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Synthesis and Regulation of Thyroid Hormones

Synthesis and Regulation of Thyroid Hormones

Low blood levels of the thyroid hormones — triiodothyronine (T3) and thyroxine (T4) — signal the hypothalamus to release the thyrotropin-releasing hormone (TRH). TRH then reaches the pituitary gland and stimulates the release of thyroid-stimulating hormone(TSH) into the bloodstream.
Upon reaching the thyroid gland, TSH stimulates the follicular cells' active uptake of iodide ions from the blood. The ions diffuse to the apical surface of the cells and are oxidized to iodine. The...

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Related Experiment Video

Updated: Sep 18, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Spatial Transcriptomics in Thyroid Cancer: Applications, Limitations, and Future Perspectives.

Chaerim Song¹, Hye-Ji Park², Man S Kim¹

¹Translational-Transdisciplinary Research Center, Clinical Research Institute, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul 05278, Republic of Korea.

|June 25, 2025

Summary

This summary is machine-generated.

Spatial transcriptomics (ST) reveals gene expression in thyroid cancer tissues. This technology enhances understanding of tumor heterogeneity, evolution, and cellular interactions for personalized treatments.

Keywords:

precision medicine spatial transcriptomics thyroid cancer tumor microenvironment

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Area of Science:

Oncology
Genomics
Biotechnology

Background:

Thyroid cancer research benefits from understanding gene expression within the tumor microenvironment.
Spatial transcriptomics (ST) offers unprecedented spatial context to gene expression data.

Purpose of the Study:

To review recent applications of ST in thyroid cancer research.
To highlight ST's role in analyzing tumor heterogeneity, evolution, and cellular interactions.
To discuss limitations and future directions for ST in thyroid cancer.

Main Methods:

Review of studies applying spatial transcriptomics to thyroid cancer samples.
Analysis of gene expression patterns and cellular distributions within tumor tissues.
Examination of spatial relationships between cells, ligands, and receptors.

Main Results:

ST enables mapping of distinct cell types and gene expression patterns across thyroid cancer regions.
Spatial context aids in studying tumor invasion, metastasis, and dysregulation at the leading edge.
Accurate inference of signaling pathways through ligand-receptor proximity.

Conclusions:

ST is a powerful tool for dissecting thyroid cancer complexity and heterogeneity.
Overcoming technical limitations (resolution, sequencing depth, sample quality, data handling) is crucial.
Future ST applications hold promise for advancing personalized thyroid cancer treatment.