DOT1L inhibition attenuates graft-versus-host disease by allogeneic T cells in adoptive immunotherapy models
Bibliographic record
Abstract
Adoptive T-cell therapy is a promising therapeutic approach for cancer patients. The use of allogeneic T-cell grafts will improve its applicability and versatility provided that inherent allogeneic responses are controlled. T-cell activation is finely regulated by multiple signaling molecules that are transcriptionally controlled by epigenetic mechanisms. Here we report that inhibiting DOT1L, a histone H3-lysine 79 methyltransferase, alleviates allogeneic T-cell responses. DOT1L inhibition reduces miR-181a expression, which in turn increases the ERK phosphatase DUSP6 expression and selectively ameliorates low-avidity T-cell responses through globally suppressing T-cell activation-induced gene expression alterations. The inhibition of DOT1L or DUSP6 overexpression in T cells attenuates the development of graft-versus-host disease, while retaining potent antitumor activity in xenogeneic and allogeneic adoptive immunotherapy models. These results suggest that DOT1L inhibition may enable the safe and effective use of allogeneic antitumor T cells by suppressing unwanted immunological reactions in adoptive immunotherapy.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".