Gene expression profiling of advanced ovarian cancer: Characterization of a molecular signature involving fibroblast growth factor 2

Loris De Cecco, Luigi Marchionni, Manuela Gariboldi, James F. Reid, M. Stefania Lagonigro, Stefano Caramuta, Cristina Ferrario, Erica Bussani, Delia Mezzanzanica, Fabio Turatti, Domenico Delia, Maria G. Daidone, Maria Oggionni, Norma Bertuletti, Antonino Ditto, Francesco Raspagliesi, Silvana Pilotti, Marco A. Pierotti, Silvana Canevari, Claudio Schneider

Research output: Contribution to journalArticlepeer-review

Abstract

Epithelial ovarian cancer (EOC) is the gynecological disease with the highest death rate. We applied an automatic class discovery procedure based on gene expression profiling to stages III-IV tumors to search for molecular signatures associated with the biological properties and progression of EOC. Using a complementary DNA microarray containing 4451 cancer-related, sequence-verified features, we identified a subset of EOC characterized by the expression of numerous genes related to the extracellular matrix (ECM) and its remodeling, along with elements of the fibroblast growth factor 2 (FGF2) signaling pathway. A total of 10 genes were validated by quantitative real-time polymerase chain reaction, and coexpression of FGF2 and fibroblast growth factor receptor 4 in tumor cells was revealed by immunohistochemistry, confirming the reliability of gene expression by cDNA microarray. Since the functional relationships among these genes clearly suggested involvement of the identified molecular signature in processes related to epithelial-stromal interactions and/or epithelial-mesenchymal cellular plasticity, we applied supervised learning analysis on ovarian-derived cell lines showing distinct cellular phenotypes in culture. This procedure enabled construction of a gene classifier able to discriminate mesenchymal-like from epithelial-like cells. Genes overexpressed in mesenchymal-like cells proved to match the FGF2 signaling and ECM molecular signature, as identified by unsupervised class discovery on advanced tumor samples. In vitro functional analysis of the cell plasticity classifier was carried out using two isogenic and immortalized cell lines derived from ovarian surface epithelium and displaying mesenchymal and epithelial morphology, respectively. The results indicated the autocrine, but not intracrine stimulation of mesenchymal conversion and cohort/scatter migration of cells by FGF2, suggesting a central role for FGF2 signaling in the maintenance of cellular plasticity of ovary-derived cells throughout the carcinogenesis process. These findings raise mechanistic hypotheses on EOC pathogenesis and progression that might provide a rational underpinning for new therapeutic modalities.

Original languageEnglish
Pages (from-to)8171-8183
Number of pages13
JournalOncogene
Volume23
Issue number49
DOIs
Publication statusPublished - Oct 21 2004

Keywords

  • Automated class discovery
  • Epithelial-mesenchymal transition
  • Epithelial-stromal interaction
  • Gene expression profiling
  • Ovarian cancer

ASJC Scopus subject areas

  • Molecular Biology
  • Cancer Research
  • Genetics

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