Immunotherapies that target cancer by utilizing a patient’s own immune system have been shown to be effective in certain cancers, with multiple potential targets being identified over numerous case studies. However, the tumor microenvironment (TME) has its own defenses, which can lead to immunosuppression and exhaustion of cytotoxic T cells, inhibiting efficacy of T cell-based therapies. For instance, cancer cells often express the ligand for the inhibitory programmed cell death protein 1 (PD-L1 and PD-1, respectively), a receptor expressed on T cells whose binding inhibits normal effector functions. Blocking the interaction between PD-1 and its ligand has shown to be an effective anti-cancer therapy. Despite success, efficacy of this approach is limited to only certain types of tumors and is often associated with drug-related toxicities.
T cell receptors (TCRs) can be engineered to target specific antigens, ideally those highly expressed exclusively on cancer cells, to increase the specificity of the therapy. The Preferentially Expressed Antigen in Melanoma (PRAME) has previously been shown to be highly expressed in multiple types of cancers with limited expression in healthy tissue mainly restricted to the testis, making it a viable target antigen. Furthermore, PD-L1 expression of cancer cells can be exploited by combining the extracellular PD-1 domain with a stimulatory signaling molecule, such as 4-1BB. Targeting both antigens simultaneously could result in increased potency and improved efficacy of immunotherapies. Characterizing how TCR-based therapies function through the measurement of cytokine secretions at single cell level is critical to predicting cell potency and persistence. Single-cell functional proteomics can identify highly polyfunctional “superpowered” engineered T cells to guide more effective therapeutic product development for better clinical outcomes.
Co-Stimulation to Increase Potency of TCR-T Therapies
In a recent study published in Cancers, researchers compared TCR-Ts targeted to PRAME with those co-expressing receptors for PRAME and PD-1 with the chimeric stimulatory 4-1BB domain. When tested in previous studies against different types of melanomas, the tumors with high expression of PD-L1 were unresponsive to PRAME-targeted TCR-Ts; however, when treated with TCR-Ts co-expressing PRAME-specific T-cell receptor in combination with the chimeric PD-1-4-1BB costimulatory receptor, survival was increased and tumors were eliminated in the majority of subjects.
To understand this increase in potency, the researchers used IsoPlexis’ single-cell functional phenotyping platform. IsoPlexis’ proprietary Polyfunctional strength index (PSI), a metric that captures the percentage of single T cells secreting at least two cytokines and their respective signaling intensities, was used to compare the PRAME-targeted TCR-Ts and the TCR-Ts co-expressing PRAME-targeted receptor and the PD-1-4-1BB chimera. Researchers observed that co-expressing TCR-Ts had a higher PSI compared to those without PD1-41BB. Further characterization of cytokine secretions revealed that the co-expressing TCR-Ts secreted more effector and stimulatory cytokines, revealing a possible mechanism for the increased potency observed in the in vivo experiments. The researchers also noted that regulatory and inflammatory cytokine release was low, suggesting that the co-expressing TCR-Ts are less likely to cause autoinflammation.
Using Single-Cell Characterization to Better Understand Engineered T Cell Therapies
This study demonstrates, for the first time, how co-expressing engineered PRAME-specific T-cell receptor and chimeric PD-1-4-1BB can increase the potency of anti-cancer cell therapies. Moreover, the use of single-cell functional proteomics demonstrated that this increased potency was associated with increased polyfunctionality of the engineered T-cells. Based on these results, PSI can be used as a biomarker of potency and response to evaluate the anti-cancer potential of engineered T-cell products. As such, the functional phenotyping of cell therapies through single-cell analysis can help to evaluate therapies, identify mechanisms of action, and determine the most potent treatments in pre-clinical models.
