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Abstract B059: Synergistic activation of antitumor immunity by an oncolytic virus VG161 armed with multiple immune-stimulating genes

2019· article· en· W2912834094 on OpenAlexaff
Ronghua Zhao, Jun Ding, Dmitry Choujenko, Yanal Murad, Erica Lee, Guoyu Liu, Luke Bu, William Jia

Bibliographic record

VenueCancer Immunology Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsVancouver Biotech (Canada)University of British Columbia
Fundersnot available
KeywordsOncolytic virusImmune systemTumor microenvironmentCancer researchImmunotherapyCancer immunotherapyVirotherapyImmunologyBiologyHerpes simplex virusVirusMedicineVirology

Abstract

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Abstract Oncolytic viruses (OVs) are among the most powerful approaches in cancer immunotherapy. OVs not only cause cancer cell lysis but more importantly, their infection in tumors induces anti-tumor immune response from the host, resulting in lasting anti-tumor immunity. It has been recognized that anti-tumor immune response requires multiple immune regulatory factors that act synergistically and tumor microenvironment is critical for tumor to grow. Herpes simplex virus type-1 (HSV-1) has been approved by FDA as an oncolytic viral drug to treat melanoma. One advantage of HSV-1 is its large genomic capacity for carrying multiple exogenous genes.A HSV-1 oncolytic viral vector (VG161) was constructed to simultaneously express IL12, IL15 with its receptor alpha unit and a PDL-1 blocking peptide. Antitumor activity of VG161 was tested in both immune competent mice (CT26 and A20 tumor models) and nude mice for human tumor models (LNCaP and U87). Since CT26 and A20 are poorly permissive for HSV-1 replication, the mouse tumor models were able to demonstrate the antitumor immune response induced by VG161 while oncolytic activity of VG161 was demonstrated in LNCaP and U87 models since the immune system is compromised in those models.VG161 completely inhibited tumors in all the models tested and the animals survived tumor-free for many months till sacrificed. VG161 induced tumor oncolysis in both LNCaP and U87 tumors. In the CT26 model, animals were protected from the second challenging with CT26 cells following previous virally induced tumor regression. Furthermore, in a A20 double tumor model, intratumoral injection into the tumor on one side caused tumor regression on both sides. Transcriptome analysis showed significant change in tumor microenvironment. Finally, tumor specific memory T-cells were evident in the treated animals. The anti-tumor immune response by VG161 was significantly stronger than similar viruses that did not express any immune stimulating gene or only express GM-CSF. These results showed that intratumorally expressed multiple immune regulatory factors by an oncolytic virus may significantly change the tumor immune microenvironment to enhance efficacy of the oncolytic virus. Citation Format: Ronghua Zhao, Jun Ding, Dmitry Choujenko, Yanal Murad, Erica Lee, Guoyu Liu, Luke Bu, William Jia. Synergistic activation of antitumor immunity by an oncolytic virus VG161 armed with multiple immune-stimulating genes [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B059.

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 categoriesMeta-epidemiology (narrow)
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 score0.009
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.376
Teacher spread0.331 · 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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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