Identification and Characterization of TF-lncRNA Regulatory Networks Involved in the Tumorigenesis and Development of Adamantinomatous Craniopharyngioma

Abstract

Craniopharyngiomas (CPs) are rare tumors arising from the sellar region. Although the best outcome for patients with one subtype, adamantinomatous craniopharyngioma (ACP), is obtained by gross total resection, little is known about the roles of long noncoding RNAs (lncRNAs) and transcription factors (TFs) in ACP tumorigenesis. In total, 12 human ACP and 5 control samples were subjected to transcriptome-level sequencing. We built an integrated algorithm for identifying lncRNAs and TFs regulating the CP-related pathway. Furthermore, ChIP-Seq datasets with binding domain information were used to further verify and identify TF-lncRNA correlations. RT–PCR and immunohistochemistry staining were performed to validate the potential targets. Five pathways associated with ACP were identified and defined by an extensive literature search. Based on the specific pathways and the whole gene expression profile, 266 ACP-related lncRNAs and 39 TFs were identified by our integrating algorithm. Comprehensive analysis of the ChIP-Seq datasets revealed that 29 TFs were targeted by 12000 lncRNAs in a wide range of tissues, including 161 ACP-related lncRNAs that were identified by the computational method. These 29 TFs and 161 lncRNAs, constituting 1004 TF-lncRNA pairs, were shown to potentially regulate different ACP-related pathways. A total of 232 TF-lncRNA networks were consequently established based on differential gene expression. Validation by RT–PCR and immunohistochemistry staining revealed positive expression of the ACP-related TFs E2F2 and KLF5 in ACP. Moreover, the expression of the lncRNA RP11-360P21.2 was shown to be upregulated in ACP tissues. In this study, we introduced an integrated algorithm for identifying lncRNAs and TFs regulating the ACP-related pathway. This is the first comprehensive study to systematically investigate the potential TF and lncRNA regulatory network in ACP. The resulting data serve as a valuable resource for understanding the mechanisms underlying ACP-related lncRNAs and TFs.