Ibrutinib Resistance Is Reduced by an Inhibitor of Fatty Acid Oxidation in Primary CLL Lymphocytes
Bibliographic record
Abstract
Chronic Lymphocytic Leukemia (CLL) is an incurable disease, characterized by the accumulation of malignant B-lymphocytes in the blood stream (quiescent state) and homing tissues (where they can proliferate). In CLL, the targeting of B-cell receptor signaling through a Burton's tyrosine kinase inhibitor (ibrutinib) has rendered outstanding clinical results. However, complete remission is not guaranteed due to drug resistance or relapse, revealing the need for novel approaches for CLL treatment. The characterization of metabolic rewiring in proliferative cancer cells is already being applied for diagnostic and therapeutic purposes, but our knowledge of quiescent cell metabolism-relevant for CLL cells-is still fragmentary. Recently, we reported that glutamine metabolism in primary CLL cells bearing the del11q deletion is different from their del11q negative counterparts, making del11q cells especially sensitive to glutaminase and glycolysis inhibitors. In this work, we used our primary CLL lymphocyte bank and compounds interfering with central carbon metabolism to define metabolic traits associated with ibrutinib resistance. We observe a differential basal metabolite uptake linked to ibrutinib resistance, favoring glutamine uptake and catabolism. Upon ibrutinib treatment, the redox balance in ibrutinib resistant cells is shifted toward NADPH accumulation, without an increase in glutamine uptake, suggesting alternative metabolic rewiring such as the activation of fatty acid oxidation. In accordance to this idea, the curtailing of fatty acid oxidation by CPT1 inhibition (etomoxir) re-sensitized resistant cells to ibrutinib. Our results suggest that fatty acid oxidation could be explored as a target to overcome ibrutinib resistance.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".