Open AccessIdentifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis
Author(s) -
Ying Wang,
Xiaolian Zhang,
Huilin Leng,
Yin Wang,
Weizhong Zeng,
Congling Zhang
Publication year - 2020
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.9120
Subject(s) - gene , thyroid cancer , malignancy , thyroid carcinoma , kegg , database , biology , bioinformatics , microarray , gene expression profiling , candidate gene , survival analysis , computational biology , cancer research , cancer , medicine , oncology , gene expression , thyroid , gene ontology , genetics , computer science
Background Thyroid carcinoma (THCA) is a common endocrine malignant tumor. Papillary carcinoma with low degree of malignancy and good prognosis is the most common. It can occur at any age, but it is more common in young adults. Although the mortality rate is decreased due to early diagnosis, the survival rate varies depending on the type of tumor. Therefore, the purpose of this study is to identify hub biomarkers and novel therapeutic targets for THCA. Methods The GSE3467 , GSE3678 , GSE33630 and GSE53157 were obtained from the GEO database, including 100 thyroid tumors and 64 normal tissues to obtain the intersection of differentially expressed genes, and a protein-protein interaction network was constructed to obtain the HUB gene. The corresponding overall survival information from The Cancer Genome Atlas Project-THCA was then included in this research. The signature mechanism was studied by analyzing the gene ontology and the Kyoto Encyclopedia of Genes and Genome database. Results In this research, we identified eight candidate genes (FN1, CCND1, CDH2, CXCL12, MET, IRS1, DCN and FMOD) from the network. Also, expression verification and survival analysis of these candidate genes based on the TCGA database indicate the robustness of the above results. Finally, our hospital samples validated the expression levels of these genes. Conclusion The research identified eight mRNA (four up–regulated and four down–regulated) which serve as signatures and could be a potential prognostic marker of THCA.