The progression and metastatic capacity of solid tumors are strongly influenced by immune cells in the tumor microenvironment. In non–small cell lung cancer (NSCLC), accumulation of anti-inflammatory tumor-associated macrophages (TAM) is associated with worse clinical outcome and resistance to therapy. Here we investigated the immune landscape of NSCLC in the presence of protumoral TAMs expressing the macrophage receptor with collagenous structure (MARCO). MARCO-expressing TAM numbers correlated with increased occurrence of regulatory T cells and effector T cells and decreased natural killer (NK) cells in these tumors. Furthermore, transcriptomic data from the tumors uncovered a correlation between MARCO expression and the anti-inflammatory cytokine IL37. In vitro studies subsequently showed that lung cancer cells polarized macrophages to express MARCO and gain an immune-suppressive phenotype through the release of IL37. MARCO-expressing TAMs blocked cytotoxic T-cell and NK-cell activation, inhibiting their proliferation, cytokine production, and tumor killing capacity. Mechanistically, MARCO+ macrophages enhanced regulatory T (Treg) cell proliferation and IL10 production and diminished CD8 T-cell activities. Targeting MARCO or IL37 receptor (IL37R) by antibody or CRISPR knockout of IL37 in lung cancer cell lines repolarized TAMs, resulting in recovered cytolytic activity and antitumoral capacity of NK cells and T cells and downmodulated Treg cell activities. In summary, our data demonstrate a novel immune therapeutic approach targeting human TAMs immune suppression of NK- and T-cell antitumor activities.

Significance:

This study defines tumor-derived IL37 and the macrophage scavenger receptor MARCO as potential therapeutic targets to remodel the immune-suppressive microenvironment in patients with lung cancer.

Lung cancer is responsible for the highest number of cancer-related deaths worldwide. Non–small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for 84% of all diagnosed cases. Although tyrosine kinase–based targeted therapy can interfere with oncogenic signaling in NSCLC, acquired resistance to these therapies evolves, leading to rapid clinical relapse and disease progression (1). Checkpoint immunotherapies have resulted in some success in NSCLC, still, monotherapy utilizing anti-PD1 or anti-CTLA4 is currently having clinical efficacy in less than 50% of patients (2). The immunosuppressive tumor microenvironment (TME), hallmarked by prominent myeloid presence in combination with poor infiltration and inactivation of T cells, is likely a major contributor to treatment failure (3). TAMs represent a major inflammatory component of the stroma in many tumors and have been associated with poor prognosis in NSCLC and other cancers (4, 5). It has also been shown that the cancer-driven myeloid cell transition from a proinflammatory to an anti-inflammatory state is a key feature of tumor progression (6, 7). We have recently shown that targeting the scavenger receptor MARCO reduces tumor growth and impairs metastasis in murine tumor models of melanoma, colon, and breast cancer (8). Scavenger receptors constitute a large family of pattern recognition receptors that have the capacity to bind modified lipids and have mostly been studied in connection to cardiovascular disease (9, 10). We also described that MARCO-expressing macrophages are present in human cancers where they represent a protumoral and anti-inflammatory macrophage subset (8, 11). Thus, we hypothesize that targeting MARCO would remodel the suppressive tumor environment, release the antitumor responses, and potentially increase the efficacy of immunotherapy. However, there is limited knowledge about the function of MARCO-expressing human macrophages, and the immune landscape in which MARCO-expressing TAMs operate. It is thus important to know how targeting this subpopulation of TAMs affects other immune cells to have good measures for clinical efficacy besides tumor regression. To accomplish this, the density and localization of T-cell subsets, natural killer (NK) cells, and MARCO-positive and -negative macrophages were assessed in NSCLC. In the same series of patient tissues, we searched for differentially expressed immune-regulatory candidate genes using RNA-sequencing (RNA-seq) data. We then explored the effects of MARCO and associated regulators in functional assays in vitro regarding T-cell and NK-cell effector functions. Finally, we attempted to reverse the MARCO-induced immune suppression using a blocking antibody to the key regulator IL37 as well as direct targeting of macrophages via our newly developed antibody to human MARCO. Our study uncovers novel mechanistic pathways in situ in the TME and tests innovative approach to specifically target suppressive myeloid compartment for the treatment of NSCLC.

