Clinical significance of TC21 overexpression in oral cancer
Bibliographic record
Abstract
BACKGROUND: In search of novel molecular markers for oral cancer, we reported increased levels of TC21/R-Ras2 transcripts in oral squamous cell carcinoma by differential display. The aim of this study was to determine the clinical significance of TC21 in oral cancer. METHODS: Immunohistochemical analysis of TC21 protein expression was carried out in 120 leukoplakias, 83 OSCCs and 30 non-malignant tissues, confirmed by immunoblotting, and correlated with clinicopathological parameters as well as disease prognosis. Co-immunoprecipitation assays were carried out to identify the interaction partners of TC21 protein in oral cancer cells and tissues. RESULTS: TC21 nuclear expression increased from normal oral tissues to leukoplakia and frank malignancy (P < 0.001). TC21 overexpression was observed in 74.2% leukoplakia with no dysplasia, 75.9% dysplasias and 79.5% OSCCs in comparison with normal oral tissues. Receiver operating characteristic analysis showed that the area-under-the curve values were 0.895, 0.885, and 0.919, while the positive predictive values were 95.8%, 95.6%, and 97.1%, for nuclear immunostaining for normal versus leukoplakia with no dysplasia, leukoplakic lesions with dysplasia, and OSCCs, respectively. Immunoblotting confirmed overexpression of TC21 in oral lesions. Using co-immunoprecipitation assays, we showed interactions of TC21 with Erk2, PI3-K, 14-3-3zeta and 14-3-3sigma proteins in oral cancer cells. CONCLUSION: Our findings suggested that alteration in TC21 expression is an early event in oral cancer and correlates with poor prognosis of OSCCs. TC21 interactions with Erk2, PI3-K, 14-3-3zeta and 14-3-3sigma proteins in oral cancer cells and tissues suggests the involvement of TC21 in signaling pathways in oral cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".