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A combination of genetically engineered oncolytic virus and melittin-CpG for cancer viro-chemo-immunotherapy

2023· other· en· W6921393307 on OpenAlexaff

Bibliographic record

VenueFigshare · 2023
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOncolytic virusImmune systemImmunotherapyMelanomaCancerTumor microenvironmentImmunogenic cell deathVirusCancer immunotherapy

Abstract

fetched live from OpenAlex

Abstract Background Immunotherapy has emerged as an efficient therapeutic approach for cancer management. However, stimulation of host immune system against cancer cells often fails to achieve promising clinical outcomes mainly owing to the immunosuppressive characteristics of the tumor microenvironment (TME). Combination therapeutics that can trigger sustained immunogenic cell death (ICD) have provided new opportunities for cancer treatment. Methods In this study, we designed and applied an ICD inducer regimen, including a genetically engineered oncolytic virus (miRNA-modified coxsackieviruses B3, miR-CVB3), a pore-forming lytic peptide (melittin, found in bee venom), and a synthetic toll-like receptor 9 ligand (CpG oligodeoxynucleotides), for breast cancer and melanoma treatment. We compared the anti-tumor efficacy of miR-CVB3 and CpG-melittin (CpGMel) alone and in combination (miR-CVB3 + CpGMel) and investigated possible mechanisms involved. Results We demonstrated that miR-CVB3 + CpGMel had no major impact on viral growth, while enhancing the cellular uptake of CpGMel in vitro. We further showed that combination therapy led to significant increases in tumor cell death and release of damage-associated molecular patterns compared with individual treatment. In vivo studies in 4T1 tumor-bearing Balb/c mice revealed that both primary and distant tumors were significantly suppressed, and the survival rate was significantly prolonged after administration of miR-CVB3 + CpGMel compared with single treatment. This anti-tumor effect was accompanied by increased ICD and immune cell infiltration into the TME. Safety analysis showed no significant pathological abnormalities in Balb/c mice. Furthermore, the developed therapeutic regimen also demonstrated a great anti-tumor activity in B16F10 melanoma tumor-bearing C57BL/6 J mice. Conclusions Overall, our findings indicate that although single treatment using miR-CVB3 or CpGMel can efficiently delay tumor growth, combining oncolytic virus-based therapy can generate even stronger anti-tumor immunity, leading to a greater reduction in tumor size.

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 score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.058
GPT teacher head0.245
Teacher spread0.187 · 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
Published2023
Admission routes1
Has abstractyes

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