Patients and healthy donors

Human lung tumor tissues were used according to the Swedish Biobank Legislation and Ethical Review Act (reference 2012/532, Uppsala Ethical Review Board) and in accordance with the Declaration of Helsinki. Human biological samples, consisting of healthy donor (HD) blood, were sourced ethically, and their research use was in accordance with the terms of the written informed consents under the approved protocol. Cryopreserved peripheral blood mononuclear cells (PBMC) from HD blood donors were obtained following Ficoll-Hypaque density gradient purification. Blood samples from HD donors were procured from the Stockholm Blood Bank. Non–small cell lung cancer (NSCLC) samples (patient characteristics, Supplementary Table S1) with macrophage infiltration were selected and grouped as either MARCO negative or positive based on IHC and transcriptomic analysis performed earlier (11). All samples included in this study had a significant macrophage infiltration based on CD68 staining (2+ or 3+). Cases included in the MARCO-positive subgroup had a MARCO IHC annotation of either 2+ or 3+ and MARCO FPKM values >20 based on RNA-seq data. The MARCO-negative cases had an IHC annotation of 0 (negative) and FPKM values <10.

Immunofluorescence, IHC, and image analysis

Multiplex IHC staining was performed in a sequential order on 4-μm–thick sections from formalin-fixed paraffin-embedded NSCLC tissues. Two six-marker panels were analyzed; a T-cell panel (CD4, CD8, FOXP3) and a NK-cell panel (CD3, CD56, CD57), both including macrophage markers (MARCO and CD68) and a combination of epithelial identifiers, using the Opal 7-color IHC Kit (PerkinElmer). Antigen retrieval and removal of antibodies from the previous cycle was performed by microwave treatment at pH6 or 9. Finally, 4′,6-diamidino-2-phenylindole was used for nuclear staining, followed by mounting with Prolong Diamond Antifade Mountant (Thermo Fisher Scientific). A 10× magnification whole-slide scan was acquired followed by selection of regions for 20× multispectral imaging in Phenocart, using the Vectra 3 system (PerkinElmer). Protein signal intensity was normalized for exposure and spectral unmixing was performed with the inForm Cell Analysis software (PerkinElmer) and normalized with spectral libraries (12). Briefly, images were visually evaluated to exclude areas with necrosis, normal lung tissue, or staining artefacts. Then, tissue segmentation based on manual annotation of three selected regions (tumor, stroma, and blank) was performed using the defined software algorithm. Nuclear dye was used to guide the detection of FOXP3, while the cytoplasmic regions were used to evaluate the expression of MARCO, CD68, CD4, CD8, CD56, and CD57. Data analysis was executed with R software, version 3.6.1. The spatial analysis was based on the x and y coordinates acquired from the inForm software and using the k-nearest neighbor algorithm.

Macrophage isolation and polarization

Monocytes were isolated from HD PBMCs, cultured for 5 days in MCSF, and overnight polarized toward proinflammatory or anti-inflammatory macrophages with LPS (200 ng/mL) + IFNγ (20 ng/mL; LPS + IFNγ) or IL4 (20 ng/mL) + IL10 (20 ng/mL; IL4 + IL10), respectively. Fresh medium supplemented with MCSF was added at day 3. Alternatively, 5-day differentiated macrophages were cocultured with lung cancer cell lines; H1299, H1975, H460, and A549 (authenticated from ATCC, used within three months of the first passage and Mycoplasma tested) for 48 hours separated in transwell inserts to avoid cell-to-cell contact.

NK- and T-cell function assays

CD56+CD3 NK cells were isolated using negative depletion kit. T cells were isolated by CD3-positive selecting microbeads. NK cells were cocultured with macrophages for 3 days at a 1:1 ratio in the presence of IL15 (10 ng/mL) and evaluated for degranulation, IFNγ production, and proliferation. T-cell proliferation, IFNγ, and IL10 production were assessed following stimulation using CD3/CD28 activation in a mixed lymphocyte reaction (MLR). NK- and T-cell function was then evaluated following stimulation with PMA (100 ng/mL) and ionomycin (500 ng/mL) for 6 hours prior to staining.

NK-cell migration assay

NK cells were seeded in transwell inserts with pore size of 5-μm, separated from polarized anti- and proinflammatory macrophages, or medium only. Cells actively migrating to the bottom well were collected, manually counted by blinded personnel, or counted by an automated cell counter, and NK-cell numbers were determined by relative CD56 percentages by flow cytometry.

