Amplification of the human epidermal growth factor receptor 2 gene in differentiated thyroid cancer correlates with telomere shortening
Bibliographic record
Abstract
The human epidermal growth factor receptor 2 (HER2) proto-oncogene plays an important role in the development and progression of breast and gastric cancer. Monitoring of the HER2 status and treatment with trastuzumab was performed initially in breast cancer, and subsequently in gastric cancer. However, the HER2 status of thyroid cancer remains unexplored. Telomere alteration and telomerase activity have been observed in most human cancers and are known to be a feature of malignancy. The aims of this study were to clarify the HER2 status of thyroid cancer and to examine any correlations to various characteristics of malignancy. We investigated 69 cases of differentiated thyroid cancers with reference to: i) telomere length as measured using tissue quantitative fluorescence in situ hybridization (Q-FISH), ii) expression of human telomerase reverse transcriptase (hTERT) as determined by immunohistochemistry (IHC), and iii) overexpression of the HER2 protein as determined by IHC and amplification of the HER2 gene as determined by fluorescence in situ hybridization (FISH). The telomeres of thyroid cancers, especially follicular carcinomas, were significantly shorter compared to those of adjacent normal tissues. Positivity for hTERT expression and HER2 amplification were observed in approximately 70 and 22% of thyroid cancers, respectively. Our data demonstrated that telomeres in HER2-positive cancers were significantly shorter compared to those in HER2-negative cancers. These results suggest that highly malignant differentiated thyroid cancer can be detected by monitoring HER2 status and telomere shortening, and that trastuzumab therapy may be effective for refractory thyroid cancer.
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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) | 0.001 | 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 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".