Antitumor activity of cell‐penetrant kinin B1 receptor antagonists in human triple‐negative breast cancer cells
Bibliographic record
Abstract
High nuclear expression of G protein-coupled receptors, including kinin B1 receptors (B1R), has been observed in several human cancers, but the clinical significance of this is unknown. We put forward the hypothesis that these "nuclearized" kinin B1R contribute to tumorigenicity and can be a new target in anticancer strategies. Our initial immunostaining and ultrastructural electron microscopy analyses demonstrated high B1R expression predominantly located at internal/nuclear compartments in the MDA-MB-231 triple-negative breast cancer (TNBC) cell line as well as in clinical samples of patients with TNBC. On the basis of these findings, in the present study, we evaluated the anticancer therapeutic potential of newly identified, cell-permeable B1R antagonists in MDA-MB-231 cells (ligand-receptor binding/activity assays and LC-MS/MS analyses). We found that these compounds (SSR240612, NG67, and N2000) were more toxic to MDA-MB-231 cells in comparison with low- or non-B1R expressing MCF-10A normal human mammary epithelial cells and COS-1 cells, respectively (clonogenic, MTT proliferative/cytocidal assays, and fluorescence-activated cell-sorting (FACS)-based apoptosis analyses). By comparison, the peptide B1R antagonist R954 unable to cross cell membrane failed to produce anticancer effects. Furthermore, the putative mechanisms underlying the anticancer activities of cell-penetrant B1R antagonists were assessed by analyzing cell cycle regulation and signaling molecules related to cell survival and apoptosis (FACS and western blot). Finally, drug combination experiments showed that cell-penetrant B1R antagonists can cooperate with suboptimal doses of chemotherapeutic agents (doxorubicin and paclitaxel) to promote TNBC death. This study provides evidence on the potential value of internally acting kinin B1R antagonists in averting growth of breast cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".