Flow cytometry analysis

Phenotype and function of tumor cell lines, macrophage, NK-cell, and T-cell function were assessed by surface and intracellular protein staining using fluorochrome-conjugated antibodies against CD14, HLADR, CD68, CD86, CD163, CD206, CD3, CD4, CD8, CD25, CD56, FOXP3, IL10, TGFβ, IL37, TNFα, IL12, ARGI, VEGF, IFNγ, Ki67 (proliferation), and CD107a (degranulation). Detection of cytokines, CD107a and Ki67, was performed following fixation and permeabilization (eBioscience) according to the manufacturer's instructions. Proliferation dye CellTrace (Thermo Fisher Scientific) was used to label T cells and NK cells prior to coculture with macrophages. Fixable live/dead cell dye (Thermo Fisher Scientific) was used to determine viable cells. All cells were acquired by LSRFortessa and analyzed by FlowJo 10.7.

Quantitative RT-PCR

For quantification of gene expression, RNA was isolated from macrophages by RNeasy Mini Kit (Qiagen). cDNA was synthesized from RNA using Superscript IV Reverse transcription (Thermo Fisher; 37°C for 15 minutes, 65°C for 10 minutes). qRT-PCR reactions were performed using SYBR Green Master Mix (Applied Biosystems). Primers used for analysis of gene expression and mRNA quantification were for TNF, IL1B, IL12B, MARCO, MRC1, IL10, PTGS2, PDGFD, IL1RN, RETNLB, FN1, MMP12, TIMP1, and GAPDH (Sigma-Aldrich). All reactions were carried out in the Bio-Rad thermal cycler (Applied Biosystems 7500 Real Time PCR System).

Anti-human MARCO antibody production

Three female MARCO knock-out mice at 8 weeks of age were immunized with 50 μg human MARCO recombinant protein in 100 μL PBS + 100 μL Gerbu adjuvant intraperitoneally injected in accordance with the ethical approval by the Swedish Board of Agriculture and regional ethical committee (Stockholm, reference N161/15). Mice were boosted twice before the collection of spleens. Anti-MARCO antibody production was performed according to the manufacturer's procedure (ClonaCell-HY Hybridoma Cloning Kit, StemCell Technologies). In brief, splenocytes were fused with myeloma cells at 5:1 ratio. After colony formation, individual colonies were disrupted in individual wells in 96-well plates and later tested for MARCO specificity in a sandwich ELISA. Specific clones were expanded, and supernatant was collected for purification of antibodies. Culture supernatants were collected, and the antibodies were isolated by standard protein purification techniques using G-protein–specific separation columns.

Transwell assay

CD3 T cells were isolated from healthy blood donors and cocultured with macrophages for 3 days in direct contact or separated by transwell inserts to allow only for soluble factors exchange in the presence of anti-CD3/anti-CD28 activation beads. Macrophages were either treated with IgG control antibodies or with anti-MARCO antibodies prior to coculture (10 μg/mL). T cells were then assessed for the production of IFNγ and proliferation by flow cytometry.

CRISPR deletion of IL37

We designed two guide RNAs (gRNAs; chopchop; ref. 13) targeting exon 5 of human IL37 gene, g1: CTCTACTGTGACAAGGATAA and g2: AGGAAGTCCGATTCTCCTGG. The two gRNAs were cloned into pX459V2.0-HypaCas9 (Addgene#108294; ref. 14). This vector was used to reduce off-target effects. Two million cells were transduced with gRNA1 (6 μg), gRNA2 (6 μg) plasmids and pmax-GFP plasmid (1 μg) were mixed in nucleofection solution (100 μL) and then nucleofected with the X-001 program (A549 cells), T-020 program (H460 cells) using a Nucleofector 2b device (Lonza; Supplementary Fig. S1A). After 2 days of puromycin selection (1.5 μg/mL), cells were singularized and sparsely seeded to generate single-cell–derived clones in 10-cm dishes. Later, transfection efficacy was investigated by flow cytometry (Supplementary Fig. S1B).

Statistical analysis

All data were first analyzed in the software mentioned above and summarized by Prism Version 8 software (GraphPad). All data were first tested for normal distribution. Thereafter, differences among groups were analyzed by a Student t test or nonparametric Mann–Whitney U tests. P values were corrected using FDR for multiple comparisons (FDR < 0.05 was considered significant). Representative histograms or images were chosen based on the average values.

