Investigating Therapeutic Effects of Retinoic Acid on Thyroid Cancer via Protein-Protein Interaction Network Analysis

Background: Thyroid cancer is the most malignant type of endocrine tumor. The molecular investigation of applied treatments for this type of neoplasm could provide a better understanding of their mechanisms of action. Objectives: Here, the differentially expressed proteins from a 2D gel-based proteomics of thyroid cancer cells treated by retinoic acid (RA) were considered for protein-protein interaction (PPI) network analysis. Methods: Eight proteins related to the thyroid cancer cell line (FTC-133) treated with RA were extracted from an investigation by Trojanowicz et al. The query proteins and 50 neighbors were interacted by Cytoscape software via the STRING database. The network was analyzed, and hub-bottlenecks were identified. GeneMANIA determined the relationship between hub-bottlenecks. Protein complex analysis was done via MCODE. ClueGO + CluePedia was used to analyze gene ontology enrichment for hub-bottlenecks, differentially expressed hub-bottlenecks and the central cluster of the constructed network. Results: GAPDH, ENO1, and PKM proteins as hub-bottleneck and PDHB as the seed protein of the main protein complex were introduced as central proteins. However, the query proteins were not included oncogenic proteins, several oncogene genes such as MYC, STAT3, and AKT1among neighbor proteins were connected to the query proteins. The Glycolytic process through fructose-6-phosphate was the leading group of biological processes that were related to the central proteins. Conclusions: It can be concluded that retinoic acid suppressed the activated glycolysis in thyroid cancer cells. The finding can be useful in the follow-up of patients. Additionally, RA regulates many oncogenes that act as a regulator of the determined central proteins.