Crizotinib Inhibits Viability, Migration, and Invasion by Suppressing the c-Met/PI3K/Akt Pathway in the Three-Dimensional Bladder Cancer Spheroid Model
Bibliographic record
Abstract
We aimed to evaluate the therapeutic potential of crizotinib, a broad-spectrum tyrosine kinase inhibitor against bladder cancer (BC) cells, based on a three-dimensional (3D) cell culture system. After proliferating cell masses (spheroids) using T24 cisplatin-naïve and T24R2 cisplatin-resistant human BC cell lines, the spheroids were exposed to various crizotinib concentrations in order to derive an ideal crizotinib concentration to suppress cell survival, migration, and invasion. Crizotinib suppressed cell proliferation, migration, and invasion in both T24 and T24R2 BC cell lines under a 3D spheroid model, which was more appropriate than the conventional two-dimensional cell culture model. Real-time quantitative polymerase chain reaction analysis revealed a reduced expression of E-cadherin and an enhanced expression of vimentin, suggesting EMT suppression and the subsequent suppression of tumor aggressiveness following crizotinib administration. Meanwhile, the expressions of apoptosis-related genes increased. Western blot analysis revealed that the expression levels of phosphorylated mesenchymal–epithelial transition factor (c-Met) and phosphorylated Akt decreased following crizotinib administration, suggesting that the antitumor effect of crizotinib can be associated with the inhibition of the phosphorylated activation of the c-Met/PI3K/Akt pathway. Crizotinib showed a potential antitumor effect on both cisplatin-naïve and cisplatin-resistant human BC cells, likely through c-Met-induced PI3K/Akt pathway inhibition.
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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) | 0.001 | 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 | 0.001 |
| 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".