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Abstract B034: CD27 is a new promising T cell co-stimulatory target for cancer immunotherapy

2023· article· en· W4389227750 on OpenAlexaboutno aff
Thierry Guillaudeux, Yulia Ovechkina, Kurt Lustig, Shawn P. Iadonato

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
Fundersnot available
KeywordsCancer immunotherapyMonoclonal antibodyT cellImmunotherapyCD8ImmunologyCancer researchImmune systemBiologyTumor necrosis factor alphaAntibodyCell biology

Abstract

fetched live from OpenAlex

Abstract Members of the tumor necrosis factor receptor superfamily (TNFRSF) are key co-stimulators of T cells. CD27, a member of the TNFRSF, is expressed only on the surface of lymphocytes, including naive and activated CD4+ and CD8+ T cells as well as NK cells. It enhances T cell activation, proliferation, and differentiation of effector and memory T cells after stimulation with its ligand, CD70. The costimulatory signal of CD27 is mediated via the NFkB pathway but also via the phosphatidylinositol 3 kinase and the protein kinase B pathways. CD27 signaling also influences the innate immune response via direct activation of NK cells and subsequent secretion of interferon-gamma (IFNg). Several published preclinical studies demonstrated that anti-CD27 agonistic monoclonal antibodies can promote T-cell activation and antitumor immunity making CD27 an attractive cancer immunotherapy target. Here we describe the characterization, preclinical development, and selection of our anti-CD27 fully human monoclonal antibody (mAb) lead candidate. We selected this candidate from a library of 147 anti-CD27 mAbs generated after immunization of humanized Trianni® mice with soluble human CD27 extracellular domain (hCD27-ECD). Anti-CD27 mAbs were tested in an accelerated stability study and showed excellent stability parameters for up to 7 days at 4 and 37°C in commonly used formulation buffers. The selected agonist anti-CD27 mAb demonstrated high affinity binding to both human and cynomolgus monkey CD27 and not to mouse CD27. It also demonstrated high specificity against CD27 with no cross-reactivity detected against other members of the TNFRSF. This lead candidate did not block the binding of CD27 natural ligand, CD70 and induced strong NFkB-mediated CD27 signaling in the absence or presence of cross-linking by Fc gamma receptors or secondary cross-linking antibodies. Moreover, this anti-CD27 mAb mediated NFkB activation is significantly potentiated by the addition of a sub-optimal amount of soluble CD70. The anti-CD27 lead mAb induced T cell proliferation and secretion of pro-inflammatory cytokines only in the presence of sub-optimal TCR stimulation in vitro using primary human T cells. It also activated NK cells demonstrated by CD69 expression induction. The anti-CD27 mAb lead candidate showed extended serum half-life in hCD27-KI mice. It also demonstrated a significant antitumor effect as a single agent in human CD27-Knockin mice (hCD27-KI) subcutaneously implanted with MC38 or in NOD-SCID mice subcutaneously implanted with Raji. These preclinical results establish that the selected anti-CD27 mAb is a promising drug candidate and we are actively pursuing its development. Citation Format: Thierry Guillaudeux, Yulia Ovechkina, Kurt Lustig, Shawn Iadonato. CD27 is a new promising T cell co-stimulatory target for cancer immunotherapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B034.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.092
GPT teacher head0.415
Teacher spread0.323 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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