Metabolic dysregulation is a hallmark of cancer. Many tumors exhibit auxotrophy for various amino acids, such as arginine, because they are unable to meet the demand for these amino acids through endogenous production. This vulnerability can be exploited by employing therapeutic strategies that deplete systemic arginine in order to limit the growth and survival of arginine auxotrophic tumors. Pegzilarginase, a human arginase-1 enzyme engineered to have superior stability and enzymatic activity relative to the native human arginase-1 enzyme, depletes systemic arginine by converting it to ornithine and urea. Therapeutic administration of pegzilarginase in the setting of arginine auxotrophic tumors exerts direct antitumor activity by starving the tumor of exogenous arginine. We hypothesized that in addition to this direct effect, pegzilarginase treatment indirectly augments antitumor immunity through increased antigen presentation, thus making pegzilarginase a prime candidate for combination therapy with immuno-oncology (I-O) agents. Tumor-bearing mice (CT26, MC38, and MCA-205) receiving pegzilarginase in combination with anti–PD-L1 or agonist anti-OX40 experienced significantly increased survival relative to animals receiving I-O monotherapy. Combination pegzilarginase/immunotherapy induced robust antitumor immunity characterized by increased intratumoral effector CD8+ T cells and M1 polarization of tumor-associated macrophages. Our data suggest potential mechanisms of synergy between pegzilarginase and I-O agents that include increased intratumoral MHC expression on both antigen-presenting cells and tumor cells, and increased presence of M1-like antitumor macrophages. These data support the clinical evaluation of I-O agents in conjunction with pegzilarginase for the treatment of patients with cancer.
Tumor cells require an adequate supply of key nutrients, such as the amino acid arginine, which they can either endogenously synthesize or take up from the environment in order to accommodate their metabolic reprogramming, maintain abnormally elevated rates of proliferation, and generate biomass. However, amino acid auxotrophy, the state of dependence on exogenous amino acids, is a common metabolic abnormality found in tumors (1). Due to low or absent expression of key enzymes involved in arginine synthesis, most notably argininosuccinate synthetase 1 (ASS1; ref. 2), arginine auxotrophic tumors cannot endogenously synthesize sufficient arginine to meet their metabolic demands (3) and therefore depend on the uptake of extracellular arginine. Therapeutic strategies that exploit this vulnerability deplete systemic arginine, which limits arginine auxotrophic tumor growth and survival (Fig. 1A; ref. 3). Pegzilarginase, an engineered human arginase-1 enzyme that possesses superior serum stability and enzymatic activity relative to the native enzyme, depletes systemic arginine by converting it to ornithine and urea (4). For arginine auxotrophic tumors, therapeutic administration of an arginase, like pegzilarginase, deprives the tumor of exogenous arginine and results in direct antitumor activity. This mechanism of action underlies the single-agent antitumor activity of pegzilarginase in a variety of arginine auxotrophic murine and xenograft human tumor models (4). Clinically, a PEGylated recombinant human arginase, BCT-100, induced a sustained complete remission in a patient with immunotherapy–resistant melanoma (5).
Immunotherapy has significantly improved outcomes for many patients by either boosting T-cell–mediated antitumor immunity by releasing the brakes on tumor-reactive T cells via checkpoint blockade (e.g., anti–CTLA-4, anti–PD-1, anti–PD-L1) or costimulating T cells via ligation of TNF receptor family members [e.g., OX40 (CD134); refs. 6–12]. The antitumor immune response generated by these treatments depends on neoantigen recognition and subsequent tumor cell killing; thus, neoantigen abundance profoundly influences immunotherapeutic efficacy. In addition to a sensitivity to depletion of extracellular arginine, urea cycle–disordered tumors, like those with reduced ASS1 expression, have more neoantigens, owing to a pyrimidine imbalance, and respond better to immune checkpoint blockade than do tumors in which enzymes involved in the urea cycle are expressed normally (13). Therefore, a therapeutic strategy that combines manipulation of extracellular arginine with exploitation of an enhanced immunogenicity may be an effective means to control arginine auxotrophic tumor growth. Here, we tested whether combining arginine depletion with immunotherapy enhances antitumor efficacy by exploiting the dual sensitivities of extracellular arginine dependence and increased antigenicity.
Arginase plays a complex role in immune modulation. T cells require sufficient nutrients, including amino acids like arginine, to carry out their essential functions (14, 15); thus, a lack of arginine results in downregulation of T-cell receptor zeta (16) and reduction of proliferation (17). In this vein, it is no surprise that some studies have shown that T-cell proliferation is inhibited by arginase secreted by myeloid-derived suppressor cells (MDSC) in the tumor microenvironment (TME; refs. 18, 19). However, other studies suggest that human arginase-1 possesses relatively poor catalytic activity and serum stability (20) and that MDSC-mediated suppression of T-cell activity does not require arginase (21). T cells compensate for low-arginine conditions by consuming citrulline and upregulating ASS1 (22, 23), an enzyme that converts citrulline and succinate to arginine (24), and producing arginine intracellularly. This allows T cells to proliferate in low-arginine environments and may explain several lines of evidence suggesting that arginine depletion is immune neutral or even immune promoting. For example, CD8+ T-cell cytotoxicity, perforin secretion, and IL2 secretion (25) are not impaired by the absence of arginine (26), and innate lymphoid 2 cells, which regulate proinflammatory functions in a number of tissues (27), are positively regulated by arginase-1. Thus, the effect of arginine depletion on immune cells may depend on the environment, the efficiency of upregulation of compensatory pathways, or the severity of depletion.
Herein, we demonstrated that pegzilarginase monotherapy increased intratumoral CD8+ T-cell number and activation relative to controls. Combining pegzilarginase with various immuno-oncology (I-O) agents, including anti–PD-1 and an agonist anti-OX40, uniformly resulted in increased therapeutic benefit compared with the respective I-O agents alone, including an increase in complete tumor regression and survival. Combining pegzilarginase with I-O agents evinced the greatest number of activated intratumoral CD8+ T cells and elevated systemic IFNγ among all treatment groups. Based in part on the data presented herein, we initiated a phase I to II trial examining the combination of pegzilarginase with pembrolizumab in patients with small-cell lung cancer (NCT03371979). Altogether, these data suggest that combining pegzilarginase with I-O agents may benefit patients harboring arginine auxotrophic tumors.
Materials and Methods
Wild-type female C57BL/6 and BALB/c mice (6–8 weeks of age) were purchased from Charles River or The Jackson Laboratory. All mice were maintained under specific pathogen-free conditions in the Providence Cancer Institute or Aeglea Research Labs animal facility. Experimental procedures were performed according to the National Institutes of Health Guide for the Care and Use of Laboratory Animals and in accordance with, and with the approval of, the Institutional Animal Care and Use Committee of either Aeglea BioTherapeutics or the Earle A. Chiles Research Institute (Animal Welfare Assurance No. A3913–01).
Chemicals and reagents
Pegzilarginase (AEB1102, Co-Arg1-PEG) was produced under good manufacturing practice conditions at KBI Biopharma as described previously (4). The drug was supplied in vehicle (10% glycerol in PBS, pH 7.4) at a concentration of 3 mg/mL and diluted as appropriate for each specific biological application. Pegzilarginase is available from Aeglea BioTherapeutics through a material transfer agreement.
