The significance of dynamin 2 expression for prostate cancer progression, prognostication, and therapeutic targeting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dynamin 2 (Dyn2) is essential for intracellular vesicle formation and trafficking, cytokinesis, and receptor endocytosis. In this study, we investigated the implication of Dyn2 as a prognostic marker and therapeutic target for progressive prostate cancer (PCA). We evaluated Dyn2 protein expression by immunohistochemistry in two cohorts: men with localized PCA treated by retropubic radical prostatectomy (n = 226), and men with advanced/castrate-resistant PCA (CRPC) treated by transurethral resection of prostate (TURP) (n = 253). The role of Dyn2 in cell invasiveness was assessed by in vitro and in vivo experiments using androgen-responsive and refractory PCA preclinical models. Dyn2 expression was significantly increased across advanced stages of PCA compared to benign prostate tissue (P < 0.0001). In the CRPC cohort, high Dyn2 was associated with higher Gleason score (P = 0.004) and marginally with cancer-specific mortality (P = 0.052). In preclinical models, Dyn2 gene silencing significantly reduced cell migration and invasion in vitro, as well as tumor size and lymph node metastases in vivo. In isolated PCA cells, Dyn2 was found to regulate focal adhesion turnover, which is critical for cell migration; this mechanism requires full Dyn2 compared to mutants deficient in GTPase activity. In conclusion, Dyn2 overexpression is associated with neoplastic prostate epithelium and is associated with poor prognosis. Inhibition of Dyn2 prevents cell invasiveness in androgen-responsive and -refractory PCA models, supporting the potential benefit of Dyn2 to serve as a therapeutic target for advanced PCA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it