Identification of 14‐3‐3zeta associated protein networks in oral cancer
Bibliographic record
Abstract
Advancements in genomics, proteomics, and bioinformatics have improved our understanding of gene/protein networks involved in intra- and intercellular communication and tumor-host interactions. Using proteomics integrated with bioinformatics, previously we reported overexpression of 14-3-3ζ in premalignant oral lesions and oral squamous cell carcinoma tissues in comparison with normal oral epithelium. 14-3-3ζ emerged as a novel molecular target for therapeutics and a potential prognostic marker in oral squamous cell carcinoma patients. However, the role of 14-3-3ζ in development and progression of oral cancer is not known yet. This study aimed to identify the 14-3-3ζ associated protein networks in oral cancer cell lines using IP-MS/MS and bioinformatics. A total of 287 binding partners of 14-3-3ζ were identified in metastatic (MDA1986) and nonmetastatic (SCC4) oral cancer cell lines including other 14-3-3 isoforms (2%), proteins involved in apoptosis (2%), cytoskeleton (9%), metabolism (16%), and maintenance of redox potential (2%). Our bioinformatics analysis revealed involvement of 14-3-3ζ in protein networks regulating cell cycle, proliferation, apoptosis, cellular trafficking, and endocytosis in oral cancer. In conclusion, our data revealed several novel protein interaction networks involving 14-3-3ζ in oral cancer progression and metastasis.
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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) | 0.000 | 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".