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Record W4407866729 · doi:10.1158/2326-6074.io2025-b122

Abstract B122: Genetically engineered Vaccinia Virus expressing MHC-I as a precision medicine cancer vaccine

2025· article· en· W4407866729 on OpenAlexaff
Shae J Komant, Jun Li Wang, Nicole A. Favis, David H. Evans, Ryan S. Noyce, Troy A. Baldwin

Bibliographic record

VenueCancer Immunology Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVacciniaVirologyGenetically engineeredCancerVirusCancer vaccineGenetically modified organismCancer immunotherapyMedicineMajor histocompatibility complexBiologyImmunologyImmunotherapyImmune systemRecombinant DNAGeneticsGene

Abstract

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Abstract Immunotherapy is a promising treatment strategy for many forms of cancer; however, patient response rates vary with only a subset of patients responding favorably within a cohort. Recently, progress has been made in the development of oncolytic viral therapy (OV), which uses viruses to selectively target and kill cancer cells while inducing anti-tumor immunity. Producing a strong anti-cancer immune response is challenging, and strategies to direct immune responses toward the tumor are key to developing novel therapeutics. Current oncolytics struggle to stimulate potent anti-tumor responses and though the immune system offers an immense resource that can be used to treat cancers, these cells must be instructed to recognize cancer cells as foreign. T cell recognition and killing of cells requires the expression of the major histocompatibility complex (MHC) that can present peptides from cancer cells and stimulate T cell responses. The ability to target this response toward a cancer specific peptide is critical for the directed activity of T cells. Vaccinia virus (VACV) is a promising oncolytic due to its safety profile, manipulatable genome, and its induction of potent immune responses. Here, we investigated the use of modified VACV expressing MHC-I with a defined peptide and ß2-microglobulin as a single chain trimer (SCT), and the T cell co-stimulatory molecule CD80 (VACV4x-SCT). We began by determining if OV treatment of murine EMT6 breast cancer can lead to tumor regression in vivo. A previously described EMT6 tumor specific antigen, E22, was expressed by the SCT. Following intratumoral virus treatment, ∼70% of mice cleared the tumor, and E22 specific CD8+ T cells were observed to infiltrate tumors. Further, all mice that cleared primary tumor rejected secondary tumor challenge. The use of combination therapy was then evaluated, where tumor bearing mice were treated with VACV4x -SCTE22 and anti-PDL-1, which further enhanced animal survival, surpassing 75%. The ability to clear tumor and stimulate tumor specific T cells using VACV treatment led us to explore the use of OV therapy in a metastatic model. Here, we implanted tumors bilaterally and treated only one tumor. This led to the clearance of both tumors in ∼25% of mice, and the clearance of primary tumor but disease progression of secondary tumor in 13% of mice. With the ability to induce tumor clearance at a non-OV treated site, we investigated the efficacy of percutaneous administration on tumor clearance and immune stimulation. VACV4x-SCTE22 administered as a single percutaneous dose led to an extension in survival, however percutaneous immunization was not as effective as intratumoral treatment. Though modest tumor clearance was observed, E22 specific CD8+ T cells were detected in mice that did not clear the tumor. These data highlight the potential to generate a VACV stimulated immune response by delivery of a defined peptide-MHC-I complex. Bolstering a T cell response using virus is an important step for the advancement of immunotherapies and the use of VACV as a vaccine platform. Citation Format: Shae J Komant, Jun Li Wang, Nicole Favis, David H Evans, Ryan S Noyce, Troy A Baldwin. Genetically engineered Vaccinia Virus expressing MHC-I as a precision medicine cancer vaccine [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr B122.

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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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.416
Teacher spread0.377 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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