Axl inhibition on dendritic cells enhances STING anticancer therapy through type I interferon signaling

Axl inhibition on dendritic cells enhances STING anticancer therapy through type I interferon signaling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Axl inhibition on dendritic cells enhances STING anticancer therapy through type I interferon signaling Todd Aguilera, Isaac Gonzalez, Eslam Elghonaimy, Qiongwen Zhang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5569516/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The Axl receptor tyrosine kinase is pivotal for metastatic tumor progression, tumor immune evasion, and regulating inflammation of innate immune cells. In this study we investigated Axl’s immune function in immunogenic tumors and found that Axl knockout (KO) mice exhibited a significant delay in tumor growth. Single-cell RNA sequencing revealed that Axl deficiency increases CD8 T cell activity. Tumor growth delay was dependent on CD8 T cells and BATF3 expression, indicating a role for Axl in regulating dendritic cell (DC) cross priming activities. Cre-driven conditional KO models further demonstrated that loss of Axl on DCs—but not on macrophages—was sufficient to slow tumor growth, a process reliant on type I interferon (IFN) signaling. Given Axl’s role in modulating IFN-I signaling, we discovered that its absence enhanced the effectiveness of STING agonists and improved the cross-priming capacity of both cDC1 and cDC2 subsets. Biological sciences/Cancer/Tumour immunology Biological sciences/Immunology/Tumour immunology Biological sciences/Cancer/Cancer microenvironment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Tyro3, Axl and MerTK are collectively known as TAM family of receptor tyrosine kinases, which can be expressed by tumor and innate immune cells with differential functions on each cell type. 1 , 2 Axl signaling occurs when its ligand, growth arrest-specific gene 6 (Gas6), binds to phosphatidylserine (PS) on the surface of apoptotic cells most effective when clustered by phosphatidylserine. 1 , 3 On tumor cells, Axl signaling leads to pro-oncogenic cellular pathways promoting increased metastasis, cell proliferation, therapy resistance, and survival through dysfunctional apoptosis/ necroptosis pathways. 4 – 8 The signaling also hinders an anti-tumor adaptive immune response by down-regulating antigen presentation via cell surface MHC class I and altering tumor cytokine expression, supporting an immunosuppressive TME. 9 – 11 Preclinical studies have demonstrated that inhibiting Axl shows therapeutic promise in treating triple-negative breast cancer (TNBC), non-small cell lung cancer (NSCLC), and pancreatic ductal adenocarcinoma (PDAC) tumors. 4 , 11 , 12 By disrupting pro-oncogenic cellular pathways, Axl inhibition restored sensitivity towards chemotherapies, making it a valuable therapeutic target in these cancer types. On myeloid cells, Axl acts as a mediator of inflammation, facilitating the recognition and clearance of apoptotic cells and by the downstream production of suppressor of cytokine signaling proteins 1 and 3 (SOCS1/3). 2,13 SOCS1/3 proteins hinder the production and signaling of pro-inflammatory cytokines, by blocking toll like receptor and type I interferon (IFN) signaling in response to tumor derived danger associated molecular patterns (DAMPs). 14 , 15 Research has shown that IFN signaling in dendritic cells (DCs) is crucial for triggering an anti-tumor immune response. 16 IFNs improve DCs' ability to present antigens, increase the expression of costimulatory molecules, boost the release of pro-inflammatory cytokines, and enhance their movement within tumors and to lymph nodes. Together, these effects enable DCs to activate naïve CD8 T cells. 17 – 21 Expression of Axl has been associated with dysfunctional populations of conventical and plasmacytoid DCs (cDC/pDC) leading to limited anti-tumor and antiviral immunity respectively. 22 , 23 In addition, Axl inhibition can restore sensitivity to targeting PD1in resistant LKB1 mutant NSCLC via sustained TCF1 T cell activity driven by increased IFN production by DCs. 24 Consistently, poorly immunogenic cancers are characterized by a lack of neoantigens and disparities in cDC signaling. 25 Thus, addressing scarcity and functional checkpoints of dendritic cells offers a significant opportunity to identify new therapeutic targets. In this work, we investigated the impact of Axl expression on host immune cells and its influence on anti-tumor immune responses. While much prior research focused on the role of Axl on tumor cells, we aimed to evaluate its significance in the context of host immune cells in the TME. To achieve this, we used Axl knockout (KO) mice with various syngeneic tumor models. This allowed us to assess how the loss of Axl in host immune cells influences tumor growth independently of Axl expression in the tumor cells. We observed CD8 T cell dependent tumor growth delay of immunogenic tumors. This prompted us to investigate the role of dendritic cells and macrophages in Axl-mediated immunosuppression. Our findings revealed that Axl loss on DCs, but not macrophages, was sufficient to enhance T cell-mediated anti-tumor immune responses. The absence of Axl enhanced cDC1 and cDC2 mediated T cell priming that was dependent on type I IFN signaling. Translationally, this mechanism helped us identify a combination therapeutic approach to inhibit Axl while stimulating type I IFN with therapeutics such as radiotherapy or STING agonists. Results Axl KO results in delayed growth of immunogenic tumors To assess the impact of Axl absence on host's immune response, we implanted three syngeneic tumors, immunogenic MC38 (colorectal cancer), B16F0 (melanoma), and Py8119 (triple-negative breast cancer)—into Axl KO mice and compared tumor growth delay to wild-type (WT) mice. B16F0 and Py8119, which are poorly immunogenic, were engineered to express cytoplasmic ovalbumin (cOva) to model antigen presentation. 9 , 26 , 27 All three tumors showed delayed growth in Axl KO mice (Figs. 1 A- 1 C), independent of Axl expression on tumor cells, as confirmed by flow cytometry ( Figure S1 A ). To investigate the tumor growth delay in Axl KO mice, we performed single-cell RNA sequencing (scRNAseq) 7 days after implanting MC38 or B16F0-cOva into WT and Axl KO mice ( Fig. 1 D ). We hypothesized that this analysis would reveal differences in cellular responses, functional states, or cellular interactions. Since the delay was observed in the host knockout mice likely driven by immune mechanisms, day seven was chosen as the peak of adaptive immune response. 28 , 29 To enhance immune cell profiling, CD45 + cells were sorted after tumor dissociation, labeled with CITE-Seq antibodies to aid in cellular annotations and analyzed using 10X platform (Supplementary Table 1). After quality control, 14018 to 14071 cells were identified from MC38 and B16F0-cOva tumors respectively in both WT and Axl KO mice. We observed comparable clusters and cell frequencies between WT and Axl KO hosts in both MC38 and B16F0-cOva tumors ( Figs. 1 E and S1B ). Cell populations were annotated based on canonical markers for each tumor type ( Figs. 1 F and S1C ). We identified Axl expression in immune cell subpopulations, with the highest levels in cDCs, macrophages and monocytes ( Figs. 1 G and S1D ). Similarly, scRNAseq data of myeloid cells from eight different human tumors showed Axl predominantly expressed on cDCs, macrophages and monocytes ( Figs. 1 H and 1 I ). To determine if Axl ablation led to off-target deletions or compensation by other TAM receptors, we assessed MerTK and Tyro3 expressions. MerTK was primarily expressed on macrophages, with no noticeable difference in expression between WT and Axl KO models (Figure S1 E and S1F) . Tyro3 was not detected by scRNAseq in our samples. Cytotoxic T cell activity mediates tumor growth delay in Axl knockout mice Given predominant expression of Axl on myeloid cells, we hypothesized that Axl deficiency might alter the adaptive immune response through myeloid-T cell interactions. We analyzed tumor-infiltrating lymphocytes (TILs) using scRNAseq ( Figs. 2 A and S2A ) and identified three major T cell subpopulations with elevated Ki67 in both WT and Axl KO tumors: Tregs, CD8 + T cells, and NK cells in MC38, and CD8 + T cells in B16F0-cOva models. Ki67 expression was significantly higher in CD8 + T cells from Axl KO mice in MC38 but only slightly increased in B16F0-cOva, suggesting that Axl loss enhances the adaptive immune response, particularly in the MC38 model ( Figs. 2 B and S2B ) . We then assessed CD8 + T cell function status through evaluation of exhaustion and activation markers. In MC38 bearing Axl KO mice, exhaustion markers (Ctla4, Lag3, and Tim3) were significantly reduced, while Pd-1 remained unchanged ( Fig. 2 D ) . Conversely, activation and cytotoxicity markers (Ccr5, Cd28, Eomes, and Gzmk) were elevated in Axl KO CD8 + T cells ( Fig. 2 E ) . In the B16F0-cOva model, CD8 + T cells showed increased immune checkpoints, indicating terminal exhaustion from chronic activation (Figure S2D) , with activation markers also elevated, though Ccr5 and Eomes were not significantly increased (Figure S2E) . These markers are integral to the T cells homing ability to inflammatory sites, sustain activation, and execute their cytotoxic functions, suggesting CD8 + T cells in Axl KO mice are in a more activated state and have enhanced effector functions. 30 – 33 We then observed that Axl KO CD8 + T cells showed increased expression of type I and II interferon receptors and Tcf7, indicating greater sensitivity to interferon signaling ( Fig. 2 F ). This enhanced signaling is known to boost T cell responses, cytokine production, and expands the TCF7-expressing stem-like CD8 + T cell population. 34 , 35 These cells are critical for sustaining immune responses through self-renewal and effector differentiation. 36 , 37 Gene set enrichment analysis (GSEA) confirmed enriched T cell receptor signaling and adaptive immune pathways in Axl KO CD8 + T cells ( Fig. 2 G ) . In contrast, B16F0-cOva bearing Axl KO mice CD8 + T cells exhibited reduced Tcf7 expression and elevated exhaustion markers, indicating terminal exhaustion (Figure S2F) . Despite this, GSEA revealed increased antigen response and reduced wound healing pathways, suggesting these cells were in a later phase of inflammation (Figure S2G) . Overall, Axl KO CD8 + T cells display a more activated and effector phenotype, positioning them as key players in controlling tumor growth. In MC38 tumors, Tregs from Axl KO mice exhibited significantly reduced levels of Ctla4 and Pdl1, which are known to suppress anti-tumor immunity (Figs. 2 C). 38 , 39 The higher expression of these immune checkpoints in WT Tregs suggests a stronger immune suppression in WT mice, alleviated in Axl KO mice. Additionally, Axl KO Tregs had increased IL-2 receptor expression, indicating altered functional dynamics, as this receptor is crucial for Treg proliferation and maintenance ( Fig. 2 C ) . 40 – 42 These differences were not observed in B16F10-cOva (Figure S2C) . We next observed there were no differences tumor models and knockouts of Tgfb1, a well-known known mediator of Treg immunosuppression 43 ( Fig. 2 C and Figure S2C) . These findings suggest that Axl alters the regulatory landscape of the TME by reducing key inhibitory markers on Treg cells that could support greater antitumor immunity. To confirm T cell-mediated antitumor response, we depleted T cells in the MC38 and B16F0-cOva tumor models ( Fig. 2 H ) . CD8 + T cell depletion in Axl KO mice eliminated the tumor growth delay, confirming its dependence on CD8 + cells ( Fig. 2 I ) . In contrast, CD4 + T cell depletion led to a more pronounced tumor growth delay in both models, likely due to the removal of Tregs, which were highly suppressive in these tumors ( Fig. 2 J ) . 44 These results underscore the distinct roles of CD8 + and CD4 + T cells in modulating tumor growth in Axl KO mice. We considered NK cells as mediators of tumor growth delay given that Axl has been implicated in NK cell function. However, Axl expression was low on NK cells in both tumor models, and no significant changes in NK cell activities were observed in Axl KO mice (Figs. 1 G and S1E ). Previous studies report that Axl is crucial for NK cell development, as Axl-deficient mice exhibit impaired NK cell maturation, reduced differentiation, prevent metastases, and diminished cytotoxic activity. 45 – 48 Our scRNAseq data support a marginal difference in NK cell activation or cytotoxicity following Axl knockout with these tumor models ( Figure S2H ). These findings suggested that, while Axl may influence NK cell function in certain contexts, the enhancement of anti-tumor immunity in Axl KO mice is primarily driven by CD8 + T cells. Axl deficient cDC1 cells are key to tumor growth suppression Given the increased CD8 + T cell activation in Axl KO mice, we investigated whether DCs drive the antitumor response, as they bridge innate and adaptive immunity. 