Aberrant ERBB4-SRC Signaling as a Hallmark of Group 4 Medulloblastoma Revealed by Integrative Phosphoproteomic Profiling

Antoine Forget, Loredana Martignetti, Stéphanie Puget, Laurence Calzone, Sebastian Brabetz, Daniel Picard, Arnau Montagud, Stéphane Liva, Alexandre Sta, Florent Dingli, Guillaume Arras, Jaime Rivera, Damarys Loew, Aurore Besnard, Joëlle Lacombe, Mélanie Pagès, Pascale Varlet, Christelle Dufour, Hua Yu, Audrey L. Mercier, Emilie Indersie, Anaïs Chivet, Sophie Leboucher, Laura Sieber, Kevin Beccaria, Michael Gombert, Frauke D. Meyer, Nan Qin, Jasmin Bartl, Lukas Chavez, Konstantin Okonechnikov, Tanvi Sharma, Venu Thatikonda, Franck Bourdeaut, Celio Pouponnot, Vijay Ramaswamy, Andrey Korshunov, Arndt Borkhardt, Guido Reifenberger, Patrick Poullet, Michael D. Taylor, Marcel Kool, Stefan M. Pfister, Daisuke Kawauchi, Emmanuel Barillot, Marc Remke, Olivier Ayrault
September 2018
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Abstract

The current consensus recognizes four main medulloblastoma subgroups (wingless, Sonic hedgehog, group 3 and group 4). While medulloblastoma subgroups have been characterized extensively at the (epi-)genomic and transcriptomic levels, the proteome and phosphoproteome landscape remain to be comprehensively elucidated. Using quantitative (phospho)-proteomics in primary human medulloblastomas, we unravel distinct posttranscriptional regulation leading to highly divergent oncogenic signaling and kinase activity profiles in groups 3 and 4 medulloblastomas. Specifically, proteomic and phosphoproteomic analyses identify aberrant ERBB4-SRC signaling in group 4. Hence, enforced expression of an activated SRC combined with p53 inactivation induces murine tumors that resemble group 4 medulloblastoma. Therefore, our integrative proteogenomics approach unveils an oncogenic pathway and potential therapeutic vulnerability in the most common medulloblastoma subgroup.

Type
Journal article
Publication
Cancer Cell, (34), 3, pp. 379–395.e7, https://doi.org/10.1016/j.ccell.2018.08.002
data-analysis
Arnau Montagud
Arnau Montagud
Researcher on Computational Systems Biology

My research interests include Boolean and multiscale modelling, data analyses and data integration.

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