Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma

Abstract

Aim Anaplastic thyroid carcinoma (ATC) is the most lethal thyroid malignancy. Identification of novel drug targets is urgently needed. Materials & Methods We re-analyzed several GEO datasets by systematic retrieval and data merging. Differentially expressed genes (DEGs) were filtered out. We also performed pathway enrichment analysis to interpret the data. We predicted key genes based on protein–protein interaction networks, weighted gene co-expression network analysis and genes’ cancer/testis expression pattern. We also further characterized these genes using data from the Cancer Genome Atlas (TCGA) project and gene ontology annotation. Results Cell cycle-related pathways were significantly enriched in upregulated genes in ATC. We identified TRIP13, DLGAP5, HJURP, CDKN3, NEK2, KIF15, TTK, KIF2C, AURKA and TPX2 as cell cycle-related key genes with cancer/testis expression pattern. We further uncovered that most of these putative key genes were critical components during chromosome segregation. Conclusion We predicted several key genes harboring potential therapeutic value in ATC. Cell cycle-related processes, especially chromosome segregation, may be the key to tumorigenesis and treatment of ATC.

Keywords

• Anaplastic thyroid carcinoma
• Key genes identification
• Bioinformatics
• Cancer/testis gene
• Meta-analysis of microarray datasets
• Chromosome segregation