Tim-3 adaptor protein Bat3 is a molecular checkpoint of T cell terminal differentiation and exhaustion.

T cell exhaustion has been associated with poor prognosis in persistent viral infection and cancer. Conversely, in the context of autoimmunity, T cell exhaustion has been favorably correlated with long-term clinical outcome. Understanding the development of exhaustion in autoimmune settings may provide underlying principles that can be exploited to quell autoreactive T cells. Here, we demonstrate that the adaptor molecule Bat3 acts as a molecular checkpoint of T cell exhaustion, with deficiency of Bat3 promoting a profound exhaustion phenotype, suppressing autoreactive T cell-mediated neuroinflammation. Mechanistically, Bat3 acts as a critical mTORC2 inhibitor to suppress Akt function. As a result, Bat3 deficiency leads to increased Akt activity and FoxO1 phosphorylation, indirectly promoting Prdm1 expression. Transcriptional analysis of Bat3 -/- T cells revealed up-regulation of dysfunction-associated genes, concomitant with down-regulation of genes associated with T cell effector function, suggesting that absence of Bat3 can trigger T cell dysfunction even under highly proinflammatory autoimmune conditions.

Single-cell analyses identify circulating anti-tumor CD8 T cells and markers for their enrichment.

The ability to monitor anti-tumor CD8+ T cell responses in the blood has tremendous therapeutic potential. Here, we used paired single-cell RNA and TCR sequencing to detect and characterize "tumor-matching" (TM) CD8+ T cells in the blood of mice with MC38 tumors or melanoma patients using the TCR as a molecular barcode. TM cells showed increased activation compared with nonmatching T cells in blood and were less exhausted than matching cells in tumors. Importantly, PD-1, which has been used to identify putative circulating anti-tumor CD8+ T cells, showed poor sensitivity for identifying TM cells. By leveraging the transcriptome, we identified candidate cell surface markers for TM cells in mice and patients and validated NKG2D, CD39, and CX3CR1 in mice. These data show that the TCR can be used to identify tumor-relevant cells for characterization, reveal unique transcriptional properties of TM cells, and develop marker panels for tracking and analysis of these cells.

A bilateral tumor model identifies transcriptional programs associated with patient response to immune checkpoint blockade.

Immune checkpoint blockade (ICB) is efficacious in many diverse cancer types, but not all patients respond. It is important to understand the mechanisms driving resistance to these treatments and to identify predictive biomarkers of response to provide best treatment options for all patients. Here we introduce a resection and response-assessment approach for studying the tumor microenvironment before or shortly after treatment initiation to identify predictive biomarkers differentiating responders from nonresponders. Our approach builds on a bilateral tumor implantation technique in a murine metastatic breast cancer model (E0771) coupled with anti-PD-1 therapy. Using our model, we show that tumors from mice responding to ICB therapy had significantly higher CD8+ T cells and fewer Gr1+CD11b+ myeloid-derived suppressor cells (MDSCs) at early time points following therapy initiation. RNA sequencing on the intratumoral CD8+ T cells identified the presence of T cell exhaustion pathways in nonresponding tumors and T cell activation in responding tumors. Strikingly, we showed that our derived response and resistance signatures significantly segregate patients by survival and associate with patient response to ICB. Furthermore, we identified decreased expression of CXCR3 in nonresponding mice and showed that tumors grown in Cxcr3-/- mice had an elevated resistance rate to anti-PD-1 treatment. Our findings suggest that the resection and response tumor model can be used to identify response and resistance biomarkers to ICB therapy and guide the use of combination therapy to further boost the antitumor efficacy of ICB.