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Abstract A032: Antitumor activities of different RIG-I agonists in a murine model of kidney adenocarcinoma

2023· article· en· W4389241397 on OpenAlexaboutno aff
Dominik Gulyás, Márta Lőrincz, I. Jankovics, Béla Dénes, Dóra Földi, Rhiannon Rodgers, Katie Commins, Gábor Andócs, Gábor G. Kovács

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineKidneyAdjuvantTLR9CpG siteCancer researchCpG OligodeoxynucleotideInternal medicinePharmacologyImmunologyBiologyGeneGene expression

Abstract

fetched live from OpenAlex

Abstract Purpose: Activation of retinoic acid-inducible gene I (RIG-I) signaling induces tumor cell apoptosis and enhances NK, dendritic, and effector T cell activity. We applied two distinct RIG-I agonists: purified influenza virus RNA (IV RNA) in combination with an agonistic OX40 receptor-specific monoclonal antibody (anti-OX40) and a 3p-hpRNA (5' triphosphate hairpin RNA) combined with unmethylated CpG oligonucleotide (CpG). We also investigated the CpG and anti-OX40 combination. The study aimed to establish the efficacy of these compounds in a murine model of kidney adenocarcinoma (Renca). Methods: Renca cells were subcutaneously engrafted in 40 BALB/c mice. The animals were allocated into three treatment groups and a control group. Intratumoral administration of specific adjuvant combinations was carried out thrice as follows: Group 1: CpG+anti-OX40, Group 2: CpG+3p-hpRNA, Group 3: IV RNA+anti-OX40, and Group 4: PBS. Daily monitoring encompassed assessment of primary tumor sizes and physiological parameters. Deceased mice underwent dissection, and histological evaluations were performed. Treatment efficacy was ascertained based on tumor growth, distant metastases' occurrence, and cytokine levels' alterations. Statistical analysis was conducted, with p-values<0.05 considered statistically significant. Results: On day 38 post-implantation, the survival rates for the various groups were as follows: Group 4: 20%, Group 1: 70% (sig), Group 2: 50% (ns), and Group 3: 60% (sig). Measurements of primary tumor sizes were conducted following the final treatment on day 17 and subsequently every seven days until day 38. On day 17, no significant disparities in primary tumor sizes were observed between Groups 1, 2, 3, and 4. However, on day 24, Groups 1, 2, and 3; on day 31, Groups 1 and 2 exhibited significantly smaller primary tumors than Group 4. By day 38, no significant differences in tumor sizes were evident among the groups. Notably, discernible variations in primary tumor characteristics were observed: Groups 1, 2, and 3 demonstrated incipient demarcation, whereas Group 4 exhibited diffuse primary tumors accompanied by necrosis. Concerning metastatic development, the results are currently under evaluation and will be available for presentation at the conference, alongside the outcomes of cytokine ELISA tests. Discussion: After concluding the experiment, we deem the treatments to hold considerable promise. Notably, while the treatment effects were sustained, tangible outcomes were achieved: prolonged survival of the mice, reduction in primary tumor sizes, and mitigated metastatic formation. However, following the final treatment, there was a notable decline in the animals' overall quality of life. Consequently, we decided to terminate the experiment. In light of our findings, we ascertain that the treatments serve as a solid foundation for further exploration. By modifying the composition of the treatment cocktails and adjusting the treatment frequency, there exists the potential for further enhancement of the achieved results. Citation Format: Dominik Gulyás, Márta Lőrincz, István Jankovics, Béla Dénes, Dóra Földi, Rhiannon Rodgers, Katie Commins, Gábor Andócs, Gábor Kovács. Antitumor activities of different RIG-I agonists in a murine model of kidney adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A032.

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.088
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.069
GPT teacher head0.388
Teacher spread0.318 · 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.

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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