Title: Reprogramming immunosuppressive myeloid cells facilitates immunotherapy for colorectal cancer
Abstract: Article7 December 2020Open Access Source Data Reprogramming immunosuppressive myeloid cells facilitates immunotherapy for colorectal cancer Weiqiang Lu Corresponding Author [email protected] orcid.org/0000-0003-1349-6597 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, ChinaThese authors contributed equally to this work. Search for more papers by this author Weiwei Yu Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, ChinaThese authors contributed equally to this work. Search for more papers by this author Jiacheng He Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Wenjuan Liu Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Junjie Yang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Xianhua Lin Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Yuanjin Zhang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Xin Wang orcid.org/0000-0001-8079-8638 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Wenhao Jiang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Jian Luo Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Qiansen Zhang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Huaiyu Yang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Shihong Peng Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Zhengfang Yi Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Shancheng Ren Department of Urology, Changhai Hospital, Second Military University, Shanghai, China Search for more papers by this author Jing Chen School of Basic Medical Sciences, Ningxia Medical University, Yinchuan, China Search for more papers by this author Stefan Siwko Department of Molecular and Cellular Medicine, Institute of Biosciences and Technology, Texas A&M University Health Science Center, Houston, TX, USA Search for more papers by this author Ruth Nussinov Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research Sponsored by the National Cancer Institute, Frederick, MD, USA Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel Search for more papers by this author Feixiong Cheng Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA Search for more papers by this author Hankun Zhang Corresponding Author [email protected] orcid.org/0000-0002-5008-0825 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Mingyao Liu Corresponding Author [email protected] orcid.org/0000-0001-7339-5048 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Weiqiang Lu Corresponding Author [email protected] orcid.org/0000-0003-1349-6597 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, ChinaThese authors contributed equally to this work. Search for more papers by this author Weiwei Yu Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, ChinaThese authors contributed equally to this work. Search for more papers by this author Jiacheng He Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Wenjuan Liu Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Junjie Yang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Xianhua Lin Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Yuanjin Zhang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Xin Wang orcid.org/0000-0001-8079-8638 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Wenhao Jiang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Jian Luo Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Qiansen Zhang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Huaiyu Yang Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Shihong Peng Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Zhengfang Yi Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Shancheng Ren Department of Urology, Changhai Hospital, Second Military University, Shanghai, China Search for more papers by this author Jing Chen School of Basic Medical Sciences, Ningxia Medical University, Yinchuan, China Search for more papers by this author Stefan Siwko Department of Molecular and Cellular Medicine, Institute of Biosciences and Technology, Texas A&M University Health Science Center, Houston, TX, USA Search for more papers by this author Ruth Nussinov Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research Sponsored by the National Cancer Institute, Frederick, MD, USA Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel Search for more papers by this author Feixiong Cheng Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA Search for more papers by this author Hankun Zhang Corresponding Author [email protected] orcid.org/0000-0002-5008-0825 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Mingyao Liu Corresponding Author [email protected] orcid.org/0000-0001-7339-5048 Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China Search for more papers by this author Author