Regulation of the Tumor Suppressor PTEN through Exosomes: A Diagnostic Potential for Prostate Cancer
Bibliographic record
Abstract
PTEN is a potent tumor-suppressor protein. Aggressive and metastatic prostate cancer (PC) is associated with a reduction or loss of PTEN expression. PTEN reduction often occurs without gene mutations, and its downregulation is not fully understood. Herein, we show that PTEN is incorporated in the cargo of exosomes derived from cancer cells. PTEN is not detected in exosomes derived from normal, noncancerous cells. We found that PTEN can be transferred to other cells through exosomes. In cells that have a reduction or complete loss of PTEN expression, the transferred PTEN is competent to confer tumor-suppression activity to acceptor cells. In PC patients, we show that PTEN is incorporated in the cargo of exosomes that circulate in their blood. Interestingly, normal subjects have no PTEN expression in their blood exosomes. Further, we found that the prostate-specific antigen (PSA) is incorporated in PC patients' and normal subjects' blood exosomes. These data suggest that exosomal PTEN can compensate for PTEN loss in PTEN deficient cells, and may have diagnostic value for prostate cancer.
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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 | 0.001 |
| 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".