Abstract
Advanced and metastatic THCA patients usually have a poor prognosis. Thus, this study aimed to establish a risk model to discriminate the high risk population. The expression and clinical data were obtained from TCGA database. The cluster analysis, lasso, univariate and multivariate cox analyses were used to construct risk model. K-M, ROC and DCA were applied to validate the efficiency and stability of the model. GO, KEGG, and ssGSEA analysis were performed to identify the potential mechanism of signatures. The 7-gene prognosis model was constructed, including FAM27E3, FIGN, GSTM4, BEX5, RBPMS2, PHF13, and DCSTAMP. ROC and DCA results showed our model had a better prognosis prediction performance than other risk models. The high risk score was associated with the poor prognosis of THCA patients with different clinical characteristics. The risk score was closely related to cell cycle. Further, we found that the expressions of signatures were significantly dysregulated in THCA and associated with prognosis. These gene expressions were affected by some clinical characteristics, methylation and CNV. Some signatures played a role in drug sensitivity and pathway activation. We constructed a 7-gene signature model based on the integrin-related genes, which showed a great prognostic value in THCA.