Cancer cells adapt FAM134B/BiP mediated ER-phagy to survive hypoxic stress
Bibliographic record
Abstract
In the tumor microenvironment, cancer cells experience hypoxia resulting in the accumulation of misfolded/unfolded proteins largely in the endoplasmic reticulum (ER). Consequently, ER proteotoxicity elicits unfolded protein response (UPR) as an adaptive mechanism to resolve ER stress. In addition to canonical UPR, proteotoxicity also stimulates the selective, autophagy-dependent, removal of discrete ER domains loaded with misfolded proteins to further alleviate ER stress. These mechanisms can favor cancer cell growth, metastasis, and long-term survival. Our investigations reveal that during hypoxia-induced ER stress, the ER-phagy receptor FAM134B targets damaged portions of ER into autophagosomes to restore ER homeostasis in cancer cells. Loss of FAM134B in breast cancer cells results in increased ER stress and reduced cell proliferation. Mechanistically, upon sensing hypoxia-induced proteotoxic stress, the ER chaperone BiP forms a complex with FAM134B and promotes ER-phagy. To prove the translational implication of our mechanistic findings, we identified vitexin as a pharmacological agent that disrupts FAM134B-BiP complex, inhibits ER-phagy, and potently suppresses breast cancer progression in vivo.
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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 | 0.000 |
| 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".