Abstract
BACKGROUND: Thyroid cancer (THCA) has become increasingly common in recent decades, and women are three to four times more likely to develop it than men. Evidence shows that estrogen has a significant impact on THCA proliferation and growth. Nevertheless, the effects of estrogen-related genes (ERGs) on THCA stages, immunological infiltration, and treatment susceptibility have not been well explored. METHODS: Clinicopathological and transcriptome data of patients with THCA from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were cleaned before consensus clustering. Differential expression analysis was performed on the genes expressed between THCA and paraneoplastic tissues in TCGA, and Wayne analysis was performed on the ERGs obtained from the Gene Set Enrichment Analysis MsigDB and differentially expressed genes (DEGs). Univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were used to identify the set of estrogen-related differentially expressed genes (ERDEGs) associated with progression-free intervals (PFI) and to establish a prediction model. Receiver operating characteristic curves were plotted to calculate the risk scores and PFI status to validate the predictive effect of the model. Enrichment analyses and immune infiltration analyses were performed to analyze DEGs between the high- and low-risk groups, and a nomogram plot was used in the risk model to predict the PFI of THCA. RESULTS: The expression of 120 ERDEGs differed significantly between the two groups (P < 0.05). Five (CD24, CAV1, TACC1, TIPARP, and HSD17B10) of the eight ERDEGs identified using univariate Cox and LASSO regression were validated via RT-qPCR and immunohistochemistry analysis of clinical tissue samples and were used for clinical staging and drug sensitivity analysis. Risk-DEGs were shown to be associated with immune modulation and tumor immune evasion, as well as defense systems, signal transduction, the tumor microenvironment, and immunoregulation. In 19 of the 28 immune cells, infiltration levels differed between the high- and low-risk groups. High-risk patients in the immunotherapy dataset had considerably shorter survival times than low-risk patients. CONCLUSION: We identified and confirmed eight ERDEGs using a systematic analysis and screened sensitive drugs for ERDEGs. These results provide molecular evidence for the involvement of ERGs in controlling the immunological microenvironment and treatment response in THCA.