TWIST1 is a molecular marker for a poor prognosis in oral cancer and represents a potential therapeutic target
Bibliographic record
Abstract
BACKGROUND: Locoregional recurrence and distant metastases are ominous events in patients with advanced oral squamous cell carcinoma (OSCC). The objective of this study was to identify functional biomarkers that are predictive of OSCC progression to metastasis. METHODS: The expression profile of a network of epithelial-mesenchymal transition (EMT) genes was investigated in a large cohort of patients with progressive OSCC using a complimentary DNA microarray platform coupled to quantitative reverse transcriptase-polymerase chain reaction and immunohistochemical analyses. Therapeutic potential was investigated in vitro and in vivo using an orthotopic mouse model of metastatic OSCC growing in the tongue microenvironment. RESULTS: Among deregulated EMT genes, the Twist-related protein 1 (TWIST1) transcription factor and several of its regulated genes were significantly overexpressed across advanced stages of OSCC. This result was corroborated by the clinical observation that Twist1 up-regulation predicted the occurrence of lymph node and lung metastases as well as poor patient survival. In support of Twist1 as a driver of OSCC progression, the up-regulation of Twist1 was observed in cells isolated from patients with metastatic OSCC. The inhibition of Twist1 in these metastatic cells induced a potent inhibition of cell invasiveness in vitro as well as progression in vivo. CONCLUSIONS: The current results provide evidence for the prognostic value and therapeutic potential of a network of Twist genes in patients with advanced OSCC.
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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) | 0.000 | 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) | 0.002 | 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 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".