A major mechanism through which neutrophils have been suggested to modulate tumor progression involves the interaction and subsequent modulation of other infiltrating immune cells. B cells have been found to infiltrate various cancer types and play a role in tumor immunity, offering new immunotherapy opportunities. Nevertheless, the specific impact of tumor-associated neutrophils (TAN) on B cells has largely been overlooked. In the current study, we aimed to characterize the role of TANs in the recruitment and modulation of B cells in the tumor microenvironment (TME). We showed that TANs actively participate in the recruitment of B cells to the TME and identified TNFα as the major cytokine mediating B-cell chemotaxis by TANs. The recruitment of CD45+B220+CD138− splenic B cells by TANs in vitro resulted in B-cell phenotypic modulation, with 68.6% ± 2.1% of the total migrated B cells displaying a CD45−B220+CD138+ phenotype, which is typical for plasma cells. This phenotype mirrored the large proportion (54.0% ± 6.1%) of CD45−B220+CD138+ intratumoral B cells (i.e., plasma cells) in Lewis lung carcinoma tumors. We next confirmed that the differentiation of CD45+B220+CD138− B cells to functionally active CD45−B220+CD138+ plasma cells required contact with TANs, was independent of T cells, and resulted in IgG production. We further identified membranal B-cell activating factor (BAFF) on TANs as a potential contact mechanism mediating B-cell differentiation, as blocking BAFF-receptor (BAFF-R) significantly reduced IgG production by 20%. Our study, therefore, demonstrates that TANs drive the recruitment and modulation of B cells into plasma cells in the TME, hence opening new avenues in the targeting of the immune system in cancer.
The contribution of nonmalignant cells to tumor development and progression is now indisputable (1). Multiple immune cell types have been demonstrated to infiltrate the tumor and participate in the modulation of the tumor microenvironment (TME) together with other nonimmune stromal cells. In cancer, modulation of the immune system occurs, which is regarded as an “immunosuppressive switch” during which tumor-infiltrating immune cells are polarized and modulated to support tumor progression (2–4).
Neutrophils make up a significant portion of the immune infiltrate in many types of cancer (5, 6). Data collected from both animal models and human studies have identified tumor-associated neutrophils (TAN) as key players in multiple aspects of cancer, from malignant transformation to tumor progression, modification of the extracellular matrix, immunosuppression, and angiogenesis (7–9). A major mechanism through which neutrophils have been suggested to affect tumor growth has been via modulation of other infiltrating immune cells (10, 11).
The function of B cells in cancer has also been the subject of growing interest. B cells infiltrate tumors in a wide variety of cancer types, including lung, ovaries, colon, liver, and pancreas tumors (12). However, thus far, conflicting evidence has accumulated about their role in the cancerous process—B cells have been shown to, on the one hand, facilitate tumor progression and, on the other, retain the ability to inhibit tumor growth. The antitumoral activity of B cells can be mediated via production of antibodies driving direct toxicity toward tumor cells, called antibody-dependent cellular cytotoxicity (13), as well as via activation of T and natural killer cells through cytokine production (14, 15). In contrast, B cells can support tumor growth through the initiation of an inflammatory process which promotes carcinogenesis, production of lymphotoxin, angiogenesis, and inhibition of T-cell activity (16, 17). A possible explanation for this duality could be the presence of different B-cell subsets, such as regulatory B cells or antibody-secreting plasma cells, presenting different functions and abilities (18, 19).
B-cell migration is driven by a variety of chemokines and cytokines such as CXCL13, CXCL12, CCL21, and CCL19, or by direct contact with target cells via membrane receptors. Although secretion of cytokines and chemokines by tumor cells has been suggested to be one of the main mechanisms driving B cells' infiltration into tumors (20), there are still limited data on the mechanisms driving B-cell accumulation in tumors and the cues modulating B-cell fate in the TME. In the current work, we investigated the role of TANs in the modulation and recruitment of B cells into the TME.
Materials and Methods
The Lewis lung carcinoma (LLC) cell line and murine breast tumor 4T1 cell line were purchased within the last 6 years from the ATCC. Tumor cells were cultured and maintained in DMEM supplemented with 10% heat-inactivated FBS (HI-FBS), 2 mmol/L glutamine, penicillin (100 U/mL), and streptomycin (100 μg/mL; all from Biological Industries), at 37°C with 5% CO2. All cell lines were regularly tested and maintained negative for mycoplasma contamination. The cell lines were expanded and cryopreserved according to ATCC guidelines. Cell lines were typically passaged 4 to 6 times between thawing and injection to mice. Cell lines were not authenticated.
Five- to 6-week-old, 20 to 25 g, female C57BL/6 or Balb/c mice were purchased from Harlan Laboratories. TNF-knockout (KO) mice (C57Bl/6 background) were a kind gift from Professor Michal Banyash, Faculty of Medicine, University of Jerusalem, Israel. Mice were housed under specific pathogen–free conditions at the Hebrew University School of Medicine Animal Resource Center. The protocols were approved by the Institutional Animal Care and Use Committee of the Hebrew University School of Medicine (Approval number MD-17-15237-5). In all experiments, animals were euthanized before surgery.
