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肿瘤类型间代谢变化的全景图。

A Landscape of Metabolic Variation across Tumor Types.

机构信息

Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.

cBio Center, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA.

出版信息

Cell Syst. 2018 Mar 28;6(3):301-313.e3. doi: 10.1016/j.cels.2017.12.014. Epub 2018 Jan 27.

Abstract

Tumor metabolism is reorganized to support proliferation in the face of growth-related stress. Unlike the widespread profiling of changes to metabolic enzyme levels in cancer, comparatively less attention has been paid to the substrates/products of enzyme-catalyzed reactions, small-molecule metabolites. We developed an informatic pipeline to concurrently analyze metabolomics data from over 900 tissue samples spanning seven cancer types, revealing extensive heterogeneity in metabolic changes relative to normal tissue across cancers of different tissues of origin. Despite this heterogeneity, a number of metabolites were recurrently differentially abundant across many cancers, such as lactate and acyl-carnitine species. Through joint analysis of metabolomic data alongside clinical features of patient samples, we also identified a small number of metabolites, including several polyamines and kynurenine, which were associated with aggressive tumors across several tumor types. Our findings offer a glimpse onto common patterns of metabolic reprogramming across cancers, and the work serves as a large-scale resource accessible via a web application (http://www.sanderlab.org/pancanmet).

摘要

肿瘤代谢在面对与生长相关的应激时会重新组织以支持增殖。与癌症中代谢酶水平变化的广泛分析相比,人们对酶催化反应的底物/产物,即小分子代谢物,关注较少。我们开发了一种信息学管道,可同时分析来自 7 种癌症类型的 900 多个组织样本的代谢组学数据,揭示了相对于起源组织不同的癌症的正常组织,代谢变化具有广泛的异质性。尽管存在这种异质性,但许多代谢物在许多癌症中反复出现差异丰度,例如乳酸盐和酰基辅酶 A 物种。通过对代谢组学数据与患者样本临床特征的联合分析,我们还确定了少量代谢物,包括几种多胺和犬尿氨酸,它们与多种肿瘤类型的侵袭性肿瘤有关。我们的研究结果提供了对癌症之间代谢重编程的常见模式的初步了解,这项工作是通过一个网络应用程序(http://www.sanderlab.org/pancanmet)提供的大型资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3640/5876114/794d2d757902/nihms930795f1.jpg

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