A2AR eGFP reporter mouse enables elucidation of A2AR expression dynamics during anti-tumor immune responses

Todd, Kirsten L.; Lai, Junyun; Sek, Kevin; Huang, Yu-Kuan; Newman, Dane M.; Derrick, Emily B.; Koay, Hui-Fern; Nguyen, Dat; Hoang, Thang X.; Petley, Emma V.; Chan, Cheok Weng; Munoz, Isabelle; House, Imran G.; Lee, Joel N.; Kim, Joelle S.; Li, Jasmine; Tong, Junming; N. de Menezes, Maria; Scheffler, Christina M.; Yap, Kah Min; Chen, Amanda X. Y.; Dunbar, Phoebe A.; Haugen, Brandon; Parish, Ian A.; Johnstone, Ricky W.; Darcy, Phillip K.; Beavis, Paul A.

doi:10.1038/s41467-023-42734-0

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Published: 01 November 2023

A_2AR eGFP reporter mouse enables elucidation of A_2AR expression dynamics during anti-tumor immune responses

Nature Communications volume 14, Article number: 6990 (2023) Cite this article

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Abstract

There is significant clinical interest in targeting adenosine-mediated immunosuppression, with several small molecule inhibitors having been developed for targeting the A_2AR receptor. Understanding of the mechanism by which A_2AR is regulated has been hindered by difficulty in identifying the cell types that express A_2AR due to a lack of robust antibodies for these receptors. To overcome this limitation, here an A_2AR eGFP reporter mouse is developed, enabling the expression of A_2AR during ongoing anti-tumor immune responses to be assessed. This reveals that A_2AR is highly expressed on all tumor-infiltrating lymphocyte subsets including Natural Killer (NK) cells, NKT cells, γδ T cells, conventional CD4⁺ and CD8⁺ T lymphocytes and on a MHCII^hiCD86^hi subset of type 2 conventional dendritic cells. In response to PD-L1 blockade, the emergence of PD-1⁺A_2AR^- cells correlates with successful therapeutic responses, whilst IL-18 is identified as a cytokine that potently upregulates A_2AR and synergizes with A_2AR deficiency to improve anti-tumor immunity. These studies provide insight into the biology of A_2AR in the context of anti-tumor immunity and reveals potential combination immunotherapy approaches.

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Introduction

Adenosine is an immunosuppressive metabolite that modulates anti-tumor immunity and is produced from the degradation of adenine nucleotides by the ecto-enzymes CD73 and CD39 on tumor cells, stroma and fibroblasts or through direct export from the intracellular compartment of cells undergoing hypoxia and/or stress^{1,2,3,4,5,6,7}. Adenosine binds to four known G-coupled receptors, A₁R, A_2AR, A_2BR, and A₃R on immune cells with the majority of immunosuppressive effects thought to be mediated through A_2AR and A_2BR. A_2AR and A_2BR elicit immunosuppressive effects on tumor-infiltrating immune cells due to activation of adenylate cyclase, which results in increased intracellular cAMP. Pioneering studies by Sitkovsky and colleagues have demonstrated that extracellular adenosine potently modulates immune responses and antitumor immunity^2,3.

Accordingly, enhanced anti-tumor responses are observed in A_2AR deficient mice^3,5,8,9, an observation that led to the development of small molecule antagonists, which elicit anti-tumor immunity against solid tumors in mice^{3,5,8,10,11,12}. A_2AR antagonists have been evaluated in clinical trials against a range of solid tumors including renal cell carcinoma, non-small cell lung carcinoma, prostate, breast, and head and neck cancers¹³. Moreover, preclinical investigations have highlighted that targeting the A_2AR either genetically or pharmacologically enhances the efficacy of immune checkpoint blockade^5,8,14 or adoptive cellular therapy^{3,12,15,16,17,18,19,20,21}. Despite the intense interest in targeting this pathway, the mechanism of action is not completely understood. While A_2AR is known to be expressed on a range of immune cell types including CD8⁺ T cells, CD4⁺ T cells²², Tregs²³, NK cells^24,25, NKT cells²⁶, and myeloid cells²⁷, this has predominantly been determined from mRNA analyses due to a lack of an effective antibody recognizing this receptor that is suitable for flow cytometry. Therefore, a detailed analysis of the immune cell subpopulations expressing A_2AR have not been determined and, in addition, the factors driving A_2AR expression both within tumors at baseline and in response to therapy remain largely unknown. To overcome this, we describe a transgenic mouse model enabling the quantification of A_2AR through the expression of a GFP reporter gene. Using this model enables the expression of A_2AR on immune cells within solid tumors, draining lymph nodes (DLN) and the spleen to be assessed, allowing for analyses of A_2AR expression at baseline and in response to immunotherapies (anti-PD-L1, anti-CTLA-4 and IL-18) or chemotherapy (carboplatin).

This reveals that A_2AR is highly expressed in NK, CD8⁺, CD4⁺, NKT, and γδ T cells within tumors, with NK cells and conventional T cells constituting more than 50% of all A_2AR positive cells. Relatively limited A_2AR expression is observed on myeloid cells within the tumor, apart from cDC2s, and expression is absent from tumor-infiltrating B cells. When comparing the expression of A_2AR in the tumor and DLNs, T cells in the tumor uniquely express significantly more A_2AR than their counterparts in the DLN. We observe that whilst A_2AR expression is elevated in activated tumor antigen-specific CD8⁺ T cells in the DLN, A_2AR expression is fairly ubiquitous amongst CD8⁺ T cell sub-populations within the tumor, regardless of their antigen specificity or differentiation status. Treatment of tumor-bearing mice with anti-PD-L1 alone or combined anti-PD-L1 and anti-CTLA-4 leads to the emergence of a population of PD-1⁺A_2AR^- CD8⁺ T cells that correlate with therapeutic outcome. Transcriptomic analysis of A_2AR⁺ cells reveals that the most apparent difference between A_2AR⁺ and A_2AR^- CD8⁺ T cells is reduced expression of STAT5 target genes in A_2AR⁺ cells, a phenotype that is restored following anti-PD-L1 treatment. Lastly, these studies reveal that IL-18 is a potent inducer of A_2AR expression and that the therapeutic activity of IL-18 is accentuated in the context of A_2AR-deficient mice. In summary, we report the development of a mouse model that provides insight into the biology of A_2AR expression in the context of anti-tumor immunity and reveals potential mechanisms of action and combinatorial approaches for A_2AR blocking therapies.

