Impact of circular RNA ZMIZ1 silencing on dendritic cell activity and immune regulation 4392
Bibliographic record
Abstract
Abstract Description Dendritic cell (DC)-based therapies for cancer have shown great promise in the past; however, optimization of DC function is necessary to increase therapy efficacy. Recently, circular RNAs have been shown to be differentially expressed between tolerogenic versus immunogenic DCs. Our study examines the role of circular RNA ZMIZ1 (circZMIZ1). Our data on bone marrow-derived DCs shows that circZMIZ1 is up-regulated in tolerogenic DCs and is positively correlated with PD-L1 expression, suggesting circZMIZ1 is antagonistic to immunogenic DC production. We aim to demonstrate that circZMIZ1 is immunosuppressive, and that silencing of circZMIZ1 can promote the production of inflammatory, immunogenic DCs, resulting in increased activation of T cell immune responses. Knockdown of circZMIZ1 decreased PD-L1 in DCs, which translated into decreased induction of T cell exhaustion and generation of regulatory T cells. We found circZMIZ1 to have a high binding probability to the JNK1 kinase, a regulator of PD-L1 in other cell types; however, it’s role in DC function is understudied. We found that knockdown of JNK1 decreased PD-L1 expression in DCs. Future experiments will test the ability of circZMIZ1-silenced DCs to activate anti-tumor T cell immunity in a murine breast cancer model. Here we propose the circZMIZ1–DC axis as a novel regulator of DC function, providing insight on how DCs can be further optimized for use in immunotherapeutic treatment of immune dysfunction diseases. Funding Sources Supported by Canadian Institutes of Health Research (CIHR) MOP#142278, PJT 162448 Supported by The Natural Sciences and Engineering Research Council of Canada (NSERC) RGPIN-2019-04545 Topic Categories Immune Response Regulation: Molecular Mechanisms (IRM)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".