A TRPV2 interactome-based signature for prognosis in glioblastoma patients

Pau Doñate-Macián, Antonio Gómez, Irene R. Dégano, Alex Perálvarez-Marín

Research output: Contribution to journalArticleResearchpeer-review

10 Citations (Scopus)


© 2018 Doñate-Macián et al. 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 twohybrid 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.
Original languageEnglish
Pages (from-to)18400-18409
Issue number26
Publication statusPublished - 1 Apr 2018


  • Gene signature
  • Gene-disease associations
  • Glioblastoma multiforme
  • Proteomics
  • TRPV2


Dive into the research topics of 'A TRPV2 interactome-based signature for prognosis in glioblastoma patients'. Together they form a unique fingerprint.

Cite this