Network signatures of survival in glioblastoma multiforme.
To determine a molecular basis for prognostic differences in glioblastoma multiforme (GBM), we employed a combinatorial network analysis framework to exhaustively search for molecular patterns in protein-protein interaction (PPI) networks. We identified a dysregulated molecular signature distinguishing short-term (survival<225 days) from long-term (survival>635 days) survivors of GBM using whole genome expression data from The Cancer Genome Atlas (TCGA). A 50-gene subnetwork signature achieved 80% prediction accuracy when tested against an independent gene expression dataset. Functional annotations for the subnetwork signature included "protein kinase cascade," "IκB kinase/NFκB cascade," and "regulation of programmed cell death" - all of which were not significant in signatures of existing subtypes. Finally, we used label-free proteomics to examine how our subnetwork signature predicted protein level expression differences in an independent GBM cohort of 16 patients. We found that the genes discovered using network biology had a higher probability of dysregulated protein expression than either genes exhibiting individual differential expression or genes derived from known GBM subtypes. In particular, the long-term survivor subtype was characterized by increased protein expression of DNM1 and MAPK1 and decreased expression of HSPA9, PSMD3, and CANX. Overall, we demonstrate that the combinatorial analysis of gene expression data constrained by PPIs outlines an approach for the discovery of robust and translatable molecular signatures in GBM.
Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio, United States of America.
Vishal N
VN
Patel
Giridharan
G
Gokulrangan
Salim A
SA
Chowdhury
Yanwen
Y
Chen
Andrew E
AE
Sloan
Mehmet
M
Koyutürk
Jill
J
Barnholtz-Sloan
Mark R
MR
Chance
D001932:Brain Neoplasms / Q000201:enzymology / Q000235:genetics* / Q000473:pathology; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D005909:Glioblastoma / Q000201:enzymology / Q000235:genetics* / Q000473:pathology; D006801:Humans; D011494:Protein Kinases / Q000235:genetics / Q000378:metabolism; D040901:Proteomics; D017741:Survivors
D011494:Protein Kinases