Results

GFP expression accurately maps A_2AR expression in A_2AR eGFP reporter mice

To characterize the A_2AR eGFP reporter mice and ensure that GFP was a bona fide readout of A_2AR expression we first examined the expression of GFP within the spleens of mice. Immunofluorescent analysis indicated detectable expression of GFP in the spleens of A_2AR eGFP reporter mice, particularly in the T cell-rich region of the arterioles (Fig. 1A). Flow cytometry analyses of splenocytes revealed that GFP expression was highest in NK cells that are known to express high levels of A_2AR (Fig. 1B)^24,28 and CD8⁺CD44⁺ T cells, which is also consistent with a previous report²⁹ (Fig. 1C). FACS sorting of splenocytes from A_2AR eGFP reporter mice indicated that GFP⁺ splenocytes expressed significantly higher levels of A_2AR mRNA (Fig. 1D), confirming that GFP expression correlated with increased expression of the A_2AR. Consistent with previous reports indicating that activation of T cells through the TCR led to increased A_2AR mRNA expression³⁰, stimulation of splenocytes with anti-CD3/anti-CD28 led to a significant increase in GFP expression by both CD8⁺ and CD4⁺ T cells (Fig. 1E). Moreover, elevated GFP expression was associated with increased expression of PD-1 and CD44, highlighting that A_2AR expression was associated with an activated T cell phenotype in vitro (Fig. 1F). To confirm that A_2AR expression in reporter mice was functional we evaluated their response to adenosine receptor stimulation. Suppression of TNF by NECA, a pan adenosine receptor agonist, and reversal of this phenotype by SCH58261, an A_2AR antagonist, was observed following activation of splenocytes from A_2AR eGFP reporter mice or wild-type controls (Fig. 1G). To assess the impact of tumor antigen recognition on A_2AR expression, we generated anti-Her2 CAR T cells from A_2AR eGFP reporter splenocytes in line with our previous work using anti-Her2 CAR T cells¹⁶. Generation of CAR T cells led to increased expression of GFP relative to naïve T cells (Fig. 1H) and coculture of anti-Her2 CAR T cells with AT-3-, E0771-, or MC38-Her2 expressing tumor cells led to a further and significant induction of GFP in both CD8⁺ and CD4⁺ CAR T cells (Fig. 1I).

**Fig. 1: Validation of A_2AR eGFP reporter mice.**

A_2AR is expressed in a broad range of immune cells within the tumor microenvironment

A_2AR expression has been reported on a broad range of immune cells including conventional αβ T lymphocytes and NK cells but the expression of this receptor in the context of the tumor microenvironment has not been extensively investigated, and much less in a comparative analysis between subsets. Therefore, we examined the expression of GFP (A_2AR) within the tumor microenvironment. Having confirmed an important role for A_2AR in the control of AT3ova tumors (Fig. 2A), consistent with our previous observations⁸, GFP expression was determined in the tumors and draining lymph nodes of mice bearing AT3ova tumors (representative flow cytometry Fig. 2B, gating strategy; Supplementary Fig. 1A). This analysis revealed that, within the draining lymph nodes, A_2AR expression was most abundantly expressed on NK cells on a per cell basis (mean 74% positive), followed by γδ T cells (49.3% positive) and type I NK T cells (33.7% positive) (Fig. 2C). Expression of A_2AR was lower on CD8⁺ and CD4⁺ lymphocytes (4.7% and 5.4% positive respectively) and virtually absent on B lymphocytes (1.9% positive). However, over 50% of the A_2AR positive cells within draining lymph nodes were either CD4⁺ or CD8⁺ lymphocytes because of their higher overall frequency relative to innate lymphocyte subsets (Fig. 2D). We next investigated the expression of A_2AR within tumor-infiltrating lymphocytes. Notably, A_2AR expression was highly expressed in all subsets except for B lymphocytes (Fig. 2E), with NK cells, CD4⁺ lymphocytes and CD8⁺ lymphocytes together constituting over 50% of A_2AR⁺ cells within the tumor (Fig. 2F). Comparison of the expression of A_2AR in these lymphocyte subsets indicated that A_2AR was significantly upregulated in tumor-infiltrating lymphocytes relative to their counterparts in the tumor-draining lymph node, but this was more apparent with conventional CD8⁺ and CD4⁺ lymphocytes (5 fold increased expression in tumor relative to draining lymph node) than with NK, NKT and γδ T cells (all ~1.5 fold increased expression in the tumor) (Fig. 2B, G). Within the tumors, NK cells expressed a significantly higher level of A_2AR than all other immune subsets analyzed on a per cell basis (Fig. 2H). A similar pattern of A_2AR expression was observed in MC38 and E0771 tumors, that is to say A_2AR was highly expressed on innate-like cells (NK cells, NKT cells, γδ T cells) isolated from either DLNs or tumors and was significantly increased on conventional T lymphocytes isolated from tumors relative to counterparts isolated from draining lymph nodes (Supplementary Fig. 1B-F, Supplementary Fig. 2A, B). To investigate the relationship between A_2AR and tumor progression we assessed the expression of GFP on each of these subsets within AT3ova tumors at days 10, 17, 21 and 28 post tumor inoculation. Interestingly, A_2AR expression was at its highest point within total CD45⁺ cells at day 10 post-tumor inoculation and gradually decreased over time (Fig. 2I). This effect was largely caused by reduced A_2AR expression within CD8⁺ T cells, whilst the expression of A_2AR in other subsets remained relatively stable. A similar reduction of A_2AR expression in CD8⁺ T cells over time was observed in E0771 tumors, albeit that the time course was shorter than in the AT3ova model due to the more aggressive growth of this tumor line (Supplementary Fig. 2C). These data suggest that early intervention with A_2AR antagonists may be critical for achieving maximum impact on CD8⁺ T cell mediated anti-tumor immunity. Given previous reports indicating a role for A_2AR expression on myeloid cells, we next assessed the expression of A_2AR on myeloid subsets isolated from either AT3ova or E0771 tumors using a panel including antibodies for CD11b, CD11c, F4/80, Ly6C, CD103, XCR1, CD64, and MHCII. These analyses revealed that, amongst all myeloid subsets, A_2AR expression was significantly higher on CD11b⁺ cDC2 cells (defined as Ly6c⁻CD64⁻CD11c⁺MHCII⁺CD103⁻XCR1⁻F4/80^low/dim), relative to all other myeloid cell subsets (Fig. 2J, Supplementary Fig. 2D). Interestingly the GFP⁺ subset of cDC2s exhibited significantly higher expression of MHCII, CD80 and CD86 (Fig. 2K, L, Supplementary Fig. 2D), indicating that this population may represent a more mature subset of cDC2 cells with enhanced capacity to prime T cell responses.

