Decoding Thyroid Disease Heterogeneity Through Single-Cell, Spatial, and Multi-Omics Approaches

Thyroid disease encompasses autoimmune disorders, nodular conditions and thyroid cancers with substantial clinical, cellular and molecular heterogeneity. Conventional bulk molecular assays and clinicopathological classifications often overlook disease-driving cell populations, spatially restricted tissue niches and dynamic interactions among epithelial, immune, stromal and vascular compartments. Recent single-cell RNA sequencing, single-nucleus profiling and spatial transcriptomics studies have begun to define thyroid cellular atlases and reveal disease-associated states, but important questions remain regarding how these states emerge, interact and influence disease progression, treatment response and clinical outcomes. Although multi-omics integration is increasingly being used to connect transcriptional, epigenetic, proteomic and metabolic changes, challenges persist in harmonizing datasets, validating findings across cohorts and translating molecular signatures into clinically useful tools. A more comprehensive investigation is therefore needed to link thyroid tissue organization and cellular programs with disease mechanisms and precision endocrinology.This Research Topic aims to advance the characterization of thyroid disease heterogeneity through integrated single-cell, spatial and multi-omics approaches. It will examine cell-type-specific mechanisms, disease-associated cellular states, microenvironmental remodeling and interactions among thyroid epithelial, immune, stromal and vascular populations in autoimmune thyroid disease, nodular disease and thyroid cancer. The Research Topic will also assess how molecular and spatial signatures relate to clinical phenotypes, disease progression, treatment response and prognosis. Particular emphasis will be placed on studies that combine omics technologies with clinical cohorts, histopathology, functional experiments or independent translational validation to identify robust biomarkers, clarify actionable pathways and support improved diagnosis, risk stratification and therapeutic development.To gather further insights into the cellular, spatial and molecular determinants of thyroid disease, this Research Topic will focus on studies spanning autoimmune thyroid disease, thyroid nodular disease and thyroid cancer, while recognizing the limitations of currently available cohorts, technologies and validation models. We welcome articles addressing, but not limited to, the following themes:o Single-cell and single-nucleus transcriptomic profiling of thyroid tissueso Spatial transcriptomics and high-resolution spatial profiling, including Xenium, Visium and related technologieso Cellular atlases of normal, inflamed, nodular and malignant thyroid tissueo Hashimoto thyroiditis, Graves disease and other autoimmune thyroid disorderso Thyroid cancer heterogeneity, tumor evolution and treatment resistanceo Thyroid follicular cell states and mechanisms of thyroid hormone dysregulationo Immune infiltration and immune–stromal–epithelial communicationo Tumor and inflammatory microenvironmentso Fibrosis, vascular remodeling and tissue architectureo Integrated epigenomic, proteomic and metabolomic analyseso Computational methods for multi-omics integration and spatial data analysiso Biomarker discovery, molecular classification and precision treatmento Integration of omics data with clinical cohorts, pathology and experimental validationAppendix: We welcome Original Research, Reviews, Mini Reviews, Methods, and Perspectives. Topic editors: JIN ZHOU, Juan Pablo Nicola Source: https://www.frontiersin.org/research-topics/85259/decoding-thyroid-disease-heterogeneity-through-single-cell-spatial-and-multi-omics-approaches