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Transcriptomic analysis of glioblastoma multiforme providing new insights into GPR17 signaling communication

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Abstract Glioblastoma Multiforme (GBM) is one of the most aggressive malignant tumors in the central nervous system, which arises due to the failure or crosstalk in the signaling networks. GPR17,… Click to show full abstract

Abstract Glioblastoma Multiforme (GBM) is one of the most aggressive malignant tumors in the central nervous system, which arises due to the failure or crosstalk in the signaling networks. GPR17, an orphan G protein-coupled receptor is anticipated to be associated with the biology of the GBM disease progression. In the present study, we have identified the differential expressions of around 170 genes along with GPR17 through the RNA-Seq analysis of 169 GBM samples. Coordinated expression patterns of all other gene products with this receptor were analysed using gene ontology and protein–protein interaction data. Several crucial signaling components and genes that play a significant role in tumor progression have been identified among which GPR17 was found to be significantly interacting with about 30 different pathways. High-throughput molecular docking of GPR17 by homology-based model against differentially expressed proteins, showed effective recognition and binding of PX, SH3, and Ig-like domains besides Gi protein. Pathways of PI3, Src, Ptdn, Ras, cytoplasmic tyrosine kinases, phospholipases, nexins and other proteins possessing these structural domains are identified as critical signaling components of the complex GBM signaling network. Our findings also provide a mechanistic insight of GPR17-T0510-3657 interaction, which potentially regulates the interaction of PX domain and helical mPTS recognition domain-containing proteins. Overall, our results demonstrate that GPR17 mediated signaling networks could be used as a therapeutic target for GBM. Communicated by Ramaswamy H. Sarma

Keywords: analysis; glioblastoma; glioblastoma multiforme; gpr17; gbm

Journal Title: Journal of Biomolecular Structure and Dynamics
Year Published: 2020

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