**Fig. 2: A_2AR expression is elevated on tumor-infiltrating T cells and cDC2s.**

A_2AR expression is indicative of CD8⁺ T cell activation status within draining lymph nodes but less so within tumors

Given that A_2AR expression was significantly enhanced on tumor-infiltrating CD8⁺ and CD4⁺ lymphocytes within the tumor microenvironment, we further analyzed the phenotype of A_2AR⁺ T cells relative to their A_2AR^- counterparts. This analysis included the expression of markers associated with differentiation status (CD62L, SLAMF6, CD69, CD44), the immune checkpoint PD-1 and CD39, the ectoenzyme responsible for the breakdown of ATP to AMP. Notably, CD39 is also a recognized marker of tumor-reactive terminally differentiated CD8⁺ T cells and its expression limits anti-tumor immunity^31,32,33. A SIINFEKL-loaded tetramer reagent was also used to identify tumor-antigen (Ova) specific CD8⁺ T cells. We first investigated the expression of A_2AR on tetramer⁺ and tetramer^- subsets. Within tumor-draining lymph nodes A_2AR expression was significantly upregulated on CD44⁺tetramer⁺ CD8⁺ T cells relative to other CD8⁺ T cell subsets (Fig. 3A), consistent with the notion that A_2AR was upregulated following activation of these cells by tumor antigens presented by APCs in the draining lymph nodes. However, within the tumors there was only a modest increase in A_2AR expression on CD62L^- tetramer positive cells relative to CD62L^- tetramer negative counterparts (Fig. 3B, Supplementary Fig. 1G). Within tumors, CD8⁺ T cells follow a pathway of differentiation from TCF7⁺ precursor exhausted cells to TCF7⁻ terminally differentiated cells. Given the technical complexities of TCF7 staining in GFP reporter mice due to quenching of GFP following nuclear permeabilization, we employed the gating strategy described by Beltra et al. using the markers CD69 and SLAMF6 whereby T cells transition from CD69⁺SLAMF6⁺ > CD69⁻SLAMF6⁺ > CD69^-SLAMF6- >CD69⁺, SLAMF6⁻³⁴. Analysis of these distinct subsets indicated that A_2AR was modestly but significantly enriched within the CD69⁺SLAMF6⁺ subset relative to SLAMF6- counterparts (Fig. 3C). Similarly, within E0771 tumor cells it was observed that A_2AR expression was significantly higher on SLAMF6⁺CD39⁻ or SLAMF6⁻CD39⁺ cells relative to SLAMF6⁻CD39⁻ counterparts (Supplementary Fig. 2E). We next investigated whether these differences contributed to the decreased expression of A_2AR observed in CD8⁺ tumor infiltrating lymphocytes over time (Fig. 2I). We observed that in the course of tumor progression that the proportion of both the antigen specific tetramer positive population and the SLAMF6⁺CD69⁺ progenitor population were progressively diminished (Supplementary Fig. 1H). Given that these cell types were the highest expressers of A_2AR this partly accounts for the reduced expression of A_2AR in total CD8⁺ T cells over time. Moreover, on a per cell basis these cell populations elicited significantly higher expression of A_2AR at day 10 than other timepoints but there was no significant difference from day 17 onwards (Supplementary Fig. 1H). Therefore, the reduction in A_2AR expression in CD8⁺ T cells over time is partly explained by a reduced frequency of the tetramer positive and SLAMF6⁺CD69⁺ cells and partly due to reduced expression of A_2AR by these subsets on a per cell basis at later timepoints. To confirm this using a complementary approach we determined the expression of A_2AR following treatment of mice with FTY720. FTY720 acts to block S1PR1 and thus prevent the egress of immune cells from lymph nodes into the tumor site. We reasoned that if A_2AR was expressed more highly on terminally differentiated cells that GFP expression would be increased following FTY720 treatment since this treatment would prevent cells egressing from the draining lymph node and replenishing the SLAMF6⁺CD69⁺ population. FTY720 treatment was effective, as demonstrated by significantly reduced numbers of CD8⁺ and CD4⁺ T cells in the peripheral blood (Supplementary Fig. 1I). Within tumors, FTY720 treatment resulted in a reduction in the proportion of CD69⁺SLAMF6⁺ (less-differentiated population) CD8⁺ T cells and A_2AR expression was significantly reduced (Fig. 3D), supporting our earlier observations that A_2AR expression was not enhanced on more terminally differentiated CD8⁺ T cells.

**Fig. 3: A_2AR expression is elevated on tumor antigen-specific CD8⁺ T cells within draining lymph nodes but not tumors.**

To further investigate this relationship, we determined the expression of A_2AR on PD-1⁺ and CD39⁺ subsets. Somewhat surprisingly and counter to our observations in vitro, A_2AR was expressed equally between PD-1⁺/ PD-1⁻ and CD39⁺/CD39⁻ subsets, whereas PD-1 and CD39 were largely co-expressed. Thus, A_2AR was not co-expressed with other known inhibitory checkpoint receptors on CD8⁺ T cells suggesting that A_2AR blockade may modulate the function of distinct subsets of CD8⁺ T cells (Fig. 3E).

In contrast to CD8⁺ T cells, both CD39 and PD-1 were expressed to a significantly greater extent on CD4⁺A_2AR⁺ cells relative to their A_2AR⁻ counterparts (Fig. 3F). This may reflect an increased expression of A_2AR on Treg cells, which are known to express high levels of CD39 and PD-1 in the tumor microenvironment^35,36,37,38, particularly given CD4⁺GFP⁺CD39⁺ cells were enriched for CD25⁺ cells relative to CD4⁺GFP⁺CD39⁻ counterparts (Fig. 3G). However, this could not be confirmed with Foxp3 counterstaining due to the issues of GFP degradation upon nuclear permeabilization as aforementioned. Taken together, these results suggest that TCR-mediated activation/ differentiation may not be the major factor driving A_2AR expression within the tumor microenvironment on CD8⁺ T cells.

The efficacy of immune checkpoint blockade is correlated with the emergence of PD-1⁺A_2AR^- cells following therapy

Given previous studies indicating that A_2AR blockade enhances the efficacy of conventional immune checkpoint blockade or chemotherapy^5,8,14 and the clinical interest in targeting this pathway, we next assessed the effect of anti-PD-L1, anti-CTLA-4, the combination of anti-PD-L1 and anti-CTLA-4 or carboplatin on the expression of the A_2AR within the tumor microenvironment. As expected, immune checkpoint blockade therapy resulted in significantly reduced tumor weights and an increase in tumor-infiltrating CD8⁺ lymphocytes (Supplementary Fig. 3A, B). Immunofluorescent analyses confirmed that combination (anti-PD-L1 and anti-CTLA-4) therapy resulted in increased numbers of CD45⁺ cells infiltrating the tumors, and this was associated with an increased abundance of GFP⁺ cells (Fig. 4A).

