Development and Validation of Potential Molecular Subtypes and Signatures of Thyroid Carcinoma Based on Aging-related Gene Analysis.

Abstract

Background/aim: 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.

Materials and methods: Thyroid carcinoma (THCA) transcriptome-related expression profiles 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; prognosis-related senescence genes were used to further construct our prognostic models by univariate 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 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. 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.