Enhanced radiation sensitivity in prostate cancer by inhibition of the cell survival protein clusterin.
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to evaluate the role of the cell survival gene clusterin in radiation-induced cell death in human LNCaP and PC-3 prostate cancer models. EXPERIMENTAL DESIGN: Radiation sensitivities were compared in parental and clusterin-overexpressing LNCaP cells and in PC-3 cells and tumors treated with antisense or mismatch clusterin oligonucleotides. RESULTS: Clusterin-overexpressing LNCaP cells were less sensitive to irradiation with significantly lower cell death rates (23% after 8 Gy) compared with parental LNCaP cells (50% after 8 Gy) 3 days after irradiation. Clusterin expression in PC-3 cells after radiation was found to be up-regulated in a dose-dependent manner in vitro by 70% up to 12 Gy and in vivo by 84% up to 30 Gy. Inhibition of clusterin expression in PC-3 cells using antisense oligonucleotides (ASOs) occurred in a sequence- and dose-dependent manner and significantly enhanced radiation-induced apoptosis and decreased PC-3 cell growth rate and plating efficiency. Compared with mismatch control oligonucleotide treatment, clusterin ASO treatment enhanced radiation therapy and significantly reduced PC-3 tumor volume in vivo by 50% at 9 weeks. In addition, TUNEL staining revealed increased number of apoptotic cells in clusterin ASO-treated and irradiated PC-3 tumors, compared with treatment with mismatch control oligonucleotides plus radiation. CONCLUSIONS: These findings support the hypothesis that clusterin acts as a cell survival protein that mediates radioresistance through the inhibition of apoptosis. In vivo results further suggest that inactivation of clusterin using ASO technology might offer a novel strategy to improve results of radiation therapy for prostate cancer patients.
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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".