Genomics and Multi-Omics to Guide Clinical Management in Thyroid Cancer

Abstract

Thyroid cancer comprises a biologically diverse group of tumors initiated by a limited number of recurrent driver alterations, with additional molecular events promoting dedifferentiation, therapeutic resistance, and aggressive clinical behavior. Advances in tumor sequencing have clarified the molecular architecture of papillary, follicular, oncocytic, poorly differentiated, anaplastic, and medullary thyroid carcinomas, and have already changed management in selected settings. Molecular testing improves diagnostic refinement and risk assessment in cytologically indeterminate thyroid nodules, while alterations involving BRAF, RET, and NTRK can guide targeted therapy in advanced disease. Beyond DNA, transcriptomic, proteomic, epigenetic, metabolomic, immune, spatial, and liquid-biopsy approaches offer functional insight into differentiation state, treatment sensitivity, and resistance, although most remain investigational. Their clinical value depends not only on biological plausibility, but on reproducibility, incremental value beyond established clinicopathological variables, and the ability to alter patient management. Computational tools may further support integration of molecular and clinical data, but their usefulness likewise depends on calibration, external validation, interpretability, and demonstration of decision impact. This review synthesizes the genomic and multi-omics determinants of thyroid cancer management across diagnosis, risk stratification, treatment selection, resistance monitoring, and follow-up, and discusses the practical barriers that continue to limit routine implementation, including assay standardization, cost, access, and real-world feasibility. Progress in precision thyroid oncology will depend on robust validation of emerging biomarkers and clear evidence that they improve patient outcomes.