**Fig. 4: PD-L1 blockade results in the emergence of a PD-1⁺A_2AR⁻ subset of CD8⁺ T cells that correlates with therapeutic outcomes.**

In terms of T lymphocyte phenotype, whilst the overall frequency of CD8⁺A_2AR⁺ (but not CD4⁺A_2AR⁺) T cells was increased by therapy due to an increase in the proportion of CD8⁺ T cells as determined by flow cytometry analyses (Fig. 4B), the expression of A_2AR on a per cell basis was not significantly modulated by these treatment regimens at day 7 post-therapy (Fig. 4C). Moreover, carboplatin treatment also failed to modulate A_2AR expression on CD8⁺ or CD4⁺ lymphocytes (Supplementary Fig. 3C). To further interrogate the impact of immune checkpoint blockade on A_2AR expression, and to investigate the possibility that A_2AR was transiently upregulated following treatment, further experiments were performed to determine the expression of GFP on CD8⁺ tumor-infiltrating lymphocytes (TILs) at days 2 and days 4 post-treatment with either anti-PD-L1 or anti-PD-L1 and anti-CTLA-4. Consistent with our analyses at day 7, no significant modulation of A_2AR expression was observed (Supplementary Fig. 3D). Although immune checkpoint blockade did not modulate A_2AR expression on a per cell basis, the expression of PD-1 was increased on CD8⁺ T cells as expected (Supplementary Fig. 3E, F) and further analysis of the activated PD-1⁺ cells that emerged following therapy revealed that anti-PD-L1 or anti-PD-L1 and anti-CTLA-4 treatment induced a significant increase of PD-1⁺A_2AR^- cells (Fig. 4D). Similarly, a significant increase in CD8⁺PD-1⁺A_2AR^- cells (but not PD-1⁺A_2AR⁺ cells) were observed in MC38 tumors following treatment with anti-PD-L1 (Supplementary Fig. 3G). Interestingly, the emergence of these cells was positively correlated with increased therapeutic efficacy in response to anti-PD-L1 single agent therapy (Fig. 4E, F). Lastly, the expression of A_2AR in draining lymph nodes was assessed in the context of therapy. In contrast to the lack of modulation of A_2AR expression within the tumor by anti-PD-L1 therapy, a significant increase in the proportion and absolute number of tetramer⁺A_2AR⁺ CD8⁺ T cells within the draining lymph nodes was observed, suggesting that these cells may be more susceptible to adenosine mediated immunosuppression post-treatment (Fig. 4G).

Finally, given that we observed the expression of A_2AR on myeloid subsets including cDC2s within the tumor microenvironment (Fig. 2J–L), we also assessed the impact of immunotherapy on the expression of A_2AR on myeloid cells. Interestingly, anti-CTLA-4 significantly enhanced the expression of A_2AR on cDC2 and, to a lesser extent, cDC1s, when combined with anti-PD-L1 (Supplementary Fig. 4A, B). CTLA-4 blockade has previously been shown to induce upregulation of CD80 and CD86³⁹ and thus we hypothesized that A_2AR expression may be indicative of an activated cDC2 population. To investigate this, we generated dendritic cells from bone marrow of A_2AR eGFP reporter mice. Consistent with our observations in tumors, a subset of cDC2 were identified to express A_2AR that also exhibited increased expression of CD80 and CD86 (Supplementary Fig. 4C, D). Furthermore, activation of bone marrow derived dendritic cells with poly IC resulted in cDC2 maturation, as evidenced by increased expression of MHCII, CD80 and CD86, which was concomitant with enhanced A_2AR expression (Supplementary Fig. 4C, D). To determine the consequence of adenosine signaling on bone marrow-derived dendritic cell (BMDC) function, they were cocultured with NECA, a pan adenosine receptor agonist, prior to coculture with naïve T cells in a T cell priming assay. These experiments revealed that adenosine signaling resulted in significantly attenuated ability of BMDCs to induce T cell proliferation (Supplementary Fig. 4E).

A_2AR⁺ CD8⁺ TILs exhibit reduced STAT5 transcriptional signatures

To further investigate the phenotype of A_2AR⁺ CD8⁺ T cells within tumors, we performed 3’RNA-sequencing on CD8⁺GFP⁺ and CD8⁺GFP⁻ tumor-infiltrating T cells both at baseline and in the context of anti-PD-L1 treatment. As expected GFP^- and GFP⁺ cells clustered differently as did anti-PD-L1 and non-treated samples (Fig. 5A). Analysis of differentially expressed genes between GFP⁺ and GFP^- cells confirmed that A_2AR was more highly expressed in CD8⁺GFP⁺ cells (Fig. 5B). Pathway analysis of differentially expressed genes revealed significant negative enrichments for “Interferon alpha response”, “Interferon gamma response” and for the expression of STAT5 target genes based on a signature developed by Grange et al.⁴⁰ within A_2AR⁺ cells (Fig. 5C, D, Supplementary Fig. 5). This gene signature included notable effector genes such as Ifng, Tnf, Prf1 and Gzmb. The association between A_2AR⁺ status and reduced STAT5 target genes was of interest because of our previous observations that A_2AR agonists negatively regulate JAK-STAT signaling¹⁶ and a previous report from Cekic and colleagues that IL7R signaling protects CD8⁺ T cells from adenosine mediated-suppression⁴¹. Although Cekic et al. attributed the impact of IL7 signaling on adenosine-mediated suppression to the inactivation of FOXO1, the activation of STAT5 signaling by IL7 represents a possible complementary mechanism of action. Interestingly, treatment with anti-PD-L1 significantly enhanced STAT5 target genes in both A_2AR⁺ and A_2AR^- cells, such that there was no longer a significant difference in the expression of these genes between the two subsets (Fig. 5E). This infers that one consequence of anti-PD-L1 treatment is to overcome reduced STAT5 signaling in A_2AR⁺ CD8⁺ T cells.

**Fig. 5: A_2AR positive CD8⁺ T cells exhibit decreased expression of STAT5 target genes prior to treatment with anti-PD-L1.**

A_2AR is potently upregulated by IL-18 and limits the anti-tumor efficacy of IL-18

