Multi-omics, machine learning, and molecular simulation identify CD44 as a candidate target in endocrine-disrupting chemical-associated thyroid cancer progression.

Endocrine-disrupting chemicals (EDCs) are widely present in the environment and consumer products and may disturb thyroid hormone homeostasis. However, the molecular mechanisms linking EDC exposure to thyroid cancer progression remain unclear. This study integrated toxicity prediction, toxicogenomics, transcriptomic analysis, machine learning, molecular simulation, and experimental validation to identify EDC-related key targets in thyroid cancer. ADMETlab 3.0 was used to evaluate the potential toxicity of BPA, PFOA, DDT, BDE-209, TCDD, and DEHP, and compound-related genes were obtained from the CTD database. By integrating thyroid cancer-related genes from multiple disease databases, 1113 shared EDC-thyroid cancer targets were identified and were mainly enriched in PI3K-Akt, FoxO, and AGE-RAGE signaling pathways. Combined with differential expression analysis, machine learning identified a six-gene diagnostic model consisting of FN1, BCL2, CD44, CDKN1A, CTNNB1, and JUN. The Lasso + LDA model achieved an average AUC of 0.976 across the training cohort and three external validation cohorts. CD44 showed robust diagnostic performance, with AUC values of 0.950, 0.801, 0.878, and 0.938 in the training set, GSE27155, GSE29265, and GSE153659, respectively, and had the highest contribution in SHAP analysis. Immune infiltration, TCGA survival, and single-cell analyses indicated that CD44 was associated with the tumor immune microenvironment, cellular state changes, and prognosis. Molecular docking and 200 ns molecular dynamics simulations generated plausible docking poses of BPA, DEHP, and PFOA on CD44, with PFOA showing the most favorable predicted docking score. Experimental validation showed higher CD44 expression in thyroid cancer tissues and cells and increased CD44 expression following EDC exposure. CD44 knockdown attenuated EDC-associated increases in proliferation, colony formation, and migration. These findings identify CD44 as a candidate molecule associated with EDC-responsive malignant phenotypes in thyroid cancer.