PIS as a regulator of cellular heterogeneity, prognostic significance, and immune landscape in thyroid cancer

Thyroid cancer (THCA) is a common endocrine malignancy with diverse clinical outcomes and tumor characteristics. In this study, we used single-cell RNA sequencing (scRNA-seq) to explore the cellular makeup and gene expression patterns of THCA. We identified distinct tumor subpopulations with varying differentiation and immune evasion properties. Our analysis revealed how tumor progression is influenced by dynamic gene expression changes over time. We also observed differences in immune cell infiltration across tumor subpopulations, with some showing immune-suppressive traits. A prognostic model, based on genes from a specific tumor subpopulation (RGS5+), outperformed existing models in predicting patient outcomes. Additionally, we found that high PIS (prognostic immune score) was linked to genetic instability, including increased tumor mutations and copy number variations. Key biological pathways associated with different tumor subpopulations were also identified, suggesting potential therapeutic targets. Finally, our analysis indicated that PIS could help predict responses to immunotherapy, with higher scores correlating with poorer treatment outcomes. Our findings highlight the complexity of THCA and emphasize the importance of considering tumor heterogeneity in personalized treatment strategies.