Mice were injected to the flank with 2 × 106 LLC or to the breast pad with 1 × 106 4T1 cells. Following tumor inoculation, tumor size was monitored using a digital caliper (MRC Laboratory Instruments) twice a week, starting from the size of ∼100 mm3 until the end of the experiment. Two to three weeks following injection, tumors were harvested, minced, and digested in L15 medium (Merck Sigma-Aldrich) containing collagenase type II (0.05 mg/mL), elastase (0.025 mg/mL, both from Worthington Biochemical), and DNase I (0.025 mg/mL; Roche Applied Science) at 37°C for 45 minutes. Tumor lysates were then filtered through sterile 40 μm strainer (Lifegene) and centrifuged at 1,300 rpm for 8 minutes at room temperature (RT). Supernatants were discarded and red blood cells in pellets were lyzed using 1 mL RBC lysis buffer (Sartorius-Biological Industries) for 1 minute at RT. Lysis was stopped by adding 1X PBS supplemented with 0.5% BSA, and lysates were centrifuged at 1,300 rpm for 8 minutes at RT. Pellets were then resuspended in EasySep buffer (1X PBS with 2% FBS and 2 mmol/L EDTA) for further neutrophil isolation as described below or resuspended in FACS buffer (1X PBS with 2% FBS, 2 mmol/L EDTA, and 0.1% sodium azide) for flow cytometry analysis as described below. Spleens were collected in 1X Hank's Balanced Salt Solution (HBSS; Sartorius-Biological Industries) supplemented with 2% FBS for further splenic cell culture or cell isolation as described below. Bones were collected in PBS for further isolation of bone marrow neutrophils (BMN) as described below.
Neutrophil depletion was achieved by i.p. injection of 150 μg of InVivo anti-Ly6G (clone 1A8; BioXCell) in 100 μL PBS, starting from an average tumor size of 200 mm3, every 2 days for 8 (for short-term) or 11 (for long-term) days. Depletion of neutrophils from the spleen and tumor was confirmed by flow cytometry. Tumors harvested at the end of the experiment were measured and weighted, digested as described above, and total number of cells of each tumor was counted using a hemocytometer. The percentage of immune cells in the tumors was further determined by flow cytometry as described below.
Following tissue digestion, cell isolation, or overnight culture, cells were fixed with 1% paraformaldehyde (BarNoar) diluted in FACS buffer for 20 minutes at 4°C. Cells were then washed with FACS buffer, centrifuged at 1,300 rpm for 6 minutes at 4°C, and resuspended in FACS buffer. Cells at a concentration of 1 × 106cells/100 μL were then incubated with FcBlock (anti-CD16/CD32, clone 2.4G2, dilution 1:50, Biogems) for 10 minutes in ice, and stained on ice for surface markers with the following antibodies: phycoerythrin (PE)- or allophycocyanin (APC)-conjugated anti-Ly6G (Clone 1A8, Biogems), PE- or FITC-conjugated anti-CD11b (clone M1/70; Biogems), BGViolet450- or APC-conjugated B220 (clone RA3-6B2; Biogems), PE-conjugated anti-CD138 (clone REA104; Miltenyi Biotec), FITC-, APC-, or BGViolet450-conjugated CD45 (clone 30-F11, Biogems), FITC-conjugated CD19 (clone 1D3; Biogems), APC-conjugated CD256/APRIL (clone REA347; Miltenyi Biotec), APC-conjugated CD257/BAFF (clone REA767; Miltenyi Biotec), APC-conjugated anti-CD4 (clone GK1.5; Miltenyi Biotec), BGViolet450-conjugated anti-CD8 (clone 53-6.7; Biogems), VioBlue-, APC-, or PE-conjugated Ly6C (REA796; Miltenyi Biotec), BGViolet450- or PE-conjugated anti-CD11c (clone N418; BioLegend). Isotype control antibodies were as follows: APC-conjugated rat IgG2a (clone 2A3; Biogems), FITC-conjugated rat IgG2b (clone RTK4530; BioLegend), BGViolet450 rat IgG2a (clone 2A3, Biogems), PE-conjugated rat IgG2a (clone 2A3, Biogems). Antibodies were diluted in FACS buffer according to manufacturers' instruction and incubated with cells for 40 minutes on ice. Cells were then washed with additional FACS buffer, centrifuged, and resuspended in FACS buffer. Samples were then filtered through 40 μm strainers, and cell staining was evaluated using Fortessa flow cytometer (BD Biosciences). Data were analyzed using FlowJo software. Neutrophils were identified as FSClowSSChighLy6G+. Intratumoral B cells were identified as FSClowB220highCD19+CD11b−. Splenic B cells were identified as CD45+B220high.
Isolation of TANs and splenic cells
TANs were isolated from digested tumors by staining with PE-conjugated anti-mouse Ly6G (clone 1A8; Biogems) and using the EasySep PE selection Kit (STEMCELL Technologies) according to the manufacturer's protocol. Purification of neutrophils was confirmed by flow cytometry, using PE-conjugated anti-Ly6G, showing a purity of about 90%. It is possible that a minute number of other cells, though to a nonsignificant extent, contaminated the samples in isolation experiments.
