Blockade of chloride channel-3 enhances cisplatin sensitivity of cholangiocarcinoma cells though inhibiting autophagy
Bibliographic record
Abstract
Chemotherapy is one of the most important strategies in the treatment of cancer; however, chemoresistance restricts the effect of chemotherapy. Growing reports suggest that chloride channel-3 (ClC-3) is involved in regulating the sensitivity of multiple chemotherapeutic agents in the chemotherapy of various tumours, while its role in the chemotherapy of cholangiocarcinoma (CCA) is still poorly understood. Herein, we observed that ClC-3 was highly expressed in CCA chemoresistant tissues and CCA cisplatin-resistant cells QBC939/DDP, and the sensitivities of QBC939 and QBC939/DDP cells to cisplatin were all increased after inhibition of ClC-3. Further mechanism exploration revealed that ClC-3 knockdown reduced the level of autophagy. Furthermore, in both QBC939 and QBC939/DDP cells, the autophagy agonist rapamycin eliminated the increased cisplatin sensitivity of ClC-3 knockdown without affecting ClC-3 expression. Collectively, all the findings demonstrate that ClC-3 knockdown increases cisplatin-induced cell death in CCA cells though inhibiting autophagy, regardless of the occurrence of cisplatin resistance. In addition, our results also suggest that targeted inhibition of ClC-3 may be a potential strategy for chemosensitization in CCA chemotherapy.
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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) | 0.001 | 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".