC of circulating CD20-expressing cells, recently lymphoma-immigrating slan+ monocytes might also contribute to ADCC of lymphoma cells under rituximab therapy.

Based on the pattern of expression of the slan marker, our analysis on reactive lymph nodes and NHL confirms previous observation that slan+ cells are distinct from other specialized macrophages and DCs (1). This study provides an additional level of knowledge on the tissue fate of slan+ monocytes. By combining IHC and flow cytometry analysis, we found that slan+ cells within the lymphoma tissue displayed either macrophage or DC features. These two phenotypes likely reflect the dominant cytokine milieu of the lymphoma tissues. Interestingly, nodal CD163+/CD14hi/CD64hi/CD16hi slan+ macrophages are similar to slan+ cells obtained upon incubation of slan+ monocytes with IL34 for 5 days (5) and also resemble the slan+ cells residing in the lamina propria of colon tissue from patients with Crohn disease (37). However, neither did we detect sizeable amounts of IL34 mRNA and protein in nodal DLBCL containing slan+ macrophages, nor could we block the prosurvival effect of DCM on slan+ monocytes by using GW2580 (a CD115 tyrosine kinase inhibitor; ref. 38), suggesting that macrophage polarization of slan+ monocytes within infiltrated lymph nodes is driven by cytokines and growth factors other than IL34 and M-CSF. Likewise, nodal CD163/CD14low/CD64/CD16low slan+ DCs, similarly to slan+ monocytes incubated in the presence of GM-CSF plus IL4 for 5 days, resembled instead the slanDCs from human tonsils (5). However, according to their negativity for CD83, CD208, and CCR7, they appear largely in an immature state. Clarifying whether such an immature DC phenotype is coupled with immunosuppressive functions requires further studies on DLBCL purified slan+ cells. Interestingly, when slan+ monocytes were cultured in conditioned medium from nodal DLBCL tissue (DCM), they regularly acquired a macrophage-like phenotype. Therefore, we propose that soluble factors are responsible for the macrophage terminal differentiation of slan+ monocytes (at least in vitro), whereas complex cell-to-cell interactions are required to mediate a DC fate within the heterogeneous DLBCL microenvironments. These data, once again, testify for the extreme developmental plasticity of slan+ monocytes based on the tissue microenvironment in which they locate.

As a limitation of this study, we could not purify sufficient slan+ cells from lymphoma tissue to perform functional assays. To overcome such a limitation, we tested slan+ macrophages generated in vitro using DCM as differentiation medium. We found that slan+ macrophages were very effective in rituximab-mediated ADCP, but, unlike slan+ monocytes, totally incapable to perform rituximab-dependent ADCC. This functional skewing is consistent with our observation that nodal slan+ cells can express CD163 and contain apoptotic bodies (or even PAX-5+ MYC+ nuclei from lymphoma cells). The latter finding strongly supports their intrinsic propensity to phagocytose lymphoma cells (even in the absence of rituximab, as revealed by IHC), when macrophage differentiation is favored by the DLBCL microenvironment. Moreover, our data showing that slan+ DC-like cells (generated by culturing slan+ monocytes with GM-CSF plus IL4; ref. 5) are unable to perform both ADCC and ADCP reinforce the view that only the monocyte stage and their terminal differentiation into macrophage-like cells plays a role in target cell clearance via rituximab in DLBCL. Although definitive data on ADCC versus ADCP efficiency by human macrophages from CD16+ monocytes are missing, our results suggest their poor efficiency as ADCC effectors, as herein and previously (39) observed for macrophages derived from CD14+ monocytes. Accordingly, ADCC activity observed in human macrophages is low (40), and often measured at high E:T ratios (i.e., 50:1; ref. 41), or at long time points (i.e., 18 hours or even longer; refs. 40, 41). In contrast, we found that ADCP by slan+ macrophages is already maximal within few hours of coincubation with target cells. Interestingly, we found that slan+ and CD14+ monocyte–derived macrophages perform substantially similar levels of rituximab-mediated ADCP. However, we could demonstrate that they use a different set of FcγRs, namely CD16 in combination with CD32 and CD64 in the case of DCM-treated slan+ monocytes, and CD64/CD32 in the case of DCM-treated CD14+ monocytes. It is of note that ADCP, including phagocytosis of rituximab-coated target tumor B cells, represents an essential killing mechanism adopted by macrophages with a potential clinical relevance (42–44). Of note, multiple evidence of this study indicates that CD16 expression is retained during macrophage differentiation, but is downregulated following a DC program.

