Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.
Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.
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DOI:
10.1038/s41467-023-38403-x
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发表时间:
2023-05-19
影响因子:
16.6
通讯作者:
Patti, Gary J.
中科院分区:
文献类型:
--
作者:
Schwaiger-Haber, Michaela;Stancliffe, Ethan;Anbukumar, Dhanalakshmi S.;Sells, Blake;Yi, Jia;Cho, Kevin;Adkins-Travis, Kayla;Chheda, Milan G.;Shriver, Leah P.;Patti, Gary J.
Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma. Isotopologue spectral analysis was originally designed to assess metabolic fluxes from bulk samples. Here, the authors adapted this approach to infer fluxes from discrete regions in tissue by using mass spectrometry imaging, showing increased fatty acid synthesis flux in brain tumors of mice.
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影响因子:
5.7
作者:
Kuemmerle NB;Rysman E;Lombardo PS;Flanagan AJ;Lipe BC;Wells WA;Pettus JR;Froehlich HM;Memoli VA;Morganelli PM;Swinnen JV;Timmerman LA;Chaychi L;Fricano CJ;Eisenberg BL;Coleman WB;Kinlaw WB
通讯作者:
Kinlaw WB
影响因子:
8.8
作者:
Gelman SJ;Naser F;Mahieu NG;McKenzie LD;Dunn GP;Chheda MG;Patti GJ
通讯作者:
Patti GJ
影响因子:
1.1
作者:
Davis ME
通讯作者:
Davis ME
影响因子:
4.3
作者:
通讯作者:
--
影响因子:
4.7
作者:
He, Michelle Junyi;Pu, Wenjun;Wang, Xi;Zhang, Wei;Tang, Donge;Dai, Yong
通讯作者:
Dai, Yong