We next investigated the capacity of cytokines to upregulate A_2AR expression. Beginning with a broad screen of 23 cytokines on the expression of A_2AR on CD8⁺ T lymphocytes derived from splenocytes, we identified that amongst the most potent inducers of A_2AR expression were members of the IL-1 family of cytokines including IL-1β, IL-18 and IL-36 (Fig. 6A). We proceeded to investigate the impact of the top hits from this in vitro screen on the expression of A_2AR in tumor-infiltrating lymphocytes ex vivo. These results revealed that IL-12 and IL-18 increased the expression of A_2AR on multiple immune lineages including CD8⁺ T cells and NK cells (Fig. 6B, Supplementary Fig. 6A). Given these data and the clinical interest in IL-18 based therapies^42,43, we further investigated the relationship between IL-18 and A_2AR. In repeat experiments we confirmed that IL-18 was a potent inducer of A_2AR expression in both murine T cells (Fig. 6C) and human NK cells (Fig. 6D). To investigate this further we engineered AT3ova and MC38 tumor cells to express IL-18. Despite successful transduction of both cell lines, only MC38 secreted detectable levels of IL-18 (Supplementary Fig. 6B). We therefore evaluated the growth of MC38-IL-18 or MC38 mCherry control tumors and observed a significant reduction in growth of IL-18 expressing tumors (Supplementary Fig. 6C). To investigate the relationship between IL-18 and A_2AR expression in this context we inoculated A_2AR eGFP reporter mice with either IL-18 expressing or control MC38 tumors and assessed the phenotype of tumor-infiltrating lymphocytes. This analysis revealed that CD8⁺ T cells, CD4⁺ T cells and NK cells derived from IL-18 expressing tumors exhibited significantly increased levels of A_2AR expression, whereas we observed no significant increase in PD-1 expression on CD8⁺ T cells (Fig. 6E, F). To evaluate whether A_2AR expression limited the efficacy of IL-18 therapy we inoculated control or IL-18 expressing MC38 cells into A_2AR deficient or wild-type mice. Strikingly, A_2AR deficient mice elicited more pronounced anti-tumor responses with significantly reduced tumor growth and increased survival relative to WT counterparts (Fig. 6G, H; Supplementary Fig. 6D). Depletion experiments revealed that the anti-tumor efficacy of IL-18 was dependent on both CD8⁺ T cells and NK cells (Fig. 6I). Lastly, to evaluate the interplay between IL-18 and A_2AR expression in a more clinically relevant system we determined the impact of recombinant IL-18 treatment on the expression of A_2AR within the context of established MC38 tumors. These experiments revealed that A_2AR expression was significantly increased on CD8⁺ T cells and NK cells following treatment with IL-18 (Fig. 6J). These data highlight the potential of combining IL-18 therapy with A_2AR blocking therapies such as small molecule antagonists and more broadly highlight the utility of this model for establishing rationale combination therapies with therapeutics designed to target the adenosine pathway.

**Fig. 6: IL-18 treatment leads to the upregulation of A_2AR which consequently limits anti-tumor immunity.**

Discussion

Adenosine-mediated immunosuppression is a significant barrier to the formation of effective anti-tumor immune responses. Antibodies targeting the ectoenzymes responsible for the generation of adenosine, CD73 and CD39, and small molecule antagonists of the adenosine receptors A_2AR and A_2BR, have been developed for clinical application^1,44,45. A_2AR can suppress several immune cell types; however, the pattern of expression of A_2AR within the context of an anti-tumor immune response has remained largely unknown due to a lack of robust flow cytometry antibodies. We therefore sought to develop a transgenic model to investigate the pattern of expression of A_2AR in the context of anti-tumor immunity and following therapeutic intervention with either immunotherapy, chemotherapy, or cytokines.

We initially confirmed the veracity of the A_2AR transgenic model through analysis of A_2AR mRNA expression in GFP⁺ and GFP⁻ cells. Moreover, in line with our expectations, analysis of splenocytes from these mice revealed that GFP (A_2AR) was abundantly expressed in cell types known to express high levels of A_2AR such as NK cells²⁴ and NKT cells²⁶ but was not expressed in B cells. Furthermore, GFP was strongly upregulated following T cell activation through the TCR or a CAR, in line with previous observations with A_2AR mRNA. We therefore proceeded to investigate the expression of A_2AR in the context of tumor-bearing mice. Consistent with our observations using splenocytes, A_2AR was highly expressed on all innate-like subsets evaluated including NK cells, NKT cells and γδ T cells. Tumor-infiltrating CD8⁺ and CD4⁺ T cells also expressed high levels of A_2AR and notably this expression was significantly higher than observed with CD8⁺ or CD4⁺ T cells isolated from spleen or draining lymph nodes. We originally hypothesized that this may relate to the activation status of the T cells given that TCR activation is known to drive expression of A_2AR and indeed this is what we observed using the A_2AR eGFP reporter mice in vitro. Whilst antigen (ova)-specific CD8⁺ T cells expressed significantly higher levels of A_2AR than non-ova-specific CD8⁺ T cells in draining lymph nodes, this difference was more modest within tumors. Moreover, within tumors A_2AR expression was similar between PD-1⁺ and PD-1⁻ subsets and CD39⁺ and CD39^- subsets, suggesting that within tumors the activation status of the CD8⁺ T cells is not a major predictor of A_2AR expression. Therefore, whilst TCR activation appears to be a major driver of A_2AR expression in CD8⁺ T cells within draining lymph nodes other factors appear to govern the expression of A_2AR within tumors. Characterization of CD8⁺ T cells by differentiation status revealed that A_2AR expression was modestly but significantly higher within the CD69⁺SLAMF6⁺ precursor exhausted subset. This is intriguing given previous studies have indicated that A_2AR signaling is required for the maintenance of naïve cells, partly due to its ability to upregulate IL-7R expression^16,29,46,47. Whether A_2AR signaling is required for the maintenance and/or expansion of CD69⁺SLAMF6⁺ precursor exhausted CD8⁺ T cells within tumors remains to be determined but is one potential mechanism by which A_2AR signaling may actually promote a favorable differentiation status for responses to immune checkpoint blockade in some contexts. It will be interesting in follow-up studies to investigate factors that may influence A_2AR expression such as hypoxia and other local immunosuppressive metabolites found at high concentrations within tumors⁴⁸. For example, systemic oxygenation has been shown to decrease expression of CD73, A_2AR and A_2BR and improve anti-tumor immunity although the cell types that reduced A_2AR expression under these conditions could not be determined in these studies as the determination was based upon mRNA analysis of bulk tumor tissue^6,49. Amongst CD4⁺ T cells, A_2AR expression was highly abundant on CD39⁺PD-1⁺ cells, potentially indicative of Treg cells that are known to express these immune checkpoints at high levels within tumors. However, this could not be definitively confirmed due to an inability to counterstain with a Foxp3-directed antibody due to loss of GFP signal upon nuclear permeabilization. Future studies may confirm this by FACS sorting GFP⁺ and GFP^- cells and then performing analysis of transcription factor expression in each population.

One interesting observation from these analyses is that a subset of cDC2 cells was identified that expressed A_2AR. These cells exhibited higher expression of MHCII, CD80 and CD86 relative to GFP^- counterparts, indicating that they may represent an activated subset of cDC2. Indeed, consistent with this, we observed that activation of cDC2s in vitro with poly IC led to a significant increase in A_2AR expression and in vivo, treatment with immune checkpoint blockade, particularly anti-CTLA-4, led to a significant increase in A_2AR expression on cDC2s. Expression of A_2AR and A_2BR on dendritic cells has been reported previously⁵⁰ and blockade of A_2BR or CD73^9,51 or myeloid-specific deletion of A_2AR or A_2BR has been shown to enhance anti-tumor immunity^27,52 in part through modulation of DC function⁵³. More recently, it was shown that a component of the mechanism of action for the small molecule A_2AR antagonist AZD4635 was enhancement of cDC1 function⁵⁴. To our knowledge the expression of A_2AR on cDC2 cells has not been previously reported. Interestingly we observed that A_2AR expression was largely restricted to a subset of cDC2 with increased expression of MHCII, CD80 and CD86 that was increased upon treatment with anti-CTLA-4. A_2AR may therefore represent a negative feedback loop that limits the costimulatory capacity of activated cDC2s. cDC2s have been shown to be critical in priming intratumoral CD4⁺ T cell responses and so it is interesting to postulate that A_2AR expression on these cells may consequently limit the formation of these protective responses³⁹. In this study by Binnewies et al. it was shown that Tregs limit the activation and differentiation of cDC2s, which may be linked to the activation and increased expression of A_2AR observed in our study following anti-CTLA-4 blockade given we used the 9H10 clone that is known to induce Treg depletion. Therefore, in future studies, it would be of interest to isolate A_2AR⁺ and A_2AR^- cDC2s and compare their functional capacity to prime CD8⁺ and CD4⁺ T cell responses ex vivo.

