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Sci Rep. 2015 Feb 2;5:8183. doi: 10.1038/srep08183.

Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling.

Author information

1
Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden.
2
Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden.
3
1] Science for Life Laboratory, KTH - Royal Institute of Technology, SE-171 21, Stockholm, Sweden [2] Department of Proteomics, KTH - Royal Institute of Technology, SE-106 91, Stockholm, Sweden.
4
1] Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden [2] Science for Life Laboratory, KTH - Royal Institute of Technology, SE-171 21, Stockholm, Sweden.

Abstract

Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted 85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies.

PMID:
25640694
PMCID:
PMC4313100
DOI:
10.1038/srep08183
[Indexed for MEDLINE]
Free PMC Article

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