Infiltration of MARCO-expressing TAMs and regulatory T cells in NSCLC tissue

We have previously showed that MARCO expressing TAMs reside in close proximity to tumor cell nests in NSCLC and coexpress PD-L1 (11). Here, we investigated the density of MARCO-expressing TAMs and their spatial association to immune effector cells in NSCLC tumors. We performed multiplex immunofluorescent staining and multispectral imaging to identify CD4+ T cells, CD8+ T cells, Treg cells (FOXP3+/CD4+), MARCO+TAMs (MARCO+/CD68+), TAMs (CD68+), and tumor cells cytokeratin+ (CK+). Patients with high tumoral infiltration of MARCO+ TAMs had higher infiltration of CD4+ T cells in the tumor-associated stroma and significantly higher infiltration of CD8+ T cells in the tumor nests (Fig. 1A and B). Furthermore, we observed a trend toward higher proportion of MARCO+ TAMs found closer to CD4+ T cells and CD8+ T cells, and around 15% of MARCO+ TAMs were found within 20 μm from Treg cells in the tumor stroma compared with MARCO TAMs. The highest proportion of MARCO+ TAMs was found in close proximity to CD8+ T cells in the tumor nest compared with CD4+ T cells and Treg cells (Fig. 1C). Also, in tumors with high infiltration of MARCO+TAMs, a larger proportion of stromal located Treg cells, CD8+ T cells, and CD68+ cells were within close distance to CD4+ cells (Fig. 1D). In addition, in the tumor nests, we found a larger proportion of CD4+ T cells and Treg cells in close interaction with CD8+ T cells (Fig. 1D). We observed a strong decrease in CD4 T-cell and Treg cell ratio in tumor nests compared with stroma both in MARCO+ and MARCO tumors and although not significant, a trend toward a higher Treg cell ratio in the MARCO+ tumors compared with MARCO tumors (Fig. 1E). In patients with NSCLC, high infiltration of CD8+ T cells in the tumors has been shown to correlate with better prognosis, whereas macrophage and Treg cell infiltration correlated with poor survival (12, 15, 16). Although our results show that CD8+ T cells were abundant in MARCO+ areas, we hypothesize that these are suppressed or exhausted in the presence of anti-inflammatory macrophages and Treg cells.

Lung cancer–conditioned macrophages express MARCO and display an immunosuppressive phenotype

We next sought to investigate the mechanistic interactions between the MARCO+ TAMs and cytotoxic lymphocytes in vitro. Human CD14+ monocytes were differentiated in the presence of MCSF and then stimulated with IFNγ + LPS to push their development toward proinflammatory macrophages that are MARCO negative. Alternatively, they were stimulated with IL4 + IL10, which results in anti-inflammatory macrophages expressing MARCO. We also investigated whether conditioning of naïve macrophages by coculture with lung cancer cell lines (tumor-conditioned macrophages; TCMs; Supplementary Fig. S2A) would induce MARCO and associated immunosuppressive features. Tumor cells and macrophages were separated in transwell inserts to prevent cell-to-cell contact and cultured for 48 hours, allowing for soluble factors to pass freely. We found that MARCO expression was induced to a similar degree as the cocktail of IL4 + IL10 for three out of four TCMs (A549, H1975, and H460; Fig. 2A). Phenotypically, TCMs and IL4 + IL10 induced anti-inflammatory macrophages were characterized by low prevalence of CD86 and HLA-DR and high CD206 and CD163 in comparison with LPS + IFNγ–induced proinflammatory macrophages (Supplementary Fig. S2B; Fig. 2B). This resembles the phenotype that has been reported for anti-inflammatory TAMs with an immunosuppressive phenotype (17). We next used RNA-seq to analyze differential gene expression in NSCLC tumors infiltrated by MARCO-positive or -negative macrophages. Unsupervised analysis showed 674 significant differentially expressed genes (FDR ≤ 0.05, see Supplementary Fig. S3A for top 100 genes) between tumors expressing MARCO and those who did not. Notably, the levels of the differentially expressed genes were homogeneous within the MARCO-positive and -negative patient groups, respectively (Supplementary Fig. S3A). Biological pathway analysis performed in “EnrichR” revealed several regulated inflammatory immune response clusters and Wnt pathway activation (Supplementary Fig. S3B). Furthermore, the list of the most up- and downregulated genes in MARCO+ tumors demonstrated a specific signature involving immune-suppressive and myeloid regulatory genes including IL37, VEGFA, TGFΒR1, IDO1, NOS1, and SOX2 (Supplementary Fig. S3C). To verify our findings and further investigate the MARCO+ macrophage subset, the expression of candidate genes was analyzed in in vitro polarized macrophages and in TCMs using quantitative PCR. In vitro–derived anti-inflammatory macrophages and TCMs expressed high levels of MARCO and displayed reduced mRNA levels of the proinflammatory cytokines TNFa, IL1B, and IL12B, and increased levels of the anti-inflammatory molecules IL10, MRC1, COX2, TIMP1, and FIZZ1 (Fig. 2C). These results show that MARCO expression is associated with a robust anti-inflammatory environment and mimics the findings in murine macrophages (8). Because IL10 + IL4 as well as tumor conditioning from some of the lung cancer cells both induce MARCO, we investigated whether the lung cancer cell lines produced IL10 or other anti-inflammatory cytokines found to be differentially expressed in the RNA-seq analysis. Using flow cytometry, we found that the lung cancer cell lines produced IL10, TGFβ, and the IL1 family member IL37 (Fig. 2D). However, only TGFβ and IL37 levels produced by tumor cells correlated significantly with the expression of MARCO in TCMs (Fig. 2E). Neutralizing antibodies for TGFβ in TCM cultures did not reduce or block the induction of MARCO expression (Fig. 2F). Instead, blocking the IL37 receptor dramatically decreased MARCO and CD163 expression and increased CD86 expression on the macrophages (Fig. 2G). In addition, blocking IL37R in cytokine-derived anti-inflammatory macrophages (IL4 + IL10) alone did not change their suppressive function (Supplementary Fig. S4A). These data show that lung tumor cells drive polarization of macrophages toward a MARCO+ and anti-inflammatory subtype through IL37 production.

