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

A Landscape of Metabolic Variation across Tumor Types.

Author information

1
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. Electronic address: reznike@mskcc.org.
2
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.
3
Genetics and Genomics Department, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
4
Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA; Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA.
5
Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Laboratory of Metabolic Regulation and Genetics, The Rockefeller University, New York, NY 10065, USA; Tri-Institutional Training Program in Computational Biology & Medicine, New York, NY 10065, USA.
6
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
7
Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.
8
Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
9
cBio Center, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Electronic address: sander.research@gmail.com.

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).

KEYWORDS:

cancer metabolism; clinical data; genomics; meta-analysis; metabolomics; tumor

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