Carbidopa enhances antitumoral activity of bicalutamide on the androgen receptor‐axis in castration‐resistant prostate tumors
Bibliographic record
Abstract
BACKGROUND: Response to bicalutamide after castration failure is not durable and treatment options at this stage are limited. Carbidopa, an L-dopa decarboxylase (AR-coactivator) inhibitor, has been shown to retard prostate tumor growth/PSA production in xenografts. Here, we hypothesize that pharmacological targeting of the AR-axis by combination treatment with bicalutamide plus carbidopa significantly enhances antitumoral activity in vitro and in vivo compared to monotherapy with either drug. METHODS: Carbidopa was tested for its ability to enhance the effects of bicalutamide on cell viability, apoptosis and PSA transactivation in LNCaP and C4-2 cells. The castration-resistant prostate cancer (CRPC) LNCaP xenograft tumor model was used in vivo. After CRPC progression, mice were treated with carbidopa (50 mg/kg) and bicalutamide (50 mg/kg) as monotherapy or in combination. Tumor volume and serum PSA were evaluated weekly. RESULTS: Combination treatment of carbidopa plus bicalutamide significantly inhibited cell viability in both cell lines and induced apoptosis. The combination treatment also decreased androgen-induced PSA transactivation by 62.6% in LNCaP cells and by 55.6% in C4-2 cells compared to control, while bicalutamide monotherapy reduced PSA levels by 27.5% and 29.1% in LNCaP and C4-2 cells. In vivo, bicalutamide monotherapy delayed LNCaP CRPC tumor growth rate by 72.2%, while combination treatment reduced tumor growth by 84.4% compared to control. Serum PSA was also reduced 70.6% with bicalutamide monotherapy, while combination therapy reduced PSA levels by 76.7% compared to control. CONCLUSIONS: This study demonstrates preclinical proof-of-principle that pharmacological targeting of prostate tumors by combination treatment of bicalutamide plus carbidopa significantly reduces AR activity, and thereby delays CRPC tumor progression in vivo.
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.
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 | 0.001 |
| 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 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".