49 , 50 Sub-clustering of myeloid cells from the scRNAseq experiment identified cDC1, cDC2, and DC3 subpopulations of DCs in both tumor models (Figs. 3 A and S3A). Intratumoral myeloid populations were similar between Axl KO and WT mice, except for an increased frequency of cDC1 cells in MC38 tumors and a decreased presence of mast cells in B16F0-cOva tumors (Figs. 3 B and S3B). GSEA of the entire DC population revealed elevated levels of cytotoxic T cell activation, antigen processing and presentation, and humoral immune response in intratumoral DCs from Axl KO mice in MC38 tumor, with increased inflammatory signaling in B16F0-cOva tumors ( Figs. 3 C and S3C ) . We focused on cDC1 cells due to their proficiency in cross-presentation of antigens to CD8 + T cells and higher frequency in MC38 TME. 25 , 49 , 50 To test whether the absence of Axl enhances DC-mediated T cell priming, we performed a T cell priming assay using flow cytometry sorted splenic cDC1 cells ( Figure S3D ) pulsed with ovalbumin protein and Kdo2-Lipid A, a TLR-4 agonist comparable to LPS, then co-cultured with CFSE labeled CD8 + OTI cells for three days (Fig. 3 D). Co-culture with cDC1 cells from Axl KO mice significantly increased OTI T cell proliferation and CD69 expression ( Figures S3E, 3E and 3F ). To determine if cDC1s contribute to the tumor growth delay in Axl KO mice, we crossed Axl KO mice with cDC1 deficient Batf3 KO mice and assessed tumor growth delay. The delayed growth of MC38 and B16F0-cOva tumors observed in AXL KO mice, was ablated in absence of cDC1, with growth rates matching those in BATF3 KO mice (Fig. 3 G). This indicates that the tumor growth delay in Axl KO mice is dependent on cDC1 cells. To assess whether cDC1 cells are sufficient to delay tumor growth, we co-injected cDC1 cells from Axl KO mice ( Figure S3F ) with MC38 tumor cells into WT hosts ( Fig. 3 H ). This experiment led to significantly delayed MC38 tumor growth as compared to co-injection with WT cDC1. Therefore, we conclude that Axl-deficient cDC1 cells in TME are the key driver of delayed tumor growth. The loss of Axl on macrophages does not impact the tumor response Macrophages showed the highest Axl expression, leading us to investigate how Axl loss impacts their function. scRNAseq results showed minimal differences in gene expression between intratumoral macrophages from WT and Axl KO mice in both MC38 or B16F0-cOva tumors ( Figs. 4 A- 4 D ). GSEA showed only one enriched gene set in WT macrophages in MC38 tumors compared to Axl KO ( Fig. 4 B ). However, in B16F0-cOva tumors, we observed more enriched gene sets ( Fig. 4 D ). Macrophages from WT mice were enriched in metabolic pathways, while those from Axl KO mice showed enriched proinflammatory pathways ( Fig. 4 E ). To investigate how Axl loss affects macrophage role and phenotype in TME, we compared expression scores evaluating angiogenesis, phagocytosis, and M1/M2 polarization gene signatures. Axl knockout led to significant changes in macrophage polarization in both tumor types. In B16F0-cOva tumors, Axl loss upregulated M1-like gene signatures and downregulated M2-like signatures. However, in MC38 tumors, M1-like signatures were reduced, suggesting Axl plays a more nuanced role in regulating macrophage behavior depending on the tumor context ( Figs. 4 F- 4 G ). To pinpoint the cell type driving delayed tumor growth in Axl-deficient mice between macrophages and DC cells, we generated conditional Axl KO mouse models. We used CD11c-Cre and LysM-Cre crossed with Axl floxed mice to specifically delete Axl in DC or myeloid cells, respectively. The deletion of Axl on dendritic cells delayed the growth of MC38 and B16F0-cOva tumors ( Fig. 4 H ). Despite changes in macrophage identity and increased proinflammatory signaling in B16F0-cOva tumors ( Figs. 4 F- 4 G ) , these alterations did not impact tumor growth in the LysM-Cre Axl KO model ( Fig. 4 I ). This suggests that Axl loss in dendritic cells, not myeloid cells, drives the delayed tumor growth. Loss of Axl enhances cDC2 immune response and T cell priming The role of Axl in DC subpopulations ( Figs. 5 A and S5A ) remains poorly understood. cDC2 are the most abundant DCs subpopulation in mouse and human TME ( Figs. 1 H, 3 A, and S3A ). We evaluated Axl expression in DC subpopulations of WT mice ( Fig. 5 B and S5B ) . In both tumor models, cDC2 expressed the highest levels of Axl. We then analyzed the effect of Axl knockout on toll-like receptors (TLRs), adapter proteins, and maturation markers. Axl loss resulted in a general increase in these markers, most notably in cDC2 cells ( Figs. 5 C-D and S5C-D ). This suggests that Axl acts as a negative regulator of these pathways, and its absence enhances cDCs ability to sense danger signals, mature, and promote adaptive immune responses. Given the high Axl expression in DC2 cells specifically in MC38 tumor model, we subclustered cDC2 to assess the role of Axl on antitumor response. We identified four distinct subsets: DC2-1, DC2-2, DC2-3, and DC2-4 (Fig. 5 D) The DC2-4 subpopulation was enriched in tumors in Axl KO mice (Figure S5E) . Differential expression analysis showed that the DC2-4 subpopulation exhibited a cDC1-like phenotype, expressing cDC1 canonical markers such as Xcr1, Clec9a, Irf8, and Batf3 while still expressing cDC2 canonical markers (Figure S5F and Figure S5F) and cluster with cDC2 rather than cDC1 (Figure S5G) as we excluded them from being misclustered. Moreover, DC2-4 also had lower Axl expression compared to other cDC subpopulations in WT mice ( Fig. 5 F ) , suggesting that Axl may play a role in modulating the switch to a cDC1-like phenotype. Furthermore, GSEA of cDC2-4 showed enriched in pathways involving inflammatory responses, response to interferons, myeloid cells differentiation ( Fig. 5 G ). This unexpected finding led us to investigate whether Axl knockout enhanced CD8 + T cell priming efficiency in cDC2 cells. Using flow-sorted splenic cDC2 cells, we co-cultured them for three days with CFSE-labeled OTI cells after pulsing with Ovalbumin and Kdo2-Lipid A. Axl-deficient cDC2 cells increased T cell proliferation, indicating that Axl loss enhances CD8 + T cell priming in cDC2 cells ( Fig. 5 H ). Enhanced immune response in Axl-deficient DCs is dependent on Type I IFN signaling Previous studies have highlighted Axl's role in limiting type I interferon (IFN) production and signaling in DCs. 13 , 24 , 51 , 52 To determine if the enhanced anti-tumor immunity observed in the absence of Axl is dependent on IFNAR1 signaling, we assessed type I IFN production and signaling in three DC subpopulations ( Figs. 6 A and 6 B ) . DC2 and DC3 cells in Axl-deficient mice showed significantly higher type I IFN production 7 days after tumor inoculation, with all subpopulations exhibiting increased signaling, particularly in the B16F0-cOva TME. To evaluate the role of type I IFN signaling on tumor growth, we transplanted MC38 and B16F0-cOva tumors into CD11c-Cre Axl flox/flox and control Axl flox/flox mice, then treated them with intratumoral IFNAR1 antibodies to block type I IFN signaling ( Fig. 6 C ). Blocking IFNAR1 signaling eliminated the tumor growth delay observed in CD11c-Cre, Axl flox/flox mice, leading to tumor progression like that in Axl flox/flox mice ( Figs. 6 D and 6 E ). These findings suggest that the enhanced tumor immunity in Axl-deficient DCs is dependent on increased type I IFN signaling. Type I IFN dependence drives sensitivity to STING agonist in Axl KO models After exposure to environmental stress, anti-tumor immune responses, or therapeutic agents, cancer cells undergo cell death and release damage-associated molecular patterns (DAMPs) such as high mobility group box 1 (HMGB1) and dsDNA. 53 , 54 DAMPs activate Toll-like receptor 4 (TLR4) and cyclic GMP-AMP synthase (cGas) in DCs, triggering type I IFN production and subsequent immune activation. 55 – 57 To examine the role of Axl deficiency in enhancing cGAS-STING signaling, we treated mice with DMXAA, a STING agonist. When tumors reached approximately 200mm 3 , we administered a single intratumoral dose of DMXAA to mice bearing MC38 tumors ( Fig. 6 F ). The treatment significantly reduced tumor growth in Axl KO mice compared to WT mice ( Figs. 6 G ). We then evaluated how Axl deficiency enhanced DMXAA efficacy in a therapy-resistant Py8119 tumor model and added ionizing radiation to facilitate cell death. The Py8119 cells are known for their resistance to immune checkpoint blockade (ICB) and radiotherapy due to an immunosuppressive TME. 9 We implanted Py8119 cells expressing cOva into WT and Axl KO mice and treated them with either DMXAA alone or in combination with a single 15 Gy dose of ionizing radiation once tumors reached a volume of 80 mm 3 ( Fig. 6 H ). In Axl KO mice, both DMXAA alone and its combination with ionizing radiation significantly delayed tumor growth in Axl KO mice compared to WT mice under the same treatments ( Fig. 6 I ). These results suggest that Axl deficiency enhances DMXAA efficacy, likely through enhanced Type I IFN signaling that would otherwise be dampened by Axl. The marked reductions in tumor growth with both monotherapy and combination treatment in resistant tumor models underscore the potential for combination therapy. Axl inhibition replicates knockout, supporting STING-agonist combination therapy To assess the therapeutic potential of targeting Axl, we treated WT mice bearing MC38 tumors with the Axl small molecule kinase inhibitor Bemcentinib (BGB324) as a monotherapy and in combination with the STING agonist DMXAA. MC38 cells were inoculated into WT mice and half of them started receiving BGB324 daily. Once tumors reached an average volume of 160mm³, a single dose of DMXAA was delivered intratumorally ( Fig. 7 A ) . Both BGB324 and DMXAA as monotherapies significantly delayed tumor growth compared to untreated mice, but the combination therapy exhibited the greatest tumor regression ( Fig. 7 B-C ). The combination therapy led to no tumor-related deaths throughout the study and extended survival compared to either treatment alone ( Fig. 7 D ). These results demonstrate that Axl inhibition, in conjunction with STING agonist therapy, provides superior tumor control and survival outcomes, likely due to enhanced Type I IFN signaling and improved T cell priming via dendritic cells. This combination approach holds promise for enhancing anti-tumor immunity. Discussion Axl, a member of the TAM receptor family, is well-known for promoting tumor cell survival, metastasis, and immune evasion. Recent studies have expanded our understanding of Axl’s role in immune cells regulation within the TME. While most research has focused on Axl expression in tumor cells, our study shifts focus to its expression in DCs, revealing a novel role for Axl in suppressing anti-tumor immunity. Mechanistically, we showed that Axl acts as a negative regulator of type I IFN signaling in DCs, and its absence enhances antitumor immune responses in cancer models. In an Axl-deficient host, DCs exhibit increase inflammatory signaling, improved cDC1/2 cross-priming ability, and an enhanced capacity to stimulate anti-tumor CD8 T cell responses, leading to tumor growth delay. This CD8 T cell-dependent effect confirms that the loss of Axl specifically on DCs strengthens immune system's anti-tumor capabilities. These findings highlight that Axl’s impact extends beyond tumor cells to key immune cells that initiate adaptive immune responses introducing a new perspective on Axl’s role in immune regulation with potential translational implications. DCs are key immunotherapy targets, particularly following type I IFN-stimulating therapies or immune checkpoint inhibition that relies on DC mediated adaptive responses. 55 , 58 – 60 Axl blockade has previously been combined with immunotherapy, radiotherapy (RT), and chemotherapy to enhance immune responses. 9 , 12 , 24 , 61 – 63 Herein, we report direct IFN stimulation using a STING agonist can have enhanced therapeutic activity in a Axl knockout host or with inhibition. Our data supports that combining Axl inhibition with type I IFN-stimulating therapies could enhance anti-tumor immunity by reversing Axl’s suppression of IFN signaling in DCs. As anti-Axl therapies such as Bemcentinib advance in clinical development, our findings support new strategies for combination therapies that include STING agonists. Axl is associated with poor prognosis and drug resistance in multiple malignancies such as acute myeloid leukemia (AML), lung, and breast cancers. 64 – 68 This prompted the development of Axl-targeting therapies that aim to limit tumor cell proliferation, induce apoptosis, and prevent metastasis. 