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An Orthotopic Mouse Model of Anaplastic Thyroid Carcinoma
Published on: April 17, 2013
In Silico Integration Approach Reveals Key MicroRNAs and Their Target Genes in Follicular Thyroid Carcinoma
Shengqing Hu1, Yunfei Liao1, Juan Zheng1
1Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Abstract:
To better understand the molecular mechanism for the pathogenesis of follicular thyroid carcinoma (FTC), this study aimed at identifying key miRNAs and their target genes associated with FTC, as well as analyzing their interactions. Based on the gene microarray data GSE82208 and microRNA dataset GSE62054, the differentially expressed genes (DEGs) and microRNAs (DEMs) were obtained using R and SAM software. The common DEMs from R and SAM were fed to three different bioinformatic tools, TargetScan, miRDB, and miRTarBase, respectively, to predict their biological targets. With DEGs intersected with target genes of DEMs, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed through the DAVID database. Then a protein-protein interaction (PPI) network was constructed by STRING. Finally, the module analysis for PPI network was performed by MCODE and BiNGO. A total of nine DEMs were identified, and their function might work through regulating hub genes in the PPI network especially KIT and EGFR. KEGG analysis showed that intersection genes were enriched in the PI3K-Akt signaling pathway and microRNAs in cancer. In conclusion, the study of miRNA-mRNA network would offer molecular support for differential diagnosis between malignant FTC and benign FTA, providing new insights into the potential targets for follicular thyroid carcinoma diagnosis and treatment.
Insights
This study identifies key microRNAs (miRNAs) and their target genes involved in follicular thyroid carcinoma (FTC) pathogenesis. The findings offer molecular insights for diagnosing and treating FTC.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Follicular thyroid carcinoma (FTC) pathogenesis requires deeper molecular understanding.
- Identifying key regulatory molecules like microRNAs (miRNAs) and their gene targets is crucial for diagnosis and treatment.
Purpose of the Study:
- To identify key differentially expressed miRNAs (DEMs) and their target genes in FTC.
- To analyze the interactions within a miRNA-mRNA regulatory network.
- To explore potential diagnostic and therapeutic targets for FTC.
Main Methods:
- Utilized gene microarray (GSE82208) and microRNA (GSE62054) datasets.
- Employed bioinformatics tools (R, SAM, TargetScan, miRDB, miRTarBase, DAVID, STRING, MCODE, BiNGO) for data analysis.
- Constructed and analyzed a protein-protein interaction (PPI) network.
Main Results:
- Identified nine key DEMs potentially regulating hub genes like KIT and EGFR.
- Enriched pathways included PI3K-Akt signaling and microRNAs in cancer.
- A significant miRNA-mRNA interaction network associated with FTC was elucidated.
Conclusions:
- The identified miRNA-mRNA network provides molecular support for differentiating malignant FTC from benign follicular adenoma (FTA).
- These findings offer novel insights into potential diagnostic and therapeutic targets for FTC.
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