期刊
EBIOMEDICINE
卷 12, 期 -, 页码 72-85出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ebiom.2016.08.050
关键词
Glioblastoma; New methods for integrative data analysis; Mesenchymal transformation; Partial correlation based networks; Brain tumor stem cells; Annexin A2; Master regulators of cancer cell phenotypes; Epigenetic regulation; Data integration; Spare inverse covariance selection
资金
- Deutsche Forschungsgemeinschaft (DFG) [CA 1246/2-1]
- Swedish Research Council [2014-03314]
- Swedish Childhood Cancer Foundation [PR2014-0143]
- strategic research network eSSENCE
- Swedish Cancer Society [CAN 2014/579]
- Swedish Research Council [2014-03314] Funding Source: Swedish Research Council
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. (C) 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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