Although we observed increases in A_2AR expression in cDC2s and, to a lesser extent, cDC1s following immune checkpoint blockade, it was somewhat surprising that we did not observe increases in A_2AR expression within tumor-infiltrating T cells following PD-L1 blockade or treatment with anti-CTLA-4 and anti-PD-L1. Previously, an assessment of A_2AR mRNA following PD-1 blockade revealed an approximately 2-3 fold increase in A_2AR expression within tumor-infiltrating CD8⁺ T cells⁸. However, we did not observe this in our current study using the A_2AR eGFP reporter mice. The reasons for these differences are not clear but may be related to differences in kinetics in the two studies, the use of anti-PD-L1 as opposed to anti-PD-1 or a true difference between mRNA and protein. Nevertheless, we did observe an increase in A_2AR expression within CD8⁺ T cells isolated from the draining lymph nodes of mice undergoing immune checkpoint blockade, highlighting the potential for A_2AR blockade to enhance T cell priming in tertiary lymphoid structures beyond the tumor microenvironment in the context of immunotherapy. Moreover, it is likely that both immune checkpoint blockade and chemotherapy result in increased levels of extracellular adenosine due to the destruction of tumor cells, which in itself may make targeting the adenosine pathway therapeutically more relevant in this context. Interestingly, in the context of immune checkpoint blockade we observed that therapeutic efficacy of anti-PD-L1 was associated with the emergence of a PD-1⁺ A_2AR^- subset that may represent a biomarker for response.

Assessment of the transcriptional profile of A_2AR⁺ and A_2AR⁻ CD8⁺ T cells revealed that A_2AR⁺ cells elicited a reduced expression of a defined set of STAT5 target genes⁴⁰. This is consistent with previous observations we have made with CD8⁺ T cells treated in vitro with the adenosine mimetic NECA¹⁶. This may be linked to the observation that IL-2 and IL-7, cytokines that signal through STAT5, can overcome adenosine-mediated suppression^41,55. Interestingly, we observed that PD-L1 blockade resulted in increased expression of STAT5 target genes within both A_2AR⁺ and A_2AR⁻ subsets, suggesting that this may help CD8⁺ T cells to overcome adenosine-mediated suppression through upregulation of this pathway.

Lastly, to utilize this model to identify rational combination therapies we interrogated the impact of various cytokines on A_2AR expression as there is remarkably little known about the control of A_2AR expression in this regard. Our analysis identified the IL1 family of cytokines, and particularly IL-18, as a potent inducer of A_2AR expression on CD8⁺ T cells, NK cells, γδT cells and NKT cells. Given that IL-18 is known to induce anti-tumor immunity, but based upon these data may also concomitantly increase A_2AR expression, we hypothesized that suppression mediated by A_2AR signaling may limit the overall therapeutic effect of IL-18. We therefore evaluated the potential of combining IL-18 therapy with A_2AR blockade through engineering tumor cells to secrete IL-18. These experiments confirmed that IL-18 was a strong inducer of A_2AR expression in vivo, and anti-tumor effects were even greater in A_2AR knockout mice, highlighting the potential for combination therapy targeting the A_2AR in conjunction with IL-18 therapy. There has been significant work in developing a form of IL-18 suitable for clinical application, including the development of a form of IL-18 that does not bind to IL-18DR and therefore elicits greater anti-tumor potency than wild-type IL-18⁴². It would therefore be of significant interest to interrogate a possible combination strategy utilizing these such reagents and A_2AR antagonists that are currently under clinical evaluation.

Methods

This research and all study protocols have been approved and comply with the Peter MacCallum Animal Experimental Ethics Committee (AEEC) ethical regulations regarding the use of animals. Studies utilizing human PBMCs from healthy donors was approved by the Peter MacCallum Cancer Centre Human Research Ethics committee. Informed consent was obtained from the Australian Red Cross.

Animal models and tumor models

A_2AR eGFP reporter mice (Tg(Adora2a-EGFP)EP141Gsat) were obtained from The Jackson Laboratory repository and backcrossed onto a C57BL/6 background. The transgene for these mice is the cDNA of EGFP, followed by a polyadenylation signal, inserted into the mouse genomic bacterial artificial chromosome (BAC) RP24-238K3. This insertion is at the start codon of the Adora2a gene so that expression of the reporter mRNA is controlled by the regulatory sequences of Adora2a. C57BL/6 wildtype mice were purchased from Australian Bioresources (Moss Vale, New South Wales) or bred in house at the Peter MacCallum Cancer Centre. C57BL/6 A_2AR eGFP reporter mice or A_2AR^-/- mice were bred in house at the Peter MacCallum Cancer Centre. Mice used in experiments were between 6 to 16 weeks of age and experiments were approved by the Animal Experimentation Ethics Committee #E672. AT3 tumor cells were obtained from Dr. Trina Stewart and engineered to express chicken ovalbumin as described previously⁸. MC38 tumor cells were obtained from Dr. Nicole Haynes. All studies using the breast cancer cell lines AT3ova or E0771 were performed in female mice. Experiments with MC38 tumors were performed in male mice unless specified in the source data file. AT3-Her2, E0771-Her2 and MC38-Her2 were generated as previously described¹⁶. Tumor lines were verified to be Mycoplasma negative by PCR analysis and were actively passaged for less than 6 months. Tumor cells were grown in DMEM supplemented with 10% FCS, Glutamax, and penicillin/streptomycin. For in vivo experiments, the indicated number of cells were resuspended in PBS and injected subcutaneously (100 μL). Tumors were measured using callipers and calculated as mm2 (width*length). Tumor size did not exceed the maximal size approved by the AEEC ethics committee of 150 mm². To engineer AT3ova and MC38 cells to express IL-18, IL-18 cDNA (ATGAACTTTGGCCGACTTCACTGTACAACCGCAGTAATACGGAATATAAATGACCAAGTTCTCTTCGTTGACAAAAGACAGCCTGTGTTCGAGGATATGACTGATATTGATCAAAGTGCCAGTGAACCCCAGACCAGACTGATAATATACATGTACAAAGACAGTGAAGTAAGAGGACTGGCTGTGACCCTCTCTGTGAAGGATAGTAAAATGTCTACCCTCTCCTGTAAGAACAAGATCATTTCCTTTGAGGAAATGGATCCACCTGAAAATATTGATGATATACAAAGTGATCTCATATTCTTTCAGAAACGTGTTCCAGGACACAACAAGATGGAGTTTGAATCTTCACTGTATGAAGGACACTTTCTTGCTTGCCAAAAGGAAGATGATGCTTTCAAACTCATTCTGAAAAAAAAGGATGAAAATGGGGATAAATCTGTAATGTTCACTCTCACTAACTTACATCAAAGTTAG) was cloned into the MSCV Cherry vector and retrovirus generated from HEK293gp cells prior to transduction of target cells. mCherry⁺ cells were FACS sorted prior to functional experiments.

