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Updated: Sep 6, 2025

Spontaneous Murine Model of Anaplastic Thyroid Cancer
Published on: February 3, 2023
Recognition of Key Genes in Human Anaplastic Thyroid Cancer via the Weighing Gene Coexpression Network
Yun Gong1, Fanghua Xu2, Lifei Deng3
1Health Management Center, Jiangxi Provincial People's Hospital (the First Affiliated Hospital of Nanchang Medical College), Nanchang, Jiangxi 330006, China.
Methods:
For determining pathways and key genes that have relation with development of ATC, differentially expressed genes (DEGs) from GSE33630 as well as GSE65144 expression microarray were screened. Furthermore, we also worked on carrying out the task of constructing a protein-protein interaction (PPI) network and the work of weighing gene coexpression network (WGCNA). DAVID was utilized for the performance of the Gene Ontology (GO) as well as KEGG pathway enrichment analyses for DEGs. We used TCGA THCA data and GSE53072 to further verify the hub gene and hub pathway.
Results:
We came to the conclusion of the recognition of a total of 1063 genes as DEGs. Analysis regarding functional and pathway enrichment showed that there existed a notable enrichment of upregulated DEGs in the organization of extracellular structure and matrix organization, as well as in organelle fission and nuclear division. The downregulated DEG was markedly gathered in the thyroid hormone metabolic process and generation, as well as in the metabolic process of cellular modified amino acid. We identified 10 hub genes (CXCL8, CDH1, AURKA, CCNA2, FN1, CDK1, ITGAM, CDC20, MMP9, and KIF11) through the PPI network, which might be strongly linked to the carcinogenesis and the development of ATC. In the coexpression network, 6 modules that were relevant to ATC were recognized. The modules were related to the interaction of signaling pathway of p53, Hippo, PI3K/Akt, and ECM-receptor. This hub genes and hub pathway were further successfully validated as a potential biomarker for carcinogenesis and prediction in another database GSE53072.
Conclusion:
To summarize, this research displayed an illustration of hub genes and pathways that had relation with ATC development, which suggested that DEGs and hub genes, recognized on the basis of bioinformatics analyses, were valuable in the diagnosis for patients with ATC.
Insights
This study identified 10 hub genes and key pathways involved in anaplastic thyroid carcinoma (ATC) development using bioinformatics. These findings offer potential biomarkers for ATC diagnosis and prediction.
Area of Science:
- Genomics and Bioinformatics
- Molecular Oncology
- Biomarker Discovery
Background:
- Anaplastic thyroid carcinoma (ATC) is an aggressive thyroid cancer with limited treatment options.
- Understanding the molecular mechanisms underlying ATC development is crucial for improving patient outcomes.
Purpose of the Study:
- To identify key genes and pathways associated with ATC development.
- To discover potential diagnostic and predictive biomarkers for ATC.
Main Methods:
- Differential gene expression analysis of microarray datasets (GSE33630, GSE65144).
- Construction of protein-protein interaction (PPI) and weighted gene co-expression network (WGCNA).
- Gene Ontology (GO) and KEGG pathway enrichment analyses using DAVID.
- Validation using TCGA THCA and GSE53072 datasets.
Main Results:
- Identified 1063 differentially expressed genes (DEGs) in ATC.
- Upregulated DEGs enriched in extracellular matrix organization; downregulated DEGs in thyroid hormone metabolism.
- Identified 10 hub genes (e.g., CXCL8, CDH1, AURKA) and 6 ATC-relevant modules linked to p53, Hippo, PI3K/Akt, and ECM-receptor signaling pathways.
- Validated hub genes and pathways as potential biomarkers.
Conclusions:
- Bioinformatics analysis revealed significant hub genes and pathways implicated in ATC.
- The identified DEGs and hub genes hold promise as valuable diagnostic biomarkers for ATC patients.
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