Background:
Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.
Methods:
Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs (NMU, UBE2C, CDKN2A, COL19A1, and GPM6A) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.
Results:
Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score (P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1, and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.
Conclusion:
Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.