4–9,69−71 While clinical trials with these therapies have not yet demonstrated significant clinical benefits as monotherapies, phase II trials combining Axl inhibitors with immunotherapy have shown promise. However, Axl’s role in immune modulation, particularly in DCs, remains largely unexplored and is a new direction for future study based off this work. We now have the groundwork and the significance to explore Axl's role in DC biology, with future studies needed to clarify how Axl regulates DC cross-priming and interacts with other immune cells in the TME. Additional research should examine Axl’s impact on immune cell localization and signaling dynamics within DC subpopulations, such as cDC2 and cDC3. Tracking immune response dynamics could reveal insights into Axl’s modulation of immunity. Understanding Axl’s effects on specific DC subsets may inform combination therapies, integrating Axl inhibition with immune checkpoint blockade, chemotherapy, RT, and STING agonists, to enhance anti-tumor immunity and address immune resistance in cancer treatment. Improving our mechanistic understanding of Axl’s influence on DC function and establishing this relevance in humans should assist the development of targeted therapeutic combinations. Such treatments would exploit this pathway to enhance anti-tumor immunity and overcome immune resistance in cancer treatment. Methods Mouse models Mice used in this study were all C57BL/6J background, with both males and females included, when possible, aged between 6 and 16 weeks. C57BL/6J (JAX:000664), B6.Cg-Tg(Itgax-cre)1-1Reiz/J (CD11c-Cre) (JAX:008068) 72 , and B6.129P2-Lyz2tm1(cre)Ifo/J (LysM-Cre) (JAX:004781) 73 mouse strains were purchased from Jackson Laboratories. The following mice were kindly gifted from the labs of: Dr. Greg Lemke (Salk Institute for Biological Sciences) provided AXL(tm1Grl/J) (Axl −/− ) 74 mice, Dr. Carla Rothlin (Yale School of Medicine) supplied AXL(tm1.1Cvro) (Axl flox/flox ) 75 mice, and Dr. Yang Xin Fu (UT Southwestern) contributed C57BL/6-Tg(TcraTcrb)1100Mjb/J (OT-1) 76 , and B6.129S(C)-Batf3tm1Kmm/J ( Batf3 −/− ) 49 mice. All mice were housed in specific pathogen free faculties and treated in accordance with the animal experimental guidelines approved by the Institutional Animal Care and Use Committee (Protocol# XXXX). Tumor growth experiments MC38 and B16F0-cOva were grown in Dulbeccos Modified Eagle Medium (DMEM) media (10-013-CV, Corning) supplemented with 10% FetalClone II (FCII) (SH30066.03, Cytiva). Py8119-cOva cells were grown in F12 Ham’s media supplemented with 10% FCII and 1X Mito + serum extender (355006, Corning). B16F0-cOva were a gift from the Engleman lab and Py8119-cOva cells were derived from Py8119 cells transduced with Ova containing lentivirus (lentiviral vector pLenti-Blasticidin-3XCMV, gift from Guo-Min Li lab), Ova expression was confirmed by flowcytometry following IFN-g stimulation. All cells were kept in a cell culture incubator at 37°C and 5% CO2 and were tested to be free of mycoplasma (30-1012K, ATCC). In preparation for inoculation, growth media was aspirated, culture flask were then rinsed with phosphate buffered saline (PBS) solution and trypsinized (T4049, Sigma) for 5–10 mins. After which trypsinization was neutralized via the addition of complete growth media and collected in conical tubes. Cells were spun down and washed with PBS 2x additionally cells passed through a 70µM cell strainer to remove cellular aggregates. Cells were mixed at 1:1 ratio of trypan blue (Corning) were viability and cell number were measured via a TC20 automated cell counter (BioRad). Cells were then re-suspended in PBS at desired inoculated cell count per 50µL of total volume. Using a 28G insulin syringe 50µL of cell suspension was injected into the subcutaneous space on the lower right flank (MC38, B16F0-cOva) or into the mammary fat pad (Py8119-cOva). Tumor dimensions were measured via calipers every 2–3 days with tumor volumes being calculated mm 3 = (Length*Length* Width)/2. Flow cytometry Tumor cells were trypsinized from flask and washed with complete growth media. Cells were then re-suspended at 1x10 6 cells/100µLs of autoMACS Rinsing Solution containing 0.5% BSA + 2mM EDTA (Miltenyi Biotec) and stained with mouse anti-AXL antibody conjugated with PE (FAB8541P, R&D) at 1:10 dilution or with PE conjugated IgG2a isotype antibody (RTK2758, Biolegend) at a 1:100 dilution. Cells were incubated for 20 mins at 4°C, washed 2 times and run on a LSRFortessa (BD) flow cytometer. FCS files were plotted and analyzed using FlowJo software (BD). Tumor treatments Depletion of CD8 + and CD4 + T cells was achieved via the intraparietal administration of 300µg of anti-CD8 (2.43, BioXcell) or anti-CD4 (GK1.5, BioXcell) every 6 days starting 2 days prior to tumor inoculation. Control mice were administered IgG2b isotype control antibodies (LTF-2, BioXcell). Type I IFN signaling was blocked via the intratumoral administration of 50µg anti-IFNAR-1 (MAR1-5A3, BioXcell) every other day starting on the day after tumor inoculation. Control mice were treated with IgG1 isotype control antibodies (MOPC-21, BioXcell). MC38 tumors were allowed to grow and randomized into treatment groups with average tumor volumes ~ 200mm 3 . Tumors were then treated with a single 250µg dose of STING agonist DMXAA (5601/50, Tocris Bioscience) re-suspended in DMSO. Control mice received an intratumoral injection of pure DMSO. Py8119-cOva tumors were allowed to grow days and randomized into groups with mean tumor volume ~ 80mm 3 . In addition to DMXAA, some mice were treated locally with 15 Gy radiation under anesthesia. For experiments involving Axl inhibition, MC38 cells were inoculated into WT mice. These mice were then administered either a vehicle control (0.20% methylcellulose + 5% DMSO in water) or 50 mg/kg of BGB324 by oral gavage twice daily, starting on the day of inoculation. Tumors were then allowed to grow until reaching an average volume of 160mm 3 and treated with a single dose of DMXAA as previously stated. Tissue harvest and single cell sequencing To evaluate Axl’s influence over the immune landscape of the tumor microenvironment 1x10 6 MC38 or B16F0-cOva cells were each subcutaneously inoculated into 4 WT (Wild Type) (2M + 2F) and 4 AXL KO (2M + 2F) mice and allowed to grow for 7 days. After 7 days tumors were harvested from each mouse. On ice, tumors were placed in 60mm culture dish and processed into small ~ 1mm 3 pieces using scalpels. After which we add 5mL of digestion media composed of (4:1 HBSS (21-020-CV, Corning): RMPI (10-040-CV, Corning) + 3% FCII + 10ug/mL DNase I (D5025-150KU, Sigma) + 10.5 µM Y-27632 dihydrochloride (rock kinase inhibitor) (Y0503-5MG, Sigma) + 100 U/mL Collagenase IV (LS004188, Worthington) + 1mg/mL Soybean Trypsin Inhibitor (LS003571, Worthington) + 2 mg/mL Dispase II (17105-041, Gibco)) then placed in a shaking incubator set at 37°C for 30 mins. After initial incubation tissue was triturated with a pipette then incubated for an additional 15 mins. After which entire culture dish contents were paced through a 40µM cell strainer and washed with excess volume PBS supplemented with 3% FCII. Remaining red blood cells were lysed with the addition of ACK Lysis buffer (A1049201, Gibco) and incubated at room temperature for 5 mins. After lysis cells were prepped for CD45 + enrichment via MACS separation (Miltenyi Biotec) by being washed and re-suspended in autoMACS Rinsing Solution containing 0.5% BSA + 2mM EDTA. CD45 MicroBeads were added to cell suspension and incubated for 15 mins at 4°C. After being washed, cells were passed through magnetic columns and attached cells were eluted. Once single cell suspension was achieved for all tissue samples cellular viability and count was determined via TC20. Cells were re-suspended at 1x10 6 cells/ 49.5µL of Cell Staining Buffer (420201, Biolegend) and blocked with 0.50µL of TruStain FcX Plus (S17011E, Biolegend) for 10 mins at 4°C then stained with 0.50µg of each Cite-Seq antibodies. Cells were washed 3 times in staining buffer, passed through a 40µM cell strainer and re-suspended in 0.04% BSA/PBS and adjusted to 1000 cells/µl. Cells were loaded according to standard protocol of the Chromium single cell 5′ kit, capturing 10,000 cells (V3 chemistry). All subsequent procedures, including library construction, were performed according to the standard manufacturer’s protocol. Single-cell libraries were sequenced on NovaSeq (Illumina) to a depth of 50,000 reads per cell. DC sorting To amplify the production of conventional dendritic cells 10 million B16-FLT3L tumor cells grown in DMEM supplemented with 10% FCII were subcutaneously injected in 100 uL of PBS into mice of the desired genotype. Tumors were allowed to grow for 2 weeks; spleens were then harvested and CD11c + cells were isolated via MACS beads from splenocytes as previously mentioned. For FACs sorting of cDC1 and cDC2 cells isolated CD11c + cells were resuspended at 10 7 cells/mL of autoMACS Rinsing Solution containing 0.5% BSA + 2mM EDTA and incubated with anti-16/32 TruStain FcX plus (156604, Biolegend) for 10 mins at 4°C to prevent nonspecific binding of antibodies to FC receptors. Next without washing fluorescent conjugated antibodies CD11c (117311, Biolegend), MHC class II (107632, Biolegend), CD11b (101228, Biolegend), CD8a (100708, Biolegend), and XCR1 (148206, Biolegend) all antibodies were added at 1:100 dilution and incubated at 4°C in the dark for 20 minutes. After incubation cells were washed 2 times and resuspended at 5x10 6 cells/mL in autoMACS rinsing solution. Cells were sorted on FACSymphony S6 (BD) and collected in 15 mL conical tubes prefilled with RPMI + 5% heat inactivated FCII. For MACS bead separation of cDC1 cells anti-XCR1 MicroBead Kit (130-115-721, Miltenyi Biotec) was used on splenocytes according to the manufacturer provided protocol. In Vitro dendritic cell assay 200,000 flow cytometry sorted cDC1 and cDC2 cells from either WT or Axl KO mice were plated per 96 well plate well in 100 µL of RPMI + 5% heat inactivated FCII. DCs were pulsed with 25 µg/mL of Ovalbumin protein (vac-stova, Invivogen) and stimulated with 50 ng/mL of Kdo2-Lipid A (NC9765889, Avanti Polar Lipids) and incubated at 37°C for 24 hours. Prior to 24-hour incubation of DCs being up splenocytes were collected from OT-I mice and naïve CD8 T cells were isolated via MACS separation kit (130-096-543, Miltenyi) according to manufacturer provided protocol. Isolated OT-I cells were resuspended in PBS and stained with 5 µM of CFSE cell division tracker dye (423801, Biolegend) for 20 minutes at 37°C then quenched with complete media and washed in PBS. After 24-hour incubation DCs were washed with PBS and 100,000 CFSE labeled OT-I cells were added on top in RPMI + 5% heat inactivated FCII. Cells were incubated at 37°C for an additional 3 days. After 3-day incubation cells were washed then stained with Zombie NIR viability dye (423106, Biolegend) for 15 mins at 4°C diluted in PBS at 1:200 dilution. Cells were then washed in autoMACS rinsing solution and stained for flow cytometry with TCR-b (109238, Biolegend), CD11c (117310, Biolegend), CD69 (104512, Biolegend), each antibody was stained using a 1:100 dilution and incubated at 4°C for 20 minutes. Cells were run on LSRFortessa flow cytometer and analyzed using FlowJo software. DC transplants 500,000 XCR1 + isolated as previously described from either WT or Axl KO mice were mixed at a 1:1 ratio with MC38 cells in 50µL of PBS and subcutaneously inoculated in the right flank of WT mice. Tumor growth was evaluated via caliper measurements every 2–3 days with tumor volumes being calculated mm^3= (Length*Length* Width)/2. Single Cell Sequencing analysis Raw data and FASTQs were generated by North Texas Genome Center, The University of Texas at Arlington. Using Cell Ranger version 5.0.1 pipeline, FASTQ files were aligned to the mouse reference genome (mm10) using STAR version 2.7.2a and counted using Cell Ranger count with default parameters and recommendations with feature barcode option. The counting matrix was imported into Seurat (5.1.0) via R (4.4.1) for quality assessment and downstream analysis. Cells were filtered by excluding cells with less than 200 genes, all genes in less than three cells, and genes expressed as being composed of greater than 20% mitochondrial genes. Data were then normalized using the NormalizeData function with default parameters. Variable genes were detected using the FindVariableFeatures function. Data were scaled and centered using linear regression. Principle component analysis was run with the RunPCA function using default parameters. Batch effects were corrected, and samples were integrated by using harmony (1.2.0) and SeuratWrappers (0.2.0) library with default parameters. Cell clusters were identified via the FindNeighbors and FindClusters functions, with 0.5 resolutions for major cell clusters and UMAP or tSNE clustering algorithms. Subsequent clustering for the lymphoid and myeloid cells a higher resolution (0.8 and 1.2) was respectively. A FindAllMarkers table was created, and clusters were defined by using SingleR (2.6.0) and celldex (1.14.0) with ImmGenData from ( https://www.immgen.org/ ), and finally with canonical marker s. Gene Ontology (GO) enrichment for each cluster and between samples was performed using clusterprofiler (4.12.0) and GSEABase (1.66.0) using differentially expressed genes at 0.5-fold change and 0.05 Adjusted p value. GO annotations were obtained using msigdbr (7.5.1). Cell proportion differences calculated using scProportionTest (0.0.0.9000). Graphs and plots were generated by ggplot2 (3.5.1), EnhancedVolcano (1.22.0), SCP (0.5.6), or Seurat. Statistics Tumor growth curves were analyzed using repeated measures model in SAS software (SAS Institute Inc., Cary NC), accounting for variability within individual mice. Post hoc pairwise comparisons were performed using a Tukey adjustment. To assess differences in T cell priming among experimental groups, a one-way ANOVA was conducted in GraphPad Prism (GraphPad Software, San Diego, CA) using mean values from technical replicates. Mouse survival was summarized using Kaplan- Meier curves, significance was evaluated using log-rank Mantel-Cox test performed with GraphPad Prism. Survival endpoint was defined as a death due to tumor burden or a humane endpoint due to tumor size exceeding 17.5 mm in any measurement, with time-to-event data recorded for each mouse. Mice that underwent a death not due to tumor burden were censored from the survival analysis at the time of their death. 