Related Experiment Video
Updated: Jun 15, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Thyroiditis and Thyroid Cancer: Bioinformatics Analysis of Gene Expression Data
Szu-I Yu1,2, Yu-Kang Chang2, Meei-Ling Sheu3,4,5
1Institute of Biomedical Sciences, National Chung Hsing University, Taichung, Taiwan, R.O.C.
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.
Related Concept Videos
01:20Synthesis and Regulation of Thyroid Hormones
Upon reaching the thyroid gland, TSH stimulates the follicular cells' active uptake of iodide ions from the blood. The ions diffuse to the apical surface of the cells and are oxidized to iodine. The...
02:55The Nucleolus