1
|
Guex N, Crespo I, Bron S, Ifticene-Treboux A, Faes-van’t Hull E, Kharoubi S, Liechti R, Werffeli P, Ibberson M, Majo F, Nicolas M, Laurent J, Garg A, Zaman K, Lehr HA, Stevenson BJ, Rüegg C, Coukos G, Delaloye JF, Xenarios I, Doucey MA. Angiogenic activity of breast cancer patients' monocytes reverted by combined use of systems modeling and experimental approaches. PLoS Comput Biol 2015; 11:e1004050. [PMID: 25768678 PMCID: PMC4359163 DOI: 10.1371/journal.pcbi.1004050] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2014] [Accepted: 11/18/2014] [Indexed: 01/04/2023] Open
Abstract
Angiogenesis plays a key role in tumor growth and cancer progression. TIE-2-expressing monocytes (TEM) have been reported to critically account for tumor vascularization and growth in mouse tumor experimental models, but the molecular basis of their pro-angiogenic activity are largely unknown. Moreover, differences in the pro-angiogenic activity between blood circulating and tumor infiltrated TEM in human patients has not been established to date, hindering the identification of specific targets for therapeutic intervention. In this work, we investigated these differences and the phenotypic reversal of breast tumor pro-angiogenic TEM to a weak pro-angiogenic phenotype by combining Boolean modelling and experimental approaches. Firstly, we show that in breast cancer patients the pro-angiogenic activity of TEM increased drastically from blood to tumor, suggesting that the tumor microenvironment shapes the highly pro-angiogenic phenotype of TEM. Secondly, we predicted in silico all minimal perturbations transitioning the highly pro-angiogenic phenotype of tumor TEM to the weak pro-angiogenic phenotype of blood TEM and vice versa. In silico predicted perturbations were validated experimentally using patient TEM. In addition, gene expression profiling of TEM transitioned to a weak pro-angiogenic phenotype confirmed that TEM are plastic cells and can be reverted to immunological potent monocytes. Finally, the relapse-free survival analysis showed a statistically significant difference between patients with tumors with high and low expression values for genes encoding transitioning proteins detected in silico and validated on patient TEM. In conclusion, the inferred TEM regulatory network accurately captured experimental TEM behavior and highlighted crosstalk between specific angiogenic and inflammatory signaling pathways of outstanding importance to control their pro-angiogenic activity. Results showed the successful in vitro reversion of such an activity by perturbation of in silico predicted target genes in tumor derived TEM, and indicated that targeting tumor TEM plasticity may constitute a novel valid therapeutic strategy in breast cancer.
Collapse
Affiliation(s)
- Nicolas Guex
- The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland
| | - Isaac Crespo
- The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland
| | - Sylvian Bron
- Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland
| | - Assia Ifticene-Treboux
- Centre du Sein, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland
- Department of Gynecology and Obstetrics, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland
| | | | - Solange Kharoubi
- Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland
| | - Robin Liechti
- The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland
| | - Patricia Werffeli
- Department of Oncology, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland
| | - Mark Ibberson
- The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland
| | - Francois Majo
- Hopital Ophtalmique Jules-Gonin, Lausanne, Switzerland
| | | | | | - Abhishek Garg
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Khalil Zaman
- Centre du Sein, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland
| | - Hans-Anton Lehr
- Institute of Pathology, University of Lausanne, Switzerland and Institute of Pathology, Johannes Gutenberg University, Mainz, Germany
| | - Brian J. Stevenson
- The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland
| | - Curzio Rüegg
- Department of Medicine, University of Fribourg, Fribourg, Switzerland
| | - George Coukos
- Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland
| | - Jean-François Delaloye
- Centre du Sein, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland
- Department of Gynecology and Obstetrics, CHUV (Centre Hospitalier Universitaire Vaudois), University of Lausanne, Lausanne, Switzerland
| | - Ioannis Xenarios
- The Vital-IT, SIB (Swiss Institute of Bioinformatics), University of Lausanne, Lausanne, Switzerland
| | - Marie-Agnès Doucey
- Ludwig Center for Cancer Research, University of Lausanne, Lausanne, Switzerland
| |
Collapse
|
2
|
Schlatter R, Philippi N, Wangorsch G, Pick R, Sawodny O, Borner C, Timmer J, Ederer M, Dandekar T. Integration of Boolean models exemplified on hepatocyte signal transduction. Brief Bioinform 2011; 13:365-76. [PMID: 22016404 DOI: 10.1093/bib/bbr065] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The number of mathematical models for biological pathways is rapidly growing. In particular, Boolean modelling proved to be suited to describe large cellular signalling networks. Systems biology is at the threshold to holistic understanding of comprehensive networks. In order to reach this goal, connection and integration of existing models of parts of cellular networks into more comprehensive network models is necessary. We discuss model combination approaches for Boolean models. Boolean modelling is qualitative rather than quantitative and does not require detailed kinetic information. We show that these models are useful precursors for large-scale quantitative models and that they are comparatively easy to combine. We propose modelling standards for Boolean models as a prerequisite for smooth model integration. Using these standards, we demonstrate the coupling of two logical models on two different examples concerning cellular interactions in the liver. In the first example, we show the integration of two Boolean models of two cell types in order to describe their interaction. In the second example, we demonstrate the combination of two models describing different parts of the network of a single cell type. Combination of partial models into comprehensive network models will take systems biology to the next level of understanding. The combination of logical models facilitated by modelling standards is a valuable example for the next step towards this goal.
Collapse
Affiliation(s)
- Rebekka Schlatter
- Institute for System Dynamics, University of Stuttgart, Stuttgart, Germany
| | | | | | | | | | | | | | | | | |
Collapse
|