AB073. SOH24AB_228. Immunomodulatory effect of epigenetic modification on T cell phenotype and checkpoint receptor expression in oesophageal adenocarcinoma
Bibliographic record
Abstract
Background: Histone deacetylase inhibitors (HDACi) are immunotherapy agents demonstrating efficacy in malignancies such as T-cell lymphoma and Multiple Myeloma. This study aims to characterise the effects of HDACi on T-cell phenotype and function, both in health and in oesophageal adenocarcinoma (OAC), and identify opportunities for synergism with immune checkpoint inhibitors (ICIs). Methods: Through ex-vivo models, activated T-cells isolated from healthy donors and OAC patients, were treated with four HDACi (panobinostat, romidepsin, tubacin & PCI-34051). T-cell activation, immune checkpoint receptor expression and cytokine production were assessed by flow cytometry, under normal conditions and those of the microenvironment (glucose deprivation, glutamine deprivation and hypoxia). Results: HDACi did not affect activation of T-cells. Under normal conditions in both healthy and OAC T-cells, reductions in PD-1, LAG-3 and TIGIT were noted for all HDACi. Romidepsin significantly reduced TIGIT expression on helper CD4+ T-cells in OAC samples (P<0.01). Tumour microenvironment conditions further enhanced these effects, notably hypoxia. Significant reductions in PD-1, LAG-3 and TIGIT were noted in deprivation states in T-cells treated with panobinostat (P<0.05), romidepsin (P<0.05) and tubacin (P<0.05), while PCI-34051 displayed significant reductions of LAG-3 only (P<0.05). OAC samples demonstrated significantly reduced PD-1 expression at baseline on helper CD4+ T-cells, and significant increases in LAG-3 and TIGIT expression on cytotoxic CD8+ T-cells compared to healthy donors (P<0.05). Conclusions: OAC donor T-cells displayed significant differences in checkpoint expression compared to healthy donors. PCI-34051 maintained checkpoint expression in both healthy and OAC T-cells which could be crucial to understanding the potential of combinational therapeutic strategies with ICIs and epidrugs.
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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".