Recognition of Key Genes in Human Anaplastic Thyroid Cancer via the Weighing Gene Coexpression Network

Abstract

Background and Objective. Anaplastic thyroid cancer (ATC) gains the definition as an aggressive tumor that has been found in human beings. It has been put in researches that complex gene interaction networks exert an influence on ATC tumor in terms of occurrence and prognosis. Therefore, this study is conducted with the purpose of recognizing possible key genes that have relation with prognosis and pathogenesis of ATC. Methods. For determining pathways and key genes that have relation with development of ATC, differentially expressed genes (DEGs) from GSE33630 as well as GSE65144 expression microarray were screened. Furthermore, we also worked on carrying out the task of constructing a protein-protein interaction (PPI) network and the work of weighing gene coexpression network (WGCNA). DAVID was utilized for the performance of the Gene Ontology (GO) as well as KEGG pathway enrichment analyses for DEGs. We used TCGA THCA data and GSE53072 to further verify the hub gene and hub pathway. Results. We came to the conclusion of the recognition of a total of 1063 genes as DEGs. Analysis regarding functional and pathway enrichment showed that there existed a notable enrichment of upregulated DEGs in the organization of extracellular structure and matrix organization, as well as in organelle fission and nuclear division. The downregulated DEG was markedly gathered in the thyroid hormone metabolic process and generation, as well as in the metabolic process of cellular modified amino acid. We identified 10 hub genes (CXCL8, CDH1, AURKA, CCNA2, FN1, CDK1, ITGAM, CDC20, MMP9, and KIF11) through the PPI network, which might be strongly linked to the carcinogenesis and the development of ATC. In the coexpression network, 6 modules that were relevant to ATC were recognized. The modules were related to the interaction of signaling pathway of p53, Hippo, PI3K/Akt, and ECM-receptor. This hub genes and hub pathway were further successfully validated as a potential biomarker for carcinogenesis and prediction in another database GSE53072. Conclusion. To summarize, this research displayed an illustration of hub genes and pathways that had relation with ATC development, which suggested that DEGs and hub genes, recognized on the basis of bioinformatics analyses, were valuable in the diagnosis for patients with ATC.

Update on current diagnosis and management of anaplastic thyroid carcinoma

“…Additionally, epigenetic-related genes, i.e., the chromatin remodeling SWI/SNF complex in 36% of cases, histone methyltransferases in 24% of cases, and DNA mismatch repair pathway genes in 10%-15% of cases, were found[ 6 ]. Gong et al [ 54 ] recognized 10 hub genes for anaplastic thyroid carcinoma: CXCL8 , CDH1 , AURKA , CCNA2 , FN1 , CDK1 , ITGAM , CDC20 , MMP9 , and KIF11 . RAS gene mutations have been reported to correlate with increased aggressiveness and increased mortality[ 55 ].…”

Harnessing Immunity to Treat Advanced Thyroid Cancer

“…CXCR4 and CXCR7 expression is associated with large tumor size, advanced TNM staging, and short overall and recurrence-free survival in FTC [ 69 ]. Microarray analysis has revealed that CXCL8 expression is higher in ATC tissues than in normal thyroid tissues [ 70 ]. TAM may facilitate PTC metastasis through paracrine interactions with CXCL8 and CXCR1/2 [ 20 ].…”

Identification and Verification of Potential Biomarkers in Renal Ischemia‐Reperfusion Injury by Integrated Bioinformatic Analysis

“…WGCNA can identify modules of highly correlated genes, and these methods have been widely used in the fields of bioinformatics to identify candidate biomarkers. Gong et al [ 9 ] performed WGCNA and constructed a protein-protein interaction (PPI) network to identify 10 DEGs in human anaplastic thyroid cancer. Zeng et al [ 10 ] performed WGCNA and combined experimental verification to identify two hub genes in nonalcoholic fatty liver disease.…”