The CT26 (BALB/c) murine colon carcinoma cell lines were purchased from and authenticated by the ATCC. MC38 (C57/Bl6) cells were obtained from and authenticated by the NIH. MCA-205 cells were kindly provided by Dr. Andrew Weinberg (Earle A. Chiles Research Institute). CT26 cells were maintained in complete RPMI 1640 (Thermo Fisher Scientific), MC38 cells in DMEM (Thermo Fisher Scientific), and MCA-205 cells in complete RPMI 1640 [10% FBS, 10 mmol/L HEPES, 1% nonessential amino acids, 1% sodium pyruvate (Lonza), and penicillin (100 IU/mL)–streptomycin (100 μg/mL)–glutamine (29.2 mg/mL; Invitrogen)]; the identity of this cell line was verified through monthly assessment of morphology and growth kinetics; in vitro MC38 cells were supplemented with 1% nonessential amino acids and 1% sodium pyruvate (Millipore Sigma). Hs5 cells were obtained from and authenticated by the ATCC, and were grown in SFEM2 media (Stem Cell Technologies) for use in generation of bone marrow–derived macrophages (BMDM). L-929 cells were obtained from and authenticated by the ATCC, and were grown in DMEM + 10% FBS. All cell lines were used at low passage (<10 passages in vitro after receipt from source). All cell lines were tested and screened negative for Mycoplasma using the MycoAlert test (Lonza).
In vivo tumor studies
Mice were inoculated with 2.5 × 105, 5 × 105, or 1 × 106 cells s.c. for MC38 (Crown Bioscience), CT26 (ATCC), or MCA-205 cells, respectively. Treatment was initiated when mean tumor volumes were 75 to 100 mm3. All dosing of drugs was done via intraperitoneal injection. Mice were randomized into groups based on average tumor volume using the following formula: L × W2/2, where L = Length, W = Width, and L > W. Mice were treated with PBS (1×/week), isotype control (10 mg/kg; 2×/week; catalog #BP0089; Bio-X-Cell), pegzilarginase (3 mg/kg; 1×/week), anti–CTLA-4 (10 mg/kg; 2×/week; clone 9D9, Bio-X-Cell), anti–PD-L1 (10 mg/kg; 2×/week; clone B7-H1; Bio-X-Cell), and/or anti-OX40 (10 mg/kg; 2×/week for 1 week; OX86). For CD8+ T-cell neutralization studies, anti-CD8 (10 mg/kg; 2×/week; clone 53-6.7; Bio-X-Cell) was administered. For CD4+ T-cell neutralization studies, anti-CD4 (10 mg/kg; 1×/week; clone GK1.5; Bio-X-Cell) was administered. For tumor rechallenge studies, animals with fully regressed tumors were inoculated s.c. opposite of the original site of tumor cell implantation with 1 × 106 CT26 cells, and observed for 30 days in order to assess the presence or absence of discernible tumorigenesis. For all experiments noted here, tumor volumes were measured 2×/week by calipers and calculated according to the formula noted above. Body weights were measured 2×/week. Animals were euthanized when either tumor volume reached 2,500 mm3 (2,000 mm3 in the MC38 model) or when tumors became ulcerated. Animals bearing ulcerated tumors were excluded from survival and mean tumor volume analyses.
Tissue processing and flow cytometry
Tumor-bearing animals were euthanized via CO2 asphyxiation, and the tumors were removed for analysis by flow cytometry. Tumors were minced on ice using razor blades and then mechanically and enzymatically dissociated using the mouse tumor dissociation Kit (Miltenyi Biotec) in conjunction with Miltenyi C tubes and the gentleMACS Octo Dissociator with heat unit (Miltenyi Biotec) as per the manufacturer's instructions (program “37C_m_TDK_1”) to yield single-cell suspensions. The cell suspension was sequentially filtered through 70- and 40-μm mesh filters (Corning), and then the cells were washed with cold PBS. Zombie Yellow fixable viability dye (BioLegend) was added as appropriate, and cells were blocked with anti-CD16/32 (BioLegend) for 10 minutes at 4°C and then stained with antibodies directed against cell surface antigens (see “Flow cytometry antibodies and reagents” below). For intracellular staining, cells were fixed and permeabilized using the FoxP3 Staining Buffer Kit (Thermo Fisher Scientific). Spleens were harvested and used to generate control cell suspensions by mechanical dissociation through a 70-μm filter. Cells were washed with cold PBS and stained as per tumor cells. Cells were either analyzed on the Guava 12-HT machine using Incyte v3.3 software (Millipore Sigma) or acquired on an LSR-II flow cytometer running FACSDiva software (BD Biosciences), and data were processed and analyzed with FlowJo (Treestar). All tissues were processed fresh with minimal storage time on ice.
Flow cytometry antibodies and reagents
Anti-mouse CD45 (clone 30-F11), CD3 (17A2), CD4 (GK1.5), CD8 (53-6.7), CD69 (H1.2F3), CD25 (3C7), KLRG1 (2F1/KLRG1), PD-1 (29F.1A12), CD11b (M1/70), CD11c (N418), F4/80 (BM8), CD206 (C06862), MHC II/I-A I-E (M22.214.171.124), Gr-1 (RB6-8C5), Ki-67 (16A8), F4/80 (BM8), Ly-6C (HK1.4), and GzmA (3G8.5) antibodies were from BioLegend. Anti-mouse CD274 (PD-L1, M1H5), CD24 (M1/69), and Ly-6G (1A8) were from BD Biosciences. Intracellular antibodies iNOS (CXNFT; Thermo Fisher Scientific) and Arg1 (Cat: IC5868A; R&D) were used. For viability of tumors, Fixable Viability Dye eFluor 780 (Thermo Fisher Scientific) was used. Anti-calreticulin (EPR3924) was purchased from Abcam. Antibodies against murine T-bet (4B10) and Eomes (Dan11mag) were obtained from Thermo Fisher Scientific. For bone marrow analysis, anti-human CD45 (clone HI30), CD3 (OKT3), and CD19 (HIB19) were from BioLegend. Anti-human CD66b (G10F5), CD11b (ICRF44), and CD14 (61D3) were obtained from Thermo Fisher Scientific. Annexin V reagent was used to assess apoptosis, and Zombie dyes were used to assess viability (BioLegend). gp70 pentamer/MHC I reagent (H-2Ld; SPSYVYHQF) was obtained from ProImmune.
In vivo pharmacodynamic studies
Female BALB/c mice (n = 5/group) were dosed i.p. with pegzilarginase formulated in 10% glycerol in PBS, pH 7.4, at a dose of 2 or 3 mg/kg. All animals were exsanguinated at their assigned time points by cardiac puncture and euthanized. Blood collected from all groups was split between EDTA tubes with or without 18 μg nor-NOHA (NN; Haematologic Technologies). Plasma was separated from whole blood by centrifugation. All plasma samples were neutralized with glacial acetic acid at 2% of the final concentration and frozen for subsequent arginine concentration assessment. Plasma arginine concentrations were assessed at Intertek Pharmaceutical Services using an LC/MS-MS assay (Intertek Pharmaceutical Services).
Immunohistochemistry (IHC) analysis of formalin-fixed and paraffin-embedded (FFPE) tumor sections from CT26 in vivo studies was performed with the Dako Autostainer platform. A monoclonal anti-CD3 (clone SP7; Abcam) was used to detect intratumoral T cells; a monoclonal anti-CD8 was used to detect CD8+ T cells (clone 4SM15; eBioscience). A chromogenic DAB ABC detection system (Abcam) was employed to produce a visual readout of antibody binding; positivity was defined as membrane-reactive chromogenic signal above background. Nontumor-bearing mouse spleens were used as a positive control for anti-CD3 staining. Stitched imaging and quantification were performed using a Keyence BZ-X700 microscope and analysis software (Keyence). CD8 IHC analysis of FFPE sections was performed by QualTek Molecular Laboratories.
For cell culture, media were removed, and cells were collected in cold PBS. For tissues and tumors, samples were homogenized using a FastPrep-24 homogenizer (MP Biomedicals) and lysed in RIPA buffer containing protease inhibitors (Thermo Fisher Scientific). Protein was quantified using the BCA assay (Thermo Fisher Scientific). Laemmli buffer (Bio-Rad) was added to samples, which were then boiled and run on a polyacrylamide gel and transferred to a nitrocellulose membrane. The membrane was blocked with 5% milk in TBST, and then primary antibodies against LC3 (Cell Signaling Technology) or β-actin (Cell Signaling Technology) were incubated with the membrane at 1:1,000 dilution overnight at 4°C. Horseradish peroxidase–conjugated secondary antibodies (Cell Signaling Technology) at 1:2,000 dilution were then incubated with the membrane for 1 to 2 hours at 25°C, and ECL or ECL-plus (Thermo Fisher Scientific) was used for detection on a G-Box (Syngene). Original full Western blots for H2Kd, LC3, and β-actin are available in Supplementary Fig. S1.
Cytokines were analyzed using the MILLIPLEX MAP Mouse Cytokine/Chemokine Magnetic Bead Panel (Millipore Sigma) following the manufacturer's protocol. Mouse serum was diluted 1:2 with included assay buffer, and samples were incubated with beads overnight at 4°C and run on a Luminex 200 platform (Luminex) using assay standards provided in the MILLIPLEX Kit. Data were analyzed using MILLIPLEX Analyst software (Millipore).
Single-cell RNA sequencing and library preparation
CT26 tumors were harvested from mice 3 days after treatment start (n = 3/treatment group), as described above. The single-cell RNA sequencing (scRNA-seq) libraries were generated using the Chromium Single Cell 3′ Library & Gel Bead Kit v.2 (10x Genomics) according to the manufacturer's protocol. Briefly, 3 × 104 live CD45+ live cells per tumor were sorted by flow cytometry and used to generate single-cell gel beads in emulsion (10x Genomics). After reverse transcription, gel beads in emulsion were disrupted using the kit's recovery agent following the manufacturer's instructions (10x Genomics). Barcoded complementary DNA was isolated and amplified by PCR (12 cycles). Following fragmentation, end repair, and A-tailing, sample indexes were added during index PCR (10x Genomics). Samples were resuspended at a concentration of 5 ng/μL and added in equal volumes to the Illumina sequencing chip. The raw data for this experiment have been deposited to Sequence Read Archive (accession number PRJNA691630).
Single-cell sequencing was performed using Illumina NovaSeq 6000. We performed demultiplexing, alignment to GRCm38 reference sequence (GenBank accession number GCA_000001635.8), filtering, barcoding, and unique molecular identifier (UMI) counting using Cell Ranger v2.2.0 (10x Genomics). Data were further analyzed using SeqGeq software (SeqGeq v1.5.0, BD Life Science, Informatics). Briefly, for quality control, cells with the highest (top 0.2%) or lowest (bottom 0.2%) numbers of detected genes were excluded from the downstream analyses. Genes of interest, or highly variable genes to be used for downstream analysis, were selected based on a dispersion value greater than 3 (dispersion is a parameter calculated by SeqGeq). Dimensionality reduction by principal component analysis (PCA) was performed using variable genes. T-stochastic neighbor embedding (t-SNE) plots were generated based on PCA dimensions. Cell types were identified by gating on relevant gene expression.
Arginine auxotrophy screen
Two thousand CT26, MCA-205, or MC38 cells per well were seeded in a 96-well flat-bottom plate (Thermo Fisher Scientific). Cells were allowed to adhere overnight in 90 μL of media appropriate to each cell line (see “Cell lines”). Pegzilarginase was added to wells, yielding final concentrations of 3.0 μmol/L and 8 successive 10-fold serial dilutions. A final concentration 0.14 mmol/L citrulline (Millipore Sigma) was added to half of all wells. After 3 days of incubation, cell viability was assessed using the CellTiter-Glo Luminescent Cell Viability Assay (Promega). Biological triplicates were used for each condition. Luminescence was measured on a Promega GloMax plate reader (Promega). Percent viability was determined by comparing luminescence values of each well with the mean luminescent value of the control wells.
Tumor interstitial fluid collection
Tumor interstitial fluid (TIF) was isolated from tumors using a previously described centrifugal method (29–32). Briefly, tumor-bearing animals were anesthetized via isoflurane inhalation (2%–3% IsoFlo #5260-04-05, Zoetis, mixed with O2), bled via cardiac puncture, and euthanized by cervical dislocation, and tumors were rapidly dissected from the animals. Dissections took <1 minute to complete. Following collection, blood was placed immediately in EDTA tubes (Sarstedt) and centrifuged to separate plasma. Plasma was frozen in liquid nitrogen and stored at −80°C until further analysis. Tumors were then weighed and briefly rinsed in cold saline (150 mmol/L NaCl) and blotted on filter paper (VWR, 28298-020). The entire process of preparing the tumor prior to isolation of TIF took <2 minutes. The tumors were then put onto 20-μm nylon filters (Spectrum Labs, 148134), affixed atop 50 mL conical tubes, and centrifuged for 10 minutes at 4°C at 106 × g. TIF was then collected from the conical tube, frozen in liquid nitrogen, and stored at −80°C until further analysis. To neutralize residual pegzilarginase activity, NN was added to appropriate collection tubes (18 μg NN, #10006861, Cayman Chemical; 2.6 mg of K2-EDTA; 0.1% Mannitol, all dissolved in DI H2O and lyophilized).
Arginine measurements in biofluids
Quantification of arginine in plasma was performed as previously described (4). Quantification of metabolites in TIF was performed as previously described (28). Briefly, a custom library of 152 chemical standards arranged in 7 separate pools (termed external standard pools) was assembled for major polar metabolites found in mammalian plasma. Serial dilutions, prepared in high-performance liquid chromatography (HPLC)–grade water, were made of these external standard pools. External standard pools were used to confirm m/z and retention time for each analyte and to quantitate stable isotope–labeled internal standards for use in downstream analysis (see below).
