LAG-3 and PD-1 synergize on CD8+ T cells to drive T cell exhaustion and hinder autocrine IFN-γ-dependent anti-tumor immunity.

Overcoming immune-mediated resistance to PD-1 blockade remains a major clinical challenge. Enhanced efficacy has been demonstrated in melanoma patients with combined nivolumab (anti-PD-1) and relatlimab (anti-LAG-3) treatment, the first in its class to be FDA approved. However, how these two inhibitory receptors synergize to hinder anti-tumor immunity remains unknown. Here, we show that CD8+ T cells deficient in both PD-1 and LAG-3, in contrast to CD8+ T cells lacking either receptor, mediate enhanced tumor clearance and long-term survival in mouse models of melanoma. PD-1- and LAG-3-deficient CD8+ T cells were transcriptionally distinct, with broad TCR clonality and enrichment of effector-like and interferon-responsive genes, resulting in enhanced IFN-γ release indicative of functionality. LAG-3 and PD-1 combined to drive T cell exhaustion, playing a dominant role in modulating TOX expression. Mechanistically, autocrine, cell-intrinsic IFN-γ signaling was required for PD-1- and LAG-3-deficient CD8+ T cells to enhance anti-tumor immunity, providing insight into how combinatorial targeting of LAG-3 and PD-1 enhances efficacy.

Metabolic waypoints during T cell differentiation.

This Review explores the interplay between T cell activation and cell metabolism and highlights how metabolites serve two pivotal functions in shaping the immune response. Traditionally, T cell activation has been characterized by T cell antigen receptor-major histocompatibility complex interaction (signal 1), co-stimulation (signal 2) and cytokine signaling (signal 3). However, recent research has unveiled the critical role of metabolites in this process. Firstly, metabolites act as signal propagators that aid in the transmission of core activation signals, such as specific lipid species that are crucial at the immune synapse. Secondly, metabolites also function as unique signals that influence immune differentiation pathways, such as amino acid-induced mTORC1 signaling. Metabolites also play a substantial role in epigenetic remodeling, by directly modifying histones, altering gene expression and influencing T cell behavior. This Review discusses how T cells integrate nutrient sensing with activating stimuli to shape their differentiation and sensitivity to metabolites. We underscore the integration of immunological and metabolic inputs in T cell function and suggest that metabolite availability is a fundamental determinant of adaptive immune responses.

Treatment with oncolytic vaccinia virus infects tumor-infiltrating regulatory and exhausted T cells.

BACKGROUND: Oncolytic viruses (OVs) are an attractive way to increase immune infiltration into an otherwise cold tumor. While OVs are engineered to selectively infect tumor cells, there is evidence that they can infect other non-malignant cells in the tumor. We sought to determine if oncolytic vaccinia virus (VV) can infect lymphocytes in the tumor and, if so, how this was linked to therapeutic efficacy. METHODS: To investigate infection of lymphocytes by VV, we used a GFP reporting VV in a murine head and neck squamous cell carcinoma tumor model. We also performed in vitro infection studies to determine the mechanism and consequences of VV lymphocyte infection by VV. RESULTS: Our findings show that VV carries the capacity to infect proportions of immune cells, most notably T cells, after intratumoral treatment. Notably, this infection is preferential to terminally differentiated T cells that tend to reside in hypoxia. Infection of T cells leads to both virus production by the T cells as well as the eventual death of these cells. Using a mouse model which overexpressed the antiapoptotic protein Bcl2 in all T cells, we found that reducing T cell death following VV infection in MEER tumors reduced the number of complete regressions and reduced survival time compared with littermate control mice. CONCLUSIONS: These findings suggest that OVs are capable of infecting more than just malignant cells after treatment, and that this infection may be an important part of the OV mechanism. We found that exhausted CD8+ T cells and regulatory CD4+ T cells were preferentially infected at early timepoints after treatment and subsequently died. When cell death in T cells was mitigated, mice responded poorly to VV treatment, suggesting that the deletion of these populations is critical to the therapeutic response to VV.

An IRF2-Expressing Oncolytic Virus Changes the Susceptibility of Tumor Cells to Antitumor T Cells and Promotes Tumor Clearance.

IFN regulatory factor 1 (IRF1) can promote antitumor immunity. However, we have shown previously that in the tumor cell, IRF1 can promote tumor growth, and IRF1-deficient tumor cells exhibit severely restricted tumor growth in several syngeneic mouse tumor models. Here, we investigate the potential of functionally modulating IRF1 to reduce tumor progression and prolong survival. Using inducible IRF1 expression, we established that it is possible to regulate IRF1 expression to modulate tumor progression in established B16-F10 tumors. Expression of IRF2, which is a functional antagonist of IRF1, downregulated IFNγ-induced expression of inhibitory ligands, upregulated MHC-related molecules, and slowed tumor growth and extended survival. We characterized the functional domain(s) of IRF2 needed for this antitumor activity, showing that a full-length IRF2 was required for its antitumor functions. Finally, using an oncolytic vaccinia virus as a delivery platform, we showed that IRF2-expressing vaccinia virus suppressed tumor progression and prolonged survival in multiple tumor models. These results suggest the potency of targeting IRF1 and using IRF2 to modulate immunotherapy.

Evaluation of radiomics as a predictor of efficacy and the tumor immune microenvironment in anti-PD-1 mAb treated recurrent/metastatic squamous cell carcinoma of the head and neck patients.

BACKGROUND: We retrospectively evaluated radiomics as a predictor of the tumor microenvironment (TME) and efficacy with anti-PD-1 mAb (IO) in R/M HNSCC. METHODS: Radiomic feature extraction was performed on pre-treatment CT scans segmented using 3D slicer v4.10.2 and key features were selected using LASSO regularization method to build classification models with XGBoost algorithm by incorporating cross-validation techniques to calculate accuracy, sensitivity, and specificity. Outcome measures evaluated were disease control rate (DCR) by RECIST 1.1, PFS, and OS and hypoxia and CD8 T cells in the TME. RESULTS: Radiomics features predicted DCR with accuracy, sensitivity, and specificity of 76%, 73%, and 83%, for OS 77%, 86%, 70%, PFS 82%, 75%, 89%, and in the TME, for high hypoxia 80%, 88%, and 72% and high CD8 T cells 91%, 83%, and 100%, respectively. CONCLUSION: Radiomics accurately predicted the efficacy of IO and features of the TME in R/M HNSCC. Further study in a larger patient population is warranted.