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Record W2954988217 · doi:10.1158/1538-7445.am2019-1473

Abstract 1473: Dual oncolytic viral immunotherapy generates large polyfunctional tumour-specific CD8 + T cell responses that infiltrate immunosuppressive tumors

2019· article· en· W2954988217 on OpenAlexaff
David F. Stojdl

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsInterface Biologics (Canada)
Fundersnot available
KeywordsOncolytic virusImmunotherapyCancer immunotherapyAntigenCD8Cancer researchImmune systemT cellCytotoxic T cellImmunologyCancerMedicineBiologyIn vitro

Abstract

fetched live from OpenAlex

Abstract Generating effective T cell mediated clearance of solid tumors remains an unmet challenge in cancer therapy. Suppressive tumor microenvironments limit the generation of significant numbers of tumor specific T effector cells, their migration to tumor beds, and their subsequent functionality within tumors, thereby blocking the patient’s normally potent acquired immune response from contributing to tumor control. In an effort to meet this challenge, we have developed novel oncolytic viruses that were bioselected and engineered to cause cancer cell death through two distinct and complementary mechanisms-of-action, direct cancer lysis and tumor-antigen specific T cell generation. Specifically, we have selected and engineered MG1 Maraba virus which both infects tumor tissue to reverse immune suppressive programs while simultaneously delivering vector encoded tumor antigens to the spleen to vaccinate against the patient’s tumor. The result is a large increase in peripheral and tumor infiltrating CD8+ T effectors cells, strong intratumoral inflammatory signatures and ultimately curative efficacy in preclinical solid tumor models. This first-in-class therapeutic strategy is currently being evaluated in Phase 1 and Phase 2 clinical trials. In this new study, we describe the development of a novel viral immunotherapy platform based on Farmington virus that is: (1) oncolytic in solid tumor models, (2) a potent inducer of highly-functional antigen-specific T cells (expanding tumor specific CD8+ T effector pools over 1000 fold from pre-existing T central memory) and is (3) immunologically distinct from our clinical MG1 Maraba platform. We show that when used sequentially in a heterologous boosting regimen, T cell responses to encoded tumor antigens, either foreign (HPV E7), self (TRP2) or multi-neoantigen, can exceed greater than 50% of all CD8+ T cells in the periphery. The majority of these CD8+ T effectors show markers of polyfunctionality with little expression of the PD-1 exhaustion marker. We will describe our current data assessing the phenotype, localization and potency of these T cell responses in preclinical models of solid tumors and propose strategies to deploy our novel dual oncolytic viral immunotherapy boosting paradigm to the clinic. Citation Format: David Stojdl. Dual oncolytic viral immunotherapy generates large polyfunctional tumour-specific CD8 + T cell responses that infiltrate immunosuppressive tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1473.

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 score0.004
Threshold uncertainty score0.013

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)0.0040.001

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 head0.043
GPT teacher head0.355
Teacher spread0.312 · 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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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