Single-Cell Transcriptomics Decodes the Immunological Landscape of Thyroid Cancer: Implications for Immunotherapeutic Targeting and Precision Oncology.
Jul 2026· Critical reviews in oncology/hematology· Vol 225, pp.
105490
· 0 citations· 57 references
Medicine
TL;DR
It is argued that future efforts must prioritize the functional validation of inferred immune interactions through spatial multi-omics and experimental models, and leverage scRNA-seq data to define therapeutically actionable immune subtypes of the TME.
Abstract
The tumor microenvironment (TME) of thyroid cancer is a complex immunological ecosystem whose composition and interactions critically influence disease progression and therapy resistance. Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative tool to dissect this landscape at unprecedented resolution, moving beyond bulk-tissue analyses to delineate cell-type- specific immune dysfunction, stromal crosstalk, and immunosuppressive niche formation. This review synthesizes how scRNA-seq has elucidated key immunopathological mechanisms in thyroid cancer, including the establishment of dominant immunosuppressive networks involving exhausted CD8⁺ T cells, regulatory T cells, tolerogenic dendritic cells (e.g., LAMP3⁺ DCs), and tumor-associated macrophages. We highlight the discovery of recurrent immunomodulatory signaling axes-such as MIF-(CD74+CXCR4), CCL20-CCR6, and NECTIN2-TIGIT-that orchestrate immune evasion and represent potential pharmacologic targets. Furthermore, we discuss how single-cell-derived insights are fueling the development of immune-centric biomarkers and prognostic models with implications for predicting response to immune checkpoint inhibition and other immunotherapies. However, translational advancement is hampered by the correlative nature of current findings, technical artifacts, and profound inter-tumoral heterogeneity. We argue that future efforts must prioritize the functional validation of inferred immune interactions through spatial multi-omics and experimental models, and leverage scRNA-seq data to define therapeutically actionable immune subtypes of the TME. Bridging this gap will be essential to translate deep immunological profiling into tailored immunomodulatory strategies that improve outcomes for patients with thyroid cancer.
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