Chemotherapeutic Drugs Induce ATP Release via Caspase-gated Pannexin-1 Channels and a Caspase/Pannexin-1-independent Mechanism
Bibliographic record
Abstract
Anti-tumor immune responses have been linked to the regulated release of ATP from apoptotic cancer cells to engage P2 purinergic receptor signaling cascades in nearby leukocytes. We used the Jurkat T cell acute lymphocytic leukemia model to characterize the role of pannexin-1 (Panx1) channels in the release of nucleotides during chemotherapeutic drug-induced apoptosis. Diverse pro-apoptotic drugs, including topoisomerase II inhibitors, kinase inhibitors, and proteosome inhibitors, induced functional activation of Panx1 channels via caspase-3-mediated cleavage of the Panx1 autoinhibitory C-terminal domain. The caspase-activated Panx1 channels mediated efflux of ATP, but also ADP and AMP, with the latter two comprising >90% of the released adenine nucleotide pool as cells transitioned from the early to late stages of apoptosis. Chemotherapeutic drugs also activated an alternative caspase- and Panx1-independent pathway for ATP release from Jurkat cells in the presence of benzyloxycarbonyl-VAD, a pan-caspase inhibitor. Comparison of Panx1 levels indicated much higher expression in leukemic T lymphocytes than in normal, untransformed T lymphoblasts. This suggests that signaling roles for Panx1 may be amplified in leukemic leukocytes. Together, these results identify chemotherapy-activated pannexin-1 channels and ATP release as possible mediators of paracrine interaction between dying tumor cells and the effector leukocytes that mediate immunogenic anti-tumor responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".