Inhibition of the Phosphatidylinositol 3′-Kinase Pathway Promotes Autocrine Fas-Induced Death of Phosphatase and Tensin Homologue–Deficient Prostate Cancer Cells
Bibliographic record
Abstract
Rationally designed therapeutics that target the phosphatidylinositol 3'-kinase (PI3K) cell survival pathway are currently in preclinical and clinical development for cancer therapy. Drugs targeting the PI3K pathway aim to inhibit proliferation, promote apoptosis, and enhance chemosensitivity and radiosensitivity of cancer cells. The phosphatase and tensin homologue (PTEN) phosphatidylinositol 3'-phosphatase is a key negative regulator of the PI3K pathway. Inactivation of the PTEN tumor suppressor results in constitutive activation of the PI3K pathway and is found in approximately 50% of advanced prostate cancers, which correlates with a high Gleason score and poor prognosis. Inhibition of the PI3K pathway leads to apoptosis of prostate cancer cells; however, the precise mechanism by which this occurs is unknown. Here we report that apoptotic cell death of PTEN-deficient LNCaP and PC3 prostate cancer cells induced by the PI3K inhibitor LY294002 can be abrogated by disrupting Fas/Fas ligand (FasL) interactions with recombinant Fas:Fc fusion protein or FasL neutralizing antibody (Nok-1), or by expressing dominant-negative Fas-associated death domain. Furthermore, we find that apoptosis induced by expression of wild-type PTEN, driven by a tetracycline-inducible expression system in LNCaP cells, can be inhibited by blocking Fas/FasL interaction using Fas:Fc or Nok-1. These data show that apoptosis induced by blockade of the PI3K pathway in prostate tumor cells is mediated by an autocrine Fas/FasL apoptotic mechanism and the Fas apoptotic pathway is both necessary and sufficient to mediate apoptosis by PI3K inhibition.
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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".