Voruciclib, a clinical stage oral CDK9 inhibitor, represses MCL-1 and sensitizes high-risk Diffuse Large B-cell Lymphoma to BCL2 inhibition
Bibliographic record
Abstract
Aberrant regulation of BCL-2 family members enables evasion of apoptosis and tumor resistance to chemotherapy. BCL-2 and functionally redundant counterpart, MCL-1, are frequently over-expressed in high-risk diffuse large B-cell lymphoma (DLBCL). While clinical inhibition of BCL-2 has been achieved with the BH3 mimetic venetoclax, anti-tumor efficacy is limited by compensatory induction of MCL-1. Voruciclib, an orally bioavailable clinical stage CDK-selective inhibitor, potently blocks CDK9, the transcriptional regulator of MCL-1. Here, we demonstrate that voruciclib represses MCL-1 protein expression in preclinical models of DLBCL. When combined with venetoclax in vivo, voruciclib leads to model-dependent tumor cell apoptosis and tumor growth inhibition. Strongest responses were observed in two models representing high-risk activated B-cell (ABC) DLBCL, while no response was observed in a third ABC model, and intermediate responses were observed in two models of germinal center B-cell like (GCB) DLBCL. Given the range of responses, we show that CIVO, a multiplexed tumor micro-dosing technology, represents a viable functional precision medicine approach for differentiating responders from non-responders to BCL-2/MCL-1 targeted therapy. These findings suggest that the combination of voruciclib and venetoclax holds promise as a novel, exclusively oral combination therapy for a subset of high-risk DLBCL patients.
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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".