Spleens from LLC tumor–bearing mice were harvested into HBSS buffer (Biological Industries) with 2% FBS, crushed, filtered through a 40 μm filter, and centrifuged at 300 x g for 10 minutes at RT. RBCs were lysed using ACK buffer (0.15 mol/L NH4Cl, 10 mmol/L KHCO3, and 0.1 mmol/L Na2EDTA). Cells were then resuspended in 1X PBS + 0.5% BSA or RPMI supplemented with 10% HI-FBS, penicillin (100 U/mL), and streptomycin (100 μg/mL).
Splenic B cells were isolating by staining with APC-conjugated anti-mouse B220 (Biogems) and using the EasySep APC selection Kit (STEMCELL Technologies). Isolated B220+ cells were further stained with BGViolet450-conjugated anti-CD45, APC-conjugated anti-B220, FITC-conjugated CD19, or FITC-conjugated CD11b and confirmed to be CD45+/B220+/CD19+/CD11b−, with purity above 94%, ruling out contamination by myeloid cells. T cells were isolated from the spleen using an EasySep CD4+/CD8+ T-cell isolation kit (STEMCELL Technologies). Purification of isolated cells was confirmed by flow cytometry, using APC-conjugated anti-CD4 and BGViolet450-conjugated anti-CD8, showing a purity above 90%.
For isolation of BMN, bone marrow (BM) cells were harvested from the femur, tibia, and humerus of tumor-bearing mice, in PBS, RBCs were lysed as described, and neutrophils were purified using the EasySep Neutrophil Negative selection kit according to the manufacturer's protocol. Purification of neutrophils was confirmed by flow cytometry, showing a purity of about 95%.
Air pouch model: In vivo migration assay
C57BL/6 mice were anesthetized with 2% isoflurane, and dorsal air pouches were obtained by injecting 5 mL of air subcutaneously using a sterile 5 mL syringe (BD Bioscience) with 25Gx5/8″ sterile needle on days 0 and 3. On day 5, 1 × 106 TANs or BMNs were injected into the air pouches, and pouch lavage was carried out 24 hours later with sterile PBS. The total number of infiltrating cells was counted, and cells were stained using the following combinations: PE-conjugated anti-CD11b and VioBlue-conjugated anti-Ly6C, PE-conjugated anti-CD11b and BGViolet450-conjugated anti-CD11c, or APC-conjugated anti-B220 and BGViolet450-conjugated anti-CD45, and the absolute number of monocytes (CD11b+Ly6C+), dendritic cells (DC; CD11b+CD11c+), and B cells (CD45+B220+) was determined using flow cytometry. The number of immune cells entering the pouch when no neutrophils were injected to the pouch was deducted as baseline.
Boyden chamber: In vitro migration assay
Splenic cells (0.5 × 106) isolated from tumor-bearing mice were plated onto 5 μm pore size polycarbonate membrane inserts (Millipore) suited for 24-well transwell plates (Corning Costar), whereas 1 × 106 neutrophils were plated onto the bottom chamber, in the absence or presence of the CXCR4 inhibitor AMD3100 (10–12 μg/mL, Sigma), anti-CXCL12 (25 μg/mL, R&D systems), anti-CXCL13 (15 μg/mL, R&D systems), anti-MIG/CXCL9 (1–5 μg/mL, R&D systems), or anti-TNFα (Etanercept, 22 mg/mL, TEVA). Following overnight incubation, cells were harvested from the bottom chamber and stained with APC-conjugated anti-CD45 and BGViolet450-conjugated anti-B220 (Biogems). The number of migrating B cells was calculated based on the percentage of CD45+B220+cells as determined by flow cytometry out of total number of cells collected. Spontaneous diffusion was tested with RPMI media only in the bottom chamber. In experiments in which contact was prevented between TANs and B cells, splenic B cells were plated in the bottom chamber, and TANs were plated onto 0.4 μm transwell inserts (Millipore).
Differentiation of B cells to plasma cells and IgG production
For coculture of isolated splenic B cells with TANs, 0.5 × 106 of splenic B220+ B cells (isolated from spleens of tumor-bearing mice) were mixed with 0.5 × 106 of isolated TANs per well in 96-well plates, in 250 μL complete RPMI media, in the absence or presence of anti–BAFF-R (15 μg/mL), anti-TACI (15 μg/mL), or anti-BCMA (25 μg/mL; all R&D Biosystems) at 37°C for 1 hour, prior to adding neutrophils. Following overnight coculture, cells were harvested and centrifuged at 1,280 rpm (4°C for 6 minutes). Supernatants were collected for further quantification of IgG concentration using a Mouse IgG ELISA Kit (ab157719, Abcam) according to the manufacturer's instructions. One hundred microliter of supernatant either nondiluted or diluted 1:5 in diluent buffer (provided by manufacturer) was used for each well, and duplicates were made for each sample. Concentrations were calculated based on a standard curve within the range of 0 to 200 ng/mL and adjusted in case of dilution. Color development was monitored at 450 nm within 10 minutes following addition of the stop solution, using Tecan Spark microplate reader.
Pelleted cells were resuspended in FACS buffer (1X PBS, 2% FBS, 2 mmol/L EDTA, and 0.1% NaN3), stained with APC-conjugated anti-mouse B220 (Biogems) and PE-conjugated anti-mouse CD138 (Miltenyi Biotec), and analyzed via flow cytometry (described above).