Information Weiqiang Lu *,1, Weiwei Yu1, Jiacheng He1, Wenjuan Liu1, Junjie Yang1, Xianhua Lin1, Yuanjin Zhang1, Xin Wang1, Wenhao Jiang1, Jian Luo1, Qiansen Zhang1, Huaiyu Yang1, Shihong Peng1, Zhengfang Yi1, Shancheng Ren2, Jing Chen3, Stefan Siwko4, Ruth Nussinov5,6, Feixiong Cheng7,8,9, Hankun Zhang *,1 and Mingyao Liu *,1 1Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China 2Department of Urology, Changhai Hospital, Second Military University, Shanghai, China 3School of Basic Medical Sciences, Ningxia Medical University, Yinchuan, China 4Department of Molecular and Cellular Medicine, Institute of Biosciences and Technology, Texas A&M University Health Science Center, Houston, TX, USA 5Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research Sponsored by the National Cancer Institute, Frederick, MD, USA 6Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel 7Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA 8Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA 9Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA *Corresponding author. Tel: +86 21 24206642; E-mail: [email protected] *Corresponding author. Tel: +86 21 24206642; E-mail: [email protected] *Corresponding author. Tel: +86 21 24206642; E-mail: [email protected] EMBO Mol Med (2021)13:e12798https://doi.org/10.15252/emmm.202012798 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Immune checkpoint blockade (ICB) has a limited effect on colorectal cancer, underlining the requirement of co-targeting the complementary mechanisms. Here, we identified prostaglandin E2 (PGE2) receptor 4 (EP4) as the master regulator of immunosuppressive myeloid cells (IMCs), which are the major driver of resistance to ICB therapy. PGE2-bound EP4 promotes the differentiation of immunosuppressive M2 macrophages and myeloid-derived suppressor cells (MDSCs) and reduces the expansion of immunostimulated M1 macrophages. To explore the immunotherapeutic role of EP4 signaling, we developed a novel and selective EP4 antagonist TP-16. TP-16 effectively blocked the function of IMCs and enhanced cytotoxic T-cell-mediated tumor elimination in vivo. Cell co-culture experiments revealed that TP-16 promoted T-cell proliferation, which was impaired by tumor-derived CD11b+ myeloid cells. Notably, TP-16 and anti-PD-1 combination therapy significantly impeded tumor progression and prolonged mice survival. We further demonstrated that TP-16 increased responsiveness to anti-PD-1 therapy in an IMC-related spontaneous colorectal cancer mouse model. In summary, this study demonstrates that inhibition of EP4-expressing IMCs may offer a potential strategy for enhancing the efficacy of immunotherapy for colorectal cancer. Synopsis Immunosuppressive myeloid cells (IMCs) are a prominent driver of immunotherapy resistance in colorectal cancer. This study identifies EP4 as a master regulator of IMCs and highlights blockade of EP4 as a novel therapeutic strategy for enhancing immunotherapy in colorectal cancer. EP4 was identified as the main receptor of PGE2 enhancing the differentiation and expansion of immunosuppressive macrophages and MDSC. A novel EP4 antagonist, TP-16, was designed and synthesized with high potency and selectivity, as well as favorable drug-like properties. TP-16 alone or in combination with PD-1 antibody suppressed tumor growth in syngeneic mouse models and in the AOM/DSS-induced colorectal cancer model. TP-16-induced EP4 inhibition boosted T cell-mediated anti-tumor immunity through targeting of the IMCs-mediated immunosuppression in the tumor microenvironment. The paper explained Problem Immune checkpoint blockade (ICB) has emerged as the standard therapy in patients with refractory cancers owing to its unprecedented and durable responses. However, ICB activity is lost in colorectal cancer, especially in the microsatellite-stable population. Increasing evidence has indicated that immunosuppressive myeloid cells (IMCs) are a prominent driver of immunotherapy resistance in colorectal cancer. Given the plasticity and complexity of IMCs in the tumor microenvironment, novel strategies are required to target these tumor-associated myeloid cells and to enhance cancer treatment efficacy. Results We identified prostaglandin E2 receptor 4 (EP4) as the master regulator of PGE2 in IMCs. PGE2-bound EP4 promoted the differentiation of immunosuppressive M2 macrophages and myeloid-derived suppressor cells (MDSCs) and reduced the expansion of immunostimulated M1 macrophages. Treatment with TP-16, a novel EP4 antagonist, blocked the function of IMCs (M2 macrophages and MDSCs) and enhanced cytotoxic T-cell-mediated colorectal cancer elimination in vivo. Cell co-culture experiments revealed that TP-16 promoted the proliferation of T cells, which was impaired by tumor-derived CD11b + myeloid cells. Notably, the combination therapy of TP-16 and anti-PD-1 antibody significantly hampered tumor progression and prolonged survival in syngeneic mouse models. Finally, TP-16 increased responsiveness to anti-PD-1 therapy in an azoxymethane/dextran sodium sulfate (AOM/DSS) model, an IMC-related colorectal cancer mouse model. Impact These observations suggest that PGE2-bound EP4 promotes the immunosuppressive activity of IMCs. Chemical inhibition of EP4 by TP-16 induces a functional switch in myeloid cells from immunosuppression to immunostimulation and enhanced cytotoxic T-cell activation. TP-16 acts synergistically with anti-PD-1 therapy in colorectal cancer mouse models, offering a potential approach for improving the efficacy of checkpoint-based immunotherapies in colorectal cancer patients. Introduction Colorectal cancer has a high incidence and mortality rate (Siegel et al, 2019). In 2018, more than 1.8 million new cases and 881,000 deaths were reported worldwide (Bray et al, 2018). Approximately 20% of patients have distant metastatic disease at initial diagnosis, and half of the patients develop metastases during disease progression (Chiappa et al, 2009). The prognosis for patients with distant-stage disease is dismal, with a 5-year relative survival rate of only 14% (Siegel et al, 2020). Therefore, the development of innovative treatments is an urgent requirement to improve the clinical benefit for patients with advanced or metastatic colorectal cancer. Immune checkpoint blockade (ICB) has emerged as the standard therapy for many cancers due to its unprecedented and durable responses in patients with refractory cancers (Hoos, 2016; Ganesh et al, 2019). For instance, anti-CTLA4 antibody was approved for metastatic melanoma, and anti-PD-(L)1 antibodies were approved for a wide range of cancer types, such as melanoma, lung cancer, and renal carcinoma (Topalian et al, 2015; Patel & Minn, 2018). The potential benefits of ICB have been reported in approximately 15% of colorectal cancer patients with defective mismatch repair (microsatellite instability–high, MSI-H). However, the activity is lost in the microsatellite-stable (MSS) population, representing the majority of colorectal cancer patients (Pitt et al, 2016; Overman et al, 2018). Increasing evidence has indicated that immunosuppressive myeloid cells (IMCs) are a prominent driver of immunotherapy resistance in colorectal cancer (Le et al, 2017; Liao et al, 2019). IMCs mainly comprise tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs) (Gabrilovich et al, 2012). TAMs accumulation is associated with poor prognosis and is a potential diagnostic biomarker for treatment stratification (Steidl et al, 2010; Lu-Emerson et al, 2013). A high frequency of MDSCs is generally associated with poor disease progression and therapy resistance in colorectal cancer (Solito et al, 2011; Marvel & Gabrilovich, 2015; Kumar et al, 2016). Thus, abrogating IMC-mediated adaptive immune response deficiency would offer a potential strategy for tumor immunotherapy. Prostaglandin E2 (PGE2), a bioactive lipid with pro-tumor activity, acts through several mechanisms in colorectal cancer (Obermajer & Kalinski, 2012; Luan et al, 2015; Martinez-Colon & Moore, 2018). IMCs have been reported as the dominant target cells affected by PGE2 through cognate G-protein coupled receptors (GPCRs), such as E-type prostanoid receptors 1-4 (EP1-4) (Wu et al, 2019). Among these receptors, EP4 is highly expressed in IMCs and plays an important role in the differentiation of TAMs and MDSCs in the tumor microenvironment (Sinha et al, 2007; Sugimoto & Narumiya, 2007). However, the immunotherapeutic effect of targeting EP4-expressing IMCs in colorectal cancer remains elusive. In this study, we found that PGE2-bound EP4 induces a functional switch in myeloid cells from immunostimulation to immunosuppression. Chemical inhibition of EP4 by the new EP4 antagonist, TP-16, significantly reprograms IMCs and enhances cytotoxic T-cell activation. TP-16 acts synergistically with anti-PD-1 therapy in colorectal cancer mouse models, offering a potential approach for improving the efficacy of checkpoint-based immunotherapies. Results EP4 is the master regulator of IMCs EP1-4 constitutes a subfamily of cell surface receptors of the immunosuppressive molecule, PGE2. We performed bioinformatic analyses and found that in the myeloid cells of primary bone marrow (BM), the expression of EP2 and EP4 was abundant, whereas the expression of EP1 and EP3 was minimal (Fig 1A). Among EP1-4, EP4 was significantly up-regulated (P = 0.015) in colon tumor myeloid cells compared to BM myeloid cells (Fig 1A) (Yang et al, 2011). Accordingly, in a CT26 tumor-bearing mouse model, the expression level of EP4 was higher than those of EP1–3 in