Identification Of Key Genes In Thyroid Carcinoma From GEO Database Via Integrated Bioinformatics Analysis

Background: Thyroid cancer is proved to be one of the well-known and most frequent endocrine system cancers,arising from thyroid tissue.Thyroid cancers are diverse,ranging from the highly aggressive anaplastic thyroid carcinoma to the indolent differentiated thyroid tumors.Stereotypic genetic changes are frequently found in thyroid cancers,depending on the histologic classification.For example,oncogenic mutations in BRAF,NRAS,HRAS,and KRAS(i.e.,the MAPK pathway)are found in about 75% of papillary thyroid carcinoma,with BRAF V600 E being the most common.Most thyroid carcinomas are produced by follicular epithelial cells and range in severity from mild well-differentiated papillary and follicular carcinomas to extra-competitive poorly differentiated carcinomas.Anaplastic thyroid carcinoma is rare but promised to be known as a hard-hitting human tumor.However,it is still an unresolved problem to distinguish thyroid tumors with different prognosis at earlier stage and provide more precise guidance for further treatment.Hence,it has become a feasible solution to explore the gene targets related to thyroid tumors by bioinformatics technology,and then try to answer the contradictions and problems in the process of diagnosis and treatment of thyroid cancer.Objective: The purpose of this study was to uncover new human-friendly and safe treatment targets and hub biomarkers for thyroid carcinoma.Methods: In this study,we used a multitude of bioinformatic analyses which are proven to be reliable in the modern world.A gene expression omnibus database was used to obtain three datasets of thyroid cancer and normal samples.After the differential analysis was done by gene expression omnibus 2R(GEO2R),the intersection of differentially expressed genes from three datasets was obtained by using the Venn diagram package.Moreover,to analyze differentially expressed genes at the functional level,Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were conducted by using a free web tool the Database for Annotation,Visualization,and Integrated Discovery.The protein-protein interaction network was constructed by using STRING and then the hub genes from the interaction network were obtained by using Cytoscape.TF regulatory network was constructed to identify mi RNAs that bind to hub genes.The corresponding overall survival of hub genes from GEPIA-THCA was included in this study.Results: In the present study,we screened 4 key genes,aiming to diagnose and treat thyroid cancer at its early stages.A total of 80 thyroid carcinoma and 24 normal tissue cases were acquired from three datasets obtained from gene expression omnibus.Upon completion of the Venn diagram,we got a total of 495 intersections of all three datasets,39 genes were screened as upregulated,and 69 genes were screened downregulated.Using the STRING database,a PPI network was constructed,and the top10 hub genes(FGFR2,SPP1,BMP2,DPT,TNFRSF11 B,COL3A1,KIT,JUN,FMOD,and RUNX2)were obtained.Moreover,GEPIA2 revealed the significance of FGFR2,TNFRSF11 B,KIT,and JUN from all candidate hub genes by disease-free survival analysis.The receiver operating characteristic(ROC)curve was made by p ROC and ggplot2 packages to explore the prognosis of the patient with high expression hub genes.It was noted that FMOD,BMP2,TNFRSF11 B,and KIT are key genes more likely relevant to thyroid carcinoma.The results were further confirmed by clustering analysis,where FGFR2,TNFRSF11 B,KIT,and JUN were present in cluster 1.Overall results suggest that FGFR2,TNFRSF11 B,KIT,and JUN are found to be important genes,which may help medical professionals with the diagnosis as well as for the treatment ambitions of thyroid cancer patients.Conclusion: In this study,we found out that FGFR2,TNFRSF11 B,KIT and JUN are associated with occurrence and development of thyroid tumors.Combined with the MAPK cascade activation process they are involved in,there is evidence that they affect thyroid tumors.It is speculated that they may participate in the process of thyroid tumors through MAPK cascade activation.In addition,the different expressions of FGFR2,TNFRSF11 B,KIT,and JUN were significantly different from the disease-free survival status of thyroid patients,suggesting that they have an impact on the prognosis and the recurrence of thyroid tumor patients,and may have an important significance for the diagnosis and treatment of thyroid tumors.