Inhibition of bromodomain and extra-terminal proteins targets constitutively active NFκB and STAT signaling in lymphoma and influences the expression of the antiapoptotic proteins BCL2A1 and c-MYC
Bibliographic record
Abstract
The antiapoptotic protein BCL2A1 is highly, but very heterogeneously expressed in Diffuse Large B-cell Lymphoma (DLBCL). Particularly in the context of resistance to current therapies, BCL2A1 appears to play an important role in protecting cancer cells from the induction of cell death. Reducing BCL2A1 levels may have therapeutic potential, however, no specific inhibitor is currently available. In this study, we hypothesized that the signaling network regulated by epigenetic readers may regulate the transcription of BCL2A1 and hence that inhibition of Bromodomain and Extra-Terminal (BET) proteins may reduce BCL2A1 expression thus leading to cell death in DLBCL cell lines. We found that the mechanisms of action of acetyl-lysine competitive BET inhibitors are different from those of proteolysis targeting chimeras (PROTACs) that induce the degradation of BET proteins. Both classes of BETi reduced the expression of BCL2A1 which coincided with a marked downregulation of c-MYC. Mechanistically, BET inhibition attenuated the constitutively active canonical nuclear factor kappa-light-chain-enhancer of activated B-cells (NFκB) signaling pathway and inhibited p65 activation. Furthermore, signal transducer of activated transcription (STAT) signaling was reduced by inhibiting BET proteins, targeting another pathway that is often constitutively active in DLBCL. Both pathways were also inhibited by the IκB kinase inhibitor TPCA-1, resulting in decreased BCL2A1 and c-MYC expression. Taken together, our study highlights a novel complex regulatory network that links BET proteins to both NFκB and STAT survival signaling pathways controlling both BCL2A1 and c-MYC expression 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 | 0.001 |
| 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".