Enhanced expression of Cyclin D1 and C-myc, a prognostic factor and possible mechanism for recurrence of papillary thyroid carcinoma
Bibliographic record
Abstract
A direct association has been shown between Cyclin D1 and C-myc gene expressions and the proliferation of human thyroid tumor cells. Our previous study showed that increased β catenin led to a reduction in disease-free probability in patients with papillary thyroid cancer. This study was designed to investigate Cyclin D1 and C-myc genes as targets for β catenin function in PTC and to determine the association between genes expression and staging, recurrence, metastasis, and disease-free survival of PTC. This study was conducted via a thorough investigation of available data from medical records as well as paraffin blocks of 77 out of 400 patients over a 10-year period. Cyclin D1 and C-myc gene expression levels were measured using real-time polymerase chain reaction (RT-PCR) and the Kaplan-Meier method was used to evaluate disease-free survival. Higher levels of Cyclin D1 and C-myc gene expressions were observed in patients with recurrence by 8.5 (P = 0.004) and 19.5 (p = 0.0001) folds, respectively. A significant positive correlation was found between Cyclin D1 expression and the cumulative dose of radioactive iodine received by patients (r = -0.2, p value = 0.03). The ten-year survival rate in the patients included in this study was 98.25% while disease-free survival was 48.1%. Higher Cyclin D1 and C-myc gene expression levels were observed in patients with recurrence/distant metastasis. Inversely, lower expression of Cyclin D1 and C-myc genes were associated with better survival of patients (SD, 0.142-0.052) (Mantel-Cox test, P = 0.002). The enhancement of Cyclin D1 and C-myc gene expression may be a potential mechanism for recurrence and aggressiveness of PTC.
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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".