Identification of novel immune-related molecular subtypes and a prognosis model to predict thyroid cancer prognosis and drug resistance - Zhang, Wei; Liu, Ting; Li, Xinyi; Li, Tianshu; Ma, Xiangchi; Zhao, Dongxu; Liu, Yueyang; Zheng, Xueke; Zhao, Xudong (Frontiers in Pharmacology, 2023)
Background: Thyroid cancer as a common malignant tumor in endocrine system has shown increased incidence in recent decades. We explored the relationship between tumor infiltrating immune cell classification and prognosis of thyroid carcinoma. Methods: RNA-seq, SNV, copy number variance (CNV) and methylation of thyroid cancer were downloaded from TCGA dataset. ssGSEA analysis was used to calculated pathway score. Clustering was conducted using ConsensusClusterPlus. Immune infiltration was assessed by ESTIMATE, CIBERSORT. CNV and methylation were determined by GISTIC2 and KNN algorithm. Immunotherapy was predicted by TIDE analysis. Results: 3 molecular subtypes (Immune-enrich(E), Stromal-enrich(E), Immune-deprived(D)) were identified based on 15 pathways and corresponding genes. Samples in Immune-E had higher immune infiltration. Tumor mutation burden (TMB) and mutations in tumor driver genes increased in Immune-D. Methylation in CDH1 was higher in Immune-E. Samples in Immune-E had higher progression-free survival (PFS). Immuno-E was more suitable for immunotherapy and sensitive to small molecule chemotherapeutic drugs. Furthermore, immune score (IMScore) based on 4 genes were constructed, and low group had better survival outcome, which was also validated in 30 cancers. Compared to TIDE score, IMScore had better predictive ability. Conclusion: In this study, a prognostic evaluation model and molecular subtype system of immune-related genes were constructed to predict thyroid cancer prognosis of patients. Moreover, the interaction network between immune genes may play a role by affecting the biological function of immune cells in tumor microenvironment.