ArticleInternational journal of environmental research and public health2020
Network-Based Genetic Profiling Reveals Cellular Pathway Differences Between Follicular Thyroid Carcinoma and Follicular Thyroid Adenoma.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 28 citations in OpenAlex.
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- Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches.International journal of environmental research and public health · 2024Article
- Homeobox and Polycomb target gene methylation in human solid tumors.Scientific reports · 2024Article
- Contribution of FOS in neutrophils to venous thromboembolism via miR-144 based on bioinformatic prediction and validation.Journal of cellular and molecular medicine · 2024Article
- Role of hypermethylated SLC5A8 in follicular thyroid cancer diagnosis and prognosis prediction.World journal of surgical oncology · 2023Article
- Multi-Omics and Management of Follicular Carcinoma of the Thyroid.Biomedicines · 2023Review
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- Assessment of causal association between differentiated thyroid cancer and disordered serum lipid profile: a Mendelian randomization study.Frontiers in endocrinology · 2023Article
- OLFML2A Overexpression Predicts an Unfavorable Prognosis in Patients with AML.Journal of oncology · 2023Article
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- A Prognostic Model of Differentiated Thyroid Cancer Based on Up-Regulated Glycolysis-Related Genes.Frontiers in endocrinology · 2022Article
- Identification of hub genes in thyroid carcinoma to predict prognosis by integrated bioinformatics analysis.Bioengineered · 2021Article
- Article
- Therapeutically Targeting Cancers That Overexpress FOXC1: A Transcriptional Driver of Cell Plasticity, Partial EMT, and Cancer Metastasis.Frontiers in oncology · 2021Review
- Prognostic Value and Significant Pathway Exploration Associated with TOP2A Involved in Papillary Thyroid Cancer.International journal of general medicine · 2021Article
- Network analysis reveals essential proteins that regulate sodium-iodide symporter expression in anaplastic thyroid carcinoma.Scientific reports · 2020Article
- Reciprocal Dysregulation of MiR-146b and MiR-451 Contributes in Malignant Phenotype of Follicular Thyroid Tumor.International journal of molecular sciences · 2020Article
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Authors and funding
7 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular mechanisms underlying the pathogenesis and progression of malignant thyroid cancers, such as follicular thyroid carcinomas (FTCs), and how these differ from benign thyroid lesions, are poorly understood. In this study, we employed network-based integrative analyses of FTC and benign follicular thyroid adenoma (FTA) lesion transcriptomes to identify key genes and pathways that differ between them. We first analysed a microarray gene expression dataset (Gene Expression Omnibus GSE82208, n = 52) obtained from FTC and FTA tissues to identify differentially expressed genes (DEGs). Pathway analyses of these DEGs were then performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) resources to identify potentially important pathways, and protein-protein interactions (PPIs) were examined to identify pathway hub genes. Our data analysis identified 598 DEGs, 133 genes with higher and 465 genes with lower expression in FTCs. We identified four significant pathways (one carbon pool by folate, p53 signalling, progesterone-mediated oocyte maturation signalling, and cell cycle pathways) connected to DEGs with high FTC expression; eight pathways were connected to DEGs with lower relative FTC expression. Ten GO groups were significantly connected with FTC-high expression DEGs and 80 with low-FTC expression DEGs. PPI analysis then identified 12 potential hub genes based on degree and betweenness centrality; namely, TOP2A, JUN, EGFR, CDK1, FOS, CDKN3, EZH2, TYMS, PBK, CDH1, UBE2C, and CCNB2. Moreover, transcription factors (TFs) were identified that may underlie gene expression differences observed between FTC and FTA, including FOXC1, GATA2, YY1, FOXL1, E2F1, NFIC, SRF, TFAP2A, HINFP, and CREB1. We also identified microRNA (miRNAs) that may also affect transcript levels of DEGs; these included hsa-mir-335-5p, -26b-5p, -124-3p, -16-5p, -192-5p, -1-3p, -17-5p, -92a-3p, -215-5p, and -20a-5p. Thus, our study identified DEGs, molecular pathways, TFs, and miRNAs that reflect molecular mechanisms that differ between FTC and benign FTA. Given the general similarities of these lesions and common tissue origin, some of these differences may reflect malignant progression potential, and include useful candidate biomarkers for FTC and identifying factors important for FTC pathogenesis.
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