Long-term Survivors of Anaplastic Thyroid Cancer: A Genomic Predictive Model
Authors' conclusion
This model identifies mutated genes that are associated with the most aggressive ATCs and thus may aid in preoperative risk assessment when evaluating patients for surgery for curative intent.
Study context
- Population
- Anaplastic thyroid cancer (ATC) samples with sequencing and survival data, cBioPortal database
- Participants
- 204 ATC samples
- Exposure
- More aggressive vs less aggressive risk cohorts
- More aggressiven = 37
- Less aggressiven = 128reference
- Outcome
- Overall survival
Methodological details80% training and 20% validation cohorts, point-based risk model, multi-institutional, international genomic database
- 80% training and 20% validation cohorts
- Point-based risk model
- Multi-institutional, international genomic database
Main finding
As reported in the abstract
1 year
- Risk model C-index
- 0.74
- Genes associated with increased risk: TET1, MAPK12, ATP10A, PIK3CA, MUC4, PNPLA2, PLD4, EGLN2, BSN, FLNC, RADIL, ZMYND8, FRAS1, RECQL4
- 14
Observational data: associations, not effects.
Further findings
Survival in validation cohort and BRAF subanalysis
- Survival remained significantly different between risk cohorts in validation cohort and on BRAF subanalysis
KEGG pathway enrichment
- Significantly increased enrichment across several pathways for more aggressive tumors
Original publication
Long-term Survivors of Anaplastic Thyroid Cancer: A Genomic Predictive Model. J Clin Endocrinol Metab. Published 15 July 2025. doi:10.
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