ATPase Copper Transporting Beta (ATP7B) Is a Novel Target for Improving the Therapeutic Efficacy of Docetaxel by Disulfiram/Copper in Human Prostate Cancer
Bibliographic record
Abstract
Docetaxel has been the standard first-line chemotherapy for lethal metastatic prostate cancer (mPCa) since 2004, but resistance to docetaxel treatment is common. The molecular mechanisms of docetaxel resistance remain largely unknown and could be amenable to interventions that mitigate resistance. We have recently discovered that several docetaxel-resistant mPCa cell lines exhibit lower uptake of cellular copper and uniquely express higher levels of a copper exporter protein ATP7B. Knockdown of ATP7B by silencing RNAs (siRNA) sensitized docetaxel-resistant mPCa cells to the growth-inhibitory and apoptotic effects of docetaxel. Importantly, deletions of ATP7B in human mPCa tissues predict significantly better survival of patients after their first chemotherapy than those with wild-type ATP7B (P = 0.0006). In addition, disulfiram (DSF), an FDA-approved drug for the treatment of alcohol dependence, in combination with copper, significantly enhanced the in vivo antitumor effects of docetaxel in a docetaxel-resistant xenograft tumor model. Our analyses also revealed that DSF and copper engaged with ATP7B to decrease protein levels of COMM domain-containing protein 1 (COMMD1), S-phase kinase-associated protein 2 (Skp2), and clusterin and markedly increase protein expression of cyclin-dependent kinase inhibitor 1 (p21/WAF1). Taken together, our results indicate a copper-dependent nutrient vulnerability through ATP7B exporter in docetaxel-resistant prostate cancer for improving the therapeutic efficacy of docetaxel.
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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".