1396 TriTCE CPI: a novel trispecifc T cell engager platform with integrated PD-1/PD-L1 checkpoint inhibition engineered for the treatment of immunosuppressed tumors
Bibliographic record
Abstract
Background Immunosuppression in the solid tumor microenvironment (TME) is a critical obstacle that has limited the efficacy of T cell engager (TCE) immunotherapies. Though TCEs can direct T cell cytotoxicity towards tumors, T cell activation and inflammation can induce tumor cell and T cell expression of immune checkpoint proteins, such as PD-L1. This treatment-related increase in immune suppression in the TME further limits clinical responses. We have previously presented screening data on a panel of trispecific T cell engagers (TriTCEs). Preliminary mechanistic data showed enhanced antitumor activity where TriTCEs can concurrently direct T cell activity towards tumor cells while eliciting PD-1/PD-L1 checkpoint inhibition (CPI) by the addition of an affinity-engineered PD-1 domain to the TCE. Here, we present data that further characterizes and differentiates the lead TriTCE CPI formats. Methods Lead TriTCE CPI formats were screened for potency in vitro. Co-engagement of CD3, tumor-associated antigen (TAA), and PD-L1 by TriTCE CPIs was determined using on-cell binding measurements to exhausted T cells and tumor cells stimulated with IFNγ to upregulate PD-L1 and recapitulate cellular phenotypes expected to be found in an immunosuppressed TME. TriTCE CPI mediated T cell activation in the presence of PD-L1 expressing dendritic cells was assayed in co-culture. In vivo activity was determined using humanized PBMC and syngeneic mouse models. Results Lead TriTCE CPI formats were compared by assaying TAA-dependent cytotoxicity where addition of affinity-engineered PD-1 increased potency in vitro. Format-dependent differences in PD-1 location on the TriTCE and the presence of one or two α-TAA binding arms was found to enhance avidity-driven binding, which translated into increased T cell-dependent cytotoxicity compared to clinical benchmark controls. Lead TriTCE CPIs had broad anti-tumor activity across tumor cell lines with varying TAA and PD-L1 expression levels. In vivo testing of lead TriTCE CPI formats demonstrated tumor growth inhibition and enabled preliminary assessment of toxicity. A threshold for tolerability of affinity-engineered PD-1 was identified in humanized syngeneic mouse model. Conclusions Our next-generation TriTCE CPIs aim to leverage PD-L1-mediated immunosuppression for enhanced avidity-driven tumor cell targeting and CPI in the TME to improve T cell responses in solid tumors. Addition of an affinity-engineered PD-1 to the TCE enhanced activity across multiple tumor cell lines compared to a bispecific TCE, supporting that TriTCE CPIs can be active against primary and acquired PD-L1 resistance mechanisms. Humanized immunocompetent syngeneic mouse models suggest a widened therapeutic window based on measures of tumor regression with a favorable safety profile. Ethics Approval The protocol and procedures involving the care and use of animals in these studies was conducted in accordance with the regulations of the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) and were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC; CrownBio, Jackson ImmunoResearch).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".