Abstract
Glioblastoma multiforme (GBM: grade IV astrocytoma) is the most common but lethal form of brain cancer. The median survival time of GBM patients is only 15 months. Only a few predictive markers have been reported for prognosis and treatment.
This study integrates gene expression and protein-protein interaction data to search for pathways that are differentially regulated between long-term and short-term survivors of GBM patients. A novel objective function for greedy search was introduced in search for 47 significantly and differentially expressed sub-networks (SDES) or pathways in a greedy fashion. The resultant putative pathways (involving 156 genes) were tested for enrichment of known GBM cancer genes as well as GO terms related to “biological process.” Integration of gene expression profiles of GBM patients with a PPI network improves the recall rate of known GBM driver genes and shows the better GO enrichment in comparison to the conventional gene-set approach that is based solely on the expression data.
Keywords: Brain, cancer, GBM, gene, integration, pathway, PPI, protein, sub-network.
Current Bioinformatics
Title:Mining of Network Markers for Brain Tumor from Transcriptome and Interactome Data
Volume: 8 Issue: 3
Author(s): Jongkwang Kim
Affiliation:
Keywords: Brain, cancer, GBM, gene, integration, pathway, PPI, protein, sub-network.
Abstract: Glioblastoma multiforme (GBM: grade IV astrocytoma) is the most common but lethal form of brain cancer. The median survival time of GBM patients is only 15 months. Only a few predictive markers have been reported for prognosis and treatment.
This study integrates gene expression and protein-protein interaction data to search for pathways that are differentially regulated between long-term and short-term survivors of GBM patients. A novel objective function for greedy search was introduced in search for 47 significantly and differentially expressed sub-networks (SDES) or pathways in a greedy fashion. The resultant putative pathways (involving 156 genes) were tested for enrichment of known GBM cancer genes as well as GO terms related to “biological process.” Integration of gene expression profiles of GBM patients with a PPI network improves the recall rate of known GBM driver genes and shows the better GO enrichment in comparison to the conventional gene-set approach that is based solely on the expression data.
Export Options
About this article
Cite this article as:
Kim Jongkwang, Mining of Network Markers for Brain Tumor from Transcriptome and Interactome Data, Current Bioinformatics 2013; 8 (3) . https://dx.doi.org/10.2174/1574893611308030005
DOI https://dx.doi.org/10.2174/1574893611308030005 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Collaborative and Defensive Fibroblasts in Tumor Progression and Therapy Resistance
Current Medicinal Chemistry Anthocyanins As Modulators of Cell Redox-Dependent Pathways in Non-Communicable Diseases
Current Medicinal Chemistry Inhibitors of the HSP90 Molecular Chaperone: Attacking the Master Regulator in Cancer
Current Topics in Medicinal Chemistry Atomic Force Microscopy and Anodic Porous Allumina of Nucleic Acid Programmable Protein Arrays
Recent Patents on Biotechnology Screening Novel SAHA Derivatives as Anti-lung Carcinoma Agents: Synthesis, Biological Evaluation, Docking Studies and Further Mechanism Research between Apoptosis and Autophagyetween Apoptosis and Autophagy
Anti-Cancer Agents in Medicinal Chemistry Nab-Paclitaxel in Metastatic Breast Cancer: Defining the Best Patient Profile
Current Cancer Drug Targets Ursolic Acid in Cancer Treatment and Metastatic Chemoprevention: From Synthesized Derivatives to Nanoformulations in Preclinical Studies
Current Cancer Drug Targets Targeting IGF-I, IGFBPs and IGF-I Receptor System in Cancer: The Current and Future in Breast Cancer Therapy
Recent Patents on Anti-Cancer Drug Discovery From Multiple PAR1 Receptor/Protein Interactions to their Multiple Therapeutic Implications
Current Topics in Medicinal Chemistry Clinical and Forensic Signs Related to Cocaine Abuse
Current Drug Abuse Reviews Peptides and their Metal Complexes in Neurodegenerative Diseases: from Structural Studies to Nanomedicine Prospects
Current Medicinal Chemistry Interleukin-6 and Lung Inflammation: Evidence for a Causative Role in Inducing Respiratory System Resistance Increments
Inflammation & Allergy - Drug Targets (Discontinued) Azathioprine in Multiple Sclerosis
Mini-Reviews in Medicinal Chemistry Nano Conjugated PLGA-Chlorambucil: Synthesis In Vitro Anti Non- Hodgkin's Lymphoma Cellular Assay
Letters in Drug Design & Discovery Clinical, Immunological and Therapeutic Aspects of Autoimmune Encephalitis
Recent Patents on CNS Drug Discovery (Discontinued) Structure-based Virtual Screening Approaches in Kinase-directed Drug Discovery
Current Topics in Medicinal Chemistry Meet Our Editorial Board Member
Recent Patents on Anti-Cancer Drug Discovery Copper Complexes of 8-Aminoquinoline and Uracils as Novel Aromatase Inhibitors
Letters in Drug Design & Discovery Combined Effect of Parthenolide and Various Anti-cancer Drugs or Anticancer Candidate Substances on Malignant Cells in vitro and in vivo
Mini-Reviews in Medicinal Chemistry Genotype- or Phenotype-Targeting Anticancer Therapies? Lessons from Tumor Evolutionary Biology
Current Pharmaceutical Design