Quantification of tumoral TNFα
Following Ly6G-depletion experiments, control and Ly6G-depleted tumors were harvested and digested as described, and 1 × 106 whole tumor cells were plated in 600 μL complete RPMI media in a 24-well plate. Following overnight incubation, media were harvested and centrifuged at 1,300 rpm at 4°C for 6 minutes to pellet remaining cells or debris, and supernatants were collected and stored at −80°C. TNFα concentrations were quantified using the Murine TNFα Standard ABTS ELISA Development Kit (Peprotech) according to manufacturer's instructions. One hundred microliter of undiluted supernatant was used for each well, and duplicates were made for each sample. Concentration was calculated based on a standard curve within the range of 0 to 2000 pg/mL. Color development was monitored at 405 nm within 30 minutes following addition of the 2,2′-Azinobis [3-ethylbenzothiazoline-6-sulfonic acid]-diammonium salt (ABTS) substrate, using Tecan Spark microplate reader.
Correlation between neutrophils and the presence of B cells in human cancer
CEACAM8 (CD66b) and ELANE (neutrophil elastase) gene expressions in human lung adenocarcinoma and breast invasive carcinoma were determined, and correlation with various B-cell markers was assessed. Gene expression data were generated using The Cancer Genome Atlas (TCGA) consortium Firehose Legacy dataset and analyzed using the cBioportal Web tool (https://www.cbioportal.org). All samples from patients with lung adenocarcinoma (230 samples) and breast invasive carcinoma (960 samples) were included. Graphs showing the individual gene expression and correlation between the expressions of the different genes were created using cBioportal analysis tool. The Pearson correlations, Spearman correlations, and P values were calculated by the analysis tool.
Formalin-fixed paraffin-embedded LLC tumor sections (5 μm thickness) were deparaffinized with xylene and rehydrated through gradient ethanol immersions (100%, 95%, and 70%, respectively). Sections were then treated with 10 mmol/L sodium citrate (pH = 6) for antigen retrieval. Following washes with 1X PBS, sections were blocked and permeabilized with 1X PBS containing 0.3% Triton X-100 (J.T. Baker) and 20% horse serum (H0146, Merck Sigma-Aldrich) for 1 hour at RT in a wet chamber. Tissues were then stained with FITC-conjugated anti-myeloperoxidase (MPO, clone 2D4; Abcam) and APC-conjugated anti-B220 (clone RA3-6B2; Miltenyi Biotec) diluted at 1:100 and 1:50, respectively, in permeabilization buffer, and incubated in a wet chamber overnight at 4°C. Sections were then washed and mounted with mounting medium containing DAPI (Abcam), and the presence of B cells (identified by surface B220-APC) and neutrophils (identified by surface and intracellular MPO-FITC) in the tissue was assessed. Images were acquired using a Nikon Confocal A1R microscope.
Quantification and statistical analysis
For studies comparing differences between two groups, we used unpaired or paired Student t tests. For studies comparing more than two groups, we used one-way ANOVA with Tukey multiple comparisons test. Differences were considered significant when P < 0.05. Data are presented as mean ± SEM. All statistical analyses were performed using GraphPad Prism software (https://www.graphpad.com/scientific-software/prism).
TANs participate in the recruitment of B cells to the TME
We first aimed to evaluate whether TANs play a significant role in the recruitment of B cells to the TME. Using an in vivo air pouch migration assay, purified TANs or BMNs were injected into a sterile air pouch, and the presence of different immune cell types attracted into the air pouch was evaluated. Whereas TANs and BMNs showed comparable ability to attract monocytes and DCs, TANs attracted significantly more B cells than BMNs (P < 0.001; Fig. 1A). We next asked whether TANs actively participate in the recruitment of B cells to the TME. Neutrophil depletion in LLC tumor–bearing mice using monoclonal anti-Ly6G significantly delayed tumor growth (781 ± 38 mm3 for depleted tumors vs. 944 ± 61 mm3 control tumor on day 7 of treatment, P < 0.05; Fig. 1B) and reduced the presence of TANs in the tumor (P < 0.001), although the amount of intratumoral CD45+ cells was not affected (Fig. 1B). We found a significant decrease in the presence of intratumoral B cells, identified as FSClowB220highCD19+CD11b− (Fig. 1C; Supplementary Fig. S1), in the depleted animals compared with control mice. Whereas B220+ cells represented 5.92% ± 0.44% (median, 6.45%; range, 2.7%–7.9%) of the tumor in untreated mice, neutrophil depletion induced a significant reduction in B-cell infiltration (3.39% ± 0.29%; median, 3.02%; range, 1.8%–5.8%; P < 0.01; Fig. 1C). A trend of this decrease could also be seen when normalizing the absolute number of B cells by tumor weight and was further significantly enhanced if neutrophil depletion was performed for longer times (Supplementary Fig. S2A). These results suggest that TANs play an active role in the differential recruitment of B cells into tumors.
Tissue immunostaining further revealed that B cells and TANs were found in close proximity in LLC tumors (Supplementary Fig. S1D). It should be noted that neutrophil depletion in the LLC tumor model resulted in a tendency toward an increase in total intratumoral myeloid cells and intratumoral CD8+ T cells (Supplementary Fig. S2B), similarly to what has been previously described in other tumor models (21–23). However, the individual repercussion of each of these changes on B-cell phenotype needs further evaluation.
