Biosynthetic energy cost for amino acids decreases in cancer evolution

Hong Zhang, Yirong Wang, Jun Li, Han Chen, Xionglei He, Huiwen Zhang, Han Liang () and Jian Lu ()
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Hong Zhang: Peking University
Yirong Wang: Peking University
Jun Li: The University of Texas MD Anderson Cancer Center
Han Chen: The University of Texas MD Anderson Cancer Center
Xionglei He: Sun Yat-sen University
Huiwen Zhang: The University of Texas Health Science Center at Houston
Han Liang: The University of Texas MD Anderson Cancer Center
Jian Lu: Peking University

Nature Communications, 2018, vol. 9, issue 1, 1-15

Abstract: Abstract Rapidly proliferating cancer cells have much higher demand for proteinogenic amino acids than normal cells. The use of amino acids in human proteomes is largely affected by their bioavailability, which is constrained by the biosynthetic energy cost in living organisms. Conceptually distinct from gene-based analyses, we introduce the energy cost per amino acid (ECPA) to quantitatively characterize the use of 20 amino acids during protein synthesis in human cells. By analyzing gene expression data from The Cancer Genome Atlas, we find that cancer cells evolve to utilize amino acids more economically by optimizing gene expression profile and ECPA shows robust prognostic power across many cancer types. We further validate this pattern in an experimental evolution of xenograft tumors. Our ECPA analysis reveals a common principle during cancer evolution.

Date: 2018
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DOI: 10.1038/s41467-018-06461-1

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