Antibodies, pharmacological agents, and cytokines

Isotype control (2A3, catalogue number BE0089), anti-PD-L1 (clone 10 F.9G2, catalogue number BE0101) and anti-CTLA-4 (9H10, catalogue number BE0131) were purchased from BioXcell. Mice were treated every 4 days for up to 2 doses. Where indicated mice were treated at days 14, 16, 18 and 20 post-tumor inoculation with 25 µg FTY720 (Sigma). Anti-asialo GM-1 (catalogue number 986-10001, FUJIFILM Wako Pure Chemical Corporation) and anti-CD8α (clone YTS 169.4, catalogue number BE0117, BioXcell) were used for in vivo NK cell and CD8⁺ T cell depletion, respectively. Anti-CD3 (clone 145-2C11) and anti-CD28 (clone 37.51) used to stimulate murine T cells were obtained from BD Pharmingen. Cytokines used for the stimulation of murine or Human immune cells were purchased from Biolegend.

Immunofluorescence analysis

A_2AR eGFP mice were subcutaneously engrafted with 5×10⁵ AT3-ova tumor cells. Mice were treated with anti-PD-L1 (clone B7-H1) and anti-CTLA-4 (clone 9H10) on days 14 and 18 post-tumor inoculation. Tumors and spleens harvested on Day 20 were fixed with 4% paraformaldehyde (PFA) for 3 hours at 4°C, followed by an overnight incubation in a 30% sucrose PBS solution. Tissues were then embedded in O.C.T compound (Scigen) in cryomolds, stored at -80°C, and serially sectioned at 12μm per tissue slide.

Slides were dried at room temperature and fixed for 5 min in ice-cold acetone. Tissues were blocked with 0.2% bovine serum albumin (BSA) for 5 min and incubated overnight at 4°C with fluorophore-conjugated antibodies prepared at 1:200 dilution in BSA: αCD45.2 AF647 Biolegend, clone: 104, CAT:109818) and αGFP AF488 (Invitrogen, REF: A21311)]. The following day, slides were washed twice in PBS for 5 minutes each at room temperature and were coverslipped with ProLong Gold Antifade mounting medium.

Images were acquired with an Olympus DP80 camera on an Olympus BX53 microscope using the cellSens Dimension program. Images were analyzed with ImageJ.

Flow cytometry analysis of immune cells ex vivo

The tumors and draining lymph nodes of mice were isolated at the indicated timepoint post-tumor inoculation. Tumors were digested with collagenase type IV (Sigma-Aldrich) and 0.02 mg/ml DNAase (Sigma-Aldrich) for 30 minutes at 37 °C. Cells were then passed through a 70 µm filter twice. Cells were then incubated in Fc Block (supernatant from 2.4G2 hybridoma) and then stained with indicated flow cytometry antibodies and Fixable Yellow (Thermo Fischer Scientific) as a viability dye. αGal Cer loaded tetramer used for the identification of NKT cells was obtained from Dr. Hui-Fern Koay and Prof. Dale Godfrey. Flow cytometry antibodies used in the study are listed in Supplementary Table 1.

Human NK cell purification from PBMCs

Peripheral blood mononuclear cells (PBMCs) were obtained by performing a Ficoll separation on human donor blood (Source: Australian Red Cross LifeBlood). Red blood cells were lysed with ACK lysis buffer (8.29 g NH2Cl, 1 g KHC3, 0.04 g Na2 EDTA in 1 L sterile MqH₂0 filtered through a 22 μM Stericup vacuum filter (Merck)). NK cells were subsequently washed with PBS and purified using an NK isolation kit (Human NK Cell Isolation Kit, LS Columns, Miltenyi Biotec) as per the manufacturer’s instructions. Purified NK cells were washed with PBS and resuspended in culture media (RPMI media + 10% FBS, Sodium pyruvate, NEAA, Glutamax, HEPES, Penicillin/Streptomycin) prior to assay setup.

Cytokine stimulation assay

Cytokine stimulation assays were performed in 96 well plates. 1 × 10⁵ NKs were plated in RPMI media (as above). Human IL-18 (50 ng/ml) (R&D systems) and 20 IU/ml IL-2 (NIH) were added to NK cells and plates incubated at 37 °C. NK cells were then spun down at 1400 rpm for 4 min and cell pellets frozen in RLT buffer (Qiagen RNEasy kit) + 10 µl/ml 2-Mercaptoethanol (BME) and stored at −80°C.

Quantitative real-time PCR analysis

RNA was isolated using an RNeasy Mini kit (Qiagen) following which cDNA was generated using m-MLV reverse transcriptase (Promega). qRT-PCR was then performed using murine or Human A_2AR mRNA probes (Taqman; Hs00169123_m1) as per the manufacturer’s instructions with GAPDH (Taqman; Hs02786624_g1) used as a housekeeping gene. For murine cells, L32 was used as a housekeeping gene as per previous work⁸.

Generation of anti-Her2 CAR T cells

Murine splenocytes were activated with anti-CD3/ anti-CD28 before transduction with supernatants derived from a GP + E86 anti-Her2 CAR packaging line as previously described¹⁶. Briefly, supernatants were added to retronectin (10 µg/ml Takara Bio) coated 6 well plates and spun at 1200 g for 30 minutes. Subsequently 1 ml T cells were added to each well to give a final volume of 10e6 T cells per well. The cells were then spun at the same speed for 90 minutes. This process was repeated 24 h later and after transduction, CAR T cells were maintained in IL-2 and IL-7 prior to coculture with tumor cells at day 6–7 post-activation.

