A novel prognostic signature of seven genes for the prediction in patients with thymoma.

Purpose: A thymoma is a tumor arising from the epithelium of the thymus, mostly occurring in the anterior mediastinum. The incidence of this disease is low and research progress in this field is slow. Consequently, there is an urgent need to investigate the correlation between molecular regulation and the prediction of survival and prognosis in patients with thymoma.

Methods: We collected thymoma datasets from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) of TCGA datasets were then determined using R software. A gene signature was obtained by screening prognostic DEGs from the TCGA datasets using univariate and multivariate Cox survival analysis. The summation of the weighted expression levels was calculated as a risk score, which could then be used to predict the survival rate and prognosis of patients with thymoma. The validity of this model was verified by the analysis of receiver operating characteristic (ROC) curves and area under the curve (AUC).

Results: In total, 297 DEGs were identified from the integrated results of TCGA datasets. A seven-gene signature, along with a regression model of prognostic risk, was obtained by Cox survival analysis. The expression levels of the seven genes were then weighted and summed to calculate the risk score for each sample. Patients were effectively divided into high- and low-risk groups using the median risk score (P < 0.05). ROC analysis showed that this Cox regression model was effective in predicting the prognosis of patients with thymus tumors (AUC = 0.983, P < 0.05).

Conclusion: For the first time, we identified an effective seven-gene signature in patients with thymic tumors. In the future, the risk and prognosis of patients can be preliminarily assessed using this model, although further testing is required to improve rigor.