To extract polar metabolites from plasma, TIF, or the external standard pools, 5 μL of TIF, plasma, or external sample pools was mixed with 45 μL of acetonitrile:methanol:formic acid (75:25:0.1) extraction buffer (all solvents used were HPLC grade), including the following isotopically labeled internal standards: 13C-labeled yeast extract (Cambridge Isotope Laboratory, ISO1), 13C3 lactate (Sigma Aldrich, 485926), 13C3 glycerol (Cambridge Isotope Laboratory, CLM-1510), 13C6 15N2 cystine (Cambridge Isotope Laboratory, CNLM-4244), 2H9 choline (Cambridge Isotope Laboratory, DLM-549), 13C4 3-hydroxybutyrate (Cambridge Isotope Laboratory, CLM-3853), 13C6 glucose (Cambridge Isotope Laboratory, CLM-1396), 13C2 15N taurine (Cambridge Isotope Laboratory, CNLM-10253), 2H3 creatinine (Cambridge Isotope Laboratory, DLM-3653), 8-13C adenine (Cambridge Isotope Laboratory, CLM-1654), 13C5 hypoxanthine (Cambridge Isotope Laboratory, CLM-8042), 8-13C guanine (Cambridge Isotope Laboratory, CLM-1019), 13C3 serine (Cambridge Isotope Laboratory, CLM-1574), and 13C2 glycine (Cambridge Isotope Laboratory, CLM-1017). After addition of extraction buffer to the samples, they were then vortexed for 10 minutes at 4°C, and insoluble material was sedimented by centrifugation at 15 × g for 10 minutes at 4°C. Twenty microliter of the polar metabolite extract was added to sample vials for LC/MS analysis.
LC/MS analysis was performed using a Q Exactive Orbitrap Mass Spectrometer using an Ion Max source and heated electrospray ionization (HESI) probe coupled to a Dionex UltiMate 3000 UPLC system (Thermo Fisher Scientific). External mass calibration was performed every 7 days. Two microliter of each sample was injected onto a ZIC-pHILIC 2.1 × 150 mm analytic column equipped with a 2.1 × 20 mm guard column (both 5 μmol/L particle size, EMD Millipore). The autosampler and column oven were held at 4°C and 25°C, respectively. Buffer A was 20 mmol/L ammonium carbonate and 0.1% ammonium hydroxide; buffer B was acetonitrile. The chromatographic gradient was run at a flow rate of 0.150 mL/min as follows: 0 to 20 minutes: linear gradient from 80% to 20% B; 20 to 20.5 minutes: linear gradient from 20% to 80% B; 20.5 to 28 minutes: hold at 80% B. The mass spectrometer was operated in full scan, polarity-switching mode with the spray voltage set to 3.0 kV, the heated capillary held at 275°C, and the HESI probe held at 350°C. The sheath gas flow rate was set to 40 units, the auxiliary gas flow was set to 15 units, and the sweep gas flow was set to 1 unit. The MS data acquisition was performed in a range of 70 to 1,000 m/z, with the resolution set to 70,000, the automatic gain control (AGC) target at 1 × 106, and the maximum injection time at 20 msec.
Metabolite identification and quantification were performed with Xcalibur 2.2 software (Thermo Fisher Scientific) using a 5 ppm mass accuracy and a 0.5-minute retention time window. For metabolite identification, external standard pools were used for assignment of metabolites to peaks at given m/z and retention time (see Supplementary Table S1 for the m/z and retention time for each metabolite analyzed). For metabolite quantification, comparison of the peak areas of the stable isotope–labeled internal standards with the external standard pools at known concentrations allowed for determination of the concentration of labeled internal standards in the extraction buffer. For quantification of metabolite concentration in biological samples, we subsequently compared the peak area of a given metabolite in the TIF and plasma samples with the peak area of the now-quantified internal standard to determine the concentration of that metabolite in the TIF or plasma sample.
In vitro effects of pegzilarginase
CT26, MC38, or MCA-205 cells were seeded in a 96-well flat-bottom plate (3595, Corning) at a density of 1 × 105 cells/well. After 24 hours to adhere, cells were treated with 3 μmol/L pegzilarginase for 48 hours, at which point the cells were harvested and stained for viability and antibodies for calreticulin, MHC I, and MHC II (see “Flow cytometry antibodies and reagents”). Supernatant from the same wells was collected to determine ATP concentration (ATP Determination Kit, Thermo Fisher Scientific), following the manufacturer's instructions.
Ex vivo human bone marrow culture and analysis
Primary human bone marrow (AllCells) was obtained from healthy patients and cultured as follows. Briefly, Hs5 cells were cultured for 72 hours in SFEM2 media (Stem Cell Technologies) to obtain Hs5-conditioned media. Red blood cells were lysed from the human bone marrow cell population using a hypotonic lysis buffer (BioLegend). The remaining cells were plated in media (75% SFEM2 and 25% Hs5-conditioned media) and cultured at 37°C for 72 hours. Flow cytometry was performed to assess the effects of treatment on leukocyte populations of interest.
BMDMs and coculture with CT26
Femurs were collected from 6- to 8-week-old BALB/c mice. Bones were cut open at each end and flushed with PBS through a 27G needle into a sterile conical vial. Bone marrow was centrifuged at 400 × g for 5 minutes at 4°C. Cells were resuspended in BMDM growth medium [RPMI-1640 supplemented with 1 mol/L HEPES buffer, 1% penicillin–streptomycin, 10% FBS, and 15% 0.2-μm filtered L-929 cell line culture supernatant (taken at 24 hours of cell culture)] and cultured in a T175 culture flask. After incubating bone marrow cultures at 37°C for 3 days, growth media were changed to fresh growth-conditioned media without antibiotics. After 7 days in culture, cells were scraped with a cell scraper, 2 × 105 cells per well were plated in 6-well culture dishes in triplicate per culture condition, and cells were dosed with either PBS, pegzilarginase at 0.02 mg/mL, or 0.12 mg/mL. After 72-hour incubation at 37°C, cells were scraped, collected, and processed for flow cytometry.
For coculture experiments, BMDMs were cultured for 72 hours in the presence of IL4 (10 ng/mL) and IL13 (10 ng/mL; R&D Systems) to stimulate macrophage polarization toward the M2 (immunosuppressive) phenotype. M2 BMDMs (1 × 104) were cocultured with 1 × 105 CT26 cells in triplicate in the presence of PBS or pegzilarginase (0.03 or 0.12 mg/mL) for 72 hours.
All group sample sizes and biological replicate numbers are noted in the figure legends as appropriate. For comparison of more than two groups, statistical significance was determined by one-way ANOVA comparing each group against the combination treatment (for comparisons between groups). For comparison of two groups, statistical significance was determined by a Student t test. The Kaplan–Meier survival estimate was used to determine significance for tumor survival studies. Data were plotted and analyzed, and statistical tests were performed using GraphPad Prism software (GraphPad) or RStudio. A P value of <0.05 was considered statistically significant.
Pegzilarginase administration limits systemic and intratumoral arginine availability
To test the extent of extracellular arginine depletion after pegzilarginase treatment, we measured plasma arginine every 24 hours for 1 week following one dose of pegzilarginase, given at either 2 or 3 mg/kg. Across both concentrations, arginine was undetectable for 2 days after treatment and then recovered, albeit incompletely, by 144 hours (6 days; Fig. 1B). Thus, animals dosed with pegzilarginase experienced cyclical periods of arginine withdrawal and relative replenishment. At 3 mg/kg, pegzilarginase had single-agent antitumor efficacy (4) and lowered serum arginine to a nadir of approximately 1 μmol/L for 72 hours after treatment; therefore, we chose 3 mg/kg pegzilarginase for subsequent studies.
To test whether TME arginine concentrations were similarly modulated by pegzilarginase, we performed LC/MS on TIF (28) derived from CT26 tumor–bearing mice. We collected TIF in the presence of NN, an arginase inhibitor, because enzyme (wild-type arginase and/or pegzilarginase) activity during fluid collection and processing would continue to degrade arginine and result in an overestimation of the pegzilarginase and/or endogenous arginase–mediated decrease in arginine. We found that pegzilarginase treatment significantly decreased TIF arginine concentration, whereas arginine in TIF from control (PBS+NN) tumors was comparable with blood concentrations (Fig. 1C).
For arginine auxotrophic tumors, which cannot be rescued by citrulline through the ASS1-mediated compensatory pathway, the reduction of extracellular arginine due to pegzilarginase may result in increased autophagy and apoptosis (33, 34). In vitro, we observed a reduction in the viability of CT26, MCA-205, and MC38 tumor cells cultured in the presence of pegzilarginase; this compromised viability was not rescued by citrulline for CT26 and MC38, but a partial rescue for MCA-205 was observed. However, it is clear that MCA-205 cells cannot synthesize sufficient arginine to meet their metabolic requirements (Supplementary Fig. S2). To determine whether the pegzilarginase induced immunogenic cell death (ICD), we assessed two hallmarks of ICD, ATP secretion and calreticulin exposure, in CT26, MCA-205, and MC38 cells and found, indeed, that pegzilarginase significantly increased calreticulin and ATP secretion in all lines (Supplementary Fig. S3). We subsequently tested whether pegzilarginase had a similar direct tumor cell killing effect in vivo, by examining tumor cell and lymphocyte viability from CT26 tumors 3 days after treatment (Fig. 1D), when plasma arginine was at a nadir (Fig. 1B), and found no difference in the viable cell fraction (Supplementary Fig. S4). We also detected a significantly larger fraction of early apoptotic cells within the total viable cell fraction of the pegzilarginase treatment group, a finding consistent with the ability of arginine withdrawal to induce apoptosis in arginine auxotrophic tumor cells (Fig. 1E). We then asked whether the tumor cell fraction (CD45−) and CD8+ T cells were similarly susceptible to increased apoptosis due to arginine depletion. We saw a significant increase in apoptosis within the CD45− compartment following pegzilarginase treatment, indicating that tumors were susceptible to cell death. In contrast, the CD8+ T cells from tumors experienced only a small increase in apoptosis due to pegzilarginase treatment (Fig. 1E). However, splenic CD8+ T cells experienced a reduction in apoptosis (Supplementary Fig. S5A and S5B), indicating that acute arginine deprivation was detrimental to intratumoral, but not systemic, CD8+ T cells. The T-cell arginine compensatory mechanism maintains T-cell proliferative capacity through upregulation and activity of ASS1 (22). However, we did not observe differences in ASS1 due to pegzilarginase treatment in intratumoral CD8+ T cells at this time point (Supplementary Fig. S5C).
Autophagy is another hallmark of ICD; thus, we examined the extent of pegzilarginase-induced autophagy in CT26 tumors in vivo by assessing LC3 protein expression (Fig. 1F) and by sequencing bulk RNA from CD45- cells to examine expression of autophagy-related genes (Supplementary Fig. S6). Combined, these data revealed pegzilarginase-induced increased autophagy within 3 days after treatment. Taken together, these data demonstrate that pegzilarginase has direct effects on arginine auxotrophic CT26 tumors, which undergo early apoptosis and autophagy during acute windows of systemic arginine deprivation.
Pegzilarginase antitumor activity requires CD8+ T cells
Because autophagy facilitates antigen processing and loading onto MHC I and II molecules, we hypothesized that pegzilarginase indirectly enhances antitumor immunity in part by increasing antigen presentation. To test this in vitro, we treated MCA-205, CT26, and MC38 tumors with 3 μmol/L pegzilarginase and monitored MHC I and MHC II expression. We found pegzilarginase-induced increases in both MHC I and MHC II across all cell lines (Supplementary Fig. S7). To test this in vivo, we harvested CT26 tumors 3 days after treatment (Fig. 2A) and determined changes in H2Kd (MHC I) expression. Indeed, we detected increased H2Kd expression following pegzilarginase treatment (Fig. 2B). Although pegzilarginase did not significantly increase macrophage frequency (Fig. 2C), it did significantly increase macrophage MHC II expression (Fig. 2C). Thus, providing evidence that pegzilarginase increases MHC I and MHC II expression.
Given the effects on MHC I and II expression and the known increased antigenicity of arginine auxotrophic tumors, we investigated the impact of pegzilarginase on T cells. CT26 tumor–bearing mice were treated with pegzilarginase, and then tumors were harvested 3, 7, 10, and 17 days after treatment for immune profiling (Fig. 2A). CD4+ and CD8+ T cells decreased 3 days after treatment with pegzilarginase, which was significant for CD8+ T cells and corresponded with increased Annexin V staining (Fig. 1E) and known T-cell sensitivity to arginine depletion (Fig. 2D; refs. 14, 15, 26). However, by day 7 after treatment, both the CD4+ and CD8+ T-cell populations had recovered, and by days 10 and 17 after treatment, intratumoral CD8+ T cells in the pegzilarginase-treated group increased compared with controls (Fig. 2D). A slightly increased proportion of CD8+ T cells were tumor specific (Fig. 2E), perhaps resulting from increased tumor antigen presentation. We saw a reduction in tumor size beginning approximately 7 days after treatment (4, 21), which occurred in a CD8+ T-cell–dependent manner, as evidenced by a loss of tumor growth control following CD8+ T-cell depletion (Fig. 2F).
These results suggested that the population of intratumor CD8+ T cells increased over time despite arginine deprivation, which was surprising considering reports demonstrating T-cell dependence on arginine for proliferation (17). We reasoned that T cells conditioned in low-arginine environments may respond in a manner distinct from T cells that circulate in arginine-replete conditions. To test this hypothesis, we cultured human bone marrow, which expresses abundant arginase (35), ex vivo in the presence of increasing concentrations of pegzilarginase. We found that bone marrow–derived T-cell numbers increased slightly in response to treatment with 100 nmol/L pegzilarginase for 72 hours, whereas B cells and monocytes decreased in number (Fig. 2G). All together, these data indicated that pegzilarginase increases tumor-infiltrating CD8+ T cells over time, suggesting that pegzilarginase may support the activity of I-O agents.
Combining pegzilarginase with I-O agents improves antitumor efficacy relative to monotherapies
To test whether pegzilarginase enhances I-O agent efficacy, we examined the combination of pegzilarginase plus two different immunotherapy approaches: (i) Checkpoint blockade (anti–PD-L1 and anti–CTLA-4) and (ii) T-cell costimulation (agonist anti-OX40). To test the former, CT26 or MC38 tumor–bearing mice (75–100 mm3) received anti–PD-L1, pegzilarginase, or combined therapy (Fig. 3A). In both models, combined pegzilarginase/anti–PD-L1 was significantly more effective than I-O therapy alone (Fig. 3B). The pegzilarginase/anti–PD-L1 combination resulted in a pronounced increase in complete responses (defined as a tumor that exhibited positive growth trajectory prior to complete regression; 0/8 in monotherapy groups; 3/8 in combination group). Similar experiments were carried out with anti–CTLA-4, which trended toward increased efficacy for combination therapy, but statistical significance was not reached for the pegzilarginase/anti–CTLA-4 combination therapy over monotherapies (Supplementary Fig. S8).
