DAB2IP loss confers the resistance of prostate cancer to androgen deprivation therapy through activating STAT3 and inhibiting apoptosis
Bibliographic record
Abstract
Loss of DAB2IP, a novel tumor suppressor gene, is associated with the high risk of aggressive prostate cancer (PCa). Previously, we reported that DAB2IP modulated androgen receptor activation in the development of castration-resistant PCa; however, its direct action on the failure of androgen deprivation therapy (ADT) remains largely unknown. In this study, we showed that DAB2IP knockdown could significantly enhance in vitro growth and colony formation of PCa cells following ADT as well as tumorigenicity in pre-castrated nude mice. In addition, DAB2IP loss stabilized mitochondrial transmembrane potential, prevented release of cytochrome c, Omi/HtrA2 and Smac from the mitochondria to the cytoplasm and inhibited intrinsic apoptosis induced by ADT. Mechanistically, DAB2IP could interact with the signal transducer and activator of transcription 3 (STAT3) via its unique PR domain and suppress STAT3 phosphorylation and transactivation, leading to the inhibition of survivin expression in PCa cells. Moreover, the luminal epithelia in DAB2IP(-/-) mice with more activated STAT3 and survivin expression were resistant to castration-induced apoptosis. Consistently, DAB2IP expression inversely correlated with STAT3 phosphorylation and survivin expression in PCa patients. Together, our data indicate that DAB2IP loss reprograms intracellular signal transduction and anti-apoptotic gene expression, which potentiates PCa cell survival from ADT-induced cell death.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".