Inhibition of Fas Receptor Endocytosis Sensitizes Cancer Cells to Fas-induced Apoptosis
Bibliographic record
Abstract
Abstract Fas (CD95/APO-1) is a transmembrane death receptor that transduces apoptotic signals upon binding to its ligand and assembling into a death-inducing signaling complex (DISC) ( 1, 2 ). Intracellular trafficking of Fas receptors, including recycling from endosomes to the plasma membrane, plays a vital role in ligand-induced assembly of DISC ( 3, 4 ). Although Fas is highly expressed in tumor cells ( 5, 6 ), insufficient expression of these receptors on the cell surface makes cancer cells insensitive to the Fas-induced apoptosis ( 4, 7 – 9 ). Here we show that inhibition of endocytosis increases the formation of Fas microaggregates on the plasma membrane and sensitizes cancer cells to Fas-induced apoptosis. We have identified a clinically used vasodilator, Fasudil, that slows down endocytosis by increasing plasma membrane tension. Fasudil enhanced apoptosis in cancerous cells when combined with exogenous soluble Fas ligand (FasL), whereas the synergistic effect was substantially weaker in nonmalignant cells. Additionally, the FasL and Fasudil combination prevented glioblastoma cell growth in embryonic stem cell-derived brain organoids and induced tumor regression in a xenograft U87 tumor model in nude mice. Our results demonstrate that FasL treatment has strong potential as an apoptosis-directed cancer therapy when the formation of Fas microaggregates is augmented by slowing down endocytosis dynamics.
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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".