Single-cell and machine learning integration reveals OS-driven CCND1 promotes an aggressive phenotype in papillary thyroid carcinoma.

Background: Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, with rising incidence worldwide. Oxidative stress (OS), characterized by an imbalance between reactive oxygen species (ROS) and antioxidant defenses, plays a critical role in tumor initiation and progression. However, the specific relationship between OS and PTC remains underexplored, highlighting the need for further investigation. This study aims to identify OS-related biomarkers in PTC that could potentially be used for clinical diagnosis and treatment. Methods: Single-cell RNA sequencing data from PTC and normal thyroid tissues were analyzed using multiple gene set scoring and differential expression methods to evaluate OS levels across different cell types. Integrated bioinformatics analysis, including WGCNA and machine learning models, was employed to select candidate biomarkers, which were then validated in independent datasets. Pseudotime analysis and CellChat were conducted to explore cell dynamics within the tumor microenvironment. An oxidative stress model was established in TPC-1 cells using hydrogen peroxide treatment. The levels of OS and changes in tumor cell proliferative capacity were assessed through western blotting, immunoblotting, ROS detection, and cell viability assays. Results: The study revealed that Conclusion: