Integrated bioinformatics analysis for the identification of key genes and signaling pathways in thyroid carcinoma

Thyroid carcinoma (TC) is one of the most common types of endocrine neoplasm with poor prognosis due to its aggressive behavior. Biomarkers for early diagnosis and prevention of TC are in urgent demand. By using a bioinformatics analysis, the present study aimed to identify essential genes and pathways associated with TC. First, the GSE27155 and GSE50901 expression profiles were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were obtained using the two microarray datasets and further subjected to integrated analysis. A gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed 45 common DEGs in the two datasets. GO and KEGG pathway analysis indicated that the biological functions of the DEGs included protein binding, cardiac muscle cell potential involved in contraction, aldehyde dehydrogenase activity, the TGF-β receptor signaling pathway and the canonical Wnt signaling pathway. A protein-protein interaction network was also constructed and visualized to display the nodes of the top 9 up- and 36 downregulated common DEGs. The integrated bioinformatics analysis indicated that potassium inwardly rectifying channel subfamily J member 2 (KCNJ2) was the most significantly upregulated DEG. The transcriptional levels of KCNJ2 were confirmed to be elevated in TC tissues compared with those in normal tissues using reverse transcription-quantitative PCR analysis. Furthermore, the expression level of KCNJ2 was significantly associated with the 5-year survival rate of patients with TC, which was determined using the Kaplan-Meier method. In TC cell lines, KCNJ2 was also upregulated as compared with that in a normal control cell line. Finally, small interfering RNA was used to knock down the expression of KCNJ2, which was demonstrated to inhibit cell proliferation, migration and invasion, while increasing apoptosis in TC cells. In conclusion, in the present study, KCNJ2 was screened as an oncogene with a crucial role in TC development and progression and may represent a promising candidate biomarker and therapeutic target for TC.