Thyroid cancer risk prediction model using m6A RNA methylation regulators: integrated bioinformatics analysis and histological validation.

We screened DEGs from cluster m6A and constructed a highly predictive model with prognostic value by dividing TCGA-THCA into two different clusters and performing m6A score analysis. This study will help clarify the overall impact of m6A modification patterns on thyroid cancer progression and formulate more effective immunotherapy strategies.