Cell-programmed nutrient partitioning in the tumour microenvironment.
Cell-programmed nutrient partitioning in the tumour microenvironment.
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DOI:
10.1038/s41586-021-03442-1
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发表时间:
2021-05
期刊:
影响因子:
64.8
通讯作者:
Rathmell WK
中科院分区:
文献类型:
--
作者:
Reinfeld BI;Madden MZ;Wolf MM;Chytil A;Bader JE;Patterson AR;Sugiura A;Cohen AS;Ali A;Do BT;Muir A;Lewis CA;Hongo RA;Young KL;Brown RE;Todd VM;Huffstater T;Abraham A;O'Neil RT;Wilson MH;Xin F;Tantawy MN;Merryman WD;Johnson RW;Williams CS;Mason EF;Mason FM;Beckermann KE;Vander Heiden MG;Manning HC;Rathmell JC;Rathmell WK
Cancer cells characteristically consume glucose through Warburg metabolism, a process forming the basis of tumor imaging by positron emission tomography (PET). Tumor infiltrating immune cells also rely on glucose, and impaired immune cell metabolism in the tumor microenvironment (TME) contributes to tumor immunological evasion. It remains uncertain, however, if immune cell metabolism is dysregulated in the TME by cell intrinsic programs or by competition with cancer cells for limiting nutrients. Here we used PET tracers to measure access and uptake of glucose and glutamine by specific cell subsets in the TME. Surprisingly, myeloid cells had the greatest capacity to uptake intra-tumoral glucose, followed by T cells and cancer cells across a range of cancer models. Cancer cells, in contrast, demonstrated the highest glutamine uptake. This distinct nutrient partitioning was cell intrinsically programmed through mTORC1 signaling and glucose and glutamine-related gene expression. Inhibiting glutamine uptake enhanced glucose uptake across tumor resident cell types, demonstrating that glutamine metabolism suppresses glucose uptake without glucose being limiting in the TME. Thus, cell intrinsic programs drive the preferential immune and cancer cell acquisition of glucose and glutamine, respectively. Cell selective partitioning of these nutrients may be exploited to develop therapies and imaging strategies to enhance or monitor the metabolic programs and activities of specific cell populations in the TME.
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影响因子:
29
作者:
Cascone T;McKenzie JA;Mbofung RM;Punt S;Wang Z;Xu C;Williams LJ;Wang Z;Bristow CA;Carugo A;Peoples MD;Li L;Karpinets T;Huang L;Malu S;Creasy C;Leahey SE;Chen J;Chen Y;Pelicano H;Bernatchez C;Gopal YNV;Heffernan TP;Hu J;Wang J;Amaria RN;Garraway LA;Huang P;Yang P;Wistuba II;Woodman SE;Roszik J;Davis RE;Davies MA;Heymach JV;Hwu P;Peng W
通讯作者:
Peng W
影响因子:
11.2
作者:
Hesketh, Richard L.;Wang, Jiazheng;Brindle, Kevin M.
通讯作者:
Brindle, Kevin M.
影响因子:
64.5
作者:
Ho PC;Bihuniak JD;Macintyre AN;Staron M;Liu X;Amezquita R;Tsui YC;Cui G;Micevic G;Perales JC;Kleinstein SH;Abel ED;Insogna KL;Feske S;Locasale JW;Bosenberg MW;Rathmell JC;Kaech SM
通讯作者:
Kaech SM
影响因子:
10.1
作者:
Cortese, Nina;Capretti, Giovanni;Marchesi, Federica
通讯作者:
Marchesi, Federica
影响因子:
11.2
作者:
Jeong, Hoibin;Kim, Sehui;Ahn, G-One
通讯作者:
Ahn, G-One