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Original Article
- Identification of invasive subpopulations using spatial transcriptome analysis in thyroid follicular tumors
- Ayana Suzuki, Satoshi Nojima, Shinichiro Tahara, Daisuke Motooka, Masaharu Kohara, Daisuke Okuzaki, Mitsuyoshi Hirokawa, Eiichi Morii
- J Pathol Transl Med. 2024;58(1):22-28. Published online January 10, 2024
- DOI: https://doi.org/10.4132/jptm.2023.11.21
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- 4 Crossref
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Abstract
PDF - Background
Follicular tumors include follicular thyroid adenomas and carcinomas; however, it is difficult to distinguish between the two when the cytology or biopsy material is obtained from a portion of the tumor. The presence or absence of invasion in the resected material is used to differentiate between adenomas and carcinomas, which often results in the unnecessary removal of the adenomas. If nodules that may be follicular thyroid carcinomas are identified preoperatively, active surveillance of other nodules as adenomas is possible, which reduces the risk of surgical complications and the expenses incurred during medical treatment. Therefore, we aimed to identify biomarkers in the invasive subpopulation of follicular tumor cells.
Methods
We performed a spatial transcriptome analysis of a case of follicular thyroid carcinoma and examined the dynamics of CD74 expression in 36 cases.
Results
We identified a subpopulation in a region close to the invasive area, and this subpopulation expressed high levels of CD74. Immunohistochemically, CD74 was highly expressed in the invasive and peripheral areas of the tumor.
Conclusions
Although high CD74 expression has been reported in papillary and anaplastic thyroid carcinomas, it has not been analyzed in follicular thyroid carcinomas. Furthermore, the heterogeneity of CD74 expression in thyroid tumors has not yet been reported. The CD74-positive subpopulation identified in this study may be useful in predicting invasion of follicular thyroid carcinomas. -
Citations
Citations to this article as recorded by
- Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning
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Journal of Pathology and Translational Medicine.2025; 59(1): 39. CrossRef - Spatial Transcriptomics in Thyroid Cancer: Applications, Limitations, and Future Perspectives
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Current Issues in Molecular Biology.2025; 47(7): 531. CrossRef - Carbonic Anhydrase 12 as a Novel Prognostic Biomarker and Therapeutic Target for HighâRisk Follicular Thyroid Carcinoma
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Cancer Science.2025;[Epub] CrossRef
- Diagnosis of invasive encapsulated follicular variant papillary thyroid carcinoma by protein-based machine learning
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