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The Brekken lab has been supported by BerGenBio ASA for work that is distinct from the present study. The authors declare no other competing interests. Supplementary Files CITESeqTable1.docx Axl CITE Seq table 1 NatureCancerSupplementalFigures.pdf Axl Supplemental Figures Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Center","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Montgomery","suffix":""},{"id":388158891,"identity":"ba026040-49c4-480f-8a62-bbec6f85f1da","order_by":5,"name":"Peter Leung","email":"","orcid":"","institution":"The University of Texas Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Leung","suffix":""},{"id":388158892,"identity":"b73f287b-7130-43e8-a46d-9018565c6d8b","order_by":6,"name":"Arely Rodriguez","email":"","orcid":"","institution":"The University of Texas Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Arely","middleName":"","lastName":"Rodriguez","suffix":""},{"id":388158893,"identity":"a0a72522-a486-4408-815c-5c3a98e3d1bf","order_by":7,"name":"Sebastian Diegeler","email":"","orcid":"","institution":"The University of Texas Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Diegeler","suffix":""},{"id":388158894,"identity":"bc48eedb-e6bc-4bcc-8cf3-e2cecb21bad6","order_by":8,"name":"Katy Swancutt","email":"","orcid":"","institution":"The University of Texas Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Katy","middleName":"","lastName":"Swancutt","suffix":""},{"id":388158895,"identity":"4201f5c2-2f36-439d-9486-ef5cf699bbe1","order_by":9,"name":"Rolf Brekken","email":"","orcid":"https://orcid.org/0000-0003-2704-2377","institution":"The University of Texas Southwestern Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Rolf","middleName":"","lastName":"Brekken","suffix":""}],"badges":[],"createdAt":"2024-12-03 07:00:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5569516/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5569516/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73621693,"identity":"065861a5-6e20-4e0b-ba5d-89412c71a8ca","added_by":"auto","created_at":"2025-01-13 04:28:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1892517,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbsence of host Axl in leads to delayed growth of immunogenic syngeneic tumors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A-C\u003c/strong\u003e) Subcutaneous implant of 300,000 MC38 cells (n= 10 WT, 10 Axl KO), B16F0-cOva (n= 10 WT, 10 Axl KO), or Py8119-cOva (n= 18 WT, 16 Axl KO) cells into Wild type or Axl knockout mice. Mean +/- SEM, adjusted p values using mixed effect model. (\u003cstrong\u003eD\u003c/strong\u003e) Schematic for tumor implant and subsequent isolation of intratumoral immune cells for 10X single-cell RNA sequencing analysis. (\u003cstrong\u003eE\u003c/strong\u003e) UMAP projection illustrating the intratumoral immune cell populations in MC38 tumors merged between Wild type and Axl knockout host (left panel) and the proportions between each genotype (right panel). (\u003cstrong\u003eF\u003c/strong\u003e) Heatmap displaying canonical cell type markers used to annotate immune cell clusters. (\u003cstrong\u003eG\u003c/strong\u003e) UMAP projection of immune cells showing Axl expression levels in MC38 tumors. (\u003cstrong\u003eH\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eUMAP projection of human myeloid cells combined from eight different cancer types. (\u003cstrong\u003eI\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eUMAP projection of human myeloid cells showing Axl expression.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/5e920bfb8f4150d972473ff4.png"},{"id":73622854,"identity":"3e67248e-567f-44b3-9d5f-c26feb8cc1e9","added_by":"auto","created_at":"2025-01-13 04:44:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3471390,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnhanced activation of cytotoxic T cells is critical for tumor growth delay in Axl KO mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003etSNE projection of lymphoid cells in MC38 tumor-bearing mice merged between WT and Axl KO (n= 2393 cells). (\u003cstrong\u003eB) \u003c/strong\u003etSNE projection illustrating KI67 expression (left panel) on intratumoral lymphoid cells in MC38 tumors and violin plot showing increase in Axl KO mice (right panel). (\u003cstrong\u003eC-F\u003c/strong\u003e) Violin plots comparing gene expression levels of inhibitory molecules on Treg cells (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e,\u003c/strong\u003e immune checkpoints on CD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cstrong\u003eD\u003c/strong\u003e)\u003cstrong\u003e,\u003c/strong\u003e activation markers on CD8\u003csup\u003e+\u003c/sup\u003e T cells (\u003cstrong\u003eE\u003c/strong\u003e), and interferon signaling associated molecules between WT and Axl KO mice (\u003cstrong\u003eF\u003c/strong\u003e)\u003cstrong\u003e. (G\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eGene set enrichment analysis comparing CD8\u003csup\u003e+\u003c/sup\u003e T cells from WT and Axl KO mice revealing T cell receptor signaling and adaptive immune response as enriched signaling pathways in Axl KO mice. (\u003cstrong\u003eH\u003c/strong\u003e) Schematic outlining experimental design for depleting CD8\u003csup\u003e+\u003c/sup\u003e and CD4\u003csup\u003e+\u003c/sup\u003e cells throughout tumor growth evaluation. (\u003cstrong\u003eI-J\u003c/strong\u003e) Tumor growth curves of 500,000 subcutaneous transplanted MC38 cells (left) (n= 5 WT iso, 9 Axl KO iso, 7 WT anti-CD4, and 8 mice per each remaining group) or B16F0-cOva cells (right) ( n= 6 WT iso, 9 Axl iso, 7 WT anti-CD8, and 8 mice per each remaining group) in WT or Axl KO mice during the depletion of CD8\u003csup\u003e+ \u003c/sup\u003ecells (\u003cstrong\u003eI\u003c/strong\u003e) or CD4+ cell depletion (\u003cstrong\u003eJ\u003c/strong\u003e). Mean +/- SEM, adjusted p values using mixed effect model.\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/f2ae830ba10a3fed5d7c49dd.png"},{"id":73621698,"identity":"65b5030c-d866-482e-a373-b02fcf01bdd5","added_by":"auto","created_at":"2025-01-13 04:28:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2892608,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDendritic cell type 1 are key mediators of antitumor immunity in the absence of Axl on myeloid cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(A) \u003c/strong\u003eUMAP projection of myeloid cells from WT and Axl KO mice in MC38 tumors (n =11590 cells). (\u003cstrong\u003eB\u003c/strong\u003e) Relative differences in cell proportions for each sub clusters of myeloid cells population between MC38 WT versus MC38 Axl KO. Clusters colored red have an FDR \u0026lt; 0.05 and mean | Log\u003cem\u003e2\u003c/em\u003e fold enrichment | \u0026gt; 1. Permutation test; n=10,000. (\u003cstrong\u003eC\u003c/strong\u003e) GSEA depicting top signaling pathways enriched in DCs from Axl KO mice over WT. Normalized enrichment score NES with FDR \u0026lt;0.05. (\u003cstrong\u003eD\u003c/strong\u003e) Schematic depicting the T cell priming assay. (\u003cstrong\u003eE\u003c/strong\u003e) Representative flow plots depicting OTI cell proliferation by decreased CFSE signal (left) and a graph quantifying the % proliferative OTI cells each group consisting of 6-7 technical replicates. One-way ANOVA with post hoc adjustment, p=0.0031. (\u003cstrong\u003eF\u003c/strong\u003e) Representative flow plots depicting OTI cell activation by increased CD69 signal positivity (left) and a graph quantifying the % of OTI cells expressing CD69 each group consisting of 6-7 technical replicates. One-way ANOVA with post hoc adjustment, p\u0026lt;0.0001. (\u003cstrong\u003eG\u003c/strong\u003e) Tumor growth curves after 500,000 MC38 cells implanted subcutaneously (left) (n= 9 WT, 12 Axl -/-, 7 Batf3 -/-, 6 Axl -/- Batf3 -/-) or B16F0-cOva cells (right) (n= 6 WT, 6 Axl -/-, 7 Batf3 -/-, 7 Axl -/- Batf3 -/-). Adjusted p values using mixed effect model. (\u003cstrong\u003eH\u003c/strong\u003e) Schematic illustrating isolation and co-implantation of cDC1 with MC38 cells into naïve WT mice (top). Tumor growth curves of MC38 cells (n=6) compared when coinjected with WT cDC1 (n=7) and Axl KO cDC1 (n=7). Adjusted p values using mixed effect model.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/ad6ba9cdc1b961725d8cfd3c.png"},{"id":73622067,"identity":"b0a1e39b-6172-48af-8184-1ad32e46199b","added_by":"auto","created_at":"2025-01-13 04:36:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2761439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLoss of Axl signaling on DCs not macrophages delays tumor growth\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA-C\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eVolcano plot showing differentially expressed genes in intratumoral macrophages from WT or Axl\u003csup\u003e-/-\u003c/sup\u003e mice with MC38 (\u003cstrong\u003eA\u003c/strong\u003e) or B16F0-cOva (\u003cstrong\u003eC\u003c/strong\u003e) tumors (n=9193, 2759 cells respectively). (\u003cstrong\u003eB, D\u003c/strong\u003e) Diagram depicting gene set pathways enriched in intratumoral macrophages from WT or Axl\u003csup\u003e-/-\u003c/sup\u003e mice with MC38 or B16F0-cOva tumors. (\u003cstrong\u003eE\u003c/strong\u003e) Plot illustrating the top gene sets enriched in intratumoral macrophages from WT or Axl\u003csup\u003e-/-\u003c/sup\u003e mice with B16F0-cOva tumors. (\u003cstrong\u003eF/G\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eViolin plots comparing selected features between intratumoral macrophages in WT and Axl\u003csup\u003e-/-\u003c/sup\u003e mice bearing MC38 (\u003cstrong\u003eF\u003c/strong\u003e) or B16F0-cOva (\u003cstrong\u003eG\u003c/strong\u003e). (\u003cstrong\u003eH\u003c/strong\u003e) Schema illustrating the development of DC specific Axl\u003csup\u003e-/-\u003c/sup\u003e mouse model for tumor growth evaluation (top). Tumor growth curves of 500,000 subcutaneous transplanted MC38 cells (left) (n=14 Axl\u003csup\u003efl/fl\u003c/sup\u003e, 12 CD11c-Cre Axl\u003csup\u003efl/fl\u003c/sup\u003e) or B16F0-cOva cells (right) (n=10 Axl\u003csup\u003efl/fl\u003c/sup\u003e, 11 CD11c-Cre Axl\u003csup\u003efl/fl\u003c/sup\u003e). (\u003cstrong\u003eI\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eSchema illustrating the development of LysM Cre myeloid cell specific Axl\u003csup\u003e-/-\u003c/sup\u003e mouse model for tumor growth evaluation (top). Tumor growth curves of MC38 tumors (left) (n=20 Axl\u003csup\u003efl/fl\u003c/sup\u003e, 18 LysM-Cre Axl\u003csup\u003efl/fl\u003c/sup\u003e, 15 Axl\u003csup\u003e-/-\u003c/sup\u003e) or B16F0-cOva tumors (right) (n=12 Axl\u003csup\u003efl/fl\u003c/sup\u003e, 13 LysM-Cre Axl\u003csup\u003efl/fl\u003c/sup\u003e, 12 Axl\u003csup\u003e-/-\u003c/sup\u003e). All growth curves mean +/- SEM, adjusted p values using mixed effect model.\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/add76b26c525fade083360a2.png"},{"id":73622065,"identity":"bbdcabf8-1538-4657-8049-49736b90b6e3","added_by":"auto","created_at":"2025-01-13 04:36:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2229464,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLoss of Axl on cDC2s facilitates anti-tumor response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eDot plot displaying immunophenotyping markers for cDC1, cDC2, and cDC3 subpopulations found in MC38 tumors. (\u003cstrong\u003eB\u003c/strong\u003e) Heatmap comparing expression scores of toll-like receptors and adapter proteins between WT and Axl\u003csup\u003e-/-\u003c/sup\u003e DC subpopulations. (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eHeatmap comparing expression of maturation markers between WT and Axl\u003csup\u003e-/-\u003c/sup\u003e DC subpopulations. (\u003cstrong\u003eD\u003c/strong\u003e) UMAP projection of subclusters within the DC2 population in MC38 tumors (top). Pie chart illustrating the proportional contribution of each DC2 subpopulation. (\u003cstrong\u003eE\u003c/strong\u003e) Heatmap comparing expression of DC1 and DC2 canonical markers among entire cDC2 population or DC2-4 subpopulation. Feature plot displaying DC2 cells expressing either DC1 like or DC2 like signatures. (\u003cstrong\u003eF\u003c/strong\u003e) Gene set enrichment analysis comparing DC2-4 cells to rest of DC2 populations. (\u003cstrong\u003eG\u003c/strong\u003e) T cell priming assay (top panel) and representative flow plots depicting OTI cell proliferation by decreased CFSE signal (left panel). Graph quantifying proliferative OTI cells each group consisting of 3 technical replicates (right panel). Statistical analysis conducted using One-way ANOVA p=0.0100.