Gene expression profiling on DLBCL has shown that “stromal-1” (7) or “host–response” (8) signatures, partially expressed by monocytes/macrophages and including the TNF pathway, are predictors of good outcome to R-CHOP (7). In this study, however, the density of slan+ cells could not predict the outcome of patients with DLBCL to rituximab-containing regimens, even when considering their dominant polarization toward macrophages or DCs. We found that CD16, which is known to be the critical FcγR mediating ADCC by both NK cells (25) and slan+ monocytes (27), is also involved, in cooperation with CD64 and CD32, in ADCP by DCM-generated slan+ macrophages. It should be noted that the molecular mechanisms dictating the switch of CD16 from an ADCC to an ADCP receptor are presently unknown. Only a fraction of slan+ cells in DLBCL express CD16, and they are certainly macrophages. Although still neglected by the literature, our data indicate that infiltration of high amounts of CD16+ cells is recurrent in DLBCL cases. However, CD16 expression (alone or combined with slan and CD56 markers) was unable to predict a better response to rituximab-containing regimens in terms of PFS; on the contrary, it was associated with advanced disease stage. We found that CD16+ cells in DLBCL largely overlap with CD68 and CD163, marking the pool of tumor-associated macrophages (TAM). The latter population is more frequently associated with worse outcome in patients with cancer (45) and represents a relevant component also of the DLBCL microenvironment (46, 47). Of note, most of the TAMs in DLBCL, including those expressing the slan marker, coexpress CSF1R. This finding suggests that their fine modulation, by combining CSF1R blockade (48–50) with compounds mediating ADCC/ADCP effector functions, can become a clinically relevant option in DLBCL and, by extension, to other cancer types. Overall, our results highlight a potentially relevant role of slan+ cells in the NHL microenvironment, particularly in DLBCL. Of note, within DLBCL tissue, numerous CD16-expressing macrophages are found, whose function remains largely unknown. Here, we could substantiate a new role of slan+ monocytes and DLBCL slan+ macrophages as effectors of antibody-mediated tumor targeting in human cancers. Prospective clinical studies should incorporate the slan marker to further extend the knowledge on the role slan+ cells as effector in DLBCL.

S. Pileri has received speakers bureau honoraria from Takeda. No potential conflicts of interest were disclosed by the other authors.

Conception and design: W. Vermi, A. Micheletti, S. Lonardi, M.A. Cassatella

Development of methodology: A. Micheletti, G. Finotti, F. Calzetti, M. Bugatti, C. Agostinelli, P. Balzarini, G. Todeschini, S. Lonardi

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): G. Finotti, C. Tecchio, F. Calzetti, S. Costa, M. Bugatti, S. Pileri, A. Tucci, G. Rossi, L. Furlani, A. Zamò, L. Lorenzi

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): W. Vermi, A. Micheletti, S. Costa, S. Calza, S. Pileri, L. Lorenzi, S. Lonardi, M.A. Cassatella

Writing, review, and/or revision of the manuscript: W. Vermi, A. Micheletti, C. Tecchio, L. Lorenzi, S. Lonardi, M.A. Cassatella

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A. Micheletti, S. Pileri, A. Zamò, F. Facchetti, M.A. Cassatella

Study supervision: W. Vermi, M.A. Cassatella

This work was supported by grants from Associazione Italiana per la Ricerca sul Cancro – Italy to M.A. Cassatella (AIRC, IG-15454) and W. Vermi (AIRC, IG-15378), as well as from University of Verona (Ricerca di Base) to M.A. Cassatella. A. Micheletti and G. Finotti are recipients of fellowships from, respectively, “Fondazione Umberto Veronesi” and “Fondazione Italiana per la Ricerca sul Cancro,” whereas S. Lonardi. is supported by “Fondazione Beretta” (Brescia, Italy). We thank Luisa Benerini Gatta for analysis of IL34 expression in human DLBCL.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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