Using spatial transcriptomics to identify pathways for malignant transformation in pleomorphic adenoma
Bibliographic record
Abstract
Background: Pleomorphic adenomas are common benign salivary gland tumors, yet 3-12% undergo malignant transformation into carcinoma ex pleomorphic adenoma (CXPA). The molecular mechanisms underlying this transformation, remain incompletely understood. Methods: We employed spatial transcriptomics using the Xenium platform to analyze two FFPE CXPA specimens, comparing gene expression across normal salivary gland, conventional PA (cPA), and areas of malignant transformation. We performed differential gene expression analysis using a 280-gene breast cancer panel, followed by gene ontology enrichment and immunofluorescence validation. Results: Analysis revealed FASN as the sole upregulated gene in CXPA compared to cPA across both samples. Gene ontology analysis revealed enrichment in fatty acid metabolism, platinum drug resistance, and AMPK signaling pathways. Immunofluorescence confirmed FASN protein overexpression specifically in malignant cells. Conclusion: Our findings identify FASN-mediated lipogenesis as a potential marker in salivary gland tumors and may be further explored as a diagnostic marker and potential therapeutic target for CXPA.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".