Potential role for inhibition of protein phosphatase 2A tumor suppressor in salivary gland malignancies
Bibliographic record
Abstract
The aetiology and pathogenesis of salivary gland malignancies remain unknown. To reveal novel molecular factors behind the development of salivary gland cancer, we performed gene expression analyses from Smgb-Tag mouse salivary gland samples. The overall purpose was to apply these results for clinical use to find new approaches for both possible therapeutic targets and more accurate diagnostic tools. Smgb-Tag mouse strain, in which salivary neoplasms arise through a dysplastic phase in submandibular glands, was investigated using genome-wide microarray expression analysis, ingenuity pathway analysis, RT-PCR, and immunohistochemistry. Thirty-eight human salivary gland adenoid cystic carcinoma samples were investigated using immunohistochemistry for validation purposes. Our genome-wide study showed that Ppp2r1b, a PP2A subunit encoding tumor suppressor gene, is underexpressed in submandibular gland tumors of Smgb-Tag mice. mTOR signaling pathway was significantly enriched and mTOR linked PP2A subunit gene B55 gamma was significantly underexpressed in the analyses. Furthermore, parallel immunohistochemical analysis of three PP2A inhibitors demonstrated that two PP2A inhibitors, CIP2A and SET, are highly expressed in both dysplastic and adenocarcinomatous tumors of the Smgb-Tag mice. In addition, all 38 investigated human salivary adenoid cystic carcinoma samples stained positively for CIP2A and most for SET. Finally, p-S6 staining showed activation of mTOR pathway in human adenoid cystic carcinoma samples. Our results suggest that PP2A inhibition either via PP2A subunit underexpression or PP2A inhibitor overexpression play an important role in the formation of salivary gland malignancy, potentially due to mTOR signaling activation.
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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".