Effect of Ibrutinib on the IFN Response of Chronic Lymphocytic Leukemia Cells
Bibliographic record
Abstract
Abstract The Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib has profound activity in chronic lymphocytic leukemia (CLL) but limited curative potential by itself. Residual signaling pathways that maintain survival of CLL cells might be targeted to improve ibrutinib’s therapeutic activity, but the nature of these pathways is unclear. Ongoing activation of IFN receptors in patients on ibrutinib was suggested by the presence of type I and II IFN in blood together with the cycling behavior of IFN-stimulated gene (ISG) products when IFN signaling was blocked intermittently with the JAK inhibitor ruxolitinib. IFN signaling in CLL cells from human patients was not prevented by ibrutinib in vitro or in vivo, but ISG expression was significantly attenuated in vitro. ISGs such as CXCL10 that require concomitant activation of NF-κB were decreased when this pathway was inhibited by ibrutinib. Other ISGs, exemplified by LAG3, were decreased as a result of inhibited protein translation. Effects of IFN on survival remained intact as type I and II IFN–protected CLL cells from ibrutinib in vitro, which could be prevented by ruxolitinib and IFNR blocking Abs. These observations suggest that IFNs may help CLL cells persist and specific targeting of IFN signaling might deepen clinical responses of patients on ibrutinib.
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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) | 0.003 | 0.001 |
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".