| URL: | http://www.sanderlab.org/pancanmet |
| Full name: | Pan-Cancer Metabolism Data Explorer |
| Description: | Pan-Cancer Metabolism Data Explorer, is 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. |
| Year founded: | 2018 |
| Last update: | |
| Version: | |
| Accessibility: |
Accessible
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| Country/Region: | United States |
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| Data object: |
NA
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| University/Institution: | Dana-Farber Cancer Institute |
| Address: | 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. |
| City: | Boston |
| Province/State: | |
| Country/Region: | United States |
| Contact name (PI/Team): | Chris Sander |
| Contact email (PI/Helpdesk): | sander.research@gmail.com |
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A Landscape of Metabolic Variation across Tumor Types. [PMID: 29396322]
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). |