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/5cc98b0ba27f6c0e3552adbe.png"},{"id":73621700,"identity":"a90aa68d-e751-4abe-b7f8-de36d852392d","added_by":"auto","created_at":"2025-01-13 04:28:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3543680,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDelayed tumor growth in absence of Axl is mediated by type I IFN signaling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA/B\u003c/strong\u003e) Violin plots illustrating (A) Type I interferon production or (B) Type I interferon signaling in DC subsets in MC38 and B16F0-cOva tumor models. Expression scores for IFN production or signaling are shown for three DC subsets, with median bars indicated. Statistical significance was determined using Wilcoxon signed-rank test with Bonferroni adjusted p-values reported for comparisons between WT and Axl -/- groups. (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eSchema illustrating tumor implantation and inhibition of IFNAR1. (\u003cstrong\u003eD\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eTumor growth evaluation of 500,000 MC38 cells implanted subcutaneous (n=14 Axl\u003csup\u003efl/fl\u003c/sup\u003e isotype, 14 Axl\u003csup\u003efl/fl\u003c/sup\u003e anti-IFNAR1, 13 CD11c-Cre, Axl\u003csup\u003efl/fl\u003c/sup\u003e isotype, 11 CD11c-Cre, Axl\u003csup\u003efl/fl\u003c/sup\u003e anti-IFNAR1). (\u003cstrong\u003eE\u003c/strong\u003e) or B16F0-cOva cells (n=10 Axl\u003csup\u003efl/fl\u003c/sup\u003e isotype, 11 Axl\u003csup\u003efl/fl\u003c/sup\u003e anti-IFNAR1, 13 CD11c-Cre Axl\u003csup\u003efl/fl\u003c/sup\u003e isotype, 9 CD11c-Cre Axl\u003csup\u003efl/fl\u003c/sup\u003e). (\u003cstrong\u003eF\u003c/strong\u003e) Schema illustrating the intratumoral administration of 250 µg of DMXAA following the inoculation of 1,000,000 MC38 cells into WT or Axl\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eG\u003c/strong\u003e) Predicted growth curves of MC38 tumors in relation to the day of DMXAA treatment (n=10 WT Vehicle, 12 WT DMXAA, 10 Axl\u003csup\u003e-/-\u003c/sup\u003e Vehicle, 12 Axl\u003csup\u003e-/-\u003c/sup\u003e DMXAA). (\u003cstrong\u003eH\u003c/strong\u003e) Individual mouse growth curves for WT and Axl\u003csup\u003e-/- \u003c/sup\u003eDMXAA treated groups.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eI\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eSchema illustrating the intratumor administration of 250 µg of DMXAA and administration of 15Gy ionizing radiation following the inoculation of 1,000,000 Py8119-cOva cells into WT or Axl\u003csup\u003e-/-\u003c/sup\u003e mice. (\u003cstrong\u003eJ\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003ePredicted growth curves of Py8119-cOva tumors in relation to the day of DMXAA and ionizing radiation treatment (n=13 WT Vehicle, 14 WT DMXAA, 13 WT DMXAA + IR, 11 Axl\u003csup\u003e-/-\u003c/sup\u003e Vehicle, 12 Axl\u003csup\u003e-/-\u003c/sup\u003e DMXAA, 13 Axl\u003csup\u003e-/-\u003c/sup\u003e DMXAA + IR). (\u003cstrong\u003eK\u003c/strong\u003e) Individual mouse growth curves for WT and Axl\u003csup\u003e-/-\u003c/sup\u003e either treated with DMXAA alone or (\u003cstrong\u003eL\u003c/strong\u003e) DMXAA + ionizing radiation combination.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/9105626f536a7faf907b845e.png"},{"id":73622068,"identity":"ec92b1ca-80e8-4c85-979e-899df1312633","added_by":"auto","created_at":"2025-01-13 04:36:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1399769,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBGB324 enhances tumor growth delay and survival in combination with STING agonist\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eSchema illustrating tumor implantation and treatment of mice with Axl inhibitor, BGB324, and STING agonist, DMXAA. (\u003cstrong\u003eB\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eTumor growth curves of 1,000,000 subcutaneous implanted MC38 cells into WT mice randomly assigned into treatment groups (n=6 vehicle treated, 9 BGB324, 7 DMXAA, 9 BGB324 + DMXAA). Bold lines indicate predicted curve from the mixed effect model with individual mouse represented by a thin line. \u0026nbsp;The DMSO vehicle and DMXAA groups received intratumoral injections on day 12 (first arrow), while the BGB324 and BGB+DMXAA treatment groups received their injections on day 17 (second arrow). Adjusted p values using mixed effect model. (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eTumor growth curves plotted as percent change bold lines indicating mean values with individual values being depicted by thin lies. (\u003cstrong\u003eD\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eSurvival proportions\u003cstrong\u003e \u003c/strong\u003eof mice from day of inoculation. p-value using log-rank Mantel-Cox test.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/ee2e4b4dd5c1efadba1ccb7f.png"},{"id":73623061,"identity":"f9b922c5-2d97-4e2f-8244-94ea673938ca","added_by":"auto","created_at":"2025-01-13 04:53:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":18752933,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/65ff09f2-807b-459c-afc4-995112b93d2c.pdf"},{"id":73621692,"identity":"2d4c28b1-f2d5-47b1-b535-3453be493a1f","added_by":"auto","created_at":"2025-01-13 04:28:58","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23660,"visible":true,"origin":"","legend":"Axl CITE Seq table 1","description":"","filename":"CITESeqTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/8e8901f1040f41d7697b0a4d.docx"},{"id":73621696,"identity":"46b6c404-f90b-44fe-9ada-38acdbd56b9b","added_by":"auto","created_at":"2025-01-13 04:28:58","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2086147,"visible":true,"origin":"","legend":"Axl Supplemental Figures","description":"","filename":"NatureCancerSupplementalFigures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5569516/v1/731df562b444b5da5858d86e.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential Competing Interest.\nThe Brekken lab has been supported by BerGenBio ASA for work that is distinct from the present study. The authors declare no other competing interests.","formattedTitle":"Axl inhibition on dendritic cells enhances STING anticancer therapy through type I interferon signaling","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTyro3, Axl and MerTK are collectively known as TAM family of receptor tyrosine kinases, which can be expressed by tumor and innate immune cells with differential functions on each cell type.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Axl signaling occurs when its ligand, growth arrest-specific gene 6 (Gas6), binds to phosphatidylserine (PS) on the surface of apoptotic cells most effective when clustered by phosphatidylserine.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e On tumor cells, Axl signaling leads to pro-oncogenic cellular pathways promoting increased metastasis, cell proliferation, therapy resistance, and survival through dysfunctional apoptosis/ necroptosis pathways.\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The signaling also hinders an anti-tumor adaptive immune response by down-regulating antigen presentation via cell surface MHC class I and altering tumor cytokine expression, supporting an immunosuppressive TME.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Preclinical studies have demonstrated that inhibiting Axl shows therapeutic promise in treating triple-negative breast cancer (TNBC), non-small cell lung cancer (NSCLC), and pancreatic ductal adenocarcinoma (PDAC) tumors.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e By disrupting pro-oncogenic cellular pathways, Axl inhibition restored sensitivity towards chemotherapies, making it a valuable therapeutic target in these cancer types.\u003c/p\u003e \u003cp\u003eOn myeloid cells, Axl acts as a mediator of inflammation, facilitating the recognition and clearance of apoptotic cells and by the downstream production of suppressor of cytokine signaling proteins 1 and 3 (SOCS1/3).\u003csup\u003e2,13\u003c/sup\u003e SOCS1/3 proteins hinder the production and signaling of pro-inflammatory cytokines, by blocking toll like receptor and type I interferon (IFN) signaling in response to tumor derived danger associated molecular patterns (DAMPs).\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Research has shown that IFN signaling in dendritic cells (DCs) is crucial for triggering an anti-tumor immune response.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e IFNs improve DCs' ability to present antigens, increase the expression of costimulatory molecules, boost the release of pro-inflammatory cytokines, and enhance their movement within tumors and to lymph nodes. Together, these effects enable DCs to activate na\u0026iuml;ve CD8 T cells.\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Expression of Axl has been associated with dysfunctional populations of conventical and plasmacytoid DCs (cDC/pDC) leading to limited anti-tumor and antiviral immunity respectively. \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e In addition, Axl inhibition can restore sensitivity to targeting PD1in resistant LKB1 mutant NSCLC via sustained TCF1 T cell activity driven by increased IFN production by DCs.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Consistently, poorly immunogenic cancers are characterized by a lack of neoantigens and disparities in cDC signaling.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Thus, addressing scarcity and functional checkpoints of dendritic cells offers a significant opportunity to identify new therapeutic targets.\u003c/p\u003e \u003cp\u003eIn this work, we investigated the impact of Axl expression on host immune cells and its influence on anti-tumor immune responses. While much prior research focused on the role of Axl on tumor cells, we aimed to evaluate its significance in the context of host immune cells in the TME. To achieve this, we used Axl knockout (KO) mice with various syngeneic tumor models. This allowed us to assess how the loss of Axl in host immune cells influences tumor growth independently of Axl expression in the tumor cells. We observed CD8 T cell dependent tumor growth delay of immunogenic tumors. This prompted us to investigate the role of dendritic cells and macrophages in Axl-mediated immunosuppression. Our findings revealed that Axl loss on DCs, but not macrophages, was sufficient to enhance T cell-mediated anti-tumor immune responses. The absence of Axl enhanced cDC1 and cDC2 mediated T cell priming that was dependent on type I IFN signaling. Translationally, this mechanism helped us identify a combination therapeutic approach to inhibit Axl while stimulating type I IFN with therapeutics such as radiotherapy or STING agonists.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAxl KO results in delayed growth of immunogenic tumors\u003c/h2\u003e \u003cp\u003eTo assess the impact of Axl absence on host's immune response, we implanted three syngeneic tumors, immunogenic MC38 (colorectal cancer), B16F0 (melanoma), and Py8119 (triple-negative breast cancer)\u0026mdash;into Axl KO mice and compared tumor growth delay to wild-type (WT) mice. B16F0 and Py8119, which are poorly immunogenic, were engineered to express cytoplasmic ovalbumin (cOva) to model antigen presentation.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e All three tumors showed delayed growth in Axl KO mice (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), independent of Axl expression on tumor cells, as confirmed by flow cytometry (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA\u003c/b\u003e). To investigate the tumor growth delay in Axl KO mice, we performed single-cell RNA sequencing (scRNAseq) 7 days after implanting MC38 or B16F0-cOva into WT and Axl KO mice \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e We hypothesized that this analysis would reveal differences in cellular responses, functional states, or cellular interactions. Since the delay was observed in the host knockout mice likely driven by immune mechanisms, day seven was chosen as the peak of adaptive immune response.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e To enhance immune cell profiling, CD45\u003csup\u003e+\u003c/sup\u003e cells were sorted after tumor dissociation, labeled with CITE-Seq antibodies to aid in cellular annotations and analyzed using 10X platform \u003cb\u003e(Supplementary Table\u0026nbsp;1).\u003c/b\u003e After quality control, 14018 to 14071 cells were identified from MC38 and B16F0-cOva tumors respectively in both WT and Axl KO mice. We observed comparable clusters and cell frequencies between WT and Axl KO hosts in both MC38 and B16F0-cOva tumors \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE and S1B\u003cb\u003e).\u003c/b\u003e Cell populations were annotated based on canonical markers for each tumor type \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF and S1C\u003cb\u003e).\u003c/b\u003e We identified Axl expression in immune cell subpopulations, with the highest levels in cDCs, macrophages and monocytes \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG and S1D\u003cb\u003e).\u003c/b\u003e Similarly, scRNAseq data of myeloid cells from eight different human tumors showed Axl predominantly expressed on cDCs, macrophages and monocytes \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo determine if Axl ablation led to off-target deletions or compensation by other TAM receptors, we assessed MerTK and Tyro3 expressions. MerTK was primarily expressed on macrophages, with no noticeable difference in expression between WT and Axl KO models \u003cb\u003e(Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eE and S1F)\u003c/b\u003e. Tyro3 was not detected by scRNAseq in our samples.