Targeting glutamine metabolism enhances tumor-specific immunity by modulating suppressive myeloid cells
Min-Hee Oh, … , Maureen R. Horton, Jonathan D. Powell
Min-Hee Oh, … , Maureen R. Horton, Jonathan D. Powell
Published April 23, 2020
Citation Information: J Clin Invest. 2020;130(7):3865-3884. https://doi.org/10.1172/JCI131859.
View: Text | PDF
Research Article Immunology Oncology Article has an altmetric score of 27

Targeting glutamine metabolism enhances tumor-specific immunity by modulating suppressive myeloid cells

Abstract

Myeloid cells comprise a major component of the tumor microenvironment (TME) that promotes tumor growth and immune evasion. By employing a small-molecule inhibitor of glutamine metabolism, not only were we able to inhibit tumor growth, but we markedly inhibited the generation and recruitment of myeloid-derived suppressor cells (MDSCs). Targeting tumor glutamine metabolism led to a decrease in CSF3 and hence recruitment of MDSCs as well as immunogenic cell death, leading to an increase in inflammatory tumor-associated macrophages (TAMs). Alternatively, inhibiting glutamine metabolism of the MDSCs themselves led to activation-induced cell death and conversion of MDSCs to inflammatory macrophages. Surprisingly, blocking glutamine metabolism also inhibited IDO expression of both the tumor and myeloid-derived cells, leading to a marked decrease in kynurenine levels. This in turn inhibited the development of metastasis and further enhanced antitumor immunity. Indeed, targeting glutamine metabolism rendered checkpoint blockade–resistant tumors susceptible to immunotherapy. Overall, our studies define an intimate interplay between the unique metabolism of tumors and the metabolism of suppressive immune cells.

Authors

Min-Hee Oh, Im-Hong Sun, Liang Zhao, Robert D. Leone, Im-Meng Sun, Wei Xu, Samuel L. Collins, Ada J. Tam, Richard L. Blosser, Chirag H. Patel, Judson M. Englert, Matthew L. Arwood, Jiayu Wen, Yee Chan-Li, Lukáš Tenora, Pavel Majer, Rana Rais, Barbara S. Slusher, Maureen R. Horton, Jonathan D. Powell

×

Figure 4

Glutamine antagonism induces reprogramming of TAMs from a suppressive to a proinflammatory phenotype.

Options: View larger image (or click on image) Download as PowerPoint
Glutamine antagonism induces reprogramming of TAMs from a suppressive to...
(A) Percentages of TAMs from vehicle- or JHU083-treated 4T1 tumor–bearing mice (on day 17). (B) Volcano plot showing significant changes in gene expression (red) from RNA-Seq analysis on NT and JHU083-treated TAMs (CD11b+F4/80+7AAD–Ly6C–Ly6G–CD8–) from 4T1 tumor–bearing mice (on day 14). q < 0.05. (C) Gene set enrichment analysis (GSEA) plot of phagocytic vesicle and pattern recognition receptor signaling activity–related genes in NT versus JHU083 on TAMs. Enrichment scores in the gene set are shown. (D) Normalized gene expression from RNA-Seq analysis of NT (black) and JHU083-treated (red) TAMs from 4T1 tumor–bearing mice (on day 17). All differences in gene expression are significant (q < 0.05). (E) Representative histograms and summary graphs of TLR4, MHCII, CD86, CD80, and iNOS expression on TAMs. (F) Tumor-infiltrating leukocytes were harvested on day 17 from 4T1 tumor–bearing mice treated with or without JHU083. Cells were incubated with GolgiPlug in the presence or absence of LPS for 9 hours ex vivo. Percentages of TNF+ cells were analyzed by flow cytometry (left). Geometric mean fluorescence intensity (gMFI) of TNF from TNF+ cells (right). (G) Correlation of the percentage TNF-secreting TAMs after stimulation with respect to tumor weight (left). 4T1 tumor–bearing mice were treated with JHU083 every day and i.p. injected with isotype antibody or 100 μg anti-TNF antibody (depleting) twice per week starting on day 7 after tumor inoculation (right). Data are from 1 experiment with 5 mice per group (A–D) or from 3 independent experiments with 5 to 10 mice per group (E–G) and are presented as the mean ± SD. NS, not significant. *P < 0.05; ****P < 0.001 by Mann-Whitney test (A), unpaired t test (E), 1-way ANOVA with Tukey’s multiple-comparisons post hoc test (F), Spearman’s correlation (G, left), or 2-way ANOVA with Sidak’s multiple-comparisons test (G, right).