Identification of Molecular Markers Altered During Transformation of Differentiated Into Anaplastic Thyroid Carcinoma
Bibliographic record
Abstract
HYPOTHESIS: A change in tumor expression profile will be observed during the transformation of differentiated into anaplastic thyroid carcinoma. DESIGN: Cohort study. SETTING: Population-based sample (British Columbia). PATIENTS: Sequential archival cases of anaplastic thyroid cancer with an adjacent associated differentiated thyroid cancer focus, and with available paraffin blocks, that had been diagnosed and treated in British Columbia during a 20-year period (12 cases; January 1, 1984, through December 31, 2004) were identified through the provincial tumor registry for tissue microarray construction. MAIN OUTCOME MEASURE: Significant associations between marker staining and tumor pathologic diagnosis (differentiated vs anaplastic) were determined with contingency table and marginal homogeneity tests. A classifier algorithm was also used to identify useful and important molecular classifiers. RESULTS: Overall, there were 3 up-regulated and 5 down-regulated markers when comparing the anaplastic carcinoma with associated differentiated thyroid cancers. Contingency table statistics identified 5 markers (thyroglobulin, Bcl-2, MIB-1, E-cadherin, and p53) to be significantly differentially expressed by the anaplastic and differentiated tumor foci. These 5 markers and 3 others (beta-catenin, topoisomerase II-alpha, and vascular endothelial growth factor) were significant when evaluated using the marginal homogeneity test. Clustering and classification analysis based on these same 8 markers readily separated differentiated and anaplastic thyroid tumors with a high degree of accuracy. CONCLUSION: The markers we observed to change during thyroid tumor progression may not only show promise as molecular diagnostic or prognostic tools but also warrant further study as potential targets for treatment of disease.
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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 | 0.000 | 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".