Exploring the Genetic Profiles Linked to Senescence in Thyroid Tumors: Insights on Predicting Disease Progression and Immune Responses

Baoliang Zhang ¹ Yanping Pang ^2*

• ¹ Department of Emergency, Tongji Hospital of Tongji University, Shanghai, China., Shanghai, China
• ² Department of Ultrasound, Tongji Hospital of Tongji University, Shanghai, China., Shanghai, China

Thyroid cancer (THCA) is the most common endocrine tumor, causing a lot of pain each year, and further optimization of prognosis and treatment strategies is urgently needed. Research on cell Senescence Associated Genes (CSAGs), which affect many cancers, is limited in the field of THCA. In this study, we downloaded THCA sample data from several public databases and selected a set of CSAGs for subsequent analysis. differential expression genes (DEGs) obtained by differential analysis were intersected with prognostic genes identified by Cox regression analysis to further study the correlation between the crossed genes. We then used the minimum absolute contraction and selection operator (LASSO) algorithm to construct a prognostic model and verify its efficacy. We also plotted Kaplan-Meier (KM) survival curves and rigorously confirmed the accuracy of the model predictions by receiver operating characteristic (ROC) curves. In addition, to evaluate the predictive power of prognostic models in different phenotypic traits, we performed survival analysis, gene set enrichment analysis (GSEA), and immune-related differential analysis. We also analyzed differences in tumor mutation burden (TMB) and treatment response between high-risk and low-risk patient groups. Finally, we verified the predictive effect of our model on immunotherapy response, and the results proved that our model can be used as a good predictive tool for THCA patients. Our study deepens the understanding of THCA cell aging and provides new therapeutic insights.