Title
Systems biology approach to identification of biomarkers for metastatic progression in cancer.
Abstract
Metastases are responsible for the majority of cancer fatalities. The molecular mechanisms governing metastasis are poorly understood, hindering early diagnosis and treatment. Previous studies of gene expression patterns in metastasis have concentrated on selection of a small number of "signature" biomarkers.We propose an alternative approach that puts into focus gene interaction networks and molecular pathways rather than separate genes. We have reanalyzed expression data from a large set of primary solid and metastatic tumors originating from different tissues using the latest available tools for normalization, identification of differentially expressed genes and pathway analysis. Our studies indicate that regardless of the tissue of origin, all metastatic tumors share a number of common features related to changes in basic energy metabolism, cell adhesion/cytoskeleton remodeling, antigen presentation and cell cycle regulation. Analysis of multiple independent datasets indicates significantly reduced oxidative phosphorylation in metastases compared to primary solid tumors.Our methods allow identification of robust, although not necessarily highly expressed biomarkers. A systems approach relying on groups of interacting genes rather than single markers is also essential for understanding the cellular processes leading to metastatic progression. We have identified metabolic pathways associated with metastasis that may serve as novel targets for therapeutic intervention.
Year
DOI
Venue
2008
10.1186/1471-2105-9-S9-S8
BMC Bioinformatics
Keywords
Field
DocType
signal transduction,microarrays,antigen presentation,cell adhesion,algorithms,metabolic pathway,cell cycle regulation,systems biology,computer simulation,interaction network,gene expression profiling,oxidative phosphorylation,system biology,molecular mechanics,bioinformatics
Metastasis,Oxidative Phosphorylation Pathway,Biology,Systems biology,Disease progression,Biomarker (medicine),Bioinformatics,Gene expression profiling,Cancer,DNA microarray
Journal
Volume
Issue
ISSN
9 Suppl 9
S-9
1471-2105
Citations 
PageRank 
References 
34
1.16
3
Authors
3
Name
Order
Citations
PageRank
Andrey A Ptitsyn11619.32
Michael M Weil2341.16
Douglas H Thamm3341.50