Identification of Prognosis-Associated Biomarkers in Thyroid Carcinoma by a Bioinformatics Analysis.

ABSTRACT:

Background

This study aimed to identify the key genes associated with prognosis in thyroid cancer (TC), and to explore potential pathways.

Methods

GSE66783, GSE58545, and GSE129562 datasets were used to identify differentially expressed genes (DEGs) between tumor and normal tissues, followed by KEGG analyses on DEGs. The protein-protein interaction (PPI) network of DEGs was subsequently constructed to find the top 10 hub genes and seed genes in the whole network. Furthermore, the mRNA expressions of hub genes and prognostic values were explored. Regarding the seed gene, pathway activity score and GSEA analyses were conducted as well.

Results

1) A total of 183 DEGs were consistently expressed in three datasets comprising 76 up-regulated and 107 down-regulated genes. DE

SUBMITTER: Qin Y 

PROVIDER: S-EPMC8454525 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature