Abstract
Immune checkpoint inhibitors and adoptive tumor-infiltrating lymphocyte (TIL) therapies have profoundly improved the survival of melanoma patients. However, a majority of patients do not respond to these agents, and many responders experience disease relapse. While numerous innovative treatments are being explored to offset the limitations of these agents, novel therapeutic combinations with immunotherapies have the potential to improve patient responses. In this study, we evaluated the anti-melanoma activity of immunotherapy combinations with Telaglenastat (CB-839), a potent glutaminase inhibitor (GLSi) that has favorable systemic tolerance. In in vitro TIL:tumor co-culture studies, CB-839 treatment improved the cytotoxic activity of autologous TILs on patient-derived melanoma cells. CB-839 treatment decreased the conversion of glutamine to alpha-ketoglutarate (αKGA) more potently in tumor cells versus TILs in these co-cultures. These results suggest that CB-839 may improve immune function in a tumor microenvironment by differentially altering tumor and immune cell metabolism. In vivo CB-839 treatment activated melanoma antigen–specific T cells, and improved their tumor killing activity in an immune-competent mouse model of adoptive T cell therapy. Additionally, combination of CB-839 with anti-PD1 or anti-CTLA4 antibodies increased tumor infiltration by effector T cells and improved the anti-tumor activity of these checkpoint inhibitors in a high mutation burden mouse melanoma model. Responsiveness to these treatments was also accompanied by an increase of interferon gamma (IFNγ)-associated gene expression in the tumors. Together, these results provide a strong rationale for combining CB-839 with immune therapies to improve efficacy of these treatments against melanoma.
Keywords: Melanoma, Glutaminase, T cell therapy, Immune checkpoint inhibitor, Cancer metabolism
Introduction
Metabolic alterations facilitate cancer cells to obtain nutrients and building blocks needed for their unfettered growth, metastases and therapeutic resistance (1). Melanoma skin cancers upregulate mitochondrial oxidative phosphorylation (OxPhos) as a de novo or acquired mechanism to promote resistance to targeted therapies (2–5). This dependence on OxPhos is facilitated by increased glutamine consumption and its anaplerotic metabolism in the TCA cycle (6–10). Given its important role in metabolic adaptations of cancers, glutamine metabolism has been targeted for cancer therapy using different small molecule inhibitors (11). However, toxicity or lack of pharmacological efficacy have limited their clinical development as single agent therapeutics. For example, inhibitors of glutamine uptake like benzylserine and irreversible glutamine analogs like 6-diazo-5-oxo-L-norleucine (DON) exhibit unacceptable systemic toxicity (12), although a recent pro-drug version may be more tolerable (13). Allosteric inhibitors of glutaminase (GLS) like BPTES are limited by poor pharmacokinetics (PK) (14). More recently, Telaglenastat (CB-839), an investigational, first in class, potent oral inhibitor of GLS (15), has demonstrated favorable PK and pharmacodynamics (PD) and safety in an early clinical study (NCT02071862) (16). CB-839 is currently being tested in late-stage clinical trials to evaluate its combinatorial efficacy with other molecularly targeted agents and chemotherapies in different solid cancers (clinicaltrials.gov IDs: NCT03428217, NCT04265534).
In addition to being a critical nutrient for cancer cells, glutamine is also important for immune cell function, including T lymphocyte activation (17,18). Although systemic administration of GLS or glutamine utilization inhibitors would be expected to inhibit the activity of tumor infiltrating lymphocytes (TIL) in addition to tumor cells, a recent study showed that GLS inhibition may promote the proliferation and effector function of Th1 and cytotoxic T cells by inducing epigenetic alterations that increase sensitivity of these cells to IL2 (19). This suggests that glutamine consumption and its metabolism may differ between tumor cells and TILs, and inhibition of glutamine metabolism may alter their fates in different ways in the tumor microenvironment, with TILs potentially gaining anti-tumor functionality. Of note, the combination of CB-839 with anti-PD1 therapy, Nivolumab, was recently tested in 37 melanoma patients who had earlier progressed after checkpoint inhibitor therapy (clinicaltrials.gov ID: NCT02771626), the preliminary results of which showed objective responses in three patients, without additional toxicity (16). These results suggest that combination with CB-839 can re-invigorate checkpoint inhibitor therapy in refractory patients. However, this combination has not been studied in treatment-naïve patients, where it could potentially deliver greater benefit.
In the current study, we evaluated the in vitro and in vivo anti-tumor activity of CB-839 in combination with autologous T cell therapies and checkpoint inhibitor therapies, using treatment-naïve melanoma models. Our results showed that CB-839 activated T cell immune responses and significantly improved anti-tumor activity of both immunotherapy modalities.
MATERIALS AND METHODS
Cell lines, mice and inhibitors.
B16-F10 cells were from ATCC, Yummer 1.7 cells were kindly provided by Dr. Marcus Bosenberg (Yale University School of Medicine, New Haven, CT) (20). A375HG cells that constitutively express murine H-2Db and GFP-tagged gp100 melanoma tumor antigen have been described earlier (21). Patient-derived melanoma cell lines and their autologous tumor-infiltrating lymphocytes (TILs) were isolated under an institutional review board–approved laboratory protocol (LAB06–0755), as previously described (22,23). All human subjects gave verbal and written consent to participate. Cell line authentication was performed by short tandem repeat (STR) profiling as previously described (24,25). Thy1.1 positive Pmel-1 T cells that express a TCR specific for murine H-2Db–restricted epitope of gp100 were extracted from the spleens of TCR/Thy1.1 mice as described previously (26). All cell lines were grown in RPMI media containing 2mM glutamine and 10% fetal bovine serum. Pmel-1 cell culture media additionally contained 300 I.U./ml IL-2 and 0.3 µg/ml anti-mouse CD3 (BD Bioscience). For glutamine dose dependent studies, glutamine-deficient RPMI media and dialyzed fetal bovine serum were used. C57BL/6 mice were purchased from Charles River Frederick Research Facility and Pmel-1 TCR/Thy1.1 mice were from in-house breeding colonies. CB-839 was provided by Calithera Biosciences. For in vitro studies, DMSO stocks of CB-839 were freshly prepared and used at 1µM concentration, unless dose responses were studied. For in vivo treatments, CB-839 was prepared in a vehicle containing 25% hydroxypropyl-β-cyclodextrin in 10 mmol/L citrate (pH 2.0) solution. The anti-PD1 (clone 29F.1A12), anti-CTLA4 (clone 9H10) and isotype control antibodies were from BioXCell, and administered into mice via intraperitoneal injections.
Cellular Glutamine consumption analysis.
Tumor cells (2×103) or T cells (1×104) seeded in 96 well plates were incubated in serum-free RPMI media containing 2 mmol/L glutamine for 12 hours, in the presence of the indicated concentrations of CB-839 or vehicle. After incubation, the culture media was collected, and glutamine levels were quantified using the YSI 2900 Biochemistry Analyzer.
Metabolite analysis of co-cultured cells.
Targeted metabolite analysis and [U-13C]-glutamine tracing analysis were performed at the MDACC metabolomics core facility. Methodologies are described in supplementary methods.
Bioenergetics Stress tests.
Real-time oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were determined by the Seahorse XFe analyzer in 96 well plates, and data was normalized using cell numbers as previously described (2).
Cell proliferation and T cell division assays.
For the cell proliferation assay, tumor cells or TILs extracted from the same tumors were seeded in 96 well plates and treated with increasing doses of CB-839, and incubated for 72h, followed by addition of Cell Titer Blue reagent (Promega) and fluorescence measurement of viable cells as described previously (5). For the T cell division assay, T cells were purified by negative selection (Stemcell) from the spleen of C57BL/6 mice. The cells were labeled with Cell-Trace CFSE (Invitrogen) following the manufacturer’s instructions, stimulated with plate-bound anti-CD3 and soluble anti-CD28 antibodies in glutamine-free RPMI-1640 media supplemented with increasing doses of fresh glutamine. Cell division was assessed after 96 hours by CFSE dye-dilution using flow cytometry and compared to non-stimulated control cells.
Apoptosis and cell death assays.
A T-cell killing assay to detect tumor cell apoptosis by caspase 3 cleavage was performed as described previously (27,28). Induction of cell death of A375HG tumor cell death by T cells was evaluated by cytoplasmic histone-associated DNA fragmentation using the Cell Death ELISA Plus kit as described earlier (25). Methodologies are provided in supplementary methods.
Mouse vaccine model study.
This study was performed as previously described (21). Briefly, Pmel-1 T cells extracted from the spleens of Pmel-1 receptor–transgenic mice were intravenously administered into C57BL/6 mice (104 cells/mouse), and the mice were vaccinated with 100 µL of saline containing 100 µg/µL human gp100 and 4×105 IU anti-CD40 antibody (BioXcell; clone FGK45; Cat# BP0016). The vaccinated mice also received intra-peritoneal IL2 (1 × 105 IU) once on the day of vaccination and twice daily for the next two days, and were topically treated with 50 mg of 5% imiquimod cream (Fougera) on the vaccination site once after each vaccination. CB-839 treatments were performed as indicated. Mouse blood was collected from tail veins on the days shown, and complete blood counts were analyzed using a scilVet ABC hematology analyzer to determine the effect of CB-839 on white blood cell (WBC) numbers. Peripheral blood mononuclear cells (PBMC) were isolated using ACK lysis buffer and subjected to FACS analysis after appropriate antibody staining.
In vivo xenograft tumor growth studies.
The adoptive T cell therapy study was performed as described earlier (26,29), where sub-cutaneous xenograft tumors of B16-F10 were generated with 2×105 cells/animal in the right flank of C57BL/6 mice. After 50–100mm3 size tumors were established, 1×106 Pmel-1 T cells were adoptively transferred into tumor-bearing mice, followed by intraperitoneal administration of IL2 (5 × 105 IU) twice daily for three days after T cell transfer. The mice were then treated with CB-839 (200mg/kg) by oral gavage twice daily for the indicated number of days, and tumor volumes and mice weight were recorded on the indicated days. For the immune checkpoint inhibitor studies, sub-cutaneous xenograft tumors of Yummer 1.7 were generated as above in C57BL/6 mice. Mice were administered twice daily treatments of CB-839 as above, or twice a week intraperitoneal injections of anti-CTLA4 (100 µg/animal) or anti-PD1 (500µg/animal) as suggested (20,30), either as single agents or in combination with each other and with CB-839. Tumor measurements were performed as above. Animals were excluded if they showed overt toxicity, or lost >15% body-weight. For FACS and other molecular analysis of treatment-related effects, tumors from three mice per group were harvested three hours after the specified treatments on the indicated days, and analyzed accordingly. For RNA and metabolite analysis, harvested tumors were rinsed in ice-cold normal saline and flash frozen in liquid nitrogen. All animal experiments were approved by IACUC.
Immunohistochemical analysis.
Tumors were harvested at the indicated times and immunostaining performed on tissue sections using standard methodology, scanned and analyzed as described earlier (31). Antibodies and analysis are described in supplementary methods.
FACS analysis.
Peripheral blood or tumors were harvested at the indicated time points, and processed for FACS analysis of Pmel-1 cells or tumor infiltrating lymphocytes as described earlier (21,26). Antibodies and analysis are described in supplementary methods.
Gene expression analysis.
RNA was extracted from tumors using the mirVana kit, and the expression of genes associated with the immune system were profiled using the NanoString mouse Cancer Immune Panel on the nCounter platform following the manufacturer’s instructions (NanoString Technologies).
Statistical analysis.
Statistical significance testing used in the study are described in supplementary methods.
Results:
CB-839 inhibits glutamine consumption in patient-derived melanoma cell lines and promotes their killing by autologous TILs.
Inhibition of GLS activity by CB-839 impedes cellular glutamine consumption and decreases its flux into the TCA cycle, resulting in decreased mitochondrial OxPhos (15). We assessed the effect of CB-839 on glutamine consumption in four different melanoma patient-derived cell lines by analyzing glutamine levels in extracellular media. None of these patients were previously treated with TIL or checkpoint inhibitors. Treatment of these cell lines with 1 µM CB-839 potently decreased up to 80% of glutamine consumption after 12 h treatment (Figure 1A). CB-839 at 1µM was earlier shown to cause sustained inhibition of GLS in cells grown in media containing 2 mmol/L glutamine (15). Bioenergetics stress tests using the Seahorse analyzer showed that CB-839 induced a small, but significant inhibition of cellular OCR, a surrogate of mitochondrial OxPhos, in all four cell lines (Basal OCR in Figure 1B and bioenergetics profiles in Figure S1). Thus, CB-839 decreased glutamine consumption and mitochondrial OxPhos in the melanomas. In contrast, CB-839 treatment caused minimal inhibition of both glutamine consumption and OCR in the autologous TILs derived from the same patient-derived tumors that gave rise to the above melanoma cell lines (Fig 1C and S2). CB-839 did not affect ECAR, a measure of glycolytic activity, in either the melanoma or TIL lines (Figures S1–S2).
Figure 1. In vitro effects of CB-839 on patient-derived melanoma cell lines and autologous TILs.

(A) Glutamine (Gln) consumption by the indicated melanoma cell lines treated with vehicle or 1µmol/L CB-839 for 12h. (B) Basal oxygen consumption rate (OCR) by the cell lines treated with vehicle or 1µmol/L CB-839 for 24h. (C) Glutamine (Gln) consumption by the indicated TILs treated with vehicle or 1µmol/L CB-839 for 12h. (D) Growth of four melanoma cell lines measured after 72 h treatment of the cells with increasing doses of CB-839. (E–H) Apoptosis assay in an in vitro adoptive T-cell therapy experiment, showing percent activation of caspase 3 in melanoma cells by treatments with single agent CB-839, patient-specific adoptive TILs, or their combinations. Data is average of quadruplicate samples for the seahorse experiment in B, and average of triplicate samples for the others. Error bars represent standard deviation (SD). Significant treatment-induced differences (p<0.05) in results are indicated by ‘*’.
CB-839 treatment induced a modest dose-dependent inhibition of proliferation of the four melanoma cell lines, which was similarly modest in their autologous T cells (Figure 1D, Figure S3A). We then assessed the effects of CB-839 on melanoma cell killing by their autologous T cells in vitro by evaluating cleaved caspase 3 levels in the melanoma cells. Treatment with CB-839 for 24 h did not increase cleaved caspase 3 levels in any of the cell lines. However, co-culturing the melanoma cells with their autologous TILs induced a sharp increase of cleaved caspase 3, which was further increased in the cells pre-treated with CB-839 (Figure 1E–H). These results suggest that CB-839 treatment sensitizes tumor cells to apoptotic killing by TILs.
CB-839 treatment induces differential glutamine metabolism in tumors and T cells.
Glutamine is an important fuel that supports immune cell functions. Consistent with that concept, we observed that glutamine induced a dose-dependent increase in the proliferation of anti-CD3- and anti-CD28-stimulated T cells in vitro (Figure 2A). Treatment with CB-839 did not inhibit this effect (Figure 2B). We next measured the effect of CB-839 on intracellular glutamine and its GLS-catalyzed products using LC-MS in mono-cultures of gp100 antigen-specific Pmel-1 T cells; monocultures of A375HG melanoma cells which express murine MHC class I and gp100, allowing recognition by the Pmel-1 T cells (32); or the co-cultures of Pmel-1 and A375HG. In A375HG, CB-839 caused a >3-fold accumulation of intracellular glutamine (Figure 2C), but conversely caused a >2-fold decrease of glutamate and its TCA metabolite αKGA compared to vehicle controls (Figures 2D and 2E), consistent with potent inhibition of GLS activity. The non-TCA metabolites of glutamine, proline and glutathione (GSH) also underwent similar alterations (Figures 2F and S3B). Co-culturing A375HG with Pmel-1 cells interestingly decreased αKGA levels (Figure 2E). Proline and GSH levels were however not significantly altered by the Pmel-1 cells (Figure 2E and S3B). Combination of Pmel-1 and CB-839 treatments had the most significant impact on glutamate and αKGA, but not on proline and GSH in the A375HG cells (Fig 2D–2F, S3B). Similar analysis in the Pmel-1 mono-cultures showed that CB-839 treatment decreased glutamate levels, but minimally altered αKGA, proline and GSH levels compared to vehicle treatment (Figure 2G–J, S3C). Interestingly, co-culturing with A375HG induced an increase of glutamine and all four of its metabolites in the Pmel-1 cells. Treatment of the co-cultures with CB-839 increased glutamine levels, but did not significantly alter its four metabolites (Figure 2G–J, S3C). Taken together, the results suggest that co-culture with Pmel-1 cells alters glutamine metabolism in tumor cells by an unknown mechanism that inhibits αKGA levels, which is further augmented by CB-839 treatment. In contrast, CB-839 appears to have minimal effect on αKGA and in in mono- or co-cultured T cells.
Figure 2. in vitro effects of glutamine on T cell proliferation and antitumor activity.

(A, B) T cell proliferation by CD3/CD28 stimulation monitored over 96 h in the presence of increasing doses of glutamine (A) or CB-839 (B). (C – F) LC-MS analysis of glutamine (C), glutamate (D), αKGA (E) and proline (F) in A375HG tumor cells after 6 h treatment with CB-839 and Pmel-1 cells. DNA-normalized data was represented as relative abundance of metabolites in samples with indicated treatments. (G – J) Same experiment as above, but the glutamine (G), glutamate (H), αKGA (I) and proline (J) levels were analyzed in Pmel-1 cells after treatments. (K) A375HG cells were treated with CB-839 or co-cultured with IL2-activated Pmel-1 cells or both, in media without glutamine (left panel) or with 2 mmol/L glutamine (right panel). After 12 h incubation, apoptosis in the A375HG cells was quantified by immunostaining with fluorescence-labeled, activated caspase 3 antibody using FACS. Data is average of triplicate measurements; error bars, SD. Significant treatment-induced differences (p<0.05) in results are indicated by ‘*’.
