Seoul National University Hospital
Seoul, South Korea
NCT Number: NCT06969768
This study aims to refine the molecular classification of thyroid cancer (TC) using a multi-omics approach. By identifying a novel gene set and applying decision-tree modeling, the study seeks to improve diagnostic accuracy and predict tumor progression in BRAFV600E-like and RAS-like TC subtypes. Protein biomarkers were validated via immunohistochemistry (IHC), with findings confirmed across external datasets.
Looking for future studies?
Notify Me18 year and older
All sexes
Observational
Seoul, South Korea
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 1 year
The accuracy of the decision-tree model using specific gene set to classify thyroid cancer into BRAFV600E-like, RAS-like, and NT (normal thyroid) -like subtypes. Model performance will be evaluated using accuracy, sensitivity, specificity, and Cohen's kappa.
Looking for future studies?
Notify MeSeoul National University Hospital
Other
Integrative Multi-Omics Refines the Molecular Subtypes of Thyroid Cancers and Enhances Cancer-Progression Prediction
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