The Lysyl Oxidase Inhibitor, β-Aminopropionitrile, Diminishes the Metastatic Colonization Potential of Circulating Breast Cancer Cells
Bibliographic record
Abstract
Lysyl oxidase (LOX), an extracellular matrix remodeling enzyme, appears to have a role in promoting breast cancer cell motility and invasiveness. In addition, increased LOX expression has been correlated with decreases in both metastases-free, and overall survival in breast cancer patients. With this background, we studied the ability of beta-aminopropionitrile (BAPN), an irreversible inhibitor of LOX, to regulate the metastatic colonization potential of the human breast cancer cell line, MDA-MB-231. BAPN was administered daily to mice starting either 1 day prior, on the same day as, or 7 days after intracardiac injection of luciferase expressing MDA-MB-231-Luc2 cells. Development of metastases was monitored by in vivo bioluminescence imaging, and tumor-induced osteolysis was assessed by micro-computed tomography (microCT). We found that BAPN administration was able to reduce the frequency of metastases. Thus, when BAPN treatment was initiated the day before, or on the same day as the intra-cardiac injection of tumor cells, the number of metastases was decreased by 44%, and 27%, and whole-body photon emission rates (reflective of total tumor burden) were diminished by 78%, and 45%, respectively. In contrast, BAPN had no effect on the growth of established metastases. Our findings suggest that LOX activity is required during extravasation and/or initial tissue colonization by circulating MDA-MB-231 cells, lending support to the idea that LOX inhibition might be useful in metastasis prevention.
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 | 0.000 |
| 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".