As αKGA levels may also be influenced by other pathways like glycolysis, we performed 13C isotope tracing analysis to determine if CB-839 and Pmel-1 induced alterations in tumor αKGA levels were a direct result of glutamine metabolism. In this analysis, we performed the same experiment as above by replacing glutamine in the culture media with [U-13C]-glutamine. Incorporation of [U-13C]-glutamine into glutamate and αKGA was determined by LC-MS, which showed that the levels of these glutamine-derived metabolites were altered in a similar manner as the total levels of these metabolites in the A375HG (Figures S3D–S3G), and in the Pmel-1 cells (Figure S3G–S3K).
To evaluate the role of glutamine on T cell-mediated apoptotic killing of melanoma cells, we performed the caspase 3 activation assay in A375HG tumor cells co-cultured with Pmel-1 T cells in glutamine-free and glutamine-rich conditions. Tumor cells were cultured in glutamine-free media for 24 h, while Pmel-1 were simultaneously activated with IL2 in 2 mmol/L glutamine-containing media. Pmel-1 cells were then washed and added to the tumor cells at a cell number ratio of 5:1, with final glutamine concentrations of 0 or 2 mmol/L in the co-cultures. The cultures were then incubated for 12 h in the presence or absence of CB-839. Caspase 3 activity in the A375HG cells treated with CB-839 and Pmel-1 cells was assessed by FACS analysis. CB-839 treatment had no impact on caspase 3 cleavage in the absence of glutamine, either as a single agent or in the presence of Pmel-1 cells (Figure 2K, left panel). In the presence of glutamine however, CB-839 alone induced a significant increase of caspase 3 cleavage, Pmel-1 cells induced a larger increase, and their combination induced the highest increase (Figure 2K, right panel). To confirm that increased caspase 3 cleavage was leading to cell death in A375HG, we performed the co-culturing and CB-839 treatments as above. After 24h, Pmel-1 cells were washed away, and cell death in the adherent A375HG cells was measured as a function of cytoplasmic histone-complexed DNA fragments (mono- and oligonucleosomes) using the cell death ELISA plus assay. The results show the levels of cell death proportionately matched the percentage of cleaved caspase 3 following the various treatments (Figure S4A). These results demonstrate that a glutamine-rich microenvironment promotes cytotoxic activity of T cells against tumor cells, and CB-839 treatment significantly enhances this effect.
CB-839 treatment increases in vivo activation status of CD8 T cells.
As our in vitro results suggested that inhibition of GLS may benefit the activity of tumor-reactive T cells, we explored the effect of CB-839 on T cell activity in vivo using a murine melanoma vaccine model (21). As shown schematically in Figure 3A, Pmel-1 T cells were injected into mice with concurrent systemic IL2 and gp100 vaccination. Mice were randomized to treatment with vehicle or CB-839 (administered days 1–5 and 27–32). Blood was drawn at multiple time points to characterize the effects of effects of CB-839 on complete blood cell counts, plasma glutamine concentrations, effector T cell viability and their activation status. We found that CB-839 significantly increased plasma glutamine levels (Figure 3B), but did not alter the levels of total WBCs, including its component lymphocytes and monocytes (Figure S4B). PBMCs were isolated and analyzed by FACS to assess Pmel-1 effector T cell numbers using antibodies against CD3, CD8 and Thy1.1 (congenic Pmel-1 marker), and their activation using anti-CD107a. CB-839 treatment induced a small increase of total Pmel-1 cell numbers, and a more significant increase in their activation status, following initial treatment on day 8, and post-booster dose treatments on day 33 (Figures 3C and 3D). These results suggest that CB-839 treatment contributes to the proliferation and activation of melanoma antigen-specific CD8 T cells in vivo.
Figure 3. Effect of CB-839 on the in vivo activation status of adoptive lymphocytes.

(A) Schema of vaccination, Pmel-1 and CB-839 treatments in C57BL/6 mice (10/group). Blood was collected by vein puncture on days 6, 8, 27 and 33. Blood plasma was isolated on day 6 and PBMCs were isolated on every blood collection day. (B) Glutamine levels in blood plasma from vehicle and CB-839 treated mice were analyzed by using a YSI analyzer and shown as bar graphs. (C, D) PBMCs isolated on the indicated days were labeled with CD8a, CD90.1 (Thy1.1) and CD107a antibodies, and analyzed by FACS. Pmel-1 cells which stain positive for CD8a and Thy1.1 are shown in C, and the percentage of CD107a+ Pmel-1 cells are shown in D. All data is average of triplicate measurements; error bars, SD. Significant treatment-induced differences (p<0.05) in results are indicated by ‘*’.
CB-839 treatment improves the anti-tumor activity of adoptive T cell therapy.
We used an established adoptive T cell therapy model (26,29) to determine if in vivo T cell activation by CB-839 improves the anti-melanoma activity of Pmel-1 T cell therapy. In this study schematically shown in Figure 4A, IL2 stimulated Pmel-1 T cells were intravenously transferred into C57BL/6 mice growing sub-cutaneous B16 tumors. After three days of in vivo IL2 stimulation, the mice were randomized into treatment groups as shown in Figure 4B and treated for up to a month, and tumor growth was measured. Single agent CB-839 induced a small decrease of tumor growth compared to vehicle, while Pmel-1 TILs induced substantial inhibition, which was further enhanced by combining CB-839 and Pmel-1 treatments (Figure 4B). Kaplan Meier survival analysis showed that while both Pmel-1 and CB-839 treatments improved survival compared to vehicle (p=0.0004 and p=0.0004), their combination completely prevented mortality (p<0.0001) over the same time period (Figure 4C).
Figure 4. Anti-tumor activity of the combination of CB-839 with T cell therapy.

