The Mechanism of DAB2IP in Chemoresistance of Prostate Cancer Cells
Bibliographic record
Abstract
PURPOSE: The docetaxel-based chemotherapy is the standard of care for castration-resistant prostate cancer (CRPC), inevitably, patients develop resistance and decease. Until now, the mechanism and predictive marker for chemoresistance are poorly understood. EXPERIMENTAL DESIGN: Immortalized normal prostate and cancer cell lines stably manipulated with different DAB2IP expression levels were used and treated with chemotherapeutic drugs commonly used in prostate cancer therapy. Cell proliferation was measured using MTT assay; Western blot, quantitative PCR, and luciferase reporter assays were used to analyze Clusterin gene regulation by DAB2IP. Immunohistochemical analysis was conducted for evaluating DAB2IP, Clusterin and Egr-1 expression in human prostate cancer tissue. RESULTS: DAB2IP Knockdown (KD) cells exhibited resistance to several chemotherapeutic drugs, whereas increased DAB2IP in C4-2 cells restored the drug sensitivity. Parallel, DAB2IP KD cells exhibited higher expression of Clusterin, an antiapoptotic factor, whereas elevated DAB2IP in C4-2 cells decreased Clusterin expression. Functionally, knocking down Clusterin by short-hairpin RNA or antisense oligonucleotide OGX-011 decreased drug resistance, whereas overexpressing Clusterin in C4-2 D2 enhanced drug resistance. Mechanistically, DAB2IP blocked the cross-talk between Wnt/β-catenin and IGF-I signaling, leading to the suppression of Egr-1 that is responsible for Clusterin expression. A similar result was observed in the prostate of DAB2IP knockout animals. In addition, we observed a significantly inverse correlation between DAB2IP and Egr-1 or Clusterin expression from clinical tissue microarray. CONCLUSIONS: This study unveils a new regulation of the Egr-1/Clusterin signaling network by DAB2IP. Loss of DAB2IP expression in CRPC cells signifies their chemoresistance. Clusterin is a key target for developing more effective CRPC therapy.
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".