TANs recruit B cells in a TNFα-dependent manner
Multiple chemokines, primarily CXCL12, CXCL13, and CXCL9 (MIG), have been implicated in promoting the chemotaxis of B cells (24). Blocking the chemokine receptor CXCR4 or the chemokines CXCL12, CXCL13, and CXCL9 did not impair the recruitment of B cells by TANs (Fig. 2A). Following older reports that suggest TNFα may act as a chemoattractant for B cells (25), we next assessed the involvement of TNFα in B-cell recruitment by TANs. Etanercept, a TNF inhibitor that prevents binding to the TNF-receptor, significantly reduced (by 35%) the chemoattraction of B cells by TANs in a transwell assay (Fig. 2B), significantly decreasing the amount of migrating B cells in the presence of the blocking antibody (P < 0.001; Fig. 2C). To further confirm the importance of TNFα in driving this chemotaxis, we assessed the chemotactic ability of TANs isolated from TNF-KO compared with wild-type (WT) tumor-bearing mice. TANs isolated from TNF-KO mice had significantly impaired ability to attract B cells compared with WT TANs (P < 0.05; Fig. 2D), comparable with the migration recorded in the presence of TNFα-blocking antibody (Fig. 2D). Whereas supernatants collected from WT TANs drove B-cell migration (Fig. 2E), this chemotaxis was impaired in the presence of TNFα-blocking antibody (P < 0.01) or in the presence of supernatants collected from TANs isolated from TNF-KO tumor–bearing mice (P < 0.05; Fig. 2E). Intratumoral TNFα concentrations were significantly dampened in Ly6G-depleted tumors (Fig. 2F). Although TNFα is not regarded as a classical B-cell chemoattractant, we showed that it significantly triggered B-cell movement (Supplementary Fig. S3A), consistent with literature (25), and positively supported cell migration in the presence of CXCL13 or CXCL12 (Supplementary Fig. S3B and S3C).
B220+ cells display an intratumoral-like phenotype following recruitment by TANs
Following the migration assays described, we noticed that the B cells that migrated toward TANs displayed an altered phenotype. Whereas B220+ cells in the spleen or whole blood presented a CD45+B220+ phenotype (Fig. 3A, two left plots), we found that a substantial proportion of the intratumoral B cells presented a CD45−B220+ phenotype (71.7% ± 4.9% CD45−), although a high variation was found between specimens (Fig. 3A, 3rd plot). CD45−B220+ cells also represented the majority (68.6% ± 2.1%) of B220+ cells following migration toward TANs in vitro (P < 0.001; Fig. 3A, right plot), mirroring the phenotype of intratumoral B cells (Fig. 3A and B). These results suggest that TANs not only recruit B cells to the TME, but also support their phenotypic modulation during or following chemotaxis.
We, therefore, aimed to investigate the mechanism through which TANs modulated B-cell phenotype. Neutrophil depletion in tumor-bearing mice mostly affected the proportion of intratumoral CD45−B220+ cells (P < 0.05), whereas the proportion of intratumoral CD45+B220+ was not modified (Supplementary Fig. S2C). Because we identified TNFα as a major cytokine driving the recruitment of B cells by TANs, we next asked whether this cytokine may also be involved in the B-cell phenotypic modulation we observed. Blocking TNFα in a Boyden chamber assay did not affect B-cell phenotype and did not affect the CD45+/CD45− ratio (Fig. 3C). When splenocytes were exposed to TAN supernatant in a Boyden chamber assay, the majority of migrating B220+ cells expressed high CD45, reversing the CD45+/CD45− ratio (P < 0.001; Fig. 3D) compared with their phenotype following recruitment with TANs. Collectively, these results demonstrate that the major mechanism through which TANs modulate B-cell phenotype requires contact and is not mediated by TNFα, although cytokines released by TANs may still have some role in modulating B cells following chemotaxis.
TANs modulate B cells to become CD138+ IgG-producing plasma cells
It has been described that B cells can downregulate their CD45 expression when differentiating to plasma cells (26–28). We found that whereas only a minimal fraction of splenic B cells were CD138+ (4.6% ± 0.6%), a substantial proportion of intratumoral B cells (54.0% ± 6.1%) expressed high CD138, a marker for plasma cells (Fig. 4A; P < 0.001). Consequently, whereas the majority of splenic B cells displayed a CD45+B220+CD138− phenotype, the majority of intratumoral B cells exhibited a CD45−B220+CD138+ phenotype (Fig. 4B and C). Following chemotaxis by TANs in the Boyden chamber system, a high proportion (41.7% ± 2.9%) of the recruited B cells became CD138+ (SPLEEN + TAN; Fig. 4D). Blocking contact between these cells abolished B-cell expression of CD138 (SPLEEN//TAN, P < 0.01; Fig. 4D). Further analysis showed that this phenotypic change following contact with TANs mirrored the CD45−B220+CD138+ phenotype found in tumors (Fig. 4E), whereas without contact, the B cells retained their splenic phenotype and did not upregulate CD138 (Fig. 4E and F). These results demonstrate that TANs promote the differentiation of splenic CD45+B220+CD138− B cells into CD45−B220+CD138+ plasma cells, which occurs in the TME in a contact-dependent manner.
