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The nucleolus is the most prominent substructure of the nucleus. When it was first discovered, it was considered to be an isolated organelle that forms fibrils and granules. In 1931, the relationship between the nucleolus and chromosomes was first described by Heitz. He observed that the appearance and size of nucleolus varies depending on the stage of the cell cycle. He also noticed constricted regions on different chromosomes clustered together at definite cell cycle stages. These regions,...
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Related Experiment Video

Updated: Jun 15, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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Thyroiditis and Thyroid Cancer: Bioinformatics Analysis of Gene Expression Data.

Szu-I Yu1,2, Yu-Kang Chang2, Meei-Ling Sheu3,4,5

  • 1Institute of Biomedical Sciences, National Chung Hsing University, Taichung, Taiwan, R.O.C.

In Vivo (Athens, Greece)
|August 26, 2024
PubMed
Summary

Researchers identified four key genes (CXCR4, IL6ST, PPARG, TP53) as potential biomarkers for thyroiditis and thyroid cancer progression. These findings highlight promising targets for understanding and potentially treating these thyroid conditions.

Keywords:
PPARGPPARgamma geneTP53 bioinformaticsThyroiditisthyroid cancer

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Area of Science:

  • Endocrinology
  • Oncology
  • Genetics

Background:

  • Hashimoto thyroiditis (HT) is linked to thyroid lymphoma, but its association with papillary thyroid cancer (PTC) remains unclear.
  • Thyroid cancer incidence is rising, with slow-growing types often treatable.
  • Identifying biomarkers for thyroiditis-to-cancer progression is crucial.

Purpose of the Study:

  • To identify potential gene biomarkers associated with the progression from thyroiditis to thyroid cancer.
  • To analyze public gene expression datasets for differentially expressed genes (DEGs).

Main Methods:

  • Analysis of public gene expression datasets to identify 70 DEGs.
  • Prioritization of risk genes using statistical analysis and a scoring system based on six functional annotations.
  • Evaluation of gene expression and overall survival using Kaplan-Meier plots.
  • Construction of a protein-protein interaction (PPI) network to validate gene associations.

Main Results:

  • Four genes—CXCR4, IL6ST, PPARG, and TP53—were identified as highly relevant.
  • These genes were prioritized as potential biomarkers for thyroiditis and thyroid cancer.
  • Gene expression levels were assessed for their correlation with overall survival.

Conclusions:

  • The identified genes (CXCR4, IL6ST, PPARG, TP53) show significant relevance to thyroiditis and thyroid cancer.
  • These genes warrant further investigation to elucidate their role in the pathogenesis of these conditions.
  • The study provides a foundation for future research into thyroid disease biomarkers.