GNAS knockout potentiates HDAC3 inhibition through viral mimicry-related interferon responses in lymphoma
Bibliographic record
Abstract
Abstract Despite selective HDAC3 inhibition showing promise in a subset of lymphomas with CREBBP mutations, wild-type tumors generally exhibit resistance. Here, using unbiased genome-wide CRISPR screening, we identify GNAS knockout (KO) as a sensitizer of resistant lymphoma cells to HDAC3 inhibition. Mechanistically, GNAS KO-induced sensitization is independent of the canonical G-protein activities but unexpectedly mediated by viral mimicry-related interferon (IFN) responses, characterized by TBK1 and IRF3 activation, double-stranded RNA formation, and transposable element (TE) expression. GNAS KO additionally synergizes with HDAC3 inhibition to enhance CD8+ T cell-induced cytotoxicity. Moreover, we observe in human lymphoma patients that low GNAS expression is associated with high baseline TE expression and upregulated IFN signaling and shares common disrupted biological activities with GNAS KO in histone modification, mRNA processing, and transcriptional regulation. Collectively, our findings establish an unprecedented link between HDAC3 inhibition and viral mimicry in lymphoma. We suggest low GNAS expression as a potential biomarker that reflects viral mimicry priming for enhanced response to HDAC3 inhibition in the clinical treatment of lymphoma, especially the CREBBP wild-type cases.
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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) | 0.002 | 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".