Identifying hub genes of papillary thyroid carcinoma in the TCGA and GEO database using bioinformatics analysis

• Published in: PeerJ (San Francisco, CA) Vol. 8; p. e9120
• Main Authors: Wan, Ying, Zhang, Xiaolian, Leng, Huilin, Yin, Weihua, Zeng, Wenxing, Zhang, Congling
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 09.07.2020; PeerJ, Inc; PeerJ Inc
• Subjects: Bioinformatics; Biomarker; Biomarkers; Cancer genetics; Carcinoma; Computational Science; CXCL12 protein; Datasets; Gene expression; Genes; Genomes; Genomics; GEO; Health aspects; Malignancy; Medical prognosis; Metabolism; Mortality; mRNA; Oncology; Papillary thyroid carcinoma; Prognosis; Protein interaction; Protein-protein interactions; Proteins; RNA; RNA polymerase; Signature; Survival analysis; TCGA; Therapeutic applications; Thyroid; Thyroid cancer; Thyroid carcinoma; Tumors; Young adults; GEO; Biomarker; Prognosis; TCGA; Signature; Thyroid carcinoma
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.9120

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. 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. 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. 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.