NSCLC-conditioned MARCO-expressing macrophages inhibit T-cell activation and tumor killing

Given the immune-suppressive profile of MARCO+ macrophages, we next assessed their capability to suppress immune effector cells. Purified T cells from peripheral blood were cocultured with cytokine derived pro- (LPS + IFNγ) or anti-inflammatory (IL4 + IL10) macrophages and assessed for their capacity to produce IFNγ and to proliferate. We found that anti-inflammatory macrophages suppressed T-cell activation compared with MARCO-negative proinflammatory macrophages. Also, the suppressed T-cell activation correlated with increased MARCO expression and anti-inflammatory polarization of macrophages (Fig. 3AC). This shows that MARCO expression can be used as a measure of the suppressive capacity of macrophages. Similarly, proliferation and IFNγ production were suppressed in T cells cocultured with macrophages conditioned by NSCLC cells (Fig. 3D). When we tested the T cells in a killing assay using lung cancer cell lines that either induce MARCO expression, for example, A549, H460, and H1975, or cannot induce MARCO, for example, H1299 as targets, we also found that the T cells that were cultured with MARCO+ TCMs were less efficient in killing (Supplementary Fig. S4B; Fig. 3E). Thus, MARCO-expressing macrophages actively block T-cell cytotoxicity and inhibit both cytokine production and proliferation.

NSCLC-conditioned MARCO-expressing macrophages inhibit NK-cell function

Next, we investigated how MARCO-positive macrophages interacted with NK cells that also have the capacity to kill tumors and thereby complementing T-cell–mediated cytotoxicity. In NSCLC, we found low infiltration of NK cells, defined by CD56+/CD3, and mature NK cells by CD56+/CD57+/CD3, but there was a trend toward higher frequency of NK cells in the tumor nests in MARCO-negative tumors and the surrounding stromal areas (Fig. 4A and B). In line with this, we found that, in transwell migration assays in vitro, anti-inflammatory MARCO+ macrophages significantly inhibited NK-cell migration (Fig. 4C), suggesting that MARCO+ macrophages may inhibit NK-cell infiltration of NSCLC tumors. When directly testing the outcome of the interaction, we found that similar to T cells, there was a substantial reduction in NK-cell activity when cultured with MARCO-positive macrophages. We found that degranulation, proliferation, and IFNγ production were blocked as well as the NK-cell tumor-targeting capacity in vitro (Supplementary Fig. S4B; Fig. 4DG). In conclusion, MARCO-positive macrophages can suppress activation of both T cells and NK cells. Thus, targeting MARCO-positive macrophages can have a general effect on releasing cytotoxic lymphocyte activation.