CD11b+ myeloid cells isolated from tumor tissues and the spleen (Fig 1B). Figure 1. EP4 is a master regulator of IMCs The expression of EP subtypes in bone marrow myeloid cells and colon tumor myeloid cells. The short black lines indicate individual expressions, and the blue and yellow lines indicate the average expression level in each condition. The gray dotted lines represent the overall average between Ptger1 and Ptger3 or Ptger2 and Ptger4. The expression of EP subtypes in CD11b+ cells isolated from tumor tissues and spleen of CT26 tumor-bearing mice by magnetic bead separation (n = 3). Schematic diagram of the granulocyte–macrophage colony-stimulating factor (GM-CSF)/interleukin (IL)-4-induced mouse monocyte DCs/macrophages differentiation assay. Cells were treated with specific antagonists of distinct EP receptors: ONO-8711, EP1; PF-04418948, EP2; L-798106, EP3; and E7046, EP4. Representative flow cytometry plots revealing the effects of prostaglandin E2 (PGE2) and EP1-4 antagonists on mouse bone marrow monocyte dendritic cell (DC)/macrophage differentiation (n = 3). The frequencies of F4/80+CD11C− macrophages and F4/80−CD11C+ DCs under varying treatments as analyzed by flow cytometry analysis (n = 3). Schematic representation of the GM-CSF/IL-6-induced mouse bone marrow monocyte myeloid-derived suppressor cell (MDSC) differentiation assay (n = 3). Representative flow cytometry plots revealing the effects of PGE2 and EP1-4 antagonists on mouse bone marrow-derived-MDSC differentiation. Upper subpanel: vehicle group and PGE2 group. Lower subpanel: ONO-8711 (EP1 antagonist) group, PF-04418948 (EP2 antagonist) group, L-798106 (EP3 antagonist) group, and E7046 (EP4 antagonist) group. (n = 3). The frequencies of Ly6C+Ly6G− mMDSC and Ly6CmidLy6G+ PMN-MDSCs under varied treatments as analyzed by flow cytometry analysis (n = 3). Data information: Data are presented as mean ± SEM. (A) Kolmogorov–Smirnov test; (E, H) two-tailed unpaired Student’s t-test was performed; *P < 0.05; **P < 0.01; ***P < 0.001. Exact P values and statistical tests are listed in Appendix Table S8. Download figure Download PowerPoint Further, we examined the role of distinct EP subtypes by using specific antagonists in myeloid cell differentiation. Isolated mouse BM cells were stimulated with granulocyte–macrophage colony-stimulating factor (GM-CSF) and interleukin-4 (IL-4) in the presence or absence of PGE2 in vitro (Fig 1C). Dendritic cells (DCs, F4/80–CD11c+) had a greater proportion of GM-CSF/IL-4 differentiated myeloid cells than macrophages (F4/80+CD11c–), whereas PGE2 treatment largely suppressed DC differentiation, and correspondingly promoted macrophage differentiation (Fig 1D and E). Notably, we found that chemical inhibition of EP4 effectively reduced macrophage differentiation and rescued DC differentiation in the presence of PGE2 (Fig 1D and E). Further, we differentiated mouse BM cells into MDSCs in vitro by treating them with GM-CSF and IL-6 (Fig 1F). The exposure of mouse BM cells to GM-CSF/IL-6 led to the generation of immature MDSCs expressing Ly6C+Ly6G– or Ly6CmidLy6G+ (Fig 1G and H). Remarkably, PGE2 enhanced the differentiation and expansion of MDSCs (Fig 1G and H). Intriguingly, EP1 and EP3 antagonists had little effect on MDSC and the EP2 blockade was able to reduce the differentiation of monocytic MDSC (mMDSCs, Ly6C+Ly6G–CD11b+) but not polymorphonuclear MDSC (PMN-MDSCs, Ly6CmidLy6G+CD11b+), which is consistent with previous studies (Shi et al, 2014; Rodriguez-Ubreva et al, 2017). Importantly, chemical inhibition of EP4 decreased the expansion of both mMDSCs and PMN-MDSCs. In summary, EP4 was the main receptor of PGE2 in boosting the differentiation and expansion of immunosuppressive macrophages and MDSCs. TP-16 is a novel, selective EP4 antagonist We then sought to explore novel EP4 antagonists with improved drug-likeness because of the unfavorable pharmacokinetics properties of current clinical compounds (i.e., grapiprant) (Markovic et al, 2017). TP-16 is a new thienopyran-containing small molecule derived from an extensive medicinal chemistry campaign (see Appendix Methods). TP-16 demonstrated potent EP4 antagonistic activity in HEK293-EP4 cells with a half minimal inhibitory concentration (IC50) value of 2.1 ± 0.6 nM in the cAMP-responsive element (CRE) luciferase assay (Figs 2A and EV1A). A strong antagonistic activity of TP-16 was observed in the GloSensor™ cAMP assay with an IC50 value of 5.4 ± 0.8 nM (Fig 2B). EP4 recruits β-arrestin, and the Tango is a validated assay for evaluating ligand-induced GPCR/β-arrestin 2 interaction (Kroeze et al, 2015). The Tango assay revealed that TP-16 dose-dependently blocked PGE2-induced EP4/β-arrestin interaction in HEK293 cells with an IC50 value of 7.5 ± 3.0 nM (Fig EV1B). EP4 was