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Cancer Metab. 2013 Nov 7;1(1):20. doi: 10.1186/2049-3002-1-20.

The metabolic demands of cancer cells are coupled to their size and protein synthesis rates.

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Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA.



Although cells require nutrients to proliferate, most nutrient exchange rates of the NCI60 panel of cancer cell lines correlate poorly with their proliferation rate. Here, we provide evidence indicating that this inconsistency is rooted in the variability of cell size.


We integrate previously reported data characterizing genome copy number variations, gene expression, protein expression and exchange fluxes with our own measurements of cell size and protein content in the NCI60 panel of cell lines. We show that protein content, DNA content, and protein synthesis per cell are proportional to the cell volume, and that larger cells proliferate slower than smaller cells. We estimate the metabolic fluxes of these cell lines and show that their magnitudes are proportional to their protein synthesis rate and, after correcting for cell volume, to their proliferation rate. At the level of gene expression, we observe that genes expressed at higher levels in smaller cells are enriched for genes involved in cell cycle, while genes expressed at higher levels in large cells are enriched for genes expressed in mesenchymal cells. The latter finding is further corroborated by the induction of those same genes following treatment with TGFβ, and the high vimentin but low E-cadherin protein levels in the larger cells. We also find that aromatase inhibitors, statins and mTOR inhibitors preferentially inhibit the in vitro growth of cancer cells with high protein synthesis rates per cell.


The NCI60 cell lines display various metabolic activities, and the type of metabolic activity that they possess correlates with their cell volume and protein content. In addition to cell proliferation, cell volume and/or biomarkers of protein synthesis may predict response to drugs targeting cancer metabolism.

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