Integrative Single‐Cell and Machine Learning Analysis Identifies an EMT ‐Associated Prognostic Signature for Papillary Thyroid Cancer | Synapse
April 12, 2026Open Access
Integrative Single‐Cell and Machine Learning Analysis Identifies an EMT ‐Associated Prognostic Signature for Papillary Thyroid Cancer
Key Points
The aim is to identify gene signatures associated with epithelial-mesenchymal transition (EMT) in papillary thyroid cancer (PTC).
Single-cell analysis to evaluate gene expression profiles
Machine learning techniques to identify prognostic signatures
Analysis focused on genes related to epithelial-mesenchymal transition
Eight EMT-related genes identified as prognostic markers
Potential for these genes to serve as biomarkers for PTC
Findings support personalized therapeutic strategies based on gene expression
Abstract
This study identifies eight EMT-related prognostic genes in PTC and highlights their potential value as biomarkers for prognostic evaluation and therapeutic stratification.