Weighted gene co-expression network reveals driver genes contributing to phenotypes of anaplastic thyroid carcinoma and immune checkpoint identification for therapeutic targets

BACKGROUND: Anaplastic thyroid carcinoma (ATC) is a rare but extremely malignant tumor, with a rapid growth rate and early metastasis thus leading to poor survival of patients. The molecular mechanisms underlying these aggressive traits of ATC remain unknown, which impedes the substantial progress in treatment to prolong ATC patient survival. METHODS: We applied weighted gene co-expression network analysis (WGCNA) to identify ATC-specific modules. The Metascape web and R package clusterProfiler were employed to perform enrichment analysis. Combined with differentially expressed gene analysis, we screened out the most potential driver genes and validated them using receiver operator characteristic (ROC) analysis, quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blotting, immunohistochemistry (IHC), and triple immunofluorescence staining. RESULTS: A gene expression matrix covering 75 normal samples, 83 papillary thyroid carcinoma (PTC), 26 follicular thyroid carcinoma (FTC), 19 poor-differentiated thyroid carcinoma (PDTC), and 41 ATC tissue samples were integrated, based on which we detected three most potential ATC-specific modules and found that hub genes of these modules were enriched in distinct biological signals. Hub genes in the turquoise module were mainly enriched in mitotic cell cycle, tube morphogenesis, and cell differentiation, hub genes in the magenta module were mainly clustered in the extracellular matrix organization, positive regulation of cell motility, and regulation of Wnt signaling pathway, while hub genes in the blue module primarily participated in the inflammatory response, innate immune response, and adaptive immune response. We showed that 9 top genes, 8 transcription factors (TFs), and 4 immune checkpoint genes (ICGs) were differentially expressed in ATC compared to other thyroid samples and had high diagnostic values for ATC, among which, 9 novel ATC-specific genes (ADAM12, RNASE2, CASP5, KIAA1524, E2F7, MYBL1, SRPX2, HAVCR2, and TDO2) were validated with our clinical samples. Furthermore, we illustrated that ADAM12, RNASE2, and HAVCR2 were predominantly present in the cytoplasm. CONCLUSION: Our study identified a set of novel ATC-specific genes that were mainly related to cell proliferation, invasion, metastasis, and immunosuppression, which might throw light on molecular mechanisms underlying aggressive phenotypes of ATC and provide promisingly diagnostic biomarkers and therapeutic targets.