We next assessed B-cell differentiation following coculture of isolated splenic B220+ B cells and tumor Ly6G+ TANs at different B cell-to-TAN ratios (B:TAN ratio). Increasing B:TAN ratio (increasing the amount of TANs) to 1:5 significantly enhanced CD138 expression (P < 0.001 vs. 1:1 ratio), reaching a plateau at ratio 1:10 (P < 0.001 vs. 1:1 ratio; Fig. 4G). We then inquired whether B-cell modification to become plasma cells resulted in IgG production (i.e., are these functionally active plasma cells). Coculture of B cells with TANs drove a significant increase in IgG (P < 0.001 vs. B cells alone; Fig. 4H). In accordance with the increase in the expression of CD138 following modulation of B:TAN ratio (Fig. 4G), we also observed a 3-fold increase in IgG production at B:TAN ratios of 1:5 and 1:10 (P < 0.001 vs. 1:1 ratio; Fig. 4H). These results further support the crucial role of TANs as major drivers of B-cell differentiation into active, IgG-secreting, CD45−B220+CD138+ plasma cells.
B-cell differentiation to CD138+ plasma cells by TANs does not necessitate T cells
In order to examine whether T cells have a role in the differentiation of B cells to plasma cells induced by TANs, we cocultured splenic B220+ B cells, T cells, and TANs in various combinations, when contact between one or more of these cell types was avoided (Fig. 5). Coculture of B cells with T cells did not trigger CD138 expression, and only 1.9% ± 0.3% of B cells were CD138-positive. In contrast, 23.8% ± 1.4% of B cells expressed CD138 following coculture with TANs (P < 0.001; Fig. 5A). The presence of T cells together with B cells and TANs had no impact on B-cell CD138 expression. When contact between B cells and T cells was allowed but contact with TANs was avoided (B + T//TAN), CD138 induced by TANs was almost completely inhibited (P < 0.001 vs. B + TAN). Similarly, when TANs and T cells were cocultured, but contact with B cells was avoided, only minimal expression of CD138 was found (P < 0.001 vs. B + TAN; Fig. 5A and B). In accordance with these results, the presence of T cells in the coculture had no impact on IgG secretion by the B cells (Fig. 5C). In contrast, overnight incubation of B cells with TANs drove a significant increase in IgG (P < 0.001 vs. B cells alone), but was not further augmented by the presence of T cells (n.s. vs. B + TAN; Fig. 5C). Overall, these results reinforce our conclusion that TANs are major contributors to driving the differentiation of splenic naïve CD45+B220+CD138− B cells to functionally active CD45−B220+CD138+ plasma cells in the TME in a T-cell–independent manner.
Membranal BAFF expressed on TANs participates in B-cell differentiation
The main cytokines promoting B-cell differentiation to plasma cells are BAFF (tnfsf13b) and APRIL (tnfsf13). Neutrophils have been shown in different models to secrete BAFF (29) and also to express membranal BAFF (30). Because our findings demonstrate that contact is required for TAN-driven B-cell modification, we assessed the presence of membranal BAFF and APRIL on TANs. In our model, we found that TANs expressed membranal BAFF, but not membranal APRIL, and that this expression was not altered following TAN isolation from the LLC tumors (Fig. 6A and B). Blocking BAFF-R significantly reduced IgG production by about 20% (Fig. 6C). Blocking of BAFF-R, TACI, or BCMA on B cells did not modify the expression of CD138 by B cells following coculture with TANs (Fig. 6D), although a trend for decreased CD138 was observed following blocking of BAFF-R. Blocking CD40 in vitro showed not impact on CD138 expression. Collectively, these data suggest that the BAFF pathway plays a role in the differentiation of B cells to plasma cells induced by TANs, but is not the sole mechanism involved.
To investigate whether this phenomenon could occur in other tumor types, we also tested the ability of TANs isolated from the murine 4T1 breast tumor model to reproduce the B-cell modulations observed in the LLC model. We found that 4T1 tumors had minor infiltration of B cells (Supplementary Fig. S4A). TANs isolated from 4T1 tumors showed significantly lower ability to attract B cells compared with LLC-derived TANs (Supplementary Fig. S4B) and failed to trigger in vitro CD45 loss or CD138 expression in splenic B cells (Supplementary Fig. S4C and S4D), in settings identical to those reported for LLC tumors (Fig. 4D). In parallel, 4T1-derived TANs expressed much lower BAFF compared with LLC-derived TANs (Supplementary Fig. S4E and S4F).
In contrast, in our hands, splenic neutrophils isolated from LLC tumor–bearing mice were able to trigger CD138 expression, although they were not able to recruit B cells in vitro (Supplementary Fig. S5).
Neutrophils positively correlate with CD138 expression in human lung cancer
In order to relate our results to patients with human cancer, we next aimed to identify whether a correlation between the presence of intratumoral neutrophils and plasma B cells could be found in human tumors. Using CEACAM8 (CD66b) and ELANE (neutrophil elastase) as markers for the presence of neutrophils in tumor tissue, we found that in lung adenocarcinoma, CEACAM8 gene expression showed a small positive correlation with MS4A1/CD20 (Spearman 0.14, P = 0.03; Fig. 7A, top plot). CEACAM8 gene expression positively correlated with SDC1/CD138 expression (Spearman 0.19, P < 0.01; Fig. 7B, top plot) and with total TNFSF13b/BAFF expression (Spearman 0.2, P < 0.01; Fig. 7C, top plot). These correlations were consistent when correlating ELANE to SDC1/CD138 (Spearman 0.25, P < 0.001; Fig. 7B, bottom plot) or TNFSF13b/BAFF gene expression (Spearman 0.19, P < 0.05; Fig. 7C, bottom plot) and replicable when analyzing two independent TCGA databases (Firehose Legacy, PanCancer, and Nature 2014). In contrast, no such correlation was found between CEACAM8 or ELANE and either of these markers in breast invasive carcinoma. (Fig. 7D–F). We could not find any correlation in lung adenocarcinoma between CD66b and the expression of transcription factors related to B-cell differentiation to plasma cells (such as PRDM1, IRF4, and XBP1).