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCytotoxic T cell activity mediates tumor growth delay in Axl knockout mice\u003c/h3\u003e\n\u003cp\u003eGiven predominant expression of Axl on myeloid cells, we hypothesized that Axl deficiency might alter the adaptive immune response through myeloid-T cell interactions. We analyzed tumor-infiltrating lymphocytes (TILs) using scRNAseq \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and S2A\u003cb\u003e)\u003c/b\u003e and identified three major T cell subpopulations with elevated Ki67 in both WT and Axl KO tumors: Tregs, CD8\u0026thinsp;+\u0026thinsp;T cells, and NK cells in MC38, and CD8\u003csup\u003e+\u003c/sup\u003e T cells in B16F0-cOva models. Ki67 expression was significantly higher in CD8\u0026thinsp;+\u0026thinsp;T cells from Axl KO mice in MC38 but only slightly increased in B16F0-cOva, suggesting that Axl loss enhances the adaptive immune response, particularly in the MC38 model \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and S2B\u003cb\u003e)\u003c/b\u003e. We then assessed CD8\u0026thinsp;+\u0026thinsp;T cell function status through evaluation of exhaustion and activation markers. In MC38 bearing Axl KO mice, exhaustion markers (Ctla4, Lag3, and Tim3) were significantly reduced, while Pd-1 remained unchanged \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Conversely, activation and cytotoxicity markers (Ccr5, Cd28, Eomes, and Gzmk) were elevated in Axl KO CD8\u0026thinsp;+\u0026thinsp;T cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. In the B16F0-cOva model, CD8\u0026thinsp;+\u0026thinsp;T cells showed increased immune checkpoints, indicating terminal exhaustion from chronic activation \u003cb\u003e(Figure S2D)\u003c/b\u003e, with activation markers also elevated, though Ccr5 and Eomes were not significantly increased \u003cb\u003e(Figure S2E)\u003c/b\u003e. These markers are integral to the T cells homing ability to inflammatory sites, sustain activation, and execute their cytotoxic functions, suggesting CD8\u0026thinsp;+\u0026thinsp;T cells in Axl KO mice are in a more activated state and have enhanced effector functions.\u003csup\u003e\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e We then observed that Axl KO CD8\u0026thinsp;+\u0026thinsp;T cells showed increased expression of type I and II interferon receptors and Tcf7, indicating greater sensitivity to interferon signaling \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF\u003cb\u003e).\u003c/b\u003e This enhanced signaling is known to boost T cell responses, cytokine production, and expands the TCF7-expressing stem-like CD8\u0026thinsp;+\u0026thinsp;T cell population.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e These cells are critical for sustaining immune responses through self-renewal and effector differentiation.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Gene set enrichment analysis (GSEA) confirmed enriched T cell receptor signaling and adaptive immune pathways in Axl KO CD8\u0026thinsp;+\u0026thinsp;T cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e. In contrast, B16F0-cOva bearing Axl KO mice CD8\u0026thinsp;+\u0026thinsp;T cells exhibited reduced Tcf7 expression and elevated exhaustion markers, indicating terminal exhaustion \u003cb\u003e(Figure S2F)\u003c/b\u003e. Despite this, GSEA revealed increased antigen response and reduced wound healing pathways, suggesting these cells were in a later phase of inflammation \u003cb\u003e(Figure S2G)\u003c/b\u003e. Overall, Axl KO CD8\u0026thinsp;+\u0026thinsp;T cells display a more activated and effector phenotype, positioning them as key players in controlling tumor growth.\u003c/p\u003e \u003cp\u003eIn MC38 tumors, Tregs from Axl KO mice exhibited significantly reduced levels of Ctla4 and Pdl1, which are known to suppress anti-tumor immunity (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e The higher expression of these immune checkpoints in WT Tregs suggests a stronger immune suppression in WT mice, alleviated in Axl KO mice. Additionally, Axl KO Tregs had increased IL-2 receptor expression, indicating altered functional dynamics, as this receptor is crucial for Treg proliferation and maintenance \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e.\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e These differences were not observed in B16F10-cOva \u003cb\u003e(Figure S2C)\u003c/b\u003e. We next observed there were no differences tumor models and knockouts of Tgfb1, a well-known known mediator of Treg immunosuppression\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC \u003cb\u003eand Figure S2C)\u003c/b\u003e. These findings suggest that Axl alters the regulatory landscape of the TME by reducing key inhibitory markers on Treg cells that could support greater antitumor immunity.\u003c/p\u003e \u003cp\u003eTo confirm T cell-mediated antitumor response, we depleted T cells in the MC38 and B16F0-cOva tumor models \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH\u003cb\u003e)\u003c/b\u003e. CD8\u003csup\u003e+\u003c/sup\u003e T cell depletion in Axl KO mice eliminated the tumor growth delay, confirming its dependence on CD8\u003csup\u003e+\u003c/sup\u003e cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI\u003cb\u003e)\u003c/b\u003e. In contrast, CD4\u003csup\u003e+\u003c/sup\u003e T cell depletion led to a more pronounced tumor growth delay in both models, likely due to the removal of Tregs, which were highly suppressive in these tumors \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ\u003cb\u003e)\u003c/b\u003e.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e These results underscore the distinct roles of CD8\u003csup\u003e+\u003c/sup\u003e and CD4\u003csup\u003e+\u003c/sup\u003e T cells in modulating tumor growth in Axl KO mice.\u003c/p\u003e \u003cp\u003eWe considered NK cells as mediators of tumor growth delay given that Axl has been implicated in NK cell function. However, Axl expression was low on NK cells in both tumor models, and no significant changes in NK cell activities were observed in Axl KO mice (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG and S1E\u003cb\u003e).\u003c/b\u003e Previous studies report that Axl is crucial for NK cell development, as Axl-deficient mice exhibit impaired NK cell maturation, reduced differentiation, prevent metastases, and diminished cytotoxic activity.\u003csup\u003e\u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Our scRNAseq data support a marginal difference in NK cell activation or cytotoxicity following Axl knockout with these tumor models (\u003cb\u003eFigure S2H\u003c/b\u003e). These findings suggested that, while Axl may influence NK cell function in certain contexts, the enhancement of anti-tumor immunity in Axl KO mice is primarily driven by CD8\u003csup\u003e+\u003c/sup\u003e T cells.\u003c/p\u003e\n\u003ch3\u003eAxl deficient cDC1 cells are key to tumor growth suppression\u003c/h3\u003e\n\u003cp\u003eGiven the increased CD8\u003csup\u003e+\u003c/sup\u003e T cell activation in Axl KO mice, we investigated whether DCs drive the antitumor response, as they bridge innate and adaptive immunity.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e Sub-clustering of myeloid cells from the scRNAseq experiment identified cDC1, cDC2, and DC3 subpopulations of DCs in both tumor models (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and S3A). Intratumoral myeloid populations were similar between Axl KO and WT mice, except for an increased frequency of cDC1 cells in MC38 tumors and a decreased presence of mast cells in B16F0-cOva tumors (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and S3B).\u003c/p\u003e \u003cp\u003eGSEA of the entire DC population revealed elevated levels of cytotoxic T cell activation, antigen processing and presentation, and humoral immune response in intratumoral DCs from Axl KO mice in MC38 tumor, with increased inflammatory signaling in B16F0-cOva tumors \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and S3C\u003cb\u003e)\u003c/b\u003e. We focused on cDC1 cells due to their proficiency in cross-presentation of antigens to CD8\u003csup\u003e+\u003c/sup\u003e T cells and higher frequency in MC38 TME.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e To test whether the absence of Axl enhances DC-mediated T cell priming, we performed a T cell priming assay using flow cytometry sorted splenic cDC1 cells (\u003cb\u003eFigure S3D\u003c/b\u003e) pulsed with ovalbumin protein and Kdo2-Lipid A, a TLR-4 agonist comparable to LPS, then co-cultured with CFSE labeled CD8\u003csup\u003e+\u003c/sup\u003e OTI cells for three days (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Co-culture with cDC1 cells from Axl KO mice significantly increased OTI T cell proliferation and CD69 expression (\u003cb\u003eFigures S3E, 3E and 3F\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eTo determine if cDC1s contribute to the tumor growth delay in Axl KO mice, we crossed Axl KO mice with cDC1 deficient Batf3 KO mice and assessed tumor growth delay. The delayed growth of MC38 and B16F0-cOva tumors observed in AXL KO mice, was ablated in absence of cDC1, with growth rates matching those in BATF3 KO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). This indicates that the tumor growth delay in Axl KO mice is dependent on cDC1 cells.\u003c/p\u003e \u003cp\u003eTo assess whether cDC1 cells are sufficient to delay tumor growth, we co-injected cDC1 cells from Axl KO mice (\u003cb\u003eFigure S3F\u003c/b\u003e) with MC38 tumor cells into WT hosts \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH\u003cb\u003e).\u003c/b\u003e This experiment led to significantly delayed MC38 tumor growth as compared to co-injection with WT cDC1. Therefore, we conclude that Axl-deficient cDC1 cells in TME are the key driver of delayed tumor growth.\u003c/p\u003e\n\u003ch3\u003eThe loss of Axl on macrophages does not impact the tumor response\u003c/h3\u003e\n\u003cp\u003eMacrophages showed the highest Axl expression, leading us to investigate how Axl loss impacts their function. scRNAseq results showed minimal differences in gene expression between intratumoral macrophages from WT and Axl KO mice in both MC38 or B16F0-cOva tumors \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e GSEA showed only one enriched gene set in WT macrophages in MC38 tumors compared to Axl KO \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e However, in B16F0-cOva tumors, we observed more enriched gene sets \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e Macrophages from WT mice were enriched in metabolic pathways, while those from Axl KO mice showed enriched proinflammatory pathways \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate how Axl loss affects macrophage role and phenotype in TME, we compared expression scores evaluating angiogenesis, phagocytosis, and M1/M2 polarization gene signatures. Axl knockout led to significant changes in macrophage polarization in both tumor types. In B16F0-cOva tumors, Axl loss upregulated M1-like gene signatures and downregulated M2-like signatures. However, in MC38 tumors, M1-like signatures were reduced, suggesting Axl plays a more nuanced role in regulating macrophage behavior depending on the tumor context \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo pinpoint the cell type driving delayed tumor growth in Axl-deficient mice between macrophages and DC cells, we generated conditional Axl KO mouse models. We used CD11c-Cre and LysM-Cre crossed with Axl floxed mice to specifically delete Axl in DC or myeloid cells, respectively. The deletion of Axl on dendritic cells delayed the growth of MC38 and B16F0-cOva tumors \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH\u003cb\u003e).\u003c/b\u003e Despite changes in macrophage identity and increased proinflammatory signaling in B16F0-cOva tumors \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e)\u003c/b\u003e, these alterations did not impact tumor growth in the LysM-Cre Axl KO model \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI\u003cb\u003e).\u003c/b\u003e This suggests that Axl loss in dendritic cells, not myeloid cells, drives the delayed tumor growth.\u003c/p\u003e\n\u003ch3\u003eLoss of Axl enhances cDC2 immune response and T cell priming\u003c/h3\u003e\n\u003cp\u003eThe role of Axl in DC subpopulations \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and S5A\u003cb\u003e)\u003c/b\u003e remains poorly understood. cDC2 are the most abundant DCs subpopulation in mouse and human TME \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, and S3A\u003cb\u003e).\u003c/b\u003e We evaluated Axl expression in DC subpopulations of WT mice \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and S5B\u003cb\u003e)\u003c/b\u003e. In both tumor models, cDC2 expressed the highest levels of Axl. We then analyzed the effect of Axl knockout on toll-like receptors (TLRs), adapter proteins, and maturation markers. Axl loss resulted in a general increase in these markers, most notably in cDC2 cells \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-D and S5C-D\u003cb\u003e).\u003c/b\u003e This suggests that Axl acts as a negative regulator of these pathways, and its absence enhances cDCs ability to sense danger signals, mature, and promote adaptive immune responses.\u003c/p\u003e \u003cp\u003eGiven the high Axl expression in DC2 cells specifically in MC38 tumor model, we subclustered cDC2 to assess the role of Axl on antitumor response. We identified four distinct subsets: DC2-1, DC2-2, DC2-3, and DC2-4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) The DC2-4 subpopulation was enriched in tumors in Axl KO mice \u003cb\u003e(Figure S5E)\u003c/b\u003e. Differential expression analysis showed that the DC2-4 subpopulation exhibited a cDC1-like phenotype, expressing cDC1 canonical markers such as Xcr1, Clec9a, Irf8, and Batf3 while still expressing cDC2 canonical markers \u003cb\u003e(Figure S5F and Figure S5F)\u003c/b\u003e and cluster with cDC2 rather than cDC1 \u003cb\u003e(Figure S5G)\u003c/b\u003e as we excluded them from being misclustered. Moreover, DC2-4 also had lower Axl expression compared to other cDC subpopulations in WT mice \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e, suggesting that Axl may play a role in modulating the switch to a cDC1-like phenotype. Furthermore, GSEA of cDC2-4 showed enriched in pathways involving inflammatory responses, response to interferons, myeloid cells differentiation \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis unexpected finding led us to investigate whether Axl knockout enhanced CD8\u003csup\u003e+\u003c/sup\u003e T cell priming efficiency in cDC2 cells. Using flow-sorted splenic cDC2 cells, we co-cultured them for three days with CFSE-labeled OTI cells after pulsing with Ovalbumin and Kdo2-Lipid A. Axl-deficient cDC2 cells increased T cell proliferation, indicating that Axl loss enhances CD8\u003csup\u003e+\u003c/sup\u003e T cell priming in cDC2 cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEnhanced immune response in Axl-deficient DCs is dependent on Type I IFN signaling\u003c/h2\u003e \u003cp\u003ePrevious studies have highlighted Axl's role in limiting type I interferon (IFN) production and signaling in DCs.