Based on our findings that pegzilarginase treatment led to increased tumor cell death, antigen presentation, and CD8+ T-cell infiltration, we hypothesized that administration of pegzilarginase in combination with an I-O agent that directly activates T cells may be beneficial. We tested this hypothesis by dosing pegzilarginase in combination with anti-OX40 in CT26 or MCA-205 (sarcoma) tumor–bearing mice (Fig. 3C). We noted significantly enhanced antitumor activity in the combination therapy group relative to anti-OX40 monotherapy in both models (Fig. 3D). Overall, these data suggest that arginine depletion through pegzilarginase results in an increased number of intratumoral CD8+ T cells within the TME, which help drive increased therapeutic efficacy of combined pegzilarginase/immunotherapy treatment (Fig. 3E; Table 1). We performed rechallenge experiments in mice that cleared tumors, and 100% were protected against new tumor growth, indicating formation of immunologic memory after both combination therapies.
|Model .||I-O agent .||Isotope control .||Pegzilarginase single therapy .||I-O single therapy .||Combination therapy .|
|Model .||I-O agent .||Isotope control .||Pegzilarginase single therapy .||I-O single therapy .||Combination therapy .|
Note: Bold text highlights the increased number of complete responses in the combination therapy groups.
Therapeutic efficacy of pegzilarginase/I-O therapy depends on CD8+ T-cell activity
Because we observed the greatest antitumor activity and survival benefit when combining pegzilarginase with anti–PD-L1 or anti-OX40 in the CT26 model, we characterized the resulting immune activity in response to combination therapy. CT26 tumor–bearing mice were treated with pegzilarginase and anti–PD-L1, and then tumors were harvested 7, 10, and 17 days after treatment for immune profiling (Fig. 3A and C). These data revealed that pegzilarginase/anti–PD-L1 therapy increased CD4+ T cells on days 7 and 17 after treatment, which was driven by pegzilarginase treatment (Fig. 4A). In contrast, the CD8+ T-cell population increased only in response to the combination therapy 7 days after treatment and remained high throughout the time course (Fig. 4A). CD8-specific IHC on tumors collected 22 days after treatment confirmed our flow cytometry results (Fig. 4B). The gating strategy for these results and for subsequent markers is presented in Supplementary Fig. S9.
For pegzilarginase/anti-OX40 combination therapy, we examined immune infiltration 7 days after treatment because of the rapid separation in tumor growth curves between the monotherapy and combination treatment cohorts. The high rate of complete responses following combination therapy (Fig. 3D and E) precluded examination of later time points. Pegzilarginase/anti-OX40 treatment elicited a pegzilarginase-driven increase in CD4+ T cells similar to that observed for the pegzilarginase/anti–PD-L1 combination (Fig. 4C). Within the CD4+ T-cell population, anti-OX40 increased the frequency of T-effector cells (FoxP3−, Teff), which was not present in the combination therapy (Fig. 4C). Intratumoral CD8+ T cells only increased slightly in the anti-OX40 combination arm relative to controls 7 days after treatment, and this treatment demonstrated similar trends, albeit less significant, to the CD8+ T-cell increase in response to pegzilarginase/anti–PD-L1 therapy (Fig. 4D). Despite this small increase in CD8+ T cells in response to both combination therapies, treatment with a CD8-depleting mAb abrogated the antitumor effects of both (Fig. 4E and F). Due to the effects of anti-OX40 on effector and regulatory CD4+ T-cell subsets, we asked whether CD4+ T cells were necessary for pegzilarginase/anti-OX40 combination treatment efficacy by treating with a CD4-depleting mAb. CD4+ T cells appeared to be dispensible for the therapeutic efficacy of pegzilarginase/anti-OX40 combination therapy, despite an early increase in tumor growth in the absence of CD4+ T cells, by 20 days after treatment tumor growth, as it was unaffected by the absence of CD4+ T cells (Fig. 4F). This variable curve might be the result of the differing effects of depleting both Th1 effector CD4+ T cells and regulatory CD4+ T cells.
Because CD8+ T cells are required for the efficacy of pegzilarginase/I-O combination therapy, we asked whether this effect was due to increased numbers of CD8+ T cells (Fig. 4) or whether the combination therapies also influenced CD8+ T-cell activation and/or function. CT26 tumor–bearing mice were treated with pegzilarginase and/or anti–PD-L1, and subsequently tumors were harvested 7, 10, and 17 days after treatment for immune profiling (Fig. 3A and C). Differences in CD8+ T-cell memory and exhaustion were measured based upon KLRG1+PD-1hi subpopulations, and differences in short-term memory cells were measured by T-bet+Eomes− subpopulations (36); however, by 17 days after treatment, these subsets were unchanged across treatment groups (Supplementary Fig. S10A–10C). We observed a pegzilarginase-driven upregulation of CD69 and CD25 by day 7 after treatment, which was maintained until day 17 after treatment (Fig. 5A). In the pegzilarginase/anti-OX40–treated cohort, we saw similar increases in CD8+CD25+ T cells (Supplementary Fig. S10D) and significant increases in the proportion of Ki-67+CD8+ T cells 7 days after treatment (Fig. 5B). We further examined effector responses by measuring serum IFNγ by ELISA following pegzilarginase/anti–PD-L1 treatment or granzyme A+CD8+ T cells following pegzilarginase/anti-OX40 treatment. In both cases, we detected significant increases in effector function in the combination therapy treatment groups compared with either agent alone (Fig. 5C and D). We were able to confirm these phenotypes by scRNA-seq of CD4+ and CD8+ T cells isolated 3 days after therapy (Supplementary Fig. S11). This analysis revealed increased markers of exhaustion, activation, and reactive oxygen species metabolism after pegzilarginase/anti-OX40 combination therapy. This suggests combination therapy made lymphocytes uniquely adapted to survive and function in a more inflamed environment. Taken together, these data indicate that pegzilarginase/I-O combination therapy induces more robust antitumor CD8+ T-cell responses, in terms of cell numbers and function, than either monotherapy.
Pegzilarginase/anti-OX40 combination therapy alters the TME
Based upon the pegzilarginase-induced changes in tumor infiltration of activated and functional CD8+ T cells (Figs. 4 and 5), we asked whether there were changes to the TME that would promote CD8+ T-cell activity. To address this, we performed scRNA-seq on CD45+ cells isolated from CT26 tumors harvested 3 days after treatment with pegzilarginase and/or anti-OX40. The distribution of cells was visualized using a two-dimensional t-SNE projection (37). T-SNE projections from the different samples within each treatment group were similar (Supplementary Fig. S12A); thus for subsequent analyses, all cells from mice within each treatment group were pooled. The t-SNE projection revealed different cellular distributions for the combination therapy group (Fig. 6A). Clustering all cells from all samples revealed six major clusters: (i) macrophages, (ii) inflammatory monocytes, (iii) natural killer cells, (iv) dendritic cells (DC), (v) CD8+ T cells, and (vi) CD4+ T cells (Fig. 6B; Supplementary Fig. S12B). The combination therapy group was enriched in inflammatory monocytes, which appeared to be driven by anti-OX40 treatment (Fig. 6C and D), and uniquely enriched in macrophages (Fig. 6C and D). We confirmed these changes by flow cytometry (Fig. 6E). Flow cytometry further indicated that combination therapy with pegzilarginase/anti-OX40 did not enhance the absolute number of macrophages (Supplementary Fig. S13A and S13B); we saw a similar trend following pegzilarginase/anti–PD-L1 therapy (Fig. 6F).