B cells make up a significant portion of the tumor infiltrate in many types of solid tumors, including breast (31), non–small cell lung cancer (NSCLC; refs. 32, 33) and more. Yet, the function of B cells in solid tumors still remains controversial, as cancer-related B cells can present either antitumor (34) or immunosuppressive functions (35, 36).
In the current study, we demonstrate that neutrophils are involved in both the recruitment of B cells into the TME and in their differentiation to become functionally active, immunoglobulin-secreting plasma cells. TANs are shown to have both pro- and antitumor effects, either directly or through their impact on other cells of the immune system (37). Our study demonstrates a fundamental connection between TANs and the number and activity of B cells in the TME.
Only a few studies have explored the interactions between B cells and myeloid cells, mostly related to myeloid-derived suppressor cells (MDSC). Splenic monocytic-MDSCs (but not splenic neutrophils) suppress B-cell proliferation and antibody production in a nitric oxide (NO)–, Prostaglandin E2 (PGE2)–, and contact-dependent manner (38). Cancer-related splenic Gr1+ MDSCs are also reported to drive L-selectin loss in B cells and T cells in a contact-dependent manner, thus reducing their subsequent trafficking to lymph nodes (39). Similarly, Wang and colleagues report the inhibiting impact of Gr1+ MDSCs on B cells via significantly modifying B-cell subsets in the BM of tumor-bearing animals (40). In contrast, Xu and colleagues report that splenic Gr1+ MDSCs promote the proliferation and IgA production of marginal zone (MZ) B cells (41), and, interestingly, that the cross-talk between MDSCs and B cells requires the presence of TNFR2 on the surface of MDSCs.
Splenic neutrophils are shown to colonize the MZ areas of the spleen, interact with MZ B cells via neutrophil extracellular trap–like structures, and elicit an Ig class switch in a mechanism involving BAFF, APRIL, and IL21 (42). In our hands, splenic neutrophils were also able to trigger CD138 expression, although they were not able to recruit B cells in vitro. To the best of our knowledge, no study has demonstrated the potential of TANs, in contrast to splenic cells, to specifically recruit B cells into the tumor or affect their differentiation to plasma cells.
It is interesting to note that although TNFα plays a role in lymphoid development, cytokine storm and excessive TNFα can suppress germinal center (GC) B cells and impair antibody responses (43, 44). An interesting study on COVID-19, which aimed to understand the reason for the general lack of humoral immune response to coronaviruses, associated the exuberant synthesis of TNFα in secondary lymph nodes following infection and the decrease in GC B cells they observed in patients with SARS-CoV-2 (44). Our observation showing dampened secretion of TNFα in Ly6G-depleted tumors also supports the contribution of TNFα in promoting B-cell recruitment to the tumor. TNFα is not classically considered a typical B-cell chemoattractant. Nevertheless, we found that TNFα triggered B-cell movement, positively adding to the chemoattracting forces.
Our data revealed a relatively quick response of B cells to TANs. Due to neutrophils' short lifespan, coculture of B cells and TANs cannot be performed for longer than overnight, fearing the response of B cells to cell death and cellular debris. This could explain why the percentage of CD138+ cells and the amount of IgG measured were relatively low, compared with studies differentiating B cells for longer times (45, 46).
Using TCGA databases, we showed that CEACAM8 (a neutrophil marker) significantly correlates with the expression of SDC1/CD138 and BAFF/TNFSF13b in human lung adenocarcinoma but not in breast invasive carcinoma. These data recapitulated our findings in mice, showing that TANs in the 4T1 murine breast tumor model were not able to trigger CD138 expression in B cells and expressed significantly lower BAFF compared with LLC-derived TANs. These results suggest that recruitment and differentiation of B cells by TANs is a relevant and possibly important phenomenon in patients with human cancer as well. Further studies are still needed in order to understand the mechanisms through which neutrophils undergo phenotypic modulation in specific tumor types, affecting their ability to drive plasma cell differentiation.
Tumor-infiltrating B cells have been correlated by many studies with favorable survival rates (47, 48) in various tumor types. Nevertheless, the prognostic value of B cells in NSCLC remains controversial, with some studies reporting a better prognosis with high CD20 infiltration (49) and others reporting no such association (50) or negative association (51), possibly depending on tumor stage and histologic classification (52).
