Comprehensive bioinformatics analysis unveils THEMIS2 as a carcinogenic indicator related to immune infiltration and prognosis of thyroid cancer

Abstract

AbstractThe aim of this study was to identify biomarkers associated with the initiation and prognosis of thyroid cancer and elucidate the underlying pathogenic mechanisms. We obtained expression profiles and clinical information from the Cancer Genome Atlas (TCGA)-THCA and three datasets (GSE53157, GSE82208, and GSE76039). The three microarray datasets were combined using Perl and the sva package in R and termed ‘merged dataset’. Weighted gene co-expression network analysis (WGCNA) identified 15 gene co-expression modules in the merged dataset and 235 hub genes. Venn diagram analysis revealed 232 overlapping genes between the merged and THCA datasets. Overlapping genes were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The least absolute shrinkage and selection operator (LASSO) regression identified THEMIS2 as a candidate hub gene. Cox, Kaplan–Meier (K–M) survival and gene set enrichment analysis (GSEA) confirmed the correlation of THEMIS2 with overall survival, its enrichment in immunologic processes, and its association with the p53 and JAK-STAT signaling pathways. Its expression was positively correlated with those of immune checkpoints and the infiltration level of immune cells. Receiver operating characteristic curve (ROC) analysis confirmed that THEMIS2, a diagnostic biomarker, could distinguish between tumor and normal specimens. The nomogram (ROC or DCA) model containing THEMIS2, age, and stage predicted favourable prognoses. Thus, THEMIS2 was a biomarker of immune infiltration and prognosis in thyroid cancer.