LAG3+ CD8+ T cell Subset Boosts Bispecific Antibody Armed Activated T Cell Cytotoxicity Directed at Hormone Receptor+ Breast Cancers
Authors: Barnes Robert Weldon , Thakur Archana , Onengut-Gumuscu Suna , Lum Lawrence G. , Dolatshahi Sepideh 
Published: January 2025

Tumor clearance by T cells is impaired by insufficient tumor antigen recognition, insufficient tumor infiltration, and the immunosuppressive tumor microenvironment (TME). Although targeted T cell therapy circumvents failures in tumor antigen recognition, suppression by the TME and failure to infiltrate the tumor can hinder tumor clearance by these T cells. Checkpoint inhibitors (CPI) promises to reverse T cell suppression in the TME and can be combined with bispecific antibody armed T cell (BATs) therapy to improve clinical outcomes. CPIs require the target pathway of inhibition to be active in the TME to elicit a therapeutic response. We hypothesize that adoptively transferred T cell function may be improved by the addition of CPI if the inhibitory pathway is functionally active. This study develops a kinetic-dynamic model of serial killing of hormone receptor-positive (HR+) breast cancer cells mediated by BATs using single-cell transcriptomic and temporal protein data to identify T cell phenotypes and quantify inhibitory receptor expression. LAG3, PD-1, and TIGIT were identified as inhibitory receptors expressed by cytotoxic effector CD8 BATs upon exposure to HR+ breast cancer cell lines. These data were combined with real-time tumor cytotoxicity data in a multivariate statistical analysis framework to predict the relevant contributions of T cells expressing each receptor to tumor reduction. A mechanistic kinetic-dynamic mathematical model was developed and parametrized using protein expression and cytotoxicity data for in silico validation of the findings of the multivariate statistical analysis. The model corroborated the predictions of the multivariate statistical analysis which identified LAG3+ BATs as the primary effectors, while TIGIT expression dampened cytotoxic function. These results inform CPI selection for BATs combination therapy and provide a framework to maximize BATs anti-tumor function against HR+ cancers. Our model provides a means to optimize targets for CPIs used in combination with BATs in clinical strategies.

What is already known on this topic

Bispecific antibody armed T cell (BATs) therapies are adoptive T cell therapies that can effectively reroute T cell cytotoxicity toward cancerous cells, but lack consistent and durable anti-tumor responses. Checkpoint proteins expressed on the surface of activated T cells dampen immune responses and can be overstimulated in solid tumors to hamper tumor clearance by T cells. Checkpoint inhibitor drugs can improve T cell anti-tumor response by blocking checkpoint protein signaling but are only effective if the targeted checkpoint protein is expressed on the T cell and activated in the tumor microenvironment, highlighting an opportunity to enhance BAT efficacy by combining treatment with synergistic CPI.

What this study adds

This study characterizes dynamic, time-resolved patterns in checkpoint protein expression by breast cancer-targeting adoptive T cells and predicts the significance of high-prevalence checkpoint proteins on T cell function. It also demonstrates the use of multivariate statistic and mathematical modeling toward rational design of targets and timing strategies for synergistic combination therapies.

How this study might affect research, practice, or policy

The output of this study provides justification for therapeutic strategies combining adoptive T cell therapies with checkpoint inhibitor drugs targeting TIGIT and LAG3 as a means of improving patient responses in HER2-/HR+ breast cancers.