Spatial Transcriptomics in Thyroid Cancer: A PRISMA-Style Systematic Review of Platforms, Architecture, and Clinical Applications
4 affiliations
- 1School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA
- 2Department of Neurosurgery, University of Missouri School of Medicine, Columbia, MO 65212, USA
- 3Department of Otolaryngology-Head & Neck Surgery, Loma Linda University, Loma Linda, CA 92350, USA
- 4Center for Health Disparities, Loma Linda University, Loma Linda, CA 92350, USA
Abstract
Background/Objectives: Thyroid cancer spans indolent differentiated tumors to lethal poorly differentiated and anaplastic carcinomas, and histopathology and molecular testing do not capture the spatial organization of tumor, stromal, and immune compartments that underlies invasion, dedifferentiation, and treatment resistance. Spatial transcriptomics profiles gene expression in situ. We systematically reviewed its platforms, applications, and findings in thyroid cancer. Methods: PubMed/MEDLINE, Scopus, and Web of Science were searched, following PRISMA 2020 guidance and supplemented by citation chasing, for English-language primary studies applying spatially resolved transcriptomics to thyroid cancer tissue. Subtype, platform, complementary methods, and principal findings were extracted, and each study was appraised item by item with the design-matched Joanna Briggs Institute (JBI) checklist. Results: Of 104 records, 21 studies were included: 12 case series, four analytical cross-sectional studies, three single-case reports, and two reanalyses of one public dataset. Nineteen used capture-based whole-transcriptome platforms, predominantly 10x Visium, and two used GeoMx digital spatial profiling; papillary thyroid carcinoma predominated, and medullary carcinoma was not examined. Tumor-microenvironment remodeling accompanying dedifferentiation toward anaplastic carcinoma was replicated in five independent cohorts. Cancer-associated fibroblast activation was reported in three cohorts, although the SERPINE1-positive and POSTN-positive programs were each single-cohort; APOE-linked tumor states appeared in two cohorts with opposite directionality; and invasive-front extracellular-matrix dysregulation in follicular tumors was reported in two. Six studies reported functional perturbation and 12 protein-level validation; no biomarker had independent external validation. Methodological concern was low in four studies, moderate in seven, and high in 10: only one of 12 case series reported consecutive and complete inclusion, eight reported no outcomes for the profiled patients, and nine analyzed spots or cells rather than patients. Conclusions: Spatial transcriptomics has resolved reproducible microenvironmental remodeling during dedifferentiation, but its prognostic and mechanistic claims rest on small, selected cohorts without independent validation. Larger, consecutively enrolled, clinically annotated studies are needed.
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BibTeX
@article{sims2026spatial,
title = {{Spatial Transcriptomics in Thyroid Cancer: A PRISMA-Style Systematic Review of Platforms, Architecture, and Clinical Applications}},
author = {Harel C. Sims and Jason J. Sims and Monica M. Guirgus and Colby S. Grames and Alfred A. Simental and Salma Khan},
journal = {Journal of clinical medicine},
year = {2026},
month = oct,
doi = {10.3390/jcm15197636},
url = {https://europepmc.org/article/PMC/PMC13666090},
note = {CC BY},
}
RIS
TY - JOUR
TI - Spatial Transcriptomics in Thyroid Cancer: A PRISMA-Style Systematic Review of Platforms, Architecture, and Clinical Applications
AU - Harel C. Sims
AU - Jason J. Sims
AU - Monica M. Guirgus
AU - Colby S. Grames
AU - Alfred A. Simental
AU - Salma Khan
PY - 2026
DA - 2026/10/01
JO - Journal of clinical medicine
DO - 10.3390/jcm15197636
UR - https://europepmc.org/article/PMC/PMC13666090
AB - Background/Objectives: Thyroid cancer spans indolent differentiated tumors to lethal poorly differentiated and anaplastic carcinomas, and histopathology and molecular testing do not capture the spatial organization of tumor, stromal, and immune compartments that underlies invasion, dedifferentiation, and treatment resistance. Spatial transcriptomics profiles gene expression in situ. We systematically reviewed its platforms, applications, and findings in thyroid cancer. Methods: PubMed/MEDLINE, Scopus, and Web of Science were searched, following PRISMA 2020 guidance and supplemented by citation chasing, for English-language primary studies applying spatially resolved transcriptomics to thyroid cancer tissue. Subtype, platform, complementary methods, and principal findings were extracted, and each study was appraised item by item with the design-matched Joanna Briggs Institute (JBI) checklist. Results: Of 104 records, 21 studies were included: 12 case series, four analytical cross-sectional studies, three single-case reports, and two reanalyses of one public dataset. Nineteen used capture-based whole-transcriptome platforms, predominantly 10x Visium, and two used GeoMx digital spatial profiling; papillary thyroid carcinoma predominated, and medullary carcinoma was not examined. Tumor-microenvironment remodeling accompanying dedifferentiation toward anaplastic carcinoma was replicated in five independent cohorts. Cancer-associated fibroblast activation was reported in three cohorts, although the SERPINE1-positive and POSTN-positive programs were each single-cohort; APOE-linked tumor states appeared in two cohorts with opposite directionality; and invasive-front extracellular-matrix dysregulation in follicular tumors was reported in two. Six studies reported functional perturbation and 12 protein-level validation; no biomarker had independent external validation. Methodological concern was low in four studies, moderate in seven, and high in 10: only one of 12 case series reported consecutive and complete inclusion, eight reported no outcomes for the profiled patients, and nine analyzed spots or cells rather than patients. Conclusions: Spatial transcriptomics has resolved reproducible microenvironmental remodeling during dedifferentiation, but its prognostic and mechanistic claims rest on small, selected cohorts without independent validation. Larger, consecutively enrolled, clinically annotated studies are needed.
SN - 2077-0383
ER -