Thyroiditis and Thyroid Cancer: Bioinformatics Analysis of Gene Expression Data

甲状腺炎和甲状腺癌:基因表达数据的生物信息学分析

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Abstract

BACKGROUND/AIM: Hashimoto thyroiditis (HT) association with thyroid lymphoma is well established; however, the association with papillary thyroid cancer (PTC) is still unclear. Thyroid cancer incidence has shown an increasing trend in recent years. It is characterized by slow growth, making it generally amenable to successful treatment. MATERIALS AND METHODS: We aimed to identify genes considered as promising biomarkers of the progression from thyroiditis to thyroid cancer in public gene expression datasets. RESULTS: We identified 70 differentially expressed genes (DEGs) and used them to prioritize biological risk genes for thyroiditis and thyroid cancer. Statistics and a scoring system based on six functional annotations of significant biological impact identified four genes of interest: CXCR4, IL6ST, PPARG and TP53. Kaplan-Meier plots were used to assess the expression levels related to overall survival. Furthermore, a manual bibliographic search was carried out for each gene, and a protein-protein interaction (PPI) network was built to verify their known associations. CONCLUSION: The results showed that all four genes (CXCR4, IL6ST, PPARG, TP53) were highly relevant to thyroiditis and thyroid cancer, thus making them worthy of further investigation to understand their relationship with these two diseases.

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