Inhibition of the sarco/endoplasmic reticulum (ER) Ca2+-ATPase by thapsigargin analogs induces cell death via ER Ca2+ depletion and the unfolded protein response
Bibliographic record
Abstract
Calcium (Ca 2+ ) is a fundamental regulator of cell signaling and function. Thapsigargin (Tg) blocks the sarco/endoplasmic reticulum (ER) Ca 2+ -ATPase (SERCA), disrupts Ca 2+ homeostasis, and causes cell death. However, the exact mechanisms whereby SERCA inhibition induces cell death are incompletely understood. Here, we report that low (0.1 μm) concentrations of Tg and Tg analogs with various long-chain substitutions at the O-8 position extensively inhibit SERCA1a-mediated Ca 2+ transport. We also found that, in both prostate and breast cancer cells, exposure to Tg or Tg analogs for 1 day caused extensive drainage of the ER Ca 2+ stores. This Ca 2+ depletion was followed by markedly reduced cell proliferation rates and morphological changes that developed over 2–4 days and culminated in cell death. Interestingly, these changes were not accompanied by bulk increases in cytosolic Ca 2+ levels. Moreover, knockdown of two key store-operated Ca 2+ entry (SOCE) components, Orai1 and STIM1, did not reduce Tg cytotoxicity, indicating that SOCE and Ca 2+ entry are not critical for Tg-induced cell death. However, we observed a correlation between the abilities of Tg and Tg analogs to deplete ER Ca 2+ stores and their detrimental effects on cell viability. Furthermore, caspase activation and cell death were associated with a sustained unfolded protein response. We conclude that ER Ca 2+ drainage and sustained unfolded protein response activation are key for initiation of apoptosis at low concentrations of Tg and Tg analogs, whereas high cytosolic Ca 2+ levels and SOCE are not required.
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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".