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Abstract A068: Determinants of efficacy in cancer immunovirotherapy

2016· article· en· W2548161278 on OpenAlexaff
Rūta Veinalde, Christian Grossardt, Marie‐Claude Bourgeois‐Daigneault, Christof von Kalle, Dirk Jaeger, Guy Ungerechts, Christine E. Engeland

Bibliographic record

VenueCancer Immunology Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsOncolytic virusMedicineImmune systemImmunotherapyAntigenImmunologyMelanomaCancer immunotherapyCancer researchCancerInternal medicine

Abstract

fetched live from OpenAlex

Abstract Replicating oncolytic viruses (OVs) are emerging as a promising therapeutic approach for different tumor entities. Positive data from numerous clinical studies are accumulating and as a first-in-class oncolytic herpes virus encoding GM-CSF, Talimogene Laherparepvec (T-VEC), has been approved for treatment of unresectable melanoma by the U.S. Food and Drug Administration at the end of 2015. Although it has been recognized that combinations of OVs with different immunomodulators can significantly improve therapeutic outcome, understanding of immune effector mechanisms determining success of a particular approach remains limited, restricting the development of rational combination strategies. In this study we aimed to determine the most beneficial immunomodulation strategies for combination with oncolytic measles virus (MeV). Furthermore, we performed a comprehensive analysis of anti-tumor immune effector mechanisms associated with response to pinpoint mechanisms crucial for therapeutic efficacy. We developed MeV Schwarz vaccine strain vectors (MeVac) encoding different immunomodulators to target the main phases in establishment of an anti-tumor immune response: GM-CSF - to enhance maturation of antigen-presenting cells, an IL-12 fusion protein (FmIL-12) and IP-10 - to enhance immune effector cell responses, antibodies against CTLA-4 and PD-L1 and a soluble form of CD80 - to counteract immunosuppression in the tumor microenvironment. Therapeutic efficacy of the novel vectors was evaluated in the fully immunocompetent murine colon adenocarcinoma model MC38cea. MeVac encoding anti-PD-L1 and FmIL-12, respectively, were identified as the most effective therapeutics. Notably, MeVac encoding FmIL-12 showed a superior therapeutic efficacy, achieving 90% complete remissions of established tumors. Animals treated with the immunomodulatory MeVac vectors rejected secondary tumor engraftments, indicating establishment of protective anti-tumor immunity. Higher IFN-γ production upon restimulation of splenocytes with tumor cells in vitro was observed for animals treated with MeVac FmIL-12 in comparison to treatment with MeVac anti-PD-L1 and a control vector encoding constant region of antibody (MeVac IgG1-Fc), indicating establishment of a more potent memory response. Intratumoral cytokine profiling with cytokine bead arrays revealed upregulation of the effector cytokines IFN-γ and TNF-α after treatment with MeVac FmIL-12. A massive decrease in intratumoral natural killer (NK) cell counts and an increase of activation marker CD69 expression on NK cells as well as an increase in T cell amount was observed in flow cytometry analysis one day after treatment with MeVac FmIL-12. This indicates early direct activation of these lymphocyte subsets through direct IL-12 signaling. An increase in intratumoral T cells and a decrease in NK cells and activated cytotoxic T cells (CD8+CD69+) was observed four days after the last treatment with both MeVac anti-PD-L1 and MeVac IgG1-Fc, with slightly more pronounced effects in the MeVac anti-PD-L1 group. This suggests that MeVac vectors per se activate T and NK cell responses, which can further be supported with PD-L1 blockade. This study establishes MeVac encoding FmIL-12 as a potent immunomodulatory oncolytic vector and provides insights into its mechanisms of action, thereby creating a basis for further rational vector modifications to translate immunomodulatory MeV into clinical application. Citation Format: Rūta Veinalde, Christian Grossardt, Marie-Claude Bourgeois-Daigneault, Christof von Kalle, Dirk Jaeger, Guy Ungerechts, Christine E. Engeland. Determinants of efficacy in cancer immunovirotherapy [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A068.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.434
Teacher spread0.363 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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