13C metabolic flux analysis clarifies distinct metabolic phenotypes of cancer cell spheroid mimicking tumor hypoxia |
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| Affiliation: | 1. Translational Science Department I, Daiichi Sankyo Co., Ltd., 1-2-58, Hiromachi, Shinagawa-ku, Tokyo, 140-8710, Japan;2. Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5, Yamadaoka, Suita, Osaka, 565-0871, Japan;1. College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China;2. MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, 100084, China;3. Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China;4. MOE Key Laboratory for Industrial Biocatalysis, Dept Chemical Engineering, Tsinghua University, Beijing, 100084, China;5. Shandong Provincial Research Center for Bioinformatic Engineering and Technology, School of Life Sciences, Shandong University of Technology, Zibo, 255049, China;1. Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, TN, USA;2. Center of Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, USA;3. Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA;4. Department of Biological Engineering, Konkuk University, Seoul, South Korea;1. Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan;2. Engineering Biology Research Center, Kobe University, 1-1 Rokkodai, Nada, Kobe, Hyogo 657-8501, Japan;3. Graduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai, Nada, Kobe, Hyogo 657-8501, Japan;4. Department of Environmental and Life Sciences, School of Food and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga, Shizuoka 422-8526, Japan;5. Graduate Division of Nutritional and Environmental Sciences, University of Shizuoka, 52-1 Yada, Suruga, Shizuoka 422-8526, Japan;1. Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China;2. National Technology Innovation Center of Synthetic Biology, Tianjin, 300308, China;3. Beijing Advanced Innovation Center for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China;4. Department of Biology and Biological Engineering, Chalmers University of Technology, SE 412 96, Gothenburg, Sweden;1. Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Yamadaoka, Suita, Osaka, 565-0871, Japan;2. Department of Environmental and Life Sciences, School of Food and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan;3. Engineering Biology Research Center, Kobe University, 1-1 Rokkodai, Nada, Kobe, Hyogo, 657-8501, Japan;4. Department of Life Science and Applied Chemistry, Nagoya Institute of Technology, Showa-ku, Nagoya, Aichi, 466-8555, Japan;5. OptoBioTechnology Research Center, Nagoya Institute of Technology, Showa-ku, Nagoya, Aichi, 466-8555, Japan;6. Graduate Division of Nutritional and Environmental Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526, Japan;7. Graduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai, Nada, Kobe, Hyogo, 657-8501, Japan |
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| Abstract: | Cancer cells adapt their intracellular energy metabolism to the oxygen-deprived tumor microenvironment (TME) to ensure tumor progression. This adaptive mechanism has focused attention on the metabolic phenotypes of tumor cells under hypoxic TME for developing novel cancer therapies. Although widely used monolayer (2D) culture does not fully reflect in vivo hypoxic TME, spheroid (3D) culture can produce a milieu similar to the TME in vivo. However, how different metabolic phenotypes are expressed in 3D cultures mimicking tumor hypoxia compared with 2D cultures under hypoxia remains unclear. To address this issue, we investigated the metabolic phenotypes of 2D- and 3D-cultured cancer cells by 13C-metabolic flux analysis (13C-MFA). Principal component analysis of 13C mass isotopomer distributions clearly demonstrated distinct metabolic phenotypes of 3D-cultured cells. 13C-MFA clarified that 3D culture significantly upregulated pyruvate carboxylase flux in line with the pyruvate carboxylase protein expression level. On the other hand, 3D culture downregulated glutaminolytic flux. Consistent with our findings, 3D-cultured cells are more resistant to a glutaminase inhibitor than 2D-cultured cells. This study suggests the importance of considering the metabolic characteristics of the particular in vitro model used for research on cancer metabolism. |
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| Keywords: | Cancer metabolism 3D culture Spheroid Hypoxic tumor microenvironment |
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