Targeting MARCO protects from macrophage immune suppression

We previously found that targeting MARCO in mice activated TAMs and resulted in decreased tumor growth in several models of cancer (8). To test targeting of human MARCO-expressing macrophages in the context of NSCLC, we generated new mAbs against the human MARCO receptor. The anti-MARCO antibodies were added during cytokine polarization to anti-inflammatory macrophages or during tumor conditioning to test whether they could alter the polarization and subsequent suppressive activity. Because we found that IL37 was responsible for MARCO expression in the coculture with lung cancer cells, we also compared the TCM phenotype in the presence of IL37R blockade compared with anti-MARCO. Indeed, anti-MARCO treatment reprogrammed the TCMs toward a proinflammatory macrophage profile and this was also true when IL37R was blocked (Fig. 5A). Furthermore, we found that anti-MARCO treatment resulted in a remarkable re-activation of T-cell proliferation and IFNγ production as well as that it restored NK-cell degranulation and IFNγ production (Fig. 5B and C). Targeting MARCO by antibody did not result in macrophage depletion rather in specific reprograming, shown in unchanged cell viability and also when we tested antibody clones that bind to MARCO, but do not mediate functional changes assessed by retained IFNγ production of T cells (Supplementary Fig. S4C and S4D) Thus, MARCO targeting leads to release of activation of both innate and adaptive arms of cytotoxic lymphocytes. Results show that blocking IL37R during macrophage polarization also resulted in maintained effector cell functions of T and NK cells at levels comparable to when cocultured with control macrophages (Fig. 5D and E). The capacity to restore effector cell activation after IL37R blockade was not observed in TCMs conditioned with the lung cancer cell line H1299 that lacks IL37 expression and cannot induce MARCO. In summary, the results show that TCMs polarized by NSCLC cells can be targeted by an anti-MARCO antibody or by blocking polarization through IL37 to release the activation of both T cells and NK cells.

Targeting MARCO decreases macrophage-induced Treg cell activation while maintaining CD8 T-cell functionality

As MARCO+ TAMs were located close to FOXP3+ Treg cells in NSCLC tissues, we examined the interaction between this T-cell subset and MARCO+ macrophages in vitro. Flow cytometry analysis showed no difference in CD4+ and CD8+ T-cell frequencies when T cells from PBMCs were cultured with pro- or anti-inflammatory macrophages. However, a remarkable increase in Treg cell frequency was observed in cultures with anti-inflammatory macrophages. Interestingly, pretreatment of macrophages with anti-MARCO antibodies reduced Treg cell frequencies back to the levels of T cells cultured with proinflammatory macrophages (Fig. 6A). Although CD8+ T-cell frequency was not affected by the presence of anti-inflammatory macrophages, we found that CD8+ T-cell function was impaired as shown earlier with bulk T-cell cultures (Fig. 6B). When investigating CD8 cells specifically, we found that anti-MARCO targeting restored their functionality. Next, we further investigated the proliferation and cytokine secretion of the Treg cells that were expanded by MARCO-expressing macrophages. We found that they both proliferated and secreted IL10 but this was blocked when anti-MARCO antibodies were added during polarization of the macrophages (Fig. 6C). Next, we examined whether anti-MARCO–treated macrophages need to be in a cell-to-cell contact to activate T cells. T cells and macrophages were either cultured in direct contact or separated by transwell inserts allowing for only soluble factor exchange. Anti-MARCO treated macrophages did not need a direct contact to reinforce T-cell activities compared with IgG-treated macrophages (Fig. 6D). In summary, MARCO+ macrophages can orchestrate the TME by direct inhibition of cytotoxic T cells or indirectly by supporting the expansion and suppressive capacity of Treg cells. Importantly, this suppression can be reversed by the addition of anti-MARCO and in distance to allow killing of tumor cells.

