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Abstract B002: Vidutolimod, an immunostimulatory virus-like particle, reduces proliferation but enhances the activation of tumor-specific T cells

2023· article· en· W4389241389 on OpenAlexaboutno aff
Travis D Fischer, Caitlin D. Lemke, George J. Weiner

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
Fundersnot available
KeywordsTumor microenvironmentT cellCD8BiologyPopulationImmune systemCytotoxic T cellSplenocyteCancer researchMolecular biologyImmunologyMedicineIn vitro

Abstract

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Abstract One approach to enhancing the anti-tumor T cell response is to alter the tumor microenvironment (TME) through intratumoral injection (IT) of immunostimulatory agents such as Vidutolimod (Vidu). Vidu is a virus-like particle (VLP) composed of a TLR9 agonist (CpG-A, known as G10) encapsulated by the Qβ bacteriophage capsid. IT Vidu shows considerable promise in early phase clinical trials. The immune response to Vidu is initiated by induction of IFNa production by pDCs within the TME. This effect is dependent on coating of Vidu with antibodies against the Qb capsid. This is followed by a series of changes in the TME that ultimately result in an enhanced anti-tumor T cell response. Mouse models have shown that the efficacy of IT Vidu depends on the presence of both CD4+ and CD8+ T cells. Most studies to date exploring the impact of Vidu on T cells have focused on the overall T cell population. The current studies were designed to further assess the complex mechanisms by which Vidu induces an anti-tumor T cell response through use of the well-established OT-1 mouse model that allows for analysis of the tumor-specific T cell population. OT-1 mice contain CD8+ T cells with a transgenic TCR that recognizes the ovalbumin (OVA) peptide SIINFEKL sequence (OVA257-264) presented on MHC Class I. Prior to culture, OT-1 splenocytes were labeled with CellTrace Violet in order to monitor proliferation over time. OT-1 splenocytes were then cultured with EL4 cells (an OVA-negative T lymphoblast cell line) or E.G7-OVA (OVA-expressing EL4 derivative cells). Minimal proliferation or evidence of T cell activation was seen when OT-1 CD8+ T cells were cultured with EL4 cells regardless of the addition of Vidu and anti-Qβ antibodies. OT-1 CD8+ T cells cultured with E.G7-OVA cells showed both proliferation and activation as indicated by increased intracellular IFNy and surface PD-1. Addition of Vidu and anti-Qb antibody reduced OT-1 CD8+ proliferation but enhanced production of IFNγ and expression of PD-1. The increase in IFNγ and PD-1 expression was strongest in the dividing OT-1 CD8+ T cell population. Preliminary results of ongoing in vivo studies are consistent with these results. In summary, Vidu reduces proliferation but enhances phenotypic markers of activation expressed by tumor-specific CD8+ T cells (OT-1 cells) when co-cultured with cells expressing OVA, their target antigen. Markers of activation are most notable in dividing OT-1 CD8+ T cells. Citation Format: Travis D. Fischer, Caitlin Lemke-Miltner, George J. Weiner. Vidutolimod, an immunostimulatory virus-like particle, reduces proliferation but enhances the activation of tumor-specific T cells [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 B002.

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 categoriesInsufficient 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.073
GPT teacher head0.360
Teacher spread0.286 · 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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