(A) Schedule of treatments with CB-839 and Pmel-1 cells in C57BL/6 mice (10/group). (B) B16 tumor growth in C57BL/6 mice after treatment with CB-839 or Pmel-1 cells or their combinations. Treatment time points at which CB-839 induced significant tumor growth inhibition (p<0.05) compared to vehicle are indicated by ‘+’, those of Pmel-1 compared to vehicle are indicated by ‘#’, and those of CB839+Pmel are indicated by ‘*’. (C) Kaplan Meir survival analysis of the mice with the indicated treatments. (D) Relative abundance of intermediary metabolites of the TCA cycle in tumors harvested from mice undergoing the indicated treatments. Bars represent normalized data with vehicle treatment adjusted to 1. (E) IHC analysis of tumor-intrinsic T cell numbers staining positive with either CD8 or CD4 antibodies in five random areas of 1 mm2 each. (F) IHC analysis of percentage of tumor cells staining positive for Ki67 or cleaved caspase 3 antibodies in five random areas. In E and F, significant treatment-induced differences (p<0.05) compared to vehicle are indicated by ‘#’ for the CD4+ or Ki67+ cells, and by ‘*’ for CD8+ or cleaved caspase3+ cells. (G) TILs were isolated from harvested tumors, and the percentage of IFNγ-positive CD8 T cells was determined by labeling cells with anti-Thy1.1, anti-CD8a and anti-IFNγ antibodies, followed by FACS analysis. Data is average of triplicates, and significant treatment-induced differences (p<0.05) are indicated by ‘*’.
LC-MS metabolite analysis was performed on tumors collected on day 27, which showed that CB-839 induced a decrease of tumor αKGA and its downstream intermediates within the TCA cycle, succinate, fumarate and malate (Figure 4D). This is indicative of GLS inhibition by CB-839. Similar to effects observed in vitro (Figure 2C and 2E), Pmel-1 treatment of tumors also decreased TCA cycle intermediates. The combination of CB-839 and T cells however did not further inhibit their levels (Figure 4D). IHC analysis of the tumors showed that Pmel-1 and Pmel-1 + CB839 treatments significantly increased the infiltration of CD4+ and CD8+ cells (Figures 4E and S5); and decreased Ki67 proliferation marker staining of tumor cells, while increasing caspase 3 cleavage in them (Figure 4F). FACS analysis of TILs isolated from tumors as above showed a significant increase of IFNγ positive Pmel-1 cells in mice treated with combination of Pmel1 + CB839 versus Pmel1 alone (Figure 4G). MCP-counter was applied to the expression profiles of 36 genes (Table S1) to predict the abundance of tumor-intrinsic immune cell types, which identified >2-fold increases in intra-tumor CD8 T cells, NK cells and B cells after treatment with single agent CB-839 and Pmel-1 cells, while their combination increased only the CD8 T and NK cells (Figure S7A). Together, these results indicate that CB-839 treatment improves the efficacy of Pmel-1 cells in the B16 adoptive T cell therapy model.
Combination of CB-839 with immune checkpoint inhibitor therapy.
We next determined if CB-839 could also improve the efficacy of immune checkpoint inhibitor antibodies. We tested the combination of CB-839 with anti-PD1 and anti-CTLA4 in the Yummer 1.7 mouse melanoma model, which mirrors human melanoma with a BRAFV600E mutation and a UV radiation-induced mutation burden (20). Treatments were performed as shown in Figure 5A, and tumor growth was analyzed. While single agent CB-839 had no effect (Figures 5B–D), single agent anti-PD1 and anti-CTLA4 antibodies significantly inhibited growth of this tumor model, which was further inhibited by their combinations with CB-839 (Figure 5B and 5C). The combination of CB-839 with anti-PD1+anti-CTLA4 co-treatments induced a marked improvement in tumor growth inhibition (Figure 5D).
Figure 5. Anti-tumor activity of the combination of CB-839 with checkpoint inhibitors.

(A) Schematic showing the Yummer 1.7 sub-cutaneous tumor generation and schedule of treatments with CB-839, anti-PD1 or anti-CTLA4 antibodies in mice (10/group). (B,C,D) Effect of the indicated single agents or their combination treatments on tumor growth. Time points at which either anti-PD1 or anti-CTLA4 treatments induced significant tumor growth inhibition (p<0.05) compared to vehicle are indicated by ‘+’; those of double combinations are indicated by ‘*’, and of the triple combination are indicated by ‘#’. (E) IHC analysis of tumor-intrinsic T cell numbers staining positive with either CD8 or CD4 antibodies in five random areas of 1 mm2 each. (F) IHC analysis of percentage of tumor cells staining positive for Ki67 or cleaved caspase 3 antibodies in five random areas. (G) FACS analysis showing the percentage of CD4 and CD8 T cells with CD107+ status in tumor infiltrates after two weeks of treatment with the indicated agents. In E, F and G, significant treatment-induced differences (p<0.05) compared to vehicle are indicated by ‘#’ for CD4+ or Ki67+ cells, and by ‘*’ for CD8+ or cleaved caspase 3 cells.
IHC analysis of tumors harvested after three weeks of treatment showed that combinations of CB-839 with anti-PD1 or anti-PD1+anti-CTLA4 induced the most potent infiltration of CD8+ and CD4+ cells, potently decreased Ki67 staining of tumor cells, and increased caspase 3 cleavage in them (Figure 5E and 5F; Supplementary Fig. S6). TILs were extracted from the harvested tumors and analyzed by FACS to quantify CD107+ effector cells in the CD4+ and CD8+ T cell fractions. The results showed that CB-839, anti-PD1, anti-CTLA4, and anti-PD1+anti-CTLA4 each increased the prevalence of CD107a+ CD4+ effector T cells, and all but anti-CTLA also increased the CD8+ effector T cells. Anti-PD1 induced the most increase of CD4+ effector TILs among the single agents, and its combination with CB-839 induced the largest increase among all treatments. Interestingly, in the tumors from mice treated with anti-CTLA4 + anti-PD1 or their triple combination with CB-839, the increase of effector TILs was not as pronounced as single agent anti-PD1 or anti-PD1 + CB-839 (Figure 5G). Anti-CTLA4 and anti-PD1 have earlier been shown to potently increase proliferation of CD4+ T cells (33). It is unclear why the combination of anti-CTLA-4 with anti-PD1 slightly dampened CD107+ effector TILs compared to the single agent treatments, and whether this may be unique to the Yummer 1.7 tumor model. As the observed effector TIL status may only be a snapshot of the specific time of measurement, and potentially influenced by factors such as effector cell exhaustion or alterations in myeloid/regulatory T cells (34), longitudinal studies exploring the numbers of effector and regulatory T cells at different time intervals could be performed in future studies to understand this result in conjunction with inhibition of tumor growth. MCP-counter analysis showed an increase of CD8 T cells, cytotoxic lymphocytes, B cells and monocyte lineage with the combination treatments (Figure S7B), suggesting an overall increase of immunogenicity in tumors from respectively treated animals.