CRISPR knockout of IL37 in lung cancer cell lines remodulates the TME

Given the important role of IL37 in inducing MARCO and an immune-suppressive profile of macrophages in lung cancer, we next knocked out (KO) IL37 in two lung cancer cell lines (Supplementary Fig. S1) and studied the effect of this specific gene targeting on the tumor cells capacity to modulating the macrophages. Wild-type (WT) and IL37 KO tumor cell lines (H460 and A549) were cultured with macrophages as previously described and macrophages were assessed for phenotype changes and suppressive capacity. We found that macrophages had abolished MARCO expression and reduced IL10 production when cultured with IL37 KO cells compared with WT (Fig. 7A and B). Moreover, T cells cultured with IL37 KO TCMs had decreased Treg cell frequency, improved CD8 functional capacity, and reduced Treg activities including proliferation and IL10 production (Fig. 7C,E). In summary, our data show that targeting IL37 or MARCO pathways result in similar phenotypic and functional changes that reprogram immune-suppressive macrophages toward an immune stimulatory phenotype, which is desired in the TME (Graphical Abstract).

Immunotherapy has lately gained attention and has become a well-established anticancer therapy to release the brakes on the immune system (17). However, still a minority of all patients with cancer are expected to respond to the current T-cell–targeted therapies as a result of the immune-suppressive microenvironment (18). Therefore, new targets for immunotherapy are highly desired for combinatory treatments, which could increase the efficacy, are being explored (2). TAMs within the TME control the tumor microenvironment and shape the antitumor responses affecting the clinical response rate in many cancers including NCSLC (5, 19). We previously described a subpopulation of MARCO expressing macrophages present in the TME in human breast cancer, metastatic melanoma, periampullary adenocarcinoma intestinal type, and NSCLC. (8, 11, 20). However, the phenotype and function of human MARCO-expressing macrophages and their interaction with immune cells in the tumor microenvironment were yet to be defined. In this study, we have visualized the spatial relations between anti-inflammatory TAM subsets and effector T cells, Treg, and NK cells in human NSCLC tumors. Using cytokine-generated and tumor-conditioned macrophages, we demonstrated that macrophage expression of the scavenger receptor MARCO is correlated with an immunosuppressive phenotype. These suppressive macrophages were efficient in blocking cytotoxic T cells and NK cells and enhanced Treg proliferation and cytokine production. We also found that human lung cancer cells supported macrophage polarization by providing tumor-derived IL37. Furthermore, we found that targeting MARCO with our newly produced mAbs or interfering with IL37 signaling, repolarizes myeloid cells toward a proinflammatory profile inhibiting their suppressive capacity on T cell and NK cells. This shows that MARCO-expressing macrophages have a similar function in human tumors and that they can be reprogramed to shift polarization toward a proinflammatory phenotype just as in mouse models (8).

