Plasma Gelsolin Inhibits CD8+ T-cell Function and Regulates Glutathione Production to Confer Chemoresistance in Ovarian Cancer
Bibliographic record
Abstract
Abstract Although initial treatment of ovarian cancer is successful, tumors typically relapse and become resistant to treatment. Because of poor infiltration of effector T cells, patients are mostly unresponsive to immunotherapy. Plasma gelsolin (pGSN) is transported by exosomes (small extracellular vesicle, sEV) and plays a key role in ovarian cancer chemoresistance, yet little is known about its role in immunosurveillance. Here, we report the immunomodulatory roles of sEV-pGSN in ovarian cancer chemoresistance. In chemosensitive conditions, secretion of sEV-pGSN was low, allowing for optimal CD8+ T-cell function. This resulted in increased T-cell secretion of IFNγ, which reduced intracellular glutathione (GSH) production and sensitized chemosensitive cells to cis-diaminedichloroplatinum (CDDP)-induced apoptosis. In chemoresistant conditions, increased secretion of sEV-pGSN by ovarian cancer cells induced apoptosis in CD8+ T cells. IFNγ secretion was therefore reduced, resulting in high GSH production and resistance to CDDP-induced death in ovarian cancer cells. These findings support our hypothesis that sEV-pGSN attenuates immunosurveillance and regulates GSH biosynthesis, a phenomenon that contributes to chemoresistance in ovarian cancer. Significance: These findings provide new insight into pGSN-mediated immune cell dysfunction in ovarian cancer chemoresistance and demonstrate how this dysfunction can be exploited to enhance immunotherapy.
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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".