Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME

Giacomo Finocchiaro, Francesco Mattia Mancuso, Davide Cittaro, Heiko Muller

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Gene expression technology has become a routine application in many laboratories and has provided large amounts of gene expression signatures that have been identified in a variety of cancer types. Interpretation of gene expression signatures would profit from the availability of a procedure capable of assigning differentially regulated genes or entire gene signatures to defined cancer signaling pathways. Here we describe a graph-based approach that identifies cancer signaling pathways from published gene expression signatures. Published gene expression signatures are collected in a database (PubLiME: Published Lists of Microarray Experiments) enabled for cross-platform gene annotation. Significant co-occurrence modules composed of up to 10 genes in different gene expression signatures are identified. Significantly co-occurring genes are linked by an edge in an undirected graph. Edge-betweenness and k-clique clustering combined with graph modularity as a quality measure are used to identify communities in the resulting graph. The identified communities consist of cell cycle, apoptosis, phosphorylation cascade, extra cellular matrix, interferon and immune response regulators as well as communities of unknown function. The genes constituting different communities are characterized by common genomic features and strongly enriched cis-regulatory modules in their upstream regulatory regions that are consistent with pathway assignment of those genes.

Original languageEnglish
Pages (from-to)2343-2355
Number of pages13
JournalNucleic Acids Research
Volume35
Issue number7
DOIs
Publication statusPublished - Apr 2007

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Transcriptome
Genes
Neoplasms
Molecular Sequence Annotation
Nucleic Acid Regulatory Sequences
Interferon-gamma
Cluster Analysis
Cell Cycle
Phosphorylation
Databases
Apoptosis
Technology
Gene Expression

ASJC Scopus subject areas

  • Genetics

Cite this

Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME. / Finocchiaro, Giacomo; Mancuso, Francesco Mattia; Cittaro, Davide; Muller, Heiko.

In: Nucleic Acids Research, Vol. 35, No. 7, 04.2007, p. 2343-2355.

Research output: Contribution to journalArticle

Finocchiaro, Giacomo ; Mancuso, Francesco Mattia ; Cittaro, Davide ; Muller, Heiko. / Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME. In: Nucleic Acids Research. 2007 ; Vol. 35, No. 7. pp. 2343-2355.
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