TCR-independent CD137 (4-1BB) signaling promotes CD8+-exhausted T cell proliferation and terminal differentiation

Agonist Antibodies for Cancer Immunotherapy: History, Hopes, and Challenges

Immunotherapy is among the most promising new treatment modalities to arise over the last two decades; antibody drugs are delivering immunotherapy to millions of patients with many different types of cancer. Initial success with antibody therapeutics came in the form of direct targeting or cytotoxic antibodies, such as rituximab and trastuzumab, which bind directly to tumor cells to elicit their destruction. These were followed by immunomodulatory antibodies that elicit antitumor responses by either stimulating immune cells or relieving tumor-mediated suppression. By far the most successful approach in the clinic to date has been relieving immune suppression, with immune checkpoint blockade now a standard approach in the treatment of many cancer types. Despite equivalent and sometimes even more impressive effects in preclinical models, agonist antibodies designed to stimulate the immune system have lagged behind in their clinical translation. In this review, we document the main receptors that have been targeted by agonist antibodies, consider the various approaches that have been evaluated to date, detail what we have learned, and consider how their anticancer potential can be unlocked.

CD137+ tumor infiltrating lymphocytes predicts ovarian cancer survival

OBJECTIVE

Ovarian cancer (OC) is the leading cause of death from gynecologic malignancy in the United States, and biomarkers of patient outcomes are limited. Data using immunohistochemical (IHC) analysis are mixed regarding whether and which tumor infiltrating lymphocytes (TILs) impact survival, and IHC does not adequately quantify rare cell populations, including CD137+ (4-1BB) tumor-reactive TILs. Our study investigates if a higher percentage of CD3+ CD137+ TILs is associated with improved overall survival (OS) in OC.

METHODS

Flow cytometry was performed on viably banked OC digests. Chart review and statistical analysis were performed. Forty-seven patients were included, 40 of whom were diagnosed with high-grade serous ovarian carcinoma (HGSOC), papillary serous carcinoma, or undifferentiated histology.

RESULTS

A high percentage of CD3+ CD137+ TILs correlated with improved OS (n = 40, r = 0.48, P = 0.0016). Subjects were divided into CD3+ CD137+ TIL high and low groups by the median. Subjects with high CD3+CD137+ TIL frequencies (>9.6%) had longer OS (Wilcoxon rank-sum test; P = 0.0032) and improved OS (logrank test; P = 0.007). Differences in CD3+ or CD3+ CD8+ TILs did not impact survival. CD3+ CD137+ TILs were predictive of OS regardless of germline mutation or debulking status. Analysis of subgroups including late stage HGSOC and late stage HGSOC with primary optimal cytoreduction indicated CD3+ CD137+ TILs correlated with improved OS after adjusting for age and PARP inhibitor use (P = 0.034 and P = 0.016, respectively).

CONCLUSIONS

Prevalence of CD3+ CD137+ TILs in digested OC specimens is associated with improved OS, while general TIL markers are not. CD137 has the potential to be a novel biomarker for survival in OC.

Tumour-retained activated CCR7+ dendritic cells are heterogeneous and regulate local anti-tumour cytolytic activity

Tumour dendritic cells (DCs) internalise antigen and upregulate CCR7, which directs their migration to tumour-draining lymph nodes (dLN). CCR7 expression is coupled to an activation programme enriched in regulatory molecule expression, including PD-L1. However, the spatio-temporal dynamics of CCR7+ DCs in anti-tumour immune responses remain unclear. Here, we use photoconvertible mice to precisely track DC migration. We report that CCR7+ DCs are the dominant DC population that migrate to the dLN, but a subset remains tumour-resident despite CCR7 expression. These tumour-retained CCR7+ DCs are phenotypically and transcriptionally distinct from their dLN counterparts and heterogeneous. Moreover, they progressively downregulate the expression of antigen presentation and pro-inflammatory transcripts with more prolonged tumour dwell-time. Tumour-residing CCR7+ DCs co-localise with PD-1+CD8+ T cells in human and murine solid tumours, and following anti-PD-L1 treatment, upregulate stimulatory molecules including OX40L, thereby augmenting anti-tumour cytolytic activity. Altogether, these data uncover previously unappreciated heterogeneity in CCR7+ DCs that may underpin a variable capacity to support intratumoural cytotoxic T cells.

