A Landscape of Metabolic Variation across Tumor Types.
A Landscape of Metabolic Variation across Tumor Types.
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DOI：
10.1016/j.cels.2017.12.014
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发表时间：
2018-03-28
期刊：
影响因子：
9.3
通讯作者：
Sander C
中科院分区：
文献类型：
--
作者：
Reznik E;Luna A;Aksoy BA;Liu EM;La K;Ostrovnaya I;Creighton CJ;Hakimi AA;Sander C
面对生长相关的压力，肿瘤代谢被重组以支持增殖。与癌症中代谢酶水平变化的广泛分析不同，相对较少关注酶催化反应的底物/产物，即小分子代谢物。我们开发了一个信息管道，以同时分析来自7种癌症类型的900多个组织样本的代谢组学数据，揭示了不同起源组织的癌症相对于正常组织的代谢变化的广泛异质性。尽管存在这种异质性，但许多代谢物在许多癌症中重复性差异丰富，如乳酸盐和酰基肉毒碱物质。通过对代谢组学数据以及患者样本的临床特征进行联合分析，我们还确定了少量代谢物，包括几种多胺和犬尿氨酸，这些代谢物与几种肿瘤类型的侵袭性肿瘤相关。我们的研究结果提供了对癌症代谢重编程常见模式的一瞥，这项工作作为一个大规模的资源，可通过网络应用程序（http：//www.sanderlab.org/pancanmet）访问。Reznik等人开发了一种用于代谢组学数据综合分析的计算方法，并将其应用于来自7种不同癌症类型的900个组织样本的数据。他们确定了与肿瘤发生和进展为侵袭性疾病相关的复发性代谢变化。
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 7 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). Reznik et al. develop a computational approach for integrative analysis of metabolomics data and apply it to data from 900 tissue samples spanning 7 different cancer types. They identify recurrent metabolic changes associated with tumor initiation and progression to aggressive disease.
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影响因子：
46.9
作者：
通讯作者：
--
各种各样的癌症相关MTOR突变是过度激活的，可以预测雷帕霉素的敏感性。
影响因子：
28.2
作者：
Grabiner BC;Nardi V;Birsoy K;Possemato R;Shen K;Sinha S;Jordan A;Beck AH;Sabatini DM
通讯作者：
Sabatini DM
影响因子：
12.3
作者：
Haider S;McIntyre A;van Stiphout RG;Winchester LM;Wigfield S;Harris AL;Buffa FM
通讯作者：
Buffa FM
影响因子：
14.9
作者：
Kim S;Thiessen PA;Bolton EE;Chen J;Fu G;Gindulyte A;Han L;He J;He S;Shoemaker BA;Wang J;Yu B;Zhang J;Bryant SH
通讯作者：
Bryant SH
影响因子：
11.2
作者：
Kamphorst JJ;Nofal M;Commisso C;Hackett SR;Lu W;Grabocka E;Vander Heiden MG;Miller G;Drebin JA;Bar-Sagi D;Thompson CB;Rabinowitz JD
通讯作者：
Rabinowitz JD