Published in:
Open Access
01-12-2014 | Research
Mesenchymal cell interaction with ovarian cancer cells induces a background dependent pro-metastatic transcriptomic profile
Authors:
Raphael Lis, Cyril Touboul, Najeeb M Halabi, Abishek Sainath Madduri, Denis Querleu, Jason Mezey, Joel A Malek, Karsten Suhre, Arash Rafii
Published in:
Journal of Translational Medicine
|
Issue 1/2014
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Abstract
Background
The cross talk between the stroma and cancer cells plays a major role in phenotypic modulation. During peritoneal carcinomatosis ovarian cancer cells interact with mesenchymal stem cells (MSC) resulting in increased metastatic ability. Understanding the transcriptomic changes underlying the phenotypic modulation will allow identification of key genes to target. However in the context of personalized medicine we must consider inter and intra tumoral heterogeneity. In this study we used a pathway-based approach to illustrate the role of cell line background in transcriptomic modification during a cross talk with MSC.
Methods
We used two ovarian cancer cell lines as a surrogate for different ovarian cancer subtypes: OVCAR3 for an epithelial and SKOV3 for a mesenchymal subtype. We co-cultured them with MSCs. Genome wide gene expression was determined after cell sorting. Ingenuity pathway analysis was used to decipher the cell specific transcriptomic changes related to different pro-metastatic traits (Adherence, migration, invasion, proliferation and chemoresistance).
Results
We demonstrate that co-culture of ovarian cancer cells in direct cellular contact with MSCs induces broad transcriptomic changes related to enhance metastatic ability. Genes related to cellular adhesion, invasion, migration, proliferation and chemoresistance were enriched under these experimental conditions. Network analysis of differentially expressed genes clearly shows a cell type specific pattern.
Conclusion
The contact with the mesenchymal niche increase metastatic initiation and expansion through cancer cells’ transcriptome modification dependent of the cellular subtype. Personalized medicine strategy might benefit from network analysis revealing the subtype specific nodes to target to disrupt acquired pro-metastatic profile.