A biomarker and molecular mechanism investigation for thyroid cancer

INTRODUCTION: This study aimed to reveal the potential molecular mechanism associated with thyroid cancer (THCA) prognosis, and investigate promising biomarkers for THCA. MATERIAL AND METHODS: Differentially expressed genes (DEGs) were compared between THCA samples (THCA group) and normal samples (N group). Then, enrichment analysis and protein-protein interaction (PPI) network analysis were performed, followed by prognostic hub gene exploration from the PPI network. Furthermore, the prognostic and mutation analysis was performed on these hub genes. Finally, the associations of the hub gene with immune cells were investigated. RESULTS: A total of 802 DEGs were obtained between the THCA group and the N group. These DEGs were mainly enriched in pathways such as lysine degradation. From the PPI network, 20 hub genes, including CD44, CCND1, SNAI1, and KIT, were investigated. The survival analysis showed that the up-regulation of CD44 and down-regulation of SNAI1 contributed to the favorable and unfavorable outcomes of patients with THCA, respectively. Meanwhile, the diagnostic analysis showed that the AUC of KIT in THCA was larger than 0.9. Furthermore, the gene mutation analysis showed that the alternated CCND1 participated in the cell cycle pathway. Finally, the correlation analysis showed that prognostic genes such as CD44 were positively correlated with immune cells such as M1 macrophages. CONCLUSIONS: A total of 20 hub genes including CCND1, CD44, SNAI1, and KIT were revealed as potential biomarkers for the differential diagnosis, prognosis, and development of drug targets of THCA. The lysine degradation pathway and cell cycle pathway might take part in the progression of THCA.