Molecular Markers in Follicular and Oncocytic Thyroid Carcinomas: Clinical Application of Molecular Genetic Testing
Bibliographic record
Abstract
Background: Oncocytic thyroid carcinoma (OTC) was previously considered a variant of follicular thyroid carcinoma (FTC) but has recently been reclassified as a separate form of thyroid cancer. This study aimed to demonstrate that FTC and OTC are fundamentally distinct entities that can potentially be differentiated preoperatively through cytology and/or molecular testing. Methods: A retrospective chart review of patients diagnosed with FTC and OTC operated upon at two university health centers from January 2016 to September 2023 (n = 3219) was conducted. Molecular testing results were correlated with histopathologic diagnosis. Results: Fifty patients met the inclusion criteria. FTC was identified in 27 (54.0%) patients, and OTC in 23 (46.0%) patients. Patients with OTC were older (61.8 years) than FTC patients (51.2 years) (p = 0.013). Moreover, aggressive tumors were found in 39.1% (9/23) of OTCs compared to 11.1% (3/27) of FTCs (p = 0.021). Amongst Bethesda category III and IV nodules, 17 out of 20 (85.0%) OTC cytology reports demonstrated an oncocytic subtype compared to only 5 out of 24 FTC cytology reports (20.8%) (p = 0.002). On molecular testing, the EIF1AX alteration was exclusively present in OTCs while the PAX8/PPARy and PTEN alterations were exclusively found in FTCs. Copy number alterations (CNAs) were found to be more prevalent in OTC (66.7%) compared to FTC (33.3%), and they were not indicative of tumor aggressiveness. Within the OTC group, all three patients who had a TP53 alteration were diagnosed with aggressive cancer. Lastly, the OTCs exhibited a higher frequency of multiple alterations on molecular testing (66.7%) compared to FTCs (33.3%). Conclusion: To our knowledge, this is the largest study to date comparing the clinical application of abnormalities found on molecular testing for FTC and OTC. It further demonstrates the distinct clinicopathological and molecular characteristics of OTC.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".