RESUMO
Sarcomas are a broad family of cancers that arise from cells of mesenchymal origin in virtually every tissue of the body. Some transcription factors (TFs) have been reported to be involved in the pathogenesis and metastasis of sarcomas. The expression of certain long noncoding RNAs (lncRNAs) has been correlated with the degree of cancer prognosis. There is an urgent need to effectively integrate TFs and lncRNA/microRNA/mRNA regulatory axis and further identify more key regulators that play crucial roles in sarcomas. We performed a network-based computational analysis to investigate the lncRNA-TF cross talks via integrating lncRNA-TF ceRNA interactions and TF-TF protein-protein interactions. Multiple topology analyses were performed to the sarcomas-related global lncRNA-TF network. Several lncRNAs or TFs with central topology structures were identified as key regulators and used to locate a hub-associated lncRNA-TF subnetwork. Three functional modules were identified from the sarcomas-related global lncRNA-TF network, which have shown significant pathway enrichment and prognosis capability. The lncRNAs and TFs of these modules were shown to participate in sarcoma-related biological phenomena through involving in mitogen-activated protein kinases (MAPK), Jak-STAT, and transforming growth factor (TGF-beta) signaling pathways. More importantly, a subset of core lncRNA-TF cross talks that might form positive feedback loops to control biological processes of sarcomas was identified. These core lncRNA-TF positive feedback loops showed more TF binding affinity than other lncRNAs. All the results can help us uncover the molecular mechanism of sarcomas and provide a novel way for diagnosis biomarker and therapeutic target identification.
