Obesity induces PD-1 on macrophages to suppress anti-tumour immunity.

Obesity is a leading risk factor for progression and metastasis of many cancers1,2, yet can in some cases enhance survival3-5 and responses to immune checkpoint blockade therapies, including anti-PD-1, which targets PD-1 (encoded by PDCD1), an inhibitory receptor expressed on immune cells6-8. Although obesity promotes chronic inflammation, the role of the immune system in the obesity-cancer connection and immunotherapy remains unclear. It has been shown that in addition to T cells, macrophages can express PD-19-12. Here we found that obesity selectively induced PD-1 expression on tumour-associated macrophages (TAMs). Type I inflammatory cytokines and molecules linked to obesity, including interferon-γ, tumour necrosis factor, leptin, insulin and palmitate, induced macrophage PD-1 expression in an mTORC1- and glycolysis-dependent manner. PD-1 then provided negative feedback to TAMs that suppressed glycolysis, phagocytosis and T cell stimulatory potential. Conversely, PD-1 blockade increased the level of macrophage glycolysis, which was essential for PD-1 inhibition to augment TAM expression of CD86 and major histocompatibility complex I and II molecules and ability to activate T cells. Myeloid-specific PD-1 deficiency slowed tumour growth, enhanced TAM glycolysis and antigen-presentation capability, and led to increased CD8+ T cell activity with a reduced level of markers of exhaustion. These findings show that obesity-associated metabolic signalling and inflammatory cues cause TAMs to induce PD-1 expression, which then drives a TAM-specific feedback mechanism that impairs tumour immune surveillance. This may contribute to increased cancer risk yet improved response to PD-1 immunotherapy in obesity.

Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms.

Intratumoral heterogeneity (ITH) can promote cancer progression and treatment failure, but the complexity of the regulatory programs and contextual factors involved complicates its study. To understand the specific contribution of ITH to immune checkpoint blockade (ICB) response, we generated single cell-derived clonal sublines from an ICB-sensitive and genetically and phenotypically heterogeneous mouse melanoma model, M4. Genomic and single cell transcriptomic analyses uncovered the diversity of the sublines and evidenced their plasticity. Moreover, a wide range of tumor growth kinetics were observed in vivo , in part associated with mutational profiles and dependent on T cell-response. Further inquiry into melanoma differentiation states and tumor microenvironment (TME) subtypes of untreated tumors from the clonal sublines demonstrated correlations between highly inflamed and differentiated phenotypes with the response to anti-CTLA-4 treatment. Our results demonstrate that M4 sublines generate intratumoral heterogeneity at both levels of intrinsic differentiation status and extrinsic TME profiles, thereby impacting tumor evolution during therapeutic treatment. These clonal sublines proved to be a valuable resource to study the complex determinants of response to ICB, and specifically the role of melanoma plasticity in immune evasion mechanisms.

Differential Effects of Glutamine Inhibition Strategies on Antitumor CD8 T Cells.

Activated T cells undergo metabolic reprogramming to meet anabolic, differentiation, and functional demands. Glutamine supports many processes in activated T cells, and inhibition of glutamine metabolism alters T cell function in autoimmune disease and cancer. Multiple glutamine-targeting molecules are under investigation, yet the precise mechanisms of glutamine-dependent CD8 T cell differentiation remain unclear. We show that distinct strategies of glutamine inhibition by glutaminase-specific inhibition with small molecule CB-839, pan-glutamine inhibition with 6-diazo-5-oxo-l-norleucine (DON), or by glutamine-depleted conditions (No Q) produce distinct metabolic differentiation trajectories in murine CD8 T cells. T cell activation with CB-839 treatment had a milder effect than did DON or No Q treatment. A key difference was that CB-839-treated cells compensated with increased glycolytic metabolism, whereas DON and No Q-treated cells increased oxidative metabolism. However, all glutamine treatment strategies elevated CD8 T cell dependence on glucose metabolism, and No Q treatment caused adaptation toward reduced glutamine dependence. DON treatment reduced histone modifications and numbers of persisting cells in adoptive transfer studies, but those T cells that remained could expand normally upon secondary Ag encounter. In contrast, No Q-treated cells persisted well yet demonstrated decreased secondary expansion. Consistent with reduced persistence, CD8 T cells activated in the presence of DON had reduced ability to control tumor growth and reduced tumor infiltration in adoptive cell therapy. Overall, each approach to inhibit glutamine metabolism confers distinct effects on CD8 T cells and highlights that targeting the same pathway in different ways can elicit opposing metabolic and functional outcomes.

Functional Overlap of Inborn Errors of Immunity and Metabolism Genes Define T Cell Immunometabolic Vulnerabilities.

Inborn Errors of Metabolism (IEM) and Immunity (IEI) are Mendelian diseases in which complex phenotypes and patient rarity can limit clinical annotations. Few genes are assigned to both IEM and IEI, but immunometabolic demands suggest functional overlap is underestimated. We applied CRISPR screens to test IEM genes for immunologic roles and IEI genes for metabolic effects and found considerable crossover. Analysis of IEM showed N-linked glycosylation and the de novo hexosamine synthesis enzyme, Gfpt1 , are critical for T cell expansion and function. Interestingly, Gfpt1 -deficient T H 1 cells were more affected than T H 17 cells, which had increased Nagk for salvage UDP-GlcNAc synthesis. Screening IEI genes showed the transcription factor Bcl11b promotes CD4 + T cell mitochondrial activity and Mcl1 expression necessary to prevent metabolic stress. These data illustrate a high degree of functional overlap of IEM and IEI genes and point to potential immunometabolic mechanisms for a previously unappreciated set of these disorders. HIGHLIGHTS: Inborn errors of immunity and metabolism have greater overlap than previously known Gfpt1 deficiency causes an IEM but also selectively regulates T cell subset fate Loss of Bcl11b causes a T cell deficiency IEI but also harms mitochondrial function Many IEM may have immune defects and IEI may be driven by metabolic mechanisms.

Elevated transferrin receptor impairs T cell metabolism and function in systemic lupus erythematosus.

T cells in systemic lupus erythematosus (SLE) exhibit multiple metabolic abnormalities. Excess iron can impair mitochondria and may contribute to SLE. To gain insights into this potential role of iron in SLE, we performed a CRISPR screen of iron handling genes on T cells. Transferrin receptor (CD71) was identified as differentially critical for TH1 and inhibitory for induced regulatory T cells (iTregs). Activated T cells induced CD71 and iron uptake, which was exaggerated in SLE-prone T cells. Cell surface CD71 was enhanced in SLE-prone T cells by increased endosomal recycling. Blocking CD71 reduced intracellular iron and mTORC1 signaling, which inhibited TH1 and TH17 cells yet enhanced iTregs. In vivo treatment reduced kidney pathology and increased CD4 T cell production of IL-10 in SLE-prone mice. Disease severity correlated with CD71 expression on TH17 cells from patients with SLE, and blocking CD71 in vitro enhanced IL-10 secretion. T cell iron uptake via CD71 thus contributes to T cell dysfunction and can be targeted to limit SLE-associated pathology.