CB-839 and checkpoint inhibitor treatments increase IFNγ-associated T cell inflammatory gene expression in tumors.
Based on an earlier study that showed increased expression of the IFNγ-associated “T cell inflamed signature” genes in anti-PD1 responsive tumors (35), we analyzed these genes, PD1 (Pdcd1) and three additional genes that promote T cell cytotoxicity (Figure S5) in the tumor RNA samples, and presented the results as ratios of treatments to vehicle controls. In the B16 tumor model, CB-839 treatment of gp100 vaccinated mice (minus Pmel-1 treatment) increased the expression of seven genes, including two of the three T cell cytotoxicity genes, Gzma and Prf1, (Figures 6A and 6B). Pmel-1 treatments of the vaccinated B16 tumor-bearing mice increased the expression of only five genes, suggesting that CB-839 treatment of gp100 vaccinated mice induced a more potent immune cell activation than Pmel-1 cells at the time tested. The combination of Pmel-1 and CB-839 upregulated all but two of the T cell inflamed signature genes, and also upregulated all three T cell cytotoxicity genes (Figure 6A and 6B), which could be attributable to the higher potency of anti-tumor activity compared to the anti-PD1 + CB-839 combination.
Figure 6. Expression of T cell inflamed gene signature by CB-839, autologous TILs and checkpoint inhibitor treatments.

(A, C) Supervised hierarchical clustering of “T cell inflamed signature” and “T cell cytotoxicity” genes in B16 (A) and Yummer1.7 (C) tumors harvested from mice treated with the indicated agents. Data depicted as heatmaps show the fold-changes of treatments versus vehicle. (B, D) Treatment-induced changes in the expression of genes involved in T cell cytotoxicity, Gzma, Gzmb and Prf1, are shown as bar graphs for B16 (B) and Yummer 1.7 (D) tumors, with the y-axis representing fold-changes between therapeutic and vehicle treatments. Significant (p<0.05) treatment-induced alterations are indicted by * for Gzma, + for Gzmb and # for Prf1. (E) Schematic figure showing the mechanism of differential glutamine consumption and metabolism in tumor cells and T cells without treatment (left panel), and after treatment with CB-839 and/or checkpoint inhibitors (right panel). Inhibition of glutaminase (GLS) by CB-839 decreases glutamine (Gln) consumption by tumor cells, resulting in its accumulation and consumption by innate or adoptive T cells, and activation of their effector function; immune checkpoint inhibitors anti-PD1 and anti-CTLA4 may further improve T cell activity (right panel).
In the Yummer1.7 model which is insensitive to CB-839, but is responsive to anti-PD-1 and anti-CTLA4 treatments, CB-839 increased the expression of only three genes in the T cell inflamed signature, but the checkpoint inhibitors induced a potent increase in almost all genes either as single agents or in combination (figure 6C and D). The largest increase was observed with the triple combination treatment of CB-839 + anti-PD1 + anti-CTLA4, with 20 of 21 genes upregulated, which correlated with enhanced anti-tumor activity. Taken together, these results suggest that CB-839 treatment synergizes with TIL and immune checkpoint inhibitor therapies to activate anti-tumor T cell functions (Figure 6E).
Discussion.
Glutamine addiction is a common adaptation of many cancers for growth and therapeutic resistance, and presents an attractive target for intervention. Among the different agents in development, the GLS inhibitor, CB-839 showed limited but promising clinical responses in combination with the anti-PD1, Nivolumab, in melanoma patients whose disease had progressed after checkpoint inhibitor therapy (16). This is suggestive of a potential for this combination and other immunotherapy combinations with CB-839 to be more efficacious in treatment-naïve patients. However, no pre-clinical studies exist that would merit a clinical study of these combinations in treatment-naïve melanoma patients. Hence, we set out to evaluate the combination efficacy of CB-839 with immune therapies using multiple treatment-naïve pre-clinical models of melanoma.
We first examined the in vitro effects of CB-893 in two models of melanoma and T cell pairs, (a) patient-derived melanoma cell lines with their patient-paired autologous TILs, and (b) the gp100 antigen-expressing mouse melanoma cells paired with gp100-reactive Pmel-1 cells. Although single agent CB-839 robustly decreased glutamine consumption and mitochondrial output in melanoma cells, it did not show similar robustness in inhibiting their cell growth or inducing cell death. However, it did significantly improve melanoma cell killing induced by autologous TILs. Metabolic analysis of melanoma cells and T cells grown separately showed that CB-839 decreased glutamine flux through GLS and toward αKGA more robustly in the melanoma cells compared to the T cells. Interestingly in co-cultures, CB-839 further decreased αKGA levels in the melanoma cells, but not in the T cells. The differences between the two cell types in glutamine consumption and its metabolism to αKGA could be a result of differences in either glutamine transporter activity, GLS dependence, or flux through the TCA cycle. Taken together, these results suggest that GLS inhibition by CB-839 in tumor cells and T cells in a tumor microenvironment may increase extracellular glutamine levels, which the T cells may use to fuel GLS-independent activities including antigenic activation (Figure 6E). Those glutamine-dependent T cell activities could be explored in future studies using cell-specific glutamine receptor or GLS ablation studies. A recent finding in the context of cellular immunity by Johnson et al. (19) suggested that inhibition of GLS selectively enhances Th1 and CTL cell differentiation and function. If this also occurs in the context of a tumor microenvironment, then GLS inhibition in effector T cells may potentially improve their anti-tumor activity, which could be explored using appropriate model systems. More recently, inhibition of glutamine consumption was shown to inhibit myeloid cell functions in tumors, resulting in increased effector T cell response (36). This could also be explored in the context of GLS inhibition using appropriate model systems.
We then evaluated the in vivo effect of CB-839 in T cells using an established model of vaccine-induced T cell immunity. In this model, CB-839 treatment moderately increased the numbers of circulating Pmel-1 T cells, and also potently increased their antigenic activation. Additionally, in tumor bearing mice, CB-839 combination with Pmel-1 TIL therapy significantly increased tumor infiltration of functionally active Pmel-1 cells compared to TIL therapy alone, resulting in improved tumor growth inhibition. As TIL, CAR (chimeric antigen receptor) and engineered T cell therapies are gaining traction as promising cancer treatments, combinations of these therapies with CB-839 could potentially improve patient outcomes for the cell-based therapies. Our study provides proof of principle for evaluating such combination treatments.
