Bioinformatics analysis of key genes and latent pathway interactions based on the anaplastic thyroid carcinoma gene expression profile

Abstract

Anaplastic thyroid carcinoma (ATC) is an aggressive malignant disease in older adults with a high mortality rate. The present study aimed to examine several key genes and pathways, which are associated with ATC. The GSE33630 gene expression profile was downloaded from the Gene Expression Omnibus database, which included 11 ATC and 45 normal thyroid samples. The differentially expressed genes (DEGs) in ATC were identified using the Limma package in R. The Gene Ontology functions and Kyoto Encyclopedia of Genes and Genomes pathways of the selected DEGs were enriched using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the DEGs was constructed to select significant modules. Furthermore, a latent pathway interactive network was constructed to select the significant pathways associated with ATC. A total of 665 DEGs in the ATC samples were screened, and four significant modules were selected from the PPI network. The DEGs in the four modules were enriched in several functions and pathways. In addition, 29 significant pathways associated with ATC were selected, and he Toll-like receptor (TLR) signaling pathway, extracellular matrix (ECM)-receptor interaction and cytokine-cytokine interaction pathway were identified as important pathways. FBJ murine osteosarcoma viral oncogene homolog (FOS), chemokine C-X-C motif ligand 10 (CXCL10), collagen type V α1 (COL5A1) and chemokine (C-C motif) ligand 28 (CCL28) were the key DEGs involved in these significant pathways. The data obtained in the present study revealed that the TLR signaling pathway, ECM-receptor interaction and cytokine-cytokine receptor interaction pathway, and the FOS, CXCL10, COL5A1, COL11A1 and CCL28 genes have different roles in the progression of ATC, and these may be used as therapeutic targets for ATC.