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Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling
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2015 (English)In: Scientific Reports, ISSN 2045-2322, Vol. 5, 8183- p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2015. Vol. 5, 8183- p.
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Other Biological Topics
URN: urn:nbn:se:kth:diva-160366DOI: 10.1038/srep08183ISI: 000348671000003OAI: diva2:791253
Knut and Alice Wallenberg Foundation

QC 20150227

Available from: 2015-02-27 Created: 2015-02-19 Last updated: 2015-02-27Bibliographically approved

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Uhlén, MathiasNielsen, Jens
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Proteomics and NanobiotechnologyScience for Life Laboratory, SciLifeLab
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