Finally, we tested CB-839 combination with immune checkpoint inhibitors in a high-mutation burden melanoma model, Yummer 1.7, which has superior responses to immune checkpoint inhibitor therapy compared to many commonly used murine melanoma models (20). Our results revealed that combination with CB-839 caused significant improvements in the antitumor efficacy of anti-PD1 and anti-CTLA4. Combining all three agents induced a complete regression of tumor growth. In a clinical study of CB-839 combination with anti-PD1 in melanoma patients who had earlier progressed with checkpoint inhibitor therapy (15), the expression of a set of genes termed “T cell inflamed signature” was predictive of objective responses versus progressive disease. Consistent with this, our pre-clinical results showed that upregulation of these genes was concomitant with the degree of anti-tumor response to CB-839 combinations with checkpoint inhibitors. Our results additionally showed that this signature is also predictive of Pmel-1 TIL therapy and its combination with CB-839. As single agent CB-839 itself activated the expression of some genes in this signature, the relevance of these genes as potential predictors of response could be further explored in samples derived from cancer clinical trials with CB-839.
While limited to examination of tumor cells and effector T cells, our study points to differential alteration of glutamine metabolism in the tumor microenvironment as an important mechanism of anti-melanoma activity of CB-839. Larger studies with additional models and functional genetic ablations could help stratify responder patients, based on the effect of GLS inhibition in different components of the tumor microenvironment. Taken together, our results elucidate the unique GLS plasticity between tumor cells and T cells, show that CB-839 is an agonist of T cell mediated anti-tumor response, and provide proof of principle to clinically evaluate its combination with immune therapies in immunotherapy-naïve melanoma patients.
Supplementary Material
Acknowledgment:
YNVG was supported by a research grant from Calithera Biosciences (55350) and a research grant from the Melanoma Research Alliance (348483). The Metabolomics Core Facility at MDACC is supported by Cancer Prevention and Research Institute of Texas grant RP130397, NIH grants S10OD012304–01, U01CA235510, and P30CA016672. The authors would like to thank Dr. Michael Davies for providing laboratory resources, advice and critical review of the study, Chantale Bernatchez and the MDACC melanoma moonshot program for patient cell lines and adoptive TILs, Rishika Prasad and Renato Guerrieri for technical assistance, Marina Gelman (Calithera Biosciences) for scientific expertise and advice, Funda Meric-Bernstam and Hussein Tawbi for discussions leading to the development of this study.
Financial Support:
Research grants from Calithera Biosciences and Melanoma Research Alliance to YNVG.
Footnotes
Conflicts of Interest: YNVG received research funding from Calithera Biosciences.
References:
- 1.Pavlova NN, Thompson CB. The Emerging Hallmarks of Cancer Metabolism. Cell metabolism 2016;23:27–47 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Gopal YN, Rizos H, Chen G, Deng W, Frederick DT, Cooper ZA, et al. Inhibition of mTORC1/2 overcomes resistance to MAPK pathway inhibitors mediated by PGC1alpha and oxidative phosphorylation in melanoma. Cancer research 2014;74:7037–47 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Haq R, Shoag J, Andreu-Perez P, Yokoyama S, Edelman H, Rowe GC, et al. Oncogenic BRAF regulates oxidative metabolism via PGC1alpha and MITF. Cancer cell 2013;23:302–15 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Zhang G, Frederick DT, Wu L, Wei Z, Krepler C, Srinivasan S, et al. Targeting mitochondrial biogenesis to overcome drug resistance to MAPK inhibitors. The Journal of clinical investigation 2016;126:1834–56 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Vashisht Gopal YN, Gammon S, Prasad R, Knighton B, Pisaneschi F, Roszik J, et al. A Novel Mitochondrial Inhibitor Blocks MAPK Pathway and Overcomes MAPK Inhibitor Resistance in Melanoma. Clinical cancer research : an official journal of the American Association for Cancer Research 2019;25:6429–42 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Rodrigues MF, Obre E, de Melo FH, Santos GC Jr., Galina A, Jasiulionis MG, et al. Enhanced OXPHOS, glutaminolysis and beta-oxidation constitute the metastatic phenotype of melanoma cells. The Biochemical journal 2016;473:703–15 [DOI] [PubMed] [Google Scholar]
- 7.Baenke F, Chaneton B, Smith M, Van Den Broek N, Hogan K, Tang H, et al. Resistance to BRAF inhibitors induces glutamine dependency in melanoma cells. Molecular oncology 2016;10:73–84 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Hernandez-Davies JE, Tran TQ, Reid MA, Rosales KR, Lowman XH, Pan M, et al. Vemurafenib resistance reprograms melanoma cells towards glutamine dependence. Journal of translational medicine 2015;13:210. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Filipp FV, Ratnikov B, De Ingeniis J, Smith JW, Osterman AL, Scott DA. Glutamine-fueled mitochondrial metabolism is decoupled from glycolysis in melanoma. Pigment cell & melanoma research 2012;25:732–9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Ratnikov BI, Scott DA, Osterman AL, Smith JW, Ronai ZA. Metabolic rewiring in melanoma. Oncogene 2017;36:147–57 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Li L, Meng Y, Li Z, Dai W, Xu X, Bi X, et al. Discovery and development of small molecule modulators targeting glutamine metabolism. European journal of medicinal chemistry 2019;163:215–42 [DOI] [PubMed] [Google Scholar]
- 12.Catane R, Von Hoff DD, Glaubiger DL, Muggia FM. Azaserine, DON, and azotomycin: three diazo analogs of L-glutamine with clinical antitumor activity. Cancer treatment reports 1979;63:1033–8 [PubMed] [Google Scholar]
