Identifying Synergistic Drug Combinations in Diffuse Large B-cell Lymphoma
Bibliographic record
Abstract
In Canada, diffuse large B-cell lymphoma (DLBCL) is the most frequently occurring type of non-Hodgkin lymphoma, further classified by cell-of origin. Specifically, the germinal center B-cell (GCB) subtype of DLBCL has shown common occurrence of EZH2 mutations. The EZH2 inhibitor tazemetostat has been tested in clinical trials, but response rates are suboptimal in DLBCL. In this study, we followed up on a screen that identified IKZF1 as one of the top hits in sensitizing a relatively resistant cell line to tazemetostat, by studying the effects of lenalidomide (a drug promoting IKZF1 degradation) in combination with tazemetostat. Here, we observed synergistic drug interaction across cell lines, with enrichment of signaling pathways involved in the interferon and antiviral response in addition to significant induction of selected interferon responsive genes and dsRNA ERV expression. Altogether, our results strongly suggest that the combined targeting of IKZF1 and EZH2 has therapeutic potential in treating 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) | 0.001 | 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".