Anaplastic thyroid carcinoma exhibits intratumoral molecular homogeneity for a therapeutic target panel.
Bibliographic record
Abstract
BACKGROUND: The objective of this work was to determine if molecular heterogeneity exists between different intratumoral histological subtype foci of anaplastic thyroid carcinoma (ATC). MATERIALS AND METHODS: A tissue microarray composed of 12 ATC specimens from 6 patients (two discrete histological subtype foci from each tumor) were evaluated for expression of 51 different molecular markers. Significant associations between marker staining and tumor focus (primary versus secondary) or subtype (epithelioid, giant cell, or spindled) were determined using contingency table statistics and samples and markers were clustered using a hierarchical clustering algorithm. Correlation between marker staining for the two tumor foci was also evaluated for each patient using a Spearman correlation. RESULTS: Significant correlations and clustering were observed for the overall staining patterns for paired anaplastic foci from the same patient. This suggests that the different intratumoral foci showed consistent or homogeneous staining. CONCLUSION: These results suggest that observed ATC phenotypic heterogeneity does not necessarily reflect heterogeneity for therapeutic target expression.
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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 | 0.000 |
| 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) | 0.001 | 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".