Lysosome-Disrupting Agents in Combination with Venetoclax Increase Apoptotic Response in Primary Chronic Lymphocytic Leukemia (CLL) Cells Mediated by Lysosomal Cathepsin D Release and Inhibition of Autophagy
Bibliographic record
Abstract
Venetoclax and obinutuzumab are becoming frontline therapies for chronic lymphocytic leukemia (CLL) patients. Unfortunately, drug resistance still occurs, and the combination could be immunosuppressive. Lysosomes have previously been identified as a target for obinutuzumab cytotoxicity in CLL cells, but the mechanism remains unclear. In addition, studies have shown that lysosomotropic agents can cause synergistic cell death in vitro when combined with the BTK inhibitor, ibrutinib, in primary CLL cells. This indicates that targeting lysosomes could be a treatment strategy for CLL. In this study, we have shown that obinutuzumab induces lysosome membrane permeabilization (LMP) and cathepsin D release in CLL cells. Inhibition of cathepsins reduced obinutuzumab-induced cell death in CLL cells. We further determined that the lysosomotropic agent siramesine in combination with venetoclax increased cell death in primary CLL cells through an increase in reactive oxygen species (ROS) and cathepsin release. Siramesine treatment also induced synergistic cytotoxicity when combined with venetoclax. Microenvironmental factors IL4 and CD40L or incubation with HS-5 stromal cells failed to significantly protect CLL cells from siramesine- and venetoclax-induced apoptosis. We also found that siramesine treatment inhibited autophagy through reduced autolysosomes. Finally, the autophagy inhibitor chloroquine failed to further increase siramesine-induced cell death. Taken together, lysosome-targeting drugs could be an effective strategy in combination with venetoclax to overcome drug resistance in CLL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".