Cell Systems
Volume 3, Issue 2, 24 August 2016, Pages 172-186
Journal home page for Cell Systems

Article
Causal Mechanistic Regulatory Network for Glioblastoma Deciphered Using Systems Genetics Network Analysis

https://doi.org/10.1016/j.cels.2016.06.006Get rights and content
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Highlights

  • A TF-target gene database for 690 human TFs (http://tfbsdb.systemsbiology.net)

  • SYGNAL pipeline integrates multi-omic data into a mechanistic regulatory network

  • gbmSYGNAL network: TF and miRNA regulating hallmarks of cancer in GBM

  • Mutated NF1 and PIK3CA modulate IRF1 to increase tumor lymphocyte infiltration in GBM

Summary

We developed the transcription factor (TF)-target gene database and the Systems Genetics Network Analysis (SYGNAL) pipeline to decipher transcriptional regulatory networks from multi-omic and clinical patient data, and we applied these tools to 422 patients with glioblastoma multiforme (GBM). The resulting gbmSYGNAL network predicted 112 somatically mutated genes or pathways that act through 74 TFs and 37 microRNAs (miRNAs) (67 not previously associated with GBM) to dysregulate 237 distinct co-regulated gene modules associated with patient survival or oncogenic processes. The regulatory predictions were associated to cancer phenotypes using CRISPR-Cas9 and small RNA perturbation studies and also demonstrated GBM specificity. Two pairwise combinations (ETV6-NFKB1 and romidepsin-miR-486-3p) predicted by the gbmSYGNAL network had synergistic anti-proliferative effects. Finally, the network revealed that mutations in NF1 and PIK3CA modulate IRF1-mediated regulation of MHC class I antigen processing and presentation genes to increase tumor lymphocyte infiltration and worsen prognosis. Importantly, SYGNAL is widely applicable for integrating genomic and transcriptomic measurements from other human cohorts.

Keywords

glioblastoma multiforme
glioma
gene regulation
systems biology
systems genetics
network

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