A TRPV2 interactome-based signature for prognosis in glioblastoma patients

Abstract

Proteomics aids to the discovery and expansion of protein-protein interaction networks, which are key to understand molecular mechanisms in physiology and physiopathology, but also to infer protein function in a guilt-by-association fashion. In this study we use a systematic protein-protein interaction membrane yeast two-hybrid method to expand the interactome of TRPV2, a cation channel related to nervous system development. After validation of the interactome in silico, we define a TRPV2-interactome signature combining proteomics with the available physio-pathological data in Disgenet to find interactome-disease associations, highlighting nervous system disorders and neoplasms. The TRPV2-interactome signature against available experimental data is capable of discriminating overall risk in glioblastoma multiforme prognosis, progression, recurrence, and chemotherapy resistance. Beyond the impact on glioblastoma physiopathology, this study shows that combining systematic proteomics with in silico methods and available experimental data is key to open new perspectives to define novel biomarkers for diagnosis, prognosis and therapeutics in disease.

Trafficking of Stretch-Regulated TRPV2 and TRPV4 Channels Inferred Through Interactomics

“…Proteomic studies provide useful tools to understand the molecular mechanism of TRPV channels. Guilt-by-association approaches aiming for mid-throughput interactome discovery for TRPV2 and TRPV4 were used, combined with standard techniques such as co-immunoprecipitation in mammalian cell lines and a novel membrane-specific yeast two-hybrid (MYTH) methodology [21,22].…”

“…The blue color intensity may be used to determine whether interactions are strong or constitutive (intense blue color staining) or transient (pale blue color intensity) [43]. Using MYTH, 20 and 44 new interactors were found for TRPV2 and TRPV4, respectively [21,22] (Table S1 and Figure 1b,c).…”

“…The TRIP database is an excellent tool to get relevant information of biological processes regarding TRP channels. To the best of our knowledge, the database was last updated in August 2015, not including any new PPIs, such as the TRPV2 and TRPV4 membrane yeast two-hybrid (MYTH) dataset from these studies [21,24]. Figure 1 and Supplementary Table S1 list all the interactions for TRPV2 and TRPV4.…”

“…Figure 1 and Supplementary Table S1 list all the interactions for TRPV2 and TRPV4. However, for the PPI trafficking analysis performed in this study, only the PPIs identified in MYTH studies [21,22] are used. Using the list of TRPV2 and TRPV4 PPIs, a gene set enrichment analysis (GSEA) is performed, and then all ion channels and transporters filtered out to avoid the bias towards transport and cation transport gene ontology terms.…”

“…Controlled and regulated trafficking of ion channels, especially in excitatory tissues, is fundamental because of the possibility of cation leakage during trafficking, which leads to unbalanced cation homeostasis promoting cell toxicity and/or excitotoxicity. This review of the published protein-protein interactions for the TRPV2 and TRPV4 channels [21][22][23][24] intends to shed light about the proteins involved in the regulated and constitutive trafficking of these two mechanosensory cation channels.…”