reported to trigger calcium flux in CHO-Gα16 cells (Wu et al, 2018). The calcium flux assay revealed that TP-16 was a potent EP4 antagonist in human (Fig 2C), monkey (Fig EV1C), rat (Fig EV1D), and mouse (Fig EV1E) with IC50 values of 2.1 ± 0.4 nM, 5.6 ± 0.3 nM, 18.7 ± 1.4 nM, and 6.8 ± 0.8 nM, respectively. In addition, this assay revealed that TP-16 had a > 3000-fold higher selectivity for human EP4 than human EP1 -3 (IC50> 10 µM for EP1, EP2, and EP3) (Fig 2C). Moreover, the LANCE Ultra cAMP assay and calcium flux assay revealed that other 25 GPCRs were not affected by TP-16 (IC50 > 10 μM) (Appendix Tables S1 and S2), indicating high target selectivity. Figure 2. Discovery and characterization of a potent and selective EP4 antagonist, TP-16 Chemical structure of TP-16. Dose–effect curve of TP-16 in GloSensor™ cAMP assay in EP4- expressing 293 cells (n = 3). Dose–effect curves of TP-16 in PGE2-induced calcium flux assay (n = 3). The Schild plot of PGE2 in the presence of varying concentrations of TP-16. TP-16 shifted the dose–response curve of PGE2-induced intracellular cAMP levels in a dose-dependent manner (n = 3). The pA2 value and slope of the Schild plot. Docked pose of TP-16 with critical residues in the putative binding pocket of human EP4 protein. EP4 is shown as a color cartoon, the residues important for the interaction are depicted in magenta sticks, and TP-16 is shown as a cyan stick figure. The LIGPLOT diagram summarizes key interactions between TP-16 (purple lines) and residues that originate from EP4. T69, T76, T168, and R316 establish hydrogen bonds with TP-16. Semicircles with radiating lines indicate non-polar interactions. Data information: Data are presented as mean ± SEM from three independent experiments with similar results. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Antagonistic activity, pharmacokinetic profiles, and safety of TP-16 A. Dose–response of TP-16 in cAMP reporter gene assay in HEK293 cells. Data are presented as mean ± SEM derived from three independent experiments (n = 3). B. Dose–effect curves of TP-16 in PGE2-induced β-arrestin Tango assay. Data are presented as mean ± SEM derived from three independent experiments (n = 3). C–E. The antagonistic activities of TP-16 on EP4 were determined by a calcium flux assay by overexpressing Gα16 protein in CHO cells. Dose–response curves of TP-16 against EP4: monkey (C), rat (D), and mouse (E). Data are presented as mean ± SEM derived from three independent experiments (n = 3). F, G. The plasma concentration over time profiles of TP-16 after intravenous and oral administration of TP-16 at a dose of 1 and 10 mg/kg, respectively. Results are presented as mean ± SEM of three CD1 mice (n = 3). H. Body weights of male and female SD rats orally administered with TP-16 (100 mg/kg/day) in 14-day repeat-dose. Data are presented as means ± SD (n = 3/sex/group). Data information: Data are presented as mean ± SEM except for H. Download figure Download PowerPoint PGE2 increased the intracellular cAMP level in a dose-dependent manner in HEK293-EP4 cells (Fig 2D). An increase in the concentration of TP-16 induced a rightward shift in PGE2 concentration–response curves without changing the maximal cAMP accumulation. Subsequently, schild plot analysis yielded a pA2 value of 8.07 with a slope of 1.08 (Fig 2E). To investigate the detailed interaction between EP4 and TP-16, in silico molecular docking was performed using AutoDock (Morris et al, 2009). The crystal structure of human EP4 bound to ONO-AE3-208 was retrieved from the Protein Data Bank (PDB ID: 5YWY) (Toyoda et al, 2019). The docking grid was created based on the ONO-AE3-208 binding pocket. The lowest energy docking model was selected for subsequent interaction analysis. We found that the predicted binding pocket of TP-16 was mainly composed of transmembrane (TM) 1, TM2, TM3, TM7, and extracellular loop 2 (ECL2) (Fig 2F and G). Specifically, the carboxyl group of TP-16 interacted with the guanidinium group of Arg316 and the hydroxyl group of Thr168 through a salt bridge. This interaction mode is similar to the antagonist, ONO-AE3-208, binding in the crystal structure of the EP4 complex (Toyoda et al., 2019). In addition, the amide group could form a hydrogen bond with the hydroxyl group of Thr76, and the oxygen atom in the six-element ring of TP-16 interacted with Thr69. Ideal pharmacokinetics and safety of TP-16 We then evaluated the pharmacokinetic properties of TP-16 in CD1 mice. The mean plasma concentration–time curves are presented in Fig EV1F and G, and the key pharmacokinetic parameters are shown in Appendix Table S3. The Cmax value of a single dose of TP-16 (10 mg/kg, p.o.) at 0.5 h was 3851.8 ng/ml. The elimination half-life (t1/2) was 5.4 h, and the AUC0-24 was 8399.8 h*ng/ml. i.v