Effects of the omega-3 fatty acid DHA on histone and p53 acetylation in diffuse large B cell lymphoma
Bibliographic record
Abstract
Diffuse large B cell lymphoma (DLBCL) often develops resistance and/or relapses in response to immunochemotherapy. Epigenetic modifiers are frequently mutated in DLBCL, i.e., the lysine (histone) acetyltransferases CREBBP and EP300. Mutations in CBP/p300 can prevent the proper acetylation and activation of ( i) enhancer sequences of genes required for essential functions (e.g., germinal center exit and differentiation) and ( ii) the tumor suppressor p53. Based on evidence that omega-3 fatty acids (ω-3 FAs) affect histone acetylation in various cancers, we investigated whether ω-3 FA docosahexaenoic acid (DHA) could modify levels of histone and p53 acetylation in three DLBCL cell lines (at different CREBBP/EP300 mutational status) versus normal B cells. Exposure to DHA at clinically attainable doses was shown to significantly alter the genome-wide levels of histone posttranslational modifications in a cell-line-dependent and dose-dependent manner. Although histone acetylation did not increase uniformly, as initially expected, levels of p53 acetylation increased consistently. Quantitative reverse transcription polymerase chain reaction results revealed significant changes in expression of multiple genes, including increased expression of CREBBP and of PRDM1 (required for differentiation into plasma cells or memory B cells). Taken together, our results provide (to our knowledge) the first characterization of the epigenetic effects of ω-3 FAs in DLBCL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".