Failure of T cells to protect against cancer is thought to result from lack of antigen recognition, chronic activation, and/or suppression by other cells. Using a mouse sarcoma model, we show that glucose consumption by tumors metabolically restricts T cells, leading to their dampened mTOR activity, glycolytic capacity, and IFN-γ production, thereby allowing tumor progression. We show that enhancing glycolysis in an antigenic ‘regressor’ tumor is sufficient to override the protective ability of T cells to control tumor growth. We also show that checkpoint blockade antibodies against CTLA-4, PD-1, and PD-L1, which are used clinically, restore glucose in tumors, permitting T cell glycolysis and IFN-γ production. Furthermore, we found that blocking PD-L1 directly on tumors dampens glycolysis by inhibiting mTOR activity and decreasing expression of glycolysis enzymes, reflecting a role for PD-L1 in tumor glucose utilization. Our results establish that tumor-imposed metabolic restrictions can mediate T cell hyporesponsiveness during cancer.

The immune system plays key roles in determining the fate of developing cancers by not only functioning as a tumour promoter facilitating cellular transformation, promoting tumour growth and sculpting tumour cell immunogenicity1–6, but also as an extrinsic tumour suppressor that either destroys developing tumours or restrains their expansion1,2,7. Yet clinically apparent cancers still arise in immunocompetent individuals in part as a consequence of cancer induced immunosuppression. In many individuals, immunosuppression is mediated by Cytotoxic T-Lymphocyte Associated Antigen-4 (CTLA-4) and Programmed Death-1 (PD-1), two immunomodulatory receptors expressed on T cells8,9. Monoclonal antibody (mAb) based therapies targeting CTLA-4 and/or PD-1 (checkpoint blockade) have yielded significant clinical benefits—including durable responses—to patients with different malignancies10–13. However, little is known about the identity of the tumour antigens that function as the targets of T cells activated by checkpoint blockade immunotherapy and whether these antigens can be used to generate vaccines that are highly tumour-specific. Herein, we use genomics and bioinformatics approaches to identify tumour-specific mutant proteins as a major class of T cell rejection antigens following αPD-1 and/or αCTLA-4 therapy of mice bearing progressively growing sarcomas and show that therapeutic synthetic long peptide (SLP) vaccines incorporating these mutant epitopes induce tumour rejection comparably to checkpoint blockade immunotherapy. Whereas, mutant tumour antigen-specific T cells are present in progressively growing tumours, they are reactivated following treatment with αPD-1- and/or αCTLA-4 and display some overlapping but mostly treatment-specific transcriptional profiles rendering them capable of mediating tumour rejection. These results reveal that tumour-specific mutant antigens (TSMA) are not only important targets of checkpoint blockade therapy but also can be used to develop personalized cancer-specific vaccines and to probe the mechanistic underpinnings of different checkpoint blockade treatments.

The principles of cancer immunoediting have set the foundations for understanding the dual host-protective and tumor sculpting actions of immunity on cancer and establishing the basis for novel individualized cancer immunotherapies. During cancer immunoediting, the host immune system shapes tumor fate in three phases through the activation of innate and adaptive immune mechanisms. In the first phase, Elimination, transformed cells are destroyed by a competent immune system. Sporadic tumor cells that manage to survive immune destruction may then enter an Equilibrium phase where editing occurs. The Escape phase represents the third and final phase of the process, where immunologically sculpted tumors begin to grow progressively, become clinically apparent and establish an immunosuppressive tumor microenvironment. This review focuses on important recent developments that have enhanced our understanding of each phase of the cancer immunoediting process, summarizes the discovery of new predictive and prognostic biomarkers and discusses development of novel and objectively effective cancer immunotherapies.