- 13.Leone RD, Zhao L, Englert JM, Sun IM, Oh MH, Sun IH, et al. Glutamine blockade induces divergent metabolic programs to overcome tumor immune evasion. Science (New York, NY) 2019;366:1013–21 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Shukla K, Ferraris DV, Thomas AG, Stathis M, Duvall B, Delahanty G, et al. Design, synthesis, and pharmacological evaluation of bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide 3 (BPTES) analogs as glutaminase inhibitors. Journal of medicinal chemistry 2012;55:10551–63 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Gross MI, Demo SD, Dennison JB, Chen L, Chernov-Rogan T, Goyal B, et al. Antitumor activity of the glutaminase inhibitor CB-839 in triple-negative breast cancer. Molecular cancer therapeutics 2014;13:890–901 [DOI] [PubMed] [Google Scholar]
- 16.Meric-Bernstam FG M; Tykodi S; Lam E; Vaishampayan U;, Chaves JN P; Fan A; Lee R; McDermott D; Shapiro G;, Gandhi LT H; Bhatia S; Muigai L; Jenkins Y; Whiting S; Voss M CX-839–004: A phase 1/2 study of CB-839, a first-in-class glutaminase inhibitor, combined with nivolumab in patients with advanced Melanoma (MEL), Renal Cell Carcinoma (RCC), or Non-Small Cell Lung Cancer (NSCLC). Society for Immunotherapy of Cancer Annual Meeting. Volume 2017. National Harbor, MD: SITC; 2017. [Google Scholar]
- 17.Carr EL, Kelman A, Wu GS, Gopaul R, Senkevitch E, Aghvanyan A, et al. Glutamine uptake and metabolism are coordinately regulated by ERK/MAPK during T lymphocyte activation. Journal of immunology (Baltimore, Md : 1950) 2010;185:1037–44 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Wang R, Green DR. Metabolic reprogramming and metabolic dependency in T cells. Immunological reviews 2012;249:14–26 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Johnson MO, Wolf MM, Madden MZ, Andrejeva G, Sugiura A, Contreras DC, et al. Distinct Regulation of Th17 and Th1 Cell Differentiation by Glutaminase-Dependent Metabolism. Cell 2018;175:1780–95.e19 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Wang J, Perry CJ, Meeth K, Thakral D, Damsky W, Micevic G, et al. UV-induced somatic mutations elicit a functional T cell response in the YUMMER1.7 mouse melanoma model. Pigment cell & melanoma research 2017;30:428–35 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Liu C, Peng W, Xu C, Lou Y, Zhang M, Wargo JA, et al. BRAF inhibition increases tumor infiltration by T cells and enhances the antitumor activity of adoptive immunotherapy in mice. Clinical cancer research : an official journal of the American Association for Cancer Research 2013;19:393–403 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Chacon JA, Wu RC, Sukhumalchandra P, Molldrem JJ, Sarnaik A, Pilon-Thomas S, et al. Co-stimulation through 4–1BB/CD137 improves the expansion and function of CD8(+) melanoma tumor-infiltrating lymphocytes for adoptive T-cell therapy. PloS one 2013;8:e60031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Cascone T, McKenzie JA, Mbofung RM, Punt S, Wang Z, Xu C, et al. Increased Tumor Glycolysis Characterizes Immune Resistance to Adoptive T Cell Therapy. Cell metabolism 2018;27:977–87.e4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Davies MA, Stemke-Hale K, Lin E, Tellez C, Deng W, Gopal YN, et al. Integrated Molecular and Clinical Analysis of AKT Activation in Metastatic Melanoma. Clinical cancer research : an official journal of the American Association for Cancer Research 2009;15:7538–46 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Gopal YN, Deng W, Woodman SE, Komurov K, Ram P, Smith PD, et al. Basal and treatment-induced activation of AKT mediates resistance to cell death by AZD6244 (ARRY-142886) in Braf-mutant human cutaneous melanoma cells. Cancer research 2010;70:8736–47 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Overwijk WW, Tsung A, Irvine KR, Parkhurst MR, Goletz TJ, Tsung K, et al. gp100/pmel 17 is a murine tumor rejection antigen: induction of “self”-reactive, tumoricidal T cells using high-affinity, altered peptide ligand. The Journal of experimental medicine 1998;188:277–86 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.McKenzie JA, Mbofung RM, Malu S, Zhang M, Ashkin E, Devi S, et al. The Effect of Topoisomerase I Inhibitors on the Efficacy of T-Cell-Based Cancer Immunotherapy. Journal of the National Cancer Institute 2018;110:777–86 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.He L, Hakimi J, Salha D, Miron I, Dunn P, Radvanyi L. A sensitive flow cytometry-based cytotoxic T-lymphocyte assay through detection of cleaved caspase 3 in target cells. Journal of immunological methods 2005;304:43–59 [DOI] [PubMed] [Google Scholar]
- 29.Hanada KI, Yu Z, Chappell GR, Park AS, Restifo NP. An effective mouse model for adoptive cancer immunotherapy targeting neoantigens. JCI insight 2019;4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Wang Z, Aguilar EG, Luna JI, Dunai C, Khuat LT, Le CT, et al. Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade. Nature medicine 2019;25:141–51 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Helmink BA, Reddy SM, Gao J, Zhang S, Basar R, Thakur R, et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature 2020;577:549–55 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Peng W, Chen JQ, Liu C, Malu S, Creasy C, Tetzlaff MT, et al. Loss of PTEN Promotes Resistance to T Cell-Mediated Immunotherapy. Cancer discovery 2016;6:202–16 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Takeuchi A, Saito T. CD4 CTL, a Cytotoxic Subset of CD4(+) T Cells, Their Differentiation and Function. Frontiers in immunology 2017;8:194. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Togashi Y, Shitara K, Nishikawa H. Regulatory T cells in cancer immunosuppression - implications for anticancer therapy. Nature reviews Clinical oncology 2019;16:356–71 [DOI] [PubMed] [Google Scholar]
- 35.Ayers M, Lunceford J, Nebozhyn M, Murphy E, Loboda A, Kaufman DR, et al. IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade. The Journal of clinical investigation 2017;127:2930–40 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Oh MH, Sun IH, Zhao L, Leone RD, Sun IM, Xu W, et al. Targeting glutamine metabolism enhances tumor specific immunity by modulating suppressive myeloid cells. The Journal of clinical investigation 2020 [DOI] [PMC free article] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
