Simultaneous inhibition of the ubiquitin-proteasome system and autophagy enhances apoptosis induced by ER stress aggravators in human pancreatic cancer cells
Bibliographic record
Abstract
In contrast to normal tissue, cancer cells display profound alterations in protein synthesis and degradation. Therefore, proteins that regulate endoplasmic reticulum (ER) homeostasis are being increasingly recognized as potential therapeutic targets. The ubiquitin-proteasome system and autophagy are crucially important for proteostasis in cells. However, interactions between autophagy, the proteasome, and ER stress pathways in cancer remain largely undefined. This study demonstrated that withaferin-A (WA), the biologically active withanolide extracted from Withania somnifera, significantly increased autophagosomes, but blocked the degradation of autophagic cargo by inhibiting SNARE-mediated fusion of autophagosomes and lysosomes in human pancreatic cancer (PC) cells. WA specifically induced proteasome inhibition and promoted the accumulation of ubiquitinated proteins, which resulted in ER stress-mediated apoptosis. Meanwhile, the impaired autophagy at early stage induced by WA was likely activated in response to ER stress. Importantly, combining WA with a series of ER stress aggravators enhanced apoptosis synergistically. WA was well tolerated in mice, and displayed synergism with ER stress aggravators to inhibit tumor growth in PC xenografts. Taken together, these findings indicate that simultaneous suppression of 2 key intracellular protein degradation systems rendered PC cells vulnerable to ER stress, which may represent an avenue for new therapeutic combinations for this disease.
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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 | 0.000 |
| 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".