ArticleMedical science monitor : international medical journal of experimental and clinical research2018
Identification of Key Pathways and Genes in Anaplastic Thyroid Carcinoma via Integrated Bioinformatics Analysis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 29 citations in OpenAlex.
- A RAIR-ATC transcriptional axis and multimodal drug-response modelling reveal class-level vulnerabilities in thyroid cancer.Frontiers in pharmacology · 2026Article
- Bioinformatics analysis reveals C5AR1's impact on thyroid cancer development via immune infiltration.Scientific reports · 2025Article
- TIM3 activates the ERK1/2 pathway to promote invasion and migration of thyroid tumors.PloS one · 2024Article
- GANT61 suppresses cell survival, invasion and epithelial-mesenchymal transition through inactivating AKT/mTOR and JAK/STAT3 pathways in anaplastic thyroid carcinoma.Cancer biology & therapy · 2022Article
- Artificial intelligence perspective in the future of endocrine diseases.Journal of diabetes and metabolic disorders · 2022Review
- Expression of colorectal neoplasia differentially expressed in anaplastic thyroid carcinoma and its effect on cancer cell proliferation.Annals of translational medicine · 2022Article
- Recognition of Key Genes in Human Anaplastic Thyroid Cancer via the Weighing Gene Coexpression Network.BioMed research international · 2022Article
- Aberrant Expression of BUB1B Contributes to the Progression of Thyroid Carcinoma and Predicts Poor Outcomes for Patients.Journal of Cancer · 2022Article
- CDCA8 Contributes to the Development and Progression of Thyroid Cancer through Regulating CDK1.Journal of Cancer · 2022Article
- Identification of hub genes in thyroid carcinoma to predict prognosis by integrated bioinformatics analysis.Bioengineered · 2021Article
- Integrated bioinformatics analysis for the identification of key genes and signaling pathways in thyroid carcinoma.Experimental and therapeutic medicine · 2021Article
- Prognostic Value and Significant Pathway Exploration Associated with TOP2A Involved in Papillary Thyroid Cancer.International journal of general medicine · 2021Article
- TMEM158 May Serve as a Diagnostic Biomarker for Anaplastic Thyroid Carcinoma: An Integrated Bioinformatic Analysis.Current medical science · 2020Article
- Updates on the Management of Thyroid Cancer.Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme · 2020Review
- Key genes involved in cell cycle arrest and DNA damage repair identified in anaplastic thyroid carcinoma using integrated bioinformatics analysis.Translational cancer research · 2020Article
- Identification of Core Prognosis-Related Candidate Genes in Cervical Cancer via Integrated Bioinformatical Analysis.BioMed research international · 2020Article
- Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis.Cancer management and research · 2020Article
- Differently Expressed Genes (DEGs) Relevant to Type 2 Diabetes Mellitus Identification and Pathway Analysis via Integrated Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- Artificial Intelligence and Machine Learning in Endocrinology and Metabolism: The Dawn of a New Era.Frontiers in endocrinology · 2019Article
- Integrated assessment of CDK1 upregulation in thyroid cancer.American journal of translational research · 2019Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND To provide a better understanding of anaplastic thyroid carcinoma (ATC) at the molecular level, this study aimed to identify the genes and key pathways associated with ATC by using integrated bioinformatics analysis. MATERIAL AND METHODS Based on the microarray data GSE9115, GSE65144, and GSE53072 derived from the Gene Expression Omnibus, the differentially expressed genes (DEGs) between ATC samples and normal controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein-protein interaction (PPI) network was constructed and visualized, with which the hub gene nodes were screened out. Finally, modules analysis for the PPI network was performed to further investigate the potential relationships between DEGs and ATC. RESULTS A total of 537 common DEGs were screened out from all 3 datasets, among which 247 genes were upregulated and 275 genes were downregulated. GO analysis indicated that upregulated DEGs were mainly involved in cell division and mitotic nuclear division and the downregulated DEGs were significantly enriched in ventricular cardiac muscle cell action potential. KEGG pathway analysis showed that the upregulated DEGs were mainly enriched in cell cycle and ECM-receptor interaction and the downregulated DEGs were mainly enriched in thyroid hormone synthesis, insulin resistance, and pathways in cancer. The top 10 hub genes in the constructed PPI network were CDK1, CCNB1, TOP2A, AURKB, CCNA2, BUB1, AURKA, CDC20, MAD2L1, and BUB1B. The modules analysis showed that genes in the top 2 significant modules of PPI network were mainly associated with mitotic cell cycle and positive regulation of mitosis, respectively. CONCLUSIONS We identified a series of key genes along with the pathways that were most closely related with ATC initiation and progression. Our results provide a more detailed molecular mechanism for the development of ATC, shedding light on the potential biomarkers and therapeutic targets.
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