Analysis of expression differences of immune genes in Thyroid carcinoma based on TCGA and ImmPort data sets and the application of a prognostic model
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Immune-related genes (IRGs) play a critical role in the tumor immune microenvironment (IME) of Thyroid carcinoma (THCA). The purpose of this study was to analyze the efficacy of the differentially expressed immune-related genes (DEIRGs) in predicting the survival rate of thyroid cancer (THCA). The study used limma R package to obtain the differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA), the ImmPort database to obtain the DEIRGs, and the Cistrome database to obtain the DETFs, to build a TFs-mediated IRGs network. A prediction model for the biomarkers of DEIRGs was established using both univariate and multivariate Cox regression analysis and verify it through experiments. Overall, THCA tissues and nearby non-carcinoma tissues yielded 878 DEGs, 82 DEIRGs, and 6 DETFs. To create a predictive model for THCA, five DEIRGs—including CXCL5, APOD, NOD1, IGHE, and IFNE—were extracted using multivariate Cox regression analysis. In order to forecast the prognosis of THCA and examine immunocyte infiltration, our work finds a prognostic model based on IRGs.This might offer a fresh perspective on investigating the possible IRGs in the THCA IME.