The host immune system plays a key role within the TME where different types of immune cells have a contrasting impact on NSCLC progression, while high infiltration of CD8+ T cells is a positive prognostic factor, macrophage infiltration is negatively correlated with survival (12, 15). We have previously shown in human periampullary adenocarcinoma that MARCO expression is linked to poor prognosis, and high infiltration of MARCO+ TAMs is associated with chemotherapy resistance (20). Our early work in a larger cohort of NSCLC unraveled that MARCO+ macrophages exclusively coexpress the immune suppressive molecules CD163 and PDL1. In addition, The MARCO gene expression correlated positively with several genes linked to immunosuppressive TAMs (CD68, CD163, MSR1, IL4R, CHIA, TGFB1, and IL10), while no correlation could be observed to inducible nitric oxide synthase (NOS2), typically expressed by macrophages with antitumor phenotype (11). Here, we show that high presence of MARCO+ myeloid cells in lung cancer tissue is associated with increased frequency of CD4+ and CD8+ T cells, including Treg cells. The balance within the immune landscape of the TME and interactions with T cells has been highlighted as a resistance mechanism for checkpoint immunotherapies (21). In this context, Peranzoni and colleagues provided evidence for the involvement of TAMs as key players in the T- and NK-cell–excluded and suppressive tumor phenotype (22). Here, we show that three out of four lung cancer cell lines induce a myeloid-suppressive phenotype including MARCO expression through IL37. This was specific as the cell line that lacked or expressed low IL37 was not able to induce MARCO. Blocking IL37 receptor or CRISPR IL37 knockout during tumor conditioning of macrophages abolished MARCO induction and reduced their suppressive capacity. We also investigated whether the genetic alterations of the lung cancer cell lines would play a role in the production of IL37. In contrast to PD-L1 expression that was shown to be highly induced in specific mutant variants of KRAS (23, 24), we found no support in the literature for a connection to IL37. However, studies show that different genetic subtypes generate distinctive immune microenvironment and future studies will show if this also connect to IL37 (25, 26). The cytokine IL37 has been shown to promote anti-inflammatory cytokines including IL10 and also IL4 that promote differentiation of myeloid cells. (27, 28). Here we find that these cytokines also induce MARCO expression and a similar suppressive phenotype. We show that IL37 supports Treg cells and it has been shown before that this cytokine influences the suppressive function of these cells. (29, 30). Thus, IL37 contributes both to an autocrine and paracrine induction of anti-inflammatory and suppressive environment. Regarding IL37 in lung cancer, Jiang and colleagues showed that exogenous IL37 treatment of lung cancer cell lines inhibits invasion and metastasis by suppressing the IL6/STAT3 signaling pathway (31). However, they studied the direct effect of IL37 on tumor cells rather than in the context of the complex TME. Also, it has been shown that different IL37 concentrations can result in opposite effects (32), thus it is of high importance to study the IL37 endogenous effect in tumor cells. On the other hand, Zhao and colleagues showed that high IL37 correlates with disease stage and higher infiltration of CD57+ NK cells in hepatocellular carcinoma (33). It is likely that several mechanisms are at work at the same time and that the outcome depends on the one dominating in separate microanatomical niches of the tumor. In the NSCLC tumors infiltrated by MARCO+ macrophages, we found increased numbers of Treg cells that could add to the suppression of T effector cells. We also found evidence that tumor pushes this differentiation including production of anti-inflammatory IL10 in vitro. Targeting IL10 in the TME has been shown to enhance T-cell antitumor responses in previous immune cold tumors lacking infiltration of T cells (34). On the other hand, systematic inhibition of IL10 can mediate adverse effects in enhancing inflammatory diseases in which this cytokine normally plays a significant inhibitory role (35). Therefore, specific targeting of suppressive myeloid cells in the TME is a better option. Because crosstalk between MARCO+ macrophages and cytotoxic lymphocytes result in suppression and that this can be recovered by antibody targeting this would be one way forward. Thus, we suggest that anti-MARCO treatment can be used in combination with anti-CTLA-4 and anti-PD-1/PD-L1 in patients with poor response to improve ineffective checkpoint therapies in patients with NSCLC. Furthermore, anti-MARCO immunotherapy could support other approaches such as cancer vaccinations in NSCLC as it increases the immunogenicity by augmenting the antigen presentation in dendritic cells (36).

To summarize, this study has uncovered an important role of MARCO in the immune landscape of NSCLC. Targeting the MARCO receptor or induction of MARCO through blockade of IL37 receptor are efficient approaches to reprogram suppressive macrophages found in the TME and to restore T-cell and NK-cell antitumor activities. Anti-MARCO antibody treatment is a promising novel modality for treatment of aggressive cancers with inherent immunosuppressive characteristics.

No disclosures were reported.

L. La Fleur: Conceptualization, resources, data curation, software, formal analysis, validation, visualization, methodology, writing-original draft, writing-review and editing. J. Botling: Conceptualization, resources, data curation, software, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, writing-original draft, project administration, writing-review and editing. F. He: Data curation, software, formal analysis, methodology, writing-review and editing. C. Pelicano: data curation, software, formal analysis, methodology, writing-review and editing. C. Zhou: Data curation, software, formal analysis, validation, visualization, methodology. C. He: Data curation, formal analysis, validation, investigation, methodology. G. Palano: Resources, data curation, software, formal analysis, validation, visualization, methodology, writing-review and editing. A. Mezheyeuski: Resources, software, formal analysis, supervision, validation, methodology, writing-review and editing. P. Micke: Resources, software, formal analysis, validation, methodology, writing-review and editing. J. Ravetch: Resources, investigation, writing-review and editing. M.C. Karlsson: Conceptualization, resources, data curation, software, formal analysis, supervision, funding acquisition, validation, investigation, methodology, writing-original draft, project administration, writing-review and editing. D. Sarhan: Conceptualization, resources, data curation, software, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, writing-original draft, project administration, writing-review and editing.

The authors would like to thank Dr. Juan E. Abrahante Lloréns at the University of Minnesota Genomics Center for performing the whole-genome preliminary analysis. This work was supported, in part, by grants from the Swedish Cancer Society, Karolinska Institutet funds, Uppsala County Council (ALF), and Sigurd and Elsa Goljes funds.

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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