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e To determine if the enhanced anti-tumor immunity observed in the absence of Axl is dependent on IFNAR1 signaling, we assessed type I IFN production and signaling in three DC subpopulations \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. DC2 and DC3 cells in Axl-deficient mice showed significantly higher type I IFN production 7 days after tumor inoculation, with all subpopulations exhibiting increased signaling, particularly in the B16F0-cOva TME. To evaluate the role of type I IFN signaling on tumor growth, we transplanted MC38 and B16F0-cOva tumors into CD11c-Cre Axl flox/flox and control Axl flox/flox mice, then treated them with intratumoral IFNAR1 antibodies to block type I IFN signaling \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC\u003cb\u003e).\u003c/b\u003e Blocking IFNAR1 signaling eliminated the tumor growth delay observed in CD11c-Cre, Axl flox/flox mice, leading to tumor progression like that in Axl flox/flox mice \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE\u003cb\u003e).\u003c/b\u003e These findings suggest that the enhanced tumor immunity in Axl-deficient DCs is dependent on increased type I IFN signaling.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eType I IFN dependence drives sensitivity to STING agonist in Axl KO models\u003c/h3\u003e\n\u003cp\u003eAfter exposure to environmental stress, anti-tumor immune responses, or therapeutic agents, cancer cells undergo cell death and release damage-associated molecular patterns (DAMPs) such as high mobility group box 1 (HMGB1) and dsDNA.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e DAMPs activate Toll-like receptor 4 (TLR4) and cyclic GMP-AMP synthase (cGas) in DCs, triggering type I IFN production and subsequent immune activation. \u003csup\u003e\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e To examine the role of Axl deficiency in enhancing cGAS-STING signaling, we treated mice with DMXAA, a STING agonist. When tumors reached approximately 200mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, we administered a single intratumoral dose of DMXAA to mice bearing MC38 tumors \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF\u003cb\u003e).\u003c/b\u003e The treatment significantly reduced tumor growth in Axl KO mice compared to WT mice \u003cb\u003e(\u003c/b\u003eFigs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe then evaluated how Axl deficiency enhanced DMXAA efficacy in a therapy-resistant Py8119 tumor model and added ionizing radiation to facilitate cell death. The Py8119 cells are known for their resistance to immune checkpoint blockade (ICB) and radiotherapy due to an immunosuppressive TME.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e We implanted Py8119 cells expressing cOva into WT and Axl KO mice and treated them with either DMXAA alone or in combination with a single 15 Gy dose of ionizing radiation once tumors reached a volume of 80 mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH\u003cb\u003e).\u003c/b\u003e In Axl KO mice, both DMXAA alone and its combination with ionizing radiation significantly delayed tumor growth in Axl KO mice compared to WT mice under the same treatments \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI\u003cb\u003e).\u003c/b\u003e These results suggest that Axl deficiency enhances DMXAA efficacy, likely through enhanced Type I IFN signaling that would otherwise be dampened by Axl. The marked reductions in tumor growth with both monotherapy and combination treatment in resistant tumor models underscore the potential for combination therapy.\u003c/p\u003e\n\u003ch3\u003eAxl inhibition replicates knockout, supporting STING-agonist combination therapy\u003c/h3\u003e\n\u003cp\u003eTo assess the therapeutic potential of targeting Axl, we treated WT mice bearing MC38 tumors with the Axl small molecule kinase inhibitor Bemcentinib (BGB324) as a monotherapy and in combination with the STING agonist DMXAA. MC38 cells were inoculated into WT mice and half of them started receiving BGB324 daily. Once tumors reached an average volume of 160mm\u0026sup3;, a single dose of DMXAA was delivered intratumorally \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Both BGB324 and DMXAA as monotherapies significantly delayed tumor growth compared to untreated mice, but the combination therapy exhibited the greatest tumor regression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB-C\u003cb\u003e).\u003c/b\u003e The combination therapy led to no tumor-related deaths throughout the study and extended survival compared to either treatment alone \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e These results demonstrate that Axl inhibition, in conjunction with STING agonist therapy, provides superior tumor control and survival outcomes, likely due to enhanced Type I IFN signaling and improved T cell priming via dendritic cells. This combination approach holds promise for enhancing anti-tumor immunity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAxl, a member of the TAM receptor family, is well-known for promoting tumor cell survival, metastasis, and immune evasion. Recent studies have expanded our understanding of Axl’s role in immune cells regulation within the TME. While most research has focused on Axl expression in tumor cells, our study shifts focus to its expression in DCs, revealing a novel role for Axl in suppressing anti-tumor immunity. Mechanistically, we showed that Axl acts as a negative regulator of type I IFN signaling in DCs, and its absence enhances antitumor immune responses in cancer models. In an Axl-deficient host, DCs exhibit increase inflammatory signaling, improved cDC1/2 cross-priming ability, and an enhanced capacity to stimulate anti-tumor CD8 T cell responses, leading to tumor growth delay. This CD8 T cell-dependent effect confirms that the loss of Axl specifically on DCs strengthens immune system's anti-tumor capabilities. These findings highlight that Axl’s impact extends beyond tumor cells to key immune cells that initiate adaptive immune responses introducing a new perspective on Axl’s role in immune regulation with potential translational implications.\u003c/p\u003e \u003cp\u003eDCs are key immunotherapy targets, particularly following type I IFN-stimulating therapies or immune checkpoint inhibition that relies on DC mediated adaptive responses.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e–\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e Axl blockade has previously been combined with immunotherapy, radiotherapy (RT), and chemotherapy to enhance immune responses.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e–\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e Herein, we report direct IFN stimulation using a STING agonist can have enhanced therapeutic activity in a Axl knockout host or with inhibition. Our data supports that combining Axl inhibition with type I IFN-stimulating therapies could enhance anti-tumor immunity by reversing Axl’s suppression of IFN signaling in DCs. As anti-Axl therapies such as Bemcentinib advance in clinical development, our findings support new strategies for combination therapies that include STING agonists.\u003c/p\u003e \u003cp\u003eAxl is associated with poor prognosis and drug resistance in multiple malignancies such as acute myeloid leukemia (AML), lung, and breast cancers.\u003csup\u003e\u003cspan additionalcitationids=\"CR65 CR66 CR67\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e–\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e This prompted the development of Axl-targeting therapies that aim to limit tumor cell proliferation, induce apoptosis, and prevent metastasis.\u003csup\u003e4–9,69−71\u003c/sup\u003e While clinical trials with these therapies have not yet demonstrated significant clinical benefits as monotherapies, phase II trials combining Axl inhibitors with immunotherapy have shown promise. However, Axl’s role in immune modulation, particularly in DCs, remains largely unexplored and is a new direction for future study based off this work.\u003c/p\u003e \u003cp\u003eWe now have the groundwork and the significance to explore Axl's role in DC biology, with future studies needed to clarify how Axl regulates DC cross-priming and interacts with other immune cells in the TME. Additional research should examine Axl’s impact on immune cell localization and signaling dynamics within DC subpopulations, such as cDC2 and cDC3. Tracking immune response dynamics could reveal insights into Axl’s modulation of immunity. Understanding Axl’s effects on specific DC subsets may inform combination therapies, integrating Axl inhibition with immune checkpoint blockade, chemotherapy, RT, and STING agonists, to enhance anti-tumor immunity and address immune resistance in cancer treatment.\u003c/p\u003e \u003cp\u003eImproving our mechanistic understanding of Axl’s influence on DC function and establishing this relevance in humans should assist the development of targeted therapeutic combinations. Such treatments would exploit this pathway to enhance anti-tumor immunity and overcome immune resistance in cancer treatment.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003ch2\u003eMouse models\u003c/h2\u003e\u003cp\u003eMice used in this study were all C57BL/6J background, with both males and females included, when possible, aged between 6 and 16 weeks. C57BL/6J (JAX:000664), B6.Cg-Tg(Itgax-cre)1-1Reiz/J (CD11c-Cre) (JAX:008068)\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, and B6.129P2-Lyz2tm1(cre)Ifo/J (LysM-Cre) (JAX:004781)\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e mouse strains were purchased from Jackson Laboratories. The following mice were kindly gifted from the labs of: Dr. Greg Lemke (Salk Institute for Biological Sciences) provided AXL(tm1Grl/J) (Axl\u003csup\u003e−/−\u003c/sup\u003e)\u003csup\u003e74\u003c/sup\u003e mice, Dr. Carla Rothlin (Yale School of Medicine) supplied AXL(tm1.1Cvro) (Axl\u003csup\u003eflox/flox\u003c/sup\u003e)\u003csup\u003e75\u003c/sup\u003e mice, and Dr. Yang Xin Fu (UT Southwestern) contributed C57BL/6-Tg(TcraTcrb)1100Mjb/J (OT-1)\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e, and B6.129S(C)-Batf3tm1Kmm/J ( Batf3\u003csup\u003e−/−\u003c/sup\u003e)\u003csup\u003e49\u003c/sup\u003e mice. All mice were housed in specific pathogen free faculties and treated in accordance with the animal experimental guidelines approved by the Institutional Animal Care and Use Committee (Protocol# XXXX).\u003c/p\u003e\u003ch2\u003eTumor growth experiments\u003c/h2\u003e\u003cp\u003eMC38 and B16F0-cOva were grown in Dulbeccos Modified Eagle Medium (DMEM) media (10-013-CV, Corning) supplemented with 10% FetalClone II (FCII) (SH30066.03, Cytiva). Py8119-cOva cells were grown in F12 Ham’s media supplemented with 10% FCII and 1X Mito + serum extender (355006, Corning). B16F0-cOva were a gift from the Engleman lab and Py8119-cOva cells were derived from Py8119 cells transduced with Ova containing lentivirus (lentiviral vector pLenti-Blasticidin-3XCMV, gift from Guo-Min Li lab), Ova expression was confirmed by flowcytometry following IFN-g stimulation. All cells were kept in a cell culture incubator at 37°C and 5% CO2 and were tested to be free of mycoplasma (30-1012K, ATCC). In preparation for inoculation, growth media was aspirated, culture flask were then rinsed with phosphate buffered saline (PBS) solution and trypsinized (T4049, Sigma) for 5–10 mins. After which trypsinization was neutralized via the addition of complete growth media and collected in conical tubes. Cells were spun down and washed with PBS 2x additionally cells passed through a 70µM cell strainer to remove cellular aggregates. Cells were mixed at 1:1 ratio of trypan blue (Corning) were viability and cell number were measured via a TC20 automated cell counter (BioRad). Cells were then re-suspended in PBS at desired inoculated cell count per 50µL of total volume. Using a 28G insulin syringe 50µL of cell suspension was injected into the subcutaneous space on the lower right flank (MC38, B16F0-cOva) or into the mammary fat pad (Py8119-cOva). Tumor dimensions were measured via calipers every 2–3 days with tumor volumes being calculated mm\u003csup\u003e3\u003c/sup\u003e= (Length*Length* Width)/2.