Numerous B-cell subtypes (such as regulatory, memory, and plasma B cells) have been described in the TME. Studies suggest that a change in the proportion of these different subtypes with disease progression as well as their location within the TME could potentially affect their overall function (53). The presence of B cells and lymphoid tertiary structures (TLS), for example, has been correlated to patients' response to therapy. In a melanoma cohort, Helmink and colleagues (54) report higher density of CD20+ B cells and TLSs in responders compared with nonresponders to immune checkpoint blockade. Similarly, Petitprez and colleagues (55) report in patients with soft-tissue sarcoma that high density of B cells and the presence of TLSs feature an immune-high class of sarcomas and are associated with the highest response rate to anti–PD-1 immunotherapy. This relationship between TLSs and patient outcome appears to depend on many parameters, including cancer type, disease stage, as well as the cellular composition, organization, and precise location of TLSs in regard to the tumor mass (56).
It is somewhat puzzling that TANs which display, in our tumor model, a global protumor impact (shown by the reduction in tumor growth following neutrophil depletion), drive the differentiation of B cells into plasma cells, a population associated with better prognosis and response to treatment. Multiple studies by us and others have demonstrated that cancer-related neutrophils, including TANs, can be modulated by the tumor milieu and retain the potential to display protumor, as well as antitumor, effects (57), including moderated cytotoxicity toward cancer cells or recruitment and modulation of other immune cells (10, 37). Therefore, it is important to remember that the global impact of TANs is shaped by the sum of all these functions. It is imperative, however, to understand the different and sometimes contradicting effects of TANs on tumor growth and development. The prognostic value of infiltrating plasma cells in solid tumors has remained controversial, as for B cells, in general. In different cancer types, the presence of plasma cells has been associated with both good (58) and bad (59) prognosis. Wouters and colleagues (12) reviewed 54 cohorts representing 15 cancer types and found contradicting prognostic behavior based on the cohorts and on the intratumoral markers used. In the context of lung cancer, the same controversy remains. In patients with lung adenocarcinoma, a high density of intratumoral CD138+ plasma cells (but not total CD20+ B cells) associates with better survival, but this correlation is not true for all patients with NSCLC in the cohort studied (60). Other studies have reported no such correlation between tumor plasma cells and survival (50, 52) or even describe plasma cells as an independent negative prognostic factor (51). In this study, plasma cells were found surrounded by APRIL-secreting cells (mainly neutrophils).
In summary, our study demonstrates in a murine model of lung cancer the recruitment and differentiation of B cells to plasma cells in the TME by TANs. This study further opens the door to many important questions. The additional cellular pathway(s) involved in B cells' rapid phenotypic change into antibody-secreting plasma cells, other functional effects that cancer-related neutrophils may have on B cells, and the clinical consequences of these intercellular connections are currently being explored.
M.E. Shaul reports grants from Israel Science Foundation, Sasson and Luisa Naor Fund, The Cooperation Program in Cancer Research of the Deutsches Krebsforschungszentrum (DKFZ) and Israel's Ministry of Science and Technology (MOST), and Joint Research Fund of the Hebrew University and Hadassah Medical Center during the conduct of the study, as well as a patent for ID-6494–1 pending and licensed to Immunyx. A. Zlotnik reports grants from Israel Science Foundation and Sasson and Luisa Naor Fund during the conduct of the study. L. Arpinati reports grants from Israel Science Foundation, Sasson and Luisa Naor Fund, and German Cancer Research Center DKFZ during the conduct of the study. N. Kaisar-Iluz reports grants from Israel Science Foundation and Sasson and Luisa Naor Fund during the conduct of the study. S. Mahroum reports grants from Israel Science Foundation and Sasson and Luisa Naor Fund during the conduct of the study. I. Mishalian reports grants from Israel Science Foundation and Joint Research Fund of the Hebrew University and Hadassah Medical Center during the conduct of the study. Z.G. Fridlender reports grants from Israel Science Foundation, Sasson and Luisa Naor Fund, The Cooperation Program in Cancer Research of the Deutsches Krebsforschungszentrum (DKFZ) and Israel's Ministry of Science and Technology (MOST), and Joint Research Fund of the Hebrew University and Hadassah Medical Center during the conduct of the study; grants from Israeli Ministry of Health, Israel Lung Association, Israel Cancer Association, and Israel Ministry of Economics, other support from Immunyx, Atrin Pharmaceuticals LTD., and TigaTx, and personal fees from GlaxoSmithKline, AstraZeneca, Roche, Novartis, Boehringer Ingelheim, Teva, and Pfizer outside the submitted work; and a patent for ID-6494–1 pending and licensed to Immunyx. No disclosures were reported by the other authors.
M.E. Shaul: Conceptualization, data curation, formal analysis, methodology, writing–original draft, project administration. A. Zlotnik: Data curation, formal analysis, methodology. E. Tidhar: Data curation, formal analysis, methodology. A. Schwartz: Data curation, formal analysis. L. Arpinati: Data curation, formal analysis. N. Kaisar-Iluz: Data curation, formal analysis. S. Mahroum: Formal analysis, methodology. I. Mishalian: Conceptualization, data curation, formal analysis. Z.G. Fridlender: Conceptualization, supervision, funding acquisition, project administration, writing–review and editing.
This work was supported by a grant from the Israel Science Foundation, the Sasson and Luisa Naor Fund, The Cooperation Program in Cancer Research of the DKFZ and Israel's Ministry of Science and Technology (MOST), and a grant from the Joint Research Fund of the Hebrew University and Hadassah Medical Center.
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