Clinically relevant immunological biomarkers that discriminate between diverse hypofunctional states of tumor-associated CD8 ⁺ T cells remain disputed. Using multiomics analysis of CD8 ⁺ T cell features across multiple patient cohorts and tumor types, we identified tumor niche–dependent exhausted and other types of hypofunctional CD8 ⁺ T cell states. CD8 ⁺ T cells in “supportive” niches, like melanoma or lung cancer, exhibited features of tumor reactivity–driven exhaustion (CD8 ⁺ T _EX ). These included a proficient effector memory phenotype, an expanded T cell receptor (TCR) repertoire linked to effector exhaustion signaling, and a cancer-relevant T cell–activating immunopeptidome composed of largely shared cancer antigens or neoantigens. In contrast, “nonsupportive” niches, like glioblastoma, were enriched for features of hypofunctionality distinct from canonical exhaustion. This included immature or insufficiently activated T cell states, high wound healing signatures, nonexpanded TCR repertoires linked to anti-inflammatory signaling, high T cell–recognizable self-epitopes, and an antiproliferative state linked to stress or prodeath responses. In situ spatial mapping of glioblastoma highlighted the prevalence of dysfunctional CD4 ⁺ :CD8 ⁺ T cell interactions, whereas ex vivo single-cell secretome mapping of glioblastoma CD8 ⁺ T cells confirmed negligible effector functionality and a promyeloid, wound healing–like chemokine profile. Within immuno-oncology clinical trials, anti–programmed cell death protein 1 (PD-1) immunotherapy facilitated glioblastoma’s tolerogenic disparities, whereas dendritic cell (DC) vaccines partly corrected them. Accordingly, recipients of a DC vaccine for glioblastoma had high effector memory CD8 ⁺ T cells and evidence of antigen-specific immunity. Collectively, we provide an atlas for assessing different CD8 ⁺ T cell hypofunctional states in immunogenic versus nonimmunogenic cancers.

Many individuals with cancer are resistant to immunotherapies. Here, we identify the gene encoding the pyrimidine salvage pathway enzyme cytidine deaminase (CDA) among the top upregulated metabolic genes in several immunotherapy-resistant tumors. We show that CDA in cancer cells contributes to the uridine diphosphate (UDP) pool. Extracellular UDP hijacks immunosuppressive tumor-associated macrophages (TAMs) through its receptor P2Y₆. Pharmacologic or genetic inhibition of CDA in cancer cells (or P2Y₆ in TAMs) disrupts TAM-mediated immunosuppression, promoting cytotoxic T cell entry and susceptibility to anti-programmed cell death protein 1 (anti-PD-1) treatment in resistant pancreatic ductal adenocarcinoma (PDAC) and melanoma models. Conversely, CDA overexpression in CDA-depleted PDACs or anti-PD-1-responsive colorectal tumors or systemic UDP administration (re)establishes resistance. In individuals with PDAC, high CDA levels in cancer cells correlate with increased TAMs, lower cytotoxic T cells and possibly anti-PD-1 resistance. In a pan-cancer single-cell atlas, CDA^high cancer cells match with T cell cytotoxicity dysfunction and P2RY6^high TAMs. Overall, we suggest CDA and P2Y₆ as potential targets for cancer immunotherapy.

While immune checkpoint–based immunotherapy (ICI) shows promising clinical results in patients with cancer, only a subset of patients responds favorably. Response to ICI is dictated by complex networks of cellular interactions between malignant and nonmalignant cells. Although insights into the mechanisms that modulate the pivotal antitumoral activity of cytotoxic T cells (Tcy) have recently been gained, much of what has been learned is based on single-cell analyses of dissociated tumor samples, resulting in a lack of critical information about the spatial distribution of relevant cell types. Here, we used multiplexed IHC to spatially characterize the immune landscape of metastatic melanoma from responders and nonresponders to ICI. Such high-dimensional pathology maps showed that Tcy gradually evolve toward an exhausted phenotype as they approach and infiltrate the tumor. Moreover, a key cellular interaction network functionally linked Tcy and PD-L1+ macrophages. Mapping the respective spatial distributions of these two cell populations predicted response to anti-PD-1 immunotherapy with high confidence. These results suggest that baseline measurements of the spatial context should be integrated in the design of predictive biomarkers to identify patients likely to benefit from ICI. Significance: This study shows that spatial characterization can address the challenge of finding efficient biomarkers, revealing that localization of macrophages and T cells in melanoma predicts patient response to ICI. See related commentary by Smalley and Smalley, p. 3198

In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically into ‘brisk’, ‘non-brisk’ and ‘absent’ entailing a functional association that has never been proved. Recently, it has been shown that lymphocytic populations can be very heterogeneous, and that anti-PD-1 immunotherapy supports activated T cells. Here, we characterize the immune landscape in primary melanoma by high-dimensional single-cell multiplex analysis in tissue sections (MILAN technique) followed by image analysis, RT-PCR and shotgun proteomics. We observed that the brisk and non-brisk patterns are heterogeneous functional categories that can be further sub-classified into active, transitional or exhausted. The classification of primary melanomas based on the functional paradigm also shows correlation with spontaneous regression, and an improved prognostic value when compared to that of the brisk classification. Finally, the main inflammatory cell subpopulations that are present in the microenvironment associated with activation and exhaustion and their spatial relationships are described using neighbourhood analysis.