Low-dose zoledronate for the treatment of bone metastasis secondary to prostate cancer
Bibliographic record
Abstract
Bisphosphonates (BPs) including zoledronate (zol) have become standard care for bone metastases as they effectively inhibit tumor-induced osteolysis and associated pain. Several studies have also suggested that zol has direct anti-tumor activity. Systemic administration at high doses is the current approach to deliver zol, yet it has been associated with debilitating side effects. Local therapeutic delivery offers the ability to administer much lower total dosage, while at the same time maintaining sustained high-local drug concentration directly at the target treatment site. Here, we aimed to assess effects of lower doses of zol on bone metastases over a longer time. Prostate cancer cell line LAPC4 and prostate-induced bone metastasis cells were treated with zol at 1, 3 and 10 µM for 7 days. Following treatment, cell proliferation was assessed using Almarblue ® , Vybrant MTT ® , and Live/Dead ® viability/cytotoxicity assays. Additionally, cell migration and invasion were carried out using Falcon™ cell culture inserts and Cultrex ® 3D spheroid cell invasion assays respectively. We show that treatment with 3–10 µM zol over 7-days significantly decreased cell proliferation in both the prostate cancer cell line LAPC4 and cells from spine metastases secondary to prostate cancer. Using the same low-dose and longer time course for treatment, we demonstrate that 10 µM zol also significantly inhibits tumor cell migration and 3D-cell growth/invasion. This project harnesses the potential of using zol at low doses for longer treatment periods, which may be a viable treatment modality when coupled with biomaterials or biodevices for local delivery.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".