AUTHOR CONTRIBUTIONS E.A. conceived and designed the experiments, collected the data, performed and interpreted the analyses, and wrote the manuscript. D.M.L and A.P.M planned experiments, and collected and analyzed data. I.K. conceived of and designed the hmMHC algorithm and performed analyses using it, and wrote the methodological description found in this manuscript. M.D. generated the KP9025 sarcoma cell line. A.M.L provided technical assistance and helped plan experiments using MHC class II tetramers. W.M. and C.F.L. planned, performed and analyzed mass spectrometry experiments. E.E. assisted with bioinformatics analyses. A.N.V. assisted with the generation of the CD4 + T cell hybridomas, and helped design and perform experiments using them. D.R. designed, collected, and analyzed data for experiments involving multi-color flow cytometry. J.P.W. provided technical support for MHC class I tetramer staining. M.M.G assisted in experiment planning. R.F.V.M. collected and analyzed data for experiments involving multi-color flow cytometry. C.D.A., K.C.F.S. and J.M.W. provided technical assistance throughout the study. A.C. collected data. K.W.W. provided mITGB1-MHC class II monomers and provided assistance in experimental design. T.J. provided support in experimental design and data analysis regarding the KP9025 sarcoma line. M.N.A. conceived and designed the hmMHC algorithm and provided bioinformatics support. E.R.U. provided assistance in experimental design. R.D.S. conceived experiments, interpreted data, and wrote the manuscript. All authors contributed to manuscript revision. R.D.S. is a cofounder, scientific advisory board member, stockholder, and royalty recipient of Jounce Therapeutics and Neon Therapeutics and is a scientific advisory board member for A2 Biotherapeutics, BioLegend, Codiak Biosciences, Constellation Pharmaceuticals, NGM Biopharmaceuticals and Sensei Biotherapeutics. K.W.W. serves on the scientific advisory board of Tscan Therapeutics and Nextechinvest and receives sponsored research funding from Bristol-Myers Squibb and Novartis; these activities are not related to the findings described in this publication. T.J. is a member of the Board of Directors of Amgen and Thermo Fisher Scientific. He is also a co-Founder of Dragonfly Therapeutics and T2 Biosystems. T.J. serves on the Scientific Advisory Board of Dragonfly Therapeutics, SQZ Biotech, and Skyhawk Therapeutics. None of these affiliations represent a conflict of interest with respect to the design or execution of this study or interpretation of data presented in this manuscript. Dr. Jacks's laboratory currently also receives funding from the Johnson & Johnson Lung Cancer Initiative and Calico, but this funding did not support the research described in this manuscript. DATA AVAILABILITY Nucleotide variant calls generated from cDNA capture sequencing of the T3 and KP9025 sarcoma lines and used in the prediction of antigens shown in Figure 1a, Extended Data Figure 3a-b, and Extended Data Figure 6b are available within the article as Supplem...

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Highlights d TREM2 is expressed by tumor-associated macrophages in different types of tumors d TREM2 deficiency and anti-TREM2 mAb treatment both curb tumor growth in mice d Anti-PD-1 treatment is more efficacious when TREM2 is either absent or engaged by a mAb d Modulation of TREM2 remodels the tumor macrophage landscape

SUMMARY While current immune checkpoint therapy (ICT) mainly targets lymphoid cells, it is associated with a broader remodeling of the tumor micro-environment. Here, using complementary forms of high dimensional profiling, we define differences across all hematopoietic cells from syngeneic mouse tumors during unrestrained tumor growth or effective ICT. Unbiased assessment of gene expression of tumor infiltrating cells by single cell RNA sequencing (scRNAseq) and longitudinal assessment of cellular protein expression by mass cytometry (CyTOF) revealed significant remodeling of both the lymphoid and myeloid intratumoral compartments. Surprisingly, we observed multiple subpopulations of monocytes/macrophages, distinguishable by the markers CD206, CX3CR1, CD1d and iNOS, that change over time during ICT in a manner partially dependent on IFNγ. Our data support the hypothesis that this macrophage polarization/activation results from effects on circulatory monocytes and early macrophages entering tumors, rather than on pre-polarized mature intratumoral macrophages.

Antibody blockade of Programmed Death-1 (PD-1) or its ligand, PD-L1, has led to unprecedented therapeutic responses in certain tumor-bearing individuals, but PD-L1 expression’s prognostic value in stratifying cancer patients for such treatment remains unclear. Reports conflict on the significance of correlations between PD-L1 on tumor cells and positive clinical outcomes to PD-1/PD-L1 blockade. We investigated this issue using genomically-related, clonal subsets from the same methylcholanthrene-induced sarcoma: a highly immunogenic subset that is spontaneously eliminated in vivo by adaptive immunity and a less immunogenic subset that forms tumors in immunocompetent mice, but is sensitive to PD-1/PD-L1 blockade therapy. Using CRISPR/Cas9-induced loss-of-function approaches and overexpression gain-of-function techniques, we confirmed that PD-L1 on tumor cells is key to promoting tumor escape. Additionally, the capacity of PD-L1 to suppresses antitumor responses was inversely proportional to tumor cell antigenicity. PD-L1 expression on host cells, particularly tumor-associated macrophages (TAMs), was also important for tumor immune escape. We demonstrated that induction of PD-L1 on tumor cells was interferon gamma (IFNγ)-dependent and transient, but PD-L1 induction on TAMs was of greater magnitude, only partially IFNγ dependent, and was stable over time. Thus, PD-L1 expression on either tumor cells or host immune cells could lead to tumor escape from immune control, indicating that total PD-L1 expression in the immediate tumor microenvironment may represent a more accurate biomarker for predicting response to PD-1/PD-L1 blockade therapy, compared to monitoring PD-L1 expression on tumor cells alone.