Dual targeting of cancer metabolome and stress antigens affects transcriptomic heterogeneity and efficacy of engineered T cells

Few cancers can be targeted efficiently by engineered T cell strategies. Here, we show that γδ T cell antigen receptor (γδ TCR)-mediated cancer metabolome targeting can be combined with targeting of cancer-associated stress antigens (such as NKG2D ligands or CD277) through the addition of chimeric co-receptors. This strategy overcomes suboptimal γ9δ2 TCR engagement of αβ T cells engineered to express a defined γδ TCR (TEGs) and improves serial killing, proliferation and persistence of TEGs. In vivo, the NKG2D-CD28WT chimera enabled control only of liquid tumors, whereas the NKG2D-4-1BBCD28TM chimera prolonged persistence of TEGs and improved control of liquid and solid tumors. The CD277-targeting chimera (103-4-1BB) was the most optimal co-stimulation format, eradicating both liquid and solid tumors. Single-cell transcriptomic analysis revealed that NKG2D-4-1BBCD28TM and 103-4-1BB chimeras reprogram TEGs through NF-κB. Owing to competition with naturally expressed NKG2D in CD8+ TEGs, the NKG2D-4-1BBCD28TM chimera mainly skewed CD4+ TEGs toward adhesion, proliferation, cytotoxicity and less exhausted signatures, whereas the 103-4-1BB chimera additionally shaped the CD8+ subset toward a proliferative state.

MAIT cells confer resistance to Lenvatinib plus anti-PD1 antibodies in hepatocellular carcinoma through TNF-TNFRSF1B pathway

The combination of antiangiogenic agents and immune checkpoint inhibitors is more efficient than monotherapy in the management of hepatocellular carcinoma (HCC). Lenvatinib plus anti-PD1 antibodies have become the mainstay in HCC treatment. However, more than half the patients with HCC are non-responsive, and the mechanisms underlying drug resistance are unknown. To address this issue, we performed single-cell sequencing on samples from six HCC patients, aiming to explore cellular signals and molecular pathways related to the effect of lenvatinib plus anti-PD1 antibody treatment. GSVA analysis revealed that treatment with lenvatinib plus anti-PD1 antibody led to an increase in the TNF-NFKB pathway across all immune cell types, as compared to the non-treatment group. Mucosal-associated invariant T (MAIT) cells were found to secrete TNF, which activates TNFRSF1B on regulatory T cells, thereby promoting immunosuppression. Additionally, TNFSF9 was highly expressed in anticancer immune cells, including CD8+ effector T cells, MAIT, and γδ T cells in the treatment group. We also detected CD3+ macrophages in both HCC and pan-cancer tissues. Overall, our findings shed light on the potential mechanisms behind the effectiveness of lenvatinib plus anti-PD1 antibody treatment in HCC patients. By understanding these mechanisms better, we may be able to develop more effective treatment strategies for patients who do not respond to current therapies.

SIMVI reveals intrinsic and spatial-induced states in spatial omics data

Spatial omics analyze gene expression and interaction dynamics in relation to tissue structure and function. However, existing methods cannot model the intrinsic and spatial-induced variation in spatial omics data, thus failing to identify true spatial interaction effects. Here, we present Spatial Interaction Modeling using Variational Inference (SIMVI), an annotation-free framework that disentangles cell intrinsic and spatial-induced latent variables for modeling gene expression in spatial omics data. SIMVI enables novel downstream analyses, such as clustering and differential expression analysis based on disentangled representations, spatial effect (SE) identification, SE interpretation, and transfer learning on new measurements / modalities. We benchmarked SIMVI on both simulated and real datasets and show that SIMVI uniquely generates highly accurate SE inferences in synthetic datasets and unveils intrinsic variation in complex real datasets. We applied SIMVI to spatial omics data from diverse platforms and tissues (MERFISH human cortex / mouse liver, Slide-seqv2 mouse hippocampus, Spatial-ATAC-RNA-seq) and revealed various region-specific and cell-type-specific spatial interactions. In addition, our experiments on MERFISH human cortex and spatial-ATAC-RNA-seq showcased SIMVI's power in identifying SEs for new samples / modalities. Finally, we applied SIMVI on a newly collected CosMx melanoma dataset. Using SIMVI, we identified immune cells associated with spatial-dependent interactions and revealed the underlying spatial variations associated with patient outcomes.