Given that pegzilarginase depleted arginine in the TME, we asked whether we could detect differences in gene expression within the arginine synthesis compensatory pathway (Ass1, Asl, and Slc7a2). Pegzilarginase did not result in significant changes in expression of these genes; however, anti-OX40 monotherapy did increase the expression and frequency of cells expressing these genes (Fig. 6G). Combination pegzilarginase/anti-OX40 therapy further expanded the expression and percentage of cells expressing genes that compensate for the lack of extracellular arginine (Fig. 6G). Cells having the highest expression of Ass1/Asl/Slc7a2 appeared to be macrophages and inflammatory monocytes (Fig. 6G). Of these, the percentage of tumor-associated macrophages expressing Ass1/Asl/Slc7a2 increased to 71% in the combination therapy cohort and 53% in the anti-OX40 monotherapy cohort. We also observed that combination therapy drove increased expression of M1-associated genes (STAT1, CXCL9, and NOS2) in macrophages (Fig. 6H). We confirmed these data by flow cytometry, which demonstrated decreased PD-L1 and increased iNOS on DCs and macrophages after pegzilarginase/anti-OX40 therapy (Supplementary Fig. S13C). Flow cytometry also revealed that pegzilarginase/anti-OX40 combination therapy resulted in fewer absolute numbers of suppressive monocytic MDSCs (Supplementary Fig. S13B). Combined with the single-cell data, these data confirmed that after pegzilarginase/anti-OX40, the TME was less suppressive and more supportive of a proinflammatory, antitumor immune response. We observed a similar finding ex vivo wherein unpolarized BMDMs cocultured with CT26 cells in the presence or absence of pegzilarginase for 72 hours displayed an increase in the M1 macrophage fraction in the presence of pegzilarginase (Supplementary Fig. S13D). These data suggest that the anti-OX40–mediated induction of genes regulating the arginine compensatory pathway was primarily within M1-polarized macrophages, which may enable their continued proliferation and/or survival under scarce extracellular arginine, thus contributing to the enhanced antitumor activity observed between these two treatment modalities.
Herein, we demonstrated that weekly dosing of pegzilarginase resulted in cyclical periods of arginine withdrawal and replenishment that increases CD8+ T-cell infiltration leading to enhanced antitumor immunity. This insight, in addition to the reported enhanced effect of immune checkpoint blockade on urea cycle–disordered tumors (13), prompted us to investigate the combination of pegzilarginase with I-O agents. Administering a combination of pegzilarginase with either anti–PD-L1 or anti-OX40 to mice bearing established syngeneic, arginine auxotrophic tumors uniformly resulted in increased therapeutic benefit compared with the respective I-O agents alone, including an increase in complete tumor regression and survival. The therapeutic efficacy of combination therapy relied on tumor-reactive CD8+ T cells exhibiting increased effector function. Altogether, these data provide a more nuanced exploration of arginine depletion in the setting of solid tumors. We found that the cyclical periods of arginine depletion and restoration present in our therapeutic model resulted in an acute window of diminished CD8+ T-cell proliferation, when available circulating arginine was at a nadir; this acute window was followed by CD8+ T-cell expansion, perhaps aided by recovering arginine levels.
Pegzilarginase activity depletes circulating arginine, leading to a corresponding reduction of arginine in the TME. The pegzilarginase-induced reduction of TME arginine levels is in contrast to endogenous MDSC-secreted arginase present in CT26 tumors, which possess a robust MDSC population (38) that does not create a low-arginine TME. This finding is significant as we believe that this is the first reported measurement of arginine in an MDSC-rich TME, and although this observation may be unexpected, it is not surprising because endogenous arginase-1 possesses poor catalytic activity and serum stability (20). This result, therefore, challenges the notion that MDSC-secreted arginase restrains T-cell activity by depleting intratumoral arginine and supports studies reporting that MDSC-driven T-cell suppression may be arginase-independent and instead requires cell-to-cell contact between MDSCs and T cells (21, 39).
The cyclical nature of arginine depletion in our in vivo studies is experimentally different from literature investigating the effects of continuous arginine depletion on immune function. Many of these studies examined chronic arginine depletion using in vitro systems in which arginine was completely absent or extremely limited (16, 23, 40–42). Clinically, however, it is not feasible to completely suppress patients' circulating arginine levels for extended intervals without incurring significant adverse events; thus, the dosing paradigm that we used in these studies and the consequent cycling of arginine levels between troughs where arginine is scarcely detectable and peaks that are below baseline but in excess of starvation conditions represent a clinically relevant scheme that produces only mild side effects in human patients (43, 44). Although chronic arginine depletion may be expected to result in tumor cell death and immunosuppression due to a lack of lymphocyte proliferation and activity, the result of a cyclical fluctuation of systemic and intratumoral arginine has not been explored. Despite this experimental difference, our results build upon established literature concerning arginine's role in immune system function in several respects. First, when plasma arginine levels were at the initial nadir (day 3 after treatment start), more intratumoral CD8+ T cells expressed apoptosis markers, and the CD8+ T-cell population was diminished in number, suggesting that T-cell proliferation required arginine (17, 40, 42). In contrast to intratumoral CD8+ T-cell populations, splenic CD8+ T cells from the same tumor-bearing animals were not reduced in number when systemic arginine was diminished. Similarly, prior research demonstrates that homeostatic naïve T-cell numbers are not decreased by systemic arginine depletion (45). This may be due to the stark difference in metabolic requirements between quiescent and activated T cells, including a differential requirement for L-arginine (46). Although arginine depletion may affect CD8+ T-cell proliferation, CD8+ T-cell activation is not impaired upon arginine depletion (26, 45); likewise, we found that intratumoral CD8+ T cells were activated during periods of cyclic arginine depletion. Thus, our data pertaining to the early posttreatment window, when arginine levels are depleted, agree with much of the literature detailing the effects of arginine depletion on T cells; however, these effects are fundamentally different at later time points, after the system experiences cycles of arginine depletion and recovery.
Given the impact of pegzilarginase on increasing CD8+ T-cell infiltration and antigen presentation machinery, we tested whether pegzilarginase augmented the antitumor efficacy of the I-O agents anti–PD-L1 and anti-OX40. Paradoxically, both systemic arginase inhibition (19) and administration of an engineered arginase enzyme (47) have been reported to elicit antitumor activity in combination with anti–PD-L1. This may be resolved by considering that an arginase inhibitor and an arginase enzyme may affect similar biological outcomes through different mechanisms. For example, an arginase inhibitor likely abrogates arginase produced by MDSCs and M2-polarized macrophages (19) that contribute to an immunosuppressive TME (42, 48), thereby reducing suppression of antitumor T cells. Administering an engineered arginase enzyme to arginine auxotrophic tumors likely induces tumor cell death, releasing tumor antigens and altering the TME to support antitumor adaptive immunity. Thus, arginase inhibition in either circumstance may result in a more polarized, proinflammatory TME that supports antitumor adaptive immunity.