Gene expression analysis

Using the Quant-seq 3′ mRNA-seq Library Prep Kit from Illumina (Lexogen), RNA-seq libraries were prepared from RNA extracted from sorted cells. 75 bp Single-end RNA-sequencing was then performed using NextSeq (Illumina, Inc., San Diego, CA) and base calling was performed using CASAVA 1.8.2. Random primer bias removal and 3’ poly-A-tail trimming was performed using Cutadapt v2.1 to derived raw sequences. Quality control was assessed using FastQC v0.11.6 and RNA-SeQC v1.1.8⁵⁶. Next, sequence alignment against the mouse reference genome mm10 was performed using HISAT2. FeatureCounts (Rsubread v2.10.5) was used to count raw reads and genes were then annotated from the Ensembl releases⁵⁷. Normalization of gene counts was performed using the using the EdgeR package^58,59 and the TMM (trimmed means of M-values) method into log2 counts per million (CPM). The quasi-likelihood F test statistical test method based on the generalized linear model (glm) framework was used for differential gene expression (DEGs) comparisons. Adjusted p values were computed using the Benjamini-Hochberg method. Principal component analysis (PCA) was performed generated based on the topmost variable genes. DEGs were classified as significant based on a false discovery rate (FDR) cutoff of less than 0.05. For heatmaps, the pheatmap R package was used to plot row mean centered and scaled normalized log2(CPM + 0.5) values. Genes, columns or rows were sorted by hierarchical clustering using Euclidean distance and average-linkage.

Unbiased gene set enrichment analysis (GSEA) using the fgsea package was performed on fold change ranked DEGs with 1000 permutations (nominal P-value cutoff <0.05). Reference gene sets were obtained from the Hallmarks dataset from the MsigDB library or previously published analyses of a STAT5 signature (GEO:GSE41819).

Statistical analysis

Statistical analyses were performed with one-way ANOVA, two-way ANOVA or unpaired t test where appropriate as indicated in the figure legend. P < 0.05 was considered significant. For survival curve analysis, mice that developed ulcerated tumors prior to the 100 mm² point were censored from the analysis

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The RNA-sequencing data used in the study have been deposited in the Gene Expression Omnibus under the accession code GSE230135 available at. The remaining data are available within the Article, Supplementary Information or Source Data file. Source data are provided with this paper.

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Acknowledgements

The authors would like to acknowledge Prof. Dale Godfrey who provide access to the αGal-Cer tetramer used in the study. This work was funded by a Program Grant from the National Health and Medical Research Council (NHMRC; Grant number 1132373). P.A.B. was supported by a National Breast Cancer Foundation Fellowship (ID# ECF-17-005, 2017-2020) and a Victorian Cancer Agency Mid-Career Fellowship (2021-Current). I.G. House was supported by a Victorian Cancer Agency Early Career Fellowship (ECRF20017). P.K.D. was supported by an NHMRC Senior Research Fellowship (APP1136680). Junyun Lai was a recipient of a US Cancer Research Institute Irvington postdoctoral fellowship (award no. 3530). The authors wish to acknowledge the contributions of Ms Karen Gill, Mr Mike Rear and Mr Graeme Sissing who act as consumer representatives for the laboratory.

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These authors contributed equally: Kirsten L. Todd, Junyun Lai.

Authors and Affiliations

Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, 3000, VIC, Australia
Kirsten L. Todd, Junyun Lai, Kevin Sek, Yu-Kuan Huang, Emily B. Derrick, Dat Nguyen, Thang X. Hoang, Emma V. Petley, Cheok Weng Chan, Isabelle Munoz, Imran G. House, Joel N. Lee, Joelle S. Kim, Jasmine Li, Junming Tong, Maria N. de Menezes, Christina M. Scheffler, Kah Min Yap, Amanda X. Y. Chen, Phoebe A. Dunbar, Brandon Haugen, Ian A. Parish, Phillip K. Darcy & Paul A. Beavis
Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, 3010, Australia
Kirsten L. Todd, Junyun Lai, Kevin Sek, Yu-Kuan Huang, Dane M. Newman, Emily B. Derrick, Dat Nguyen, Thang X. Hoang, Emma V. Petley, Cheok Weng Chan, Isabelle Munoz, Imran G. House, Joel N. Lee, Joelle S. Kim, Jasmine Li, Junming Tong, Maria N. de Menezes, Christina M. Scheffler, Kah Min Yap, Amanda X. Y. Chen, Phoebe A. Dunbar, Brandon Haugen, Ian A. Parish, Ricky W. Johnstone, Phillip K. Darcy & Paul A. Beavis
Translational Hematology Program, Peter MacCallum Cancer Centre, Melbourne, Australia
Dane M. Newman & Ricky W. Johnstone
Department of Microbiology & Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia
Hui-Fern Koay
Australian Research Council Centre of Excellence in Advanced Molecular Imaging, University of Melbourne, Melbourne, VIC, Australia
Hui-Fern Koay
Department of Immunology, Monash University, Clayton, Australia
Phillip K. Darcy

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Kirsten L. Todd
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Junyun Lai
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Kevin Sek
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Yu-Kuan Huang
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Dane M. Newman
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Emily B. Derrick
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Hui-Fern Koay
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Dat Nguyen
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Thang X. Hoang
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Emma V. Petley
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Cheok Weng Chan
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Isabelle Munoz
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Imran G. House
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Jasmine Li
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Junming Tong
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Maria N. de Menezes
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Christina M. Scheffler
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Amanda X. Y. Chen
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Phoebe A. Dunbar
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Ian A. Parish
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Ricky W. Johnstone
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Paul A. Beavis
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Contributions

K.L.T. designed and performed the majority of experiments, analyzed the data and wrote the manuscript. J.Lai, Y.K.H., D.M.N., E.B.D., D.N., and C.W.C. designed and performed experiments. K.S. analyzed data and generated scripts for RNA-sequencing analysis. H.F.K. provided reagents. K.S., T.X.H., E.V.P., I.M., I.G.H., J.N.L., J.S.K., J.Li, J.T., M.N.D.M., C.M.S., K.M.Y., A.X.Y.C., P.A.D. and B.H. assisted in the generation of data. I.A.P., R.W.J., and P.K.D. supervised aspects of the study. P.A.B. conceptualized and led the study, designed and performed experiments, analyzed the data and wrote the manuscript.

Corresponding authors

Correspondence to Kirsten L. Todd or Paul A. Beavis.

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Competing interests

P.A.B. declares the following conflicts: research funding from AstraZeneca, Bioardis, Bristol-Myers-Squibb and Gilead Sciences. P.K.D. declares the following conflicts: research funding from Myeloid Therapeutics, Prescient Therapeutics, Bristol-Myers-Squibb and Juno Therapeutics. I.A.P. declares the following conflicts: research funding from Bristol-Myers-Squibb and Astrazeneca. The Johnstone Lab receives research support from Roche, BMS, AstraZeneca and MecRx. R.W.J. is a scientific consultant and shareholder in MecRx. The remaining authors declare no competing interests.

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Todd, K.L., Lai, J., Sek, K. et al. A_2AR eGFP reporter mouse enables elucidation of A_2AR expression dynamics during anti-tumor immune responses. Nat Commun 14, 6990 (2023). https://doi.org/10.1038/s41467-023-42734-0

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Received: 11 April 2023
Accepted: 20 October 2023
Published: 01 November 2023
DOI: https://doi.org/10.1038/s41467-023-42734-0

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