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Background. Thyroid carcinoma (THCA) is a cancer of the endocrine system that most commonly affects women. Aging-associated genes play a critical role in various cancers. Therefore, we aimed to gain insight into the molecular subtypes of thyroid cancer and whether senescence-related genes can predict the overall prognosis of THCA patients. Methods.Transcriptome-related expression files were obtained from The Cancer Genome Atlas (TCGA) database. These profiles were randomly divided into training and validation subsets at a ratio of 1:1. Unsupervised clustering algorithms were used to compare differences between the two subtypes, and prognosis-related senescence genes were used to further construct our prognostic models by univariate Cox and multivariate Cox analyses and construct a nomogram to predict the 1-, 3-, and 5-year overall survival probability of THCA patients. In addition, we performed gene set enrichment analysis (GSEA) to examine different aspects of THCA-related pathways in the high- and low-risk groups and to predict the immune microenvironment and somatic mutations between the different risk groups. Finally, real-time PCR was used to verify the expression levels of key model genes. Results. The 'ConsensusClusterPlus' R package was used to cluster thyroid cancer into two categories (Cluster1 and Cluster2) on the basis of 46 differentially expressed aging-related genes (DE-ARGs); patients in Cluster1 demonstrated a better prognosis than those in Cluster2. Cox analysis was used to screen six prognosis-related DE-ARGs. The risk score and age were identified as independent prognostic factors. GSEA revealed that most genes were implicated in metabolic signaling pathways. In addition, the two risk model groups differed significantly regarding the immune microenvironment and somatic mutations. Finally, our real-time PCR results confirmed our hypothesis. Conclusion. Differences exist between the two subtypes of thyroid cancer that help guide treatment decisions. The six DE-ARG genes have a high predictive value for risk-stratifying THCA patients, accurately identifying individuals with a potentially poor prognosis, and improving patient prognosis. |
