Automated network analysis identifies core pathways in glioblastoma.

Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
PLoS ONE (Impact Factor: 3.53). 02/2010; 5(2):e8918. DOI: 10.1371/journal.pone.0008918
Source: PubMed

ABSTRACT Glioblastoma multiforme (GBM) is the most common and aggressive type of brain tumor in humans and the first cancer with comprehensive genomic profiles mapped by The Cancer Genome Atlas (TCGA) project. A central challenge in large-scale genome projects, such as the TCGA GBM project, is the ability to distinguish cancer-causing "driver" mutations from passively selected "passenger" mutations.
In contrast to a purely frequency based approach to identifying driver mutations in cancer, we propose an automated network-based approach for identifying candidate oncogenic processes and driver genes. The approach is based on the hypothesis that cellular networks contain functional modules, and that tumors target specific modules critical to their growth. Key elements in the approach include combined analysis of sequence mutations and DNA copy number alterations; use of a unified molecular interaction network consisting of both protein-protein interactions and signaling pathways; and identification and statistical assessment of network modules, i.e. cohesive groups of genes of interest with a higher density of interactions within groups than between groups.
We confirm and extend the observation that GBM alterations tend to occur within specific functional modules, in spite of considerable patient-to-patient variation, and that two of the largest modules involve signaling via p53, Rb, PI3K and receptor protein kinases. We also identify new candidate drivers in GBM, including AGAP2/CENTG1, a putative oncogene and an activator of the PI3K pathway; and, three additional significantly altered modules, including one involved in microtubule organization. To facilitate the application of our network-based approach to additional cancer types, we make the method freely available as part of a software tool called NetBox.

1 Follower
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Gene regulatory networks represent the regulatory relationships between genes and their products and are important for exploring and defining the underlying biological processes of cellular systems. We develop a novel framework to recover the structure of nonlinear gene regulatory networks using semiparametric spline-based directed acyclic graphical models. Our use of splines allows the model to have both flexibility in capturing nonlinear dependencies as well as control of overfitting via shrinkage, using mixed model representations of penalized splines. We propose a novel discrete mixture prior on the smoothing parameter of the splines that allows for simultaneous selection of both linear and nonlinear functional relationships as well as inducing sparsity in the edge selection. Using simulation studies, we demonstrate the superior performance of our methods in comparison with several existing approaches in terms of network reconstruction and functional selection. We apply our methods to a gene expression dataset in glioblastoma multiforme, which reveals several interesting and biologically relevant nonlinear relationships. © 2015, The International Biometric Society.
    Biometrics 04/2015; DOI:10.1111/biom.12309 · 1.52 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this study, we determined the expression of key signalling pathway proteins TP53, MDM2, P21, AKT, PTEN, RB1, P16, MTOR and MAPK in canine gliomas using western blotting. Protein expression was defined in three canine astrocytic glioma cell lines treated with CCNU, temozolamide or CPT-11 and was further evaluated in 22 spontaneous gliomas including high and low grade astrocytomas, high grade oligodendrogliomas and mixed oligoastrocytomas. Response to chemotherapeutic agents and cell survival were similar to that reported in human glioma cell lines. Alterations in expression of key human gliomagenesis pathway proteins were common in canine glioma tumour samples and segregated between oligodendroglial and astrocytic tumour types for some pathways. Both similarities and differences in protein expression were defined for canine gliomas compared to those reported in human tumour counterparts. The findings may inform more defined assessment of specific signalling pathways for targeted therapy of canine gliomas. © 2015 John Wiley & Sons Ltd.
    Veterinary and Comparative Oncology 03/2015; DOI:10.1111/vco.12147 · 1.45 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Stromal fibroblasts play an important role in chronic cancer-related inflammation and the development as well as progression of malignant diseases. However, the difference and relationship between inflammation-associated fibroblasts (IAFs) and cancer-associated fibroblasts (CAFs) are poorly understood. In this study, gastric cancer-associated fibroblasts (GCAFs) and their corresponding inflammation-associated fibroblasts (GIAFs) were isolated from gastric cancer (GC) with chronic gastritis and cultured in vitro. These activated fibroblasts exhibited distinct secretion and tumor-promoting behaviors in vitro. Using proteomics and bioinformatics techniques, caveolin-1 (Cav-1) was identified as a major network-centric protein of a sub-network consisting of 121 differentially expressed proteins between GIAFs and GCAFs. Furthermore, immunohistochemistry in a GC cohort showed significant difference in Cav-1 expression score between GIAFs and GCAFs and among patients with different grades of chronic gastritis. Moreover, silencing of Cav-1 in GIAFs and GCAFs using small interfering RNA increased the production of pro-inflammatory and tumor-enhancing cytokines and chemokines in conditioned mediums that elevated cell proliferation and migration when added to GC cell lines AGS and MKN45 in vitro. In addition, Cav-1 status in GIAFs and GCAFs independently predicted the prognosis of GC. Our findings indicate that Cav-1 loss contributes to the distinct activation statuses of fibroblasts in GC microenvironment and gastritis mucosa, and Cav-1 expression in both GCAFs and GIAFs may serve as a potential biomarker for GC progression.
    International journal of biological sciences 01/2015; 11(4):370-379. DOI:10.7150/ijbs.10666 · 4.37 Impact Factor

Full-text (2 Sources)

Available from
May 29, 2014