Beta-Tubulin III mRNA expression and docetaxel sensitivity in non-small cell lung cancer
Bibliographic record
Abstract
PURPOSE: Despite the success of docetaxel as an anti-tumour agent, the inter-individual variability in drug response still poses a major impediment to further use of this agent in the treatment of cancer. Current knowledge about predictive biomarkers of docetaxel sensitivity in malignant effusions is poor. The aim of this study was to investigate the association between beta-tubulin III mRNA expression and chemosensitivity to docetaxel in metastatic malignant effusions. METHODS: Real-time quantitative PCR was used for analysis of beta-tubulin III mRNA expression in 37 malignant effusions collected prospectively. Viable tumour cells obtained from malignant effusions were tested for sensitivity to docetaxel using ATP-TCA assay. RESULTS: beta-tubulin III expression was inversely correlated with sensitivity to docetaxel in pleural effusions of NSCLC patients (P =0.022). The lower level of beta-tubulin III mRNA expression in malignant effusions was associated with higher chemosensitivity to docetaxel in NSCLC patients in vitro. No correlation was found between beta-tubulin III mRNA expression and docetaxel sensitivity in malignant effusions of gastric cancer patient. CONCLUSION: Our results demonstrated that beta-tubulin III mRNA expression level in malignant effusions, in which all cancer cells were metastatic, was correlated with docetaxel sensitivity in NSCLC. This highlights the potential role of biomarkers in malignant effusions in further customized chemotherapy.
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 | 0.001 |
| 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".