Journal
NATURE COMMUNICATIONS
Volume 9, Issue -, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41467-018-06461-1
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Funding
- National Natural Science Foundation of China [91731301, 91731302]
- U.S. National Institutes of Health [CA175486, CA209851]
- CCSG grant [CA016672]
- Cancer Prevention and Research Institute of Texas [RP140462]
- University of Texas System STARS award
- Lorraine Dell Program in Bioinformatics for Personalization of Cancer Medicine
- Peking-Tsinghua Center for Life Sciences
- Chinese Initiative Postdocs Supporting Program
- NATIONAL CANCER INSTITUTE [P30CA016672, U24CA209851, R01CA175486] Funding Source: NIH RePORTER
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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.
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