Biomarkers Of Thyroid Papillary Carcinoma And Screening And Identification Of Hub Gene Were Analyzed Based On Bioinformatics

BackgroundPapillary thyroid carcinoma(PTC)originates from thyroid follicular cells,and its incidence has been increasing worldwide in the past two decades,especially in women.At present,exposure to ionizing radiation is considered to be one of the risk factors for disease,and some studies suggest that exposure to radioactive iodine or other radiotherapy measures may also lead to the occurrence of FTC but the specific pathogenesis is still inconclusive.The classic diagnosis of PTC is to perform fine-needle aspiration biopsy after the lesions are found by imaging,but this leads to some unnecessary over-operations.Postoperative pathological examination is the gold standard for PTC diagnosis and prognosis evaluation.With the development of bioinformatics and the emergence of high-throughput sequencing technologies for biomolecules such as mRNA and miRNA,molecular biology has provided a new direction for the research and exploration of PTC diagnosis and treatment.Objective1.Obtain differentially expressed genes in PTC and explere their related biological functions;2.Screen out genes with potcntial for PTC diagnosis;3.Screen out miRNAs with potential for PTC diagnosis and evaluation,and understand their roles in diseases control network.Methods1.Research data:The gene chip and miRNA chip that met the inclusion criteria were screened in the GEO database.The analysis tool was RStudio Desktop based on R 4.2.1,and the software package was downloaded from Bioconductor.2.Gene chip processing:The gene chip data of GSE33630,GSE53157,and GSE3678 are downloaded through the geo_download function of the tinyarray package.The AnnoProbe package is used for the probe ID conversion of the chip.Merge the transformed sets of three arrays and use the sva package to correct for batch differences.The limma package was used for differential expression analysis of gene matrices to obtain differentially expressed genes.Gene enrichment analysis was achieved by combining the clusterProfiler package with the GSEABase package and the DOSE package.The PPI regulatory network was drawn for DEG through the STRING online database,and the results were imported into Cytoscape 3.9.1 to calculate betweenness centrality to screen hub genes.The hub genes were validated on the UALCAN portal and survival enalysis of up-regulated hub genes was performed.3.miRNA chip processing:Differential expression analysis was performed on two miRNA chips(GSE13996 and GSE191117)by GEO2R tool to obtain DEM,and its downstream target genes were predicted in miRNet,Among these target genes,those that overlap with DEGs and whose expression in PTC is opposite to that of miRNAs will be retained.4.Determination of miRNA-gene regulatory relationship:The miRNA-gene regulatory network was drawn in Cytoscape and the enrichment analysis was performed,and the regulation of transcription factors was included when the upstream and downstream regulatory relationship was displayed.ResultsA total of 147 differentially expressed genes were obtained,including 83 up-regulated genes and 64 down-regulated genes.Gene enrichment analysis showed that the differentially expressed genes were mainly involved in biological processes such as PI3K-Akt signaling pathway.A total of 15 hub genes were obtained,and the high expression of APOE and NRCAM genes had a significant impact on the overall survival time of PTC patients.5 of the 6 differentially expressed miRNAs were incorporated into the miRNA-gene regulatory network,and 5 transcription factors including FOSL2 and JUN were also involved in the regulation of differentially expressed genes in the network.ConclusionThrough the bioinformatics analysis of PTC,this study found that 15 hub genes(10 up-regulated,5 down-regulated)can be used as potential markers for the biomolecular diagoosis of PTC,5 hub miRNAs(4 up-regulated,1 down-regulated)also has the same biological functional potential,but hsa-mir-1 5a-5p needs to be further explored.