The Identification of Three Key Genes Related to Stemness in Thyroid Carcinoma through Comprehensive Analysis

Background: Tumor heterogeneity imposes great challenges on cancer treatment. Cancer stem cells (CSCs) are a leading factor contributing to tumor occurrence. However, the mechanisms underlying the growth of thyroid cancer (TCHA) are still unclear. Methods: Key genes regulating the characteristics of THCA, such as stemness were identified by combining gene expressions of samples downloaded from the Cancer Genome Atlas (TCGA) and were used to establish an mRNA expression stemness index (mRNAsi) through machine learningbased methods. The relationships of mRNAsi, THCA clinical features and molecular subtypes were analyzed. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to obtain mRNAsi-related gene modules and determine mRNAsi-related differentially co-expressed genes. Key genes related to mRNAsi were screened by protein interaction network. Functional analysis was conducted and expressions of key genes were verified in multiple external data sets. Results: The mRNAsi score, which was found to be lower in the TCHA tissues than that in normal tissues (p<0.05), was positively correlated with a slow progression of tumor prognosis (p=0.0085). We screened a total of 83 differentially co-expressed genes related to mRNAsi and multiple tumor pathways such as apoptosis, tight junction, cytokine-cytokine receptor interaction, and cAMP signaling pathway (p<0.05). Finally, 28 protein interaction networks incorporating 32 genes were established, and 3 key genes were identified through network mining. 3 core genes were finally determined, as their low expressions were strongly correlated with the progression of THCA. Conclusion: The study found that NGF, FOS, and GRIA1 are closely related to the characteristics of THCA stem cells. These genes, especially FOS, are highly indicative of the prognosis of THCA patients. Thus, screening therapy could be used to inhibit the stemness of TCHA.