Identification of hub genes and potential molecular mechanisms related to radiotherapy in thyroid cancer.

Radiotherapy is a common approach during the treatment of thyroid cancer (THCA). It is urgent to identify the radiotherapy-related gene and explore the underlying mechanisms. An message RNA expression clinical data was gained from the Cancer Genome Atlas. The differential expression genes between normal individuals and THCA patients were identified by the "limma" package of R software. The differential expression genes between the patients without radiation therapy and the patients with radiation therapy were also obtained via the same method. Survival analysis, gene set enrichment analysis, immune analysis, drug sensitivity analysis, gene-miRNA, and nomogram analysis were performed to explore the radiotherapy-related gene value. The results showed that 354 DGEs between the THCA patients without radiation therapy and THCA patients with radiation therapy including the 148 up-regulated genes and 206 down-regulated were screened and displayed by volcano plot. A gene enrichment analysis showed radiation-related genes were enriched in various pathways such as mineral absorption, complement and coagulation cascades, B cell receptor signaling pathway, salivary secretion, and hematopoietic cell lineage. Then the hub-related-radiotherapy prognosis gene LRP1B was identified. The expression analysis showed that the LRP1B expression level was higher in normal individuals than in THCA patients with an obvious difference via T test in independent samples and paired samples. Immune analysis results showed that the stroma score, immune score, and ESTIMATES score were higher in the low-risk score than in the high-risk score. LRP1B is a vital gene that executes function via a variety of pathways in THCA patients with radiotherapy. Radiotherapy could reduce the expression of LRP1B and AL356596.1. Moreover, the constructed nomogram is based on risk score and clinical features, and it had a great function in predicting survival time for patients.