Meta-analysis and gene set analysis of archived microarrays suggest implication of the spliceosome in metastatic and hypoxic phenotypes

PLoS One. 2014 Jan 31;9(1):e86699. doi: 10.1371/journal.pone.0086699. eCollection 2014.

Abstract

We propose to make use of the wealth of underused DNA chip data available in public repositories to study the molecular mechanisms behind the adaptation of cancer cells to hypoxic conditions leading to the metastatic phenotype. We have developed new bioinformatics tools and adapted others to identify with maximum sensitivity those genes which are expressed differentially across several experiments. The comparison of two analytical approaches, based on either Over Representation Analysis or Functional Class Scoring, by a meta-analysis-based approach, led to the retrieval of known information about the biological situation - thus validating the model - but also more importantly to the discovery of the previously unknown implication of the spliceosome, the cellular machinery responsible for mRNA splicing, in the development of metastasis.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Hypoxia*
  • Neoplasms / genetics*
  • Neoplasms / pathology
  • Oligonucleotide Array Sequence Analysis
  • Phenotype
  • Signal Transduction / genetics
  • Spliceosomes / genetics*

Grants and funding

This work was supported by the FRS-FNRS Télévie (BDM) and FRS-FRNS(SD). FB is a volunteer for the University of Namur Biology Department. EB is funded by Prof. Daniel Sinnett (Division of Hematology-Oncology, Sainte-Justine UHC Research Center, University of Montreal). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.