Literature DB >> 27858266

Reverse phase protein arrays enable glioblastoma molecular subtyping.

Gregor Hutter1,2, Martin Sailer3, Tej Deepak Azad4, André O von Bueren5,6,7, Peter Nollau8, Stephan Frank9, Cristobal Tostado3, Durga Sarvepalli10, Arkasubhra Ghosh10, Marie-Françoise Ritz3, Jean-Louis Boulay3, Luigi Mariani3.   

Abstract

In the present study we investigated the phosphorylation status of the 12 most important signaling cascades in glioblastomas. More than 60 tumor and control biopsies from tumor center and periphery (based on neuronavigation) were subjected to selective protein expression analysis using reverse-phase protein arrays (RPPA) incubated with antibodies against posttranslationally modified cancer pathway proteins. The ratio between phosphorylated (or modified) and non-phosphorylated protein was assessed. All samples were histopathologically validated and proteomic profiles correlated with clinical and survival data. By RPPA, we identified three distinct activation patterns within glioblastoma defined by the ratios of pCREB1/CREB1, NOTCH-ICD/NOTCH1, and pGSK3β/GSK3β, respectively. These subclasses demonstrated distinct overall survival patterns in a cohort of patients from a single-institution and in an analysis of publicly available data. In particular, a high pGSK3β/GSK3β-ratio was associated with a poor survival. Wnt-activation/GSK3β-inhibition in U373 and U251 cell lines halted glioma cell proliferation and migration. Gene expression analysis was used as an internal quality control of baseline proteomic data. The protein expression and phosphorylation had a higher resolution, resulting in a better class-subdivision than mRNA based stratification data. Patients with different proteomic profiles from multiple biopsies showed a worse overall survival. The CREB1-, NOTCH1-, GSK3β-phosphorylation status correlated with glioma grades. RPPA represent a fast and reliable tool to supplement morphological diagnosis with pathway-specific information in individual tumors. These data can be exploited for molecular stratification and possible combinatorial treatment planning. Further, our results may optimize current glioma grading algorithms.

Entities:  

Keywords:  Cancer signaling; Glioblastoma; Molecular stratification; Proteomics

Mesh:

Year:  2016        PMID: 27858266     DOI: 10.1007/s11060-016-2316-5

Source DB:  PubMed          Journal:  J Neurooncol        ISSN: 0167-594X            Impact factor:   4.130


  32 in total

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Journal:  Science       Date:  2014-06-12       Impact factor: 47.728

2.  High TGFbeta-Smad activity confers poor prognosis in glioma patients and promotes cell proliferation depending on the methylation of the PDGF-B gene.

Authors:  Alejandra Bruna; Rachel S Darken; Federico Rojo; Alberto Ocaña; Silvia Peñuelas; Alexandra Arias; Raquel Paris; Avelina Tortosa; Jaume Mora; Jose Baselga; Joan Seoane
Journal:  Cancer Cell       Date:  2007-02       Impact factor: 31.743

3.  EGFR signals to mTOR through PKC and independently of Akt in glioma.

Authors:  Qi-Wen Fan; Christine Cheng; Zachary A Knight; Daphne Haas-Kogan; David Stokoe; C David James; Frank McCormick; Kevan M Shokat; William A Weiss
Journal:  Sci Signal       Date:  2009-01-27       Impact factor: 8.192

4.  Glycogen synthase kinase-3beta modulates notch signaling and stability.

Authors:  Daniel R Foltz; Michelle C Santiago; Bridget E Berechid; Jeffrey S Nye
Journal:  Curr Biol       Date:  2002-06-25       Impact factor: 10.834

5.  GSK-3alpha regulates production of Alzheimer's disease amyloid-beta peptides.

Authors:  Christopher J Phiel; Christina A Wilson; Virginia M-Y Lee; Peter S Klein
Journal:  Nature       Date:  2003-05-22       Impact factor: 49.962

6.  Knockdown of GluR1 expression by RNA interference inhibits glioma proliferation.

Authors:  John F de Groot; Yuji Piao; Li Lu; Gregory N Fuller; W K Alfred Yung
Journal:  J Neurooncol       Date:  2008-06       Impact factor: 4.130

7.  Glioblastoma subclasses can be defined by activity among signal transduction pathways and associated genomic alterations.

Authors:  Cameron Brennan; Hiroyuki Momota; Dolores Hambardzumyan; Tatsuya Ozawa; Adesh Tandon; Alicia Pedraza; Eric Holland
Journal:  PLoS One       Date:  2009-11-13       Impact factor: 3.240

8.  GSK3beta regulates differentiation and growth arrest in glioblastoma.

Authors:  Serdar Korur; Roland M Huber; Balasubramanian Sivasankaran; Michael Petrich; Pier Morin; Brian A Hemmings; Adrian Merlo; Maria Maddalena Lino
Journal:  PLoS One       Date:  2009-10-13       Impact factor: 3.240

9.  Visualizing molecular profiles of glioblastoma with GBM-BioDP.

Authors:  Orieta Celiku; Seth Johnson; Shuping Zhao; Kevin Camphausen; Uma Shankavaram
Journal:  PLoS One       Date:  2014-07-10       Impact factor: 3.240

10.  Selective CREB-dependent cyclin expression mediated by the PI3K and MAPK pathways supports glioma cell proliferation.

Authors:  P Daniel; G Filiz; D V Brown; F Hollande; M Gonzales; G D'Abaco; N Papalexis; W A Phillips; J Malaterre; R G Ramsay; T Mantamadiotis
Journal:  Oncogenesis       Date:  2014-06-30       Impact factor: 7.485

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Authors:  Evan K Day; Anne Campbell; Ashley Pandolf; Troy Rogerson; Qing Zhong; Aizhen Xiao; Benjamin Purow; Matthew J Lazzara
Journal:  Mol Ther       Date:  2020-12-15       Impact factor: 11.454

2.  Integrative analysis of multi-platform reverse-phase protein array data for the pharmacodynamic assessment of response to targeted therapies.

Authors:  Adam Byron; Stephan Bernhardt; Bérèngere Ouine; Aurélie Cartier; Kenneth G Macleod; Neil O Carragher; Vonick Sibut; Ulrike Korf; Bryan Serrels; Leanne de Koning
Journal:  Sci Rep       Date:  2020-12-15       Impact factor: 4.379

  2 in total

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