Screening and bioinformatics analysis of thyroid cancer-related hub genes

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Screening and bioinformatics analysis of thyroid cancer-related hub genes

Journal Title: TMR Clinical Research - Year 2020, Vol 3, Issue 3

Abstract

Objective: To identify the thyroid cancer-related hub genes and pathways by bioinformatics initially in order to lay the foundation for further study. Methods: The expression profile chips and data of thyroid cancer were screened and downloaded from the gene expression omnibus (GEO). The GEO2R was applied to identify the differential expressed genes between thyroid cancer tissues and normal thyroid tissues. And the Metascape online website was used for pathway and function enrichment. With the usage of STRING and Cytoscape, the protein-protein interaction network was constructed, and the plug-in app cytoHubba in Cytoscape was applied to screen hub genes. Kaplan-Meier Plotter was implemented to conduct survival analysis of hub genes for further screening and discussion. Results: A total of 304 differential expressed genes were screened, and were mainly enriched in the biological processes of extracellular matrix, cell-substrate adhesion, response to wounding, muscle structure development and hormone metabolic process etc. by Metascape. Protein-protein interaction network visualized 284 nodes; the top ten scores of Maximal Clique Centrality algorithm were taken as the criteria to screen out the hub genes with high connectivity in the gene expression network. The KM plotter analysis confirmed that 5 of 9 hub genes were correlated with the prognosis of thyroid cancer patients. Conclusion: FN1, SPP1, TIMP1, VCAN, COL1A1, COL1A2, MMP1, DCN, COMP and FMOD may play a significant role in the development of thyroid cancer. Genes which have prognostic significance in survival analyses were found to be relevant to the composition and regulation of extracellular matrix.

Authors and Affiliations

Shu-Fei Wu1, Shuang Yang1, Jiu Pu2, Zheng-Hai Ling1, Zheng-Wei Leng3*, Ling-Mi Hou4*

Keywords

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EP ID EP686577
DOI 10.12032/TMRCR20200717014
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