Pegzilarginase-induced arginine deprivation may promote an immune-stimulatory TME through two distinct and independent mechanisms. First, pegzilarginase, through arginine depletion, appeared to act directly on the tumor by increasing ICD and releasing tumor-associated antigens, thereby enhancing immune function. Second, pegzilarginase indirectly affects T cells by (i) enhancing antigen presentation machinery on antigen-presenting cells and (ii) potentially increasing the repertoire of tumor-associated antigens available for processing and presentation. This model is consistent with the concept of altered nucleotide pools in arginine auxotrophic cells affecting neoantigen presentation (13) and supports exploiting arginine depletion in ASS1-low tumors for both direct anticancer and indirect immune-modulatory reasons. Considering these effects of pegzilarginase, our work revealed two potential mechanisms of synergy between pegzilarginase and I-O agents. The described outcomes of pegzilarginase treatment—increased tumor cell death and increased MHC expression—may both result in a greater number of tumor-specific T cells and/or increased T-cell activation and differentiation. Subsequently, those cells can be supported by administration of I-O agents to elicit a sustained antitumor response. Anti-OX40–induced expression of genes capable of compensating for the lack of extracellular arginine, along with repolarizing M2 to M1 macrophages, would allow beneficial antitumor M1 macrophages to persist in the low-arginine environment after pegzilarginase treatment. A similar mechanism may be at play in CD8+ T cells, as T-cell costimulation induces the expression of L-type amino acid transporter 1, a protein responsible for citrulline import (17), thus activating the compensatory arginine synthesis pathway. This costimulation-specific promotion of the compensatory pathway may explain the increase in antiumor activity in combination with pegzilarginase compared with the combination of pegzilarginase with anti–PD-L1. We suspect that each of these mechanisms contributes to the beneficial outcomes we observed following pegzilarginase/I-O combination therapy.
The antitumor activity of arginase as a single agent is shown to correlate with the ornithine transcarbamylase (OTC) and/or ASS1 status of the tumor (4); however, one limitation of our study is that it is unclear whether the enhanced antitumor activity we observed when combining cyclical arginine depletion with I-O therapy depends upon tumor cell sensitivity to arginine withdrawal. In several in vivo studies, including our combination with anti-OX40 in the MCA-205 model, we noted enhanced combination activity, despite minimal single-agent pegzilarginase antitumor activity; in vitro, MCA-205 cell death upon arginine withdrawal was not fully rescued by citrulline supplementation. This suggests that the antitumor mechanism of therapeutic arginine depletion in combination with I-O agents may consist of elements that are dependent and independent of increased tumor cell death. Future studies, such as those that employ arginine prototrophic tumor models in lieu of arginine auxotrophic models, should address the question of whether single-agent antitumor activity or tumor cell killing by arginine depletion is necessary for full combinatorial antitumor activity. Similarly, the syngeneic models used in these studies induce a fairly robust adaptive immune response and therefore are considered immune “warm” or “hot”; it remains unclear whether immune “cold” tumors, which provoke only a minimal response from the adaptive immune system, would be amenable to these combination therapeutic regimens.
Clinically, targeting tumor cell metabolism is not novel, as drugs such as methotrexate and various asparaginases are established standard-of-care therapies. However, the success of I-O agents in the clinic has intensified the need to understand how immune cell metabolism is modulated by anticancer agents, particularly those that act by targeting the aberrant metabolic profile of the tumor cells themselves. This work, in total, suggests that a dosing regimen that depletes arginine periodically can combine effectively with checkpoint inhibitors and T-cell activators alike. Biomarker-aided identification of appropriate tumor histologies that are both sensitive to arginine depletion and immune activation will be key to unlocking the potential of this combination therapy in the clinic.
M.D. Badeaux reports grants from Cancer Prevention and Research Institute of Texas (CPRIT) during the conduct of the study, as well as a patent for US10729752B2 issued. A.S. Rolig reports grants and nonfinancial support from Aeglea BioTherapeutics during the conduct of the study, as well as grants and nonfinancial support from Nektar Therapeutics outside the submitted work. G. Agnello reports grants from CPRIT during the conduct of the study, as well as a patent for US10729752B2 issued. D. Enzler reports grants from CPRIT during the conduct of the study, as well as a patent for US10729752B2 issued. M.J. Kasiewicz reports grants from Aeglea BioTherapeutics during the conduct of the study. L. Priddy reports grants from CPRIT during the conduct of the study, as well as a patent for US10729752B2 issued. J.F. Wiggins reports grants from CPRIT during the conduct of the study, as well as a patent for US10729752B2 issued. C. Daige reports grants from CPRIT during the conduct of the study, as well as a patent for US10729752B2 issued. M.G. Vander Heiden reports personal fees from Aeglea BioTherapeutics, Agios Pharmaceuticals, iTeos Biotherapeutics, Faeth Therapeutics, and Auron Therapeutics outside the submitted work. J.E. Wooldridge reports receiving grants from CPRIT (to institution) during the conduct of the study and was an employee of and owns stock in Aeglea BioTherapeutics. W.L. Redmond reports grants from Aeglea BioTherapeutics and Providence Portland Medical Foundation during the conduct of the study; grants from Galectin Therapeutics, OncoSec, Calibr, Mina Therapeutics, Nektar Therapeutics, Merck, Bristol-Myers Squibb, GlaxoSmithKline, Shimadzu, Veana Therapeutics, and Inhibrx outside the submitted work; and is on the advisory board of Vesselon and receives licensing fees from Galectin Therapeutics. S.W. Rowlinson reports grants from CPRIT during the conduct of the study; a patent for US10729752B2 issued; and owns stock in Aeglea BioTherapeutics. No disclosures were reported by the other authors.
M.D. Badeaux: Conceptualization, formal analysis, supervision, validation, investigation, visualization, methodology, writing–original draft, writing–review and editing. A.S. Rolig: Conceptualization, data curation, validation, investigation, visualization, writing–original draft, writing–review and editing. G. Agnello: Conceptualization, writing–review and editing. D. Enzler: Investigation, methodology, writing–review and editing. M.J. Kasiewicz: Validation, investigation. L. Priddy: Investigation, writing–review and editing. J.F. Wiggins: Investigation, project administration, writing–review and editing. A. Muir: Investigation, methodology, writing–review and editing. M.R. Sullivan: Investigation. J. Van Cleef: Investigation, writing–review and editing. C. Daige: Conceptualization, formal analysis, supervision, methodology, project administration, writing–review and editing. M.G. Vander Heiden: Conceptualization, writing–review and editing. V. Rajamanickam: Data curation, software. J.E. Wooldridge: Conceptualization, writing–review and editing. W.L. Redmond: Conceptualization, resources, supervision, funding acquisition, project administration, writing–review and editing. S.W. Rowlinson: Conceptualization, supervision, writing–review and editing.
This research was funded in part by a grant (DP140031) awarded to Aeglea BioTherapeutics from CPRIT.
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