\u003c/p\u003e\u003ch2\u003eFlow cytometry\u003c/h2\u003e\u003cp\u003eTumor cells were trypsinized from flask and washed with complete growth media. Cells were then re-suspended at 1x10\u003csup\u003e6\u003c/sup\u003e cells/100µLs of autoMACS Rinsing Solution containing 0.5% BSA + 2mM EDTA (Miltenyi Biotec) and stained with mouse anti-AXL antibody conjugated with PE (FAB8541P, R\u0026amp;D) at 1:10 dilution or with PE conjugated IgG2a isotype antibody (RTK2758, Biolegend) at a 1:100 dilution. Cells were incubated for 20 mins at 4°C, washed 2 times and run on a LSRFortessa (BD) flow cytometer. FCS files were plotted and analyzed using FlowJo software (BD).\u003c/p\u003e\u003ch2\u003eTumor treatments\u003c/h2\u003e\u003cp\u003eDepletion of CD8\u003csup\u003e+\u003c/sup\u003e and CD4\u003csup\u003e+\u003c/sup\u003e T cells was achieved via the intraparietal administration of 300µg of anti-CD8 (2.43, BioXcell) or anti-CD4 (GK1.5, BioXcell) every 6 days starting 2 days prior to tumor inoculation. Control mice were administered IgG2b isotype control antibodies (LTF-2, BioXcell). Type I IFN signaling was blocked via the intratumoral administration of 50µg anti-IFNAR-1 (MAR1-5A3, BioXcell) every other day starting on the day after tumor inoculation. Control mice were treated with IgG1 isotype control antibodies (MOPC-21, BioXcell). MC38 tumors were allowed to grow and randomized into treatment groups with average tumor volumes ~ 200mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Tumors were then treated with a single 250µg dose of STING agonist DMXAA (5601/50, Tocris Bioscience) re-suspended in DMSO. Control mice received an intratumoral injection of pure DMSO. Py8119-cOva tumors were allowed to grow days and randomized into groups with mean tumor volume ~ 80mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In addition to DMXAA, some mice were treated locally with 15 Gy radiation under anesthesia. For experiments involving Axl inhibition, MC38 cells were inoculated into WT mice. These mice were then administered either a vehicle control (0.20% methylcellulose + 5% DMSO in water) or 50 mg/kg of BGB324 by oral gavage twice daily, starting on the day of inoculation. Tumors were then allowed to grow until reaching an average volume of 160mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and treated with a single dose of DMXAA as previously stated.\u003c/p\u003e\u003ch2\u003eTissue harvest and single cell sequencing\u003c/h2\u003e\u003cp\u003eTo evaluate Axl’s influence over the immune landscape of the tumor microenvironment 1x10\u003csup\u003e6\u003c/sup\u003e MC38 or B16F0-cOva cells were each subcutaneously inoculated into 4 WT (Wild Type) (2M + 2F) and 4 AXL KO (2M + 2F) mice and allowed to grow for 7 days. After 7 days tumors were harvested from each mouse. On ice, tumors were placed in 60mm culture dish and processed into small ~ 1mm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e pieces using scalpels. After which we add 5mL of digestion media composed of (4:1 HBSS (21-020-CV, Corning): RMPI (10-040-CV, Corning) + 3% FCII + 10ug/mL DNase I (D5025-150KU, Sigma) + 10.5 µM Y-27632 dihydrochloride (rock kinase inhibitor) (Y0503-5MG, Sigma) + 100 U/mL Collagenase IV (LS004188, Worthington) + 1mg/mL Soybean Trypsin Inhibitor (LS003571, Worthington) + 2 mg/mL Dispase II (17105-041, Gibco)) then placed in a shaking incubator set at 37°C for 30 mins. After initial incubation tissue was triturated with a pipette then incubated for an additional 15 mins. After which entire culture dish contents were paced through a 40µM cell strainer and washed with excess volume PBS supplemented with 3% FCII. Remaining red blood cells were lysed with the addition of ACK Lysis buffer (A1049201, Gibco) and incubated at room temperature for 5 mins. After lysis cells were prepped for CD45\u003csup\u003e+\u003c/sup\u003e enrichment via MACS separation (Miltenyi Biotec) by being washed and re-suspended in autoMACS Rinsing Solution containing 0.5% BSA + 2mM EDTA. CD45 MicroBeads were added to cell suspension and incubated for 15 mins at 4°C. After being washed, cells were passed through magnetic columns and attached cells were eluted. Once single cell suspension was achieved for all tissue samples cellular viability and count was determined via TC20. Cells were re-suspended at 1x10\u003csup\u003e6\u003c/sup\u003e cells/ 49.5µL of Cell Staining Buffer (420201, Biolegend) and blocked with 0.50µL of TruStain FcX Plus (S17011E, Biolegend) for 10 mins at 4°C then stained with 0.50µg of each Cite-Seq antibodies. Cells were washed 3 times in staining buffer, passed through a 40µM cell strainer and re-suspended in 0.04% BSA/PBS and adjusted to 1000 cells/µl. Cells were loaded according to standard protocol of the Chromium single cell 5′ kit, capturing 10,000 cells (V3 chemistry). All subsequent procedures, including library construction, were performed according to the standard manufacturer’s protocol. Single-cell libraries were sequenced on NovaSeq (Illumina) to a depth of 50,000 reads per cell.\u003c/p\u003e\u003ch2\u003eDC sorting\u003c/h2\u003e\u003cp\u003eTo amplify the production of conventional dendritic cells 10\u0026nbsp;million B16-FLT3L tumor cells grown in DMEM supplemented with 10% FCII were subcutaneously injected in 100 uL of PBS into mice of the desired genotype. Tumors were allowed to grow for 2 weeks; spleens were then harvested and CD11c\u003csup\u003e+\u003c/sup\u003e cells were isolated via MACS beads from splenocytes as previously mentioned. For FACs sorting of cDC1 and cDC2 cells isolated CD11c\u003csup\u003e+\u003c/sup\u003e cells were resuspended at 10\u003csup\u003e7\u003c/sup\u003e cells/mL of autoMACS Rinsing Solution containing 0.5% BSA + 2mM EDTA and incubated with anti-16/32 TruStain FcX plus (156604, Biolegend) for 10 mins at 4°C to prevent nonspecific binding of antibodies to FC receptors. Next without washing fluorescent conjugated antibodies CD11c (117311, Biolegend), MHC class II (107632, Biolegend), CD11b (101228, Biolegend), CD8a (100708, Biolegend), and XCR1 (148206, Biolegend) all antibodies were added at 1:100 dilution and incubated at 4°C in the dark for 20 minutes. After incubation cells were washed 2 times and resuspended at 5x10\u003csup\u003e6\u003c/sup\u003e cells/mL in autoMACS rinsing solution. Cells were sorted on FACSymphony S6 (BD) and collected in 15 mL conical tubes prefilled with RPMI + 5% heat inactivated FCII. For MACS bead separation of cDC1 cells anti-XCR1 MicroBead Kit (130-115-721, Miltenyi Biotec) was used on splenocytes according to the manufacturer provided protocol.\u003c/p\u003e\u003ch2\u003eIn Vitro dendritic cell assay\u003c/h2\u003e\u003cp\u003e200,000 flow cytometry sorted cDC1 and cDC2 cells from either WT or Axl KO mice were plated per 96 well plate well in 100 µL of RPMI + 5% heat inactivated FCII. DCs were pulsed with 25 µg/mL of Ovalbumin protein (vac-stova, Invivogen) and stimulated with 50 ng/mL of Kdo2-Lipid A (NC9765889, Avanti Polar Lipids) and incubated at 37°C for 24 hours. Prior to 24-hour incubation of DCs being up splenocytes were collected from OT-I mice and naïve CD8 T cells were isolated via MACS separation kit (130-096-543, Miltenyi) according to manufacturer provided protocol. Isolated OT-I cells were resuspended in PBS and stained with 5 µM of CFSE cell division tracker dye (423801, Biolegend) for 20 minutes at 37°C then quenched with complete media and washed in PBS. After 24-hour incubation DCs were washed with PBS and 100,000 CFSE labeled OT-I cells were added on top in RPMI + 5% heat inactivated FCII. Cells were incubated at 37°C for an additional 3 days. After 3-day incubation cells were washed then stained with Zombie NIR viability dye (423106, Biolegend) for 15 mins at 4°C diluted in PBS at 1:200 dilution. Cells were then washed in autoMACS rinsing solution and stained for flow cytometry with TCR-b (109238, Biolegend), CD11c (117310, Biolegend), CD69 (104512, Biolegend), each antibody was stained using a 1:100 dilution and incubated at 4°C for 20 minutes. Cells were run on LSRFortessa flow cytometer and analyzed using FlowJo software.\u003c/p\u003e\u003ch2\u003eDC transplants\u003c/h2\u003e\u003cp\u003e500,000 XCR1\u003csup\u003e+\u003c/sup\u003e isolated as previously described from either WT or Axl KO mice were mixed at a 1:1 ratio with MC38 cells in 50µL of PBS and subcutaneously inoculated in the right flank of WT mice. Tumor growth was evaluated via caliper measurements every 2–3 days with tumor volumes being calculated mm^3= (Length*Length* Width)/2.\u003c/p\u003e\u003ch2\u003eSingle Cell Sequencing analysis\u003c/h2\u003e\u003cp\u003eRaw data and FASTQs were generated by North Texas Genome Center, The University of Texas at Arlington. Using Cell Ranger version 5.0.1 pipeline, FASTQ files were aligned to the mouse reference genome (mm10) using STAR version 2.7.2a and counted using Cell Ranger count with default parameters and recommendations with feature barcode option. The counting matrix was imported into Seurat (5.1.0) via R (4.4.1) for quality assessment and downstream analysis. Cells were filtered by excluding cells with less than 200 genes, all genes in less than three cells, and genes expressed as being composed of greater than 20% mitochondrial genes. Data were then normalized using the NormalizeData function with default parameters. Variable genes were detected using the FindVariableFeatures function. Data were scaled and centered using linear regression. Principle component analysis was run with the RunPCA function using default parameters. Batch effects were corrected, and samples were integrated by using harmony (1.2.0) and SeuratWrappers (0.2.0) library with default parameters. Cell clusters were identified via the FindNeighbors and FindClusters functions, with 0.5 resolutions for major cell clusters and UMAP or tSNE clustering algorithms. Subsequent clustering for the lymphoid and myeloid cells a higher resolution (0.8 and 1.2) was respectively. A FindAllMarkers table was created, and clusters were defined by using SingleR (2.6.0) and celldex (1.14.0) with ImmGenData from (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.immgen.org/\u003c/span\u003e\u003cspan address=\"https://www.immgen.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and finally with canonical marker s. Gene Ontology (GO) enrichment for each cluster and between samples was performed using clusterprofiler (4.12.0) and GSEABase (1.66.0) using differentially expressed genes at 0.5-fold change and 0.05 Adjusted p value. GO annotations were obtained using msigdbr (7.5.1). Cell proportion differences calculated using scProportionTest (0.0.0.9000). Graphs and plots were generated by ggplot2 (3.5.1), EnhancedVolcano (1.22.0), SCP (0.5.6), or Seurat.\u003c/p\u003e\u003ch2\u003eStatistics\u003c/h2\u003e\u003cp\u003eTumor growth curves were analyzed using repeated measures model in SAS software (SAS Institute Inc., Cary NC), accounting for variability within individual mice. Post hoc pairwise comparisons were performed using a Tukey adjustment. To assess differences in T cell priming among experimental groups, a one-way ANOVA was conducted in GraphPad Prism (GraphPad Software, San Diego, CA) using mean values from technical replicates. Mouse survival was summarized using Kaplan- Meier curves, significance was evaluated using log-rank Mantel-Cox test performed with GraphPad Prism. Survival endpoint was defined as a death due to tumor burden or a humane endpoint due to tumor size exceeding 17.5 mm in any measurement, with time-to-event data recorded for each mouse. 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Cell 76:17\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0092-8674(94)90169-4\u003c/span\u003e\u003cspan address=\"10.1016/0092-8674(94)90169-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5569516/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5569516/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Axl receptor tyrosine kinase is pivotal for metastatic tumor progression, tumor immune evasion, and regulating inflammation of innate immune cells. In this study we investigated Axl’s immune function in immunogenic tumors and found that Axl knockout (KO) mice exhibited a significant delay in tumor growth. Single-cell RNA sequencing revealed that Axl deficiency increases CD8 T cell activity. Tumor growth delay was dependent on CD8 T cells and BATF3 expression, indicating a role for Axl in regulating dendritic cell (DC) cross priming activities. Cre-driven conditional KO models further demonstrated that loss of Axl on DCs—but not on macrophages—was sufficient to slow tumor growth, a process reliant on type I interferon (IFN) signaling. Given Axl’s role in modulating IFN-I signaling, we discovered that its absence enhanced the effectiveness of STING agonists and improved the cross-priming capacity of both cDC1 and cDC2 subsets.","manuscriptTitle":"Axl inhibition on dendritic cells enhances STING anticancer therapy through type I interferon signaling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-13 04:28:53","doi":"10.21203/rs.3.rs-5569516/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4099789a-3dbe-4a23-b62f-6cb2af49dc46","owner":[],"postedDate":"January 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":41365146,"name":"Biological sciences/Cancer/Tumour immunology"},{"id":41365147,"name":"Biological sciences/Immunology/Tumour immunology"},{"id":41365148,"name":"Biological sciences/Cancer/Cancer microenvironment"}],"tags":[],"updatedAt":"2025-01-13T04:28:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-13 04:28:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5569516","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5569516","identity":"rs-5569516","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}