Development of a prognostic model for thyroid cancer based on mitochondrial metabolism-related genes and immune profiling

The preliminary study found that mitochondrial metabolism and structure are abnormal in thyroid cancer (THCA) patients. Therefore, this study systematically investigates the relationship between mitochondrial metabolism-related genes (MMRGs) and the prognosis of THCA patients, while establishing a prognostic model for THCA. This study utilized THCA transcriptome data from the UCSC Xena database, performed differential expression analysis using the “limma” package, and intersected differentially expressed genes (DEGs) with MMRG to identify differentially expressed MMRGs (DEMMRGs). THCA prognostic genes were identified using the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis, and a prognostic model was constructed. Using ssGSEA, CIBERSORT and Immune Phenotype Score methods, we compared differences in immune cell infiltration levels and anti-tumor immune response capacity between distinct risk groups. Furthermore, molecular subtypes of THCA were identified through consensus clustering analysis. This study systematically identified nine MMRGs to construct a robust prognostic prediction model for THCA. Enrichment analysis revealed that patients in the low-risk group exhibited significant enrichment in multiple immune-related pathways, such as T cell-mediated immune responses to tumor cells, and demonstrated stronger responsiveness to anti-CTLA-4 and anti-PD-1 immunotherapies compared to the high-risk group. Further analysis identified two distinct molecular subtypes of THCA: Group 2 exhibited upregulation of immune checkpoint molecules, elevated ESTIMATEScore and StromalScore, and lower TumorPurity. This study adopts the unique perspective of MMRGs to elucidate their pivotal role and molecular basis within the THCA tumor microenvironment, offering novel insights for deepening our understanding of the disease’s pathogenesis and developing innovative therapeutic strategies. Based on prognostic genes, we successfully classified thyroid cancer into two molecular subtypes with distinct immune heterogeneity. In this study, nine mitochondrial metabolism-related genes associated with thyroid cancer were systematically identified and utilized to construct prognostic models. Patients with low-risk thyroid cancer exhibit higher survival rates, and their tumor microenvironments also demonstrate a more active state of immune cell infiltration.