Anaplastic thyroid cancer – an overview of genetic variations and treatment modalities
Bibliographic record
Abstract
Honey V Reddi,1 Anirudh Kumar,2 Roger Kulstad3 1Transgenomic, Inc., New Haven, CT, USA; 2University of Toronto, Toronto, ON, Canada; 3Division of Endocrinology, Marshfield Clinic, Marshfield, WI, USA Abstract: Anaplastic thyroid carcinoma (ATC) is a rare but highly aggressive malignancy that accounts for about 1%–2% of all thyroid cancer diagnoses but is responsible for up to 30%–40% of thyroid cancer deaths. ATCs are poorly differentiated tumors that develop on the background of preexisting, often undiagnosed, papillary thyroid carcinoma or follicular thyroid carcinoma, through progressive accumulation of changes in several oncogenic and tumor suppressor pathways, including p53, RAS, RAF, Wnt-β-catenin and the PTEN-AKT pathways. Consequently, the 1-year survival rate after diagnosis ranges from 5% to 15%. Current therapeutic approaches are aimed at common late oncogenic changes and involve inhibition of MAPK and PI3K cell proliferation pathways or restoration of p53 and PTEN tumor suppressor pathways. Since single-modality therapy has limited effect on anaplastic thyroid cancer, aggressive multimodal treatments are now the treatment of choice, in spite of which, the mean survival time from diagnosis to death continues to remain at about 6 months. The current review attempts to summarize the genetics involved in the development and progression of ATC and provides some insight into the therapeutic options being evaluated for this aggressive cancer. Keywords: genetic alterations, treatment strategies, diagnostic testing
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".