Mitochondrial gene expression-based model for the prediction of thyroid cancer prognosis

Abstract The roles of mitochondrial genes in the development of thyroid cancer (TC) and the associated tumor microenvironment remain to be elucidated. Based on 64 dysregulated mitochondrial genes, unsupervised consensus clustering analysis was performed using TC datasets from The Cancer Genome Atlas and integrated gene expression databases. A dysregulated mitochondrial-based prognostic model was constructed using machine learning. Fourteen prognostic genes were identified, and the correlation between semaphorin 7A (SEMA7A) and immune cell infiltration was validated. The functions of SEMA7A were