Integrative Modeling Reveals Annexin A2-mediated Epigenetic Control of Mesenchymal Glioblastoma
Journal article, 2016

Glioblastomas are characterized by transcriptionally distinct subtypes, but despite possible clinical relevance, their regulation remains poorly understood. The commonly used molecular classification systems for GBM all identify a subtype with high expression of mesenchymal marker transcripts, strongly associated with invasive growth. We used a comprehensive data-driven network modeling technique (augmented sparse inverse covariance selection, aSICS) to define separate genomic, epigenetic, and transcriptional regulators of glioblastoma subtypes. Our model identified Annexin A2 (ANXA2) as a novel methylation-controlled positive regulator of the mesenchymal subtype. Subsequent evaluation in two independent cohorts established ANXA2 expression as a prognostic factor that is dependent on ANXA2 promoter methylation. ANXA2 knockdown in primary glioblastoma stem cell-like cultures suppressed known mesenchymal master regulators, and abrogated cell proliferation and invasion. Our results place ANXA2 at the apex of a regulatory cascade that determines glioblastoma mesenchymal transformation and validate aSICS as a general methodology to uncover regulators of cancer subtypes.

Brain tumor stem cells

Partial correlation based networks

Data integration

Epigenetic regulation

Spare inverse covariance selection

New methods for integrative data analysis

Annexin A2

Master regulators of cancer cell phenotypes


Mesenchymal transformation


Teresia Kling

University of Gothenburg

Roberto Ferrarese

University of Freiburg

Darren Ó hAilín

University of Freiburg

Patrik Johansson

Uppsala University

Dieter Henrik Heiland

University of Freiburg

Fangping Dai

University of Freiburg

Ioannis Vasilikos

University of Freiburg

Astrid Weyerbrock

University of Freiburg

Rebecka Jörnsten

Chalmers, Mathematical Sciences, Mathematical Statistics

University of Gothenburg

Maria Stella Carro

University of Freiburg

Sven Nelander

Uppsala University


2352-3964 (eISSN)

Vol. 12 72-85

Subject Categories

Bioinformatics and Systems Biology

Cancer and Oncology



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