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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

2023· article· en· W4388074720 on OpenAlexaff
Meghan M. Verstraete, Maya C. Poffenberger, Matteo Zago, Veronica Luu, Brenda Ma, Nichole Escalante, Janessa Li, Diego Perez Escanda, Siran Cao, Sifa Arrafi, Yun Peng, Anna von Rossum, Genevieve Desjardins, Nina E. Weisser, Thomas Spreter von Kreudenstein

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2023
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsZymeworks (Canada)
Fundersnot available
KeywordsCancer researchTumor microenvironmentPD-L1T cellImmunotherapyImmune checkpointCytotoxicityCytotoxic T cellImmune systemChemistryCancer immunotherapyIn vitroBiologyImmunologyTumor cellsBiochemistry

Abstract

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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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.040
GPT teacher head0.269
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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